Effect of Periodic Fluctuations of Cutting Mode Parameters on the Temperature of the Front Face of a Turning Tool by E. V. Fominov, V. E. Gvindjiliya, A. A. Marchenko, C. G. Shuchev

“…Modern research aimed at improving the efficiency of the workpart procedures emphasizes the importance of taking into account the effect of periodic disturbances on the cutting dynamics. …”
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Unfolding insights about resilience and its coping strategies by medical academics and healthcare professionals at their workplaces: a thematic qualitative analysis by Salman Yousuf Guraya, Jacqueline Maria Dias, Mohamed Ahmed Eladl, Ayah Mohammad Rajai Rustom, Fatima Audi Saleem Alalawi, Majid Hassan Saleh Alhammadi, Yusra Ahmed Mohammed Ahmed, Amna Ali Omran Taryam Al Shamsi, Sarah Juman Bilalaga, Alfred Nicholson, Hani Malik, Shaista Salman Guraya

“…MHAs were concerned about academic output and research, while HCPs were stressed about patient care, delivery of services, and workload. …”
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THE PROPOSAL MODEL OF RATIONAL WORKFORCE ASSIGNMENT IN DOKUZ EYLUL UNIVERSITY BY ANALYTIC HIERARCHY PROCESS BASED 0-1 INTEGER PROGRAMMING by Yılmaz GÖKŞEN, Hakan AŞAN, Onur DOĞAN, Mustafa ÜNLÜ, Osman PALA

“…Analytical hierarchy process which is a method of multi-criteria decision-making model has been preferred as a method. …”
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Fuzzy logic-controlled three-phase dynamic voltage restorer for enhancing voltage stabilization and power quality by Abu Shufian, Sowrov Komar Shib, Durjoy Roy Dipto, Md Tanvir Rahman, Nasif Hannan, Shaikh Anowarul Fattah

“…The selection of FLC stems from its ability to mimic human decision-making and handle non-linear, imprecise data, offering superior adaptability and precision compared to traditional control methods. Unlike conventional algorithms, which struggle under fluctuating grid conditions and complex disturbances, FLC dynamically adjusts the output of DVR based on real-time reference and load voltage measurements. …”
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Multi-Task Reinforcement Learning Based on Parallel Recombination Networks by Manlu Liu, Qingbo Zhang, Weimin Qian

“…The proposed method efficiently learns the relationships between tasks from parallel recombination networks and determines the optimal path for a task through a weight network. …”
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Potato Disease and Pest Question Classification Based on Prompt Engineering and Gated Convolution by Wentao Tang, Zelin Hu

“…To address these issues, a dataset construction method based on prompt engineering is proposed, along with a question classification method utilizing a gated fusion–convolutional neural network (GF-CNN). …”
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Deep Reinforcement Learning for Vectored Thruster Autonomous Underwater Vehicle Control by Tao Liu, Yuli Hu, Hui Xu

“…To confirm the algorithm’s effectiveness, a series of simulations are carried out in the designed simulation environment, which is a method to save time and improve efficiency. Simulation results prove the feasibility of the deep RL algorithm applied to the control system for AUV. …”
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Dynamic reconfiguration of distribution networks considering wind-PV-load scenarios by LIU Ronghui, CHEN Geng, SUN Gaiping, LIN Shunfu, WANG Xu

“…To address these issues， this paper proposes a dynamic reconfiguration method for distribution networks that accounts for wind-PV-load scenarios. …”
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Around-Body Versus On-Body Motion Sensing: A Comparison of Efficacy Across a Range of Body Movements and Scales by Katelyn Rohrer, Luis De Anda, Camila Grubb, Zachary Hansen, Jordan Rodriguez, Greyson St Pierre, Sara Sheikhlary, Suleyman Omer, Binh Tran, Mehrail Lawendy, Farah Alqaraghuli, Chris Hedgecoke, Youssif Abdelkeder, Rebecca C. Slepian, Ethan Ross, Ryan Chung, Marvin J. Slepian

“…Shoulder abduction/adduction and shoulder flexion/extension motions had the lowest agreement efficiencies with 24.49% and 26.28%, respectively. MoCa was comparable to BioStamp in terms of angular displacement, though velocity and linear speed output could benefit from additional processing. …”
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BEV-CAM3D: A Unified Bird’s-Eye View Architecture for Autonomous Driving with Monocular Cameras and 3D Point Clouds by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…While LiDAR-based models dominate due to accurate depth sensing, their cost and sparse outputs have driven interest in camera-based systems. …”
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Design and Implementation of an EMG-Based Communication Interface for Enhancing Interaction with Deaf Individuals by Oussama EL GHOUL, Amina BEN HAJ AMOR, Mohamed JEMNI

“…Traditional communication methods often fall short in providing efficient and seamless interaction with the deaf community. …”
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Leveraging Large Language Models and Agent-Based Systems for Scientific Data Analysis: Validation Study by Dale Peasley, Rayus Kuplicki, Sandip Sen, Martin Paulus

“…MethodsAn agent-based system based on large language models was designed to analyze and contextualize complex scientific datasets using a “plan-and-solve” framework. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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A New Heterogeneous Hybrid Massive MIMO Receiver With an Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning by Feng Shu, Baihua Shi, Yiwen Chen, Jiatong Bai, Yifan Li, Tingting Liu, Zhu Han, Xiaohu You

“…Massive multiple input multiple output (MIMO) antenna arrays eventuate a huge amount of circuit costs and computational complexity. …”
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Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…In the class of approximate methods, we point out heuristic and meta-heuristic approaches. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…Regarding the other effective parameters of product quality, focusing on machine health is not enough to guarantee the quality of the output product. Hence, the proposed method in this research builds upon the conventional ZDM approaches since it provides an extended view on the effective root causes that influence product quality. …”
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Scenario-Based Optimized Coordinated Scheduling of Transmission and Distribution Networks With Multiple Timescales Considering Renewables Correlations by Ruifeng Zhao, Ruhao Wu, Jiangang Lu, Fengchao Chen, Qiwei Li

“…First, an adaptive multivariate nonparametric kernel density estimation (KDE) method is developed to construct high-dimensional joint probability distributions of DER outputs, capturing complex correlations between wind power and photovoltaics. …”
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Presenting the conceptual model of organizational democracy with an emphasis on the development of employees' psychological capital by Sattar jahantabi neghad, Foad Makvandi, ezat allah Kiani, ghanbar Amirnegad, Vahid Chenari

“…Abstract The purpose of this research is to present a conceptual model of organizational democracy with an emphasis on the development of psychological capital in the employees of National Iranian Oil Company. The research method is quantitative, and a researcher-made questionnaire was used to collect data, analyzed by SPSS and SmartPLS 3 software. …”
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LiDAR Sensor Parameter Augmentation and Data-Driven Influence Analysis on Deep-Learning-Based People Detection by Lukas Haas, Florian Sanne, Johann Zedelmeier, Subir Das, Thomas Zeh, Matthias Kuba, Florian Bindges, Martin Jakobi, Alexander W. Koch

“…However, to design these systems cost- and energy-efficiently, the relationship between the measurement data and final object detection output with deep neural networks (DNNs) has to be elaborated. …”
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Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers by Junxiao Wang, Shiying Zhang, Jia Li, Mei Deng, Zhi Zeng, Zehua Dong, Fangfang Chen, Wen Liu, Lianlian Wu, Honggang Yu

“…Recently, deep learning-based IHC biomarker prediction models have been widely developed, but few investigations have explored their clinical application effectiveness. Methods In this study, we aimed to create an automatic pipeline for the construction of deep learning models to generate AI-IHC (Artificial Intelligence) output using H&E whole slide images (WSIs) and compared the pathology reports by pathologists on AI-IHC versus conventional IHC. …”
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