Science topics: Computer Science
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# Computer Science - Science topic

Explore the latest questions and answers in Computer Science, and find Computer Science experts.
Questions related to Computer Science
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For computer science, is mathematics more of a tool or a language?
An equation can be considered as a sentence in the language of mathematics, at least in its formalized version as can be seen in every book about mathematical logic or ZFC set theory. Programming languages are also formalized languages, and you have to stick to these formalizations in order for a computer to work correctly. However, most mathematicians use a semi formal mathematical language, but when for instance a theorem is correct, meaning that is has a correct proof, then one can write theorem and proof in the formalized language of mathematics, but the result is almost always unreadable by a human being, but " understandable " by a formal proof system, that can be implemented on a computer. In this sense one can let computers prove theorems, but then it needs a lot of input from a human being. But doing mathematics is also an art, and in order to be able to practice this art one needs a lot of practice and mathematical knowledge.
A Gaussian law is a concept in statistics or probability theory. The notion of linear function belongs to the areas of calculus , analysis and linear algebra.
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In education system, students are diverting from basic engineering discipline to computer science, Artificial Intelligence and Machine Learning . Here knowledge from Civil engineering and concepts in Artificial Intelligence need to identify for the best use.
Opportunities for artificial intelligence (AI) in civil engineering are plentiful and expanding. AI-driven tools can increase effectiveness, performance and also safety in every stage of the life cycle of civil engineering projects, from planning, designing & execution to operational and maintenance stages. Here are some specific examples of how AI is being used in civil engineering today: Design: AI can produce and assess numerous ideas faster than traditional methods. This enables engineers to determine the optimal configuration for a specific task considering cost, performance, and green foot print, among others. Construction: AI can also automate and optimize several other construction activities, scheduling, resource allocation, quality control, to name a few. This helps to save cost, to make processes more efficient & to minimize mistakes. Operation and maintenance: Infrastructure: AI can also be deployed for monitoring and analyzing the state of infrastructure assets such as Bridges, Roads and Buildings etc. The earlier the problem is detected, less expensive it will be for you in terms of money, time and effort. AI is being used in many ways also for developing new Civil Engineering solutions. Such as AI-equipped drones examining the bridge and other structures in a faster, safer manner than traditional methods. It’s also developing new materials and techniques of constructing sustainable and long lasting structures.
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I am student of ms computer science. I am currently working on zero-shot learning. I have done most of the literature review about this topic and I have found almost 18 good methods for zero-shot learning. Now my question is should I work on these methods or should work on creating some new techniques for this. I am new to research that's why my question is very simple
There are several open areas in which you can work such as,
• Zero-shot Learning for Different Modalities: Extending ZSL to handle multiple modalities, such as combining visual data with text or audio, is an ongoing challenge. Developing models that can be generalized across modalities is an open area of research.
• Hybrid Approaches: Combining traditional supervised learning with zero-shot learning techniques can help bridge the performance gap. Developing effective hybrid models and techniques is an open area of research.
• Robustness and Adversarial Attacks: Zero-shot learning models can be vulnerable to adversarial attacks. Research into making these models more robust to such attacks is important, especially for applications where security is a concern.
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Dear Faculty and Research Community,
I hope this message finds you well. I am writing to express my genuine interest in pursuing a PhD in Computer Science, with a specific focus on Machine Learning and Neural Networks.
With a Master's degree in Computer Science and a strong academic background, I am highly motivated to contribute to cutting-edge research in these fields. I am open to exploring opportunities within your esteemed institution and collaborating with faculty members who share my research interests.
If there are any available PhD positions or opportunities for prospective doctoral candidates in Computer Science, I kindly request your guidance and consideration.
I am excited about the prospect of becoming part of your research community and making meaningful contributions to the field. Thank you for your time, and I look forward to any insights or opportunities you may offer.
Sincerely,
YASIR ALI
FROM PAKISTAN
I did Phd from Banasthali
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For example, if the maximum requirement is 6 pages of main content, but my paper only has 5 pages.
If the paper is 1 page less than the maximum required limit, does it have a big impact on its acceptance? No. Content matters.
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I heard on television a famous professor of ethics speaking about the rights of intelligent machines. There are no intelligent machines and there is no artificial intelligence. Machines function in the way people designed and programmed them to function. A discourse bout intelligent machines leads into a totalitarian society, in which people will succumb to what machines say. And machines will say what power-holders ordered to programmers to program them to say and do.
I graduated computer science; I am now retired and I regret the fact that I spent my career teaching something what now leads people into a mental and physical slavery.
Mario Radovan There is nothing to regret about, Prof. Mario Radovan. You have done what you thought needed to be done based on your judgement and analytical thinking as an educator at that time. . . . Voice of experience as an educator and a community stakeholder.
• asked a question related to Computer Science
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first i send this number to bard chat bot
6020 5603 54830 6750 23000 12370 10000
it responds this.
You have listed 7 numbers.
• 6020
• 5603
• 54830
• 6750
• 23000
• 12370
• 10000
The sum of these numbers is 103573.
The average of these numbers is 14825.
The median of these numbers is 6750.
The mode of these numbers is 10000, which appears twice.
The range of these numbers is 23000 - 10000 = 13000.
The standard deviation of these numbers is 3844.74.
then i ask it to standardize them.
Sure. Standardizing the numbers will mean subtracting the mean and then dividing by the standard deviation. This will transform the numbers so that they have a mean of 0 and a standard deviation of 1.
The standardized numbers are:
• -2.18
• -2.88
• 2.44
• -1.38
• 3.22
• -0.78
• 0.00
----------------------------------------
Bing chat respond to the same question what this
I can standardize the numbers you provided. Standardization is the process of transforming data to have a mean of 0 and a standard deviation of 1. This is done by subtracting the mean from each data point and then dividing by the standard deviation.
Here are the standardized values for the numbers you provided:
• 6020: -0.705
• 5603: -0.801
• 54830: 2.891
• 6750: -0.524
• 23000: 0.693
• 12370: -0.191
• 10000: -0.363
Is there anything else I can help with? 😊
------------------------------------------
Based on the search results, it is possible to standardize the numbers provided by converting them into z-scores. Standardizing data is a common practice in statistics to compare variables that have different scales or units of measurement. To standardize the numbers provided, one would need to calculate the mean and standard deviation of the data and then transform each value to its corresponding z-score
Here are the steps to standardize the numbers:
1. Calculate the mean of the data: Mean = (6020 + 5603 + 54830 + 6750 + 23000 + 12370 + 10000) / 7 = 15038.43
2. Calculate the standard deviation of the data: Standard deviation = sqrt(((6020 - 15038.43)^2 + (5603 - 15038.43)^2 + (54830 - 15038.43)^2 + (6750 - 15038.43)^2 + (23000 - 15038.43)^2 + (12370 - 15038.43)^2 + (10000 - 15038.43)^2) / 6) = 17523.22
3. Calculate the z-score for each value: Z-score = (X - Mean) / Standard deviationZ-score for 6020 = (6020 - 15038.43) / 17523.22 = -0.706 Z-score for 5603 = (5603 - 15038.43) / 17523.22 = -0.768 Z-score for 54830 = (54830 - 15038.43) / 17523.22 = 2.238 Z-score for 6750 = (6750 - 15038.43) / 17523.22 = -0.426 Z-score for 23000 = (23000 - 15038.43) / 17523.22 = 0.455 Z-score for 12370 = (12370 - 15038.43) / 17523.22 = -0.152 Z-score for 10000 = (10000 - 15038.43) / 17523.22 = -0.853
By standardizing the numbers, we have transformed them into a common scale that allows for easier comparison and analysis. It is important to note that the interpretation of z-scores depends on the context and the distribution of the data.
-----------------------------------------------------
so, as you can see it can't even get sum of the data correct. my question is why this models cant get sum of this number right even when they apply all the correct steps
Abolfazl Ghoodjani can you be more specific with your answer by the way the writing above are output of (chat gpt and lambda ) . my question is why this models can get sum of this number right even when they apply all the correct steps
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Is there a promising future for someone over 40 years old who is still writing code, and has not become a manager in IT company?
Anyway, they have a present. To have a future you have to continue working every day of the rest of your life. Otherwise you are dead
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How to establish a network with IEEE members that can help become an IEEE Fellow?
IEEE stands for Institute of Electrical and Electronics Engineers. The main AIM of IEEE is to ensure foster technological innovation and excellence for the benefit of humanity. The IEEE standards in computer networks ensure communication between various devices.
The nominee must meet the following three basic qualifications:
-have accomplishments that have contributed importantly to the advancement or application of engineering, science, and technology, bringing the realization of significant value to society;
-hold IEEE Senior member or IEEE Life Senior member grade at the time ...
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《Revisiting ...》
Writing a computer science paper with a title starting with "Revisit" typically indicates that you are revisiting or reevaluating a previously explored topic, concept, or method. Here's a step-by-step guide on how to write such a paper:
**1. Choose a Specific Topic or Concept:** Begin by selecting a specific topic, concept, algorithm, technique, or area within computer science that you want to revisit. It should be something that has been previously studied or discussed in the field.
**2. Review Existing Literature:** Conduct a comprehensive literature review to gather information about the topic you've chosen. This step is crucial for understanding the current state of knowledge and identifying gaps or areas where a revisit is necessary. Summarize key findings from previous research.
**3. Identify the Need for Revisiting:** Clearly articulate why there is a need to revisit the chosen topic. What has changed since the previous research was conducted? Are there new challenges, technologies, or perspectives that warrant a fresh examination?
**4. Define Your Research Questions or Objectives:** Formulate specific research questions or objectives that your paper will address. These should be focused and aligned with the purpose of revisiting the topic. What do you hope to achieve with this revisit?
**5. Methodology:** Describe the methodology or approach you plan to use in your revisit. Will you conduct experiments, surveys, simulations, or theoretical analyses? Explain how you intend to gather data or information.
**6. Data Collection and Analysis:** If applicable, collect data or perform experiments according to your chosen methodology. Analyze the data using appropriate statistical or computational techniques. Ensure that your analysis is rigorous and unbiased.
**7. Results:** Present the results of your research. Compare and contrast your findings with the results of previous studies. Highlight any significant differences, new insights, or unexpected outcomes.
**8. Discussion:** Interpret the results and discuss their implications. How do your findings contribute to the understanding of the topic? Are there practical applications or theoretical advancements that result from this revisit?
**9. Related Work:** Discuss other relevant work in the field that may not have been part of your revisit but provides additional context or insights.
**10. Conclusion:** Summarize the key points of your paper, restate the significance of revisiting the topic, and highlight the contributions of your work.
**11. References:** Provide a comprehensive list of references to acknowledge and cite all the sources you consulted during your literature review and research.
**12. Title and Abstract:** Craft a meaningful and concise title that starts with "Revisit" and accurately reflects the content of your paper. Write an informative abstract that summarizes the main points of your paper, including the need for the revisit, your methodology, and key findings.
**13. Proofreading and Editing:** Carefully proofread and edit your paper for clarity, coherence, grammar, and formatting. Ensure that it follows the specific formatting and citation style required by the target journal or conference.
**14. Submission:** Submit your paper to a relevant computer science journal or conference. Follow the submission guidelines and address any reviewer comments or feedback during the peer-review process.
Remember that a successful "Revisit" paper should contribute new insights or perspectives to the field, making it valuable to researchers and practitioners in computer science.
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Presently computer science well applicable in various fields of science and many other fields. how best use in chemistry. .
Computer science has made significant contributions to the field of chemistry, enabling researchers to model complex molecular systems, predict chemical reactions, and analyze vast datasets. Here are some notable applications of computer science in chemistry:
1. **Monte-Carlo Simulations**: These are used in various areas, including environmental and chemistry fields. Monte-Carlo simulations can help in understanding complex chemical systems by using random variables and state-of-art techniques. [Link to the study](https://doi.org/10.54097/hset.v17i.2430)
2. **Molecular Docking and Dynamics**: Computational methods have been developed to solve the molecular docking problem, which is crucial for understanding molecular interactions and designing drugs. [Link to the study](https://doi.org/10.55522/jmpas.v12i1.4137)
3. **Material Science and Molecular Design**: The combination of material science and computer science has shifted the approach from "how to make a molecule" to "what molecule to make." This involves designing new ligands and complexing them with metals like Ruthenium to develop new materials with diverse applications. [Link to the study](https://doi.org/10.33696/pharmacol.4.042)
4. **Simulation of Practical Works of Crystallography**: Technological innovations have led to the development of computer applications that simulate chemical experiments, especially in the field of crystallography. This allows students and researchers to understand and study different crystalline structures using computer-based virtual experiments. [Link to the study](https://doi.org/10.35940/ijrte.c4665.098319)
5. **Computer-assisted Structure Elucidation (CASE)**: CASE systems have been developed to help in the structure elucidation of natural products using spectroscopic data. These systems mimic the expert's way of thinking during the process of structure elucidation. [Link to the study](https://doi.org/10.1039/9781849735186-00187)
6. **Visualization of Proteins**: Modern biochemists use computational methods to visualize proteins, find ligand binding sites, and understand the three-dimensional interactions with coordinated amino acid residues. [Link to the study](https://dblp.org/rec/journals/cse/PineP20)
7. **Nanoscience and Advanced Computational Methods**: Computational methods have been employed to study and design new compounds at the atomic level, leading to the development of software for targeted simulations. [Link to the study](https://doi.org/10.4018/978-1-4666-1607-3)
8. **Quantum Algorithms for Quantum Chemistry**: Quantum algorithms have been developed for ground-state, dynamics, and thermal-state simulation in quantum chemistry, providing a new dimension to the study of molecular systems. [Link to the study](https://arxiv.org/pdf/2001.03685)
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Dear Researchers,
Subject: Call for Systematic Literature Review Papers in Computer Science Fields - Special Issue in the Iraqi Journal for Computer Science and Mathematics
I hope this letter finds you in good health and high spirits. We are pleased to announce a unique opportunity for researchers in the field of computer science to contribute to our upcoming special issue focused on systematic review papers. As a Scopus-indexed journal with a remarkable CiteScore of 2.9 and a CiteScore Tracker of 3.5, the Iraqi Journal for Computer Science and Mathematics is dedicated to advancing the knowledge and understanding of computer science.
Special Issue Details:
- Title: Special Issue on Systematic Literature Review Papers in Computer Science Fields
- Journal: Iraqi Journal for Computer Science and Mathematics
- CiteScore Tracker: 3.5 (As per the latest available data)
- CiteScore: 2.9 (As per the latest available data)
- Submission Deadline: December 31, 2023
- Publication Fee: None (This special issue is free of charge)
We invite you to contribute your valuable insights and research findings by submitting your systematic review papers to this special issue. Systematic reviews play a crucial role in synthesizing existing research, identifying trends, and guiding future research directions. This special issue aims to gather a diverse collection of high-quality systematic review papers across various computer science disciplines.
Submission Guidelines:
to submit your paper. Make sure to select the special issue "Systematic Literature Review Papers in Computer Science Fields" during the submission process.
We encourage you to review the author guidelines and formatting requirements available on the journal's website to ensure your submission adheres to our standards.
Should you have any inquiries or need further assistance, please do not hesitate to contact our editorial team at mohammed.khaleel@aliraqia.edu.iq
Your contribution to this special issue will undoubtedly enrich the field of computer science and contribute to our mission of fostering academic excellence. We look forward to receiving your submissions and collaborating towards the advancement of knowledge.
Warm regards,
Editor in Chief
Iraqi Journal for Computer Science and Mathematics
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More specifically in the fields of sensory devices, multi-modal systems, HAR etc.
Journal of Supercomputing
Wireless Networks
IEEE Sensors Journal
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Hi Dears, according to implementation RSA in python. I found that if p and q large.
the decryption phase takes a lot of time to execute.
for example, in this code i select p=23099, q=23059, message=3
it takes 26 minute it decrypts the encrypted message.!
So I wonderful how we can select to large prime number for RSA, while it cannot execute in desired time. !
So, I think that we cannot use RSA i n real time systems.
Are you agree with me?
the source code is:
from math import gcd
import time
# defining a function to perform RSA approch
def RSA(p: int, q: int, message: int):
# calculating n
n = p * q
print(n)
# calculating totient, t
t = (p - 1) * (q - 1)
start = time.time()
# selecting public key, e
for i in range(2,t):
if gcd(i, t) == 1:
e = i
break
print("eeeeeeeeeeeeee",e)
# selecting private key, d
j = 0
while True:
if (j * e) % t == 1:
d = j
break
j += 1
print("dddddddddddddddd",d)
end = time.time()
# print(end-start)
e=0
#RSA(p=7, q=17, message=3)
RSA(p=23099, q=23059, message=3)
d=106518737
n=532639841
e=5
#RSA(p=23099, q=23059, message=3)
start= time.time()
ct=(3 ** e) % n
print(ct)
pt=(ct ** d) % n
end = time.time()
print(end-start)
print(pt)
#----------------------------------------------------
If you're using Python, I'd suggest using pow(ct, d, n) instead of pt=(ct ** d) % n. That should improve the time. As Wim suggests, modular exponentiation improves the running time of large exponents.
Cheers
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I am a Computer Science PhD scholar who recently changed my thesis title. I am currently researching for a suitable title in my field. I would greatly appreciate it if you could share your recommendations, suggestions, or ideas. Your input would be highly valuable and would save me a significant amount of time. Thank you.
تجربه من
در این امور به من می گوید که هیچکس بهتر از خودتان نمی تواند به خود شما کمک کند.. از این جهت که مواردی که جای کار بیشتر را دارد شناسائی کنید و علاوه بر این علاقه و نگاه به آینده
البته بنده خیلی سال قبل در پونه دنبال قضیه دکترایم بودم و سه پروپوزالی که به هند بردم را نپسندیدند آنچه برایم جلب توجه می کرد نگاه فوق العاده سنتی گروه علم اطلاعات دانشگاه پونه بود که موضوعات جدید را برنمی تابیدند و علاوه برآن بیشتر می خواستند بدانند در کشور کسی که برای تحصیل آمده حول آن رشته تحصیلی چه می گذرد در هر صورت گروه هر سه پروپوزال را رد و آنچه مورد نظر خودشان بود را مطرح و دفاع از پروپوزال و پذیرش
البته بعد من قضیه تحصیل در هند را رها کردم
در هر صورت منظورم این است که اگر در دانشگاه شما هم چنین می کنند اول باید با خود گروه و خصوصا استاد راهنمایتان هماهنگ شوید
سال هشتاد و پنج من کتابی تالیف و منتشر کردم که هنوز هم مهم و تکست آزمون دکترا هست
یعنی این کتاب
بازیابی پیوسته:نظام ها و روش ها
متن کامل را سال بیست بیست و دو در همین ریسرچ گیت آپلود کردم
آن را مطالعه و خصوصا فصل های مربوط به روش جستجو در پایگاه های اطلاعاتی
البته شاید هم به خوبی اینها را بدانیدد
دیگرفصلی از کتاب
نگارش مقاله که آن هم تالیف خودم و یکی از استادانم بود را هم در رابطه با نحوه پیدا کردن موضوع مناسب بر مقاله و تحقیق و رساله برایتان پیوست کرده ام
بنظرم جواب های من به پرسش هایی که ممکن است به نحوی به سوال شما مربوط باشد را هم مطالعه کنید که مهمترین آنها اینها هستند
در کل معمولا اشخاص علاقه ای به اینکه اگر چیزی می دانند که به قول خودشان یونیک هست صحبتی نمی کنند و یا اینکه همکاری نمی کنند پس بهتر است خودتان دست به کار شوید
البته بررسی چند ساله من نشان می دهد که به هر ترتیبی بتوانید بین تحقیقات خود و شبکه های اجتماعی ارتباطی برقرار کنید و مطالعات خود را به آن سمت ببرید بسیار مفید خواهد بود که خود به جهت رشد روز افزون این رسانه ها می باشد
موفق باشید
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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,
The following answer is by using chatgpt (https://chat.openai.com/):
Adding a research paper to Google Scholar involves a few steps. Google Scholar is a freely accessible search engine that indexes scholarly articles from various disciplines. While you cannot directly upload papers to Google Scholar, you can ensure that your research paper gets indexed and displayed in the search results by following these steps:
1. Publish Your Paper: First and foremost, your research paper needs to be published in a reputable and credible scholarly journal or conference proceedings. Google Scholar aims to index academic content, so make sure your paper meets the academic standards of your field.
2. Provide Detailed Information: Ensure that your paper has accurate and detailed metadata. This includes the title, authors' names, abstract, keywords, publication date, and citation information. Accurate and complete metadata increases the likelihood of your paper being indexed correctly.
3. Publish Open Access (Optional): While it's not a requirement, publishing your paper as open access (freely accessible to the public) can improve its visibility on Google Scholar and other search engines. Open access papers tend to receive more citations and have a broader impact.
4. Use Scholarly Citations and References: In your paper, cite relevant and reputable sources from other researchers. Make sure to include proper citations and references according to the citation style of your field (APA, MLA, Chicago, etc.).
5. Wait for Indexing: Google Scholar's indexing process is automated and periodic. It may take some time for your paper to be discovered and indexed after it's published. The indexing frequency varies, so be patient.
6. Check Your Institutional Repository: If you're affiliated with a university or research institution, they might have an institutional repository where you can upload your paper. Google Scholar often indexes content from these repositories.
7. Create a Google Scholar Profile (Optional): If you're a researcher, you can create a Google Scholar Profile to manage your publications and citations. While this won't directly add your paper to Google Scholar, it can help ensure that your work is accurately attributed to you.
8. Engage in Academic Networking: Engage with the academic community by attending conferences, presenting your research, and collaborating with other researchers. This can lead to more citations and increase the visibility of your paper on Google Scholar.
Remember that Google Scholar's indexing process is automated, and not all papers may be indexed immediately or at all. It's also worth noting that Google Scholar doesn't verify the quality or credibility of sources, so it's essential to publish in reputable journals and conferences to maintain the integrity of your research.
If you've followed these steps and your paper is not appearing on Google Scholar, you can contact Google Scholar support for assistance or explore their official documentation for more information.
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As a CS/SE student currently I'm finding an area for research.
Currently my idea was to investigate more about recommendation systems using ML and deep Learning, but with the timeline to complete and the project is limited.
In the above topic research gap is very limited.
Please suggest some research gaps for me to consider.
Dear Rishini Hettiarachchi,
a very broad area of research is the use of Artificial Intelligence in the IoT. The idea of Digital Twins is fundamental to this. For details see:
As an appendix I added a small reference list about convergence of Digital Twin, IoT and Machine Learning.
Good luck and best regards
Maninder Jeet Kaur,Ved P Mishra, Piyush Maheshwar: „The Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action“; in book: Digital Twin Technologies and Smart Cities, Jan 2020, DOI: 10.1007/978-3-030-18732-3_1
Maninder Jeet Kaur,Ved P Mishra, Piyush Maheshwar: „The Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action“; in book: Digital Twin Technologies and Smart Cities, Jan 2020, DOI: 10.1007/978-3-030-18732-3_1
Muhammad Mazhar Rathore, Syed Attique Shah, Dhirendra Shukla, Elmahdi Bentafat, Spiridon Bakiras: „The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities“; IEEE Access, Vol. 9, Feb 2021, DOI: 10.1109/ACCESS.2021.3060863
Xiaoming Li, Hao Liu, Weixi Wang, Ye Zheng, Haibin Lv, Zhihan Lv: Big data analysis of the Internet of Things in the digital twins of smart city based on deep learning; Future Generation Computer Systems, Vol. 128, Mar 2022, DOI: 10.1016/j.future.2021.10.006
Yueyue Dai, Ke Zhang, Sabita Maharjan, Yan Zhang: Deep Reinforcement Learning for StochasticComputation Offloading in Digital Twin Networks; IEEE Transactions on Industrial Informatics, Vol. 17, Issue: 7, Jul 2021, DOI: 10.1109/TII.2020.3016320
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How can independent researchers become an IEEE fellow without supervising students?
Independent researchers can achieve IEEE Fellow status through exceptional contributions in their field, demonstrated leadership, and impact. While supervising students can be beneficial, it's not mandatory. Demonstrating significant research outcomes, publishing influential work, and engaging in professional activities can establish eligibility for the IEEE Fellow recognition.
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I just completed a draft copy of my thesis, but I still do not feel that it is up to par. I would need some input from those who have done research on medical imaging.
What are the common pitfalls to avoid?
How many pages and a bibliography?
How about clinical validation? Should I stick with majority voting or rely only on insights from a seasoned pulmonologist?
I look forward to your valuable insights.
Victor Ikechukwu Agughasi I just had the 25th Anniversary of The Internet Foundation on 23 Jul 2023. Again and again I see groups working on common topics, but NOT working together. Are there really more than 100 Million chest x-rays in India every year? But that is many separate efforts, and not one common project. Now in the world India is probably not a leader in gathering chest x-ray data into common formats, establishing best algorithms. Rather than cooperating with China and all other countries, groups will want to be "king of the hill" (a children's game, who is strongest). Global research is driven by jealousy and politics, self-interest and massive waste as groups duplicate what is already known. It is the data and models that are most important. If everyone works on their own piece of the puzzle, and does not share, everyone loses. Sounds like you have some good material in your thesis. Again, the thesis is just a step in what you might find is a very long lifetime of exploration and helping others. Try to write from your heart about real issues and what you hope to accomplish. If you think something needs to be done at national or global levels, say so and get people and groups moving in common direction. Be careful not to enable more monopolies and hoarding for self-interests. All I can suggest is so at least try to make sustainable open verifiable truly accessible systems. Then if the systems start to go astray, the tools for accepting feedback and implementing corrections will be there and work as they are supposed to. Systems should not be allowed to lock themselves tightly and ignore all feedback, which is more the norm now than the exception.
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How can a low-level employee working in an IT company, without supervising students like a university professor, become an IEEE fellow?
Becoming an IEEE fellow as a low-level IT employee may seem daunting, but it's not impossible! Embrace passion for tech, contribute to innovative projects, publish research, and network with IEEE members. Rise through the binary ranks, like a digital ninja! Your determination will power up your journey! 🚀
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Is there a way to become an IEEE fellow without becoming a doctoral supervisor at a university?
Yes, it is possible to become an IEEE Fellow without becoming a doctoral supervisor at a university. To be nominated for the IEEE Fellow title, the individual must meet specific requirements:
1. Accomplishments: They should have made significant contributions to the advancement or application of engineering, science, and technology, bringing valuable benefits to society.
2. IEEE Membership: The nominee must be an IEEE Senior member or IEEE Life Senior member at the time of nomination.
3. Impact: Their contributions should have had a notable impact in their field, paving the way for future contributors.
The nomination process involves submitting materials confidentially to the IEEE Fellow Committee, consisting of 51 members plus a chair. The committee represents the 10 IEEE Regions and possesses expertise in the technical areas represented by IEEE Societies/Technical Councils. The final slate of nominees is then presented to the IEEE Board of Directors for approval.
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Hello,
My name is ADALA Roger Bertrand and I am a master's student at the University of Yaoundé I. I am looking for a co-supervisor for my master's thesis. My thesis topic is "Dematerialization of education: use of artificial intelligence (AI) for the dematerialization of courses and exams in higher education, case of the computer science department of the University of Yaoundé I".
I am interested in this topic because I believe that AI has the potential to revolutionize education. AI can be used to personalize learning, provide feedback to students, and create interactive and engaging learning experiences.
Of course, the topic can be changed or improved. I am comfortable working in French or English.
I would be grateful if you could consider supervising my master's thesis. I look forward to hearing from you soon.
Sincerely,
Hi, I think I can help you with this. You ae absolutely right. AI has revolutionized every industry. Education is changing its landscape at a pace faster than ever.
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I am a student from Umar Musa Yaradua University Katsina
from Computer Science Department.
I need someone who is going to teach me cyber security.
One great resource for learning about cybersecurity is the Cisco Networking Academy. They offer a free, self-paced course called "Introduction to Cybersecurity" that will teach you the basics of cybersecurity. You can find the course at this link: https://skillsforall.com/course/introduction-to-cybersecurity
Once you've completed the introductory course, you can continue your education with Cisco's other cybersecurity courses. They offer a variety of courses at different levels, so you can find one that's right for your skill level.
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🌐🤝 Join us at IAIC 2023 - the International Conference on Artificial Intelligence! 🤖✨
📅 November 24-26, 2023 📍 Nanjing, China 🌐 Website: http://www.iaicconf.com/
IAIC 2023 has invited numerous experts and scholars from around the world who are researching artificial intelligence. This includes distinguished editorial board members, authors, and readers of the computer SCI journals under Tech Science Press: CMC, IASC, and CSSE. It promises to be a grand gathering for the editors, authors, and readers of these three journals.
IAIC 2023 is currently accepting workshop proposals, we welcome scholars to submit workshop proposals and serve as workshop chairs to bring together scholars with similar interests for lively discussions and exchange of academic ideas.
Conference Highlights:
🔹 IAIC 2023 is hosted by Tech Science Press, with support from prestigious institutions such as the University of Electronic Science and Technology of China, Jinan University, Nanjing University of Aeronautics and Astronautics, and more. 🔹 We are honored to have Professor Hai Jin, the Director of the Academic Committee at the School of Computer Science and Technology, Huazhong University of Science and Technology, and Professor Yi Pan, the Dean of the College of Computer Science and Control Engineering at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, as the co-chairs of IAIC 2023. Professor Yi Pan is also an Academician of the American Institute for Medical and Biological Engineering.
We continue to extend invitations to high-level scholars from both home and abroad.
Join us at IAIC 2023 to explore the frontiers of artificial intelligence and connect with leading experts in the field. Don't miss this opportunity to be part of an exceptional academic exchange!
Register now: https://lnkd.in/dNaQvPJY Propose a Workshop: https://lnkd.in/d74h2z4Y
#IAIC2023 #ArtificialIntelligence #Conference #AcademicExchange #TechSciencePress #AI #computerscience #WorkshopProposals #AIConference #CallforWorkshops
ICOAI allows academia to meet industry from the international community to exchange experiences, demonstrate their studies and further advance AI technologies.
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First part of the question is: what are the absolute essential ingredients behind computation? You need (i) switches, (ii) interconnects, (iii) input energy source, (iv) memory, (v) feedback, (iv) correct timing delays. Are these the basic magic ingredients? Is there anything I have forgotten?
Second part of the question: what are the minimum essential ingredients I need to add to a computer to make it life, ie. self-reproducing?
In other words, when we compare the computational characteristics of a living cell to that of a standard computer, what are the essential differences? It is something to do with the instruction set itself, how it comes into being, gets processed, and replicated...but I can't quite put my finger on it and express the idea succinctly. And if I can't express it, it means I don't really understand something. Any ideas how to describe the essential ingredients rigorously?
To the surprise of many, there is existing so-called emergent computation. There are published on RG several Python softwares--GoL-N24, r-GoL, and GoL, on my research profile that demonstrate the following properties: (i) emergent information processing, which arises through self-organization, (ii) error-resilient properties of some special cases of emergents, (iii) automatic creation of multi-level emergent systems.
This research is capable to reproduce into a certain extent by-the-life- utilized computing and information processing.
See some of many shared animations in my RG data section, software section, and discussion dealing with animations of complex systems, which are available here. The last paper from 2022 and the next one are dealing exactly with those issues. I recommend reading the review "Complexity in medicine ...", which serves as the introduction.
Just one animation to curb your appetite, it is in APNG format which is after its downloading easy to view in any modern web browser as a file (write at the window instead of web page '//' and chose the option to see files).
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In general, Journals Impact Factor is released in the fourth week of June every year?
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Please suggest some fast publishing Elsevier/IEEE/Springer/T&F journals in Electrical and Electronic Engineering/ Computer Science
If you look for fees in Elsevier, IEEE or Springer, you can find an Excel with the fees and journals. Their names can help you and they have usually basic specs.
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Uncontrolled development of AI - artificial intelligence is a very dangerous thing!
👉 Dangerous to humanity, really, I say that as a person from the IT sector, as someone who spent the first half of his life (39 years) well, the last 25, spent in IT, passed all levels of formal education, passed university teaching positions... etc. .
To learn robots write and walk, and not our children, or gave them smartphones instead of time in nature? So sad ... and most people doesn't have time really?!
‼️ I think most people are not aware...
• One does not need to be overly intelligent to see what is happening, that we need to react and slow down or indeed put a moratorium on the uncontrolled (I will add insane) development of AI.
Of course, such development (if it is development at all?!) humanity does not need, except for those with a bad ultimate intention for all of us as a human species.
Imagine if, as a side effect of all this, it would be the "end of the world", and we would then call ourselves the most intelligent beings on Earth? We!? 😡
"Should we allow machines to flood our information channels with propaganda and untruths? Let chaos ensue.
Should we automate all jobs, including those that fill people's lives with meaning?
Should we develop non-human minds that could eventually outnumber, outsmart, outdate and replace us?
Should we risk losing control of our civilization?
👉 The letter has so far been signed by more than 27,500 people, including the author of several bestsellers such as Sapiens Yuval Noah Harari, Apple co-founder Steve Wozniak, Skype co-founder Jaan Tallinn and numerous artificial intelligence researchers such as Stuart Russell, Yoshua Bengio, Gary Marcus and Emad Mostaque." IndexHr
‼️ Personally, I would sign this letter and topics without thinking, because we are not even aware that at some point even that will be impossible.
👉 This is not a conspiracy theory, these are the facts today!
Also, take part in discusion and thank you. 🙏
Mr Duodu, thank you.
Also, mr Amin, can I kindly ask you not to leave URL and ypur email after every comment of yours, its not professional, really.
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The article has submited IEEE-TIT. Preprint manuscript is Post Shannon Information Theory.You can find it on this website. Please give a fair review.Thank you.
Anyone can evaluate it.English is not my native language, so I hope there is no ambiguity.
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Now a days, core subjects in Engineering such as electrical, electronics, chemical, mechanical and civil apart from computer science are getting least priority for option. These days everything is controlled, operated and done by software based instead going manually or making decision collectively. Most people are depending on what computer says to follow or understand in several fields. Will this continue or in what way does other subjects may or shall occupy a prominent position or importance on par with computer science?
The increasing prominence of computer science in various industries, including engineering, is due to its role in automation, data analysis, and efficiency enhancement. However, core engineering subjects such as electrical, electronics, chemical, mechanical, and civil engineering remain crucial. Computer science complements and enhances these disciplines rather than replacing them. Interdisciplinary collaboration, automation and control, simulation and modeling, hardware design, and domain-specific challenges are some areas where core engineering subjects retain their importance. The integration of computer science and engineering leads to advancements and innovations that benefit society. Recognizing the value of both fields and fostering interdisciplinary collaboration is essential for future progress.
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what is the overlap points of triz theory and the electrical and computer engineering and computer sciences? the innovation methodology triz theory can be searched by keyword "triz",and refer to methods related to tenological innovation stimuli methods, what is its applications and examples in electrical and computer engineering and computer sciences?
can you help me to find materials and books?especially about applications and examples.
I have made a living as a consultant for years using these techniques from TRIZ. (I independently invented Service Oriented Architecture [SOA] and Model Driven Design [MDD] to make practical the results generated.) Unfortunately, the major sticking point is "functional normalization", in other words identifying when a functional entity is performing the same function and/or quantifying how much similarity exists so a decision can be made on the best implementation to be used redundantly.
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New Thesis Idea
Dear Onengiyeofori Fenibo,
Choosing the best computer science project topic is critical to the success of any computer science student or employee. After all, the more engaging and interesting topic, the more likely it is that students or employees will be able to stay motivated and focused throughout the duration of the project. However, with so many options out there, it can be tough to decide which one is right for you.
To help you get started, we have compiled a list of best computer science project topics for students and employees. From machine learning algorithms to data mining techniques, these ideas are sure to challenge and engage you. And while thinking about computer science project topics, if you find it difficult to keep up with the latest trends, go for the best online course for Web Development. This is because the coursework is updated frequently, and there are always new things to learn.
In the field of academics, we need to get rid of obsolete ideas and focus on new innovative topics which are fast spreading their arms among the vast global audience. Computer Science students both in bachelors and in masters are studying the same topics and subjects from the past few years. Students don’t even have knowledge about new masters research topics. For project and thesis work also they are relying on outdated topics. Projects like school management system, library management system etc. are now out of date. Students should shift their focus to latest technologies which are highly in demand these days and future depend upon these. Here is the list of latest topics in Computer Science that you can choose and work for your project work or thesis and research:
List of few latest thesis topics in computer science is below:
• Thesis topics in data mining
• Thesis topics in machine learning
• Thesis topics in digital image processing
• Latest thesis topics in Internet of things (IOT)
• Research topics in Artificial Intelligence
• Networking can be chosen as a thesis topic in computer science
• Trending thesis topics in cloud computing
• Data aggregation as a thesis topics in Big Data
• Research topics in Software Engineering
Data Warehousing
Data Warehousing is the process of analyzing data for business purposes. Data warehouse store integrated data from multiple sources at a single place which can later be retrieved for making reports. The data warehouse in simple terms is a type of database different and kept isolated from organization’s run-time database. The data in the warehouse is historical data which is helpful in understanding business goals and make decisions for future prospects. It is a relatively new concept and have high growth in future. Data Warehouse provides Online Analytical Processing(OLAP) tools for the systematic and effective study of data in a multidimensional view. Data Warehouse finds its application in the following areas:
• Financial Sector
• Banking Sector
• Retail Services
• Consumer goods
• Manufacturing
So start working on it if you have knowledge of database and data modeling.
INTERNET OF THINGS(IOT)
Internet of Things(IoT) is a concept of interconnection of various devices, a vehicle to the internet. IOT make use of actuators and sensors for transferring data to and from the devices. This technology is developed for better efficiency and accuracy apart from minimizing human interaction with the devices. The example for this is home heating in some countries when the temperature drops done through motion sensors which automatically detect the weather conditions. Another example for this is the traffic lights which changes its colors depending upon the traffic. Following are the application areas of Internet of Things(IoT):
• Home Automation
• Healthcare
• Agriculture
• Transportation
• Manufacturing
• Environment
BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN IOT:-
• The secure and energy efficient data routing in the IOT based networks
• The secure channel establishment algorithm for the isolation of misdirection attack in the IOT
• The clock synchronization of IOT devices of energy efficient data communication in IOT
• The adaptive learning scheme to increase fault tolerance of IOT
• Mobility aware energy efficient routing protocol for Internet of Things
• To propose energy efficient multicasting routing protocol for Internet of Things
• The novel scheme to maintain quality of service in internet of Things
• Link reliable and trust aware RPL routing protocol for Internet of Things
• The energy efficient cluster based routing in Internet of Things
• Optimizing Multipath Routing With Guaranteed Fault Tolerance in Internet of Things
Many people are not aware of this concept so you can choose for your project work and learn something new.
Big Data
Big Data is a term to denote the large volume of data which is complex to handle. The data may be structured or unstructured. Structured data is an organized data while unstructured data is an unorganized data. Big data can be examined for the intuition that can give way to better decisions and schematic business moves. The definition of big data is termed in terms of three Vs. These vs are:
• Volume: Volume defines large volume of data from different sources
• Velocity: It refers to the speed with which the data is generated
• Variety: It refers to the varied amount of data both structured and unstructured.
Application areas:
• Government
• Healthcare
• Education
• Finance
• Manufacturing
• Media
• Sports
BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN BIG DATA :-
• Privacy preserving big data publishing: a scalable k-anonymization approach using MapReduce.
• Nearest Neighbour Classification for High-Speed Big Data Streams Using Spark.
• Efficient and Rapid Machine Learning Algorithms for Big Data and Dynamic Varying Systems.
• Disease Prediction by Machine Learning Over Big Data From Healthcare Communities.
• A Parallel Multi-classification Algorithm for Big Data Using an Extreme Learning Machine.
Thus you can prepare your project report or thesis report on this.
Cloud Computing
Cloud Computing is a comparatively new technology. It is an internet-based service that creates a shared pool of resources for consumers. There are three service models of cloud computing namely:
• Software as a Service(SaaS)
• Platform as a Service(PaaS)
• Infrastructure as a Service(IaaS)
Characteristics of cloud computing are:
• On-demand self-service
• Shared pool of resources
• Scalability
• Measured service
Below is the list of few latest and trending research topics in Cloud Computing :-
• To isolate the virtual side channel attack in cloud computing
• Enhancement in homomorphic encryption for key management and key sharing
• To overcome load balancing problem using weight based scheme in cloud computing
• To apply watermarking technique in cloud computing to enhance cloud data security
• To propose improvement green cloud computing to reduce fault in the network
• To apply stenography technique in cloud computing to enhance cloud data security
• To detect and isolate Zombie attack in cloud computing
The common examples of cloud computing include icloud from Apple, Google-based Services like Google Drive and many more. The field is very demanding and is growing day by day. You can focus on it if you have interest in innovation.
Semantic Web
Semantic Web is also referred to as Web 3.0 and is the next big thing in the field of communication. It is standardized by World Wide Web Consortium(W3C) to promote common data formats and exchange protocols over the web. It is machine-readable information based and is built on XML technology. It is an extension to Web 2.0. In the semantic web, the information is well defined to enable better cooperation between the computers and the people. In the semantic web, the data is interlinked for better understanding. It is different from traditional data sharing technologies.
It can be a good topic for your thesis or project.
MANET
MANET stands for mobile ad hoc network. It is an infrastructure-less network with mobile devices connected wirelessly and is self-configuring. It can change locations independently and can link to other devices through a wireless connection. Following are the various types of MANETS:
• Internet-based mobile ad hoc network(iMANET)
You can use various simulation tools to study the functionality and working of MANET like OPNET, NS2, NETSIM, NS3 etc.
In MANET there is no need of central hub to receive and send messages. Instead, the nodes directly send packets to each other.
MANET finds its applications in the following areas:
• Environment sensors
• Healthcare
• Home
BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN MANET :-
• Evaluate and propose scheme for the link recovery in mobile ad hoc networks
• To propose hybrid technique for path establishment using bio-inspired techniques in MANET’s
• To propose secure scheme for the isolation of black hole attack in mobile ad hoc networks
• To propose trust based mechanism for the isolation of wormhole attack in mobile ad hoc networks
• The novel approach for the congestion avoidance in mobile ad hoc networks
• To propose scheme for the detection of selective forwarding attack in mobile ad hoc networks
• To propose localization scheme which reduce faults in mobile ad hoc network
• The energy efficient scheme for multicasting routing in wireless ad hoc network
• The scheme for secure localization aided routing in wireless ad hoc networks
• The cross-layer scheme for opportunistic routing in mobile ad hoc networks
Just go for it if you have interest in the field of networking and make a project on it.
Machine Learning
It is also a relatively new concept in the field of computer science and is a technique of guiding computers to act in a certain way without programming. It makes use of certain complex algorithms to receive an input and predict an output for the same. There are three types of learning;
• Supervised learning
• Unsupervised learning
• Reinforcement learning
Machine Learning is closely related to statistics. If you are good at statistics then you should opt this topic.
Data Mining
Data Mining is the process of identifying and establishing a relationship between large datasets for finding a solution to a problem through analysis of data. There are various tools and techniques in Data Mining which gives enterprises and organizations the ability to predict futuristic trends. Data Mining finds its application in various areas of research, statistics, genetics, and marketing. Following are the main techniques used in the process of Data Mining:
• Decision Trees
• Genetic Algorithm
• Induction method
• Artificial Neural Network
• Association
• Clustering
BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN DATA MINING :-
• Performance enhancement of DBSCAN density based clustering algorithm in data mining
• The classification scheme for sentiment analysis of twitter data
• To increase accuracy of min-max k-mean clustering in Data mining
• To evaluate and improve apriori algorithm to reduce execution time for association rule generation
• The classification scheme for credit card fraud detection in Data mining
• To propose novel technique for the crime rate prediction in Data Mining
• To evaluate and propose heart disease prediction scheme in Data Mining
• Software defect prediction analysis using machine learning algorithms
• A new data clustering approach for data mining in large databases
• The diabetes prediction technique for Data mining using classification
• Novel Algorithm for the network traffic classification in Data Mining
• Data Mining helps marketing and retail enterprises to study customer behavior.
• Organizations into banking and finance business can get information about customer’s historical data and financial activities.
• Data Mining help manufacturing units to detect faults in operational parameters.
• Data Mining also helps various governmental agencies to track record of financial activities to curb on criminal activities.
• Privacy Issues
• Security Issues
• Information extracted from data mining can be misused
Artificial Intelligence
Artificial Intelligence is the intelligence shown by machines and it deals with the study and creation of intelligent systems that can think and act like human beings. In Artificial Intelligence, intelligent agents are studied that can perceive its environment and take actions according to its surrounding environment.
Goals of Artificial Intelligence
Following are the main goals of Artificial Intelligence:
• Creation of expert systems
• Implementation of human intelligence in machines
• Problem-solving through reasoning
Application of Artificial Intelligence
Following are the main applications of Artificial Intelligence:
• Expert Systems
• Natural Language Processing
• Artificial Neural Networks
• Robotics
• Fuzzy Logic Systems
Strong AI – It is a type of artificial intelligence system with human thinking capabilities and can find a solution to an unfamiliar task.
Weak AI – It is a type of artificial intelligence system specifically designed for a particular task. Apple’s Siri is an example of Weak AI.
Turing Test is used to check whether a system is intelligent or not. Machine Learning is a part of Artificial Intelligence. Following are the types of agents in Artificial Intelligence systems:
• Model-Based Reflex Agents
• Goal-Based Agents
• Utility-Based Agents
• Simple Reflex Agents
Natural Language Processing – It is a method to communicate with the intelligent systems using human language. It is required to make intelligent systems work according to your instructions. There are two processes under Natural Language Processing – Natural Language Understanding, Natural Language Generation.
Natural Language Understanding involves creating useful representations from the natural language. Natural Language Generation involves steps like Lexical Analysis, Syntactic Analysis, Semantic Analysis, Integration and Pragmatic Analysis to generate meaningful information.
Image Processing
Image Processing is another field in Computer Science and a popular topic for a thesis in Computer Science. There are two types of image processing – Analog and Digital Image Processing. Digital Image Processing is the process of performing operations on digital images using computer-based algorithms to alter its features for enhancement or for other effects. Through Image Processing, essential information can be extracted from digital images. It is an important area of research in computer science. The techniques involved in image processing include transformation, classification, pattern recognition, filtering, image restoration and various other processes and techniques.
Main purpose of Image Processing
Following are the main purposes of image processing:
• Visualization
• Image Restoration
• Image Retrieval
• Pattern Measurement
• Image Recognition
Applications of Image Processing
Following are the main applications of Image Processing:
• UV Imaging, Gamma Ray Imaging and CT scan in medical field
• Transmission and encoding
• Robot Vision
• Color Processing
• Pattern Recognition
• Video Processing
BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN IMAGE PROCESSING :-
• To propose classification technique for plant disease detection in image processing
• The hybrid bio-inspired scheme for edge detection in image processing
• The HMM classification scheme for the cancer detection in image processing
• To propose efficient scheme for digital watermarking of images in image processing
• The propose block wise image compression scheme in image processing
• To propose and evaluate filter based on internal and external features of an image for image de noising
• To improve local mean filtering scheme for de noising of MRI images
• To propose image encryption base d on textural feature analysis and chaos method
• The classification scheme for the face spoof detection in image processing
• The automated scheme for the number plate detection in image processing
Bioinformatics
Bioinformatics is a field that uses various computational methods and software tools to analyze the biological data. In simple words, bioinformatics is the field that uses computer programming for biological studies. It is the current topic of research in computer science and is also a good topic of choice for the thesis. This field is a combination of computer science, biology, statistics, and mathematics. It uses image and signal processing techniques to extract useful information from a large amount of data. Following are the main applications of bioinformatics:
• It helps in observing mutations in the field of genetics
• It plays an important role in text mining and organization of biological data
• It helps to study the various aspects of genes like protein expression and regulation
• Genetic data can be compared using bioinformatics which will help in understanding molecular biology
• Simulation and modeling of DNA, RNA, and proteins can be done using bioinformatics tools
Quantum Computing
Quantum Computing is a computing technique in which computers known as quantum computers use the laws of quantum mechanics for processing information. Quantum Computers are different from digital electronic computers in the sense that these computers use quantum bits known as qubits for processing. A lot of experiments are being conducted to build a powerful quantum computer. Once developed, these computers will be able to solve complex computational problems which cannot be solved by classical computers. Quantum is the current and the latest topic for research and thesis in computer science.
Quantum Computers work on quantum algorithms like Simon’s algorithm to solve problems. Quantum Computing finds its application in the following areas:
• Medicines
• Logistics
• Finance
• Artificial Intelligence
The list is incomplete as there are a number of topics to choose from. But these are the trending fields these days. Whether you have any presentation, thesis project or a seminar you can choose any topic from these and prepare a good report.
Hope that one gives you a close feel.
Wasswa Shafik
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I am Student in EMBA in second semester, I have Bachelor in Computer science but I have more than 10 year experience in Finance and Accounting, I would like to connect my EMBA Thesis with Finance and Accounting topic, What would be your suggestion for me?
Further to my above answer, I would like elaborate to use DecisionMentor mobile app
Decision Problem: Appropriate EMBA Thesis Topic for me
Options (Alternatives):
1. Appropriate Decision Analysis framework (Integrated with Accounts & Finance, in addition to Technical, Market and HR) - Looking into variety of Multiple Criteria Decision Analysis Tools / Theories available
2. A Case of Digital Transformation: In an existing Business (you may take a case from your own company)
3. Future of Accounts and Finance Professionals with Emerging AI Tools
(or if you have any of your topic of your passion, consider those)
Criteria (Factors) to consider while choosing:
1. My interest
3. Knowledge enhancement
4. Skill Enhancement
Now, it would be easy for you to use DecisionMentor mobile app available at:
The DecisionMentor mobile app will help you to compare your criteria to generate criteria weight, then you can compare each options with the Criteria.
This process will give insight to your decision problem, Decision will be Yours, which ever topic option comes at top in ranking.
Enjoy using DecisionMentor and learn new skill !!
Best wishes,
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Hi there,
I am seeking a reliable data source or database that can provide current and past affiliations for authors of scientific publications.
While I am familiar with platforms such as Scopus and Web of Science, I am unable to use them due to the requirement of an institutional subscription or the need to search for authors individually. Ideally, I am looking for a database where I can extract information on all authors affiliated with a specific institution.
My research is focused on computer science, so a data source that specializes in this field would be perfect, but I'm open to any suggestions you might have. Thanks!
Big thanks to both of you Anne-Katharina Weilenmann and Alexander Schniedermann . Will look into these options shortly ^^
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I am Ayah Soufan, a 3rd-year Ph.D. researcher at Strathclyde University interested in designing systems to help scholars conduct literature reviews. If you are a Master's student in Computer Science or any related field, working on your literature review of your MSc project, and if you are searching for, reading, and making sense of papers on your topic, I would love to speak to you! This study will take place on Zoom for up to 1.5 hour with a £20 compensation (online voucher). Please fill out this survey: https://lnkd.in/e_vq5Kci Once your eligibility for the study is determined, I will contact you as soon as possible to set a date\time that suits you for the study session.
Dear Scholar,
I appreciate your interest. I have already volunteered for three research projects and authored three, excluding the analytical research that I am working on now. Among the mentioned, I conducted Literature Review through an LRM a few times. I am a Freshman in Computer Science. I was wondering about joining the initiation.
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One of my friend completed his bachelor degree in mechanical engineering. But now likes to join in computer science engineering related master degree program.
Is it possible to do masters in computer science related courses. If yes, please suggest the courses. Thanking you...
Dear, it's not possible to do master in computer science after mechanical graduate.
But heay try to robotics, automobile and other computer related course which is the available in Mechanical Engineering domain.
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Although, the rapid development of AI I couldn’t find AI application for designing figures for engineering or computer science
Artificial intelligence design is the new hype. To fully automate their processes, many IT companies are moving toward artificial intelligence today. They do this because they are aware that technologies that can significantly reduce the amount of work required of humans will rule the future.
Regards,
Shafagat
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Psychoanalysis is the branch of Linguistics in the Humanities that gave birth to Artificial Intelligence in Computer Science. However, there should be a link of research between the scholars from both disciplines so as to further open another trend of researches on limitations of Robotics to preform duties of humans.
Imagine a primitive man who sees a robot and who wants to figure out what the robot is thinking. This is psychoanalysis, and "what the robot is thinking" is supported by artificial intelligence
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Hello fellow researchers. I am pursuing a research career along with a full time Software Engineering Job. Does anyone have pointer on how they handled being in a similar situation. Any help would be appreciated.
Here are the action items I want to explore:
1- How do you balance work and research?
2- How do you publish, list of publication ( Computer Science AI related)?
3- How can I work as an independent researcher and collaborate?
A growing number of people in academia combine expertise in programming with an intricate understanding of research. Although this combination of skills is extremely valuable, these people lack a formal place in the academic system. This means there is no easy way to recognise their contribution, to reward them, or to represent their views.
Without a name, it is difficult for people to rally around a cause, so we created the term Research Software Engineer. We are now working to raise awareness of the role and bring the community together.
Regards,
Shafagat
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I'm pursuing Master's in Computer Science. My area of expertise is software development (web full stack).
I am new to research domain and processes. I'm trying to search for a research topic but having a hard time narrowing down to research gap.
I'm exploring following areas in NLP
1. Dialogue and Conversational agents
2. Knowledge graphs
3. Low resource & domain adaptation by transfer learning
4. Multi-lingual NLP
Apart from NLP I'm looking for
1. Microservices architecture patterns
2. Component based software frameworks
All I'm finding online are survey papers. Am I using too generic keywords? Can someone help in how to narrow down to a topic from domain/ research area?
The American University Laboratories For Electrical Engineering Part 1
You can find a computer section.
Use something you find interesting.
Thank you
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I'm pursuing Ms in Computer science. I'm search for research topic.
I've come across following areas. Can someone review and let me know if these can be research candidates?
1. Comparison of different full stack frameworks
2. Progressive web applications
3. Security in Full stack applications
Also, can someone help me narrow down to a topic in these?
It's great to see that you are considering various research topics related to full stack development. The areas you've mentioned are indeed relevant and hold potential for research. Let me provide a brief overview and some suggestions to help you narrow down the topics:
* Comparison of different full stack frameworks: Studying the features, performance, and trade-offs of various full stack frameworks can be insightful. Instead of a generic comparison, you could focus on specific aspects or challenges, such as the ease of scalability, adaptability to emerging technologies, or how well these frameworks support serverless architectures.
* Progressive web applications (PWAs): PWAs are an exciting area of research as they bring the best of both web and mobile applications. You could study the factors that influence the adoption of PWAs, explore novel approaches to optimize performance and user experience, or investigate the challenges faced in integrating PWAs with emerging technologies like augmented reality or the Internet of Things.
* Security in Full stack applications: Security is always a critical concern in any development process. Research in this area could focus on identifying and addressing common security vulnerabilities in full stack applications, developing new techniques to ensure data privacy and protection, or examining best practices for secure authentication and authorization.
To narrow down your topic, consider reflecting on your personal interests, the relevance of the topic to the industry, and the potential impact of your research. Choose a topic that you find engaging and that can contribute to the field of full stack development.
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I enrolled for a PhD Programme in Computer Science. For my research work I am looking for a topic to choose which could make an impact and solve a Business problem.
my area of interest are Data Science, Ecommerce, AL, ML Sensor technology.
Great to hear that you are pursuing a PhD in Computer Science and looking for a research topic . Research topics that can make an impact and solve a business problem include predictive analytics for e-commerce, anomaly detection in sensor data, fraud detection in e-commerce transactions, personalized products, optimizing supply chain, and optimizing logistics. These are just a few examples to consider, and you can explore and refine these topics based on your specific interests and goals. Make sure to consult with your advisor and industry experts to ensure that your research is impactful and relevant to the business problem you are trying to solve. Good luck!
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Seeking expert advice from academia. Both my bachelor’s and master’s are in the field of computer science. I have research, industry, and entrepreneurship experiences related to that field only. However, I would like to explore something new. I have always been fascinated by astronomy and astrophysics. Would it increase my chance for a Ph.D. if I have a publication relevant to the new field? Or are there other opportunities that I don’t know about yet? Thank you!
Hi Nishargo Nigar Remember that if you take your breadwinning work out of computers you can expect a massive drop in income. Fortunately, re your interests the space industry is on an upswing, and you have enough already for anyone re computers.
To your specific question, I doubt that would it increase your chance for a Ph.D. if you have a publication relevant to the new field, at least in US and Europe. Having working experience in space industry might help a little and they use a lot of computer people. Mainly I would think just pursue the PhD and don't over-worry about side efforts to encourage it.
Enjoyed my visit to Hamburg.
Karl
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The concept of formal system and/or its properties is present frequently in many practical and theoretical components of computer science methods, tools, theories, etc.
But it is frequent too, finding some non rigorous interpretations of formal. For example, in several definitions of ontology, formal is understood as something that "computer can understand".
Does the computer science specialist, BSc, need to know that concept? Are it and its properties useful for them?
For me some basic knowledge of formal systems is essential for undergraduate CS students, as this is a necessary part of the scientific education.
If not, you might still learn a lot about software construction, but you wouldn't know nor understand its bedrock.
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I need a Data visualization book for undergraduate students in computer science college.
They can learn the fundamentals, principles, techniques of data visualization
Data Visualization is incomplete without consideration of Tufte.
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Good day, Dear Colleagues!
Anyone interested in discussing this topic?
The tandem of Mathematics and Computer Science is vital for the development of AI. Mathematics provides the theoretical foundation, while Computer Science provides the practical tools to implement AI algorithms. By combining these two disciplines, researchers and practitioners can create AI systems that can perform increasingly complex tasks, and help solve some of the most challenging problems facing our society.
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Hello,
I graduated with a Master's degree in machine learning and signal processing.
I'm in the first year of my Ph.D. in computer science. I have some difficulties finding topics on smart cities.
Do you have some suggestions or ideas?
Yes, here are some potential research topics on smart cities that you could explore:
1. Smart transportation: Analyzing data from sensors to optimize traffic flow, reduce congestion, and improve transportation infrastructure.
2. Smart energy management: Developing algorithms and systems for efficient energy distribution and consumption in urban environments.
3. Smart waste management: Developing systems to optimize waste collection and disposal through sensor data and predictive analytics.
4. Smart healthcare: Developing systems to monitor and analyze health data to identify health trends and provide early warning of disease outbreaks.
5. Smart public safety: Developing systems to enhance public safety through real-time data analysis, surveillance, and response.
6. Smart buildings: Developing algorithms and systems to optimize energy use, temperature control, and other building management functions in real-time.
7. Social media analytics: Analyzing social media data to identify trends and patterns in urban communities, and to develop social interventions and programs to address community issues.
8. Urban agriculture: Developing systems for sustainable urban agriculture, including hydroponics, vertical farming, and community gardens.
9. Citizen engagement: Developing systems to engage citizens in the design, implementation, and evaluation of smart city programs and initiatives.
10. Smart tourism: Developing systems to enhance the visitor experience, including real-time travel information, augmented reality, and personalized recommendations.
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Quantum computing is fundamentally a synergistic combination of fields from quantum physics, classical information theory, and computer science. As a discipline to evolve, computationally intensive systems came into existence in the late 1990s. Quantum-inspired computational intelligence refers to an emergent field of research that concentrates on applying the principles of quantum computing.
source: Applied Quantum Computing (bonviewpress.com)
Eduard Babulak Yes, the usage of quantum computing is predicted to help enhance artificial intelligence, humanoid robots, automation, and geographic research. Quantum computing ideas can be used to these domains to possibly increase the performance and efficiency of different systems. However, it is vital to highlight that quantum computing is still in its infancy, and more study is required to fully realize its promise in these disciplines.
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I want to know about CHAT GPT. What type of data we can collect using Chat GPT and how to use it.
Thank you.
You can find some details about OpenAI, including chat gpt, on the OpenAI website: https://platform.openai.com/docs/introduction/key-concepts.
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I am running a User Experiment to learn how to design better user interfaces to help researchers conduct literature reviews. I am interested in recruiting BSc, MSc, or Ph.D. students with Computer Science or related field backgrounds. The study will be conducted via Zoom for 1 to 1.5 hours with compensation.
If you are interested, please fill out this form or forward it to your students who might be interested—much appreciated!
Seems like the survey form already expired. And....A rather sad example of user interfaces in itself. However, if you're trying to learn more about user interfaces I strongly recommend looking outside of the Computer Science field.
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Hello members,
I am currently in the process of developing my PhD proposal in computer sciences. My research interests lie in the areas of Artificial Intelligence, Data Sciences, and Blockchain. I am seeking some feedback and ideas for potential research topics that I can explore within these domains.
I would appreciate if you could share your thoughts and insights on the current challenges and opportunities within the field. It would be a great help for me to understand the current state of research and identify potential gaps that I can focus on in my proposal.
Kind regards.
Mk.
I recommend checking our Perspective paper at :
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I need reviewer for Taylor edited book from Computer Science area from Canada or USA or UK and or Australia University. URGENT!
Thank you but its outdated.
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AI, machine learning are dynamical computer science platform nowadays, is there any way to connect chaos and AI, machine learning. Some researchers are doing the research about the mentioned topic. Anyone can you give the research papers for my understanding for further studies.
Chaos theory and artificial intelligence are directly connected...
Formal models of such a connection are given in the book (the concepts of "Creative Stirring / Mixing Layer" and Inductor Space, i.e. the emergence of generalized (mental) entanglement)
More details here
Practical applications of chaos theory and artificial intelligence
Good luck to you,
Yurii
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Good afternoon,
I have prepared an article that performs a literature review on the concept of Digital Twin. Since the doctoral program in which I am is a program based on the compendium of publications, it is necessary that all the articles that I do are published in a journal that appears in the latest list published by the Journal Citation Reports (SCI and / or SSCI) or SCOPUS. In addition, at least one of them must be in the first or second quartile of its category. Therefore, I would like to try to get this article published in one that is in the Q1 quartile, so that I can take this burden off my shoulders. For now I have found the following:
IEEE
• IEEE Access: Telecommunications – Scie, Computer Science, Information Systems – Scie (Q1); Engineering, Electrical & Electronic – Scie (Q2).
ACM
• ACM Computing Surveys: Computer Science, Theory & Methods – Scie (Q1).
Elsevier
• Expert Systems with Applications: Operations Research & Management Science – Scie (Q1); Computer Science, Artificial Intelligence – Scie (Q1); Engineering, Electrical & Electronic – Scie (Q1).
• Future Generation Computer Systems: Computer Science, Theory & Methods – Scie (Q1).
• Engineering Applications Of Artificial Intelligence: Computer Science, Artificial Intelligence – Scie (Q1); Engineering, Electrical & Electronic – Scie (Q1); Engineering, Multidisciplinary – Scie (Q1); Automation & Control Systems – Scie (Q1).
• Artificial Intelligence: Computer Science, Artificial Intelligence – Scie (Q1).
• Journal of Computational Science: Computer Science, Interdisciplinary Applications – Scie (Q2); Computer Science, Theory & Methods – Scie (Q1).
• Advances in Engineering Software: Computer Science, Interdisciplinary Applications – Scie (Q2); Computer Science, Software Engineering – Scie (Q1); Engineering, Multidisciplinary – Scie (Q1).
• Decision Support Systems: Operations Research & Management Science – Scie (Q1); Computer Science, Artificial Intelligence – Scie (Q1); Computer Science, Information Systems – Scie (Q1).
• Information and Software Technology: Computer Science, Software Engineering – Scie (Q1); Computer Science, Information Systems – Scie (Q2).
• Journal of Industrial Information Integration: Computer Science, Interdisciplinary Applications – Scie (Q1); Engineering, Industrial – Scie (Q1).
• Journal of Network and Computer Applications: Computer Science, Interdisciplinary Applications – Scie (Q1); Computer Science, Hardware & Architecture – Scie (Q1); Computer Science, Software Engineering – Scie (Q1).
MDPI
• Applied Sciences: Chemistry, Multidisciplinary – Scie (Q3); Materials Science, Multidisciplinary – Scie (Q3); Physics, Applied – Scie (Q2); Engineering, Multidisciplinary – Scie (Q2).
• Future Internet: Computer Science, Information Systems (Q2).
• Applied System Innovation: Telecommunications – Esci (Q3); Computer Science, Information Systems – Esci (Q3); Engineering, Electrical & Electronic – Esci (Q3).
Does anyone have a recommendation for any other? Is it advisable to avoid generic journals? The more categories the journals deal with, the better?
Thank you very much in advance.
One way is to use the publication recommender offered by different publishers. You can search using the title and abstract to get a list of suitable journals. However, as you have already a written article and that too a review paper, you can figure out directly with your references. Digtial twins have applications in many areas, and therfore it depends which area you are working on. One excellent journal is IEEE Transactions on Industrial Informatics.
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You may often find them on the top side of Intel's CPUs, such as i7 or Xeon. My assumption is that they are need for substrate electrical testing during production process, but i couldn't find any confirmation of that.
They are alternative contacts to certain pins for testing. The idea is to avoid signal interference with high speed processors.
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Hello, please what are some research areas/topics in the field of Information Technology NOT Computer Science for PhD thesis?
Dear,
Today , we have a lot of topics: The capital topics for research in IT can be listed below: Quantum Computing, artificial Intelligence. These topics will be good for the future. If you are planning to become a staple in IT, you should take a look also in Cybersecurity,computational science,complex systems,cloud computing & virtualization,Biometrics and Conformance testing.
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Which software is best for making high-quality graphs? Origin or Excel? Thank you
origin
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Hello dear community,
Is Global Journal of Computer Science & Technology predatory.
Regards,
The papers are edited pretty professional and look misleadingly real. However, the publisher is suspect, see for example:
The same is true, when looking at the particular journal itself (https://computerresearch.org/index.php/computer ):
-If you scroll down, they mention matrices while they mean metrics
-If you scroll down further you see a sad collection of so-called misleading metrics (see also https://beallslist.net/misleading-metrics/ ) like ESJI, GIF, CiteFactor etc. often used by predatory journals/publishers
-No serious indexing (like Scopus, WoS etc.)
-Contact info looks fake. Most likely a virtual office (at best), all this to hide their true origin
So, I would say avoid.
Best regards.
PS. I suspect a relation with another dubious publisher “Dama Academic Scholary & Scientific Research Society” (https://damaacademia.com ). The well… mysterious sounding phrase in the mission “We intend to frequently modernize our dexterity and cultivate our standards to deliver exceptional quality journals in all fields of expertise.” can be found in both of them https://computerresearch.org/index.php/computer/about and https://damaacademia.com/mission/ The same is true for the sentence which can be found (using Google) here https://computerresearch.org/index.php/computer/about “is a premier research paper publisher with a global reputation for publishing quality journals and services which cover all streams”
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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.
MS Windows OS
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I am doing MPhil in Computer Science and Software Engineering is my Specialization. I am trying to choose a domain/ topic to work on for my Thesis. I am otherwise a good student but not able to narrow down what domain, field or area I should choose where I can have oppertunity for further work in future as well.
Software Engineering is a branch that deals with the development and evolution of software products by employing certain methodologies and well-defined scientific principles. For developing a software product certain processes need to be followed and outcome of which is an efficient and authentic software product. The software is a group of executable program code with associated libraries. Software designed to satisfy a specific need is known as Software Product. It is a very good topic for master’s thesis, project, and research. There are various topics in Software Engineering which will be helpful for M.Tech and other masters students write their software project thesis.
Regards,
Shafagat
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Hello, I am a new research scholar in Computer Science, having an interest in Recommender systems and reinforcement Learning. Can someone suggest any research topics/areas in recommender systems ?
please check the Domain(area) Cloud computing & Data Mining easiest way of domain..
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Hello,
I am asking for your help in suggesting ISI journals that might be interested in publishing a dentistry focused paper (orthodontics) and social media (tweets content and sentiment analysis), we analyzed only Arabic language tweets.
we tried general dentistry journals they suggested ortho journals, the ortho journals suggested computer science or similar journals, general social media and telemedicine journals suggested ortho journals.
It feels like we are running around in circles.
Thank you.
If you have access to Journal Citation Reports (JCR), it has feature named "manuscript matcher" which may be useful, but you can also look through the Dentistry, Oral Surgery & Medicine category in JCR.
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Please elaborate latest Research topics in Networks for Masters level Computer Science Student?
Dear Mubashir Iqbal,
During the SARS-CoV-2 (Covid-19) coronavirus pandemic, the scale of cybercriminal and hacking activities on the Internet increased. Therefore, I propose the following research topic for a thesis written in the field of computer networks: Improving security, procedures and techniques to protect sensitive information residing in internal and external computer networks connected to the Internet. Within the framework of this topic, the dominant trends of the said process of improving the cyber security of sensitive information in recent years through the application of new technologies typical of the current fourth technological revolution and technologies categorised as Industry 4.0 (such as artificial intelligence, machine learning, Blockchain, Big Data Analytics, etc.) can be examined.
Best regards,
Dariusz Prokopowicz
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Is it mandatory to complete PhD degree to review a research paper?
It is not mandatory to complete Ph.D. degree to act as reviewer. However, it is mandatory that the person should have published at least one article in a reputed international journal. The Scopus ID of the reviewer should be available. Journal editors usually pick up reviewer names from the publications in the same field of research. Editors will not consider a person without any publication to his credit.
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Well,
I am a very curious person. During Covid-19 in 2020, I through coded data and taking only the last name, noticed in my country that people with certain surnames were more likely to die than others (and this pattern has remained unchanged over time). Through mathematical ratio and proportion, inconsistencies were found by performing a "conversion" so that all surnames had the same weighting. The rest, simple exercise of probability and statistics revealed this controversial fact.
Of course, what I did was a shallow study, just a data mining exercise, but it has been something that caught my attention, even more so when talking to an Indian researcher who found similar patterns within his country about another disease.
In the context of pandemics (for the end of these and others that may come)
I think it would be interesting to have a line of research involving different professionals such as data scientists; statisticians/mathematicians; sociology and demographics; human sciences; biological sciences to compose a more refined study on this premise.
Some questions still remain:
What if we could have such answers? How should Research Ethics be handled? Could we warn people about care? How would people with certain last names considered at risk react? And the other way around? From a sociological point of view, could such a recommendation divide society into "superior" or "inferior" genes?
What do you think about it?
=================================
Note: Due to important personal matters I have taken a break and returned with my activities today, February 13, 2023. I am too happy to come across many interesting feedbacks.