User Cost Minimization and Load Balancing for Multiple Electric Vehicle Charging Stations Based on Deep Reinforcement Learning by Yongxiang Xia, Zhongyi Cheng, Jiaqi Zhang, Xi Chen

“…In the second stage, we use the DRL algorithm. In the DRL algorithm, we design a novel reward function that enables charging stations to meet user charging demands while minimizing user charging costs and reducing the load gap among distribution networks. …”
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SV-SAE: Layer-Wise Pruning for Autoencoder Based on Link Contributions by Joohong Rheey, Hyunggon Park

“…This paper introduces a layer-wise pruning algorithm specifically for multilayer perceptron-based autoencoders. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…A new algorithm called YOLO-APDM is proposed to address low quality and multi-scale target detection issues in infrared road scenes. …”
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Multiobjective Coverage Control Strategy for Energy-Efficient Wireless Sensor Networks by Hui Zhou, Tian Liang, Chen Xu, Jing Xie

“…A new evolutionary algorithm named Multiobjective free search algorithm (MOFS) is designed for WSN optimization problem based on fitness functions and binary coding schemes. …”
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Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems by Ahmed Al Hammadi, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri, Paschalis C. Sofotasios, Merouane Debbah

“…Moreover, the synergy between the MPF and the DQL algorithms is investigated. To this end, we demonstrate that the MPF algorithm maximizes the fairness amongst the users while the DQL algorithm maximizes the overall SE and improves the robustness against the noise. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Transcranial direct current stimulation and methylphenidate interact to increase cognitive persistence as a core component of metacontrol: Evidence from aperiodic activity analyses by Yang Gao, Anna Helin Koyun, Veit Roessner, Ann-Kathrin Stock, Moritz Mückschel, Lorenza Colzato, Bernhard Hommel, Christian Beste

“…Background: Metacontrol is the ability to optimize the balance between cognitive persistence and flexibility. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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Estimation of Leaf Chlorophyll Content of Maize from Hyperspectral Data Using E2D-COS Feature Selection, Deep Neural Network, and Transfer Learning by Riqiang Chen, Lipeng Ren, Guijun Yang, Zhida Cheng, Dan Zhao, Chengjian Zhang, Haikuan Feng, Haitang Hu, Hao Yang

“…Leaf chlorophyll content (LCC) serves as a vital biochemical indicator of photosynthetic activity and nitrogen status, critical for precision agriculture to optimize crop management. While UAV-based hyperspectral sensing offers maize LCC estimation potential, current methods struggle with overlapping spectral bands and suboptimal model accuracy. …”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
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Fusion-Based Localization System Integrating UWB, IMU, and Vision by Zhongliang Deng, Haiming Luo, Xiangchuan Gao, Peijia Liu

“…Among them, visual–inertial odometry (VIO)-based techniques are notably limited by lighting conditions, while ultrawideband (UWB)-based algorithms are highly susceptible to environmental interference. …”
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Anomaly-Based Intrusion Detection System for the Internet of Medical Things by Eichie Franklin, Bernardi Pranggono

“…Our hyperparameter optimization using the Random search algorithm accurately classified normal cases for all six models, with Random Forest (RF) and K-Nearest Neighbors (KNN) performing the best in accuracy. …”
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Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model by Yingzhang Wang, Li Zhang, Yang Chen, Chaokai Li, Baocheng Du, Jinlin Han

“…The real-world driving emission model is then embedded into the dynamic planning algorithm using a bi-variate interpolation algorithm on the state-space plane. …”
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An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks by Pengcheng Fu, Hongying Tang, Yongbo Cheng, Baoqing Li, Hanwang Qian, Xiaobing Yuan

“…Then, we put forward a novel energy-balanced sensor nodes scheduling algorithm, Greedy Balance Replace Heuristic Algorithm, to select a near-optimal task sensor set from the candidate sensor node set to balance tracking quality and network lifetime. …”
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Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

“…By targeting regions most relevant to the human visual system, the proposed method enhances perceptual quality while optimizing resource usage, making it particularly suitable for embedded systems and bandwidth-limited communication channels. …”
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Optimasi Proses Klasterisasi di MySQL DBMS dengan Mengintegrasikan Algoritme MIC-Kmeans Menggunakan Bahasa SQL dalam Stored Procedure by Issa Arwani

“…Median Initial Centroid (MIC)-Kmeans algorithm is a development of the K-means algorithm that can provide the optimal solution in determining the initial centroid which has an impact on the accuracy and duration of iterations. …”
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Investigation of comparative machine learning models in effluent dephenolization process onto H3PO4-anchored corn cob by Chijioke Elijah Onu, Joseph Tagbo Nwabanne, Ositadimma Chamberline Iheanocho, Paschal Enyinnaya Ohale, Chiamaka Peace Onu, Marcel Ikenna Ejimofor, Suraj Kumar Bhagat, Christian O. Asadu, Christopher C. Obi, Chidiogo Ezekwem

“…Artificial intelligence models such as adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and response surface methodology (RSM) were used in modeling the dephenolization process. Genetic algorithm (GA) was used to optimize the best models. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…This shows that K-means discretization plays a role in optimizing the performance of the Naïve Bayes algorithm to produce better accuracy. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Conventional autofocusing algorithms operate under the assumption that measurement errors primarily perturb phase components while exerting negligible influence on signal envelopes. …”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

“…Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of-the-art DE algorithm. …”
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