Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU by Jonathan Decker, Vincent Florens Hasse, Julian Kunkel

“…Kubernetes has emerged as the industry standard for container orchestration in cloud environments, with its scheduler dynamically placing container instances across cluster nodes based on predefined rules and algorithms. Various efforts have been made to extend and improve upon the Kubernetes scheduler. …”
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Effective Detection of Malicious Uniform Resource Locator (URLs) Using Deep-Learning Techniques by Yirga Yayeh Munaye, Aneas Bekele Workneh, Yenework Belayneh Chekol, Atinkut Molla Mekonen

“…Through iterative refinement, we optimized the model’s performance to maximize its effectiveness. …”
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AI-Enhanced Design and Application of High School Geography Field Studies in China: A Case Study of the Yellow (Bohai) Sea Migratory Bird Habitat Curriculum by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

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Hybrid Multi-Granularity Approach for Few-Shot Image Retrieval with Weak Features by Aiguo Lu, Zican Li, Yanwei Liu, Pandi Liu, Ke Wang

“…The optimized loss function further enhances the robustness and distinctiveness of features, improving retrieval accuracy. …”
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Data Augmentation for Voiceprint Recognition Using Generative Adversarial Networks by Yao-San Lin, Hung-Yu Chen, Mei-Ling Huang, Tsung-Yu Hsieh

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Nav2Scene: Navigation-driven fine-tuning for robot-friendly scene generation by Bowei Jiang, Tongyuan Bai, Peng Zheng, Tieru Wu, Rui Ma

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Efficient RANSAC in 4D Plane Space for Point Cloud Registration by Chang Liu, Chao Liu, Yuming Zhang, Zhongqi Wu, Jianwei Guo

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PID Control and Input Shaping for Quadrotor UAV Stabilization and Payload Swing Reduction by Liyana Ramli, Izzuddin M. Lazim, Amalin Aisya Awi, Aina Syazwin Shukor

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Information-guided adaptive learning approach for active surveillance of infectious diseases by Qi Tan, Chenyang Zhang, Jiwen Xia, Ruiqi Wang, Lian Zhou, Zhanwei Du, Benyun Shi

“…Based on a probabilistic model, we evaluate the information gain of monitoring a spatio-temporal target and design a greedy selection algorithm for monitoring targets selection. …”
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Dynamic Control and Analysis of Dual Active Bridge Converters in Grid-Connected PV-BESS by Mehmet Can Sekanli, Samet Yalçin, Okan Bingol

“…The Perturb & Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm optimized power extraction from the PV array, while the DAB converter employed Single Phase Shift (SPS) control for efficient, bidirectional energy management. …”
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Optimising Connectivity and Energy: The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by Izzah N. Buang, K. Zen, Syahrul N. Junaini

“…However, the mobility of IoT devices introduces challenges in optimizing energy efficiency. This study provides a comprehensive review of energy-efficient routing algorithms for LoRaWAN in mobile IoT applications. …”
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Myocarditis Diagnosis Using Semi-Supervised Generative Adversarial Network and Differential Evolution by Haifeng Gui, Na Zhang

“…To minimize reliance on hyperparameters, the Random Key method is employed, optimized using the DE algorithm. The efficacy of the model is demonstrated on the Z-Alizadeh Sani myocarditis dataset, with further validation achieved through experiments on the EMIDEC dataset, assessing transfer learning (TL) effects. …”
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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

“…Active learning Kriging（ ALK） model is able to only approximate the performance function in a narrow region around the limit state surface.Therefore,the efficiency of reliability analysis is remarkably improved.However,most of the existing strategies build the ALK model based on a so-called DACE toolbox.DACE cannot obtain the global optimal parameter of a Kriging model and the training point chosen in each iteration cannot be the optimal one.In this paper,one famous global optimization,i.e.…”
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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

“…The influence of the PV output power characteristics and local shading on the power generation efficiency of the PV system was analyzed using MATLAB and the improved model. Aiming at the problem that most maximum power point tracking (MPPT) algorithms have difficulty quickly tracking the maximum power point (MPP) under fast-varying solar irradiation; a polynomial fitting-MPPT (PF-MPPT) algorithm and a simple fitting-MPPT (SPF-MPPT) algorithm based on polynomial fitting were proposed to track the maximum power point under the fast-varying solar irradiation. …”
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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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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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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…For this purpose, a new decision-making model is developed that includes expert weighting with the entropy game, evaluation balancing with the Q-learning algorithm, calculation of criterion weights with the least squares optimization (LSO) and alternative ranking with the molecular ranking (MORAN) method. …”
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Degradation and reliability assessment of accuracy life of RV reducers by XU Hang, NIE Yixuan, WEN Dongjie, REN Jihua, HONG Zhihui

“…A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. …”
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Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System by Guo Tong, Wang Jiawen, Liang Yingnan, Peng Buyu, Liu Tao, Liu Yiqun

“…Through mathematical models and computer simulations, it is the current mainstream optimization direction to optimize the structure of the boom linkage mechanism and improve its strength and stability. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. …”
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