Science topics: Computer Science
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Questions related to Computer Science
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I am currently writing thesis for my undergraduate where i need to design a machine learning model to estimate the soil data between 2 borehole based on the bore log data. Sorry in advance if i have terminology mistake as I am a computer science student.
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Two boreholes is not that much data. You could do this in KH coder if you were going to classify the soil data using descriptive language.
I would think it would be advisable to have the records from a range of drilling or borehole logs relevant for the areas being investigated for background.
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Some journal listed as good journal in SCImago Journal & Country Rank (http://www.scimagojr.com) with relatively good h-index for example Journal of Computer Science (from Science Publication) is identified as possible predatory Journal in Beall's list. Which one I should follow?
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I agree with Víctor Herrero-Solana
"Scimago just include all the active journals in Scopus database "
and in my opinion, Scopus is not a whitelist. Journal in Scopus can still be predatory, and predatory Journal in scopus can be delisted. So beware, if your article got accepted as it is without peer review!!!
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Dear Colleagues,
The occurrence of a new, extremely pathogenic betacoronavirus, SARS-CoV-2 (2019-nCoV), is responsible for the CoVid-19 pandemic health emergency. Accordingly, SARS-CoV-2 represents a serious global health warning characterized by high mortality, a high contagion rate, and a lack of clinically approved drugs and vaccines. In order to find safe and effective therapeutic options to treat this infectious disease, computer science could play an extremely relevant role to better understand the virus pathogenic mechanism as well as to propose novel therapeutic strategies. Accordingly, due to progress in computer science, in silico methodologies in medicinal chemistry, pharmacology, biology, genetics, and virology cover relevant tasks in modern research in these fields. Furthermore, due to the current global health warning, such computational techniques could speed up research in order to provide innovative and targeted approaches to fight the coronavirus emergency. In light of this, this Special Issue will highlight progress in terms of drug discovery, virus biology, and epidemiology to provide researchers with the most innovative computer-driven methodologies for fighting SARS-CoV-2.
For this Special Issue of Computation, we invite researchers in the fields of computational drug discovery (including drug repurposing approaches), computational biology/genetics, virology, bioinformatics, and epidemiology to submit original research, short communications, and review articles related to the use of computation to fight SARS-CoV-2.
Dr. Simone Brogi Prof. Vincenzo Calderone Guest Editors
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Salute Simone,
Tante grazcie. This is most valuable to bring together best minds to seek solutions to monitor, heal and prevent the COVID-19.
Tanti auguri. Eduard
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Dear All;
I know that most of you have good experience with writing a strong research paper with novelty and originality of the ideas and results. I want some strategies and steps to start writing again because, since my master's thesis, I have not written something quite strong.
Therefore, please I need your following strategies, not links because I could find a lot of links. However, I'm asking the experts in my field (Computer Science) and especially in Deep Learning!
Thanks all in advance!
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First, it is important you identify your area of interests within your field. Then, download related articles on the identified area. Study the articles and see which of the papers attracts your interests the more. Study the paper, download about three to four more of the papers from high profile publishers. Using one of the papers as a template, make attempt to start writing yours and download more materials as the need arises during the course of putting your writings together. Note that, when you start writing at first, you're merely making a skeletal draft that would need revisit to shape accordingly. Do that and be sure to use one of the reference managers for ease of your writing especially in managing your citations. Be sure to go from review to technical papers (high profile recent journals) before studying the technical aspects from books, internet sources or other related materials.
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please i need suggestions about a research based topic that would help me achieve a great result for my dissertation
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Hey Colleagues,
I hope you are healthy and safe during this quarantine.
For any machine learning model, we evaluate the performance of the model based on several points, and the loss is amongst them. We all know that an ML model:
1- Underfits, when the training loss is way more significant than the testing loss.
2- Overfits, when the training loss is way smaller than the testing loss.
3- Performs very well when the training loss and the testing loss are very close.
My question is directed to the third point. I am running a DL model (1D CNN), and I have the following results: (Note that, my initial loss was 2.5)
- Training loss = 0.55
- Testing Loss = 0.65
Nevertheless, I am not quite sure if the results are acceptable. Since the training loss is a bit high (0.5). I tried to lower the training loss by giving more complexity to the model (Increasing the number of CNN layers and MLP layers); however, this is a very tricky process as whenever I increase the complexity of the architecture, the testing loss increases, and the model easily overfits.
Finally, to say that our model performed very well, should we get a low training loss (say less than 0.1) or my case is still considered good too?
I look forward to hearing from you,
Thanks and regards,
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That seems quite close really.
If you want to really get them closer, you could add a Dropout/SpatialDropout layer, which would help prevent overfitting.
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saying texture i mean topography.
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Hello,
If I am going to submit my work to a CS conference, and also make my Python code available publicly, is it absolutely necessary that I set seed in my Python code?
I ran an experiment, but I realized that I forgot to set seed. Will my publication be rejected at the conference because the seed is not set?
Thank you....
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You do not have to rerun the experiment. A referee or a researcher or other reader will want to. They cannot so precisely without the seed which you apparently forgot to set. What is the default seed? 0000? 1234? 3141? Send an email with a corrigendum immediately to the conference organisers stating the randomiser was not seeded, so the run can never be exactly replicated. As it is a conference paper and not a journal paper, they may let you get away with this corrigendum.
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If we have a problem and we build four methods to solve it, should we say we build a model that contains four methods ? or should we use another word instead of model ?
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They are almost the same, however., you have to use it according to the fitness/coherence nature, style, and style of your manuscript. However., the tiny differences still arises with respect different situitions. For example:
1) Model may be mathematical/statistical/physical/nominal/real/exact/approximate/optimal/maximal/minimal etc.
2) Approach may be some way of data processing, computation, scaling, idea, technique etc.
3) Method may be one of the chosen procedure for data processing, computation, calculations etc.
4) Algorithm is just step by step procedure for computation, calculation, computer or programming coding etc.
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Hello
I have the following situation: I have a paper X about topic Y. For paper X I did a forward search with Web of Science (checking all new papers which cite paper X). Then I have downloaded all articles I have identified via forward search (approx. 1'000 Papers). Now I would like to sort these papers according to the frequency of specific keywords used.
For example: I have found paper Z via forward search (so paper Z cites paper X which is about topic Y). Now I want to check if paper Z is also concerned about topic Y or if it just refers to it in passing. For that I search for specific keywords which correspond to topic Y. According to the frequency of the specific keywords mentioned in paper X, I want to classify it in the category "relevant" or "not relevant". Now, how can I determine the threshold for the keywords? That is, if paper X only uses the specific keyword once it is most probably not relevant to topic Y. But if it mentions the specific keyword 20 times it is probably relevant for topic Y.
Is there a recognized methodology to determine or approximate a threshold for the keyword frequency which allows to distinguish if a paper is relevant to topic Y or not?
With this approach I hope to reduce the 1'000 papers to those which are about topic Y.
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Can someone suggest a fully funded distance learning postgraduate diploma in computer science or related area? It would be a great help😊
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This will not be easy. The countries that still have tuition-free education are few and mostly found in Europe, you can see them here https://www.study.eu/article/study-in-europe-for-free-or-low-tuition-fees . If you come from a non-EU/EEA-country there often are fees, but sometimes lower, in these countries. For participation, you also have to qualify for a student visa for that country as a non-EU/EEA citizen, which involves showing that you have funds enough also for supporting yourself for living costs. In the category of non-tuition master programmes, there are almost no "distance educations" where you can remain in your home country. For master education, however, you can look for "Erasmus Mundus" university cooperations and master programmes. They often have, as part of the concept, some student places with a grant, enabling students from third countries to study,
For PhD candidate education, there are sometimes, as in Sweden, PhD student positions that you apply for, and if accepted, you have both tuition-free education and a monthly salary and a student visa for 4 years. it is like this in some other countries as well, as in other Nordic countries, Germany, Switzerland and Belgium. See this RG discussion https://www.researchgate.net/post/which_countries_offer_PhD_positions_as_paid_jobs_in_English
These PhD positions are advantageous, but not often "on distance", whatever that means. They can however sometimes be used in a half-flexible way. If you want a PhD "on distance", try Walden university
There is another option that may come close. The MOOC platforms have for long worked with nano-master, specialisations, micro-masters and similar course packages in interesting fields and certificates from these are often attractive for employers as a part of a CV. Not cost-free, but rather cheap, and fees are sometimes adapted after country economy. And, more and more, these platforms are offering also BSc and master programmes with ordinary credits and exams. Not free, but not very expensive, and with a lot of flexibility. begin here https://www.coursera.org/degrees and continue search other MOOC platforms as EdX, Futurelearn etc, and search them overall at classcentral.com.
There are also on some US universities online PhD and masters programmes, but they come with a cost - but sometimes cheaper than a campus option.
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Can the complexity theory solve complete or partially problems in Math?
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I read your notes, but I got nothing! You described some open problems. Complexity theory is useful in the presence of an algorithm to tackle the problem.
First, you need to show a concrete theory and then build your algorithm with a suitable complexity time to support your proofs.
We have nothing to do with complexity in the absence of the theory.
Best regards
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Hi! I am student at the University of Maribor - Faculty of electrical engeneering and computer science (specifically Electronics). I want to know more about how can I merge the BDDs or ZBDDs with the electronic problems? Any concrete ideas?
Thanks, bGood 😉
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Hi Jovanka,
at first glance, nothing seriously applicable comes to mind but just for exercise, and if you don't mind reducing the wide field of electronics to ordinary resistors:
You could define functions like
fs8(1.0, 1.2, 1.5, .. 8.2) which decide whether a set of resistors in series results in a total resistance of 8 Ohm or not. The arguments are taken from the E12 series, for example. The argument "1.0" has the value 1 if a resistor of 1.0 Ohm is present, and 0 otherwise. For example, fs8(0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0) = 1 because 1.2 + 6.8 = 8, or fs8(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1) = 0 because 8.2 != 8.
For such functions, you could sketch (part of) the binary tree, then the BDD, and at last the ZBDD.
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Currently there is a trend to apply virtual methods, ICT based, to teaching in HE . Frequently professors face the situation, when they have been teaching in face-to-face modality and want/need to do the same, but in distance education, virtual modality. Do anybody have a practical experience, or knowing about a specific methodology for Computer Science courses?
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Hi. I think you can use a lot of tools according to circumstances:
LMS (with password for your students) in case of official courses and for limited number;
Website (containing all course program and some quizz, with external links for technical tools and usefull softwares)+using e-mail/other ICT for continuous contact and eventual questions;
MOOC for fast courses for large public+using e-mail/other ICT for continuous contact and eventual questions;...
Good luck.
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My research focus on assessing an organization security culture , and really some persons advice me to use fuzzy methods , my question is that Does fuzzy AHP and Topsis are related to Computer Science because my paper must related to computer science?
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Dear Wasnaa,
AHP and TOPSIS are both the most known and effective MCDM techniques. In fact many applications of them in computer science until now. You can search for that in Journal of Computers and Industrial Engineering
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Please I am an Msc Computer Science and Technology student and my research area is software testing. My professor is really interested in Fault Localization but I am having huge challenges in performing experiment. Please could you recommend me to any company for intern so i can gain industrial experiences in software testing.
I am currently in China and i can travel to any country just to acquire the knowledge please.
Thanks in advance
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There is no need to travel to any country to acquire the knowledge that you can easily get on internet, books
I would suggest for you to work on projects on different platforms like GitHub on which you can even collaborate and apply while learning to build your resume and gain practical experience,
You can then apply for internship on various sites that can be easily found on internet.
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To keep it precise and simple what topics must be included and what learning path mustbe followed for designing computer science syllabus for future.
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Foremost the syllabus must be flexible to adapt the current advances in Computer Science, such as React Js and the use of Node.
Topics must include:
(1) Programming Languages such as Python extended to it's useful applications such as in the field of Data Science, AI
(2) Operating Systems: Linux and how to use virtual machines (such as Ubuntu Studio, Kali linux) and bootable pendrive such as that of Tails OS
(3) Arduino Uno , Raspberry pi to learn how to make use of the programming (software)- hardware (physical objects) interaction[for example: making VPN router or EEG for measurement and recording],
(4) Background and history of Computer Science with the inclusion of the current syllabus but giving less priority to the old concepts which are replaced by better practical ones
(5) Students must be taught how to develop their own website, mobile application, software pc apps, and many other practical applications of Computer Science
(6) AI, data Science, machine learning
(7) GitHub should gain more priority and importance
The list isn't over yet, it will never be as the future technology keeps on evolving, for example quantum technology could be the next big thing that can be studied in Computer Science,
I think, The best Syllabus must include topics which allows Computer Science students to think for themselves and create a learning attitude which will allow them to learn different subtopics such as learning about Tensorflow , opencv and how Python can be used to analyse videos.
Also the syllabus must be designed with more emphasis on practical work for which rote learning is not possible and which allows every student after having completed the syllabus to have skills that are of practical value and in demand in the market.
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I wonder how a machine viz computer became a stream of study with science appended with it. How it happend ? Is it a science ?
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I'm now thinking more than five. Wrt liberal arts, use of computers in design of graphic arts, music/sound arts, movie arts, and art arts. Computers in medical science, urban planning, forensics, one could go on and on...
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I have been struggling to get endorsement for putting preprint in arXiv. What is the best method to get endorsement in arXiv for computational geometry in computer science (cs.CG)?
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Hi,
If you have any academic email address, you will not need to be endorsed. So, it suffices you to register via your academic email address. If you do not have an academic email address, you have to ask someone having such a thing to endorse you. By getting the endorsement from that person you can upload your preprints to arXiv.
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I am looking to enter the field of Complex Systems or Complexity Science as a postgraduate in my Computer Science faculty, specifically focusing on Agent-Based Modeling. However, I am unclear on the current problems being addressed, what the research trends are, and how it may be applied in industry from a CS perspective, because there is currently no one in my faculty involved in Complex Systems. Any clarification on this issue would be greatly appreciated, thank you.
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The Purdue Homeland Security Institute has been using AnyLogic ABM software to garner insights related to active shooter events, test "run, hide, fight" methodologies, and establish effective evacuation procedures for theme parks. I'm only familiar with this software, but I know there are other good ones out there. Look to see if there are libraries available for your intended use. We rely on the logic for the pedestrian libraries pretty often that AnyLogic provides.
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Hi friends, I am looking for the help to decide the topics for the PhD proposal in Data Science. I am from BPFI domain and working in Retail banking. I have had an opportunity to work some of compliance and regulatory projects e.g Digital transformation, Replatform, Data Migration, BASEL, SEPA, PSD2, CRM, GDPR and recently completed my masters in computer science (Data Analytics)
Please also help me with the challenges and post PhD future in academic as well as jobs.
Thanks in advance !
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In general the first principle is a basic assumption that cannot be deduced any further. Related to different fields of human activity there are different definitions of first principles, for example for engineering those are the laws of physics. Often great innovation in science/engineering happens when the new idea is not build on top of the current state of the art or commonly accepted technology. Instead the problem is initiated from those first principles or in other words "what we know for sure" and re-build from there.
So, what are the first principles known so far in computer vision, particularly in object detection. Are there fundamental "can do" and "cant do" that take its roots and proofs in computer science, physics, mathematics?
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Object recognition is a computer vision technique for identifying objects in images or videos. ... Using object recognition to identify different categories of objects. Object recognition is a key technology behind driverless cars, enabling them to recognize a stop sign or to distinguish a pedestrian from a lamppost.
Size, color, and shape are some commonly used features. system depend on the types of objects to be recognized and the organization of the model database. Using the detected features in the image, the hypothesizer assigns likelihoods to objects present in the scene.
Refer the following link:
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Please if you state one in answer do provide
What are pros and cons of each?
Have you applied what is your experience.
What is funding limit?
Is it every year or twice a year?
Range of project funding duration?
Competitiveness of funding?
Is a one university based or a collaborative kind of funding?
etc
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It will be better if you can state the country to which you belong. Different countries have different funding agencies.
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“AIs will colonize and transform the entire cosmos,” says Juergen Schmidhuber, a pioneering computer scientist based at the Dalle Molle Institute for Artificial Intelligence in Switzerland, “and they will make it intelligent.”
What do you think? do you think the AI will change everything in the life? do you believe that the AI will become a threat for human or not?
and if yes, how near is that day?
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Dear Colleagues and Friends from RG,
The above discussion inspired me to formulate the following question:
How can artificial intelligence evolve into artificial consciousness in the future?
On the basis of the above considerations and conclusions from the discussion on interesting issues discussed, I formulated the following thesis that the unlimited development of artificial intelligence may lead in the future to the creation of artificial awareness by combining cybernetics, ICT information technologies, bioinformatics, cyberbergetics, neuroinformatics and through the development and implementation of achievements from range of machine learning technologies and other advanced data processing technologies Industry 4.0.
Below I have described the key determinants confirming the formulated research thesis. To the above discussion I would like to add the following conclusion formulated as a summary of my previous considerations on this topic: Axiomatic and technological implications of the possibility of building artificial awareness.
For several years, artificial intelligence researchers and scientists have been discussing the axiomatic and technological implications of building artificial consciousness, one of whose goals is to seek the answer to the question: Will artificial intelligence evolve into artificial consciousness in the future?
Technologies of advanced data processing Industry 4.0, including above all Learning machines and Artificial Intelligence is also used in the attempt to build machines equipped with the ability to self-improve the performed tasks and programmed activities.
Perhaps in the future there will be an attempt to build artificial awareness in which supercomputers will be equipped. In my opinion, consciousness can only be mathematically modeled in theory. Even if a mathematical model of artificial consciousness were built using ICT and Industry 4.0 and in the future Industry 5.0 and based on this model artificial intelligence would be created in quantum computers installed e.g. in autonomous robots, androids, it will still be only artificial intelligence without emotions and the essence of human consciousness. An analysis of the nature of human thoughts is necessary to distinguish between human intelligence and various artificial intelligence technologies being developed.
In advanced computerized systems of neural networks, artificial intelligence systems are created, whose task will be to solve tasks consisting of complex sequences of many algorithms and self-learning systems for solving complex problems with the help of many algorithms. In these systems, man will try to create a structure that solves complex analytical tasks and learns from his mistakes. The advantage of artificial intelligence systems over their creator, i.e. man, is to rely on a much smaller number of mistakes made during repeated processes of solving complex tasks and learning new complex formulas to apply specific increasingly complex algorithms. However, after developing these artificial intelligence systems and applying them in many computerized fields of modern economies, what will be the next stage of technological progress in this field?
Therefore, will the age of artificial intelligence and artificial consciousness come after the age of artificial intelligence? In my opinion, this is impossible. In my opinion, despite the rapid progress in the development and creation of new generations of artificial intelligence, it will never be possible to create an artificial creation that can be the equivalent of human intelligence taking into account human emotional intelligence and the specifics of human thoughts, human consciousness, human feelings. Therefore, the thesis can be formulated that in some respects artificial intelligence will probably never match human intelligence. The machine will be able to solve very complex problems and tasks but will not know why it does it, who it is, in what world it operates, it will not be able to realize its existence in the Universe etc. Machines in the form of autonomous androids can perform physically difficult works that a man cannot is able to perform.
Quantum computers equipped with Big Data Analytics will be able to solve analytical tasks many times faster than the most powerful human minds. However, they will not be aware of their existence. Human awareness of its existence has been evolved in millions of years of evolution of the human mind and also of human ancestors that preceded the human being, i.e. human-like primates belonging to primates. Human consciousness was created in a process of evolution lasting millions of years, during which the process of continuous interaction of a complex biological organism with the environment has evolved. While artificial intelligence is based on systems of neural networks in a simplified way, to a small extent mimicking the human central nervous system and the computational power of performing specific elementary tasks exceeding the analytical abilities of a human being, however, the level of complexity of the living organism of mammals is still many times higher than the most advanced computers.
In line with the above, in my opinion, the unlimited development of artificial intelligence may lead to the creation of artificial awareness in the future by combining cybernetics, ICT information technologies, bioinformatics, cyberbergetics, neuroinformatics and through the development and implementation of technology achievements learning machine and other advanced data processing technologies Industry 4.0.
In view of the above, the following question arises:
Will artificial neural structures become such advanced artificial intelligence that artificial consciousness will arise? Theoretically, you can consider this type of projects, however, to verify it realistically, you would need to create this type of artificial neural structures. Research on the human brain shows that it is a very complex and not fully understood neural structure. The brain has various centers, areas that manage the functioning of specific organs and processes of the human body. In addition, consciousness is also complex and consists of elements of emotional, abstract, creative intelligence, etc., which also function in separate sectors of the human brain.
Best wishes.
Dariusz Prokopowicz
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I'm looking for journals that are indexed in Scopus and Clarivate that may accept articles monthly for free of cost!!
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Dear Mokhaled Al-Hamadani, You can check the web sites of Scopus and Web of science to identify the journal titles. Similarly, you may check the www.doaj.org for identification of indexed journals which are not charging the authors.
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I feel very happy to tell you ,I am interested in networking,i would like to continue my research in the field of wireless networks.i need some suggestion regarding where i need to start my journey in the field of computer science and networking.i am also thankful to you if you suggest present research trends and evolution .
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If you want to work on the Vehicular communicationnetwork system. then go for the VANET, and work on the VCC (Vehicular cloud computing)
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In layman terms, Artificial Intelligence is an area of computer science where computers are developed to behave much the way as humans do. The research topic will aim to illustrate the various levels of AI in various companies implemented till date, the future projects that may impact and discussion of the argument of whether AI will 'support' HR Industry or 'replace' the current workforce, till what extent will the HR Industry be impacted globally. Which skills can be automated and which cannot be automated are a few things which i want to reach at the end!
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HR (Human Resource) Industry will be HR ( Human Responsability) Industry. Beyond AI, the changes should be analyzed with the perspective of a sustainable future building. Our research should be as much contributive as possible.
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I need help plz, anybody can help me to find a good master thesis topic in the field of computer science/IT.
The topic related to improving wireless network performance/security using one of Artificial intelligence techniques.
any help would be appreciated
thank you in advance
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Read the documents produced by ITU-T-FG-NET2030 (Networks by 2030). Several use cases refer to AI for the management of advanced network features.
Another source is ETSI-ISG-NFV (network function virtualisation) where AI might help manage complexity beyond human (control layer).
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There are a lot of problems in medicine that needs the newest technologies in computer science fields like Machine Learning and Deep Learning to solve them.
Can anyone mention some of these problems that are unsolved till now?
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Let's start with a field that I know the best: biosignals processing, clarification, and prediction. There are many unresolved problems like
* Prediction of arrhythmias
* Prediction of epileptic seizures
* Reconstruction of physiological interdependencies of various physiological processes using biosignals.
* Reconstruction of physiological paths in the brain from biosignals.
* Assessing the health condition of people using biosignals.
We can do the following research
* Data mining for disease-genome dependencies from available databases.
* Prediction of disease spreads using internet searches.
* Assessment of the population health using internet searches.
* Cross AI methods with deep knowledge of complex systems theory and apply it to medicine -- this is my area of research.
* Study and predict drug interactions and side effects in patients. This will save a lot of unnecessary suffering in those using medical drugs.
* The above can be supported by an active search through all available data for possible, future drug interactions prior to their application to patients.
* Such research can help medical doctors to avoid deadly or highly damaging drug interactions. Each patient reacts differently to the same drugs! We need to know why and especially when it happens!
* Start development of advanced AI methods tailored towards the needs of bio-medicine.
All the above depends on how reliable databases of biosignals, medical records, bio-imaging, laboratory results, and many other database build.
When you want to have successful research in the field of AI, perfect databases that are open-access are a must. We have an extreme shortage of those databases. You can build a very successful carrier by building such a database(s). :-)
This is just a short list of all possibilities. :-)
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I'm looking forward to getting some suggestions for writing a research proposal about car plate detection using DL. Looking for the following:-
1- Writing Style
2- Topics for Ph.D. research proposal in Deep Learning.
3- How to engage the attention of the reader in my research proposal?
4- Examples of research proposals using deep learning techniques!!
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First you search near by university and which is avaliable Ph.D. in Computer science in external part-time mode and search availability of guide.
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I need lists of top journals in computing that are free or inexpensive.
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Well, there are some journals indexed in Scopus and web of science that are free but in the real sense nothing is actually free.
Firstly, free journals take a very long time to publish. When i first publish in a free inderscience journal, the review period was 13months.
Secondly, after publication, you are placed on an embargo not to share the journal for some months.
These are the difficulties with approaching free high indexed journals. However, besides all these limitations, one can still get funding for high impact journals that are not free.
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AI has been an interesting topic in other fields especially in Instrumentation Engineering and Computer Science. Can we, Geotechnical Engineer, use AI in our field? If yes, then, how we can use it?
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Journal, Magazines and Letters publish scientific articles. What is technical difference between these articles and their recognition?
Writing Style, technical soundness, number of words etc.
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A magazine is definitely not the same as a Journal. Magazines normally carry popular articles, not original work. A Scientific Journal publishes original scientific work not published elsewhere. 'Letters' or 'Notes' are of shorter length. It may include a comment on an already published recent paper by the author or someone else. Normally, Editor takes decisions on 'Letters' and 'Notes'. Seldom are they are sent to reviewers.They get published quickly. A full length paper in a reputed Journal has to undergo peer review process and may take up to an year or so to get published.
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Mathematics is crucial in many fields.
What are the latest trends in Maths?
Which recent topics and advances in Maths? Why are they important?
Please share your valuable knowledge and expertise.
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For me, as well as for majority of other researchers, Mathematics is the language of Science!
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Hi all,
surfing the web I wasn't able to find a simple and effective answer to my question. In other words, I need to speed up a code I wrote using several packages such as raster, rgdal, biomod2 and ncd4 on GIS data: do I need to wait somebody else (or me too) to develop a NEW ratser etc. package which forces R to use GCPU or is it already possible siply loading additional packages before my code run such as gpuR, parallel or what else?
All my bests
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Dear Maurizio,
Although I find your question really interesting and important and hope that somebody will give a more positive answer to it, I'm afraid it's not possible to let all packages use multiple CPU cores and GPU as well with a simple package loading. A workaround instead of solution: Microsoft R Open provides built-in multithreaded matrix algebra which is used by a lot of packages. You may find that this software is a useful alternative to R.
HTH,
Ákos
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I want to ask what could the scope of IOT in agriculture or smart agriculture if I want to start a research in this field?
Also i need some suggestion on what could be the area of research in this field for a person from computer science field?
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As a person from computer science field, you are more focused on the technological aspects of the project.
usually such projects starts with defining a problem (monitoring dryness of soil, monitoring ripeness of fruits, monitoring specific diseases of the plants, monitoring cattles or sheep, ...etc.), then you deploy the appropriate sensors for the selected application, collecting data from these sensors, analyse the data with different ML/AI tools to give reports or predictions about the required value of the project to the farmers.
This is only one example and you can find more examples here:
good luck
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someone knows information on Summer Student Programme in CERN?
for example your Experience , condition there, Is it desirable or not, Do you think I 'll sign up or not and Any other information.
I am materials engineering.
thanks.
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Mr
Thomas Breuer
thanks for you.
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I am doing MS in computer science my sub field is networking, i have interest to do research in IOT that's why I need guide and help for selection of topic for my research. Please anyone enlist best topics according to my interest. Thank you in anticipation.
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1)IoT and Data: data fusion from multiple sensors, and extraction of behaviours/patterns
2) IoT and people
People can be beneficiaries or victims (my neighbours automatic vacuum cleaner, etc)
3) IoT and AI
AI supporting IoT (data analysis, decision, action)
IoT supporting AI: IoT google cars gather data, serving as input for Google map AI
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Dear Friends,
Can anyone answer this question that has been perplexed me for years? What kind of scientific discipline blatantly violates basic principles or proven rules of scientific method? What kind of scientist fiercely defends such blatant violation of basic principles or proven rules of scientific method?
Last time a scientific discipline that blatantly violated scientific method was before 17th century, when researchers fiercely defended geocentric paradox in violation of scientific method. In their defense, most of the basic rules and principles of scientific method were not yet known or properly established. Most of the basic rules and principles of scientific method were formed and which have been perfected since 17th century by many great philosophers of science and brilliant scientists, particularly based on valuable lessons and insights learned from the painful experiences gained from subverting geocentric paradox, which transformed the basic science from fake science into a real science.
What is a scientific discipline? A discipline can be a scientific discipline, if and only if the BoK (Body of Knowledge) in all the published textbooks and accepted research publications for the discipline must have been acquired and accumulated without violating basic principles and rules of scientific method. The purpose of modern scientific method is perfecting the quality of knowledge by finding and eliminating imperfections and/or anomalies. Scientific method doesn’t offer a recipe, hints, and guidelines or impose restrictions for doing research to acquire new knowledge, but provide tools to keep scientific research in the right path by detecting mistakes that can divert research efforts into a wrong path.
Each piece of knowledge in the BoK must be supported by falsifiable proof (backed by evidence and facts), where each piece of knowledge and its proof is open for challenge and perfected by rigorous testing and empirical validation. The research community in 17th blatantly violated basic scientific rule, when they tried to suppress and tacitly sabotage efforts to expose 2300-year-old unproven flawed presumption (i.e. the Earth is at the center) in it’s vary foundation.
Except computer science, I could not find any evidence that any other scientific discipline violated scientific method so blatantly. It is beyond my comprehension, why researchers of computer science fiercely defending such blatant violation of basic principles or proven rules of scientific method.
Unfortunately, software researchers acquired so much invalid BoK by blatantly violating scientific method. Since it is impossible to solve any problem by relying on invalid knowledge, software researchers concluded that it is impossible to solve certain problems (e.g. real-CBD/CBE or real computer intelligence). But it is not hard to solve those problems by acquired relevant valid knowledge. Please refer to ValidKnowledge.pdf for more information.
P.S: I also failed to find a real scientist, who can understand code of conduct for real scientists: CodeOfConduct.pdf
Best Regards,
Raju Chiluvuri
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Dear Raju and Shadi,
Excellent idea that to enter more in depth in these subjects, studying your work Raju, and provide Shadi team with a first article suite for SDE 2020, so it can introduce to the book with an extensive work. I will work on this in a few days and come back to you.
Kind regards,
Laurent
PS one article gives an idea of this work going from a political point of view to a metaphysical one (may be efficiently translated from french by automatic translators): https://une-vraie-politique-pour-notre-pays.net/2019/01/04/limposture-intellectuelle-face-cachee-dun-desastre-clef-dune-reussite-a-venir/
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Hi, I'm working on sequence alignment algorithms. My background is Computer Science. Given two sequences, what could be the max length of a gap and how many insertions/deletion at one stretch I may consider? I think more than one insertion/deletion at one stretch is useless...? My algorithm will accept a large text file, and report locations in the file where the best regions are found.
For example:
Query: ATCGACTAACCA
File: TCAGCTTCCAGCTA
When I executed these two strings on ebi.ac.uk, I got the following result, 7 pairs match.
EMBOSS_001 A T C G A C T A A C C A ---- EMBOSS_001 - T C A G C T - T C C A G C T A
However, my algorithm reports an 8 pairs match, which one is better? Please suggest. Many Thanks in advance...
Query A T C G A C T A A C C A File: - T C A G C T T C C A G C T A
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With classical biological sequence alignment algorithms such as blast, psiblast and fastA, the number of gaps inserted is controlled by two parameters, by the gap insertion penalty and gap extension penalty, which contribute to the alignment score. A high gap insertion penalty and low gap extension penalty gives preference to few large gaps rather then many short gaps.
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Being a computer science student, I don't know much about statistical testing. However, recently, a lot of work has reported statistical validation of their result. In machine learning-based prediction of effector proteins, how do you apply statistical tests to validate the result?
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For statistical learning methods like regression and discriminant anaysis, it is easy to validate results by checking underlying assumptions (white noise in residuals, normality., et.c.). For machine learning methods which are assumption free, you can use validation methods as @drsharma mentioned (for a great introductory book see: Introduction to Statistical Learning, Springer). If you want to compare and validate performance of several prediction models, you can use pairwise comparison tests.
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Hello everyone!, my team and I are working on a mobile application dedicated for promoting mental health and we need some insight.. Please take our survey and if you would like to help further you can spread it in your communities. If you have any suggestions we would love to hear them.
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Interesting project. I don't use apps to reslove stress problems ect. but I did used some traditional therapy with psychologist. I wonder if fitness and physical exercise apps count, because I use them for workouts and workouts help me to improve my mood.
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I am pursuing B.Tech.
I need a good project topic on Networking.
Can you please help me?
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Narrow your topic down to your area of interest
Networking is broad
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are any one of you doing research on sat implementation in cryptanalysis?
if so please help me....
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Sat Solvers likely will not work well for the purpose of trying to mine Bitcoin. That said it can have many other useful purposes in a blockchain context.
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I completed a study in which participants experienced two developed interaction conditions and completed the same questionnaire post each condition. I am trying to analyse the data to look for correlations between question answers and whether the condition had any significant effect on answers.
I have performed a Wilcoxon signed rank test which showed no statistically significant difference in answers between the two conditions. However, I have also performed a spearman correlation test which showed some statistically significant differences. This contradiction has me a bit confused.
I have been doing a lot of reading online to work out the tests that i could use. If anyone could help shed some light on this it would be most appreciated.
There seems to be a lot of debate between subject areas so to clarify things, my research is in the field of computer science.
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OOPS -- speaking of glitches, the correct position of this piece on RG is:
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It is my understanding that machine learning approaches perform best for predicting secondary structures in proteins ( having prediction accuracy of up to 80% ). However, protein structure prediction with ML relies on finding homologous regions established from previously determined structures. So, it won't work for proteins for which no known homologues exist. My background is computer science and, not being from the field of biochemistry, I wonder whether non-ML methods like improved Chou-Fasman and GOR are still being worked on.
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A note: The paper mentioned above doesn't distinguish between homologous and non-homologous proteins. The reported average prediction accuracy is around 85%. So, we don't know how does the method perform for sequences without known homologues.
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How Machine Learning can be helpful to developing production of new materials?
In my opinion it is so useful in materials engineering.
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Dear Hossein Homayoun ,
Machine learning provides a new means of screening novel materials with good performance, developingquantitative structure-activity relationships (QSARs) and other models, predicting the properties ofmaterials, discovering new materials and performing other materials-relateds studies.
Regards,
Shafagat
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My field of study: Computer Science
Topic of Interest: Cyber Security, machine learning and virtualization. But I am fine with other are too
Thank you in advance
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"A solution to detect a malware at packet level and directing it to a honeypot in order to further analyze and find the attack vector or the attack source" would be a great use of machine learning and Cyber Security.
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Dear colleagues,
I would like to announce that we have started a Special Issue on Artificial Intelligence and Blockchain in the IJIMAI journal. Publication in IJIMAI is peer reviewed, open access and free of charge.
Additionally, is was recently announced that IJIMAI is indexed in Science Citation Index Expanded (Clarivate Analytics) beginning with vol. 4(3) March 2017. The journal will be listed in the 2019 Journal Citation Reports with a 2019 Journal Impact Factor when released in June 2020.
If you are working on interesting Blockchain and AI synergies, I would like to invite you to contribute to this SI.
Please, find all the info in the SI dossier:
Shall you contribute a paper, please submit it through email to either editor.
Best regards.
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Dear Arjun R ,
It is advisable that the paper is related to some cross-fertilization of AI and Blockchain, otherwise it risks being rejected for being out of scope.
That said, if the work involves Blockchain to some extent even if it is not core to the proposal, I still suggest that you submit the paper for consideration.
Best!
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Dears,
Is the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) applicable for research in the Computer science field? I noticed that often this method of literature research is used only on medical studies.
If not... What do you suggest as a method for a systematic and structured literature review?
I appreciate your contribution.
Abdullah.
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The AMSTAR (Assessment of Multiple Systematic Reviews) and PRISMA are basically very good and applicable across different research areas.
My recommendation for reading literature reviews, systematic reviews and meta-analysis:
► Green, B. N., Johnson, C. D., & Adams, A. (2006). Writing narrative literature reviews for peer-reviewed journals: Secrets of the trade. Journal of Chiropratic Medicine, 5, 101-117.
This is very basic overview of writing literature reviews which is focused towards biomedicine, but is very accessible and covers lots of things that are so basic they are not covered in the other recommended reading texts.
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  • The majority of university professors are from their specific field where they were trained
  • It is likely that an expert professor of his discipline or professional specialty will allow him to transmit the specific knowledge to his students; but nothing ensures that in reality this happens
  • At present, university professors are hired not only for having a bachelor's degree or a degree; but also, for its competence in telecommunications and computer science, for being an indispensable tool in all human knowledge and doing activities
  • University professors, experts in their discipline and competent in communication and computer science, are more likely to have a successful teaching practice
  • Training in Pedagogy or Education Sciences, are already indispensable in university professors to be better teachers, for the management in methodology and instruments to improve the significant learning of their students
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Well, what I believe, it is may be depending on the situations and level of educational institutions as well as grades of student. And certainly professor have to be experienced in their own discipline.
Regards,
MJ Khan
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Those knowledge representation forms can be considered traditional, because they are related with historically first times, mainly symbolic period of Artificial Intelligence. Are they applied so widely, to justify their inclusion in a general undergraduate course for Computer Science students?
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Greetings professor and great question!
I do hope to see interesting answers here. I will contribute based on my brief experience in the area.
I think that we can see several classical knowledge representation forms in modern applications, for example semantic networks is really popular. In the other hand, vector representation seems the most widespread representation form for machine learning. Vectorial knowledge representation is a different (bottom-up) approach compared to semantic networks. Fussing the top-down approach of semantic networks with the conventional bottom-up approach of machine learning seems to be a current-to-future trend in the area.
No matter what, I think that is more important to discuss the limitations of
vectorial data representation despite its widespread. Maybe that would be a good opportunity to explain how this is one of the core issues in pattern recognition and the role of the sub discipline of learning representations from data (and the incredible hypo that deep learning have had in this area due to its ability to learn several layers of representation from raw sensorial data). The current trend is clear when enough data is available: skip manually handcrafted features and learn the representation automatically.
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I'm trying to run a tensorflow program that requires at least a cuda cpu (I think).
Google Cloud has a 300 dollar voucher for their parallel processing service. From what I understand, the 300 dollars can run out real quick.
I may go buy a cuda cpu.
Does anybody have a computer that can run Open AI's GPT-2's (see below) application? Perhaps we can collaborate on a paper.
I was thinking of contacting somebody at my school's computer science department but don't want to ruffle any feathers. Besides, not sure if they even have sophisticated computer equipment. No harm in asking.
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Academic access to HPC resources that are not available on campus is typically at a national shared facility rather than on another academic campus. In Korea, you might check out KISTI (Korea Institute of Science and Technology Information), Also, CUDA is a software system from NVIDIA. You are probably looking for hardware like a GPU or Tensorflow chip.
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Hello Everyone,
I build a framework that describes how culture influence requirement engineering activities. I want to represent the framework using set theory and mathematical modelling. However, I do not have the basic to build it. Is there any article.books/publish papers on software engineering or computer science that might help me to understand the basic to represent the framework using set theory and mathematical modelling
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Following
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One of my potential research areas, when I was working on my M.S. in Computer Science, was data sonification. There’s so much information on data visualization, and it is a tool that is used in so many industries. But there seems to be a lot less interest in data sonification. While I admit that the use cases are more limited, I think there’s still plenty of research that can be done.
For one thing, time series data may be more usefully encoded, at least in some cases, as sound, rather than a visualization.
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Springer has just released my new book on the subject: Sonification Design: From data to intelligible soundfields. It contains an extensive overview ++ https://www.springer.com/gp/book/9783030014964
(also available on Amazon)
For researchers, there's the Sonification Handbook: https://sonification.de/handbook/
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I was thinking about what would be truly impossible problems in machine learning, even with unlimited data. I quickly taught of the well known halting problem, which is known to be impossible to decide.
However humans are in many cases able to decide the problem by analyzing code. While my initial instincts are that machine learning could never fully solve the problem, would it be reasonable to believe that it would be possible to improve on human performance?
After all any program can be converted to a turing machine which is a grammar. A sort of compiler can be used to build a meaning representation, which could then be used to train a machine learning application.
And could working on such problems allow us to study better models that incorporate some sort of reasoning capability?
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May not be possible I feel
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Good Evening,
Recently I have applied at some university for PHD admission in computer science. I got cleared the entrance and i have got a call for GDPI for research proposal. Now several times i have applied but i have failed, can any one guide me how to do it?
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Dear Sir
I just suggest you before designing your proposal see some sample proposals it will help you to make your outer frame for the proposal. You may go through previous research design of the department. I think it will be helpful for you.
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In a research (e.g. computer science, etc.) that involves enhancing existing algorithm or introducing a new algorithm: 1. What will the research design involves? 2. How does one quantify the research method (since research method is either quantitative or qualitative or mixed methods) ?
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Research design is a plan to answer the research question in effective way which divided into two groups: exploratory and conclusive.
A research method is a strategy used the data obtain to archive that plan which divided into: qualitative and quantitative
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computer science bioinformatics
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Deep learning technique is the most hot topic approach in this field.
See for example:
Regards
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Do you think scientists are more susceptible to concluding that a false positive is a real positive or that a false negative is a real negative?
As I understand,
A) A false positive is when a scientist concludes that an experiment/assay succeeded when actually it failed.
B) A false negative is when a scientist concludes that an experiment/assay failed when actually it succeeded.
A scientist can waste a lot of resources on a false positive if (s)he doesn't notice that the material (s)he is testing is not what (s)he thinks it is. All observations are irrelevant to what you think you are studying as well as anything you publish about it.
A scientist could dismiss a powerful medical drug by falling for a false negative. The drug works. You just didn't test its properties well never to return to it ever again. Are theorists more susceptible to falling for false positives and experimentalists are more susceptible to falling for false negatives, for instance? For theorists, maybe we talking about models more than assays.
Also do you think scientists are conditioned to look out for false positives or false negatives more so? Which one is more dangerous to science?
Nearly all experiments and theories require optimization so false positives and false negatives are certainly possible occurrences.
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I wouldn't speak for everyone but in my surroundings people don't conclude anything from a single experiment. In molecular biology, experiments are done several times, as a rule, but what's more, different experiments are done to corroborate one point.
For example, when a biologist looks for a certain gene in a certain cell line, he checks for RNA (e.g. qPCR), then for protein (e.g. western blot), then for specific localization of the gene product (e.g. immunostaining). Then, if all of the data fit together, the scientist can conclude - okay, this gene is there and it seems to work. You don't do one qPCR run and then "conclude" that, oh, the gene is/isn't there.
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How to write an effective research proposal in computer science and engineering so that it has the maximum probability to be selected? What kind of proposal are given more preference? What are the parameter on which a research proposal is evaluated?
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Sudhakar - For writing an effective research proposal for a grant you need to follow certain steps which are common to all subjects whether it is computer science and engineering or sociology 1) Download, read carefully and follow guidelines very strictly, 2) Pick a catchy title among the themes given in guidelines, 3) Write a clear concept note and highlight your objectives very clearly, 4) Cite international and national literature relevant to the title, 5) Highlight the significance of the study and how it will have an impact in the advancement of knowledge or policy making 6) Keep budget as low as possible and don't cross your limits, 7) Present your strong bio-data.
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I'm a third year computer science student.I have taken an interest in this project and i really appreciate it if you could help me.It's for my final year project and i really don't know what to do...
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Thank you so much,Mr Mahamat Moussa...That was really helpful, I really appreciate it...Thank you
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Helloo hi
im computer science student at final year .. im doing research on it .. i need help
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Could anyone please suggest which one is easier to get accepted for conference proceedings inclusion?
Lecture Notes in Computer Science(LNCS), Lecture Notes in Artificial Intelligence (LNAI), Lecture Notes in Bioinformatics (LNBI), LNCS TransactionsLecture Notes in Business Information Processing (LNBIP), Communications in Computer and Information Science (CCIS), Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST), and IFIP Advances in Information and Communication Technology (IFIP AICT), formerly known as the IFIP Series.
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What is impact of your paper getting published in Springer Lecture notes?
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The Genetic Algorithm can be modified in different ways. Even Goldberg's book, Genetic Algorithms in Search, Optimization and Machine Learning, specifies various enhancements that could be done for genetic search.
Which is the exact method implemented in Weka for genetic search for attribute selection? The software does refer Goldberg's book, but I'm still not sure about its deeper specifics.
Some of which are
  • Precise fitness evaluation function
  • If fitness modification to add weight to diversity is implemented
  • Structure encoding of the chromosome
  • Type/variant of crossover implemented: single point, multi-point, and which point to be exact.
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The GA in WEKA is from Goldberg (1989)
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Looking for independent recommendations
Its based on my research paper. The link is below
preferably somebody from computer science/cyber-security background.
if you agree i will provide in the letter to sign in , you just have to review hand sign and scan it back to me.
Thank you so much for your time and consideration.
Best regards
parves
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Me agree
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Dear all,
I am currently studying masters in software engineering and management and looking for thesis topics related to android.
it would be great if you could provide some ideas.
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resources sharing app in fog computing environment and metering
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I need to write a proposal and then apply for PhD and i am interested in machine learning computer science field, so i need to know what are the latest topics and what already done and then find a problem to write my proposal any help to start read about latest work done in machine learning and what is the newest topics.
regards,
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swarm intelligence (mostly utilization of machine learning in design and development)
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I will like to investigate the effect of bore hole drilling on environment relating to vibration of the land and possible side effect. My area of concentration is Intelligent System Engineering in Computer Science field.
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Dear Wasiu,
I suggest you to see links on subject.
possible environmental impacts of drilling exploratory ... - Orkustofnun
Assessment of Groundwater Investigations and Borehole Drilling ...
(PDF) Borehole Drilling, Usage, Maintenance and Sustainability in ...
Professional Water Well Drilling - Unicef
Professional Management of Water Well Drilling ... - Skat Consulting
Carbonate Systems During the Olicocene-Miocene Climatic Transition
Best regards
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There are many vanet simulators available, I want to know specifically from GrooveNet and Nuctns simulator which one is best 
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Matlab
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Hello,
I am working on the different use and perception of different terms for describing a procedure / activity to solve a problem from the point of view of different research areas; these terms are 'method', 'tool', 'strategy', 'approach', 'guideline', 'framework', 'methodology', and similar. For this purpose, I plan to compare the above terms, their definition and usage from the point of view of product development research with those of business management research as well as human-computer interaction/ computer sciences. My hypotheses are that they 1) name similar activities differently and 2) in some cases use different definitions for the same terms. The definitions I am looking for are usually published in standard works and textbooks. However, I find it difficult to find these for the two disciplines that are unfamilar to me, business administration and computer science. Can someone help me?
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Following
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Topology in computer sci?
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Suggest some research topics in Machine Learning in the field of computer science.
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Amit Das You can work on Deep learning with supervised approaches, semi-supervised and unsupervised techniques on various domains such as :
Facial recognition
Voice Recognition
Financial Services
Health Care
Virtual Personal Assistants
Predictions
Computer Vision/Videos Surveillance
Social Media Services
Email Spam and Malware Filtering
Online Customer Support
Product Recommendations
Online Fraud Detection
Biometrics
And Many More
Automation and prediction in all of the above domains with high precision is in high demands. Further, below links will be helpful for you :
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I would like to know the list of ISI indexed journals that publish robotic motion planning problems including robotic related journals and computer science journals. Moreover, it is very important that their review process is not too long.
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Fast journals are often of low quality or even predatory, don't trust speed as an effective metric.
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should we consider data science subject under computer science or statistics? If we have to choose one of these.
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If you take a wide angle view of statistics, data science is statistics https://www.amazon.com/gp/product/1119570700/ref=dbs_a_def_rwt_bibl_vppi_i0
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