Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries by Sadiqa Jafari, Jisoo Kim, Wonil Choi, Yung-Cheol Byun

“…Using sophisticated machine learning algorithms, we suggest an all-encompassing methodology for predicting the SOH. …”
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Effective Diabetic Retinopathy Classification With Siamese Neural Network: A Strategy for Small Dataset Challenges by Maria Tariq, Vasile Palade, Yingliang Ma

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Peculiarities of the pedagogical situation at the training of bachelors on the direction 08.03.01 «Construction» on the example of discipline of specialization by Nelli I. Taraseeva

“…For the efficient operation of the system “lecturer” – “student” it is necessary to have highly qualified lecturers and modern material and technical equipment for the educational process.The goal of this work is to perform the analysis of the current teaching situation; on the example of the profile discipline to develop a learning algorithm and its implementation in accordance with the laws of the didactics of Bachelors in 08.01.03 construction direction “Highways”.Materials and methods: the methods of research consist in studying the basics of Didactics (learning theory) with positions of interdisciplinary areas of knowledge, such as general theory and graph sys tems, familiarizing with the functioning laws of the learning process, pedagogical technologies of domestic and foreign researchers. …”
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EDUCATIONAL AUTONOMY AS A PREREQUISITE FOR THE FORMATION OF THE INDEPENDENCE OF FUTURE PSYCHOLOGISTS by Voshkolup Hanna

“…It was found that the formation of students’ independence under the influence of educational au- tonomy is considered as a process of so-called cooperative learning, during which guidance (coordina- tion, mentoring) takes place on the part of teachers, in contrast to traditional pedagogical functions. …”
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Learning Regionalization Using Accurate Spatial Cost Gradients Within a Differentiable High‐Resolution Hydrological Model: Application to the French Mediterranean Region by Ngo Nghi Truyen Huynh, Pierre‐André Garambois, François Colleoni, Benjamin Renard, Hélène Roux, Julie Demargne, Maxime Jay‐Allemand, Pierre Javelle

“…A possible approach is to search for a transfer function that quantitatively relates physical descriptors to conceptual model parameters. …”
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Intellectual ability and cortical homotopy development in children and adolescents by Li-Zhen Chen, Xi-Nian Zuo

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Brain tumor detection across diverse MR images: An automated triple-module approach integrating reduced fused deep features and machine learning by Yugal Pande, Jyotismita Chaki

“…Brain tumors pose a significant threat to human health due to their potential to disrupt normal brain function. Early and accurate detection is crucial for effective treatment. …”
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Validation of the Virtual Reality Stroop Room: Effects of inhibiting interfering information under time-pressure and task-switching demands by Veronika Ringgold, Luca Abel, Bjoern M. Eskofier, Nicolas Rohleder

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Enhancing software development effort estimation with a cloud-based data framework using use case points, fuzzy logic, and machine learning by Ritu, Pankaj Bhambri

“…Fuzzy logic predicts the time using fuzzy rules and a triangle membership function to improve accuracy and reliability. By comparing the results with well-known datasets, the estimation's accuracy is shown. …”
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LM-CycleGAN: Improving Underwater Image Quality Through Learned Perceptual Image Patch Similarity and Multi-Scale Adaptive Fusion Attention by Jiangyan Wu, Guanghui Zhang, Yugang Fan

“…At the same time, the Learned Perceptual Image Patch Similarity (LPIPS) is introduced into the loss function to make the training process more focused on the structural information of the image. …”
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Designing and implementing healthcare technology for rehabilitation processes—a wicked problem? Lessons learned from a collaboration between healthcare personnel and technologists... by Jo Inge Gåsvær, Ilona Heldal, Tobba Sudmann

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Multi-User Opportunistic Spectrum Access for Cognitive Radio Networks Based on Multi-Head Self-Attention and Multi-Agent Deep Reinforcement Learning by Weiwei Bai, Guoqiang Zheng, Weibing Xia, Yu Mu, Yujun Xue

“…Meanwhile, a multi-constraint dynamic proportional reward function is designed to guide the agent in selecting more rational actions by refining the constraints and dynamically adjusting the reward proportion. …”
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Quantitative Analysis of Vertical and Temporal Variations in the Chlorophyll Content of Winter Wheat Leaves via Proximal Multispectral Remote Sensing and Deep Transfer Learning by Changsai Zhang, Yuan Yi, Shuxia Zhang, Pei Li

“…Quantifying the vertical distribution of leaf chlorophyll content (LCC) is integral for a comprehensive understanding of the physiological status and function of winter wheat crops, having significant implications for crop management and yield optimization. …”
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Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation S... by Byungeun Shon, Sook Jin Seong, Eun Jung Choi, Mi-Ri Gwon, Hae Won Lee, Jaechan Park, Ho-Young Chung, Sungmoon Jeong, Young-Ran Yoon

“…The ML model was developed using 8 clinical laboratory parameters, including complete blood count and liver and kidney function tests, along with the dates of acquisition. …”
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Comparative study of interpretable and black-box machine learning for modeling mechanical and tribological properties of 3D-printed PLA/date pits composites by Ahmed Asker, Ahmed Fouly, Mohamed G. B. Atia, Hany S. Abdo, Omar Salah

“…3D-printed polymers have been applied in various fields. Machine learning (ML) has revolutionized material science by providing powerful tools for modeling complex properties. …”
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Basrah Score: a novel machine learning-based score for differentiating iron deficiency anemia and beta thalassemia trait using RBC indices by Salma A. Mahmood, Asaad A. Khalaf, Saad S. Hamadi

“…This study proposes a novel and interpretable diagnostic model, the Basrah Score, developed using Elastic Net Logistic Regression (ENLR). This machine learning–based approach yields a flexible discrimination function that adapts to variations in clinical and environmental factors. …”
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Integrative multi-omics analysis and machine learning reveal the unique role of ASCC3 in combination with various immune-related genes in rectal adenocarcinoma by Chuang Miao, Fei Qian

“…Furthermore, ASCC3 may regulate tumor immunity by affecting T cell function.ConclusionASCC3 can serve as an independent prognostic factor for READ and can synergize with various immune-related genes to influence patient prognosis.…”
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Exploring statistical and machine learning methods for modeling probability distribution parameters in downtime length analysis: a paper manufacturing machine case study by Vladimir Koković, Kosta Pavlović, Andjela Mijanović, Slavko Kovačević, Ivan Mačužić, Vladimir Božović

“…Our approach specifically focuses on modeling parameters of these distribution, rather than directly modeling probability density function (PDF) values, as is common in other approaches. …”
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Region Boosting for Real-Time Object Detection Using Multi-Dimensional Attention by Jinlong Chen, Kejian Xu, Yi Ning, Zhi Xu

“…Moreover, we introduce a new label assignment strategy called STA, along with a novel loss function named GEIOU Loss, to further refine our object detector’s performance. …”
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Microstrip Patch Antenna Design Using a Four-Layer Feed Forward Artificial Neural Network Trained by Levenberg-Marquardt Algorithm by Jitu Prakash Dhar, Maodudul Hasan, Eisuke Nishiyama, Ichihiko Toyoda

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