Memory-Efficient Batching for Time Series Transformer Training: A Systematic Evaluation by Phanwadee Sinthong, Nam Nguyen, Vijay Ekambaram, Arindam Jati, Jayant Kalagnanam, Peeravit Koad

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Quantum Computing and Machine Learning in Medical Decision-Making: A Comprehensive Review by James C. L. Chow

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Automatic Scheduling Method for Customs Inspection Vehicle Relocation Based on Automotive Electronic Identification and Biometric Recognition by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Jinchao Xiao, Jingfeng Yang

“…This research addresses these challenges by integrating EVI and biometric systems into a comprehensive framework aimed at improving vehicle scheduling. The proposed method utilizes genetic algorithms and intelligent optimization techniques to dynamically allocate resources and prioritize vehicle movements based on real-time data. …”
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Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0 by Vicente González-Prida, Carlos Parra Márquez, Pablo Viveros Gunckel, Fredy Kristjanpoller Rodríguez, Adolfo Crespo Márquez

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Enhanced Wind Energy Forecasting Using an Extended Long Short-Term Memory Model by Zachary Barbre, Gang Li

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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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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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Adaptive Cut Selection in Mixed-Integer Linear Programming by Turner, Mark, Koch, Thorsten, Serrano, Felipe, Winkler, Michael

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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…The extended search mode was refined by integrating the simplex method, while the optimization capability of the Whale Optimization Algorithm (WOA) was enhanced with Levy flight to improve step length. …”
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A Hybrid Dynamic Path-Planning Method for Obstacle Avoidance in Unmanned Aerial Vehicle-Based Power Inspection by Zheng Huang, Chengling Jiang, Chao Shen, Bin Liu, Tao Huang, Minghui Zhang

“…Based on a breadth-first search strategy, the path obtained is optimized to reduce path complexity. To address the RRT* algorithm’s limitation in dynamic obstacle avoidance, a local path-planning method combining the improved DWA algorithm is proposed, improving efficiency in areas with dense obstacles. …”
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Research on the cooperative offloading strategy of sensory data based on delay and energy constraints by Peiyan YUAN, Saike SHAO, Ran WEI, Junna ZHANG, Xiaoyan ZHAO

“…The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center, which protects data privacy and improves user experience.In the process of cooperative offloading, the transmission of the sensing data and the information exchange among edge servers will consume system resources, resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently, a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally, simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA), the distributed optimization algorithm (DOA), and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.…”
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Bio-inspired clustering scheme for Internet of Drones application in industrial wireless sensor network by Farooq Aftab, Ali Khan, Zhongshan Zhang

“…The results indicate that the proposed scheme has improved 60% and 38% with respect to ant colony optimization and grey wolf optimization, respectively, in terms of average cluster building time while average energy consumption has improved 23% and 33% when compared to the ant colony optimization and grey wolf optimization, respectively.…”
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Exploration of Energy-Saving Chilling Landscape Design Based on Algo for Group Intelligence by Zhuo Li

“…The experimental results show that the algo for group intelligence outperforms another algorithm in terms of solving ability to the extent that the average optimization ability is improved by 13.45%, so the algo for group intelligence demonstrates its superior ability to take into account both local and global search. …”
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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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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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Adaptive Safe Data Driven Control Strategy for Closed Loop System by Wen Ruchun

“…Finally, some simulation results are given to show our theoretical results on adaptive safe data driven control and its improved switching form. Generally, this new paper extends our previous contributions about data driven control to complete its synthesis research, combining some advanced factors together from both the academic theory and practice, for example, adaptation, safety, optimization theory and algorithm, switching logic together.…”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Methods:To reduce inter-user interference,an improved K-means algorithm is proposed to group users and select a cluster head for each group of users, which maximizes the correlation of user channels in the same cluster and reduces the correlation between users in different clusters as much as possible;Then,a low-complexity analog precoding is designed to maximize the array gain of the antenna based on the relevant user channel matrix composed of the cluster head set, followed by a digital precoding designed to eliminate inter-user interference with the maximum equivalent channel gain between beams using a forced-zero technique; Finally, an EE maximization problem is formed to optimize the transmit power under users'quality of services and total transmit power constraints,and a two-layer iterative algorithm is proposed for the resulting non-convex optimization problem. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…In addition to supporting eco-friendly mobility, the technology lowers grid dependency and improves energy reliability. The manuscript introduces a hybrid technique for efficient electric vehicle (EV) charging integrating the Dollmaker Optimization algorithm (DOA) and spatial Bayesian neural network (SBNN). …”
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Pickup and delivery planning for the crowdsourced freight delivery routing problem. by Jingxian Zhang

“…The objective is to minimize total service costs, including fixed vehicle costs, transportation costs, and penalty costs for delays, while planning routes that cover all orders. To solve this combinatorial optimization problem, we propose an improved partheno genetic algorithm (IPGA) and a simulated annealing algorithm (SA). …”
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