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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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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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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Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…The simulator uses sampling-based path planning algorithms such as RRT*, Fast RRT*, RRT*-Smart, informed-RRT*, and Honey Bee Mating Optimization-based Fast-RRT*. …”
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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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Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…While deep learning-based computer vision techniques have emerged as powerful tools for crop disease recognition, these methods are heavily reliant on large datasets, which are often difficult to obtain in practical agricultural settings. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…Consequently, SNet inherits TNet’s capabilities and further refines them during optimization. For comparison, we combine three interpolation algorithms with three super-resolution algorithms and select the one with the best performance. …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

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Research on Urban Traffic Signal Control Systems Based on Cyber Physical Systems by Li-li Zhang, Qi Zhao, Li Wang, Ling-yu Zhang

“…With this proposed system, managers and researchers can realize the construction and simulation of various types of traffic scenarios, the rapid development, and optimization of new control strategies and can apply effective control strategies to actual traffic management. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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Causal Unit Selection using Tractable Arithmetic Circuits by Haiying Huang, Adnan Darwiche

“…This is done through compiling the meta-model into a special class of tractable arithmetic circuits that allows the computation of optimal units in time linear in the circuit size. …”
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Image Super Resolution Reconstruction Based on Multi-Level Residual Skip Connection Network by WANG Xiaoyu, LU Jianyu, WEI Yuxin, YU Yue

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Three-Dimensional Guidance Approach with Obstacle Avoidance against Maneuvering Targets by Zi-jie Jiang, Xiu-xia Yang, Yi Zhang, Cong Wang, Hao Yu

“…Finally, to solve the above optimization problems, a hybrid solver is developed based on the adaptive moment estimation (Adam) algorithm, whose output will serve as the real-time guidance command. …”
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning by Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo

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