Encoding-Based Machine Learning Approach for Health Status Classification and Remote Monitoring of Cardiac Patients by Sohaib R. Awad, Faris S. Alghareb

“…In short, this study aims to explore how ML algorithms can enhance diagnostic accuracy, improve real-time monitoring, and optimize treatment outcomes. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

“…Simulation results demonstrate the superior performance of the proposed framework and the novel resource allocation algorithm based on alternating optimization. These results highlight the transformative potential of IRS with discrete phase shifts in enhancing EH-CRN efficiency, particularly in improving energy harvesting and SU throughput under practical constraints.…”
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A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…MHMXAI approach selects the features with the highest scores from the Metaheuristic algorithm-Eagle Search Strategy, Hybrid Metaheuristic algorithm-Great Salmon Run-Thermal Exchange Optimization and eXplainable AI (XAI) tools like Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP) for their effectiveness. …”
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A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

“…Most of modern technological networks that can perform their tasks with various distinctive levels of efficiency are multistate networks, and reliability is a fundamental attribute for their safe operation and optimal improvement. …”
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Power Allocation Technology of Long Time Multi-Star Hopping Beam for LEO Satellite by Ziyi LIU, Xiaoning ZHANG, Zesong FEI

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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. …”
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Modular-based psychotherapy (MoBa) versus cognitive–behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol fo... by Elisabeth Schramm, Martin Hautzinger, Carolin Jenkner, Moritz Elsaesser, Sabine Herpertz, Hannah Piosczyk

“…By optimally tailoring module selection and application to the specific needs of each patient, MoBa has great potential to improve the currently unsatisfying results of psychotherapy as a bridge between disorder-specific and personalised approaches.Methods and analysis In a randomised controlled feasibility trial, N=70 outpatients with episodic or persistent major depression, comorbidity and childhood maltreatment are treated in 20 individual sessions with MoBa or standard cognitive–behavioural therapy for depression. …”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…MethodsTo address these issues, Multi-Way Improved Whale Optimization Algorithm (MWIWOA) was proposed to optimize the SVM-based prediction model for the internal corrosion rate of long-distance submarine pipelines. …”
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Designing and implementing a Web-based real time routing service for crisis management (a case study for district 11 of Tehran) by javad sadidi, seyed hassan hosseini sajedi

“…Timing framework associated with catastrophes is one of the most important issues in crisis management. In such cases, being immediate has a considerable importance and web based real-time routing service as an important tool has a significant role in relief operations improvement. …”
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Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading by Yi-Jui Chiu, Bi Li, Chin-Ling Chen, Shui-Yang Lien, Ding Chen, Ji-Ming Yi, Yung-Hui Shih

“…In addition, under fast-varying solar irradiation and local shading, the speed, ability, and stability of the improved MPPT system with the PF-MPPT algorithm when tracking the maximum power were 9.52, 1.32, and 1.84 times of the MPPT system with the P&O algorithm and 2.18, 1.41, and 2.00 times of the MPPT system with the particle swarm optimization algorithm, respectively.…”
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Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
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Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

“…The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. …”
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Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

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Green Energy Strategic Management for Service of Quality Composition in the Internet of Things Environment by Jianhao Gao

“…The simulation results reveal that MFO has good optimization effect in the abovementioned models, and the optimization effect of MFO is improved by 8% and 6% compared with the genetic algorithm and particle swarm optimization, so as to realize the green energy strategic management of QoS composition in the environment of IoT.…”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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Notice of Violation of IEEE Publication Principles: Dynamic Embedding and Scheduling of Service Function Chains for Future SDN/NFV-Enabled Networks by Haotong Cao, Hongbo Zhu, Longxiang Yang

“…If the resource and QoS requirements of the VNFs are not satisfied, a re-embedding and re-scheduling scheme will be triggered in order to optimize certain existing VNFs. The dynamic embedding and scheduling algorithm has flexible network function placement and improves the underlying resource utilization. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

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