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Structure Your Paper

Learn how to structure your paper for publication. IEEE has put together some tips and best practices for what should be included in your conference paper.

Your paper title should be specific, concise, and descriptive. Avoid using unnecessary words such as “new” or “novel”. Include keywords that will help a reader find your paper.

Provide a concise summary of the research conducted. Include the conclusions reached and the potential implications of those conclusions. Your abstract should also:

  • consist of a single paragraph up to 250 words, with correct grammar and unambiguous terminology;
  • be self-contained with no abbreviations, footnotes, references, or mathematical equations;
  • highlight what is unique in your work;
  • include 3-5 keywords or phrases that describe the research, with any abbreviations clearly defined,  to help readers find your paper.

First Footnote

Funding footnote.

If the research reported in your paper was supported by a funding source, include the funder’s name and grant information in a footnote on the first page of the paper.

Human and animal research statements

For papers reporting on research involving human subjects or animals, complete and include one of the following human/animal research statements in a footnote on the first page of the paper:

  • Papers That Are Reporting on Human/Animal Research and Have Review Board Approval:   This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by (Name of Review Board or Committee) (if provided under Application No. xx, and performed in line with the (Name of Specific Declaration (if applicable/provided)).
  • Papers That Are Reporting on Human/Animal Research and Are Exempt From Review Board Approval: This work involved human subjects or animals in its research. The author(s) confirm(s) that all human/animal subject research procedures and protocols are exempt from review board approval.

Refer to the IEEE’s policy on Research on Human and Animal Subjects .


Help the reader understand why your research is important and what it is contributing to the field.

  • Start by giving the reader a brief overview of the current state of research in your subject area.
  • Progress to more detailed information on the specific topic of your research.
  • End with a description of the exact question or hypothesis that your paper will address.

Also state your motivation for doing your research and what it will contribute to the field.

Formulate your research question. It should include:

  • a detailed description of the question;
  • the methods you used to address the question;
  • the definitions of any relevant terminology;
  • any equations that contributed to your work.

The methods section should be described in enough detail for someone to replicate your work.

Results and Discussion

Show the results that you achieved in your work and offer an interpretation of those results. Acknowledge any limitations of your work and avoid exaggerating the importance of the results.

Summarize your key findings. Include important conclusions that can be drawn and further implications for the field. Discuss benefits or shortcomings of your work and suggest future areas for research.


You can recognize individuals who provided assistance with your work, but who do not meet the definition of authorship . The acknowledgments section is optional.

Provide citation information for all the previous publications referred to in your paper. Cite only those references that directly support your work.


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IEEE Publications Dominate Latest Citation Rankings

Each year, the Journal Citation Reports® (JCR) from Web of Science Group examines the influence and impact of scholarly research journals. JCR reveals the relationship between citing and cited journals, offering a systematic, objective means to evaluate the world’s leading journals. The 2022 JCR study, released in June 2023, reveals that IEEE journals continue to maintain rankings at the top of their fields.

Structure Your Article

Learn about the elements that organize a typical IEEE journal article and how to compose your work to help communicate your ideas more clearly.

The article’s title should be specific, concise, and descriptive to help readers decide if they should read the full article.  Use keywords and short phrases to describe the article’s content in as few words as possible.  Avoid terms such as “new” or “novel” since the reader already knows that your research is new and worthy of publication.

Follow the IEEE authorship guidelines when determining who belongs on the author list. 

You may publish your name in your native language, alongside the English version of your name, in the author list if you wish.  The guidelines below are for Chinese, Japanese, and Korean characters. All other native language names should be submitted via Unicode characters. In your article’s cover letter, indicate that the article includes author names in native languages.

Be sure to carefully check the rendering of your name in your article during the proof stage before article publication.

Chinese, Japanese, and Korean characters

The following font styles will be used when rendering Chinese, Japanese, or Korean characters in the final publication. Use the appropriate font for your native language to avoid potential errors.

  • Simplified Chinese: SongMT
  • Traditional Chinese: SungMT
  • Japanese: MS Mincho
  • Korean: Batang

Use Microsoft Word’s Insert Symbols feature to add the correct characters in parentheses after the name of each author who would like to have their name shown in their native language. Use the standard font listed above to ensure accuracy.

When writing in LaTeX, provide the CJK Ascii Unicode for Chinese (traditional or simplified), Japanese, or Korean.

Your abstract should provide a brief summary of the research conducted, the conclusions reached, and the potential implications of those conclusions.

A strong abstract will also:

  • Consist of a single paragraph up to 250 words, with correct grammar and unambiguous terminology
  • Be self-contained; without abbreviations, footnotes, references, or mathematical equations
  • Highlight what is novel in your work
  • Include 3-5 keywords or phrases that describe the research, with any abbreviations clearly defined, to help readers find your article

Most authors write the abstract last and edit it multiple times before article publication to ensure it accurately captures the entire article.

IEEE recommends that you do not include mathematical symbols in your article title or abstract because they may not display properly.

Using the right keywords in your article can make your article more easily and reliably discoverable—which leads to a broader readership for your article. For best results, define any abbreviations and, where possible, strive to use standardized keywords. Using the IEEE Thesaurus  can help you find the best standardized keywords to fit your article. Use the  thesaurus access request form  for free access to the  IEEE Thesaurus .   

Back to Top

First Footnote

The first footnote is not numbered. All other footnotes in the article are numbered consecutively. Do not use asterisks or daggers. The first footnote (or the author affiliation paragraph) is made up of at least three paragraphs.   

First paragraph

The first paragraph consists of:

  • all IEEE-provided received, revised, and accepted dates of the article, as well as the two additional online published dates (i.e., first and final publication dates)
  • author-provided name(s) of the corresponding author(s) (as well as names of equally contributed authors or co-first authors, if applicable)
  • author-provided full financial support for the work in the article (listed here and not in the Acknowledgment)
  • author-provided   information of full or partial prior presentation of an article (referred to as a “paper”) at a conference, including the DOI of the prior presentation, which links to the conference version and not a preprint; if an article is a thesis or part of a thesis or dissertation, this should be noted in the last sentence of the first paragraph
  • Articles That Are Reporting on Human/Animal Research and Have Review Board Approval: This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by (Name of Review Board or Committee) (if provided under Application No. xx, and performed in line with the (Name of Specific Declaration (if applicable/provided)).
  • Articles That Are Reporting on Human/Animal Research and Are Exempt From Review Board Approval: This work involved human subjects or animals in its research. The author(s) confirm(s) that all human/animal subject research procedures and protocols are exempt from review board approval.

Refer to the IEEE’s policy on Research on Human and Animal Subjects .

Second paragraph

The second paragraph consists of author affiliations, including author-provided department, university or corporation, city, state, province or prefecture (if provided), postal code, and country for each author. Note that the country and corresponding author’s e-mail address must be included. All authors may include their e-mail addresses, which would be separated by semicolons.

See IEEE Editorial Style Manual for Authors for detailed examples of author affiliation types for two or more authors, changed affiliation, retired author, deceased author, and consultant.

Third paragraph

The third paragraph consists of an IEEE-provided notice if the article has supplementary materials and/or color figures in the online version.


The introduction section includes a review of the existing literature to position your research within the broader scientific field and to show the novelty of your work.  The introduction should also describe the question you’re trying to answer with your research and why that question is important to the field.


The methodology section is a straightforward description of what you did in your research and how you did it.  A detailed methodology section will make your article reproducible by other researchers, which helps others trust and build upon your work.

Ensure your mathematical equations and formulas display correctly in your published article by following either the IEEE Math Typesetting Guide for LaTeX Users or the IEEE Math Typesetting Guide for MS Word Users .

The results section describes the results you obtained in your research.  Include figures and tables as appropriate to illustrate your results. Figures can show data trends or other visual information. Tables are best to use when the exact values are important.

In the discussion section, describe what your results mean and how they are an important contribution to the research field.

The conclusion section can highlight potential broader implications of your work and areas that need further study.  Be careful not to inflate your findings.

The reference section is important because all scientific and technical research builds upon previous work. References help give proper credit and attribution to that preceding body of work.  References also support and validate your hypothesis.  Be sure to only cite references that directly support your work. Inflating citations by adding unnecessary references is considered a breach of publishing ethics.


The acknowledgments section is where you can recognize and thank those who have helped you publish this article. Here you can thank your funder, someone who supported you during the research project, or the anonymous reviewers who evaluated the article.  The Acknowledgements section is optional but quite common.

Refining the Use of English in Your Article

Communicate your work clearly. If you are not fully proficient in English, consider using an English language editing service before submitting your article. An expert editing service can help you refine the use of English in your article, so you can communicate your work more effectively.

The use of an editing service is paid for by the author. It does not guarantee acceptance in an IEEE publication.

IEEE authors are eligible for discounts at the following language editing services:

  • American Journal Experts : 10% discount
  • Enago : 30% discount ( review Enago’s services for authors in Chinese )

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proceedings of the ieee cover march 2024

Regular Papers

Volume 112, Issue 3

Scanning the Issue

An overview of advancements in multimotor drives: structural diversity, advanced control, specific technical challenges, and solutions.

By C. Gong, Y. R. Li, and N. R. Zargari

This article reviews the advances in multimotor drives from multiple perspectives and provides insights into future directions and opportunities.

Internet-Based Social Engineering Psychology, Attacks, and Defenses: A Survey

By T. T. Longtchi, R. Montañez Rodriguez, L. Al-Shawaf, A. Atyabi, and S. Xu

This article systemizes Internet-based social engineering attacks through a psychological lens and investigates why current defenses have limited success. It also provides a roadmap for future research studies.

Drawing the Boundaries Between Blockchain and Blockchain-Like Systems: A Comprehensive Survey on Distributed Ledger Technologies

By B. Bellaj, A. Ouaddah, E. Bertin, N. Crespi, and A. Mezrioui

This article aims to establish clearer distinctions between different categories within the distributed ledger technology ecosystem by providing a structured framework.

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Electric Vehicles

Abstract – This paper gives a mini overview of the recent research and works in the sector of electric vehicles. The paper describes the main part of electric vehicles and their work. The major components are battery, motor, charger, steering, and braking. The paper finally shows basic concepts of electric vehicles with working. There are electric buses in the main focus of this paper. The solar system also can be used for electric busses and this is described in this paper.

Keywords – Electric vehicle, motor, braking system, battery systems, hybrid system


Electrical vehicle (EV) based on electro mechanical system. No, any internal combustion engine is used for torque development. All the power which is used is electric power as the energy source. In the electric vehicle main power source is electricity which is stored in the battery. The advantage of the highly efficient in power conversion through its proposition system of electric motor. Now in the world, there are several situations in which we cannot tolerate the environment that why we need to reduce carbon emission. In the sector of the automobile, there is a lot of petroleum used and therefore a lot of carbon emissions are occurring in the environment [1]. Electric busses work on the electricity from the power grid and also can work on the solar plates. There is a battery that can be charged and then used. All the car manufacturers have to develop at least one model in hybrid electric vehicles for the reduction in the carbon footprint. France and Japan are the countries who totally close the production of petrol vehicles by 2030. This is one more step toward pollution control and the improvement in electrical vehicles for a clean environment [2]. The table shows the various types of EVs. Image 1 shows the first electric vehicle in 1943-35 (America).

                                                                         Table 1

research paper ieee papers


There are many components in electric vehicles, some main ones are spark ignited, traction system, thermal cooling system, DC/DC converter, power electronics control, battery, motor, storage, braking system etc. [3]. Image 2 shows the main components of the electric busses. There are various parts with different function and working shown in the figure.

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DC to DC converter: A full-bridge DC/DC converter is the frequently implemented converter for fuel-cell power conditioning when electrical isolation is needed. Full bridge DC to DC converter is suitable for high-power electrical transmission because switch voltage is not high and current are also not high [3,5].  Electric Motor Generator : Electric vehicle drive system for plug-in hybrid vehicles the integrated motor-generator set provides electric propulsion for the vehicle in its function as a motor, while work as a generator it converts mechanical braking energy into electrical energy, that is college regenerative braking system.  Regenerative Braking system : In the battery-powered electric vehicle system, regenerative braking is the conversion of the electric vehicle's kinetic energy into chemical energy stored in the electric battery system, where it can be used to drive the vehicle.   Recharge Station : In these stations, busses can be charged by an electrical charging system and it will convert electrical supply power into battery storage power. Battery Packs : In this battery packs are arranged and this will provide the power to the motor. Which can be charged by the recharge station. The capacity of the battery is for the 120 km distance which can be charged in 1.5 hours (nearly). Solar Cell : Solar cells can be used in an emergency for electric busses. When there is charging not available cell can work for small distances. It can be mounted on the top of the buses and it will charge through the solar system. There is a lot of space on the bus which can be utilized. The solar cell efficiency formula is shown below.  

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III.  The Motor

There are a number of motors available for electric vehicles: DC motors, Induction motors, DC brushless motors, Permanent magnetic synchronous motors and Switched reluctance motors.

research paper ieee papers

1.   2. Induction motor: It’s a very popular Alternate Current motor. It also has a large market share in controlled speed drive applications such as AC, elevator, or escalator. There are various higher power electric vehicles, for more than 10kW. 

research paper ieee papers

5.  Switched reluctance motor: This motor specification is also good for the use of electric and hybrid vehicles. It has variable reluctance that why this machine [14].  IV.  Conclusion

This paper discusses the basics of electric vehicles and the development of electric vehicles, especially electric buses. The electric vehicle is very useful for the reduction of carbon emission and the change of climate. Consumption of petroleum is also reduced due to the use of that. The paper first describes the main components of electric vehicles, it then extends the description of the components with uses.  The paper provides a mini overview of electric vehicles.   Acknowledgment The author acknowledges the support of various references which is very useful for this paper. References [1] Chikhi, F. El Hadri, A. Cadiou, J.C. “ ABS control design based on wheel-slip peak localization”. Proceedings of the Fifth International Workshop on Robot Motion and Control, Publication Date: 23-25 June 2005, pp.73- 77  URL: [2] Beier, J. et  al, “Integrating on-site Renewable Electricity Generation into a Manufacturing System with Intermittent Battery Storage from Electric Vehicles”, Procedia CIRP, Vol. 48, 2016, pp. 483-488. [3] Rahman, K.M.; Fahimi, B.; Suresh, G.; Rajarathnam, A.V.; Ehsani, M., “Advantages of switched reluctance motor applications to EV and HEV: design and control issues”, IEEE Transactions on Industry Applications, Vol. 36, Issue 1, Jan.-Feb. 2000, pp. 111 – 121. [4] K W E Cheng; “Recent Development on Electric Vehicles”, 3rd International Conference on Power Electronics system and it's application, 2009 [5] M.J. Bradley & Associates. 2013. “Electric Vehicle Grid Integration in the U.S., Europe, and China.” [6] Chan, C.C. (1996), Chau, K.T., Jiang, J.Z., Xia, W., Zhu, M., and Zhang, R., Novel permanent magnet motor drives for electric vehicles. IEEE Transactions on Industrial Electronics, Vol. 43, pp. 331-339. [7] B Smith, M. and J. Castellano. 2015. “Costs Associated with Non-Residential Electric Vehicle Supply Equipment.” [8] C Clint, J., B. Gamboa, B. Henzie, and A. Karasawa. 2015. “Considerations for Corridor Direct Current Fast Charging Infrastructure in California.” [9] Chan, C.C., Jiang, J.Z., Chen, G.H., and Chau, K.T., Computer simulation and analysis of a new polyphase multipole motor drive. IEEE Transactions on Industrial Electronics, Vol. 40, 1993, pp. 570-576. [10] Zhan, Y.J., Chan, C.C., and Chau K.T., A novel sliding-mode observer for indirect position sensing of switched reluctance motor drives, IEEE Transactions on Industrial Electronics, Vol. 46, 1999, pp. 390-397. [11] Nunes, P., M.C. Brito and T. Farias, “Synergies between electric vehicles and solar electricity penetrations in Portugal,” 2013 World Electric Vehicle Symposium and Exhibition, 2013, pp. 1-8. [12] Mwasilu, F. et  al., “Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration”, Renewable and Sustainable Energy Reviews, Vol. 34, 2014, pp. 501-516 [13] Ates, M.N. et al., “In Situ Formed Layered-Layered Metal Oxide as Bifunctional Catalyst for Li-Air Batteries”, Journal of the Electrochemical Society, Vol 163, No. 10, 2016, pp. A2464-A2474 [14] Tuffner, F. and M. Kintner-Meyer, Using Electric Vehicles to Meet Balancing Requirements Associated with Wind Power, U.S. Department of Energy Pacific Northwest National Laboratory, 2011

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IEEE Blockchain Transactive Energy (BCTE) Position Paper

This Position Paper describes the basic framework and principles for using blockchain technology in power and energy domains with the emerging participatory grid. A key goal is the development of the most promising global Transactive Energy use cases which can be advanced toward broader commercialization using blockchain technology.

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Reinforcing the Links of the Blockchain IEEE Future Directions - November 2017

The purpose of this white paper is to explore the various ways by which the IEEE can lead and support an initiative on Blockchain while providing educational materials that will foster the next generation of blockchain engineers. This white paper summarizes and expands upon the IEEE Blockchain Incubator Workshop held by IEEE Future Directions at the end of October in 2017.

Download the white paper (PDF, 1 MB)

IEEE Blockchain Articles

Blockchain for Business Value: A Contract and Work Flow Management to Reduce Disputes Pilot Project IEEE Engineering Management Review - December 2018

By Liang Xi Downey; Frédéric Bauchot; Jos Röling

Blockchain technology has seen significant growth, hype, and potential new developments over the past few years. In this article additional insights into how blockchain can add value to a business process relationship is detailed. Specifically an engineering contract workflow use application pilot including various high level system architectural aspects are presented. This application shows the integration of blockchain technology with existing legacy systems. Some management and technology issues are also overviewed for the reader.

Read more at IEEE Xplore

Blockchain-Enabled E-Voting IEEE Software - July/August 2018

By Nir Kshetri and Jeffrey Voas

Published in the July/August 2018 issue of IEEE Software ; recognized among the top eight winners of the 2018 Most Influential Blockchain Research Papers by the Third Blockchain Connect Conference Awards.

"E-Voting is among the key public sectors that can be disrupted by blockchain technology. The idea in blockchain-enabled e-voting (BEV) is simple. To use a digital-currency analogy, BEV issues each voter a “wallet” containing a user credential. Each voter gets a single “coin” representing one opportunity to vote. Casting a vote transfers the voter’s coin to a candidate’s wallet. A voter can spend his or her coin only once. However, voters can change their vote before a preset deadline."

Download the paper (PDF, 463 KB)

Blockchain-GDPR Privacy by Design

By Claudio Lima, Ph.D., Blockchain Engineering Council, BEC Co-Founder; Vice Chair, IEEE Blockchain Standards

"The General Data Protection Regulation (GDPR) that was recently approved for implementation in the EEUU by May 25th, 2018 is already creating some controversies, when confronted with emerging Blockchain technologies, regarding what they have most in common: data privacy and protection. These are two are essential areas where Blockchain shines."

Download the paper (PDF, 899 KB)

Read Dr. Lima's article "Adapting Blockchain for GDPR Compliance" at InformationWeek

External Publications

Enhanced Distributed Ledger Technology NIST Computer Security Resource Center - September 2019

The blockchain data structure and proof-of-work protocol were designed to solve the problem of double spending in cryptocurrencies. Although blockchain has found many applications outside of cryptocurrency, many of its features are not well suited to common data management applications. The added trust of distributed ledgers is a valuable feature, providing greatly simplified auditability and verification of actions among multiple parties in applications such as supply chain and others, but there are tradeoffs.

Blockchain's hash-based integrity verification provides trust, at the cost of an inability to delete or update records, leading to design complications that would not arise with conventional database management systems. Similarly, the sequencing guarantees of blockchain consensus protocols are needed for cryptocurrency in the absence of a universal timestamp. Moreover, actions within the distributed ledger must be connected with other actions in the real world, through accurate timestamps. We are developing a new architecture that provides the trust features of blockchains, with characteristics that allow for simpler designs and greater practicality in conventional data management problems. We believe this alternative can lead to new approaches to incorporating trust into distributed systems applications.

Read more at NIST

Blockchain and Economic Development: Hype vs. Reality Center for Global Development - July 2017

Increasing attention is being paid to the potential of blockchain technology to address long-standing challenges related to economic development. Blockchain proponents argue that it will expand opportunities for exchange and collaboration by reducing reliance on intermediaries and the frictions associated with them. The purpose of this paper is to provide a clear-eyed view of the technology’s potential in the context of development. In it, we focus on identifying the questions that development practitioners should be asking technologists, and challenges that innovators must address for the technology to meet its potential.

Read more at the Center for Global Development

A Case Study for Blockchain in Healthcare: “MedRec” prototype for electronic health records and medical research data MIT Media Lab, Beth Israel Deaconess Medical Center - August 2016

A decentralized record management system to handle electronic health records, using Blockchain technology that manages authentication, confidentiality, accountability and data sharing.

Download white paper at (PDF, 591 KB)

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Efficiency Optimization Design That Considers Control of Interior Permanent Magnet Synchronous Motors Based on Machine Learning for Automotive Application

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Interior permanent magnet synchronous motors have become widely used as traction motors in environmentally friendly vehicles. Interior permanent magnet synchronous motors have a high degree of design freedom and time-consuming finite element analysis is required for their characteristics analysis, which results in a long design period. Here, we propose a method for fast efficiency maximization design that uses a machine-learning-based surrogate model. The surrogate model predicts motor parameters and iron loss with the same accuracy as that of finite element analysis but in a much shorter time. Furthermore, using the current and speed conditions in addition to geometry information as input to the surrogate model enables design optimization that considers motor control. The proposed method completed multi-objective multi-constraint optimization for multi-dimensional geometric parameters, which is prohibitively time-consuming using finite element analysis, in a few hours. The proposed shapes reduced losses under a vehicle test cycle compared with the initial shape. The proposed method was applied to motors with three rotor topologies to verify its generality.

View this article on IEEE Xplore

Published in the IEEE Vehicular Technology Society Section

An Intelligent IoT Sensing System for Rail Vehicle Running States Based on TinyML

Real-time identification of the running state is one of the key technologies for a smart rail vehicle. However, it is a challenge to accurately real-time sense the complex running states of the rail vehicle on an Internet-of-Things (IoT) edge device. Traditional systems usually upload a large amount of real-time data from the vehicle to the cloud for identification, which is laborious and inefficient. In this paper, an intelligent identification method for rail vehicle running state is proposed based on Tiny Machine Learning (TinyML) technology, and an IoT system is developed with small size and low energy consumption. The system uses a Micro-Electro-Mechanical System (MEMS) sensor to collect acceleration data for machine learning training. A neural network model for recognizing the running state of rail vehicles is built and trained by defining a machine learning running state classification model. The trained recognition model is deployed to the IoT edge device at the vehicle side, and an offset time window method is utilized for real-time state sensing. In addition, the sensing results are uploaded to the IoT server for visualization. The experiments on the subway vehicle showed that the system could identify six complex running states in real-time with over 99% accuracy using only one IoT microcontroller. The model with three axes converges faster than the model with one. The model recognition accuracy remained above 98% and 95%, under different installation positions on the rail vehicle and the zero-drift phenomenon of the MEMS acceleration sensor, respectively. The presented method and system can also be extended to edge-aware applications of equipment such as automobiles and ships.

Code Generation Using Machine Learning: A Systematic Review

Recently, machine learning (ML) methods have been used to create powerful language models for a broad range of natural language processing tasks. An important subset of this field is that of generating code of programming languages for automatic software development. This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description, and code-to-code. The most popular applications that work in these paradigms were found to be code generation from natural language descriptions, documentation generation, and automatic program repair, respectively. The most frequently used ML models in these studies include recurrent neural networks, transformers, and convolutional neural networks. Other neural network architectures, as well as non-neural techniques, were also observed. In this review, we have summarized the applications, models, datasets, results, limitations, and future work of 37 publications. Additionally, we include discussions on topics general to the literature reviewed. This includes comparing different model types, comparing tokenizers, the volume and quality of data used, and methods for evaluating synthesized code. Furthermore, we provide three suggestions for future work for code generation using ML.

Combining Citation Network Information and Text Similarity for Research Article Recommender Systems

Researchers often need to gather a comprehensive set of papers relevant to a focused topic, but this is often difficult and time-consuming using existing search methods. For example, keyword searching suffers from difficulties with synonyms and multiple meanings. While some automated research-paper recommender systems exist, these typically depend on either a researcher’s entire library or just a single paper, resulting in either a quite broad or a quite narrow search. With these issues in mind, we built a new research-paper recommender system that utilizes both citation information and textual similarity of abstracts to provide a highly focused set of relevant results. The input to this system is a set of one or more related papers, and our system searches for papers that are closely related to the entire set. This framework helps researchers gather a set of papers that are closely related to a particular topic of interest, and allows control over which cross-section of the literature is located. We show the effectiveness of this recommender system by using it to recreate the references of review papers. We also show its utility as a general similarity metric between scientific articles by performing unsupervised clustering on sets of scientific articles. We release an implementation, ExCiteSearch (, to allow researchers to apply this framework to locate relevant scientific articles.

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice

Smart health is one of the most popular and important components of smart cities. It is a relatively new context-aware healthcare paradigm influenced by several fields of expertise, such as medical informatics, communications and electronics, bioengineering, ethics, to name a few. Smart health is used to improve healthcare by providing many services such as patient monitoring, early diagnosis of disease and so on. The artificial neural network (ANN), support vector machine (SVM) and deep learning models, especially the convolutional neural network (CNN), are the most commonly used machine learning approaches where they proved to be performance in most cases. Voice disorders are rapidly spreading especially with the development of medical diagnostic systems, although they are often underestimated. Smart health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is needed to obtain a smart and precise mobile health system. The main contribution of this paper consists of proposing a multiclass-pathologic voice classification using a novel multileveled textural feature extraction with iterative feature selector. Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). A more compact multileveled features are then obtained by sample-based discretization techniques and Neighborhood Component Analysis (NCA) is applied to select features iteratively. These features are finally integrated with MCMTTP to achieve an accurate voice-based features detection. Experimental results of six classifiers with three diagnostic diseases (frontal resection, cordectomy and spastic dysphonia) show that the fused features are more suitable for describing voice-based disease detection.

*Published in the IEEE Electronics Packaging Society Section within IEEE Access .

Machine Learning Empowered Spectrum Sharing in Intelligent Unmanned Swarm Communication Systems: Challenges, Requirements and Solutions

The unmanned swarm system (USS) has been seen as a promising technology, and will play an extremely important role in both the military and civilian fields such as military strikes, disaster relief and transportation business. As the “nerve center” of USS, the unmanned swarm communication system (USCS) provides the necessary information transmission medium so as to ensure the system stability and mission implementation. However, challenges caused by multiple tasks, distributed collaboration, high dynamics, ultra-dense and jamming threat make it hard for USCS to manage limited spectrum resources. To tackle with such problems, the machine learning (ML) empowered intelligent spectrum management technique is introduced in this paper. First, based on the challenges of the spectrum resource management in USCS, the requirement of spectrum sharing is analyzed from the perspective of spectrum collaboration and spectrum confrontation. We found that suitable multi-agent collaborative decision making is promising to realize effective spectrum sharing in both two perspectives. Therefore, a multi-agent learning framework is proposed which contains mobile-computing-assisted and distributed structures. Based on the framework, we provide case studies. Finally, future research directions are discussed.

Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity

Cybersecurity is a fast-evolving discipline that is always in the news over the last decade, as the number of threats rises and cybercriminals constantly endeavor to stay a step ahead of law enforcement. Over the years, although the original motives for carrying out cyberattacks largely remain unchanged, cybercriminals have become increasingly sophisticated with their techniques. Traditional cybersecurity solutions are becoming inadequate at detecting and mitigating emerging cyberattacks. Advances in cryptographic and Artificial Intelligence (AI) techniques (in particular, machine learning and deep learning) show promise in enabling cybersecurity experts to counter the ever-evolving threat posed by adversaries. Here, we explore AI’s potential in improving cybersecurity solutions, by identifying both its strengths and weaknesses. We also discuss future research opportunities associated with the development of AI techniques in the cybersecurity field across a range of application domains.

A Study on the Elimination of Thermal Reflections

Recently, thermal cameras have been used in various surveillance and monitoring systems. In particular, in camera-based surveillance systems, algorithms are being developed for detecting and recognizing objects from images acquired in dark environments. However, it is difficult to detect and recognize an object due to the thermal reflections generated in the image obtained from a thermal camera. For example, thermal reflection often occurs on a structure or the floor near an object, similar to shadows or mirror reflections. In this case, the object and the areas of thermal reflection overlap or are connected to each other and are difficult to separate. Thermal reflection also occurs on nearby walls, which can be detected as artifacts when an object is not associated with this phenomenon. In addition, the size and pixel value of the thermal reflection area vary greatly depending on the material of the area and the environmental temperature. In this case, the patterns and pixel values of the thermal reflection and the object are similar to each other and difficult to differentiate. These problems reduce the accuracy of object detection and recognition methods. In addition, no studies have been conducted on the elimination of thermal reflection of objects under different environmental conditions. Therefore, to address these challenges, we propose a method of detecting reflections in thermal images based on deep learning and their elimination via post-processing. Experiments using a self-collected database (Dongguk thermal image database (DTh-DB), Dongguk items and vehicles database (DI&V-DB)) and an open database showed that the performance of the proposed method is superior compared to that of other state-of-the-art approaches.

Machine Learning Designs, Implementations and Techniques

Submission Deadline: 15 February 2020

IEEE Access invites manuscript submissions in the area of Machine Learning Designs, Implementations and Techniques.

Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to deployment of machine and deep learning systems, supervised /unsupervised techniques for mining healthcare data, and time series similarity and irregular temporal data analysis. Most deployments are in the cloud, with abundant and scalable resources, and a free choice of computation platform. However, with the advent of intelligent physical devices—such as intelligent robots or self-driven cars—the resources are more limited, and the latency may be strictly bounded.

To address these questions, the focus of this Special Section in IEEE Access is on machine and deep learning designs, implementations and techniques, including both system level topics and other research questions related to the general use and framework of machine learning algorithms.

The topics of interest include, but are not limited to:

  • Real time implementation of machine and deep learning,
  • System level implementation, considering full pipeline from raw data until the decision layer
  • Novel and innovative applications with strong emphasis on design and implementation
  • Novel approaches for Temporal / Spatial/Spatio-Temporal Association analysis
  • Pattern discovery from Time stamped Temporal and Interval databases
  • High performance data mining in cloud
  • Novel approaches for handling Uncertain and Imbalanced data
  • Supervised/Unsupervised techniques for mining healthcare data
  • Deep learning for translational bio-informatics
  • Periodic/Sequential pattern mining
  • Evolutionary algorithms
  • Privacy-Preserving Data mining
  • Time series similarity and Irregular temporal data analysis
  • Mining Text Web and Social network data
  • Imputation techniques for Temporal data
  • Causality and Event Processing
  • Applications of Data Mining in Anomaly and Intrusion detection
  • Applications to medical informatics

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Shadi A. Aljawarneh, Jordan University of Science and Technology, Jordan

Guest Editors:

  • Oguz Bayat, Altinbas University, Turkey
  • Juan A. Lara, Madrid Open University, Udima, Spain
  • Robert P. Schumaker, University of Texas at Tyler, USA

Relevant IEEE Access Special Sections:

  • Visual Analysis for CPS Data
  • Emerging Approaches to Cyber Security
  • Data-Enabled Intelligence for Digital Health

IEEE Access Editor-in-Chief:   Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:

For inquiries regarding this Special Section, please contact:  [email protected] , [email protected] .

Most Popular Article of 2017: Machine Learning With Big Data: Challenges and Approaches

The Big Data revolution promises to transform how we live, work, and think by enabling process optimization, empowering insight discovery and improving decision making. The realization of this grand potential relies on the ability to extract value from such massive data through data analytics; machine learning is at its core because of its ability to learn from data and provide data driven insights, decisions, and predictions. However, traditional machine learning approaches were developed in a different era, and thus are based upon multiple assumptions, such as the data set fitting entirely into memory, what unfortunately no longer holds true in this new context. These broken assumptions, together with the Big Data characteristics, are creating obstacles for the traditional techniques. Consequently, this paper compiles, summarizes, and organizes machine learning challenges with Big Data. In contrast to other research that discusses challenges, this work highlights the cause-effect relationship by organizing challenges according to Big Data Vs or dimensions that instigated the issue: volume, velocity, variety, or veracity. Moreover, emerging machine learning approaches and techniques are discussed in terms of how they are capable of handling the various challenges with the ultimate objective of helping practitioners select appropriate solutions for their use cases. Finally, a matrix relating the challenges and approaches is presented. Through this process, this paper provides a perspective on the domain, identifies research gaps and opportunities, and provides a strong foundation and encouragement for further research in the field of machine learning with Big Data.

At a Glance

  • Journal: IEEE Access
  • Format: Open Access
  • Frequency: Continuous
  • Submission to Publication: 4-6 weeks (typical)
  • Topics: All topics in IEEE
  • Average Acceptance Rate: 27%
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MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields

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Entrant must submit a video with an article submission to IEEE Access . The video submission must clearly be relevant to the submitted manuscript.  Only videos that accompany an article that is accepted for publication in IEEE Access will qualify.  The video may be simulations, demonstrations, or interviews with other experts, for example.  Your video file should not exceed 100 MB.

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A Fresh Perspective on “Brave New World” by Aldous Huxley

This essay about Aldous Huxley’s “Brave New World” provides an analysis of the dystopian themes and societal critiques presented in the novel. It discusses the futuristic setting where the World State controls every aspect of life, categorizing citizens into castes and eliminating individuality through conditioning and the drug soma. The narrative follows characters like Bernard Marx and John the Savage, who challenge the societal norms and expose the cost of maintaining such a controlled utopia. The essay explores the novel’s reflection on contemporary issues like technological control, loss of personal freedom, and the ethical dilemmas of progress, suggesting that Huxley’s work remains relevant today as it questions the balance between societal stability and personal freedom. Through “Brave New World,” the essay prompts readers to consider the moral implications of our own societal choices and the future we are navigating.

How it works

In his dystopian novel “Brave New World,” Aldous Huxley presents a terrifying picture of a society in which the government has painstakingly planned every aspect of society to guarantee stability and happiness for all. First published in 1932, the book continues to be a key work of dystopian literature, addressing issues of control, technology, and the willingness to give up personal freedom in the name of social harmony. As we delve deeper into Huxley’s universe, we find a civilization that at first glance could seem utopian—all disputes and discomforts are supposedly eliminated—but a closer look exposes a troubling price for this peaceful way of life.

The futuristic London of “Brave New World” is ruled by the World State, which assumes the appearance of kindness but really has an iron grip. From birth, the residents are socialized into classes that range from the highly intelligent Alphas to the lowly Epsilons who work as laborers. This indoctrination permeates every aspect of life, as individuality is reduced to a historical idea and free will is given up for the benefit of the group.

The government ensures compliance through the distribution of soma, a drug that eradicates pain and ensures compliance among the masses, promoting an ethos of “a gramme is better than a damn.” Huxley’s narrative begins to twist when Bernard Marx, an Alpha plus psychologist, feels out of sync with the society he’s supposed to lead. His restlessness leads him to question the foundations of the World State, a curiosity ignited further by his relationship with Lenina Crowne and his interactions with John, a “savage” from an unassimilated reservation in New Mexico.

John, who grew up outside the societal norms of the World State, serves as a poignant contrast to the controlled denizens of the utopia. His presence in London acts as a catalyst, challenging the core tenets of this society. His struggle with the World State’s ethos of consumption, sexual freedom, and emotional suppression brings the philosophical debates to the forefront of the narrative. The tragic arc of John’s character underscores the novel’s central thesis: the loss of human dignity and freedom in the face of technological and governmental control.

Through vivid characterization and a richly imagined world, Huxley critiques contemporary issues of his time, many of which resonate profoundly today. The novel contemplates the impact of advanced science and technology on human values and behaviors, highlighting the dangers of a society willing to sacrifice liberty for perceived security and comfort. It prompts a reflection on the meaning of happiness and the price of progress, questioning whether true contentment requires a balance between freedom and order.

As we reflect on Huxley’s work in the context of modern society, it’s apparent that many of the ethical and philosophical questions he raised remain pertinent. From genetic engineering to the role of government in personal lives, “Brave New World” offers a crucial lens through which to examine the moral implications of our choices. Huxley’s speculative world, with its technological wonders and social stratifications, serves not only as a warning but also as a mirror, reflecting our own struggles with technological advancement and ethical governance.

In summary, “Brave New World” is a pertinent remark on the modern world as well as a relic of dystopian literature. Readers are prompted to consider the future of our civilization by its examination of the human condition, societal expectations, and the frequently hazy boundary between utopia and dystopia. Huxley’s book serves as a timely warning of what happens to us when we let the monetization of human experience determine our future, even while we forge our own daring new paths. It is an engaging investigation on the extent and price that mankind should pay in its quest for the ideal society.

This classic story still functions as a critical analysis of our decisions and goals, demonstrating how a deeper comprehension of a work this complex may enhance not only our enjoyment of literature but also our grasp of society structures and the human mind.


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A Fresh Perspective on "Brave New World" by Aldous Huxley. (2024, May 12). Retrieved from

"A Fresh Perspective on "Brave New World" by Aldous Huxley." , 12 May 2024, (2024). A Fresh Perspective on "Brave New World" by Aldous Huxley . [Online]. Available at: [Accessed: 12 May. 2024]

"A Fresh Perspective on "Brave New World" by Aldous Huxley.", May 12, 2024. Accessed May 12, 2024.

"A Fresh Perspective on "Brave New World" by Aldous Huxley," , 12-May-2024. [Online]. Available: [Accessed: 12-May-2024] (2024). A Fresh Perspective on "Brave New World" by Aldous Huxley . [Online]. Available at: [Accessed: 12-May-2024]

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