Performance evaluation of different building envelopes integrated with phase change materials in tropical climates by Rolains Golchimard Elenga, Li Zhu, Steivan Defilla

“…To achieve this goal, a multiobjective genetic algorithm is used in conjunction with EnergyPlus building energy models to determine the optimal balance between total building energy consumption, lifecycle cost, and CO2 emissions. …”
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Drilling dynamics measurement of drilling motors and its application in recognition of motor operation states through machine learning by Fei Li, Haolan Song, Yifan Wang

“…This paper presents a miniature vibration recorder, an automatic statistical analysis method, and a layered recognition algorithm to resolve these challenges and improve tool maintenance efficiency. …”
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Static Voltage Stability Evaluation and Correction Strategy Based on Stage Solving Strategy and SIFT by Yan Wen, Xiaoming Liu, Yongzhi Zhou, Huiwen Zhang, Donglei Sun

“…Aiming at the static voltage instability problem of the power grid caused by large-scale access of renewable energy sources, the study adopts the scale invariant feature transform algorithm for boundary feature extraction, while optimizing the traditional generalized resilience index of the power grid. …”
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Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks by Shichao Sun, Zhengyu Duan, Dongyuan Yang

“…The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.…”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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MultS-ORB: Multistage Oriented FAST and Rotated BRIEF by Shaojie Zhang, Yinghui Wang, Jiaxing Ma, Jinlong Yang, Liangyi Huang, Xiaojuan Ning

“…Experimental results demonstrate that for blurred images affected by illumination changes, the proposed method improves matching accuracy by an average of 75%, reduces average error by 33.06%, and decreases RMSE (Root Mean Square Error) by 35.86% compared to the traditional ORB algorithm.…”
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An adaptive continuous threshold wavelet denoising method for LiDAR echo signal by Dezhi Zheng, Tianchi Qu, Chun Hu, Shijia Lu, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

“…The adaptive threshold is dynamically adjusted according to the wavelet decomposition level, and the continuous threshold function ensures continuity with lower constant error, thus optimizing the denoising process. Simulation results show that the proposed algorithm has excellent performance in improving SNR and reducing root mean square error (RMSE) compared with other algorithms. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

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Energy-Balanced Data Gathering and Aggregating in WSNs: A Compressed Sensing Scheme by Xiaofei Xing, Dongqing Xie, Guojun Wang

“…In WSNs, data aggregating can reduce data transmission cost and improve energy efficiency. Existing CS-based data gathering work in WSNs utilizes the centralized method to process the data by a sink node, which causes the load imbalance and “coverage hole” problems, and so forth. …”
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Modular-based psychotherapy (MoBa) versus cognitive–behavioural therapy (CBT) for patients with depression, comorbidities and a history of childhood maltreatment: study protocol fo... by Elisabeth Schramm, Martin Hautzinger, Carolin Jenkner, Moritz Elsaesser, Sabine Herpertz, Hannah Piosczyk

“…By optimally tailoring module selection and application to the specific needs of each patient, MoBa has great potential to improve the currently unsatisfying results of psychotherapy as a bridge between disorder-specific and personalised approaches.Methods and analysis In a randomised controlled feasibility trial, N=70 outpatients with episodic or persistent major depression, comorbidity and childhood maltreatment are treated in 20 individual sessions with MoBa or standard cognitive–behavioural therapy for depression. …”
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Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…The proposed TL-SAM framework effectively extracts spatial and spectral features from patient health data, optimizing classification accuracy. Furthermore, the model employs an Improved Wild Horse Optimization with Levy Flight Algorithm (IWHOLFA) for hyperparameter tuning, enhancing its predictive performance. …”
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A PSO-XGBoost Model for Predicting the Compressive Strength of Cement–Soil Mixing Pile Considering Field Environment Simulation by Jiagui Xiong, Yangqing Gong, Xianghua Liu, Yan Li, Liangjie Chen, Cheng Liao, Chaochao Zhang

“…A cement–soil preparation system considering actual immersion conditions was established, based on controlling the initial water content state of the foundation soil before pile formation and applying submerged conditions post-formation. Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. …”
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Analysis of injured-skin SS-OCT images based on combined attention UNet. by Xiyu Zheng, Jingyuan Wu, Qiong Ma, Diantao Luo, Qingyu Cai, Haiyang Sun, Hongxing Kang

“…To enhance image clarity, we applied noise reduction using the BM3D algorithm. We employed an improved UNet network model that incorporates SimAM and PSA modules, forming three attention mechanisms: TandemAT-UNet, ParallelAT-UNet, and NestedAT-UNet. …”
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Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…The results of three different cases, minimum, average, and specific cost time slots, show that the system with RESs outperforms the case of without RESs, resulting in an 11.25% improvement in cost reduction and a 7.29% improvement in PAR reduction.…”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

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A Fruit-Tree Mapping System for Semi-Structured Orchards Based on Multi-Sensor-Fusion SLAM by Bingjie Tang, Zhiyang Guo, Chuanrong Huang, Shuo Huai, Jingyao Gai

“…Secondly, a fruit tree localization algorithm was developed to localize the fruit trees around the robot using both images and LiDAR point clouds, after which the global positions of the detected fruit trees were optimized using the SLAM-derived robot pose real-time. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…The purpose of the work is the development of basic data structures, speed-efficient and memoryefficient algorithms for tracking changes in predefined decisions about sets of shortest paths on transport networks, notifications about which are received by autonomous coordinated transport agents with centralized or collective control. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…This research underscores the potential of integrating MD simulations with ML methodologies to improve the accuracy and efficiency of aqueous solubility predictions in drug development.…”
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Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

“…The Strategic Choice Approach (SCA) was employed to structure complex decision-making processes, leveraging the expertise of industry professionals to identify key uncertainties and variables. A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

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