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AutoML: A systematic review on automated machine learning with neural architecture search

Journal of Information and Intelligence 2024年第1期2卷 52-81页

作者： Imrus Salehin md.Shamiul Islam Pritom Saha S.M.Noman Azra Tuni md.mehedi hasan md.Abu Baten Department of Computer Engineering Dongseo University47 Jurye-roSasang-guBusan 47011Republic of Korea Department of Computer Science and Engineering Daffodil International UniversityDhaka 1216Bangladesh Department of Computer Science and Engineering Bangladesh University of Business and TechnologyDhaka 1216Bangladesh Faculty of Computer Science and Engineering Frankfurt University of Applied SciencesFrankfurt 60318Germany Department of Computer Science and Engineering University of Asia PacificDhaka 1205Bangladesh Department of Computer Science and Engineering Ahsanullah University of Science and TechnologyDhaka 1208Bangladesh Department of Computer Science and Engineering Northern University BangladeshDhaka 1215Bangladesh

AutoML(Automated Machine Learning)is an emerging field that aims to automate the process of building machine learning *** emerged to increase productivity and efficiency by automating as much as possible the inefficient work that occurs while repeating this process whenever machine learning is *** particular,research has been conducted for a long time on technologies that can effectively develop high-quality models by minimizing the intervention of model developers in the process from data preprocessing to algorithm selection and *** this semantic review research,we summarize the data processing requirements for AutoML approaches and provide a detailed *** place greater emphasis on neural architecture search(NAS)as it currently represents a highly popular sub-topic within the field of *** methods use machine learning algorithms to search through a large space of possible architectures and find the one that performs best on a given *** provide a summary of the performance achieved by representative NAS algorithms on the CIFAR-10,CIFAR-100,ImageNet and wellknown benchmark ***,we delve into several noteworthy research directions in NAS methods including one/two-stage NAS,one-shot NAS and joint hyperparameter with architecture *** discussed how the search space size and complexity in NAS can vary depending on the specific problem being *** conclude,we examine several open problems(SOTA problems)within current AutoML methods that assure further investigation in future research.

关键词： AutoML Neural architecture search Advance machine learning Search space Hyperparameter optimization

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iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features

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Genomics, Proteomics & Bioinformatics 2020年第5期18卷 593-600页

作者： md.mehedi hasan Mst.Shamima Khatun Hiroyuki Kurata Department of Bioscience and Bioinformatics Kyushu Institute of TechnologyIizukaFukuoka 820-8502Japan Biomedical Informatics R&D Center Kyushu Institute of TechnologyIizukaFukuoka 820-8502Japan

Linear B-cell epitopes are critically important for immunological applications,such as vaccine design,immunodiagnostic test,and antibody production,as well as disease diagnosis and *** accurate identification of linear B-cell epitopes remains challenging despite several decades of *** this work,we have developed a novel predictor,Identification of Linear B-cell Epitope(i LBE),by integrating evolutionary and sequence-based *** successive feature vectors were optimized by a Wilcoxon-rank sum *** the random forest(RF)algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell *** combined the RF scores by the logistic regression to enhance the prediction *** yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent *** is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests.A web application with curated datasets for iLBE is freely accessible at http://***/iLBE/.

关键词： Linear B-cell epitope BLAST Feature encoding Feature selection Random forest

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Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

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Protection and Control of Modern Power Systems 2023年第3期8卷 97-138页

作者： Faiaz Ahsan Nazia hasan Dana Subrata K.Sarker Li Li S.M.Muyeen md.Firoj Ali Zinat Tasneem md.mehedi hasan Sarafat Hussain Abhi md.Robiul Islam md.Hafiz Ahamed md.Manirul Islam Sajal K.Das md.Faisal R.Badal Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh School of Electrical and Data Engineering Faculty of Engineering and ITUniversity of Technology SydneyUltimoAustralia Electrical Engineering Department Qatar UniversityDohaQatar

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO_(2) *** structure of these technologies relies on the deep inte-gration of advanced data-driven techniques which can ensure efficient energy generation,transmission,and *** conducting thorough research for more than a decade,the concept of the smart grid(SG)has emerged,and its practice around the world paves the ways for efficient use of reliable energy ***,many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid(NGSG).Also,to deal with the non-linearity and uncertainty,the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of *** paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation,including intelligent control,agent-based energy conversion,edge computing for energy management,internet of things(IoT)enabled inverter,agent-oriented demand side management,***,a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques(DDTs)for the sustainable operation of the *** prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering,technology,et ***,the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied,while some major future issues are *** paper can offer extended support for engineers and researchers in the context of data-driven technology and the SG.

关键词： Data-driven technology Smart grid Sustainable energy evolution Next-generation smart grid Intelligent

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Next-generation blockchain enabled smart grid: Conceptual framework, keytechnologies and industry practices review

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能源与人工智能(英文) 2023年第2期12卷 187-205页

作者： Shekh S.Uddin Rahul Joysoyal Subrata K.Sarker S.M.Muyeen md.Firoj Ali md.mehedi hasan Sarafat Hussain Abhi md.Robiul Islam md.Hafiz Ahamed md.Manirul Islam Sajal K.Das md.Faisal R.Badal Prangon Das Zinat Tasneem Department of Mechatronics Engineering Rajshahi University of Engineering&TechnologyRajshahi 6204Bangladesh Department of Electrical Engineering Qatar UniversityQatar

Technological advancements in smart grid energy systems (SGESs) are introducing sustainable frameworksto meet the demand for the fourth industrial energy revolution. These frameworks are planned to be usedin the forthcoming future to maintain the energy network operation with optimization, energy trading, gridautomation, and so on. Blockchain (BCn), developing after passing a diverse period of the research journey,comes to the mind of researchers and its integration in SGES paves the way to reach the goal of energydemand. However, still of interest is ongoing in the improvement of BCn features which can be regarded asthe next-generation blockchain framework. This paper exhibits the technical framework of the next-generationBCn framework and explores its benefits and challenges in performing the emerging aspects of SGES. Thisframework enables some advanced features for the sustainable operation of SGES like smart metering, peer-topeer (P2P) energy trading, self-operation, and transparency. The technical explanation of this BCn technologyestablished on essential features and requisites is also presented in this paper from various points of viewwhich include smart mechanism, intelligent storage system, and interoperability. We also highlight the recentprogress and limitations of the current BCn framework in SGES. Finally, some challenges towards integratingthe next-generation BCn technology in SGES are reported. This work can provide extended support for thepractitioner and researcher in the context of BCn technology and SGES.

关键词： Blockchain Smart grid energy system Smart contract

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Towards electric digital twin grid: Technology and framework review

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能源与人工智能(英文) 2023年第1期11卷 179-195页

作者： md.Mhamud Hussen Sifat Safwat Mukarrama Choudhury Sajal K.Das md.Hafiz Ahamed S.M.Muyeen md.mehedi hasan md.Firoj Ali Zinat Tasneem md.Manirul Islam md.Robiul Islam md.Faisal R.Badal Sarafat H.Abhi Subrata K.Sarker Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh Department of Electrical Engineering Qatar UniversityDoha2713Qatar

The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.

关键词： Electric digital twin grid Online analysis of grid Cloud platform of grid Real-time grid analysis Self-healing Cybersecurity

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Towards next generation Internet of Energy system: Framework and trends

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Energy and AI 2023年第4期14卷 660-681页

作者： Muqit Farhan Tanzim N.Reza Faisal R.Badal md.R.Islam S M Muyeen Z.Tasneem md.mehedi hasan md.F.Ali md.H.Ahamed S.H.Abhi md.Manirul Islam Subrata K.Sarker Sajal K.Das Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering TechnologyRajshahi 6204Bangladesh Department of Electrical Engineering Qatar UniversityDohaQatar

The quickening propensity of growth within the areas of information and communications technology and en-ergy networks has triggered the emergence of a central idea termed as Internet of Energy(IoE).Such a concept relates the internet of things,which is the term used in describing the usage of sophisticated digital control devices with the capability of transmitting data via IT *** concept of an interconnected energy network is being formed in the upcoming days through upgrades in the field of intelligent energy systems to control real-time energy optimization and *** energy industry has had a sustained expansion,reaching the IoE milestone and continuing to this cutting-edge power system,which is the next generation of IoE.A directional pathway from the traditional power system to the IoE has been conducted in this research work by addressing the importance of integrating the smart transmission and communication infrastructure,smart metering,pricing and energy management scheme.A detailed investigation of the IoE with respect to technical angles,such as communication architecture,IoE on the supply&demand side,and IoE protocol based on fundamental elements and essential technologies has been carried out to indicate the blueprint and jurisdiction *** inte-gration,security and energy management challenges may deviate the performance of the IoE technology that has been focused with proper control issues and ***,a directional framework to establish the next-generation IoE system has been constructed with future scopes to insure higher resiliency,cyber-security and stability.

关键词： Internet of Energy IoT Microgrid Smart grid Virtual power plant Next generation power system

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Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin md.Al mehedi hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

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Risk Factors Categorizations of Ischemic Heart Disease in South-Western Bangladesh

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Data Intelligence 2024年第3期6卷 834-868页

作者： M.Raihan Sami Azam Laboni Akter md.mehedi Hassan Ryana Quadir Asif Karim Saikat Mondal Arun More Department of Computer Science and Engineering North Western UniversityKhulna 9100Bangladesh Faculty of Science and Technology Charles Darwin UniversityNT 0909Australia Departmentof Biomedical Engineering Khulna University of Engineering&TechnologyKhulnaBangladeh Computer Science and Engineering Discipline Khulna UniversityKhulna 9208Bangladesh Department of Computer Science and Engineering Daffodil International University(DIU)Bangladesh Department of Cardiology Ter Institute of Rural Health and ResearchMurud-413510India

Ischemic heart disease(IHD)is one of the leading causes of death ***,different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of *** study examines the current IHD condition in southern Bangladesh,a Southeast Asian middle-income *** main approach to this research is an Al-based proposal of a reduced set of the greatest impact clinical traits that may cause *** approach attempts to reduce IHD morbidity and mortality by early detection of risk factors using the reduced set of clinical ***,diagnostic,and symptomatic features were considered for analysing this clinical *** pre-processing utilizes several machine learning techniques to select significant features and make meaningful interpretations.A proposed voting mechanism ranked the selected 138 features by their impact *** this regard,diverse patterns in correlations with variables,including age,sex,career,family history,obesity,etc.,were calculated and explained in terms of voting *** the 138 risk factors,three labels were categorized:high-risk,medium-risk,and low-risk features;19 features were regarded as high,25 were medium,and 94 were considered low impactful *** research's technological methodology and practical goals provide an innovative and resilient framework for addressing IHD,especially in less developed cities and townships of Bangladesh,where the general population's socioeconomic conditions are often *** data collection,pre-processing,and use of this study's complete and comprehensive IHD patient dataset is another innovative *** believe that other relevant research initiatives will benefit from this work.

关键词： Ischemic heart disease Machine learning CVD Data categorization Medical data

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Development of a Lightweight Model for Handwritten Dataset Recognition: Bangladeshi City Names in Bangla Script

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Computers, Materials & Continua 2024年第8期80卷 2633-2656页

作者： mdMahbubur Rahman Tusher Fahmid Al Farid mdAl-hasan Abu Saleh Musa Miah Susmita Roy Rinky mehedi hasan Jim Sarina Mansor mdAbdur Rahim Hezerul Abdul Karim Department of Computer Science and Engineering Bangladesh Army University of Science and Technology(BAUST)Saidpur5310Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Pabna University of Science and Technology Pabna6600Bangladesh

The context of recognizing handwritten city names,this research addresses the challenges posed by the manual inscription of Bangladeshi city names in the Bangla *** today’s technology-driven era,where precise tools for reading handwritten text are essential,this study focuses on leveraging deep learning to understand the intricacies of Bangla *** existing dearth of dedicated datasets has impeded the progress of Bangla handwritten city name recognition systems,particularly in critical areas such as postal automation and document ***,no prior research has specifically targeted the unique needs of Bangla handwritten city name *** bridge this gap,the study collects real-world images from diverse sources to construct a comprehensive dataset for Bangla Hand Written City name *** emphasis on practical data for system training enhances *** research further conducts a comparative analysis,pitting state-of-the-art(SOTA)deep learning models,including EfficientNetB0,VGG16,ResNet50,DenseNet201,InceptionV3,and Xception,against a custom Convolutional Neural Networks(CNN)model named“Our CNN.”The results showcase the superior performance of“Our CNN,”with a test accuracy of 99.97% and an outstanding F1 score of 99.95%.These metrics underscore its potential for automating city name recognition,particularly in postal *** study concludes by highlighting the significance of meticulous dataset curation and the promising outlook for custom CNN *** encourages future research avenues,including dataset expansion,algorithm refinement,exploration of recurrent neural networks and attention mechanisms,real-world deployment of models,and extension to other regional languages and *** recommendations offer exciting possibilities for advancing the field of handwritten recognition technology and hold practical implications for enhancing global postal services.

关键词： Handwritten recognition Bangladeshi city names Bangla handwritten city name automated postal services

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Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： md. mehedi hasan md. Masud Rana Abu Sayed md. Mostafizur Rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

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