Intelligent Dual Basal–Bolus Calculator for Multiple Daily Insulin Injections via Offline Reinforcement Learning by Junyoung Yoo, Vega Pradana Rachim, Suyeon Jung, Sung-Min Park

“…These results suggest that our offline learning approach effectively mitigates early-stage risks while providing stable, personalized treatment optimization. …”
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Real-time active cell balancing using QPSO-controlled switched capacitor and transformer methods by S. Ida Evangeline, B. Subashini

“…The QPSO algorithm optimizes balancing strategies in real time, reducing computational load while achieving faster convergence and energy efficiency. …”
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Self-Adjusting Look-Ahead Distance of Precision Path Tracking for High-Clearance Sprayers in Field Navigation by Xu Wang, Bo Zhang, Xintong Du, Huailin Chen, Tianwen Zhu, Chundu Wu

“…This is done based on the principle of minimizing the overall error, enabling the dynamic and adaptive optimization of the look-ahead distance within the pure pursuit algorithm. …”
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Mixed Balanced Truncation for Reducing the Complexity of Large-Scale Electrical and Electronic System Simulations by Huy-Du Dao, Thanh-Tung Nguyen, Ngoc-Kien Vu, Van-Ta Hoang, Hong-Quang Nguyen

“…This paper proposes the Mixed Balanced Truncation (MBT) algorithm, which combines the strengths of Balanced Truncation (BT) and Positive-Real Balanced Truncation (PRBT) while addressing their respective limitations. …”
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Maintenance Scheduling Strategy for MMCs Within an MVDC System Using Sensitivity Analysis by Tae-Yang Nam, Dong-Il Cho, Joong-Woo Shin, Kwang-Hoon Yoon, Jae-Chul Kim, Won-Sik Moon

“…The proposed algorithm optimizes the maintenance timing and priority by performing a sensitivity analysis of the system reliability indicators, from both the consumer and operator perspectives. …”
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A hybrid blockchain-based solution for secure sharing of electronic medical record data by Gang Han, Yan Ma, Zhongliang Zhang, Yuxin Wang

“…This algorithm not only streamlines the signature process across chains but also strengthens system security and optimizes storage efficiency, addressing a key challenge in multi-chain systems. …”
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Joint uplink and downlink resource allocation for D2D communication based on weighted bipartite graph matching and interference clustering by SHEN Bin, YUAN Wenjun, LI Xuan

“…Moreover, the transmit power of DUE was optimized to maximize the system sum rate while ensured that DUE did not cause serious interference to CUE. …”
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Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process by Yang Zhou, Xinmin Tang, Xuanming Ren

“…Secondly, we adopt the Markov Decision Process as the autonomous decision-making method for the own aircraft, proposing a method by which to calculate the optimal decision sequence based on the prediction scenarios of the IMM algorithm; that is, in both multi-step prediction and single-step prediction scenarios, the payoff values of different action strategies at each decision moment are calculated to obtain the optimal decision sequence. …”
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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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Learned Shrinkage Approach for Low-Dose Reconstruction in Computed Tomography by Joseph Shtok, Michael Elad, Michael Zibulevsky

“…Our numerical simulations indicate that the proposed algorithm can manage well with noisy measurements, allowing a dose reduction by a factor of 4, while reducing noise and streak artifacts in the FBP reconstruction, comparable to the performance of a statistically based iterative algorithm.…”
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WSNs data acquisition by combining expected network coverage and clustered compressed sensing. by Zhouzhou Liu, Yangmei Zhang, Yang Bi, Jingxuan Wang, Yuanyuan Hou, Chao Liu, Guangyi Jiang, Shan Li

“…Combined with an optimized network coverage algorithm, a node scheduling strategy is introduced to focus on critical observation areas while minimizing overall energy consumption. …”
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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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Accelerated Tensor Robust Principal Component Analysis via Factorized Tensor Norm Minimization by Geunseop Lee

“…Experimental results demonstrate that our algorithm achieves significantly faster performance than existing reference methods known for efficient computation while maintaining high accuracy in recovering low-rank tensors for applications such as color image recovery and background subtraction.…”
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Fast Processing of Massive Hyperspectral Image Anomaly Detection Based on Cloud-Edge Collaboration by Yunchang Wang, Jin Sun, Yang Xu, Zhihui Wei, Shangdong Zheng, Zebin Wu

“…With the improvement of hyperspectral image resolution, existing anomaly detection algorithms find it challenging to quickly process large volumes of hyperspectral data while fully exploiting spectral information. …”
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A Study on Multi-ship Avoidance System for Unmanned Surface Vehicles Using the Quaternion Ship Domain and Collision Risk Index by Dong-Hun Lee, Mu-Yeong Seo, Hyo-Geun Lee, Won-Jun Yoo, Sanghyun Kim, Kwang-Jun Paik

“…This paper proposes a multi-ship collision avoidance algorithm that integrates the quaternion ship domain (QSD) and collision risk index (CRI) to assess collision risk and generate optimal avoidance trajectories. …”
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A Time- and Space-Integrated Expansion Planning Method for AC/DC Hybrid Distribution Networks by Yao Guo, Shaorong Wang, Dezhi Chen

“…A modified graph attention network (MGAT)-based deep reinforcement learning (DRL) algorithm is used for optimization, balancing economic and reliability objectives. …”
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Utilizing weak graph for edge consolidation-based efficient enhancement of network robustness by Wei Ding, Zhengdan Wang

“…We compare the proposed algorithm with optimal and approximate algorithms across graphs of varying scales. …”
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Zynq FPGA-Based Acceleration of Kernelized Correlation Filters via High-Level Synthesis of a Custom DFT Block by Enver Çavuş, Mustafa Yetiş

“…Within this framework, a custom combined DFT and inverse DFT IP, named CDFT, is developed and optimized on the Programmable Logic (PL) side of the Xilinx ZCU102 FPGA, whereas the rest of the KCF algorithm is run with customized Petalinux build on the (Processing System) side. …”
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Local Search-Based Metaheuristic Methods for the Solid Waste Collection Problem by Haneen Algethami

“…The routing solver in the Google OR-tools solver is utilised with three well-known metaheuristic methods for neighbourhood exploration: a guided local search (GLS), a tabu search (TS), and simulated annealing (SA), with two initialisation strategies, Clarke and Wright’s algorithm and the nearest neighbour algorithm. Results showed that optimal solutions are found in faster computational times than using only an IP solver, especially for large instances. …”
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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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