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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir sanjeev singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

作者： (美)桑吉耶夫·辛格(sanjeev k. singh)，(美)斯文·弗尔(Sven Feurer)，(美)马库斯·鲁布萨姆(Marcus Ruebsam)

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Exploring the role of N-acetyltransferases in diseases:a focus on N-acetyltransferase 9 in neurodegeneration

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Neural Regeneration Research 2025年第10期20卷 2862-2871页

作者： Prajakta Deshpande Anuradha Venkatakrishnan Chimata Amit singh Department of Biology University of DaytonDaytonOHUSA Premedical Program University of DaytonDaytonOHUSA Center for Tissue Regeneration and Engineering at Dayton(TREND) University of DaytonDaytonOHUSA Integrative Science and Engineering Center University of DaytonDaytonOHUSA Center for Genomic Advocacy(TCGA) Indiana State UniversityTerre HauteINUSA

Acetyltransferases,required to transfer an acetyl group on protein are highly conserved proteins that play a crucial role in development and *** acetylation is a common post-translational modification pivotal to basic cellular *** to 80%-90%of proteins are acetylated during translation,which is an irreversible process that affects protein structure,function,life,and *** this review,we have discussed the various N-acetyltransferases present in humans,their function,and how they might play a role in ***,we have focused on N-acetyltransferase 9 and its role in microtubule *** have shed light on how N-acetyltransferase 9 and acetylation of proteins can potentially play a role in neurodegenerative *** have specifically discussed the N-acetyltransferase 9-acetylation independent function and regulation of c-Jun N-terminal kinase signaling and microtubule stability during development and neurodegeneration.

关键词： acetyl-coenzyme A Alzheimer’s disease animal models cell death drosophila eye human disease c-Jun N-terminal kinase signaling N-Acetyltransferases N-acetyltransferase 9 neurodegeneration

Fibrinogen’s potential role in connecting cerebrovascular abnormalities with glymphatic dysfunction in Alzheimer’s disease

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Neural Regeneration Research 2025年第1期20卷 203-204页

作者： Vishal singh Arnab Choudhury Hyung Jin Ahn Department of Pharmacology Physiology and NeurosciencesRutgers-New Jersey Medical SchoolNewarkNJUSA Brain Health Institute Rutgers UniversityPiscatawayNJUSA

Alzheimer’s disease(AD)stands out as the primary manifestation of age-related dementia,portraying a chronic neurodegenerative disorder distinguished by the accumulation of fibrillar amyloid-β(Aβ)plaques and neurofibrillary tangles of hyperphosphorylated ***,from a clinical standpoint,AD presents itself as a complex condition with a spectrum of dysfunctions rather than a singular pathological *** often-overlooked aspect of the disease is the presence of extensive cerebrovascular abnormalities,given that the majority of AD patients experience altered cerebral blood flow,damaged vasculature,increased microinfarcts and *** models of AD further support this observation,showing cerebrovascular dysfunction such as impaired cerebral blood flow and altered cerebrovascular reactivity(Tataryn et al.,2021;Gareau et al.,2023).

关键词： cerebrovascular dysfunction Alzheimer

Information hiding with adaptive steganography based on novel fuzzy edge identification

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Defence Technology（防务技术） 2019年第2期15卷 162-169页

作者： sanjeev kumar Amarpal singh Manoj kumar I.k.G Punjab Technical University Department of ECE Beant College of Engineering & Technology DAV Institute of Engineering & Technology

The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing ***, diverse steganography techniques using edge identification have been proposed in *** methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.

关键词： Information security Adaptive steganography Fuzzy edge detection Pattern recognition

Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition

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Friction 2017年第1期5卷 66-86页

作者： sanjeev kATOCH Rakesh SEHGAL Vishal singh Centre for Materials Science and Engineering National Institute of Technology Hamirpur(HP)177005 IndiaInstitute for Auto Parts & Hand Tools Technology A-9 Phase V Focal Point Ludhiana(Punjab)141010 India Department of Mechanical Engineering National Institute of Technology Hamirpur(HP)177005 India Centre for Materials Science and Engineering National Institute of Technology Hamirpur(HP)177005 India

Cryogenic treatment (CT) is a relatively new field,which has emerged during the last three decades of the twentieth ***,its impact on material shaping and making tool life,and enhancement of their mechanical properties are quite *** selection of appropriate process parameters for CT is essential for cost reduction and optimum *** study focuses on the influence of key parameters of CT cycles (i.e.,soaking temperature and duration) on the friction and wear behavior of AISI H13 hot die steel under dry sliding conditions against hardened and tempered AISI D3 cold work tool steel (counter face) at varying sliding speeds and *** models have been developed for wear rate,the average coefficient of friction,and maximum contact temperature using the Box-Cox *** developed mathematical models have been validated by comparing with the experimental ***,the optimum values of the process parameter have been employed to maximize the output and validate the same by confirmation of the *** the best of our knowledge,this is the first study that demonstrates the modeling and optimization of sliding friction and wear characteristics of AISI H13 under varied CT cycles.

关键词： cryogenics treatment hot die steel friction wear modeling Box-Cox method optimization

Evaluation and analysis of cutting speed, wire wear ratio, and dimensional deviation of wire electric discharge machining of super alloy Udimet-L605 using support vector machine and grey relational analysis

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Advances in Manufacturing 2018年第2期6卷 225-246页

作者： Somvir singh Nain Dixit Garg sanjeev kumar Department of Mechanical Engineering National Institute of Technology Kurukshetra 136119 India Department of Mechanical Engineering PEC University of Technology Chandigarh 160012 India

The current study investigates the behavior of wire electric discharge machining （WEDM） of the super alloy Udimet-L605 by employing sophisticated machine learning approaches. The experimental work was designed on the basis of the Taguchi orthogonal L27 array, consid- ering six explanatory variables and evaluating their influ- ences on the cutting speed, wire wear ratio （WWR）, and dimensional deviation （DD）. A support vector machine （SVM） algorithm using a normalized poly-kernel and a radial-basis flow kernel is recommended for modeling the wire electric discharge machining process. The grey rela- tional analysis （GRA） approach was utilized to obtain the optimal combination of process variables simultaneously, providing the desirable outcome for the cutting speed, WWR, and DD. Scanning electron microscope and energy dispersive X-ray analyses of the samples were performed for the confirmation of the results. An SVM based on the radial-basis kernel model dominated the normalized poly- kernel model. The optimal combination of process vari- ables for a mutually desirable outcome for the cutting speed, WWR, and DD was determined as Ton1, Toffa, Ip1, WT3, SV1, and WF3. The pulse-on time is the significant variable influencing the cutting speed, WWR, and DD. The largest percentage of copper （8.66%） was observed at the highest cutting speed setting 7.05% of copper at the low of the machine compared to cutting speed setting of the machine.

关键词： Support vector machine (SVM) Greyrelational analysis (GRA) Wire electric dischargemachining (WEDM) Udimet-L605 Scanning electronmicroscope (SEM) Wire wear ratio (WWR)