Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks by Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

“…To achieve this goal, we formulate the model partitioning problem among heterogeneous hardware and introduce a hierarchical searching algorithm to solve the optimization problem. Besides, a mixed-precision pipeline method is used to reduce the cost of inter-cluster communications. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”

Design a low-noise 5GHz wideband microwave power amplifier using 90nm CMOS technology with area reduction employing an active inductor by Taha Naufal Fadhil, A.Z. Yonis

“…Lastly, this work illustrates how genetic algorithm optimization has drastically changed LNA design. …”
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Calcium dynamics in habenular astrocytes regulate active coping within behavioral transitions by Léo Michel, Denys Osypenko, Patricia Molina, Kadir A. Mutlu, Salvatore Lecca, Chihiro Hisatsune, Katsuhiko Mikoshiba, Toko Kikuchi, Emre Yaksi, Andrea Volterra, Manuel Mameli

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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Methods: This study combines a literature review and case analysis to assess the impact of AI on forestry logistics. Machine Learning algorithms, optimization systems, and monitoring tools based on the Internet of Things (IoT) and computer vision were analyzed to assess impacts in areas such as transportation planning, inventory management, and forest monitoring. …”
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Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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A Novel Minimization Method for Sensor Deployment Via Heuristic 2-Sat Solution by Waleed Ahmed, Ali Muhammad Ali Rushdi

“…Other algorithms like Pseudo-Boolean SAT Solvers can also be used for the minimization purpose. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…Statistical <i>t</i>-tests confirm the superiority of DRL-NSABC over other algorithms, while achieving a variance of 0.00014. Moreover, DRL-NSABC demonstrates the fastest convergence, reaching near-optimal accuracy within the first 100 epochs. …”
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Weibull-Type Incubation Period and Time of Exposure Using <i>γ</i>-Divergence by Daisuke Yoneoka, Takayuki Kawashima, Yuta Tanoue, Shuhei Nomura, Akifumi Eguchi

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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

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Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods by Anton S. Chepurnenko, Tatiana N. Kondratieva, Ebrahim Al-Wali

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Enabling High-Level Worker-Centric Semantic Understanding of Onsite Images Using Visual Language Models with Attention Mechanism and Beam Search Strategy by Hui Deng, Kejie Fu, Binglin Yu, Huimin Li, Rui Duan, Yichuan Deng, Jia-rui Lin

“…However, a significant portion of this information remains underutilized by construction managers due to the limitations of existing image processing algorithms. These algorithms primarily rely on low-level visual features and struggle to capture high-order semantic information, leading to a gap between computer-generated image semantics and human interpretation. …”
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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…As software systems grow in size, complexity, and functionality, the parallel expansion of the test suite leads to an inefficient utilization of computational power and time, presenting challenges to optimization. …”
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An Application of Site Selection for Solid Waste Management System Using Neutrosophic Set by A.Savitha Mary, D. Sarukasan, C. Kayelvizhi, L. Jethruth Emelda Mary, F. Josephine Daisy, K. Pitchaimani

“…To improve the efficiency and accuracy of waste management site selection, novel computational algorithms have been developed using a proposed distance formula. …”
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Machine Learning to Assess Relatedness: The Advantage of Using Firm-Level Data by Giambattista Albora, Andrea Zaccaria

“…We also discuss the effect of using parameter optimization and community detection algorithms to identify clusters of related companies and products, finding that a partition into a higher number of blocks decreases the computational time while maintaining a prediction performance well above the network-based benchmarks.…”
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Multi-Dimensional Arms for Combinatorial Multi-Armed Bandit by Qi Li, Lijun Cai

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Satellite-Derived Bathymetry Combined With Sentinel-2 and ICESat-2 Datasets Using Deep Learning by Weidong Zhu, Yanying Huang, Tiantian Cao, Xiaoshan Zhang, Qidi Xie, Kuifeng Luan, Wei Shen, Ziya Zou

“…This article proposes a convolutional neural network and bidirectional long short-term memory hybrid model based on the Bayesian optimization algorithm (BOA-CNN-BILSTM) to enhance bathymetric inversion accuracy and efficiency. …”
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Introducing a Novel Method to Identify the Future Trend of Nikkei 225 Stock Price in Order to Reduce Investment Risk by Freyr Björgvinsson

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Performance of Various Artificial Intelligence Models for Predicting Temperature in an Industrial Building—A Case Study by Johan Roussel, Zoubeir Lafhaj, Pascal Yim, Thomas Danel, Laure Ducoulombier

“…This research underscores the importance of an algorithmic approach tailored to both the thermal characteristics of the building and the computational capabilities of industrial infrastructure, with feature importance analysis confirming that external temperature and heating system states are the primary predictive factors, thereby helping to optimize industrial operations.…”
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