Science topics: Computer Science
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Hi, I've just started my PhD in Computer Science. My area of interest is Emotion AI (Affective Computing), which aims to understand emotions in Image, Video, Speech, Body-language and Brain-wave data. I've been trying to explore all of these data-types, with the aim to frame my PhD research proposal with one of them.
To get started with EEG data, I'm planning to buy an EEG device to gather the same. My budget is $100-200. I'd immensely appreciate any recommendations about the kind of device I could go for, or available EEG data-sets I could explore. Thank you.
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Hi Puneet, do not buy device yourself! You can use any of existing repositories with already used EEG data for your aim. I also suggest to consider fractal and nonlinear measures to characterize EEG data, a Physionet is a good source to learn more about it.
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see above
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I anticipate that following areas provided that opportunities for pursuing research in Computer Science and Technology.
1. Cloud Computing((IaaS), (PaaS), (SaaS)), Big Data and industrial analytics, Industrial IoT, Robotics, Robotic Process Automation (RPA),Increased automation to reduce costs, Deep Learning, Computer Vision, NLP, digitalization, unstructured video, audio and image data analysis, Cyber security, Context-Rich Systems, Continued mobile pervasiveness, Web-Scale IT (bringing development and operations together in a coordinated way like DevOps), 3D Printing (New industrial, biomedical and consumer applications), Ad-hoc Mobile and Sensor Networks; Graphics and Visualization. Intelligent Systems, Modelling and Simulation.
2. Reinforcement learning is a paradigm for learning by trial-and-error inspired by the way humans learn new task.
3. Generative models to discriminative models that are used for classification or regression tasks learn a probability distribution over training examples.
4. Networks with memory like neural networks and in-memory systems
5. Hardware for training and inference like central processing unit (CPUs),graphics processing units (GPUs) with massively parallel architecture.
6.Autonomous Vehicles which are Self-driving vehicles use ML and deep learning (DL) algorithms to power computer vision that are similar to human decision making.
7.Writing Instruction to students and evaluation in academic research and analysis of innovations in the education system.
8. Industrial Internet of Things (IIoT) use built-in sensors on everyday objects, from fuel gauges to tires.
9.Inbound Logistics Planning ensures the right person receives the right number of supplies at the right place at the right time.
10.Retail Commerce which are market trends to offer personalized product recommendations that can increase sales.
11.Financial Analytics, Insurance, Banking and financial services like Fraud Detection, inbound traffic and detect suspicious behavior that is typical for spam and phishing, NPA, Credit Lending / Scoring and Regulatory compliance.
12.detect deviations from normal environmental characteristics, such as air pollution, climate variability and climate change.
13.Marketing metrics of Retargeting customers, products Recommendation engine, Social analytics and automation, Product Information Management, Marketing analytics and Pricing optimization and Return on marketing investment (ROMI).
14.Shelf audit/analytics like use video, images or robots on the retail area to audit and analyze B2C sales, Merchandising optimization Leverage machine learning and big data to optimize your online or offline merchandising.
15.Customer Service like Chatbot, Intelligent call routing and Call analytics, Survey & review analytics and Voice authentication etc.
16.GPS, Image recognition and visual analytics, Geo-analytics platform like Enables analysis of granular satellite imagery for predictions.
17.Healthcare market research and hospitalization like Personalized medications and care, Drug discovery, Early diagnosis, Suggest best treatment based on patient complaint and other data and Medical imaging insights.
18.Digital logic and embedded system, advanced nano technology, telecommunication, agribusiness, energy, and transportation, Air and rail transport management, sports, media and entertainment analytics, stock market and investments.
19. Computer applications of Genetic Engineering; Biotechnology; Microbiology, Computational Biology and Bioinformatics, Bio-metrics, Computer Security, digital crime and forensic investigation (Forensic Data Analysis).
20 Computer applications of Space Science, Airborne Astronomy, Space Exploration, Observation and Sensing Satellite. Spacecraft and satellites operating in deep space can generate huge amounts of data to explore.
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In my country and due to the present economic situation, we have problems with participation and attendance at conferences. Fees are often too expensive without mentioning travel and accommodation costs. Our research structures are no longer able to finance us. As a mentor I can not find conferences for my students which are either good and affordable. So my questions are:
- do you know of any good IT , education and/or computer science conferences that are not too expensive or that offer a special reduced fees for students?
-do you know organizations that can finance students from developing countries?
Thank you all.
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Arranging conference is the business with the intellectual people without risk and harms. So, try to never attend in the seminar , conferences without sponsor. Few days back a conference committee from Sri Lanka sent me a mail for my permission to join there as the keynote speaker. I agreed and the following week , they mailed me for a donation of $1500 ! I didn't reply at all. So, be careful !!!
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I would want to know how researchers from the developed countries could use their expertise to assist researchers in the developing countries to improve education in order to meet world standards. What is/are the philosophical foundations or research papers to support ways to improve educational standards.
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If u r asking about how to raise ranking of universities of ur country, it is actually done in several ways, but as a researcher ,publishing in ISI indexed journals, participation with international researchers , targeting hot areas in publications and etc would rather help. hope my answer can give a brief idea.
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I am planning to do some new research in intelligent information system.
My subjects Currently are Information retrivial and Advance data Science Can anyone suggest some interesting research topic to do my research work?
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I advise you not to look for a "hot" topic, but one which develops a sustainable skill set. Today's front page line's the bottom of tomorrow's birdcage!
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Dear Friends,
I am sure no scientist such as Copernicus, Kepler or Galileo bribed anyone to validate their discoveries that exposed 2300-year-old flawed belief (e.g. the Earth is static at centre) at the root and very foundation of then dominant paradigm (i.e. in 16th century) later referred to as geocentric paradigm or paradox.
But today research community expect me to bribe them or someone influential to get endorsement for my new discovery that exposes 50 to 60-year-old flawed beliefs (e.g. about components and CBD/CBE) at the root and very foundation of existing dominant paradigm for software engineering. Please refer to attached PDF for my discoveries that expose the flawed beliefs.
I never heard that any researcher ever paid bribe for investigation proof for getting endorsement for his discovery or theory, even in case of very complex and disruptive discoveries or theories by researchers such as a junior patent clerk (I.e. Einstein), Newton, Plank, Maxwell or Darwin.
Such discoveries or theories require investing many months of time and money for investigating evidence, facts and reasoning. Research community gladly investigated the evidence, facts and reasoning, without expecting any bribe or favours. It is the sacred duty of any researcher or scientist to investigate such new discoveries or theories. The scientific method requires publishing each new discovery or theory openly backed by evidence, facts and reasoning.
The scientific method requires other researchers and scientists to investigate the proof backed by evidence, facts and reasoning. They can reject such discovery or theory only by finding a flaw in the proof, evidence, facts or reasoning. Only an incompetent scientist or researcher rejects a new discovery based on his pre-connived notions or prejudice without looking at the evidence and facts.
Any researcher is only obligated to provide proof backed by evidence, observable facts and reasoning publicly. It is the moral and ethical obligation of the research community (having expertise in relevant domains) to validate the proof. It is humiliating to beg researchers to investigate the proof and being snubbed. Unfortunately, since no one in computer science is willing to fulfil their moral duty to investigate proof for a new discovery, I feel that I left with no other option but bribing scientists and researchers of software to investigate the proof for my discovery.
Isn’t is demeaning, if not unethical, to pay (or expect) money to get (or give) endorsement for a new discovery. The scientific process or method requires openly publish proof for such discovery backed by evidence, observable facts and reasoning. It is the duty of the members of research community to investigate the proof.
I feel, it is my moral duty and obligation to investigate such proofs for any new discovery (of another researcher), if the domain of the discovery and its proof are within the reach or realm of my expertise.
Often disruptive discoveries in any domain would be outside of the existing knowledge base of the domain but would be within the reach of experts in the domains but requires putting more effort to stretch to expand the boundaries to reach the new discovery. But discoveries in physics, chemistry or biological sciences are not in my realm of my expertise.
For example, I am qualified to validate proofs in software engineering domain, which includes even a disruptive discovery that is outside the boundaries and/or contradictory to existing BoK (Body of Knowledge). I will not abdicate my duty to investigate proof for new discoveries for expanding our boundaries of BoK (or to uphold the Truth) and is it wrong to expect other researchers to do the same (i.e. not abdicate their duty for the cause of expanding BoK or upholding the Truth)?
Best Regards,
Raju Chiluvuri
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Dear Dr. Pfeifer,
It is well documented in History, nationalism and national pride played major role in promoting new ideas, theories and discoveries and scientists made them between 17th and 19th century in the western European nations. Research communities in each of the nations made efforts to rigorously debated and discussed proposal of every possible discovery or theory, for example, in forums or societies such as Royal Society of London. Such societies acted as incubator of new theories to form and provided healthy debate and feedback for promising discoveries to flourish.
In general, I agree with you that it is a bribe. But I feel, in certain cases, it is not a bribe, if such journals are non-profit but created to provide a small forum or society for each specialized domain. The purpose of the society or forum is to provide healthy environment for debate and discussion for exploring new frontiers to incubate new theories and to grow for reasonable fee, if such forum requires money to create and sustain.
For example, Royal Society of London was incubator for ideas such as Gravity. Robert Hooke proposed idea of Gravity nearly 20 years earlier than Newton, but Newton provided mathematical proof for inverse square law.
I feel, our scientific knowledge could expand much faster, if we can create small online communities, where each community is targeted at addressing particular and small aspect or issue. It must provide healthy environment for debate and explore various new assumptions for incubating new theories, where promising theories can grow (as long as they can’t be falsified) and other theories that fail rigorous validation would be quickly discarded.
Another example for such society I knew was Homebrew Computer Club in Silicon Valley that incubated new ideas at that time, when it was small non-profit and promoted healthy debate between enthusiasts having pure passion (before it was captured by parasites for profit): https://en.wikipedia.org/wiki/Homebrew_Computer_Club
Best Regards,
Raju
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1- what is the new trends and recommendations in teaching project management subject for technical students?
2- is there different in teaching this subject for computer science major and information science major? what is it, if exist?
3- what are recommended book?
4- what is the best teaching strategy for teaching it?
5- what are related sciences that can teach with it?
6- how can I congener it with 'system analysis and design'?
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Hai Amany,
Hope students knew the concept about basics of software engineering before they start with SPM. In the beginning of course itself we can initiate project work to carry on SPM tools for real time problem. instruct them to write a case study by listing complete stuffs that provides planning insight then start working with tools. Plenty of open source tools available .
As Susanne mam mentioned more of virtual works is up in industry and certainly mainly tools have already built in feature of all the latest technology.
When providing with real time flavor , it will be interesting. Need to review it actively.
Towards end effective talk from industrial expert will add value to it.
Happy Teaching !
Suja
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Dear Friends,
I have encountered many researchers in the field of computer science and software engineering, each of them considers himself to be a scientist. But all most all of them fail basic test that can show weather a researcher is a real scientist, so fooling himself to be a scientist.
As per one of the greatest philosophers Dr. Karl Popper, a scientist must no longer hold on to a theory or belief, when conclusive counter evidence is presented to falsify a theory or belief.
I confronted many researchers by showing conclusive evidence that prove that their beliefs about the so-called software components and CBE/CBD (Component Based Design or Engineering) or fundamentally flawed.
The beliefs about so called software components and theories about CBD/CBE for software are in clear contradiction to facts and reality we know about the physical components and CBD/CBE for physical product respectively.
Instead of investigating evidence and facts presented to expose flawed beliefs and theories, each of the so-called scientists or researchers tried to viciously suppress the Truth and counter evidences or reasoning by resorting to personal attacks, snubbing or humiliations. A real scientist is morally and ethically obligated to engage in productive debate to uphold the Truth.
For example, in the context of CBD/CBE of countless physical products (e.g. cars, computers, cell-phones, bikes, TVs, ACs, airplanes, office equipment such as printers, machines or machinery for factory): What is the striking difference between kind of parts that are certainly components and all the other kinds of parts that are certainly not components?
Isn’t this an obvious or self-explanatory fact: In this context, no part can be a component, if the part is not conducive to be assembled and disassembled? Today, no known kind of so-called components for software is designed or conducive to be assembled and disassembled.
What is CBD/CBE? The CBD/CBE in brief has three parts (i) Partitioning a large or complex product in to smaller parts, where each part implements a small sub-set of self-contained features and functionality of the product, (ii) design and build each of the parts individually as a component, which can be assembled and disassembled, and (iii) building the product by assembling all the components, once all of the components are built and tested individually. Isn’t this a reality?
It is not hard to achieve this reality for complex software products. We have conclusive proof and evidence that this reality can be easily achieved, but software researchers refusing to look at the evidence or facts. They have been doing everything in their power to hold on to their flawed beliefs and myths by resorting to vicious personal attacks or snubbing to suppress counter evidences.
Who is a scientist (in another perspective)? Scientist is a person doing research in the pursuit of Truths for understanding the objective really and obligated to uphold the Truths in one or more related scientific disciplines (in which he claims to be a scientist).
What is a scientific discipline? Each scientific discipline is a BoK (Body of Knowledge) acquired and accumulated by using proven scientific method, process and principles. It is a mandatory duty and obligation for a scientist to follow or use proven scientific method, process and principles for doing the research and to uphold the Truth.
The scientific method was created in the 17th century by great philosophers such as Galileo, Descartes, Bacon and Newton to name a few. The scientific method has been perfected during past 300 years by countless contributions of great philosophers of science including Karl Popper, Thomas Kuhn, Arthur Schopenhauer, Russell or Feyerabend to name a few.
I am sure that the scientific method will be continuously improved and perfected by great philosophers in the future as well. No one can be a scientist, if he blatantly violates the basic principles or processes of scientific method. No person can be a scientist, if he doesn’t know the basic principles or processes of scientific method and/or blatantly violate the scientific method.
Computer science and software engineering defined nature and/or characteristics of components and CBD/CBE by blatantly violating the basic principles or processes of scientific method. Those basic assumptions made 50 to 60 years ago without any basis in rarity or fact, which are at the foundation of existing dominant software engineering paradigm and are fundamentally flawed.
Isn’t wrong to claim to be a scientist, if he blatantly violates scientific method? Today many software researchers claiming to be scientists but refusing to know or follow scientific method for understanding the reality and facts about components and CBD/CBE.
It is the duty of a scientist is to acquire and accumulating valid BoK (e.g. facts and theories backed by evidence and sound reasoning) by using the scientific method for comprehending the objective reality, for example, about components and CBD/CBE of physical or real products. Today software researchers denying basic scientific principles to maintain a paradox.
By denying scientific principles, one may maintain any paradox. - Galileo
P.S: Kindly forgive me if anybody is offended by the above inconvenient facts. Such facts must be said and knowing the facts is in his/her best interest, if any researcher doesn’t want to waste his/her lifetime of hard work and efforts in the pursuit of fool’s errand for expanding a flawed paradox in a scientific discipline, which is similar to the flawed geocentric paradox existed until 16th century.
The very purpose of research in any scientific discipline is acquiring and accumulating knowledge for expanding the BoK to comprehend objective reality by using the scientific method. How can anyone be a scientist, if he doesn’t know and/or blatantly violates the basic principles and processes of scientific method?
Best Regards,
Raju Chiluvuri
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Good discussion. Following.
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Hi all,
Please let me know me what’s the best teaching method that faculty should use to teach the computer science undergraduate and graduate students and why?
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I do not believe there is the best teaching method- "no one size shoe fits all" syndrome. Remember, there are teacher centered and student centered approaches. You must decided what approach will be appropriate or applicable for your teaching style to accommodate students' learning style. Then you must also consider the context and type of student (Net Generation) because these two factors can have an influence on the outcome of the lesson. In your case use more practical teaching approaches - a student centered approach -get them more involve and collectively engaging in the scenario or problem-based learning caases.
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je cherche comment construire La compétence structure d'un jeu généré par le modèle de domaine
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Can numbers (the Look then Leap Rule OR the Gittins Index) be used to help a person decide when to stop looking for the most suitable career path and LEAP into it instead or is the career situation too complicated for that?
^^^^^^^^^^^^^^^^^
Details:
Mathematical answers to the question of optimal stopping in general (When you should stop looking and leap)?
Gittins Index , Feynman's restaurant problem (not discussed in details)
Look then Leap Rule (secretary problem, fiancé problem): (√n , n/e , 37%)
How do apply this rule to career choice?
1- Potential ways of application:
A- n is Time .
Like what Michael Trick did https://goo.gl/9hSJT1 . Michael Trick A CMU Operations Research professor who applied this to his decide the best time for his marriage proposal., though he seems to think that this is a failed approach.
In our case, should we do it by age 20-70= 50 years --- 38 years old is where you stop looking for example? Or Should we multiply 37% by 80,000 hours to get a total of 29600 hours of career "looking"?
B- n is the number of available options. Like the secretary problem.
If we have 100 viable job options, we just look into the first 37? If we have 10, we just look into the first 4? If we are still in a stage of our lives where we have thousands of career paths?
2- Why the situation is more complicated in the career choice situation:
A- You can want a career and pursue it and then fail at it.
B- You can mix career paths. If you take option c, it can help you later on with option G. for example, if I went as an IRS, the irs will help me later on if I decide to become a writer so there's overlap between the options and a more dynamic relationship. Also the option you choose in selection #1 will influence the likelihood of choosing other options in Selection 2 (For example, if in 2018 I choose to work at an NGO, that will influence my options if I want to do a career transition in 2023 since that will limit my possibility of entering the corporate world in 2023).
C- You need to be making money so "looking" that does not generate money is seriously costly.
D- The choice is neither strictly sequential nor strictly simultaneous.
E- Looking and leaping alternates over a lifetime not like the example where you keep looking then leap once.
Is there a practical way to measure how the probability of switching back and forth between our career options affects the optimal exploration percentage?
F- There is something between looking and leaping, which is testing the waters. Let me explain. "Looking" here doesn't just mean "thinking" or "self-reflection" without action. It could also mean trying out a field to see if you're suited for it. So we can divide looking into "experimentation looking" and "thinking looking". And what separates looking from leaping is commitment and being settled. There's a trial period.
How does this affect our job/career options example since we can theoretically "look" at all 100 viable job positions without having to formally reject the position? Or does this rule apply to scenarios where looking entails commitment?
G- * You can return to a career that you rejected in the past. Once you leap, you can look again.
"But if you have the option to go back, say by apologizing to the first applicant and begging them to come work with you, and you have a 50% chance of your apology being accepted, then the optimal explore percentage rises all the way to 61%." https://80000hours.org/podcast/episodes/brian-christian-algorithms-to-live-by/
*3- A Real-life Example:
Here are some of my major potential career paths:
1- Behavioural Change Communications Company 2- Soft-Skills Training Company, 3- Consulting Company, 4-Blogger 5- Internet Research Specialist 6- Academic 7- Writer (Malcolm Gladwell Style; Popularization of psychology) 8- NGOs
As you can see the options here overlap to a great degree. So with these options, should I just say "ok the root of 8 is about 3" so pick 3 of those and try them for a year each and then stick with whatever comes next and is better?!!
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Hey Kenneth Carling , I got this number from page 29 in their book (Always Be Stopping, Chapter 1). They quote research results from Seale & Rapoport (1997) who found that on average their subjects leapt at 31% when given the secretary problem - they say that most people leapt too soon. They also say that there are more studies ("about a dozen") with the same result, which makes it more credible in my view.
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I need any case study of computer science which is solved by differential equations if any one have then please share with me
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Good day,
I am a current masters (by research) student and I am looking for an interesting and challenging topic for my research. I have been reading articles specifically for integrating computer science with a medical application. The areas I have been looking at is: using robotics in operations such as coming up with more accurate algorithms and methods. My other idea is to use sensory data to notify practitioners about the condition of the patient in order to suggest possible actions to be taken.
I just would like to ask on opinions of possible topics, and also if there are points on which I could expand on my suggested topics above.
Thank you
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Multidisciplinary study are the need of the hour. Can we do a multidisciplinary study on consumer behavior (Management) and Artificial Intelligence (Computer Science)?? If yes than what may be the title?
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Yes. You can do this. In fact, it may a good area of research if it be properly handled.
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Hi,
Do you know any postdoc position about computer science and privacy-preserving in IoT
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Hi All,
If any one know about paper format for Frontiers of Computer Science Journal like
-font size
-line space
-indent etc
please let me know...
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Following...
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Hello all,
I am aware of "formal methods" as it is used in computer science, to make sure our specifications are mathematically and logically sound (before we put them into a specific language). Isn't there a tool or form of notation so we can do that while we construct legitimate hypotheses for psychological research?
It is common knowledge that the construction of natural language questions (surveys about thinking and behavior), can be very questionable when it comes to construct validity. For example, did I cover everything? Am I even asking the right question? Trial and error without a formal test of our logic doesn't seem very efficient.
Does anyone know of a formal notation or research tool that lets us test natural language questions for how "sound" they are? After all, whether computer code (if/then we can do this) or human language (if/then we can assume that), it's pretty much the same logic. Thanks for any advice!
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I think you will need to address the use of formal methods in the society of engineering before you can use the methods more broadly. I am familiar with these methods, and I am quite skeptical of their application as you suggest.
However, I do believe that there is merit to the development of mathematics in the description of social behaviors on the underlying biophysical basis. A step beyond the statistical analysis and game theory so far.
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I am looking for different questionnaires based on Bloom Taxonomy (Affective, Cognitive and Social domains) to assess the learning of computer science student in CS1 courses(such as intro to programming class with java or c or python).
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Can you recommend some VALID questionnaires for Affective, Cognitive and Social domain?
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How to evaluate the( Data Flow Diagram / structure of processes/process description) with the expected output ? Could be by experts? Any referance??
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Dear you can visit RG for me ,so I written for this subject and meet to our idea
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Can anyone share any Journal Related to
Computer Science /Computer Engineering/ Information Security
where we can publish our research manuscript with very short period
Please : I dont want to submit in any of Open Access Journal
Thanking you in anticipation
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Its free and as i know it takes about one month for acception
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I would like to publish SCI -INDEXED journal ? is the above mentioned is SCI-indexed or not? pls. suggest
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International Journal of Applied Mathematics and Computer Science
Language English
Edited byJózef Korbicz
Publication details
Former name(s)Applied Mathematics and Computer Science
Publication history 1991-present
Publisher University of Zielona Góra and Lubuskie Scientific Society (Poland)
Frequency Quarterly
Open access Yes
Impact factor (2016)1.420 Standard abbreviations ISO 4 Int. J. Appl. Math. Comput. Sci.Math Sci Net Internat. J. Appl. Sci. Comput.
Indexing
ISSN 1641-876X (print) 2083-8492 (web) OCLC no.54678624 Links
  • Journal homepage
  • Online archive
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Theory of Computation is core subject of Computer science. Looking for resources for study material including presentations, tutorials to solve and question papers with guidelines to solve / verify solved problems. Thanks
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There are lots of Optimization method /Evolutionary algorithms (EAs) in literature. Some of them is more effective (for solving linear/nonlinear problem) compared to other. But we don’t know which will fit our model. As a result we checked for everything as we can do. But cant get the desire result. Some of those methods are 1. Genetic algorithms (GA) ; Haupt and Haupt (2004) 2. Pattern search (Mathlab) 3. Particle swarm optimization (PSO), Binary Particle Swarm Optimization (BPSO); Eberhart and Kennedy (1995) 4. Bee optimization; Karaboga and Bosturk (2007) Pham et al (2006) 5. Cuckoo algorithm; Yang and Deb (2009, 2010) 6. Differential evolution (DE) ; Storn and Price (1995, 1997) 7. Firefly optimization; Yang (2010) 8. Bacterial foraging optimization; Kim, Abraham and Cho (2007) 9. Ant colony optimization (ACO) ; I Dorigo and Stutzle (2004) 10. Fish optimization; Huang and Zhou (2008) 11.Raindrop optimization ; Shah-Hosseini (2009) 12.Simulated annealing ; Kirkpatrick, Gelatt and Vecchi (1983) 13.Biogeography-based optimization (BBO), 14. Chemical reaction optimization (CRO) 15. A group search optimizer (GSO), 16. Imperialist algorithm 17. Swine flow Optimization Algorithm. 18. Teaching Learning Based Optimization (TLBO) 19. Bayesian Optimization Algorithms (BOA) 20. Population-based incremental learning (PBIL) 21. Evolution strategy with covariance matrix adaptation (CMA-ES) 22. Charged system search Optimization Algorithm 23. Continuous scatter search (CSS) Optimization Algorithm 24. Tabu search Continuous Optimization 25. Evolutionary programming 26. League championship algorithm 27. Harmony search Optimization algorithm 28. Gravitational search algorithm Optimization 29. Evolution strategies Optimization 30. Firework algorithm, Ying Tan, 2010 31. Big-bang big-crunch Optimization algorithm, OK Erol, 2006 32. Artificial bee colony optimization (ABC), Karaboga,2005 33. Backtracking Search Optimization algorithm (BSA) 34. Differential Search Algorithm (DSA) (A modernized particle swarm optimization algorithm) 35. Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) 36. Multi-objective bat algorithm(MOBA) Binary Bat Algorithm (BBA) 37. Flower Pollination Algorithm 38. The Wind Driven Optimization (WDO) algorithm 39. Grey Wolf Optimizer (GWO) 40. Generative Algorithms 41. Hybrid Differential Evolution Algorithm With Adaptive Crossover Mechanism 42.Lloyd's Algorithm 43.One Rank Cuckoo Search (ORCS) algorithm: An improved cuckoo search optimization algorithm 44. Huffman Algorithm 45. Active-Set Algorithm (ASA) 46. Random Search Algorithm 47. Alternating Conditional Expectation algorithm (ACE) 48. Normalized Normal Constraint (NNC) algorithm 49. Artificial immune system optimization; Cutello and Nicosia (2002) 50. fmincon .
Besides this there are many other optimization algorithm recently invented which are generally called Hybrid optimization Technique because it’s a combination of two method. If we share our experiences then it will be helpful for all of us who are in the field of optimization. I may be missing some methods, researcher are requested to add those algorithms and the way of use like many model needs initial value, weight, velocity, different type of writing objective function etc. I am facing some problems that’s why I make this format which will definitely help me as well as all other researchers in this field. Expecting resourceful and cordial cooperation.
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Dear Mashud,
I have some experiences in improving optimization algorithms like quantum invasive weed optimization algorithm ( ) and world cup optimization algorithm ( ).
From my experiences two point are important to select a good optimization algorithm:
1) check that do your problems can be solved by the classic methods? if so, do not go to the meta-heuristics.
2) If your problem was NP-hard and can not solve by the classic methods:
after a lot of testifying, I found that there is no more differences among the evolutionary algorithms. of course in some case, one algorithm may have better performance or has high speed, but this prominence is not so bold.
3) Two cases that you should point to them (in evolutionary algorithms) are: Exploration and Exploitation.
Exploration parameter is for places that you have no information about the search space anymore and Exploitation is about that you have an approximate solution for your problem and this parameter in this case finds better solution.
These two parameters comprise the structure of all of the optimization algorithms. for example, in Genetic algorithm, Mutation is an exploration parameter and crossover is an exploitation parameter.
So based on your requirements, select an algorithm that has promonancy about your considered parameter.
good luck,
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I'm currently doing a forecast for users expenditures, but i want to determine if a certain expenditure is going to happen or not before forecasting the amount. What method can i use?
I was currently looking at Markov chain but i'm falling to develop one.
Your help will be appreciated.
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One more idea of extending my previous answer. I would go for complexity measures. They are based on the work of Stefan Boltzmann and equation
H = SUM_i (p_i * ln_2(p_i)), over all I
Where I stay for slots which collects certain intervals of the measured value. You can, in this way, map even complex systems into a simple measured based on the Boltzmann equation.
This enables you to observe even subtle changes within the system, and in the tip of it, long time before their ma roscopic evidence.
Try to study how biosignals are processed using complexity measures: approximative, permutation, alphabetic, FFT, etc. Machine learning techniques are very useful in assessing complex systems measures as well.
Try to find good overviews of those issues. Very good level of complexity measures is developed in the field of processing EEG signals my field) and even EEGs.
Feel free to ask more. The area is very wide and deep and not easy to orientate.
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In a convolution neural network, given an input signal, each processing element gives out an output that is fed in other elements of the network. What happens with the original signal? As it propagates through the network and splits in different pathways it passes through various elements. Is it possible that is passes through an element and continue its pathway unmodulated, regardless the output of this particular element? What does the modulation (if present) depend on?
Excuse my lack of knowledge of the technical language, as I am not an expert in computer science.
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Imagine each neuron has an input-output function (a.k.a activation/transfer/response function) by which the input signal temporally modulates (i.e., convolutes in Fourier domain).
The neurons in a usual 'convoluted network' use non-linear-though very simple-transfer functions (e.g., Sigmoid, Heaviside step, etc), therefore:
  • If a signal get passed a neuron it is most probably modulated unless if the neuron's transfer function is a constant number (e.g., in a buffer).
  • You cannot decompose the original signal from the modulated signal because of this non-linear modulation.
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Interested in remote research in Public Policy that is voluntarily unpaid, and where I can use my computer science background. Technologies in particular I want to use are Machine Learning, Data Science etc. I wish to pursue Masters/Ph.D. in this field, and hence looking for opportunities to build a profile.
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Rafiya,
I would first concentrate on public policy that is more or less neutral so that you can focus on your Masters/Ph.D. degree before embarking on more complicated public policy issues.
I would start by focusing on initiatives that are carried by institutions that are outside or at the periphery of government agencies which can be more open to proposals and help from external people. This would depend on your particular geographical location and the organizations that are available there. Doing it alone, while more rewarding and less restricted will probably be lot while you are also focusing on your degree.
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What is the main difference between dual band and dual radio?
Let
A system equipped with:
Dual Band= 2.4 GHz and 5 GHz
Dual Radio=802.11 and 802.14.5
where 802.11 with 5GHz is deploy between air to air link
and 802.11 with 2.4 GHz between air to ground.
similarly some nodes are also connected through 802.15.4 with 2.4 GHz between air to air.
The above system is dual band dual radio
or triple band dual radio
or triple band triple radio?
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Dual band refers to a device which uses two different frequencies to communicate.
Dual radio refers to a device which uses two different protocols to communicate.
Maybe an illustration would help. A dual band device is like a person at a party who can move between two different rooms (different frequencies) to talk with other people, while a single band device would be limited to talking to people in only one room. On the other hand, a dual radio device can speak with people who speak in two different languages, while a single radio device can only speak one language.
A dual radio device is typically used as an intermediary between two different networks like 802.11 (like WiFi) and 802.15.4 (like many wireless sensors).
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This question is probably stupid but I am a computer science student so I don't know much about MRI's literature.
I have read some studies on MRI preprocessing and in each the authors talk about 3D images. But when I asked a doctor to show me MRIs, he showed me a list of 2D images. Do I have to build a 3D image from the 2D images? Should I ask the doctor for the 3D images?
Thank you in advance!
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Actually we can and often do true 3D aquisitions in MRI. In that case a thick slab is excited and phase-encoding is applied in two densions. MPRAGE images, for example, are usually acquired this way. Since the data is 3D, a 3D- FFT is used to reconstruct the images. But DICOM files are basically 2D, so the scanner software saves the 3D data as a series of 2D images. Whether the data was truly acquired as 3D or a set of 2D slices as Bazhdar described, most DICOM views will group the "slices" and display the data as a 3D volume.
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Social effects of young people using social media on smartphones are currently an important topic of research. It is not easy to research a topic that has been developing for several years and is still developing. Social media has dominated the online communication of young people. The social behavior of young people has changed. Added to this are health issues. It has already been shown that due to the use of smarfons, the degree of deterioration of young people has significantly increased.
However, worsening eyesight, emerging vision defects in many young people using smarfons are not potentially the only negative aspects. The research conducted on this issue shows that there are various social effects of using young people from social media portals in smartphones. Unfortunately, there are also more and more research on negative aspects of social use by young people from social media portals in smartphones.
Research on the social effects of young people using smartphones to communicate via social media portals should be conducted. First of all, we do not know the potential effects of changes in the social behavior of citizens, which may have a psychological basis. These studies should also answer the question: whether dynamic technological progress in the field of communication techniques can significantly modify the social behavior of citizens and what the significance of changes in psychosocial behavior regarding entire societies may have.
Young people using social media portals in smartphones point to many positive aspects, but these are basically only facilitations in terms of communication and obtaining information. However, negative social aspects are not perceived by young people using social media portals in smarfons. Research is already being carried out in some research centers in the field of sociology, but we will have to wait for full confirmation of the research.
In addition, these studies will be continued in the following years because the technology of online social media portals and also in the field of communication techniques and devices, including smarfonów is still developing and now it is difficult to determine in which direction this progress is going, what new categories of risks will appear in relation to with this progress.
Do you agree with me on the above matter?
In the context of the above issues, I am asking you the following question: What is the legitimacy of conducting social research on the effects of smartphone use by young people to communicate via social media portals?
Please reply
I invite you to the discussion
Thank you very much
Best wishes
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I also like to add that the original conception of smart phones by Nokia is based on Master and Slave arguments from the point of view of technology [communication nodes and receivers] but in reality has a negative social connotation, because the reality is that people became real slaves to the masters of smartphone companies!!
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Mathematics has been always one of the most active field for researchers but the most attentions has gone to one or few subjects in one time for several years or decades. I'd like to know what are the most active research areas in mathematics today?
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Mathematics is a science that creates, models, describes, explains, applies, and of course its areas of research are always new. Ask about a branch in recent development and of interest to the scientific community is to prepare to find countless answers. Of course, the investigator's self-interest will guide him to appropriate topics.
I have read some answers to this question, published in this medium and I am surprised. They do not do science a favor with them.
What is the reason for writing " Physics will beat mathematics — look at my reform! " . What reform? Somebody knows about that reform?
Physics is a great science, and from its observations mathematics has developed very serious theories (Fourier - Heat, Gauss - sound). They were times of illustration. And conversely, Physics has found that without the development of mathematics there are many observations that could not be modeled.
But, returning to the initial question, I think you should look for an answer, and in that I agree with @ Mirjana Vukovic , if your interest is in pure or applied mathematics.
Greetings from Venezuela
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The development of innovation is currently one of the key production factors in developed economies.
In recent years, developed economies have created many technological, process, product, service, marketing, ecological, material and other innovations.
In some countries cooperation programs for research and R & D centers with enterprises are being developed to activate entrepreneurship and innovation of business entities.
Because in developed countries information, innovations, new technologies and entrepreneurship are considered as one of the most important factors of the country's economic development and, as a consequence, also economic growth measured, for example, by the Gross Domestic Product in subsequent years.
In addition, research and implementation works are conducted in these themes, which further underline the high level of significance of innovation, new technologies and entrepreneurship in contemporary national economies.
Clusters are created within which enterprises undertake cooperation with other business entities, with scientific, research and implementation centers, universities, public sector institutions to exchange experiences, transfer knowledge, run and develop joint research and implementation projects, including innovative technological and process solutions , research, organizational and other.
However, in order to be able to objectively verify the effectiveness of these programs to activate the level of innovation, it is necessary to periodically perform a precise measurement of changes in the level of innovation in geographical, local, national, in relation to individual departments, sectors of the national economy or by examining specific types of business entities, companies and corporations.
Because innovation is determinant of economic development of a qualitative nature, it is difficult to measure.
In connection with the above, I would like to ask you the following question: How is the level of innovation most often measured in your country?
Are they carried out periodically, eg surveys among management, among managers of companies and corporations, or other methods, are periodical changes in the level of innovation in specific types of business entities or in individual sectors of the national economy?
Do you have specific quantitative measures developed that can be helpful in measuring innovation?
Please, answer, comments. I invite you to the discussion.
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There are quite a few methodologies: in Croatian research we often use WEF methodology. I find GEM appeoach very interesting.
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I have started programming binary bat algorithm to solve knapsack problem. i have misunderstanding of position concept in binary space :
Vnew= Vold+(Current-Best) * f;
S= 1/ ( 1+Math.exp(-Vnew));
X(t+1) = { 1  S>Rnd  , 0   Rnd>=S)
the velocity updating equation use both position from previous iteration (Current) and global best position (Best). In continuous version of BA, the position is real number but in the binary version, position of bat represented by binary number. In Knapsack Problem it means whether the item is selected or not. In the binary version, transfer function is used to transform velocity from real number to binary number. I'm confused whether the position in BBA is binary or real number ? if binary then the (Current-Best) can only be 1 - 0, 0 - 1, 1 - 1, etc. and if real number then how to get the continous representation if no continous equation to update the position (in original BA, the position updating equation is X(t+1) = X(t) + Vnew
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Unless you are doing just an "exercise", I discourage you from trying "new" metaheuristics for knapsack. Besides being a widely studied problem, there are very good knapsack specific algorithms. Check David Pissinger's webpage for codes and test instances generators.
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Is there a lists of free journals in computer science?
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most of springier and Elsevier journals are free if you don-not need to purplish open access
you can choose the journal according to your work from the below links
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Everyone, at some point, has probably thought about the problem artificial intelligence(AI) may represent in the future when the rate of unemployment is rising at an alarming speed thanks to robots that do a much better job than any human ever did but the question is : how, when, and where will the impact of artificial intelligence hit hardest?!
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Perhaps another way to answer the question is with another question. Did electronic calculators, and subsequently computers, replace mathematicians, accountants, statisticians, and engineers? No. Just made them that much more productive.
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Hello all, I would like to know of any good alternatives to Springer theses. I would like to publish my PhD thesis and Springer theses was a good option but you have to be nominated by a partnering university so this is not an option for me. So, what is the next best thing for a Computer Science/ Machine learning/ Natural language processing /health Informatics thesis?
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Go for inderscience
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Like AI, space technology etc.
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A very wide field of technologies in a variety of sectors, indeed. For example chemical science and industry. See:
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with general knowledge, we can easily understand whether a shape is circular or not. seeing the attached picture we can easily say that it is circular. For small deviation or deformation we don't get confused.
now-a-days computer has its own vision. without complex computation, can computer understand a shape as circle ?
what are the methods using which computer can identify a shape as circle?
I am looking for a simple algorithm which can perform some simple computation on an image to understand its circularity.
Foran example, if radius of image is equal to the redius of equivalent circle, the image is ⭕️ circle.
Thank you all,
appreciate your time and contribution.
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first you have to determine the center, then you can map the use the equation 4 * pi * Area/(r2)
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Is there a mathematical way to determine how much data points are required to map a 3D object?
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Aparna Sathya Murthy : A shape is fixed by three point in 3D. In terms of translations and rotations, you can think of it this way. If point A maps to A', that takes care of three translations, but the shape can freely rotate attached to A'. If a second point B maps to B', the shape can only rotate around line A'B'. A third point C' fixates that last degree of freedom.
Chin Fung Tsang : If there are deformations, we are not talking about linear transformations anymore; the "degrees of freedom" (if that term still makes sense) might be infinite. The number of points needed depends on the accuracy you want. There is no general recipe.
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Greeting! Is there any Pakistani Computer Science journal indexed in Master list of Science Citation Index Expanded (SCIE)?
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I want to know the answer, because I want to pursue my PhD in Computer Science by research on Software Engineering area.
I have already completed my MSc in Computer Science where my Major was Software Engineering.
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I think that the ICT adoption in SMEs is good topic.
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I am a thrid year undergraduate student at IIT (BHU) Varanasi..My aim is to pursue masters in field of computer science..i am looking for foreign research internship at the interface of ML/computer vision..could anyone suggest me , please?
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Keep your eyes on:
University of California Santa Barbara
New York University
University of Texas at Austin
Texas A&M University Corpus Christi
University of Arizona
Rutgers University
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Please tell me list of scopus indexed journals with rapid publication and low publication charges in the field of data mining or computer science
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List of Scopus Indexed Open Access Journals are as
Computer Science
(Artificial Intelligence)
1. Journal of Artificial Intelligence and Soft Computing Research.
2. Journal of Machine Learning Research.
3. Journal of Artificial Intelligence Research.
4. Computational Linguistics.
5. Frontiers in Neurorobotics.
6. Systems Science and Control Engineering.
7. Bulletin of the Polish Academy of Sciences: Technical Sciences.
8. International Journal of Advanced Robotic Systems.
9. i-Perception.
10. Journal of Intelligent Systems.
11. International Journal of Intelligent Systems and Applications.
12. Cybernetics and Physics.
13. Journal of Automation, Mobile Robotics and Intelligent Systems.
14. Kybernetika.
15. Statistics, Optimization and Information Computing.
16. International Journal of Computer Information Systems and Industrial Management Applications.
17. International Journal of Automation and Smart Technology.
18. Paladyn.
19. Journal of Information Systems and Telecommunication.
20. Inteligencia Artificial.
21. Linguistica
22. Applied Computational Intelligence and Soft Computing
Computer Science
(Computational Theory and Mathematics)
1. Theory of Computing.
2. Algorithms for Molecular Biology.
3. BioData Mining.
4. International Journal of Computers, Communications and Control.
5. Algorithms.
6. Journal of Graph Algorithms and Applications.
7. Electronic Journal of Combinatorics.
8. Prikladnaya Diskretnaya Matematika.
Computer Science
(Computer Graphics and Computer-Aided Design)
1. Journal of Cheminformatics.
2. International Journal of Design.
3. Journal of Computational Design and Engineering.
4. International Journal of Computer Games Technology.
5. Journal of WSCG.
6. VLSI Design.
7. Artnodes.
Computer Science
(Computer Networks and Communications)
1. Journal of Big Data.
2. Engineering Science and Technology, an International Journal.
3. Digital Communications and Networks.
4. Journal of Internet Services and Applications.
5. Journal of Cloud Computing.
6. Electronics (Switzerland).
7. Journal of King Saud University, Engineering Sciences.
8. Animal Biotelemetry.
9. Journal of Biomedical Semantics.
10. International Journal of Telemedicine and Applications.
11. International Journal of Communication Networks and Information Security.
12. Journal of Electromagnetic Engineering and Science.
13. Eurasip Journal on Wireless Communications and Networking.
14. Security and Communication Networks.
15. International Journal of Distributed Sensor Networks.
16. First Monday.
17. Bulletin of the Polish Academy of Sciences: Technical Sciences.
18. Future Internet.
19. Journal of Computer Networks and Communications.
20. Mobile Information Systems.
21. International Journal of Computers, Communications and Control.
22. Wireless Communications and Mobile Computing.
23. International Journal of Intelligent Systems and Applications.
24. International Journal of Electronics and Telecommunications.
25. South African Computer Journal.
26. Periodica polytechnica Electrical engineering and computer science.
27. Serbian Journal of Electrical Engineering.
28. International Journal of Interactive Mobile Technologies.
29. International Journal of Networked and Distributed Computing.
30. Journal of Information Systems and Telecommunication.
31. Journal of Electronic Science and Technology.
32. Applied Computational Intelligence and Soft Computing.
33. International Journal of Network Security.
Computer Science
(Computer Science Applications)
1. SoftwareX.
2. GigaScience.
3. Scientific data.
4. Frontiers in Neuroinformatics.
5. Journal of Cheminformatics.
6. EPJ Data Science.
7. Journal of Internet Services and Applications.
8. Computational Linguistics.
9. Egyptian Informatics Journal.
10. BMC Bioinformatics.
11. Eurasip Journal on Information Security.
12. Journal of Theoretical and Applied Electronic Commerce Research
13. Language Learning and Technology
14. Logistics Research
15. Applied Sciences (Switzerland)
16. BioData Mining
17. Research in Learning Technolog
18. Eurasip Journal on Wireless Communications and Networking
19. Journal of Interactive Online Learning
20. Electronic Journal of e-Learning
21. International Journal of Advanced Robotic System
22. Transport and Telecommunication
23. Data Science Journal
24. Mobile Information Systems
25. International Journal of Computers, Communications and Control
26. TripleC
27. Scientific Programming
28. Modeling, Identification and Control
29. Journal of Graph Algorithms and Applications
30. International Journal of Intelligent Systems and Applications
31. Digital Education Review
32. Mathematical and Computational Forestry and Natural-Resource Sciences
33. Journal of innovation in health informatics
34. International Journal of Advances in Soft Computing and its Applications
35. Interaction Design and Architecture(s)
36. Journal of Control Science and Engineering
37. Modelling and Simulation in Engineering
38. Nordic Journal of Digital Literacy
39. South African Computer Journal
40. Periodica polytechnica Electrical engineering and computer science
41. Journal of Machine Engineering
42. Journal of E-Learning and Knowledge Society
43. International Journal of Computer Science and Applications
44. International Journal of Electronic Commerce Studies Journal of Information and Organizational Sciences
45. Eurasian Journal of Mathematical and Computer Applications
46. Language Documentation and Conservation
47. International Journal of Interactive Mobile Technologies
48. International Journal of Networked and Distributed Computing
49. EasternEuropean Journal of Enterprise Technologies
50. Annals of Library and Information Studies
51. Australian Educational Computing
52. Journal of Information Systems and Telecommunication
53. Applied Computational Intelligence and Soft Computing
55. Meridian (Raleigh)
56. Virtual Archaeology Review
Computer Science
(General Computer Science)
1. IEEE Access.
2. International Journal of Health Geographics.
3. Human-centric Computing and Information Sciences.Engineering.
4. Journal of King Saud University - Computer and Information Sciences.
5. Engineering Applications of Computational Fluid Mechanics.
6. International Journal of Computational Intelligence Systems.
7. Computational Intelligence and Neuroscience.
8. International Journal on Advanced Science, Engineering and Information Technology.
9. Logical Methods in Computer Science.
10. IAENG International Journal of Computer Science.
11. Journal of Universal Computer Science.
12. Studies in Informatics and Control.
13. ETRI Journal.
14. Computer Science and Information Systems.
15. Journal of Information Technology Education:Research.
16. Journal of Graph Algorithms and Applications.
17. Advances in Electrical and Computer Engineering.
18. Foundations of Computing and Decision Sciences.
19. Turkish Journal of Electrical Engineering and Computer Sciences.
20. Discrete Mathematics and Theoretical Computer Science.
21. Journal of ICT Research and Applications.
22. Journal of the Brazilian Computer Society.
23. Interdisciplinary Journal of Information, Knowledge, and Management.
24. Journal of Computing and Information Technology.
25. International Journal of Computer Science in Sport.
26. . Cybernetics and Information Technologies.
27. Journal of Theoretical and Applied Information Technology.
28. Internetworking Indonesia Journal.
29. Acta Scientiarum - Technology.
30. Iranian Journal of Information Processing Management.
31. Journal of International Commercial Law and Technology.
Computer Science
(Human—Computer Interaction)
1. Journal of Computational Design and Engineering
2. International Journal of Computer Games Technology
3. Journal of Interactive Online Learning
4. Advances in Human-Computer Interaction
5. First Monday
6. Australasian Journal of Information Systems
7. International Journal of Intelligent Systems and Applications
8. Interaction Design and Architecture(s)
9. South African Computer Journal
10. International Journal of Automation and Smart Technology
11. Paladyn
12. CrossTalk
Computer Science
(Information Systems)
1. Journal of Big Data
2. Molecular Systems Biology
3. Scientific data
4. Journal of Artificial Intelligence and Soft Computing Research
5. Database : the journal of biological databases and curation
6. Egyptian Informatics Journal
7. APSIPA Transactions on Signal and Information Processing
8. Eurasip Journal on Image and Video Processing
9. Journal of Spatial Information Science
10. Library and Information Science Research
11. Informatica
12. Security and Communication Networks
13. Bulletin of the Polish Academy of Sciences: Technical Sciences
14. Journal of Computer Networks and Communications
15. Information (Switzerland)
16. Journal of Intelligent Systems
17. Wireless Communications and Mobile Computing
18. Australasian Journal of Information Systems
19. Information Technology and Libraries
20. Electronic Journal of Information Systems in Developing Countries
21. South African Computer Journal
22. Periodica polytechnica Electrical engineering and computer science
23. Journal of Information and Organizational Sciences
24. Eurasian Journal of Mathematical and Computer Applications
25. Statistics, Optimization and Information Computing
26. International Journal of Computer Information Systems and Industrial Management Applications
27. Journal of Information Systems and Telecommunication
Computer Science
(Signal Processing)
1. Electronics (Switzerland)
2. APSIPA Transactions on Signal and Information Processing
3. Eurasip Journal on Image and Video Processing
4. Image Analysis and Stereology
5. Sensing and Bio-Sensing Research
6. Eurasip Journal on Information Security
7. Eurasip Journal on Wireless Communications and Networking
8. Eurasip Journal on Advances in Signal Processing
9. International Journal of Intelligent Systems and Applications
10. Cybernetics and Physics
11. Journal of Electrical and Computer Engineering
12. Journal of Automation, Mobile Robotics and Intelligent Systems
13. Periodica polytechnica Electrical engineering and computer science
14. Statistics, Optimization and Information Computing
15. International Journal of Computer Information Systems and Industrial Management Applications
16. International Journal of Automation and Smart Technology
17. Prikladnaya Diskretnaya Matematika
18. Journal of Electronic Science and Technology
Computer Science
(Software)
1. CrossTalk
2. Journal of Statistical Software
3. SoftwareX
4. Journal of Machine Learning Research
5. Journal of Cloud Computing
6. Transactions on Data Privacy
7. International Journal of Computer Games Technology
8. International Journal of Advanced Robotic Systems
9. E-Informatica Software Engineering Journal
10. Journal of Object Technology
11. Diagnostyka
12. Scientific Programming
13. Journal of Intelligent Systems
14. Modeling, Identification and Control
15. Kybernetika
16. Journal of WSCG
17. Periodica polytechnica Electrical engineering and computer science
18. Electronic Letters on Computer Vision and Image Analysis
19. Journal of Communications Software and Systems
20. Telfor Journal
21. Inteligencia Artificial
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If a Journal was not indexed at the time of publication. After few years if that specific journal gets indexed with Scopus or SCI/SCIE. What will be the status of previously published papers?
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Previously published papers are not considered. Only those papers are considered, which are submitted after the journal is indexed.
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I teach computer programming (in high school) for the mere reason of increasing the impact of the future of the Computer Science Industry. I stand on my theory that computer science curriculum is missing the mark by focusing on computer science instead of building a foundation through teaching programming so when high school students gain the math skills needed to excel in CS they will be successful. I teach programming to 150 students a year with a waiting list when most colleagues can't fill one class due to the prerequisite of a strong math foundation. I am interested in your project. Feel free to contact me.
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Raju Chiluvuri that is part of my dilemma. I hear that all the time so those are the students that teachers are recruiting. I am in a high school that if I only recruited those students I would have to compete with engineering, aerospace, and advanced math and science classes for students. So I take the other approach for two reasons, I was never very good at math and I love programming and it fulfills me and gives me joy. The other reason, is students that are not labeled as being "good" in math and science have more fight and determination in them. They don't give up if they don't get it at first. The students that graduate after several years in my program are foundationally sound to pick up almost any language and report back to me their success in college. So maybe I should detail the question a bit different and add should we teach a few computer science or many to program? What would college professors rather see in their seats? More students with a solid foundation or a few students that already excel in programming before they reach college?
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Now, AI and ML are considered more fields of the computer science, and more of the research are made in post graduate studies where goes people with differente grade titles. It's possible to have a real "machine learning engineering" or something like that in the universities?
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In optimization problem often we use local optimum but is it global? Or are there any meta-heuristics algorithm to obtain global solution? If there any then what is the name of that algorithm and if possible how we can get that solution?
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I wish not to let you down, but the basic answer is "very seldom", and another one is "you will not know if you have stumbled upon an optimal solution, because there is no natural termination criterion based on the concept of optimality". (In contrast, a branch-and-bound, or branch-and-cut, methodology is based on local AND global bounds on the optimal value generated throughout the procedure, and in most cases the correct procedures will either fix some variables to their optimal values before termination, and they will be able to discard a very large portion of the search space based on parts of the search space being infeasibie or inferior, in which case we do know for sure that an optimum has been reached.)
If you have a structure of the problem that makes it emanable to be solved by special methods, such as Benders decomposition - when you have a mix of integer variables and continuous variables. you also have a fail-proof method.
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Dear Friends,
History shows that many influential members of the research community actively instigated and clandestinely aided the prosecution and conviction of Galileo and others. I can't find any scientist who vocally opposed the prosecution by saying that they have moral obligation to uphold the Truth, if they can show sound evidence for proving the Truth. The other researches even refused to look at the evidence.
How can we blame Vatican alone when we can't find any vocal supporter for freedom to show evidence? I can't believe that Vatican had prosecuted them, if few researchers opposed the prosecution by saying if they have sound evidence, they have right to pursue and obligation to present evidence to uphold Truth. It is immoral to prosecute anyone for pursuing objective Truth (since objective Truth is divine).
Even if few members of community of philosophers or researchers don’t agree or refuse to look at evidence, they must take blame for instigating and aiding such prosecution. We doomed to repeat the same mistake again, if we fail to learn lessons from past mistakes by successfully deflecting the blame onto some else.
If you are a researcher, which one you should believe: Your sense, intellect and reasoning, or authority of books that are rooted in such fallacies? If Holy Scripture says all swans are white, would you advocate prosecuting someone for committing heresy, if he/she offers to show black swans to expose the fallacy?
If all the books in the world say dolphins lay eggs. Isn’t wrong to prosecute someone, when he tries to expose such fallacy by requesting for an opportunity to demonstrate sound evidence for proving that dolphins give birth to baby dolphins?
What is authentic: The objective reality that can be observed, or text books that has fallacies such as software parts that can be reusable in multiple products are components for CBD/CBE (Component Based Design or Engineering) of large products, where reusable parts for software are equivalent to parts such as steel, cement, plastic, silicon, alloys or metals, which are sourced from the makers of respective parts and reusable by the designers of many products such as cars, cell-phones, computers or makers of computer chips etc.?
What is the Objective Reality in the context of large products we know and use every day such as cars, computers, cell-phones, TVs, ACs, equipment such as printers, airplanes, machines or machinery for factory etc.?
Let me list couple of facts: A component is a specific kind of part that can be (or designed to be) assembled and disassembled. Except software products, every known large product is built by assembling such specific kind of parts that can be assembled, where the specific kind of parts are widely referred to as components. Also, no other kind of parts is referred to as components in this context.
I was either banned or humiliated, when I politely requested for an opportunity to prove this truth to researchers at few IITs or IIIT at Hyderabad. I was banned for politely requesting an opportunity for demonstrating such software applications built by assembling components (i.e. specific kind of parts that can be assembled).
If there is an institution in 21st century that has authority to prosecute such efforts, I feel, many of those researchers would not hesitate to instigate the institution. In that case, whom should we blame? The institution that prosecuted or those researchers instigated the institution? I would rather be prosecuted for heresy than being ignored, because that may give me an opportunity to present evidence.
Also, the researchers those who watched silently must also share blame. Today no book or research paper on software components for CBD/CBE say this obvious fact: A part can be component in the context of CBD/CBE of large products, only if the part is designed and/or conducive to be assembled and disassembled.
Unfortunately, saying this fact (no part can be a component, if the part can’t be assembled) is considered heresy by the software community. Most researchers I requested for an opportunity to expose this fallacy, tried hard to supress me. Others either choose to be silent or provided tacit support to those vocal suppressors.
It is not hard to demonstrate many examples to prove that there is no valid reason, why we can't design and build large software products in the same way engineers have been designing and building every other kind of complex products we know and use every day such as cars, computers, cell-phones, TVs, ACs, equipment such as printers, airplanes, machines or machinery for factory etc.
That is, each large product is built by assembling specific kind of parts that can be assembled. Where the specific kind of parts that are designed to be assembled and disassemble (or can be assembled) are known as components in the context of every such large product we know and use every day.
If every book in the world says that Dolphins lay eggs, don’t you have right to expose such fallacies by presenting evidence (if you have sound evidence)? Any reseacher has moral obligation to expose such fallacy, if it wastes research efforts of thousands by diverting the efforts into inexplicable paradox like geocentric paradigm.
Why the following fallacy is any different from the above fallacy about the Dolphins: Today software parts that can be reusable are defined as components for CBD/CBE for software products? Today no known kind of so called components for software products is conducive to be assembled by any stretch of imagination.
I am willing to be prosecuted and punished, if an opportunity is given and if I fail to provide sound and conclusive proof that it is possible to build software products by assembling real components, where the real components for CBD/CBE for products imply specific kind of parts that can be assembled and disassembled.
Isn’t it wrong to ostracize me (e.g. by resorting to vicious personal attacks) for politely requesting an opportunity to expose a fallacy that is root cause for the infamous software crisis? I am not prosecuted, only because today there is no such institution as Vatican of 17th century to instigate the institution to prosecute me. Too bad, I wish I could get an opportunity to present evidence even in such inquisition.
Is saying this fact heresy: The Dolphins are mammals, so don’t lay eggs? But a similar fact is perceived to be heresy today: Any part can be a component in the context of CBD/CBE of products, only if the part can be assembled. Unfortunately, this fact offended common sense and egos of many renowned researchers and influential experts on so called components for the CBD/CBE of software products.
Every book or research paper on software says: The components for CBD/CBE (Component Based Design and Engineering) for software products are parts that are designed and/or conducive to be reusable across multiple software products (or conform to a so called component model).
But the objective reality in the context of CBD/CBE of countless products we know and use every day (e.g. cars, computers, cell-phones, TVs, ACs, airplanes, office equipment such as printers, machines or machinery for factory) is: The components for CBD/CBE for products are specific kind of parts that are designed and/or conducive to be assembled and disassembled.
Not even a single book or research paper on components for CBD/CBE of products mentions this self-evident fact: A part that is not conducive or designed to be assembled is not a component, in the context of countless products (e.g. cars, computers, cell-phones, TVs, ACs, airplanes, office equipment such as printers, machines or machinery for factory) we know and use every day.
The single greatest contributor for increasing manual productivity in designing, engineering and building large or complex physical products is specific kind of parts that can be assembled and disassembled, where the specific kind of parts are widely known (and/or referred to) as components. Isn’t it a fact: No other kind of part is referred to as component in the context of CBD/CBE of large products?
Many influential or powerful members from the software community have been tried their best to ostracize me for struggling to expose such fallacies about the components at the very foundation of the BoK (Body of Knowledge) for existing dominant software engineering paradigm. Many software experts or researchers won’t hesitate to instigate and aid prosecution for heresy (for offending their egos by exposing sacred beliefs or faith about components), if such option is available.
I feel that it is an honour to be prosecuted for trying to uphold the Truth by any respectable institution or honourable court. If I were convicted, I only blame the researches those aided such inquisition and those who watched silently. I believe, Galileo also would have blamed scientists those who instigated and aided Vatican. Those scientists abdicated their sacred duty of pursuit of objective reality and Truth (e.g. to satisfy their egos offended by the Truth or to cover-up their incompetence).
Whom would you blame, if you were a neutral observer: The Vatican whose sacred duty is upholding the Faith, or the philosophers or scientists (gave evidence as expert witnesses) whose sacred duty is upholding the Truth? I blame the scientists for abdicating their sacred duty. I am sure the Vatican’s inquisition could not have convicted Galileo without the evidence given by those expert witnesses.
Best Regards,
Raju Chiluvuri
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Dear Dr. Peter,
Let me continue previous message to make an interesting and funny observation about Incommensurability between competing paradigms:
Almost every engineer knows engineering paradigm for designing & building other kind of large or complex products by using components and component based design.
Please wear hat of engineering paradigm expert for other kind of large or complex products, then try to explain about components and component-based design to a 2nd yourself wearing hat of software engineer.
P.S: Let me caution you :-) The 2nd you likely resort to personal attacks on the 1st you trying explain engineering paradigm for other kind of large and/or complex products ;-).
Many great philosophers such as Dr. Popper were critical about Dr. Kuhn's concept of Incommensurability. I feel, Dr. Kuhn realized that most of the human endeavors would have imperfections, including scientific research, knowledge and progress.
In my humble opinion, the main difference between Dr. Popper and Dr. Kuhn is, one is more of an Idealist while the other is more of a realist.
Dr. Kuhn studied history of science and learned valuable lessons and insights from the history of science by being astute student of history. He realized that imperfections are unavoidable, and by knowing about possibility of imperfections allow us to take corrective measures.
For example, accepting the possibility of imperfections in our knowledge allow you to make discoveries by detecting or accepting imperfections sooner than others, who are blissfully ignorant and denying such possibility (as software research community have been refusing to accept imperfections in CBD/CBE for years).
Best Regards,
Raju
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Hello there!
I'm working as an RA in a project that examines wearable technologies (production and consumption) from a sustainability perspective.
Do you have some reading suggestions, journal articles or conference proceedings, from the fields of computer science or social science?
Any tips are highly appreciated. Have a great start for a new semester!
Sincerely,
Jenna Kuronen
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is nano technology possible to come in the human cantrol and it will be use in futre?
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There are lots of Optimization method /Evolutionary algorithms (EAs) in literature. Some of them is more effective (for solving linear/nonlinear problem) compared to other. But we don’t know which will fit our model. As a result we checked for everything as we can do. But cant get the desire result. Some of those methods are 1. Genetic algorithms (GA) ; Haupt and Haupt (2004) 2. Pattern search (Mathlab) 3. Particle swarm optimization (PSO), Binary Particle Swarm Optimization (BPSO); Eberhart and Kennedy (1995) 4. Bee optimization; Karaboga and Bosturk (2007) Pham et al (2006) 5. Cuckoo algorithm; Yang and Deb (2009, 2010) 6. Differential evolution (DE) ; Storn and Price (1995, 1997) 7. Firefly optimization; Yang (2010) 8. Bacterial foraging optimization; Kim, Abraham and Cho (2007) 9. Ant colony optimization (ACO) ; I Dorigo and Stutzle (2004) 10. Fish optimization; Huang and Zhou (2008) 11.Raindrop optimization ; Shah-Hosseini (2009) 12.Simulated annealing ; Kirkpatrick, Gelatt and Vecchi (1983) 13.Biogeography-based optimization (BBO), 14. Chemical reaction optimization (CRO) 15. A group search optimizer (GSO), 16. Imperialist algorithm 17. Swine flow Optimization Algorithm. 18. Teaching Learning Based Optimization (TLBO) 19. Bayesian Optimization Algorithms (BOA) 20. Population-based incremental learning (PBIL) 21. Evolution strategy with covariance matrix adaptation (CMA-ES) 22. Charged system search Optimization Algorithm 23. Continuous scatter search (CSS) Optimization Algorithm 24. Tabu search Continuous Optimization 25. Evolutionary programming 26. League championship algorithm 27. Harmony search Optimization algorithm 28. Gravitational search algorithm Optimization 29. Evolution strategies Optimization 30. Firework algorithm, Ying Tan, 2010 31. Big-bang big-crunch Optimization algorithm, OK Erol, 2006 32. Artificial bee colony optimization (ABC), Karaboga,2005 33. Backtracking Search Optimization algorithm (BSA) 34. Differential Search Algorithm (DSA) (A modernized particle swarm optimization algorithm) 35. Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) 36. Multi-objective bat algorithm(MOBA) Binary Bat Algorithm (BBA) 37. Flower Pollination Algorithm 38. The Wind Driven Optimization (WDO) algorithm 39. Grey Wolf Optimizer (GWO) 40. Generative Algorithms 41. Hybrid Differential Evolution Algorithm With Adaptive Crossover Mechanism 42.Lloyd's Algorithm 43.One Rank Cuckoo Search (ORCS) algorithm: An improved cuckoo search optimization algorithm 44. Huffman Algorithm 45. Active-Set Algorithm (ASA) 46. Random Search Algorithm 47. Alternating Conditional Expectation algorithm (ACE) 48. Normalized Normal Constraint (NNC) algorithm 49. Artificial immune system optimization; Cutello and Nicosia (2002) 50. fmincon .
Besides this there are many other optimization algorithm recently invented which are generally called Hybrid optimization Technique because it’s a combination of two method. If we share our experiences then it will be helpful for all of us who are in the field of optimization. I may be missing some methods, researcher are requested to add those algorithms and the way of use like many model needs initial value, weight, velocity, different type of writing objective function etc. I am facing some problems that’s why I make this format which will definitely help me as well as all other researchers in this field. Expecting resourceful and cordial cooperation.
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Abu, you are not very clear. If you want to discuss effectiveness, then you need to define what that is, and run experiments on a huge set of carefully randomized test problems in order to make any claims about one method being better than another. I have mentioned on more than one occasion that if you have a deep knowledge of your problem and its properties, chances are very slim that a metaheuristic will be the winner against your own devise.
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Hello,
According to the NIST test suite's instruction, there are 15 tests for proving randomness and each tests require different minimum length of the sequence (i.e. Frequency : n > 100, Maurer's Universal : n> 10^6). Thereby, some tests are not applicable to examine the randomness of short sequences (I want to use the sample length n = 128 or 256. ). In fact, I have seen some studies omit those tests that require long sequence instead. I would like to ask a couple questions.
1. In the case of testing such short sequences, is it to neglect the test which require long length of sequence such as Binary Matrix Rank Test, Non-overlapping Template Matching Test, Overlapping Template Matching Test. and report only results from the remained tests?
2. Is there any other way to examine the randomness of short sequences ?
Thank you in advance
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Dear Karakot,
I suggest you to see links and attached files in topic.
-Statistical Testing of Cryptographic Randomness - DergiPark
-NIST SP 800-22: Documentation and Software - Random Bit ...
-CryptRndTest: An R Package for Testing the ... - The R Journal
-true random number sequences from gamma ... - Academia Romana
-Using Information Theory Approach to Randomness Testing
Best regards
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Suggest some project topics and ideas in Computer Science field
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Well, after some researches I got that understanding:
we can measure the Effectiveness of the security system through analyzing its works without facing the system to any threats or attacks. And after the analysis we gonna be able to know whether the system effective or not.
Whereas,
In order to meassure the functionality of the security system, it should apply under an attack scenarios and analysis its work. And after the analysis we can know how much the functionality of the security system.
Any better illustration, and thanks in advance (:
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Hello, Ahmed. Effectiveness and Efficiency are universal concepts. When something is effective, it means it works as it is supposed to.
Efficiency is a comparison between two or more machines, people, software or appliances. When something works "better" than another thing, we say the first is more efficient than the second. Usually a more efficient thing costs less than another or takes less time to perform the same task.
However, in different domains, different restrictions apply.
In network security (IDS/IPS) one software can be more effective than another if the first one has less false negatives (it fails to detect a real attack). We assume that it is very difficult to detect 100% of the attacks. Please note there are no logs for false negatives. The network administrator or security expert will detect the attack by other means.
Nevertheless, it can clearly be more efficient than the second if it reports less false positives (it detects a legitimate traffic as an attack).
For anti-malware software the reasoning is the same. Some software detect only what is in their knowledge base, while others use machine learning to detect malware mutations automatically. In this case, the second anti-malware is more effective than the first. In terms of efficiency, the second software may take to much CPU time and memory to run, while the first takes much less. In this context, the first software is more efficient than the second one.
If you want to test an IDS/IPS you may try the LOIC (Low Orbit Ion Cannon) software. https://sourceforge.net/projects/loic/
Do not test it against your production network. You should build a test environment instead.
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Due to the nature of my research and data analysis, our lab uses Matlab. I am not from a Computer Science background and have no knowledge on computer programming and writing scripts. What are the must do for beginners to grasp the complexity of script writing in Matlab? Any advise and suggestions woukd greatly be appreciated.
Thank you.
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Dear Mr. Ayon
plenty of you-tube videos are available for beginners. there you can learn and then practice yourself.
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I am doing research in the field of computer science and need to review the English language
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No problem i have ph.D lecturer can help you
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Dear Friends,
Kindly allow me to extract few interesting quotes from this page “Science is at its end, all the important things have already been discovered!”. The following paragraph is extracted from http://amasci.com/weird/end.html
"Sometimes I really regret that I did not live in those times when there was still so much that was new; to be sure enough much is yet unknown, but I do not think that it will be possible to discover anything easily nowadays that would lead us to revise our entire outlook as radically as was possible in the days when telescopes and microscopes were still new." - Heinrich Hertz as a physics student
I heard many researchers making such despairing statements (in fact I used to feel the same way 20 years ago). It is always much simpler to discover many things when any new paradigm for a scientific discipline was in its fledgling nascent stage. There would be many low hanging fruits for easy picking, when any field in its nascent stage. Even less intelligent people have chance of finding things or could start picking low hanging fruits, while brilliant renowned experts wasting time being skeptical or fighting to suppress the new reality/paradigm.
Instead of trying to find easy pickings in such newly discovered fledgling nascent Heliocentric model of their discipline, most of the brilliant fools fiercely defend the flawed Geocentric paradox of their discipline (e.g. by resorting to vicious personal attacks on the proponents of new model).
Kindly refer to wiki for normal science at: https://en.wikipedia.org/wiki/Normal_science, which says:
Normal science, identified and elaborated on by Thomas Samuel Kuhn in The Structure of Scientific Revolutions, is the regular work of scientists theorizing, observing, and experimenting within a settled paradigm or explanatory framework, Regarding science as puzzle-solving, Kuhn explained normal science as slowly accumulating detail in accord with established broad theory, without questioning or challenging the underlying assumptions of that theory.”
In short: Normal science solves puzzles that are posed by the prevailing paradigm but does not challenge the paradigm's basic beliefs (that are at the root and used as foundation for building the paradigm). For example, 2300 years old belief “the Earth is static at center” was at the root and foundation for 16th century dominant geocentric paradox.
The wiki on “Normal Science” further states:
“Kuhn stressed that historically the route to normal science could be a difficult one. Prior to the formation of a shared paradigm or research consensus, would-be scientists were reduced to the accumulation of random facts and unverified observations, in the manner recorded by Pliny the Elder or Francis Bacon, while simultaneously beginning the foundations of their field from scratch through a plethora of competing theories.”
The physics went through that stage between 400BC (i.e. time of Plato and Aristotle) and 16th century, when the basic tenet at the root “the Earth is static at the center”. A complex geocentric paradigm had been evolved for 1800 years until 16th century. We now know that no meaningful progress was possible in the geocentric paradox, except exposing the error “the Earth is at the center”.
When heliocentric model was proposed most of the brilliant fools choose to fiercely defend the flawed Geocentric paradox, rather than finding easy pickings on nascent Heliocentric model. Many brilliant people (e.g. Heinrich Hertz) and ordinary people like me must have longed for such simpler times.
Even ordinary people like me had a chance to make meaningful contribution in such simpler times. But today, people like me can’t even understand theory relativity. It is beyond mental capability of brilliant people to even comprehend theories such as String theory. Only handful of people in the world has the intellectual capability to comprehend such complex theories.
I learned hard way that: A monkey has better chance of understanding trigonometry, than the chance ordinary old engineers like me has to understand String theory. No wonder many people like me long for simpler times, where there is a chance (even if it is very small chance) to make useful contribution.
From 1874:
"When I began my physical studies [in Munich in 1874] and sought advice from my venerable teacher Philipp von Jolly... he portrayed to me physics as a highly developed, almost fully matured science... Possibly in one or another nook there would perhaps be a dust particle or a small bubble to be examined and classified, but the system as a whole stood there fairly secured, and theoretical physics approached visibly that degree of perfection which, for example, geometry has had already for centuries." - from a 192 4 lecture by Max Planck (Sci. Am, Feb 1996 p.10)
Many experts such as Dr. Fred Brooks and other Turing Award winning researchers stated that Software engineering and computer science reached this stage in mid 1980s. That is, Software engineering as a whole stood there fairly secured, and software components approached visibly that degree of perfection which, for example, geometry has had already for centuries.
Dr. Fred Brooks wrote seminal book “Mythical Man Month” in 1975 and influential Papers such as "No Silver Bullet – Essence and Accident in Software Engineering" in 1986.
Those books and papers were published more than 30 and 40 years ago. They withstood the test of time (i.e. no significant progress is made as theorized by Dr. Brooks) and in the process acquired many strong supporters. I was one of them. It is hard to attract treasure hunters to such well trodden and thoroughly explored discipline.
Chance of making any useful contribution is nearly Zero. How can anyone discover anything, when there is nothing there to discover in the geocentric paradox of software.
Only brilliant people have mental capability to master mature paradigms such as Theory of Relativity. No one can make any contribution without mastering such mature paradigm. It requires many decades of hard work even to brilliant people to master such mature paradigm.
Isn’t it despairing to people like me having average intellect? What chance a person having ordinary intellect has to discover something new, when tens of thousands of researchers before him already explored found everything that can be found in a dominant paradigm?
But lucky me! Existing dominant paradigms for Computer Science and software engineering has been evolving for past 50 to 60 years by relying on flawed assumptions (as the 16th century geocentric paradox evolved for 1800 years by relying on flawed assumptions).
Exposing the flawed assumptions open vast uncharted and hidden realms for exploration. This gives an opportunity to build new superior paradigm rooted in well tested facts from scratch. Such virgin territories offer many easy pickings, even for people having ordinary intellect.
But the problem is that: Instead of trying to find easy pickings, even brilliant fools choosing to fiercely defend the flawed Geocentric paradox of software engineering. Many of them not able to recognize the simpler times they have been longing for, even such simpler times hits in their face.
The huge BoK (Body of Knowledge) for existing dominant software engineering paradigm has been acquired and accumulated for over 50 years. This huge BoK is result of passionate hard work of Tens of thousands of researchers at any time during past 50 years.
Even today tens of thousands of researchers around the world are working hard, hoping to find something that earlier generations might have missed on the well-trodden path. Few dozen researchers must already be exploring anything you would choose to explore.
It is a tall order that a small thing hidden from combing sight of countless brilliant people explored before still to be found in a nook and corner of a dominant paradigm. Isn’t it despairing for a young researcher, who must spend many decades to master already existing huge BoK before he can have any chance of finding some thing hidden or new? Is there any wonder many young aspiring researchers yearn for simpler times?
In a mature dominant paradigm, everything has 4-digit accuracy. His efforts might increase it to 5-digit accuracy, if at all brilliant people before him overlooked an insignificant nook or corner.
Look at the bright side: We get to build a brand-new paradigm (a huge tree of BoK having many branches and sub branches) from clean slate by finding each of the new facts and rigorously test for validating each of the facts before relying each on the facts for acquiring to accumulate each piece of knowledge for the BoK starting from scratch.
Join me in growing the tree of BoK from budding seed for evolving a new paradigm. This kind of opportunity comes once in a century and no more than once in the history of each scientific discipline.
My request to each software researcher is, don’t be a brilliant fool. Existing dominant paradigm of CBD/CBE is rooted in lies. Nothing of significance is left to be found.
A new paradigm opens vast new uncharted territory. A new paradigm must be built from clean slate. Whatever you find might become a bud-seed for a new branch of knowledge in the tree of the BoK for the new paradigm.
Best Regards,
Raju Chiluvuri
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Dear Dr. Sieving,
Let me make an interesting observation. Normal Science for advancing a complex dominant paradigm requires brilliant peoples, who could master the huge BoK (Body of Knowledge) acquired and accumulated for many decades for the dominant paradigm.
The influential book “The Structure of Scientific Revolutions” by Thomas Kuhn says: Normal science solves puzzles that are posed by the prevailing paradigm but does not challenge the paradigm's basic tenets.
One must be brilliant to make any contribution (e.g. by solving a scientific puzzle) to any topic in normal science, because many other researchers also working of solving the same puzzle posed by each of the topics. Hence, one must be able to find a solution for a puzzle, where many experts failed already failed to solve the puzzle.
With little luck, it is much simpler to start a scientific revolution, particularly for ordinary people like me who cannot solve such complex puzzles by mastering the huge BoK of dominant paradigm. Please refer to attached PDF.
Isn’t ironic that starting scientific revolution is much simpler than making even a small contribution to a dominant paradigm?
It is very hard even for a brilliant researcher to make a small contribution to a dominant paradigm.
But even person having ordinary intelligence could start scientific revolution with curiosity and little luck.
Best Regards,
Raju
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Dear all,
I would like to publish my papers in a journal. Since it is strongly required to publish the paper in an international journal indexed by Scopus, I face some difficulties due to some fees that must be paid by the author. My research areas are computer science, electrical and electronic engineering, artificial intelligence, and image processing.
Are there any Scopus-indexed journals without publication fees suitable for my research areas?
I would like to thanks for your kind help.
With best regards,
Wikky
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Dear Maki,
Rachid is right.
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Dear All
Have a nice day. I am planning to start my new project on Big Data Analytics in Healthcare. I am not from from Computer Science Background. I am just little bit confuse, which software uses is easier for beginners as non computer science background.
Your valuable comments are highly appreciates.
Thanks in Advance.
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Tableau is not a big data analytic software, it's a BI/Reporting software, but i agree it's very user-friendly.
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For the sake of interest I was out looking for a discussion of functions in computer science as generalized functions. I started my search by something such as "computer functions as mathematical functions". NO paper discusses functions in computer science in terms of set theory, and they compare (not equate) mathematical functions and functions in programming. Where did I miss the buss? Mathematics need not be done with numbers, although the largest application of mathematics is to numbers.
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Short answer. The use of the term "function" as a designator in commonly-used programming languages is actually a mistaken use of the mathematical notion having the same name. It seems that, in the early days of computer software and programming language development, the choice of nomenclature was in some sense a corruption of the mathematical usage. It wasn't malicious, but an over-reaching that was perhaps not well-understood at the time.
In programming languages, "function" is used to designate a specific computational procedure. For appropriately-written procedures, there is establishment of a specific algorithm for some similarly-named mathematical function. It is not the function, it is an algorithmic procedure. When accurate, the correspondence between represented operands and the represented result satisfies the relationship established for the mathematical functions domain and range members.
There are many procedures for the same function, in this sense (and there can be many mathematical characterizations of the same function).
The clouding of nomenclature becomes an issue when one needs to deal with the fact that mathematical use of functions need not have any direct connection with computation.
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Wich online system or website you use to track submissions and calls of main journals for Computer Science?
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There were two methods of doing modular transformations from Entity Relationship Diagrams to Class Diagrams according to international researchers. In order to establish which method would best suit software engineers, we conducted a survey by giving a group of students in the computer science field, whom we considered potential future software engineers. The results we got were valid, but did not match those of any of the international researchers. We found that this situation could only be explained using Eastern Four-Valued logic, also known by such names as Catuskoti and Tetralemma.
Yours Sincerely,
N D Kodikara, G K A Dias and R S Madanayake
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I would not necessarily categorize either system as particularly eastern or western. I think we all are raised with an understanding of On, Off, and something in the middle or have walked up a staircase.
The reason that binary "won" in terms of the representation of digital data is that it is the easiest to implement with the fewest number of transistors. Tri-state logic emerged more out of practical necessity because we need to make "real" computers. 4 and 5 state logics emerged also for the same reason - making electrons move around. Even in such systems, rarely are these multiple states used for computing, but rather buffering and interfacing various things withing a computing device.
With that said, there are some curiosities which emerge if a particular fabrication technique make it cheaper, smaller, easier to implement N-state gates. Then you can do things like have a base 3 or base 4 computing element.
In chip design VHDL uses a 9-state logic to allow the representation of arbitrary logic circuits, including tri-state or 4 or 5 state logic. Look at IEEE 1164, then hope you never need to look at it again.
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Hello everyone, I have problem with multi output regression.
I want to find a model that makes an image,output, with a voltage,input.
However, because the image shape is too various, I want to make a model with
a train set that only deal with a single each pixel.
Than I want it to use at the various shape of image.
For example, I want to make a model that maps v to X that is a vector having a shape of (1,0,0,0), (0,1,0,0) ,(0,0,0,1).. example.
With that model I want to map the test v to x that is like (1,0,1,0).
Through linear activation function based learning, it suceeded.
However it is hard to make it in a more precise way with nonlinear activation function, like ReLU.
Actually it seems that ReLU tends to pick a single pixel of the desired test image.
So if there is some tips related to this problem, I want to ask some help.
Because I am not majoring in computer science, I need your help, please.
Thank you.
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Do you really need regression? You can see an example of regression in week 2 videos of this course https://www.coursera.org/learn/neural-networks-deep-learning/home/info (videos are free).
The difference in image shape can be treated by padding. Convolutional neural networks are designed to capture features regardless their position (e.g. eyes, nose, hand). You can find pretty simple implementations of traditional neural architectures that proved their efficiency. The Stanford course is quite good https://www.coursera.org/learn/convolutional-neural-networks/home/info
You have several free deep learning frameworks (keras https://keras.io/, thensorflow, theano, pytorch...). Keras, in my opinion, is the simplest one, especially for standard architectures (https://keras.io/getting-started/sequential-model-guide/). You can also find free pre-trained models
You can also find a lot of examples of CNN in Keras just by googling "convolutional neural networks keras"