A Comparative Study of Deep Reinforcement Learning Algorithms for Urban Autonomous Driving: Addressing the Geographic and Regulatory Challenges in CARLA by Yechan Park, Woomin Jun, Sungjin Lee

“…This performance gap highlights the advantage of approaches like TQC and SAC, which address <i>Q</i>-value overestimation through statistical methods, in improving the robustness and effectiveness of autonomous driving in diverse urban environments.…”
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Social Network Analysis Reveals Spatiotemporal Patterns of Green Space Recreational Walking Between Workdays and Rest Days by Jiali Zhang, Zhaocheng Bai

“…Growing concerns about the negative impacts of high-density built environments on residents’ physical and mental health have made optimizing recreational walking networks in green spaces a crucial issue for improving urban public health service efficiency. While previous studies have largely focused on static accessibility measures, these methods cannot capture actual human recreational behaviors and temporal variations in green space usage. …”
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Exploring Clinicians’ and Patients’ Acceptance and Utilization of a Digital Solution to Support Individualized Care in Diabetes Specialist Outpatient Care (DigiDiaS): Qualitative S... by Maria Aadland Mollestad, Annesofie Lunde Jensen, Heidi Holmen, Tone Singstad, Eirik Årsand, Jacob Andreas Winther, Astrid Torbjørnsen

“…ResultsOur analysis resulted in the following three main themes that describe the interplay between clinicians’ and patients’ acceptance, utilization, and perceived clinical value of a digital outpatient solution: (1) clinicians’ acceptance of the digital outpatient solution influences patients’ acceptance, (2) variations in the use of different features influence the extent of individualized care, and (3) clinicians’ and patients’ utilization influences perceived care efficiency and quality. …”
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An Explicit Investigation in Demand Side Management Based on Artificial Intelligence Techniques by Md. Abul Kalam, Abhinav Saxena, Md. Zahid Hassnain, Amit Kumar Dash, Jay Singh, Gyanendra Kumar Singh

“…Less fuel consumption also helps to reduce carbon emissions from these power generation projects, which helps power suppliers save on additional fuel costs due to severe and unpredictable margin variations in power generation. The various aspects of the charging of electric vehicles using demand-side management, considering the clustering methods and forecasting strategies with brief descriptions, data, range have been assessed by using the different artificial intelligence and machine learning methods.…”
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Design and simulation of reduced switch converter based solar PV and energy storage fed shunt active power filter with butterfly optimization by Koganti Srilakshmi, Sravanthy Gaddameedhi, Alapati Ramadevi, Praveen Kumar Balachandran, J. Ganesh Prasad Reddy, Ramprasad Vangalapudi

“…The efficiency of the optimally designed controller is examined with three test studies using MATLAB/Simulink. …”
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Quantum machine learning regression optimisation for full-scale sewage sludge anaerobic digestion by Yomna Mohamed, Ahmed Elghadban, Hei I Lei, Amelie Andrea Shih, Po-Heng Lee

“…Abstract Anaerobic digestion (AD) is a crucial bioenergy source widely applied in wastewater treatment. However, its efficiency improvement is hindered by complex microbial communities and sensitivity to feedstock properties. …”
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Optimized hybrid deep learning for cross-linguistic sentiment analysis: a novel approach by Vipin Jain, Lokesh Malviya, Anjana .S

“…However, traditional sentiment analysis methods often struggle with multilingual data due to the complexities of language variations and differences in culture. …”
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Multi-Dimensional Anomaly Detection and Fault Localization in Microservice Architectures: A Dual-Channel Deep Learning Approach with Causal Inference for Intelligent Sensing by Suchuan Xing, Yihan Wang, Wenhe Liu

“…The system reduced the average troubleshooting time by 43% and false localization rates by 31% compared to state-of-the-art methods, while maintaining a computational efficiency suitable for real-time monitoring. …”
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RFID-Based Real-Time Salt Concentration Monitoring with Adaptive EKF by Renhai Feng, Xinyi Lin

“…Salt concentration monitoring is crucial for industrial process control and wastewater management, yet existing methods often lack real-time capability or require invasive sampling. …”
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Dynamic load balancing in cloud computing using predictive graph networks and adaptive neural scheduling by K. Rajammal, M. Chinnadurai

“…The traditional load balancing procedures struggle to adapt the real-time variations which leads to inefficient resource utilization and increased response times. …”
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Finite-element analysis on the parameters influencing the brittle crack arrest in steel plates by Jeongung Park, Gyubaek An

“…The arrest performance is typically assessed by determining the brittle crack arrestability value (Kca) through large-scale experimental methods. However, due to the high cost, time, and equipment demands of such tests, alternative approaches using small-scale specimens and numerical simulations have been actively investigated to estimate Kca more efficiently. …”
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Performance Analysis of Resampling Techniques for Overcoming Data Imbalance in Multiclass Classification by Anggit Larasati, Sugiyarto Surono, Aris Thobirin, Deshinta Arrova Dewi

“…This research shows that the performance of MobileNetV2, which implements the bootstrap-based random oversampling technique, has the highest accuracy compared to random undersampling and no resampling methods. The oversampling technique with the RMSprop optimizer produced the highest accuracy, namely 95%. …”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…Additionally, DTC-FL and DTC-SMC excel in robustness against system parameter variations, a valuable asset for evolving industrial environments. …”
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Transferring CLIP for visual grounding in remote sensing images by Linlin Liang, Yizhuo Quan, Chengbo Wang, Yuanfei Chang, Yanyou Qiao

“…This effectively enhances the feature representation of target objects, thereby mitigating issues such as scale variations and cluttered backgrounds in remote sensing imagery. …”
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Impact of Premedication on Preoperative Anxiety in Females with Gynecological Diseases by I. G. Bobrinskaya, V. M. Yaltonsky, S. S. Khaikin, O. A. Bykova

“…Objective: to study preoperative psychoemotional, autonomic, and hematodynamic responses in patients to develop criteria for evaluating the efficiency of premedication.Subjects and methods. Sixty gynecological patients (mean age 38.5±1.1 years), who were being prepared for elective surgery, were examined. …”
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Comparison of growth, photosynthetic, and chlorophyll fluorescence characteristics of different native cultivars in Castanea henryi by XU Bin, WU Jingyi, WU Jianfeng, SU Xinyu, ZHAO Junru, ZHU Zhoujun, LI Jianxin

“…The recorded parameters included: initial fluorescent light (F0); maximal fluorescence (Fm), PS Ⅱ primary light energy conversion efficiency (Fv/Fm), potential efficiency of primary conversion of PS Ⅱ (Fv/F0), actual photochemical efficiency of PS Ⅱ (Fv'/Fm'), photochemical quenching coefficient (qP), electron transport rate (ETR), and non-photochemical quenching (NPQ). …”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…On one hand, existing methods are constrained by the limited availability of labeled data, often performing inadequately when addressing complex protein-ligand interactions. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…However, in the presence of targets with high aspect ratios and significant scale variations in remotely sensed images, existing methods prefer CNN or transformer architectures but suffer from the limitations of overly fixed receptive fields or excessive computational complexity. …”
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MSKT: multimodal data fusion for improved nursing management in hemorrhagic stroke by Ting Zhou, Dandan Li, Jingfang Zuo, Aihua Gu, Li Zhao

“…Results The proposed MSKT-NSGP model outperformed traditional algorithms in prediction accuracy, computational efficiency, and uncertainty handling. For hematoma expansion prediction, it achieved 85.5% accuracy, an area under the curve (AUC) of 0.87, and reduced mean squared error (MSE) by 18% compared to the sparse variational Gaussian process (SVGP). …”
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FEATURES OF THE CHRONIC PAIN SYNDROME IN PATIENTS WITH RHEUMATOID ARTHRITIS AND MEDICAL DIAGNOSTIC TACTICS by M. A. Gromova, S. E. Myasoedova

“…The integrated approach to diagnostics of a chronic pain syndrome for rheumatoid arthritis allows to estimate pain strengths in dynamics of disease development, to reveal existence of pain variations, anxiety and depression. It enables usage of patient maintenance tactics and increases efficiency of treatment in therapeutic practice.…”
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