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2024 IEEE 14th Annual computing and Communication Workshop and Conference, CCWC 2024

作者： Mulder, Aaron M. Kandalaft, Nabeeh Grand Valley State University Padnos College of Engineering & Computing Grand Rapids United States

ISBN: (纸本)9798350360134

Embedded machine learning has presented the ability to increase the effectiveness of embedded systems by offering a new means to process and adapt to complex data enabling them to detect patterns, anomalies, and repetition in sensor data. Myoelectric sensing systems can take advantage of these properties by detecting patterns from an array of electrodes to categorize and adapt to a specific individual's muscle movements, enhancing control of robotic systems, or prosthetics. This article discusses a proposed implementation of such a system using edge computing neural networks on an STM32F746 MCU using a TI ADS1198 ADC SPI peripheral. © 2024 IEEE.

关键词： Edge computing

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Automatic lung cancer detection using hybrid particle snake swarm optimization with optimized mask RCNN

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Multimedia Tools and Applications 2024年第31期83卷 76807-76831页

作者： Sudha, R. Maheswari, K. M. Uma Department of Computer Science and Engineering School of computing College of engineering and technology SRM Institute of Science and Technology Kattankulathur India Department of Computing Technologies School of Computing College of engineering and technology SRM Institute of Science and Technology Kattankulathur India

As a result of its aggressive nature and late identification at advanced stages, lung cancer is one of the leading causes of cancer-related deaths. Lung cancer early diagnosis is a serious and difficult challenge that is crucial to a person's survival. The first diagnosis of the malignant nodules is typically made using chest radiography (X-rays) and computed tomography (CT) scans;however, the potential presence of benign nodules results in incorrect conclusions. The early phases of both benign and malignant nodules exhibit striking similarities. In this paper, a novel deep learning-based model is proposed for the precise diagnosis of malignant nodules. The proposed approach consists of two stages namely, pre-processing and lung nodule detection. Initially, the Lung CT scan images are collected from the dataset. Then, to remove the noise present in the input image, we apply an adaptive median filter. Then, to enhance the image, Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied. After pre-processing, the image is given to the optimized mask RCNN classifier to detect the malignant and benign nodules. To enhance the performance of the Mask RCNN classifier, the hyper-parameters are optimally selected using hybrid particle snake swarm optimization (PS2OA). The proposed PS2OA is a hybridization of particle swarm optimization (PSO) and snake swarm optimization (SSO). The performance of the proposed approach is analyzed based on different metrics and effectiveness compared with state-of-the-art works. The proposed approach attained the maximum accuracy of 97.67%. This work aimed at assisting radiologists to detect and diagnose small-size pulmonary nodules more accurately. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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Adaptive Multi-strategy Rabbit Optimizer for Large-scale Optimization

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Journal of Bionic engineering 2025年第1期22卷 398-416页

作者： Baowei Xiang Yixin Xiang Department of Computing School of Electronic and Information Engineering Taizhou UniversityTaizhou318000China Department of Software Engineering College of Software Nankai UniversityTianjin300350China

As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly ***,the challenge lies in identifying the right parameters and strategies for these *** this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization *** employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy *** parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational *** offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and *** is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to *** results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and ***,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.

关键词： Adaptive parameter Large scale optimization Rabbit algorithm Swarm intelligence engineering optimization

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Ensemble Multimodal Disease Risk Prediction: Integrating Chest X-Ray Images and Medical Data with ERSGB-RSW Method

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Journal of The Institution of Engineers (India): Series B 2025年第2期106卷 697-711页

作者： Amirtharaj, Shiny Irene David Marudappa, Pushpalatha Sachin, Lade Khalid, Mohammad Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Campus Chennai India

The emergence of multimodal disease risk prediction signifies a pivotal shift towards healthcare by integrating information from various sources and enhancing the reliability of predicting susceptibility to specific diseases. Traditional methods face several challenges such as limited capacity to handle heterogeneous datasets, high computational power, and less efficiency. To solve the drawbacks a novel Ensemble Random Support vector Gradient Bayes Random Seal Whiskers method is proposed. In this study, the Random Forest is utilized to extract chest X-ray images from the dataset, the Support Vector Machine (SVM) is employed to categorize images by integrating various medical data modalities, the gradient boosting is implemented to capture complex relationships in chest X-ray images and Naive Bayes is used to classify image features. Also, a weighted average ensemble is employed to integrate the outcomes of the methods namely Random Forest, SVM, Gradient boosting, and Naive Bayes by assigning different weights based on its predictions in this work, the Harbor seal whiskers optimization algorithm with a random update is employed to optimize the tuned parameters based on the datasets. The experimental results revealed that the proposed method improved the efficiency in the process of multimodal disease risk prediction. © The Institution of Engineers (India) 2024.

关键词： Support vector machines

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Study of the Inhibition of Schumann Resonance-inspired Electromagnetic Field on Cancer Cell Proliferation

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Journal of Bionic engineering 2025年第1期22卷 341-353页

作者： Xianqiang Yan Xuelei Liu Shujun Zhang Zhenning Liu Luquan Ren Key Laboratory of Bionic Engineering(Ministry of Education) College of Biological and Agricultural EngineeringJilin UniversityChangchun130022China School of Computing and Engineering University of GloucestershireThe ParkCheltenhamGL502RHUK School of Mechanical Engineering Shandong University of TechnologyZibo255000China

Organisms on Earth evolve and coexist with natural Electromagnetic Fields(EMFs).Although many reports have suggested the potential anti-neoplastic effects of EMFs with specific parameters,the studies on the influence of natural EMFs on cancers are still ***,an EMF emitter has been developed to investigate the effects of the extremely-low frequency SR-mimicking EMF(SREMF)on cancer and normal cell *** numerical simulation has revealed that the emitter with specific parameters is able to enhance EMF intensity and uniformity on the designated plane above the *** importantly,honeycomb-like emitter array can generate a stronger EMF intensity on the 20 mm plane above the *** colony formation assays have demonstrated that SREMF generated by the honeycomb-like emitter array can significantly inhibit Hela cell proliferation in a cell-density-dependent *** morphological changes of SREMF-exposed Hela cells suggest that the anti-proliferative effect of SREMF may be caused by apoptosis *** contrast,no detrimental effect is observed for SREMF-treated normal cells,which probably can be explained by the evolutionary ***,this work can not only contribute to understanding the impact of natural EMF on creatures,but also afford a novel strategy to personalized cancer prevention and treatment.

关键词： Electromagnetic fields(EMFs) Schumann resonance EMF emitter Cancer Cell proliferation

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Embedded Virtualization on RISC-V with seL4 14

Embedded Virtualization on RISC-V with seL4

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14th IEEE Annual Ubiquitous computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Doran, Michael A. Kandalaft, Nabeeh Grand Valley State University Padnos College of Engineering & Computing Grand Rapids United States

ISBN: (纸本)9798350304138

Embedded virtualization is a key enabler for system designers to meet SWaP-C requirements for mission critical systems that execute various military, aerospace, medical, and commercial applications. The demand is now on the software designer to implement high assurance software that can reliably satisfy safety and time critical requirements. This article presents the first public implementation of the formally proven microkernel, seL4, on the RISC-V hypervisor using H-extension v0.6.1. This implementation uses the Rocketchip softcore executing in the FPGA fabric of a Zynq UltraScale+MPSoC ZCU102. © 2023 IEEE.

关键词： Formal methods

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Optimizing Image Retrieval in Cloud Servers with TN-AGW: A Secure and Efficient Approach

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Journal of The Institution of Engineers (India): Series B 2025年第2期106卷 459-473页

作者： Ponnuviji, N.P. Nirmala, G. Kokila, M. L. Sworna Priyadharshini, S. Indra Department of Computer Science and Engineering RMK College of Engineering and Technology Puduvoyal Thiruvallur India Department of Computer Science and Engineering RMD Engineering College Chennai India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nādu Kattankulathur Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received considerable attention in transmitting data and ensuring data confidentiality among cloud servers and users. Various traditional image retrieval techniques regarding security have developed in recent years but they do not apply to large-scale environments. This paper introduces a new approach called Triple network-based adaptive grey wolf (TN-AGW) to address these challenges. The TN-AGW framework combines the adaptability of the Grey Wolf Optimization (GWO) algorithm with the resilience of Triple Network (TN) to enhance image retrieval in cloud servers while maintaining robust security measures. By using adaptive mechanisms, TN-AGW dynamically adjusts its parameters to improve the efficiency of image retrieval processes, reducing latency and utilization of resources. However, the image retrieval process is efficiently performed by a triple network and the parameters employed in the network are optimized by Adaptive Grey Wolf (AGW) optimization. Imputation of missing values, Min–Max normalization, and Z-score standardization processes are used to preprocess the images. The image extraction process is undertaken by a modified convolutional neural network (MCNN) approach. Moreover, input images are taken from datasets such as the Landsat 8 dataset and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset is employed for image retrieval. Further, the performance such as accuracy, precision, recall, specificity, F1-score, and false alarm rate (FAR) is evaluated, the value of accuracy reaches 98.1%, the precision of 97.2%, recall of 96.1%, and specificity of 917.2% respectively. Also, the convergence speed is enhanced in this TN-AGW approach. Therefore, the proposed TN-AGW approach achieves greater efficiency in image retrieving than other existing

关键词： Extraction

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TRS Scheduling for Improved QoS Performance in Cloud System

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Computers, Materials & Continua 2023年第4期75卷 1547-1559页

作者： G.John Samuel Babu M.Baskar Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India Department of Computing Technologies School of ComputingCollege of Engineering andTechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadline, and popularity. However, the methods are inappropriate forachieving higher scheduling performance. Regarding data security, existingmethods use various encryption schemes but introduce significant serviceinterruption. This article sketches a practical Real-time Application CentricTRS (Throughput-Resource utilization–Success) Scheduling with Data Security(RATRSDS) model by considering all these issues in task scheduling anddata security. The method identifies the required resource and their claim timeby receiving the service requests. Further, for the list of resources as services,the method computes throughput support (Thrs) according to the number ofstatements executed and the complete statements of the service. Similarly, themethod computes Resource utilization support (Ruts) according to the idletime on any duty cycle and total servicing time. Also, the method computesthe value of Success support (Sus) according to the number of completions forthe number of allocations. The method estimates the TRS score (ThroughputResource utilization Success) for different resources using all these supportmeasures. According to the value of the TRS score, the services are rankedand scheduled. On the other side, based on the requirement of service requests,the method computes Requirement Support (RS). The selection of service isperformed and allocated. Similarly, choosing the route according to the RouteSupport Measure (RSM) enforced route security. Finally, data security hasgets implemented with a service-based encryption technique. The RATRSDSscheme has claimed higher performance in data security and scheduling.

关键词： Cloud task scheduling TRS quality of service RSM route security data security SDE RATRSDS

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Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the Department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： Communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

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Carbon emission reduction and hydrogen production maximization from carbon emission-based hydrogen sources

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Environmental Science and Pollution Research 2024年 1-13页

作者： Abifarin, Johnson Kehinde Abifarin, Fredah Batale School of Engineering College of Engineering Computing and Cybernetics Australian National University Canberra Australia Department of Metallurgical and Materials Engineering Ahmadu Bello University Zaria Nigeria

This study aims to optimize hydrogen (H2) production via ethanol steam reforming (ESR) and water gas shift reaction (WGSR) pathways, focusing on minimizing CO, CO2, and CH4 emissions while maximizing H2 yield. Employing Taguchi grey relational analysis, we investigate the intricate balance between production conditions and multi-response gas generation. Utilizing Origin Pro software, regression modeling forecasts individual and overall gas generation. Our analysis identifies optimal conditions: a feed liquid flow rate of 2 mL/min, water-to-carbon ratio of 3, ESR temperature of 300 °C, and WGSR temperature of 350 °C. These conditions promise clean, efficient H2 production. Key results show the water-to-carbon ratio and ESR temperature contributing 59.22% and 32.69% to production conditions’ impact, respectively. Graphical and mathematical models validate these findings. Moving forward, further experimental validation of optimal conditions for multi-response gas generation is recommended. This study pioneers a transformative approach towards sustainable, environmentally friendly H2 production. © The Author(s) 2024.

关键词： Water gas shift

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