STUDI PENGUKURAN KONSTANTA DIELEKTRIK KAIN RAJUT PAKAN POLIESTER DAN KATUN MENGGUNAKAN METODE KAPASITANSI PERANGKAT KAPASITOR PLAT SEJAJAR by Taufik Munandar, Valentinus Galih Vidia Putra, Wiah Wardiningsih

“…The weft knitted fabric were fabricated using weft knit machine Stoll CMS 530HP. Six different samples of polyester and cotton knitted fabric were fabricated by computerized flat knitting machine. …”
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Do Mechatronic Poles Change the Gait Technique of Nordic Walking in Patients with Ischemic Heart Disease? by Agnieszka Szpala, Sławomir Winiarski, Małgorzata Kołodziej, Bogdan Pietraszewski, Ryszard Jasiński, Tadeusz Niebudek, Andrzej Lejczak, Dariusz Kałka, Karolina Lorek, Krzysztof Bałchanowski, Sławomir Wudarczyk, Marek Woźniewski

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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…This research presents a unique machine learning model based fault diagnosis and detection method for a 33 KW solar PV system at P.S.R. …”
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Is National Early Warning Score (NEWS) effective in older populations with acute illnesses? by Luke Oakes, Ella Riley, Amna Riaz, Radhiya Bakth, David Goldsmith, Vibhor Barve, Zahra Nejad, Sarah Md Fuad, Kausik Chatterjee

“…Integrating frailty scores and applying machine learning tools could refine risk prediction and guide timely, appropriate interventions. …”
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Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser by Takatomo Mihana, Yuta Terashima, Makoto Naruse, Song-Ju Kim, Atsushi Uchida

“…We examine the dependence of making correct decisions on different values of the memory parameter. The degree of adaptivity is found to be enhanced with a smaller memory parameter, whereas the degree of convergence to the correct decision is higher for a larger memory parameter. …”
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Computational modeling and thermal analysis of magnetized nanofluid flow with physio-chemical interaction and chemical reaction between two non-parallel walls by Shahid Sohail, Zahir Shah, Muhammad Rooman, Waris Khan, Mansoor H. Alshehri, Narcisa Vrinceanu, Elisabeta Antonescu

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BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART by ZHAO LiJuan, FAN JiaYi

“…Roller is an important task of the coal winning machine cutting coal institutions,its structure and motion parameters will directly affect the working efficiency and working reliability of coal winning machine.Based on virtual prototype technology coal winning machine the coupled model is established,through dynamic simulation of coal winning machine equivalent stress values of key parts;Simulation different drum rotating speed,drawing speed,cylinder helix Angle,and the cutting line spacing they cut the shell and the equivalent stress value of planet carrier,the roller structure and motion parameters on reliability of key parts of coal winning machine cutting part influence trend;Combined with neural network technology,with different roller structure and motion parameters of the equivalent stress of key parts of coal winning machine values as the neural network training sample,the helix Angle of optimization design,stress value of key parts in the hour of cylinder helix Angle.The research for the drum more accurate theoretical foundation for the selection of structure and motion parameters,has certain engineering application value.…”
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Gesture Recognition System Based on Time-Frequency Point Density of sEMG by Qiang Wang, Yao Chen, Chunhua Sheng, Shuaidi Song

“…It is usually realized by extracting the characteristics of different finger movements and then using machine learning or deep learning algorithms to classify and recognize them. …”
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Designing and planning a bioethanol supply chain network under uncertainty using a data-driven robust optimization model under disjunctive uncertainty sets by Farzaneh MansooriMooseloo, Maghsoud Amiri, Mohammad Taghi Taghavi Fard, Mostafa Hajiaghaei-Keshteli

“…Therefore, the aim of this study is to design and optimize the biomass-to-bioethanol supply chain network using data-driven robust optimization methods and disjunctive uncertainty sets.Methodology: The methodology of this study is a multi-methodology approach based on mathematical modeling and machine learning algorithms. Initially, uncertainty sets for the non-deterministic model parameter were created using K-means and SVC methods. …”
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Numerical examination of the chemically reactive MHD flow of hybrid nanofluids over a two-dimensional stretching surface with the Cattaneo–Christov model and slip conditions by Algehyne Ebrahem A., Alamrani Fahad Maqbul, Seada M. M., Saeed Anwar, Bognár Gabriella

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An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

“…In this study, support vector machine (SVM) is applied to develop prediction models for machining processes. …”
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Design and Development of Miniature Measuring Instrument for Parachute Cords Dynamic Load for Stepless Parachute Opening by Wei Liang, Xin Zhao, Pengpeng Wu, Yuxin Li, Shuai Lv

“…The force value of the miniature measuring instrument is calibrated and tested many times by using the microcomputer-controlled electronic universal testing machine. The experimental results show that the designed miniature measuring instrument has accurate data, strong stability, and good real-time performance, which meets the demand for real-time accurate measurement of miniature measuring instruments, and can provide reliable data for parachute cords parameter validation and stepless unfolding design.…”
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Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals by Jinge Xu, Christopher H. J. Moran, Arup Ghorai, Fazel Bateni, Jeffrey A. Bennett, Nikolai Mukhin, Koray Latif, Andrew Cahn, Pragyan Jha, Fernando Delgado Licona, Sina Sadeghi, Lior Politi, Milad Abolhasani

“…Abstract Metal halide perovskite (MHP) nanocrystals (NCs) offer extraordinary tunability in their optical properties, yet fully exploiting this potential is challenged by a vast and complex synthesis parameter space. Herein, we introduce Rainbow, a multi-robot self-driving laboratory that integrates automated NC synthesis, real-time characterization, and machine learning (ML)-driven decision-making to efficiently navigate MHP NCs’ mixed-variable high-dimensional landscape. …”
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SimProx: A Similarity-Based Aggregation in Federated Learning With Client Weight Optimization by Ayoub El-Niss, Ahmad Alzu'Bi, Abdelrahman Abuarqoub, Mohammad Hammoudeh, Ammar Muthanna

“…Federated Learning (FL) enables decentralized training of machine learning models across multiple clients, preserving data privacy by aggregating locally trained models without sharing raw data. …”
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Construction of a Deep Learning Model for Unmanned Aerial Vehicle-Assisted Safe Lightweight Industrial Quality Inspection in Complex Environments by Zhongyuan Jing, Ruyan Wang

“…In this context, federated learning, as a new distributed machine learning method, becomes one of the key technologies to realize edge intelligence. …”
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In vitro evaluation of tear strength, antifungal effect, and polymicrobial resistance in Glycyrrhiza glabra–incorporated maxillofacial silicone by Harshini Sivakumar, Jeyaraj Brintha Jei, Balasubramaniam Muthukumar

“…Methods: A total of 192 samples were prepared and divided into groups based on Glycyrrhiza glabra concentrations, with further subgroups for each parameter with 48 samples in each concentration group. …”
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Effects of Composite Formulation on Mechanical Properties of Biodegradable Poly(Propylene Fumarate)/Bone Fiber Scaffolds by Xun Zhu, Nathan Liu, Michael J. Yaszemski, Lichun Lu

“…Main effects of each parameter on the measured property were calculated. …”
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Modelling the future of cleaner energy: Explainable artificial intelligence model for green hydrogen production rate estimation by Okorie Ekwe Agwu, Saad Alatefi, Ahmad Alkouh

“…Despite advancements in machine learning-based models, previous studies often lack explainability, diminishing user trust in their deployment. …”
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Using a Multivariate Virtual Experiment for Uncertainty Evaluation with Unknown Variance by Manuel Marschall, Finn Hughes, Gerd Wübbeler, Gertjan Kok, Marcel van Dijk, Clemens Elster

“…Beyond their common usage as a modeling and validation tool, a virtual experiment may also be employed to perform a parameter sensitivity analysis or to carry out a measurement uncertainty evaluation. …”
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A Comprehensive Monte Carlo-Simulated Dataset of WAXD Patterns of Wood Cellulose Microfibrils by Ricardo Baettig, Ben Ingram

“…It enables the development, validation, and benchmarking of novel algorithms and machine learning models for MFA prediction from diffraction patterns. …”
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