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Recent Advances in In-Memory computing:Exploring Memristor and Memtransistor Arrays with 2D Materials

Nano-Micro Letters 2024年第7期16卷 1-30页

作者： Hangbo Zhou Sifan Li Kah-Wee Ang Yong-Wei Zhang Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)1 Fusionopolis Way#16-16 ConnexisSingapore 138632Republic of Singapore Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Republic of Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and Research(A*STAR)2 Fusionopolis WaySingapore 138634Republic of Singapore

The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing *** response,in-memory computing has emerged as a promising alternative architecture,enabling computing operations within memory arrays to overcome these *** devices have gained significant attention as key components for in-memory computing due to their high-density arrays,rapid response times,and ability to emulate biological *** these devices,two-dimensional(2D)material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing,thanks to their exceptional performance driven by the unique properties of 2D materials,such as layered structures,mechanical flexibility,and the capability to form *** review delves into the state-of-the-art research on 2D material-based memristive arrays,encompassing critical aspects such as material selection,device perfor-mance metrics,array structures,and potential ***,it provides a comprehensive overview of the current challenges and limitations associated with these arrays,along with potential *** primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing,leveraging the potential of 2D material-based memristive devices.

关键词： 2D materials Memristors Memtransistors Crossbar array In-memory computing

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting

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computers, Materials & Continua 2024年第9期80卷 4997-5027页

作者： Milos Dobrojevic Luka Jovanovic Lepa Babic Miroslav Cajic Tamara Zivkovic Miodrag Zivkovic Suresh Muthusamy Milos Antonijevic Nebojsa Bacanin Technical Faculty Singidunum UniversityBelgrade11000Serbia Informatics and Computing Singidunum UniversityBelgrade11000Serbia Business Economics Singidunum UniversityBelgrade11000Serbia Computing and Informatics Sinergija UniversityBijeljina76300Bosnia and Herzegovina Department for Information Systems and Technologies University“Union Nikola Tesla”Cara DusanaBelgrade11080Serbia Department for Computer Science and Informatics School of Electrical EngineeringUniversity of BelgradeBelgrade11000Serbia Department of Electrical and Electronics Engineering Kongu Engineering College(Autonomous)PerunduraiErode638060India Department of Mathematics Saveetha School of Engineering(Deemed to be University)SIMATS ThandalamChennai602105India MEU Research Unit Middle East UniversityAmman11831Jordan

Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones,computers,or *** can occur through various channels,such as social media,text messages,online forums,or gaming *** involves using technology to intentionally harm,harass,or intimidate others and may take different forms,including exclusion,doxing,impersonation,harassment,and ***,due to the rapid growth of malicious internet users,this social phenomenon is becoming more frequent,and there is a huge need to address this ***,the main goal of the research proposed in this manuscript is to tackle this emerging challenge.A dataset of sexist harassment on Twitter,containing tweets about the harassment of people on a sexual basis,for natural language processing(NLP),is used for this *** algorithms are used to transform the text into a meaningful representation of numbers for machine learning(ML)input:Term frequency inverse document frequency(TF-IDF)and Bidirectional encoder representations from transformers(BERT).The well-known eXtreme gradient boosting(XGBoost)ML model is employed to classify whether certain tweets fall into the category of sexual-based harassment or ***,with the goal of reaching better performance,several XGBoost models were devised conducting hyperparameter tuning by *** this purpose,the recently emerging Coyote optimization algorithm(COA)was modified and adjusted to optimize the XGBoost ***,other cutting-edge metaheuristics approach for this challenge were also implemented,and rigid comparative analysis of the captured classification metrics(accuracy,Cohen kappa score,precision,recall,and F1-score)was ***,the best-generated model was interpreted by Shapley additive explanations(SHAP),and useful insights were gained about the behavioral patterns of people who perform social harassment.

关键词： Coyote optimization algorithm NLP TF-IDF BERT XGBoost online harassment and cyberbullying metaheuristics

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Remote Control of Residential Meter Involving E-Billing 4

Remote Control of Residential Meter Involving E-Billing

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4th International Conference on Electronic and electrical engineering and Intelligent System, ICE3IS 2024

作者： Khan, Sher Dali Alamsyah, Nurwahyu Mufti, Naveed Ul Haq, Qazi Mazhar Mukhtar, Abbas Haq, Muhamad Amirul Malaysia Universitas Muhammadiyah Yogyakarta Information Technology Department Yogyakarta Indonesia UET Mardan Department of Telecommunication Engineering Pakistan Yuan Ze University Department of Computer Science and Engineering and IBPI Taoyuan Taiwan University of Windsor Department of Electrical and Computing Engineering ON Canada Universitas Muhammadiyah Surabaya Computer Science Department Surabaya Indonesia

ISBN: (纸本)9798350378368

In electrical energy distribution, losses are a challenging problem, among these losses electricity theft plays a prominent role. Not only Pakistan but many other countries throughout the world face this challenge. This paper presents a system based on smart meter to detect the approximate location of electricity theft. Along with electricity theft detection, this paper also proposes a system for the elimination of illegal consumers. The approach used is that the total energy is compared with the legally consumed energy. For communication between the meters wireless communication techniques are used including Global System for Mobile Communications (GSM) and Network Repository Function (NRF). © 2024 IEEE.

关键词： Global system for mobile communications

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Vaxina: Decentralized Vaccination Tracking System 9

Vaxina: Decentralized Vaccination Tracking System

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9th International Conference on Information Technology Trends, ITT 2023

作者： Almobaideen, Wesam Mohammed, Mohammad Rochester Institute of Technology Dubai Electrical Engineering and Computing Sciences Department United Arab Emirates The University of Jordan Computer Science Department Amman Jordan

ISBN: (纸本)9798350327502

With the epidemic of Covid-19, a realisation has come into effect that the healthcare industry requires a more efficient method of storing non-tamperable vaccination certificates as well as sharing them with the relevant parties when required. As such, the need for efficient and secure vaccination tracking has led to the development of decentralized solutions. This paper aims to bring forth a Ethereum platform-based vaccination blockchain certificate system which supports authenticated consensual vaccination certificate sharing through the use of solidity smart contracts. We analyse the system architecture, implementation and evaluation, which will support the system's ability to resolve some of the security issues associated with centralised database systems such as low availability, integrity of the vaccination information as well as confidentiality and privacy of patient medical records. Vaxina system is a real-world implementation of a decentralized vaccination tracking system based on the Ethereum platform. It focuses more on the practical implementation and addresses some of the limitations of the previous proposed systems. It has been implemented and tested on the Ethereum blockchain and is available on GitHub for public use. The paper provides valuable insights for future work in the field of decentralized healthcare solutions. © 2023 IEEE.

关键词： Smart contract

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Efficient Vehicle Detection and Classification using YOLO v8 for Real-Time Applications

Efficient Vehicle Detection and Classification using YOLO v8...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Ravichandran, M. Laxmikant, Kumar Muthu, Annamalai Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India University of Technology & Applied Science Department of Electrical and Electronics Engineering Nizwa Oman

ISBN: (纸本)9798350308167

In the realm of real-time applications such as autonomous driving and surveillance, efficient vehicle detection stands as a paramount concern. The revolutionary You Only Look Once (YOLO) framework, renowned for its rapid object recognition, has reshaped this landscape. This study delves into the fusion of real-time vehicle detection and YOLO v8, optimizing its architecture for swift and precise identification. Empirical validation underscores the model's prowess, achieving a remarkable accuracy of 97.9% on mAP50 and 91.3% on mAP50-95. This achievement not only attests to the model's accuracy but also reaffirms its real-time processing capabilities. The implications resonate across transportation safety and urban planning, promising transformative potential. This research underscores the power of YOLO v8 in intelligent object detection, poised to reshape and enhance various domains. © 2023 IEEE.

关键词： mAP50 mAP50-95 Object Detection Vehicle Detection YOLO Framework

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3D Modeling of Automated Robot for Seeding and Transplantation of Rice and Wheat Crops 1

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4th International Conference on Communication and Intelligent Systems, ICCIS 2022

作者： Krishna, G. Venkata Sai Amitasree, Palanki Manitha, P.V. Rajesh, M. Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9789819923229

ISBN: (纸本)9789819923212

The most important sector of Indian economy which is identified as the backbone is agriculture. The major part of agriculture lies in paddy cultivation. In earlier days, agriculture was the major sector where most people were employed but nowadays, due to industrial growth and IT revolution, the employment in agriculture has become too less. The major part of economy which is vital for India’s economic growth is now facing serious issues due to the manpower shortage, lack of advancement in technological usage. This proposes a solution to meet out this issue by bringing in automation in the agriculture domain. Agricultural processes are chains of systematic, repetitive and time-dependent tasks. It requires lot of manual labor and accurate placement and managing of seeds and saplings. It’s a case where a human error is highly possible. In this work, an attempt is made to automate the process of distributing the seeds and once they are grown big enough to get transplanted, the robotic solution will transplant these plants. The automated solution will distribute the seeds in an organized and optimized way. The robotic platform will pluck the plants and replant them in an organized way. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Three dimensional computer graphics

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A Machine Learning Approach for Detecting Fake News in Hindi 10

A Machine Learning Approach for Detecting Fake News in Hindi

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10th IEEE Uttar Pradesh Section International Conference on electrical, Electronics and computer engineering, UPCON 2023

作者： Nagesh, Shreyas Sampath, Aditya N Guruprasad, Pradhumna Salai Sanjay, S. Jeyakumar, G. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electrical and Electronics Engineering Coimbatore India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science Engineering Coimbatore India

ISBN: (纸本)9798350382471

Several solutions exist to detect whether English news articles are fake or not. However, in a country such as India, news articles are published in numerous regional languages too. There has been little research work done on regional languages such as Hindi. This work proposes a framework to detect Hindi fake news articles. A dataset of nearly 4500 news articles has been collected in Hindi, written using the Devanagari Script. These news articles are scraped using BeautifulSoup and Scrapy libraries. The IndicBERT and MuRIL libraries, developed earlier in Hindi, are used to generate the word embedding. SVM, Logistic Regression, and a simple CNN are used as classifiers. Extensive experiments have been methodically conducted in order to find the best combination to detect fake news in Hindi. The best combination was found to be MuRIL and SVM, yielding 98.58% classification accuracy. A standalone GUI running on a local host is built to demonstrate the working model. © 2023 IEEE.

关键词： Hindi Fake News IndicBERT Machine Learning MuRIL Natural Language Processing StanfordNLP

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Assessing the Efficacy of Symbolic Regression for Scientific Data Classification and Regression 14

Assessing the Efficacy of Symbolic Regression for Scientific...

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14th International Conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Guruprasad, Pradhumna Nagesh, Shreyas Sampath, Aditya N Salai Sanjay, S. Jeyakumar, G. Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering India Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science Engineering India

ISBN: (纸本)9798350335095

Symbolic regression (SR) is a subdomain of evolutionary computing which aims to generate mathematical equations which best fit a given dataset. This is done with the help of genetic algorithms. Symbolic Regression is especially useful in cases where features in a dataset are known to have distinct mathematical relations to each other and its output. Therefore, this paper aims to compare and provide insight on the results of using SR on two datasets with two python libraries. These results are further compared with other ML models to assess their performance in classification and regression tasks. The detailed methodology and results are discussed further test metrics and obtained equations. The results show that symbolic regression can perform very well on certain datasets whose target outputs have a mathematical connection to the input features. SR is found to work better than other ML models in the classification and regression tasks. © 2023 IEEE.

关键词： Genetic algorithms

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High-performance and Multi-functional Control of Transformerless Single-phase Smart Inverter for Grid-connected PV System

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1386-1394页

作者： Kamran Zeb Saif Ul Islam Waqar Uddin Imran Khan Muhammad Ishfaq Tiago Davi Curi Busarello H.J.Kim Department of Electrical Engineering Pusan National University School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Control Automation and Computing EngineeringFederal University of Santa Catarina Blumenau

Highly reliable and flexible control is required for distributed generation(DG) to efficiently connect to the *** inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter(SPV-SSI) of 5 k VA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling(PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator(STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i. e., fuzzy proportional-integral(F-PI) controller and fuzzy-sliding mode controller(F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop(islanded mode) and current control loop(grid-connected mode).

关键词： Distributed generation(DG) inverter convert-er fuzzy-sliding mode controller(F-SMC) fuzzy proportionalintegral(F-PI)controller

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