Science topics: Computer Science
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Computer Science - Science topic

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ACST’21: 1st National Conference on Applied Computing and Smart Technologies
July 10, 2021, Ecole supérieure en Informatique, Sidi Bel Abbes, Algeria
Conference Web Page: https://acst.esi-sba.dz Conference Easychair Page: https://easychair.org/cfp/ACST21
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Thanks for sharing!
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Hi,
I'm hoping to pursue a PhD in either Computer Science or Data Science. I'm relatively new to Data Science and I'm open to any research area in any of the above categories. So any research topic recommendation for a doctoral research?
Best Regards,
Panchali
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I suggest you select a topic in "high-dimensional data" and link yourself to the subjects like genetic data.
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I am looking for computer science journal
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Dear researcher,
Use Journal finder (open Google and search it).
Best regards
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I need suggestions for a good book that covers the basics of Blockchain Technology that will be prescribed for BS Computer Science students.
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I agree with Kristian Kostal and also recommend Bitcoin and Cryptocurrency Technologies from Princeton University.
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In this regard, I reviewed the articles indexed in DOAJ, but no suitable case was found.
I need an open-access journal in the field of computer science (cloud computing) that
  1. does not limit the number of pages of the submitted article
  2. does not have a processing or publishing fee
  3. is indexed in JCR or Scopus
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Unfortunately, almost all open access journals charge processing fees especially scopus indexed journals.
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Is it possible now or in the future to create an artificial intelligence that will draw knowledge directly from the analysis of Internet resources and learn this knowledge?
Please reply
Best wishes
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The issue of the possibility of self-improvement of the system of artificial intelligence, which gained autonomy, got out of human control and by downloading data from the Internet it is becoming an increasingly powerful and threatening system for humans since the 1990s in science fiction literature and film. With each subsequent year, the technology of artificial intelligence is developed and improved. So, can the scenario presented above come true in the future? What do you think about this? Please reply.
Thank you, Regards,
Dariusz Prokopowicz
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In which scientific studies you run or plan to run would be artificial intelligence helpful?
Please reply
Best wishes
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Dear Vladimir Rotkin,
No. The discussion was not over. The overwhelming majority of the topics discussed in my Research Gate profile are still relevant and the discussions are open. Yes you are right. The issue of varieties of "analytical" artificial intelligence is also important. You added an important point to our discussion.
Thank you, Have a nice day, Stay healthy! Best wishes,
Dariusz Prokopowicz
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Can anyone suggest payment based fast track sure publication in computer science or cybersecurity SJR or JCR journals?
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Many thanks
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1. Functions
2. Matrix algebra & eigenvectors
3. Vector algebra
4. Complex numbers
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The topics mentioned are mathematical in nature and without a focus on a particular computer science application that you have in mind it is difficult to provide research papers.
You could start by focusing on getting your hands on a linear algebra book (most linear algebra books cover all these areas including complex numbers) and understand the subject. You might also search for a particular book on linear algebra applied to computer science.
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Dear,
I m finding low cost but impact factor journal of computer science.
Which domain as Network and communications,
Please help me, I will be thankful to you...
Regard......
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Acta Informatica, AI and Ethics, AI & SOCIETY, Algorithmica,Annals of Mathematics and Artificial Intelligence, Applicable Algebra in Engineering, Communication and Computing, etc
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Computer Science and Engineering
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- Formal methods for analysis and verification of robotic software
- Analysis and verification of smart-contracts in blockchains
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Hello,
I'm interesting in to know if you have had educational experiences with m-learning (mobile learning) in engineering or computer science. In the literature, it seems to be that there are few proposals with m-learning platforms or applications to strengthen the skills or competences of the students in the basis of engineering and even computer science. Typical applications are located, e.g., in EFL and math.
Under this context, What have been your experiences with m-learning in engineering education or computer science?, and What advantages or difficulties do you consider regarding m-learning?
Thank you for your answers.
Best regards,
Jonathan
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Interesting
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Dear All,
I am developing a small computer program "kendo" ( ) for the data processing and visualization of mass spectral data (MS1 and/or MS2, SWATH, IM-MS...) mainly using netCDF and mzML file formats.
For mzML files, I haven't found any complete list of the "accession" codes defining specific parameters (e.g. <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value=""/>; <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>; <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value=""/> ...)
Does anybody have such a list so I can generate clean mzML files ?
Thank you !
Thierry
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Hey Thierry, I am not an expert on this, but this may help:
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One interpretation includes the following explanation:
Application of computer science and technology, special purpose scanners, for recognition of signals obtained by excitation of magnetic fields in electrotechnical devices, apparatus and measurement.
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Vishnu Kumar Gupta's
Additional question:
What does UDC 004.6:004.86 mean?
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Any decision-making problem when precisely formulated within the framework of mathematics is posed as an optimization problem. There are so many ways, in fact, I think infinitely many ways one can partition the set of all possible optimization problems into classes of problems.
1. I often hear people label meta-heuristic and heuristic algorithms as general algorithms (I understand what they mean) but I'm thinking about some things, can we apply these algorithms to any arbitrary optimization problems from any class or more precisely can we adjust/re-model any optimization problem in a way that permits us to attack those problems by the algorithms in question?
2. Then I thought well if we assumed that the answer to 1 is yes then by extending the argument I think also we can re-formulate any given problem to be attacked by any algorithm we desire (of-course with a cost) then it is just a useless tautology.
I'm looking foe different insights :)
Thanks.
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rez-ord.docx
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Hello,
I am seeking recommendations from the Research Gate community regarding studies about
the IT and Artificial intelligence solutions to assisting medical emergency cases.
What are the perspectives and future works that could be done in this area?
Best regards,
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Kindly, suggest me some SCIE, ESCI or SCOPUS indexed computer science journals which are paid but fast response?
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IEEE Access, PeerJ Computer Science, Journal of Intelligent and Fuzzy systems
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Information processing and communication are described by a tri-state system, in classical systems such as FPGAs, ICs, CPUs, and others, in multiple applications programmed by Verilog, an IEEE standard. This has replaced the Boolean algebra of a two-state system indicated by Shannon, also in gate construction with physical systems. The primary reason, in my opinion, is in dealing more effectively with noise.
Although, constructionally, a three-state system can always be embedded in a two-state system, efficiency and scalability suffers. This should be more evident in quantum computing, as explained in the preprint
As new evidence accumulates, including in modern robots interacting with humans in complex computer-physical systems, this question asks first whether only the mathematical nature is evident as a description of reality, while a physical description is denied. Thus, ternary logic should replace the physical description of choices, with a possible and third truth value, which one already faces in physics, biology, psychology, and life, such as more than a coin toss to represent choices.
The physical description of "heads or tails", is denied in favor of opening up to a third possibility, and so on, to as many possibilities as needed. Are we no longer black or white, but accept a blended reality as well?
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Great idea
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Hi everyone! I would like to write my bachelor's thesis on a topic that's currently relevant in the sphere of finance, marketing or computer science (or if it's possible a topic concerning all the three fields of interest). Those fields are the same upon which my bachelor is based (Bachelor of Science in Economics, Management and Computer Science).
I've some broad ideas about the topics, for example: the link between brand equity and financial performance; the effects of aggressive marketing on financial markets; the new generation of traders (covid has increase the number of retail investors with no previous experience); machine learning applied to behavioral finance (I really enjoy those last two topics but have no idea on how to connect them).
Obviously any kind of suggestions, regarding new topic (broad or specific) or the development of cited ones would be greatly appreciated.
Thank you in advance!
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A good answer would be: Digital currencies and digital payment - an IT challenge for safe transactions.
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Dear Friends,
Can you guess which one is the most mysterious and enigmatic physical thing among these things such as biological cells, light, elementary particles (e.g. electrons, neutrons or protons), viruses, fungi, bacteria, atoms, chemical compounds, biological cells, blood cells or finally plain old components, in the context of engineering paradigms (e.g. mechanical, electronics, or aerospace) for designing and building large products (e.g. cars, airplanes, computers, factory machinery or spacecraft)?
The greatest tools for acquiring and using knowledge for technological progress and great inventions are (i) scientific method and (ii) mathematics, where these two tools provide complementary perspectives for gaining deeper insights. Each act like a light to illuminate mutually complementary sides, perspectives or dimensions. Since software researchers refuse to use scientific method (i.e. light of science), software community wasted 50 years and failed to solve software crisis and ended up with a useless fake CBE-paradigm.
If fake scientists still don’t realize that it is a mistake to blatantly violate scientific principles, they are going to repeat same kind of mistakes for Artificial Intelligence research and development. Many things would stay enigmatic and end up in a crisis, like software crisis. Many things that are inexplicable and puzzling or enigmatic in the perspective of mathematics can become crystal clear from the scientific perspective, since light of scientific method illuminates the dark spots left by light of mathematics.
Today, greatest enigmas for researchers of software and computer science include answers to following simple questions such as what is meant by a component in the context of all the other engineering disciplines, and what is meant by CBE (Component Based Engineering) that successfully eliminated engineering crisis form designing and building large and complex products (unlike software crisis).
Even if we know just 30% about bacteria or viruses that has been documented in the textbooks, each and every piece of knowledge can only be included in the textbooks, if and only if the piece of knowledge is supported by falsifiable proof. It impossible to find a piece of knowledge that is not supported by a falsifiable proof. There is a possibility that 20% of the knowledge in the textbooks might be falsified by finding counter evidence in the future such as new discoveries or empirical evidence.
Since mankind have enough valid knowledge about things such as bacteria, light or electrons, researchers are able to invent great things such as treatments for many kinds of infections, fibre-optic networks or semi-conductor chips respectively.
On the other hand, none of the knowledge about the components in the textbooks for computer science or software is either tested (e.g. no one challenged) or supported by any falsifiable proof. But there is a possibility that up to 20% of the knowledge might be proven valid in the future. However, I am sure that 80% of the knowledge in the textbooks is invalid and not open for challenge.
Even simple things such as what component is and what is meant by CBE stayed an enigma and mysterious for many decades, since knowledge in the textbooks about components is untested and invalid. Fake scientists at NSF ( that I prefer to call National Fake Science Foundation) feel offended, if anyone challenges their myths about so called components.
Anything would be less enigmatic or mysterious, even if we only have 30% valid knowledge than another thing that has huge knowledge, but significant portion of the knowledge is invalid. Hence, plain old components are far more mysterious and enigmatic than the invisible things such as viruses, electrons and biological cells. We made many useful inventions by even by relying on the limited valid knowledge.
Can you name any physical thing on the Earth that is more mysterious and enigmatic for scientific community than plain old components used for designed and building large products, by taking into consideration all the knowledge in the published scientific literature and textbooks for all scientific disciplines?
A thing must be the most mysterious and enigmatic, if there is a large BoK (Body of Knowledge) for the thing and if larger percentage of the BoK is invalid (e.g. untested and unproven). The main reasons that makes anything enigmatic is not just lack of sufficient valid BoK but also having large chunks of invalid knowledge.
Isn’t it fascinating? Even such simple to acquire knowledge would stay mysterious and enigmatic (and creates a paradox and crisis), if researchers refuse to use the light of scientific principles to illuminate dark spots that are in the realm of science, since such dark spots can’t be illuminated by the light of mathematics.
I invented solutions for software crisis by gaining scientific knowledge essential for understanding mysterious components essential for achieving the elusive and enigmatic CBE-paradigms, in the context of all the other engineering disciplines. The fake scientists of computer science foolishly refusing to use light of scientific method.
The NSF that supposed to uphold scientific principles and scientific method, but is breaking scientific principles, protocols and code of conduct for scientific discourse, which is essential for progress of science and technology. Any accepted theory (i.e. theory or concepts derived from the theory that are being used by practitioners of any craft or trade) must be treated as an assumption, if the theory is not supported by a falsifiable proof (that is backed by repeatable evidence and/or verifiable facts).
The practitioners of astronomy or astrology had been practiced their trade or craft until 16th century by relying on the 2300-year-old theory “the Earth is static at the centre” (and concepts or observations derived from the theory). Mankind falsely concluded that “the Earth is static at the centre” is self-evident fact, so no one bothered to support this unproven theory by finding a falsifiable proof.
Since there was no falsifiable proof for such core first-principles in the foundation, it was impossible to challenge the huge BoK (Body of the Knowledge) acquired and accumulated for 1800 years for creating the dominant paradigm until 16th century by relying on such core first-principles. The scientific community in dark ages used illegal circular logic to defend the core first-principles.
For example, they used the observable facts such as epicycles, non-uniform speeds of planets, lack of stellar parallax and retrograde motions to defend the presumption “the Earth is static at the centre”. Countless concepts, observations and other derived theories in the whole BoK that had been accumulated for 1800 years can be used to defend the belief “the Earth is at the centre”.
The scientific method, protocols and processes for discourse has been created and perfected to prevent this. The biggest problem to subvert a flawed dominant paradigm is overcoming the illegal circular logic, which rely on the huge BoK acquired and accumulated for the paradigm. This kind of thing can be prevented by having falsifiable proof for the core first-principles at the foundation of any dominant paradigm.
When there is a falsifiable proof and if the theory is flawed, it is straight forward to falsify the proof by finding one or more verifiable and/or repeatable counterevidence. This is the reason the scientific method is created, which requires that each theory must be supported by a falsifiable proof.
Unfortunately, today software researchers and experts using the huge BoK in the textbooks and published literature that has been acquired and accumulated for past 50 years by relying on untested and unproven core first-principles in the pre-paradigmatic foundation such as about so called components for software and computer science is a branch of mathematics etc.
About 80% of the accumulated knowledge we have in textbooks and other published literature about the components for software is untested, unchallenged and invalid. Having invalid knowledge makes anything enigmatic, mysterious or paradoxical. Anything would become more and more enigmatic, mysterious or paradoxical, if it acquires and accumulates more and more knowledge and if larger and larger percent of the knowledge accumulated is invalid.
Every piece of scientific knowledge for any physical thing in the textbook must be well tested, challenged, and musty be supported by falsifiable proof backed by empirical evidence that must be open for challenge. Scientists of computer science must be ashamed of them-selves, if they feel offended by counter evidence or facts to expose untested or unproven knowledge about the enigmatic components.
Isn’t it pathetic, if the NSF (National Fake Science Foundation) don’t know or can’t understand basic scientific principles, processes and basic code of conduct? I oppose passing “The Endless Frontiers Act (S. 3832)” to fund the Fake Science foundation, until fake scientists at NSF understand basic scientific principles and processes and strictly implement the code of conduct for upholding the truth.
I wish to file a court case to block the act (i.e. The Endless Frontiers Act) to prevent tens of billions of dollars flush down the drain by the fake scientists at CISE, since nearly 50% of the US$100 billion goes to the CISE of Fake Science Foundation.
Best Regards,
Raju Chiluvuri
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Dear Raju Thank you very much for sharing your thoughts.
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One of important aspects of a researcher career is searching for funding of his/her scientific projects. What kinds of projects in computer science are likely to be supported? What are the most important aspects in a project proposal? What are the best opportunities for a young scientist?
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Hi,
I have been through some discussion regarding survey paper writing tips and tricks. However, these are very generic. I want to know how to write a survey paper related to computer science topics (e.g., blockchain,.internet of things, so on). I have some following queries regarding the aforementioned concerns.
  • How to design the flow of the survey paper?
  • What will be the minimum length of the survey paper?
  • How to pick up a reference paper and which criteria should be the first concern while selecting it? What is the minimum number of references that should I pick?
  • Is it necessary to propose an idea in the paper? If yes then is it necessary to show a performance evaluation of the proposed scheme?
  • While writing a survey paper which things should I focus on or care about?
Please share your experience regarding this.
Thanks for your time and input.
Thanks in advance.
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Importance and significance of the topic.
Discuss the background and target audience.
Summarize the surveyed research area and explain why the surveyed area has been studied.
Summarize the classification scheme you used to do the survey.
Summarize the surveyed techniques with the above classification scheme.
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Hello,
I would appreciate it if you could suggest me studies based on natural language processing (NLP) to help assisting medical emergency cases.
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I have been working in the field of domain specific artificial intelligence and domain specific synthetic languages for several years. This is a very important question. I discussed this subject with a colleague just yesterday. A few notes from our discussion follows.
There are some jobs where a person’s eyes and hands must be free to perform their work, yet they must be able to communicate with other people and computer systems that help them perform that work. In some of these jobs, safety is most important.
Although systems like Alexa and Siri are already in wide use, they do not today provide the degree of reliability and safety that would be required for use in an emergency room or neonatal ICU.
In such cases, it would be prudent to a create a task specific synthetic language designed for communication between humans and computer systems while humans perform their work, and computers answers questions, provide information, control task specific equipment, and other functions, thereby enabling a person to perform their work with their hands and eyes free to focus on the task at hand.
In short summary this would require implementation of computer systems that are able to:
· reliably hear and process spoken words
· translate spoken words into human and machine-readable form (text)
· verify that the spoken words, in human and machine-readable, form comply with the specification (grammar) of the synthetic language
· determine what question or command has been voiced by the human,
· invoke the procedure that will answer the question, provide requested information, or perform the command using task specific equipment.
· reply in some audible or visible form if the spoken words were not recognized or if the spoken words in human and machine-readable form do not comply with the specification of the synthetic language, or if they are used in the wrong context.
For added safety, before such capability is put into use, it would be necessary to generate many requests and commands both correct and incorrect in their formation to verify that both correct and incorrect commands can be successfully categorized as such.
For added safety, before such capability is put into use, it would be necessary to generate many requests and commands and to verify that the correct procedures are invoked, and through simulation, verify that the procedures safely perform the intended action.
Simply stated, a synthetic language is a set of words and set of rules for how to create requests or commands using the words of that language that can be spoken by a human, recognized by a computer, properly interpreted by a computer, and safely translated into the intended actions.
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Hello,
My research work focuses on the use of NLP and voice recognition for the medical emergency assistance.
So I would appreciate it if you suggest me some contributions that could be done in this area.
Best regards,
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Dear Artem Kramov , thank you so much for your valuable reply, I'll take your suggestions into consideration.
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I'm currently working on my undergraduate thesis where I develop a genetic algorithm that finds suboptimal 2D positions for a set of buildings. The solution representation is a vector of real numbers where every three elements represents the position and angle of one building. In that every three elements, the first element represents the x position, the second represents the y position, and the third represents the angle. A typical solution representation would look like:
[ building 0 x position, building 0 y position, building 0 angle, building 1 x position, ... ]
I have already managed to create a genetic algorithm that produces suboptimal solutions and it uses uniform crossover and discards infeasible solutions. However, it is only fast for small problems (e.g. 4 buildings), and adding more buildings makes it too slow to the point that I think it devolves into brute force, which is definitely not what we want. I tried to keep infeasible solutions into the population but with a poorer fitness before, but that only results in best solutions that is worse than when I threw away the infeasible ones.
Now, I am looking for a crossover operator that can help me speed up the genetic algorithm and allow it to scale to more buildings. I have already experimented arithmetic crossover and box crossover but to no avail. So, I am hoping that the community can suggest crossovers that I could try. I would also appreciate any suggestions to improve my genetic algorithm (and not just for the crossover operator).
Thanks!
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Hi,
Since your representation is in R^d, I strongly advice you to look into Evolution Strategies (ES) instead of GAs.
ES are evolutionary algorithms that are naturally suited to evolve real-valued solutions and are state-of-the-art. They operate by updating a distribution and sampling new real-valued solutions from it.
The most famous approach is Hansen's CMA-ES:
A modern approach that can operate very efficiently if linkage structure is known (e.g., what variables should be sampled at the same time) is Bouter's RV-GOMEA:
If your problem has many local minima and you want to explore them, you can look into Maree's Hill valley clustering-based ES:
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Dear colleagues,
I am working on an intervention study with 3 different groups of students. One group represents the intervention group and consists of a seminar with a practical phase and computer science content. Another group has only a theory seminar with computer science content and the last group has a seminar with other content. The last group is used to check how stable the constructs are. The 3 measurement points are equally spaced as pre-inter-post-tests in a quasi-experimental setting. Latent growth curve modelling doesn´t fit! Is there a method that uses the strength of the 3 measurement time points with a small sample size?
Thank you
Martin
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I would use a repeated measures ANOVA for Between x Within subjects designs.
In attachment a script using R for such a design, with Post Hoc tests. In the example there are 5 observations in each Condition.
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recently i prepared a research work for publication in IJCSSE. The site has been shut for weeks now. I feel the journal could be predatory .
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This ‘journal’ “International Journal of Computer Science and Software Engineering (IJCSSE)” is published by “Dorma Trading” and this publisher is, as indicated by others, mentioned in the Beall’s list: https://beallslist.net/ as a stand-alone journal (while it strictly speaking is not since there is a ‘publisher’ behind it) it is included as well: https://beallslist.net/standalone-journals/
Other red flags are:
-As said by Peter Breuer the way too short acceptance and publication time (10 days is impossible for serious peer review, paper editing etc.).
-As indicated by Ah M Kamal numerous pointless databases/indexing services are mentioned. Do realize that Citefactor, DRJI, Global Impact factor (GIF) etc. are notorious examples of misleading metrics often used by predatory journals/publishers: https://beallslist.net/misleading-metrics/
-DOAJ claim is false, etc. etc.
So, for sure this is a predatory journal and the conclusion is: avoid.
Best regards.
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anyone suggest what are the merits and demerits of GAN and classical data augmentation in plant leaf disease detection and classification systems
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interested
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What are the links in their definitions? How do you interconnect them? What are their similarities or differences? ...
I would be grateful if you could reply by referring to valid scientific literature sources.
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AI is an objective, which can be achieved by utilizing ML techniques and Evolutionary Algorithms. Hierarchy wise, EAs come under ML techniques, while both these techniques come under the umbrella of AI. Hope this helps!
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Good morning everyone. As a part of my research work, I designed a network that extracts the leaf region from the real field images. when I search about performance evaluation metrics for the segmentation I found a lot of metrics. Here I provided the list
1. Similarity Index = 2*TP/(2*TP+FP+FN)
2. Correct detection Ratio = TP/TP+FN
3. Segmentation errors (OSE, USE, TSE)
4. Hausdorff Distance
5. Average Surface distance
6. Accuracy = (TP+TN)/(FN+FP+TP+TN);
7. Recall = TP/(TP+FN);
8. Precision = TP/(TP+FP);
9. Fmeasure = 2*TP/(2*TP+FP+FN);
10. MCC = (TP*TN-FP*FN)/sqrt((TP+FP)*(TP+FN)*(TN+FP)*(TN+FN));
11. Dice = 2*TP/(2*TP+FP+FN);
12. Jaccard = Dice/(2-Dice);
13. Specitivity = TN/(TN+FP);
14. Sensitivity = TP/(TP+FN);
suggest to me which performance evaluation metrics are best suited for my work. thank you.
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Apparently, the largest technology companies are already working on a new type of electronic gadgets, which in the next stage of the current technological revolution, known as Industry 4.0, will replace smartphones.
Therefore, I am asking you: What type of electronic gadget will replace smartphones in the future?
Please reply.
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Voicebots, I guess.
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I am currently writing a proposal for my computational social science thesis, I need help to focus on the sentiment analysis of how each sentiment change over time in a social science field. The current research question I have in mind is: how do the sentiments of English tweets regarding COVID-19 as a threat evolve over the year 2020? However, it does not seem to link with social scientific topics but rather a computer science project. I got my research idea based on this paper Any advice is much appreciated!
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The idea is good. Check if there is some already data set available for this problem. And then work on that data. Visualise the data and check if u get any idea from that. It is basically an NLP problem.
Check if this link might help you.
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Dear Colleague,
The University of Dayton’s Department of Computer Science invites applications for multiple tenure-track Assistant Professor positions beginning on August 16, 2021.
The Department seeks experts committed to excellence in undergraduate and graduate education who also have a focus on research. The individuals holding these positions are expected to teach undergraduate and graduate courses, pursue an externally funded research program, advise and mentor students, and engage in service to the university and the community. Applicants must have completed all course work needed for a Ph.D. in Computer Science or equivalent related field, the potential for quality teaching and scholarly research, and articulate a commitment to excellence in undergraduate and graduate education with a focus on research.  
The Department of Computer Science offers a stimulating academic environment with active research programs in growing areas of computer science. Recently, the Department has relocated to a brand new state-of-the-art facility with numerous cutting-edge research labs and classrooms, and a commitment to further expand and grow the faculty and student opportunities. The department offers Bachelor’s, Master’s, and Ph.D.  degrees in Computer Science, and also a certificate in Autonomous Systems and Data Science.
View the complete job description, information about the University, and application instructions here: https://sciences.academickeys.com/job/zlja1rkx/
Warm regards,
Valerie Woodruff Academic Keys
--  - Valerie Woodruff    Ph. +1.203.693.1101
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Thank you for spreading the news.
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Hi Everybody
I am a phd student, working currently in detecting miRNA target based on the many-to-many relation between miRNAs and targets .I have created miRNA-Target modules .
I have used Guided Clustering technique to achieve my goals.
My background is Computer Science and I need to interpret my results, any Volunteers?
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Thank you very much. Dr Muhammad.That was really useful :)
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At the Computer Science Department at the beginning of the first semester there are p freshmen (study) groups: group i contains ni students, for all i = 1, p. For the second semester the Department wants to reorganize these groups in such a way that:
(1) the new organizing schema has r groups;
(2) the new group j contains mj students, for any j = 1, r;
(3) any new group cannot contain more than c students which were classmates in a same old group from the former organizing schema (c ∈ NN∗ \ {1}).
We want to know if such a new organizing schema exists.
(a) Devise a network flow model for building (if possible) the new organizing schema.
(b) Prove a characterization of the existence of a solution to this problem in terms of maximum flow in the above network. (In the affirmative case provide a way of building the new schema: which old group will have to cede and how many students to which new group).
(c) What is the time complexity for deciding if a solution exists? (Discuss the time complexity for at least three algorithms.)
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2 Peter Breuer: as far, as I understand, there is a constraint on composition of newly organized groups, e.g. it is not possible to keep them unrearranged. Does your hydrologic analogy take it into account?
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If we have three different domain of data (e.g. security, AI and sport) and we did 3 different case study or experiments (1 for each domain) and we estimate the Precision, Recall and F-measure for each experiment. How we can estimate the overall Precision, Recall, F-measure for the model. Is use normal mean average is suitable or F1 or p-value? Which one is better?
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Mohamed Elhadad Than you for your answer
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Dear Friends and Colleagues from RG,
I wish You all the best in the New Year. I wish you a successful continuation and successes in scientific work, achieving interesting results of scientific research in the New Year 2019 and I also wish you good luck in your personal life, all the best.
In the New Year, I wish You success in personal and professional life, fulfillment of plans and dreams, including successes in scientific work, All Good.
In the ending year, we often ask ourselves:
Have we successfully implemented our research plans in the ending year? We usually answer this question that a lot has been achieved, that some of the plans a year ago have been realized, but not all goals have been achieved.
I wish You that the Next Year would be much better than the previous ones, that each of us would also achieve at least some of the planned most important goals to be achieved in personal, professional and scientific life.
I wish You dreams come true regarding the implementation of interesting research, I wish You fantastic results of research and effective development of scientific cooperation.
I wish You effective development of scientific cooperation, including international scientific cooperation, implementation of interesting research projects within international research teams and that the results of scientific research are appreciated, I wish You awards and prizes for achievements in scientific work.
I wish You many successes in scientific work, in didactic work and in other areas of your activity in the New Year, and I also wish you health, peace, problem solving, prosperity in your personal life, all the best.
Thank you very much.
Best wishes.
I wish you the best in New Year 2019.
Happy New Year 2020.
Dariusz Prokopowicz
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Dear Colleagues and Friends from RG,
Hello Dear Everyone,
In the New Year of 2021, I wish all researchers, scientists and users of the Research Gate portal fulfill their plans and dreams, success in their professional work and personal life, success in the field of research and publication of their results, all the best. I wish all my colleagues and friends from the Research Gate portal that the New Year 2021 will be better than the previous years, that the SARS-CoV-2 (Covid-19) coronavirus pandemic ends as soon as possible, that there is a quick return to "normal", to the pre-pandemic state . The year 2021 begins a new decade of many new challenges related to solving key problems of the development of civilization, solving problems resulting from the pandemic crisis, economic, social and climate crises, etc. Let us hope that the development of science, further scientific research, new technologies, the current fourth technological revolution will enable the solution of key problems of civilization development.
Happy New Year 2021
Best regards, Stay healthy!
Dariusz Prokopowicz
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Q3,Q4 will be okay. I need scopus publication without APC and fast published. The paper is from Computer science discipline.
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Domain please
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I am looking for a journal, related to Psychology and Computer Science. IF < 2.0. If anyone has published some related work, or know any journal. that would be nice.
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One more alternative is Human Factors (IF 3.17).
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Dear Friends,
I can bet that no one in the world today (particularly in the software industry) knows or has the right answers to two simple questions: (i) What a component is, and (ii) What is meant by CBE (Component-Based Engineering), in the reality and context of all other engineering disciplines such as mechanical, electronics, and aerospace engineering.
Learning the right answers to these two simple questions would have two huge benefits: (i) Inventing effective solutions for the notorious software crisis by eliminating infamous spaghetti code, and (ii) Proving Computer Science is a fake science (i.e. paradox), that opens the door to transforming Computer Science into a real science that can address not only problems that have stood unsolved for decades (e.g. human-like computer intelligence that can be achieved by gaining valid scientific knowledge about the functioning and anatomy of bio-neurons in bio-neural networks) but also problems of the future such as bio-cellular computing, which cannot be solved by fake scientists or practitioners of fake science.
If a problem requires acquiring valid scientific knowledge, it is impossible for fake scientists practicing fake science to acquire such valid scientific knowledge essential to solving the problem. To provide tangible proof, I invented effective solutions for the infamous software crisis by gaining and using valid scientific knowledge that can provide the right answers to these simple questions about components, where scientific knowledge implies knowledge that clearly falls under the realm of science and is acquired without violating the core principles and proven rules of the scientific method.
I have been requesting software researchers to find right answers to the simple questions for over a decade, and my request has been seen as heresy. Please see attached PDF.
Why does the software research community find it repugnant or heretical when requested to recognize the reality and truth objectively? I feel, any Scientist must be ashamed of himself if he feels such a request is repugnant or heretical and resort to snubbing and personal attacks.
Best Regards,
Raju Chiluvuri
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Dear Friends,
One of the hardest problems we all face (as a researcher or a scientist) is inability to make observations objectively, without any subconscious or subliminal prejudice or biases influenced by preconceived notion.
Let me try to explain by using as example. Both Galileo and Kepler were good friends and working to promote Heliocentric model. Galileo already conducted experiments about motion and have strong opinions about things.
Galileo was not able to comprehend non-uniform speeds of the planets and elliptical orbits. Galileo believed that the planets must be traveling at uniform speed and orbiting in circular orbits.
Kepler on the other hand, is not theoretical physicist conducting on motion, so ignored all such distractions to document observations objectively. For example, no bothered about mysterious acceleration and deceleration, when orbiting.
We all have pre-conceived notions and biases, and they skew our perception of reality away from the objective reality. It took me more than a decade to make such objective observations about the components.
I may not be perfect, but I hope I improved substantially. I used to find many large shortcoming more frequently few years back. But, now I am finding minor shortcoming rarely. I feel this is evidence, that I get close to objective reality.
Best Regards,
Raju
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Mac OS vs Linux vs Windows??
I personally use MacOS but would like to know what other people use for their research work, preferably researchers associated with Computation work. If possible do let me know the reason. This is just a survey.
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MS Windows OS
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-
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Mendeley
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I am using data augmentation and decaying learning rate after each epoch. If I don't use data augmentation but keeping callback, then my training accuracy reaches to 99.65% but not validation. Another scenario is, if I remove callback of learning rate decay but keeping data augmentation then training accuracy also improves and reaches 99% but not validation. Why is it stucking with current configuration (lr decay + Data Augmentation) ?
What could be the reason to have this problem with data augmentation?
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Still you're are not stating what algorithm you are using, that's the software
But anyway, what's the problem if you can successful train the model and the accuracy is that high?
Why are we interested in the values in the training step ?
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Dear All,
I have the data of metabolic pathways in case and control, well there are pathways which are represented several times due to the involvement of reactions in case, well now I would like to see if the no. of reactions in metabolic pathways in the case are significant when compared to no. of reactions in the control sample. I have attached an excel sheet to this message which includes pathway names and the no. of reactions in case and control. My next step is to perform fisher exact test using R and to identify false discovery rate in R. kindly let me know how this could be performed by using R programme
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Try this one:
FDR(pvals, qlevel = 0.05)
Arguments
pvals
a vector of pvals on which to conduct the multiple testing
qlevel
the proportion of false positives desired
Good luck-
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Hello,
My situation is a little strange because I am a Statistics PhD student but I ended up doing research in Natural Language Processing (NLP)/ Deep Learning due to my supervisor's recommendation.
I feel strange because although I can read the NLP paper, understand them, and come up with my own research topics (so far I have identified 3 different research topics), I am not a part of computer science department NLP lab. My supervisor into applying/developing machine learning algorithms for analyzing open-ended questions, so I guess his work is somewhat related to NLP, but he is not really an expert in NLP/Deep Learning. I do like my current supervisor, he is trying to help me out in the best way he can, and I want to continue work with him. But I am wondering,
- Is it advisable for me to seek a professor from computer science NLP lab to be my co-supervisor (upon my supervisor's consent)?
- What are the advantages of doing a NLP research in a big computer science NLP lab?
- Is collaboration important for a PhD student to do research in NLP? I see many PhD students who publishes at top NLP conferences are often co-authored with multiple number of collarborators. I am just doing NLP research with my supervisor, and my supervisor and I don't really have any connection with NLP researchers. Should I make an effort to find NLP researchers whom I can work with for my research (of course, I will be doing most of the work since I want to be the first author)?
- If I need to seek collaborator / co-supervisor who are familiar with the field of NLP, how should I approach them? can I try sending them emails and see if they are interested in my research? I guess the best way is to talk to people at a conference but due to COVID-19, everything is taking place online and I doubt whether I will be able to make any connections.
- Do PhD student from a big NLP lab have better computational resource than the PhD students who does NLP research outside of those labs? My supervisor recently set up an account for the national supercomputer so that I may take an advantage of it, but since almost every researchers in my country have access to this resource, when I submit the job on SLURM the queue wait time can be long. Are PhD students from computer science NLP lab often free of this problem? (do they have a access to better computational resource?)
...Lots of questions! Could someone advise me on these issues?
Thank you so much for your time,
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Python and R. Do coding and try by yourself, do not do theoretical study only from papers.
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Hi reader,
I'm conducting a research on digital literacy and its linkage to the digital economy in a developing country like Pakistan.
I'm looking for experts in the following areas: economics, literacy, primary acedemia, digital economy, entrepreneurship, digital literacy, computer science, computer engineering, IT, as well as other associated fields.
I would be really grateful if you could take some time out to fill my questionnaire survey.
This quetionnaire corresponds to my first area of focus: impact of digital literacy on the digital economy.
For context: the digital economy embodies all economic transactions that either require the use of digital technologies or are related to the selling & purchasing of digital goods & services.
For the scope of this study, digital literacy has been defined through some key competences as outlined by the UN in their Digital Literacy Global Framework. The purpose of this study is to determine whether there is a relationship between digital literacy and growth in the digital economy. Furthermore, this study aims to map the relationships o fthe competencies of digital literacy against the factors leading to growth in the digital economy.
For any queries and concerns, you may reach out to us via email at gem1974@giki.edu.pk
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Dunia sedang menghadapi masalah yang anda kemukakan. Apapun hasil riset anda akan sangat membantu banyak orang dalam mengatasi solusi bisnis mereka maupun problem pribadi
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Journal of Management in Engineering
American Society of Civil Engineers (ASCE)
Special Collection-Call for Papers 
Management of Resilience in Civil Infrastructure Systems: An Interdisciplinary Approach
Objective: The objective of this special issue is to document scholarly interdisciplinary contributions in the field of resilience, with a specific focus on the engineering managerial issues at the interface of the built environment with social and ecological systems. In particular, we look for interdisciplinary contributions to management of resilience in civil infrastructure systems from other engineering disciplines as well as disciplines such as management, sociology, ecology, political science, psychology, urban sciences, geography, and economics.
Submission information: Authors wishing to submit papers should contact the Guest Editors [Nader Naderpajouh (nnp@rmit.edu.au), Juyeong Choi (jchoi@eng.famu.fsu.edu), and David Yu (davidyu@purdue.edu)] to submit an extended abstract (maximum 800 words) summarizing a proposed submission. The guest editorial team are from the fields of civil and environmental engineering and social sciences, and are encouraging submissions from a range of disciplinary perspectives and using a wide range of quantitative and qualitative methods. The authors are specifically required to highlight the interdisciplinary links and contributions from other fields to the scholarly field of civil engineering. In order to be considered for the special issue, authors should submit extended abstracts by January 31, 2019. The Guest Editors will review submitted proposals upon their receipt and contact authors with invitations to submit full-length articles soon thereafter. Note that in case of earlier submission the review process will start immediately.
Guest Editors
Juyeong Choi, FAMU-FSU College of Engineering  (jchoi@eng.famu.fsu.edu)
David Yu, Purdue University (davidyu@purdue.edu)
Young Hoon Kwak, The George Washington University (kwak@gwu.edu)
Deadline for extended abstract: January 31, 2019
Links:
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And we also discussed the special collection concluding remarks here: https://ascelibrary.org/doi/10.1061/%28ASCE%29ME.1943-5479.0000871
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Please could you urgently assist in getting this article titled “Influence of time pressure on aircraft maintenance errors” by Kimura Akisato, T. V. Thaden, William D. Geibel Published 2008 by Computer Science
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I am not sure if any one study on this topic. It has been observed in certain cases that success-full researchers have poor academic record. These are exceptions, I am interested to know any study on this topic. Please also cite examples that shows negative or positive examples. Ideally there should be high positive correlation, if it is not than why?
I mean if person got good grade/marks or rank at school/university level will be a grate scientist. For example if topper of JEE (top exam in India for getting admission in engineering college) join research, he/she will be best scientist in the world.
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From my long experience of teaching, the researchers who have rich researching CV usually have poor teaching records and vice versa. That is especially true for the universities that haven't a sufficient researching budget. The reason behind that is that researching needs more time at the expense of teaching.
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I am starting my Masters Dissertation and my area of interest is on Fraud Detection in Banking Transactions using Machine Learning.
I am interested to see what others have done around this context so if you have an idea or a reference or just a comment that will give me a lead, will be much appreciated.
Frank Tilugulilwa
Masters in Computer Science - candidate (University of Dar es Salaam)
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https://pdf.sciencedirectassets.com/280203/1-s2.0-S1877050919X00046/1-s2.0-S1877050919300079/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEPf%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaCXVzLWVhc3QtMSJGMEQCIBockarKhYknfqr4FM3I%2FkoDhefu%2FCn0mGnR7%2FwKrA8bAiAWElEU8xHlI%2BXb4eRhyt3KVHwCJUcHXU9c2Bd04yi6Fyq0AwhwEAMaDDA1OTAwMzU0Njg2NSIMP7B5Bawohs6qwbptKpEDNhtX4YHVgpgOunX7B00FVpDE%2B1VC2awtSV4NUiRa7fajnnvEyHgzo2A%2BENKBVKB2%2Bv5r0Jt82sieOzocnzwLdQSNK4utsOIWBompyMI8aPcRdUizk5ODIge%2BAXrtKkP%2Bu4bxVFB0qi5CuXXvbSW4h%2FmOqdUNprjhvA4VOVNayZFYJvYivT90E2eQq7zqSrqYU28P8kR419KbfeLVAefMXONaheQ%2FAoZ4hXUmGJ%2B%2FXfeqUZycll%2FFjT4qLQnfzISNXyfMv7b41yR450gTLsPNvtIgb0QeRPvlbcCstLzNvwFJzAkB29RQr%2BhdUXTWcqSUqihECaoxGfVQ6Ku2rM%2BOwYzL%2BWkvaXTmbhcgTZugeLf3zzOdW3c2jO4GkR4lBXCKdSnn9%2FqlB68TJn5hrFvQDsnSKx6eiTk4zI8iixNLkQyfR8NDDmz3qhoCJXSrG04sauASuTG5epR9MT9FLEYP%2FaT9ZQrkQx%2F27Ew5bPrLVoOKHKlWA%2BM6Wn9g2yGZEpCV9unXAxagT4FXuKst40EEO3sw6NTd%2FQU67AEJdd%2Fp4iaEQKMmEhAwewfRWwi2bEe8jfFZq7wGR89Q3LCh7euIKCDemAPa0gbePSdAGPWLtBbdhsMSV49JYDmbnkzyvo41TX%2BIHvTK1mPmFwHwJvXeat4i3qs2urhuLXtNS5RyE5TijvFFKZSjMqSKAZpUz%2BggyeTZUQGmREg3kvYACztP04ipMNPUoXzFLmWyv8d2Nf0WdRrrwKveKfpbNfekVwPQ36LFOJvp6H%2BgY78F9NWcHRxMDEZb2E9ts5aXbL2NsuZFSo4%2FmC9J5%2FCyDY2%2FjpQ8Ypp29Jzm05R8T75Gqn82dH6uFSrNwA%3D%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20201120T082508Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTY5TP66NU7%2F20201120%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=57b21d5881b499aaa60c61ff23e7802904d289e82757c78a0bbd449dc9583c87&hash=be8e6f9b84c277d0400847771ba9a075995b6ebf0fa4ea2e6a3654c71148d9a9&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S1877050919300079&tid=spdf-705892e6-e3c1-4a27-a5c1-697d0d4df056&sid=1efa36836f2fd943228bfe67c67cb01ee17fgxrqb&type=client
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Dear all,
I hope this question finds you in good health & spirit!
This is a repeated question but in a different way.
How can I add a research paper to Google Scholar? I have the following three papers, all of them have been added manually to the "Research Scholar":
Nidhal El-Omari, “Sea Lion Optimization Algorithm for Solving the Maximum Flow Problem”, International Journal of Computer Science and Network Security (IJCSNS), e-ISSN: 1738-7906, DOI: 10.22937/IJCSNS.2020.20.08.5, 20(8):30-68, 2020.
Nidhal El-Omari, “An Efficient Two-level Dictionary-based Technique for Segmentation and Compression Compound Images”, Modern Applied Science, The Canadian Center of Science and Education, published by Canadian Center of Science and Education, Canada, p-ISSN:1913-1844, e-ISSN:1913-1852, DOI:10.5539/mas.v14n4p52, 14(4):52-89, 2020.
Nidhal El-Omari, M. H. Alzaghal, and Sameh Ghwanmeh, “ICT and Emergency Volunteering in Jordan: Current and Future Trends”, Computer Science and Information Technology, published by Horizon Research Publishing Corporation (HRPUB), p-ISSN:2331-6063, e-ISSN:2331-6071, DOI: 10.13189/csit.2015.030402, 3(4):105-112, 2015.
But, I couldn't find any one of them when I search for the usual way. To be sure, you can see the three attached snapshots.
Thank you!
Regards,
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I appreciate your valuable assistance. But, I have already added my research articles manually before putting this question on this portal. My question is related to another different situation. I want to see my papers when I make searching as in the attached snapshots with the original question; please make another glance at them. Anyway, the problems of the first and second papers have solved after I have uploaded them on the "www.academia.edu" using the following link:
Until this moment, the problem of the third paper, namely "ICT and Emergency Volunteering in Jordan: Current and Future Trends", hasn't been solved despite that it has been loaded on the "academia" and other sites. Thanks again for your great assistance.
Finally, I want to introduce my gratitude, thankfulness, and acknowledgment to Dr. Roman Anufriev, Dr. Mohammed O. Al-Amr, Prof. Vadym Slyusar, and all the other respected researchers for their contributions, attentions, and participations.
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Isn’t that grateful that everyone knows how to make a phone, know what are capacitors and transistors used in computers. Maybe China is ahead of all because they can make one at home despite availability of all materials at cheaper cost.
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Dear bhavesh
It looks interesting. But practically it may be feasible. Technology has not yet become that much user friendly. Also many other constraints are there.
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Good Morning All,
I am pursuing phd in computer science. I am thankful to all the people who are guiding me whenever I have been stuck. I have got a list of parameters or features related to my topic, but now I am confused how to select the feature from that list? How to represent this feature during our RDC presentation? Do we need to only list out the attributes or do we need to give data in detail for those attributes?
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Hi Shah,
In terms of how you can select an appropriate subset of features, there are a number of algorithms that can be applied such as the “Sequential Feature Selection”. The Sequential Feature Selection algorithm has been implemented in Python and Matlab, and it is one of the commonly used methods for obtaining a subset of highly informative features from the entire feature space/vector.
I hope you would find this helpful.
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Hello Friends,
I am a master's student at the University of Baghdad, Department of Computer Science in the second stage, and the topic of my research in mobile and network computing about tracking, movement and mobility via mobile phone. So, I need a spatiotemporal data about the participants that give temporal and spatial indicators with the type of activity?
Any one can inform me where can I get it?
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Dear Khalid,
For your understanding, I have attached two YouTube links how to track and plot the real-time spatiotemporal data. After tracking data you have to take the data into your pc or laptop and get a tracking map with elevation and location ( Lat & Long). Please See this link. Hopefully your requirements may fulfill through this videos.
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I need help understanding how to use the Java Netbeans IDE for writing and compiling programmes
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Dear A : If you still need any help in Java or/and Netbeans, I have long experience in using them.
This is my email: nidhal.omari@wise.edu.jo
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Dear Friends,
Kindly allow me to ask you a very basic important question. What is the basic difference between (i) scientific disciplines (e.g. physics, chemistry, botany or zoology etc.) and (ii) disciplines for branches of mathematics (e.g. caliculus, trigonometry, algebra and geometry etc.)?
I feel, that objective knowledge of basic or primary difference between science and math is useful to impart perfect and objective knowledge for science, and math (and their role in technological inventions & expansion)?
Let me give my answer to start this debate:
Each branch of Mathematics invents and uses complementary, harmonious and/or interdepend set of valid axioms as core first-principles in foundation for evolving and/or expanding internally consistent paradigm for each of its branches (e.g. calculous, algebra, or geometry etc.). If the foundation comprises of few inharmonious or invalid axioms in any branch, such invalid axioms create internal inconsistences in the discipline (i.e. branch of math). Internal consistency can be restored by fine tuning of inharmonious axioms or by inventing new valid axioms for replacing invalid axioms.
Each of the Scientific disciplines must discover new falsifiable basic facts and prove the new falsifiable scientific facts and use such proven scientific facts as first-principles in its foundation, where a scientific fact implies a falsifiable discovery that cannot be falsified by vigorous efforts to disprove the fact. We know what happened when one of the first principles (i.e. the Earth is static at the centre) was flawed.
Example for basic proven scientific facts include, the Sun is at the centre, Newton’s 3 laws or motion, there exists a force of attraction between any two bodies having mass, the force of attraction decreases if the distance between the bodies increase, and increasing the mass of the bodies increases the force of attraction. Notices that I intentionally didn’t mention directly and/or indirectly proportional.
This kind of first principles provide foundation for expanding the BoK (Body of Knowledge) for each of the disciplines. The purpose of research in any discipline is adding more and more new first-principles and also adding more and more theoretical knowledge (by relying on the first-principles) such as new theories, concepts, methods and other facts for expanding the BoK for the prevailing paradigm of the discipline.
I want to find answer to this question, because software researchers insist that computer science is a branch of mathematics, so they have been insisting that it is okay to blatantly violating scientific principles for acquiring scientific knowledge (i.e. knowledge that falls under the realm of science) that is essential for addressing technological problems for software such as software crisis and human like computer intelligence.
If researchers of computer science insist that it is a branch of mathematics, I wanted to propose a compromise: The nature and properties of components for software and anatomy of CBE (Component-based engineering) for software were defined as Axioms. Since the axioms are invalid, it resulted in internally inconsistent paradigm for software engineering. I invented new set of valid axioms by gaining valid scientific knowledge about components and CBE without violating scientific principles.
Even maths requires finding, testing, and replacing invalid Axioms. I hope this compromise satisfy computer science scientists, who insist that software is a branch of maths? It appears that software or computer science is a strange new kind of hybrid between science and maths, which I want to understand more (e.g. may be useful for solving other problems such as human-like artificial intelligence).
Best Regards,
Raju Chiluvuri
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Dear @Raju Chiluvuri
To my opinion, mathematics is the precursor to all the disciplines of science. And, in fact, mathematics is also a science.
Thanks!
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I know this question is clear but I want to know the difference between these facts especially in computer science?
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Dear Dr. Albahri:
My four-cent is as follows:
Model in computer science is the result of a process of representing a real-world object or phenomenon as a set of logical, mathematical and computational concepts and equations. Contemporary scientific practice employs at least three major categories of models: concrete models, mathematical models, and computational models. Simulation of a system is the operation of a model in terms of time or space, which helps analyze the performance of an existing or a proposed system.
Architecture in computer science is logical/functional/structural arrangement as well as a set of rules and methods that describe the functionality, organization, and implementation of an architected system. Some definitions of architecture define it as describing the capabilities and programming model of a computer but not a particular implementation. In a pragmatic view, it is the conceptual structure around which a given system is designed.
Framework in computer science is an abstraction in which a system providing generic functionality can be selectively changed by additional, purposely developed constituents, thus providing application-specific features and services. In a pragmatic view, a framework (a software, a system, or an environment) is a platform for developing specific applications.
Protocol in computer science is a standardized set of rules (of types, commands, constraints, acknowledgement) for preparation, processing, and communicating something (e.g. data, instruction, etc.). Protocols enable computers to be networked with one another and transfer (like OSI). Protocols are typically constructed by following reductionist principles.
Best regards, I.H.
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Is there a freely available test dataset of research papers in computer science field? I need to evaluate my text retrieval system which uses a computer science domain ontology, so the dataset should come with a ground truth/relevance judgments for text retrieval task and/or classification task.
I appreciate any suggestion. Thanks
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Yes and too many, see e.g., free publicly available databases : https://www.visualdata.io/discovery and https://www.robots.ox.ac.uk/~vgg/data/
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I need a very good text book which is self explanatory and easy to understand for self study by a beginner in JAVA PROGRAMMING
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Just I want to add to
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Since technology has seemed to extensively pervade virtually every facet of medicine, do you feel that students of medicine (MD or MBBS) should be better equipped with knowledge and skills in mathematics, physics, biomedical image processing (to better process medical images for diagnostics and surgical planning), biomedical signal processing (for better analysis of bioelectrical signals, e.g. EEG, EKG, EMG), and basic computer science?
Care to discuss?
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Myles Joshua Toledo Tan dear, I don't think medical students need to study math or physics as they already has to acquire a good basics on them to qualify for the admission test. In MBBS level they have to cover a vast and extensive curriculum. If you want to add something to them you can add--English language, Behavioral science and Psychology.
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I want to check whether the ( Journal of Advances in Mathematics and Computer Science ISSN: 2456-9968 ) is a fake one or not? I could not find it in the Clarivate Analytics list.
Thanks for ur help!
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Hi,
The website of this journal does not specify its publisher, and the indexing is in remote Chinese database, so , I am not sure it is fake, but I would be very cautious about sending papers to this journal. This journal charges APC, so, be cautious.
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cloud computing security
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Dear respected researchers:
Kindly, you can click the link below to find a complete, new, and full answer:
Or refer to this:
Nidhal Kamel Taha El-Omari, “Cloud IoT as a Crucial Enabler: a Survey and Taxonomy”, Modern Applied Science, The Canadian Center of Science and Education, published by Canadian Center of Science and Education, Canada, p-ISSN: 1913-1844, e-ISSN: 1913-1852, DOI:10.5539/mas.v13n8p86, 13(8):86-149, 2019.
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Rodgers’ evolutionary concept analysis is being used in Nursing field. I could not find any paper that prove that Rodgers’ evolutionary concept analysis has been used in any other fields other than Nursing.
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A method for developing knowledge in nursing science. A brief description of the evolutionary process, from data collection to data analysis, with the concepts' context, surrogate and related terms, antecedents, attributes, examples and consequences, is presented.
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Is there really a significant difference between the performance of the different meta-heuristics other than "ϵ"?!!! I mean, at the moment we have many different meta-heuristics and the set expands. Every while you hear about a new meta-heuristic that outperforms the other methods, on a specific problem instance, with ϵ. Most of these algorithms share the same idea: randomness with memory or selection or name it to learn from previous steps. You see in MIC, CEC, SigEvo many repetitions on new meta-heuristiics. does it make sense to stuck here? now the same repeats with hyper-heuristics and .....   
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Apart from the foregoing mentioned discussion, all metaheuristic optimization approaches are alike on average in terms of their performance. The extensive research studies in this field show that an algorithm may be the topmost choice for some norms of problems, but at the same, it may become to be the inferior selection for other types of problems. On the other hand, since most real-world optimization problems have different needs and requirements that vary from industry to industry, there is no universal algorithm or approach that can be applied to every circumstance, and, therefore, it becomes a challenge to pick up the right algorithm that sufficiently suits these essentials.
A discussion of this issue is at section two of the following reference:
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What kind of technique is used for systems of IoT?
What are the challenges for testing IoT?
Do we need to modify traditional testing technique for IoT?
I really appreciate if anyone discuss or refer some papers.
Thank you
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Why most researchers are shifting from tensorFlow to Pytorch?
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Tensorflow creates static graphs, PyTorch creates dynamic graphs.
In Tensorflow, you have to define the entire computational graph of the model and then run your ML model. In PyTorch, you can define/manipulate/adapt your graph as you work. This is particularly helpful while using variable length inputs in RNNs.
Tensorflow has a steep learning curve. Building ML models in PyTorch feels more intuitive. PyTorch is a relatively new framework as compared to Tensorflow. So, in terms of resources, you will find much more content about Tensorflow than PyTorch. This I think will change soon.
Tensorflow is currently better for production models and scalability. It was built to be production ready. PyTorch is easier to learn and work with and, is better for some projects and building rapid prototypes.
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I wanted to get a scatter plot but the constraint is to plot these points over an image with same dimension as the range of points. Is is possible? If yes which library is good to start with? I tried using gnuplot but it is causing problems. For now I have a code which was stated here but didn't work. I tried using a bitmap image with the points to be plotted in data1.dat file and used the gnuplot script which is stated in the link
set terminal pngcairo transparent
set output 'Figure1.bmp'
plot "Co_ordinates0.dat"
set output
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To do this using matplotlib in python:
import matplotlib.pyplot as plt
import cv2
fig, ax = plt.subplots()
img = cv2.imread(<filepath>)
ax.imshow(img)
ax.scatter(e.xdata, e.ydata, label=str(counter))
This is working for me. The patches library also works for the purpose of more extensive visualizations.
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To apply graph theory concepts in computer science and engineering.
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As continue of Juho Andelmin answer I can identify next areas of applications of graph theory and her components: Natural Language Processing (NLP), routing networks, Big Data and Data Science, Hypergraph semi-supervised learning etc.
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When Einstein published 4 great papers in one year, it was something very special. Now this is not the case,
there are many professors who publish papers every week even if they don't do any work in this papers. What is the reason to write a professor name in your paper from your perspective?
How can a young professor reach that in the beginning of academic career path?
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Dear all,
I think that the main reason is that the universities give money to the professors for any research article.
Thank you!
Regards,
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Which Q1 and Q2 research journal of computer science and cybersecurity area journal are most suitable for speedy review and publication process preferably not the paid journal?
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As the above suggested, Artificial Intelligence Review if you don't have money its take between 120 to 140 days for the first decision, but if you can pay, IEEE Access is faster it takes around 3 weeks only for the first decision then if you accepted you need to pay 1750 $ US
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I found so many papers aplying the Deep Deterministic Policy Gradient (DDPG) algorithm implementing a critic neural network (NN) architecture where the action vector skips the first layer. That is, the state vector is connected to the first layer, but the actions are connected directly to the second layer of the critic NN.
Actually, in the original DDPG paper ("CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING", Lillicrap 2016) they do that. But they do not explain why.
So... why is this? Which are the advantages of this architecture?
Thanks in advance.
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Look the link, maybe useful.
Regards,
Shafagat
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Can we affirm that whenever one has a prediction algorithm, one can also get a correspondingly good compression algorithm for data one already have, and vice versa?
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There is some correlation between compression and perdition. Prediction is a tool of compression. Assume you have data and you you have redundancy in it you can predict the redundancy from the context of the signal and remove the redundancy by simply subtracting the the predicted signal from the real signal.
The difference will be the compressed signal.
The prediction is a powerful concept to reduce the redundancy in the signals and consequently compress it.
prediction is used intensively in video codecs and other signal codecs.
Best wishes
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This Special Issue will focus on control, modeling, various machine learning techniques, fault diagnosis, and fault-tolerant control for systems. Papers specifically addressing the theoretical, experimental, practical, and technological aspects of modeling, control, fault diagnosis, and fault-tolerant control of various systems and extending concepts and methodologies from classical techniques to hybrid methods will be highly suitable for this Special Issue.
Potential themes include, but are not limited to:
Modeling and identification
Adaptive and hybrid control
Adaptive and hybrid observers
Reinforcement learning for control
Data-driven control
Fault diagnosis
Fault-tolerant control of systems based on various control and learning techniques
Prof. Dr. Jong-Myon Kim
Prof. Dr. Hyeung-Sik Choi
Dr. Farzin Piltan
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Dear Farzin,
Nice sharing. Thank you.
Ashish
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There are many subjects covered in Computer Science studies. we should do the discussion on Which subject is most important in Computer Science? and why?
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I think it slightly depends on what specialty one is going to consider in computer science. However, for any specialty data structures and algorithms is absolutely crucial, it is almost an axiom that this subject is the basis of computer science. Another important subject, in my opinion, is computer systems and organisation, because it provides the basic knowledge of how computers actually work at the lowest level (i.e. the interface between software and hardware). Additionally, something that is not obligatory but I think is very important, is discrete mathematics in computer science as it provides the mathematical foundation of computer science using logic, principles of computing, proofs etc.
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Hello Researchers, I would like to know some Q1 paid journals with fast publication in the field of computer science major?
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IEEE Access and CMC.
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I am currently enrolled in bachelors computer science program and i have chosen my final year project in "securing supply chain using block chain" i am currently searching different research works in this field any help would be appreciated
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Jan H Jansen currently i am learning solidity on etherium
how can i ger into your‘e community that’s working on the project
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Dear Friends,
How could any proof for disruptive discovery or theory could see the light of day (or error in our knowledge can be exposed), if no one is willing to investigate evidence that can prove the disruptive discovery or theory?
For example, how is it possible to expose flawed basic beliefs (e.g. such as the Earth is static at the center), if no one is willing to look at evidence that can expose such basic errors? If anyone try to expose such error, often many scientists or researchers resort to personal attacks or humiliating insults to suppress open honest debate.
The basic moral and ethical obligation or sacred duty of every scientist is pursuit of absolute Truth directly or indirectly, where indirectly also includes moral and ethical obligation to validation of sacred tenets for upholding Truth. Refusal to investigate conclusive evidence that can prove a new discovery of fact is tantamount to promoting an error by suppressing the Truth. Suppressing truth (by any scientist) is a volition of scientific method and moral code of conduct (for anyone consider himself a scientist).
How any new discovery of fact, basic error in mankind’s knowledge or new theory could see the light of day, if each member of community of researchers or scientists evade their mandatory moral obligation of investigating evidence and facts that can prove the theory or expose a flawed belief? Any real discovery only shines under rigorous validation or scrutiny by brilliant critics or opponents.
No researcher or scientist should ever ask anyone to blindly believe his/her discovery or theory. Every discovery or theory must be backed by falsifiable proof, evidence and reasoning. Falsifiable doesn’t imply that the discovery or theory is flawed, but it can be falsified, if it is flawed, for example, by finding a counter evidence or sound counter reasoning.
Scientific research is nothing but pursuit of absolute Truth (and upholding the Truth), which also includes getting closer and closer to the Truth by eliminating imperfections in our BoK (Body of Knowledge). The community of researchers and scientists are morally and ethically obligated to uphold the Truths, by investigating the evidence to determine the validity of the discovery or theory.
What would have happened, if everyone ignored or snubbed seminal theories or discoveries of a young 25-year-old low level clerk (named Einstein) at a patent office in Bern? Research community successfully suppressed disruptive discovery of Copernicus for hundred years, which eventually prevailed due to great sacrifices of researchers like Giordano Bruno and Galileo, which resulted in a scientific revolution.
Mankind would be still in the dark ages without their sacrifices to uphold the Truth. Disruptive or outside of box discoveries expose inconvenient Truths/facts, so face fierce resistance and hostilities.
Almost every disruptive or revolutionary discovery faces fierce resistance and opposition. If any scientist disagrees with a theory and proof backed by evidence, scientific process requires channeling the fierce resistance and opposition for falsifying the evidence and facts for invalidating proof. Only incompetent or ignorant people resort to personal insults. Any determined efforts to falsify proof for any discovery end up proving the discovery, if the discovery is Truth/fact. But it is unethical to suppress or snub the discovery to evade such mandatory moral obligation of investigating evidence by resorting to personal attacks or insults.
What would you do, if you stumbled onto a revolutionary discovery, and if no one in the scientific or research community is willing to investigate the evidence and facts, which can provide conclusive proof for the discovery by employing unethical evasive tactics such as personal attacks or humiliating snubs to suppressing facts?
What can you do, if research community ostracizes you (e.g. by resorting to personal attacks, humiliation and snubbing), when you politely request for an opportunity to present evidence that can provide conclusive proof for your theory or discovery?
Assume, you spent more than 12 years making sure that you are absolutely right by accumulating many proofs, where each proof is backed by more than enough evidence. If you are not very wealthy and powerful, you would be helpless (e.g. can do nothing), if research community refuses to look at your evidence that can prove your discovery.
What can you do, if you don’t have large financial resources to force the research community to investigate your evidence, for example, by dragging them to courts for abdicating their moral and ethical obligations (e.g. upholding the Truth) or for gross negligence, in case if researchers are being funded by taxpayer money and having mandatory obligation to find and promote such discoveries?
It is a laudable example that few great researchers took time to investigate disruptive discovery by a low-level young patent clerk. But in case of Galileo and others, research community blatantly abdicated their moral obligation and failed the mandate of scientific method or process for upholding the Truth. Most people claim to be a scientist doesn’t even know what is meant by being a scientist and what are the moral or ethical obligations and mandate of scientific method.
How can we advance mankind’s scientific knowledge into new unexplored frontiers, if research or scientific community abdicates their sacred duty – Pursuit of absolute Truth, flawless knowledge and wisdom? One must stop pretending to be a scientist, if he is not willing to fulfill moral or ethical obligations and mandate of scientific methods for pursuit flawless knowledge and/or upholding of the Truth.
Best Regards,
Raju Chiluvuri
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Thank You Mr. Ali for your kind wishes.
I could use a break from fake scientists.
The world is full of fake scientists (particularly computer science) without even having elementary knowledge of scientific method or philosophy of science, but pretending to be scientists.
Any scientific discipline end up in fake science phase, if its pre-paradigmatic foundation comprises of flawed core/seed principles: http://real-software-components.com/raju/ModifiedKuhnBlackHolePhase.pdf (Please see figure in page-1, and description for the figure inpage-2)
I have been struggling to expose a toxic fake science for many years without any success: https://www.researchgate.net/post/How_to_expose_a_toxic_fake_science_that_has_being_deceptively_promoted_as_a_scientific_discipline
You may find my other recent questions at: https://www.researchgate.net/profile/Raju_Chiluvuri4/questions
Best Regards,
Raju Chiluvuri
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I have found a beautiful technique to solve math problems such as:
  • Goldbach’s conjecture
  • Riemann hypothesis
The technique uses the notions of regular languages. The complexity class that contains all the regular languages is REG. Moreover, these mathematical proofs are based on if some unary language belongs to NSPACE(S(log n)), then the binary version of that language belongs to NSPACE(S(n)) and vice versa. The complexity class NSPACE(f(n)) is the set of decision problems that can be solved by a nondeterministic Turing machine M, using space f(n), where n is the length of the input.
We prove there are non-regular languages that define mathematical problems. Indeed, if those math problems are not true, then they have a finite or infinite number of counterexamples (the complement languages contain the counterexample elements). However, we know every finite language is regular. Therefore, those languages are true or they have an infinite number of counterexamples, because if they have a finite number of counterexamples, then the complement language should be in REG, that is, this complement must be a regular language. Indeed, we show some mathematical problems cannot have a finite number of counterexamples using the complexity result, that is, we demonstrate their complement languages cannot be regular. In this way, we prove these problems should be true or they have an infinite number of counterexamples as the remaining only option.
See more in my notions:
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I have to find out what software and operating systems are used in education. More into lower education than in high and in different countries (USA, Australia, Great Britain, Germany, France, Scandinavia, Romania, Hungary, the Czech Republic, and other mostly European countries). Do you have some idea where can I find such statistical data?
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To all who teach math subjects, I will recommend to use GeoGebra: leading provider of dynamic mathematics software, supporting STEM education and innovations in teaching and learning worldwide. It is an open source multiplatform software, available in many languages for Windows, Linux, Mac OS, Android, iPad and it has an easy-to-use interface.
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Hi Everyone. Please suggest me the SCI journals list which don't contains article processing charges.
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Dear Srinivas Talasila, you can check here to find out your desired SCI Journal without APC: https://www.letpub.com/index.php?page=journalapp
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We want to have 5'000 to 10,000 words from several technical languages judged according to emotional criteria (valence, arousal, imaginability). Computer science often uses a few raters (2-5). In other disciplines ten or more raters are used (e.g. psychology, linguistics).
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For a technical language, the emotional factor should be...close to zero. The emotion is, for one word, the relation between form (written or spoken) and effect over a human-subject. Technical language is tailored exclusively on a non-emotional factor, but on a scientific embodiment of data. Therefore, ideally, the emotional factor shouldn't interfere at all.
However, if you really want to extract this information, I would rely more on a human evaluation. 10,000 words means more or less @30-33 pages which is not too much of reading after all...I think.
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