The Alliance of BIM and Artificial Intelligence: Challenges for a Reinvented Future – The State of the Art by Ellyssa Abdelmoula, Meriem Zammel, Najla Allani

“…A literature review was conducted to examine research published on the integration of BIM and AI, identifying key challenges, gaps and proposed solutions to improve interoperability, data security and workflow optimization. …”
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Pavement pothole detection system based on deep learning and binocular vision by Tian Guan, Jianyuan Cai, Yu Wang, Wei Yang, Xiaobo Chang, Yi Han

“…A pothole distance estimation model based on binocular vision was established by analyzing the stereo ranging model and semi-global block matching algorithm. …”
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Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based... by Yasin P, Ding L, Mamat M, Guo W, Song X

“…The optimal model was further refined through threshold tuning to enhance performance metrics. …”
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基于逆动力学的柔性机械臂力学特性研究 by 刘晓芳, 张洛花

“…In order to study the mechanical property of the flexible manipulator,through using the low vibration manipulator inverse dynamics and time-varying modal expansion method to establish dynamics model of the single-link flexible manipulator,the manipulator self-excited vibration model is introduced to calculate the elastic model,the calculation method of optimal input torque and optimal torque disturbance is proposed,and the dynamic response analysis on different working conditions of joints is carried on,and finally the related model is established based on numerical calculation data to make a numerical validation.The results show that in the process of flexible manipulator modeling includes nonlinear terms,eliminating model linearization error,giving the structure and movement of the manipulator arm when requires,the optimal input torque can be calculated firstly to achieve the openloop control manipulator.By using perturbation model to understand the role of flexible,the convergence and speed of the algorithm are significantly improved compared with ordinary model,the results have good robustness.When rotating joints fixed,manipulator endpoint for harmonic vibration,if the natural frequency of the vibration frequency is close to the manipulator,the disturbance response divergence,and vice versa for the steady state vibration,when the joint moves fixed,manipulator endpoint for uniform rotation,when the speed is less than the critical speed,the disturbance attenuation response or stabilization,otherwise divergent.…”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The model’s architecture was optimized to handle variations in lighting conditions, angles, and orientations commonly found in field settings. …”
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Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu, Xialin Zhang

“…The system integrates three core technological components: (1) a heterogeneous cloud resource scheduling method employing an optimized CMMN algorithm with unified cloud API standardization to enhance task distribution efficiency; (2) a block model-based dynamic data aggregation approach utilizing semantic unification and attribute mapping for multi-source geological data integration; (3) a GPU-accelerated rendering framework implementing occlusion culling and batch processing to optimize 3D visualization performance. …”
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INFLUENCE OF MAIN GEAR RATIO ON CAR FUEL EFFICIENCY IN THE DRIVE CYCLE by S. A. Gorozhankin, N. V. Savenkov, V. V. Ponyakin

“…The article presents the improvement efficiency of fuel and economic properties of the vehicle in WLTC driving cycle by means of the main gear ratio changing. …”
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Current approaches to diagnosis, treatment, and monitoring in patients with cryopyrin-associated periodic syndromes (CAPS) by S. O. Salugina, E. S. Fedorov, N. N. Kuzmina

“…Interleukin-1 inhibitors are target agents, by which one can monitor activity and prevent complications. The given algorithm will be able to improve the timely diagnosis of CAPS and to optimize treat-to-target treatment and management in patients.…”
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Transient stability assessment of wind turbine grid-connected systems using ISSA-MSVR by FAN Hong, XU Yongjie, XU Tao

“…To address the issue of inaccurate transient stability analysis in power systems after wind farm integration， this paper proposes a method combining improved sparrow search algorithm （ISSA）-optimized multi-output support vector regression （MSVR）. …”
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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

“…Moreover, this algorithm determines the optimal offloading strategy based on the global model while considering trustworthiness, the heterogeneous nature of tasks, resource availability, and latency. …”
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Predicting Diabetic Retinopathy and Nephropathy Complications Using Machine Learning Techniques by D. R. Manjunath, J. J. Lohith, S. Selva Kumar, Abhijit Das

“…This paper shows the possibility of machine learning based frameworks in diabetic complication management by predicting accurately and in time. These models can be integrated into clinical decision support systems (CDSS) to give insights to clinicians, improve patient outcomes through personalized interventions and optimize resource allocation. …”
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Prevalence and patterns of antiretroviral resistance in HIV-infected Latin American asylum seekers by Samuel Manzano, Juan Torres-Macho, Neda Deihim-Rahampour, Guillermo Cuevas, Felipe Perez-Garcia, Luz Balsalobre, Salvador Resino, Matilde Sanchez-Conde, Jorge Valencia, Pablo Ryan

“…These findings underscore the need for optimized treatment strategies and improved healthcare access for migrant populations with HIV.…”
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Research on High-Precision Motion Planning of Large Multi-Arm Rock Drilling Robot Based on Multi-Strategy Sampling Rapidly Exploring Random Tree* by Qiaoyu Xu, Yansong Lin

“…A dual Jacobi iterative inverse solution method, coupled with a forward kinematics error compensation model, is introduced to dynamically correct target positions, improving end-effector positioning accuracy. …”
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Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

“…To address these issues, this study proposes a helmet detection method based on unmanned aerial vehicles (UAVs) and the YOLOv8 object detection algorithm. The method utilizes UAVs to flexibly capture construction site images, combined with the optimized YOLOv8s model, and employs transfer learning to annotate and train labels for “person” and “helmet”. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

“…The GML considers geographical characteristics in the analysis by calculating the optimal bandwidth area in its algorithm. The study employs nine scenarios to identify which parameters significantly contribute to the model and determine the best parameter combinations. …”
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Resource allocation mechanism in the TWDM-PON and C-RAN joint architecture with hybrid energy supply by Ruyan WANG, Ningning XU

“…Aiming at the problems of low resource utilization rate,high energy consumption and poor user service quality in the existing virtualized Cloud Radio Access Network,an energy-aware virtualized resource allocation mechanism with hybrid energy supply was proposed.According to the energy sources and energy consumption of different network devices,energy arrival and energy consumption models were established.Furthermore,under the premise of guaranteeing the quality of user services,considering proportional fairness and energy consumption optimization,distributed algorithms based on asynchronous update were used to allocate resources and harvested energy for different types of virtual cloud radio access networks and user virtual base stations to effectively improve the energy efficiency of network.The simulation results show that the proposed resource allocation mechanism can reduce energy consumption while effectively reducing the latency and improving the throughput.…”
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Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
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Physical Implementation and Experimental Validation of the Compensation Mechanism for a Ramp-Based AUV Recovery System by Zhaoji Qi, Lingshuai Meng, Haitao Gu, Ziyang Guo, Jinyan Wu, Chenghui Li

“…Based on the structural and geometric characteristics of the platform, a dual-channel closed-loop control strategy was proposed utilizing midpoint tracking of the capture window, accompanied by multi-level software limit protection and automatic centering mechanisms. The control algorithm was implemented using a discrete-time PID structure, with gain parameters optimized through experimental tuning under repeatable disturbance conditions. …”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…We propose a dual-stream neural network architecture that simultaneously models students’ knowledge states and cognitive load levels to optimize learning trajectories. …”
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