Integrating an artificial neural network with genetic, particle swarm optimization algorithms, and fuzzy rule to optimize the surface roughness in dry turning AISI 1045 steel by Abdulmajeed Dabwan, Mohammed K Almatani, Mohammed Alqahtani, Husam Kaid, Khaled N Alqahtani, Mustafa M Nasr, Adham E Ragab

“…This research aims to propose optimization methods including a hybrid artificial neural network (ANN) with genetic algorithms (GA) particle swarm optimization (PSO), and Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict and optimize surface roughness during dry machining of AISI 1045 steel. To achieve this experimentally investigates and statistical analyses on how different cutting parameters affect the performance of machining AISI 1045 steel were performed. …”
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Host-derived protein profiles of human neonatal meconium across gestational ages by Yoshihiko Shitara, Ryo Konno, Masahito Yoshihara, Kohei Kashima, Atsushi Ito, Takeo Mukai, Goh Kimoto, Satsuki Kakiuchi, Masaki Ishikawa, Tomo Kakihara, Takeshi Nagamatsu, Naoto Takahashi, Jun Fujishiro, Eiryo Kawakami, Osamu Ohara, Yusuke Kawashima, Eiichiro Watanabe

“…Furthermore, we developed a machine learning model to predict gestational ages using meconium proteins. …”
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Clinically available predictors of obstructive sleep apnoea requiring treatment in type 2 diabetes patients in primary care by Jonas Agholme, Kim Ahtola, Ebba Toll, Carl-Johan Carlhäll, Pontus Henriksson, Stergios Kechagias, Peter Lundberg, Patrik Nasr, Oleg Sysoev, Magnus Wijkman, Mattias Ekstedt, Martin Ulander, Fredrik Iredahl

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Development of Residual Dense U-Net (RDU-Net)-Based Metal Artefacts Reduction Technique Using Spectral Photon Counting CT by Osama Khan, Briya Tariq, Nadine Francis, Nabil Maalej, Abderaouf Behouch, Amer Kashif, Asim Waris, Aamir Raja

“…We aim to develop an innovative machine learning-based technique called residual dense U-Net (RDU-Net), specifically for spectral photon-counting CT (SPCCT), to mitigate metal artefacts across all energy bins. …”
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Automatic Detection and Classification of Natural Weld Defects Using Alternating Magneto-Optical Imaging and ResNet50 by Yanfeng Li, Pengyu Gao, Yongbiao Luo, Xianghan Luo, Chunmei Xu, Jiecheng Chen, Yanxi Zhang, Genxiang Lin, Wei Xu

“…To further enhance the classification accuracy of natural weld defects, a convolutional neural network (CNN) classification model and a ResNet50 classification model for MO images of natural weld defects are established, and the model parameters are evaluated and optimized. The experimental results show that the overall classification accuracy of the ResNet50 model is 99%. …”
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Flexural properties of 3D printed continuous flax fiber reinforced polyethylene composites by Minggan Wang, Xiaohui Song, Zhengwei Yang, Chunlei Luo, Songda Chi, Hao Jiang

“…The influence of various 3D printing parameters on bending performance and dimensional accuracy of CFF/PE composites was investigated. …”
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Bone Mineral Density in Gravida: Effect of Pregnancies and Breast-Feeding in Women of Differing Ages and Parity by Ehud Lebel, Yuri Mishukov, Liana Babchenko, Arnon Samueloff, Ari Zimran, Deborah Elstein

“…BMD was performed by dual-energy X-ray absorptiometry (DXA) machine at femoral neck (FN) and lumbar spine (LS) by a single technician. …”
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Effective Gait Abnormality Detection in Parkinson’s Patients for Multi-Sensors Surveillance System by Abdulwahab Alazeb, Mouazma Batool, Naif Al Mudawi, Mohammed S. Alshehri, Sultan Almakdi, Nouf Abdullah Almujally, Asaad Algarni

“…A framework using artificial intelligence and machine learning techniques has been proposed to address this. …”
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Leveraging dendritic complexity for neuromorphic computing by Suma G Cardwell, Mark Plagge, Luke Parker, Claire E Plunkett, David Munkvold, Paloma T Gonzalez-Bellido, Scott Koziol, Conrad James, Frances S Chance

“…Beyond-von Neumann computing approaches are necessary to sustain the growth of microelectronics and the increasing appetite for artificial intelligence/machine learning algorithms. Neuromorphic computing is an emerging paradigm that takes inspiration from the brain to provide a path forward to improve the computational efficiency and computational density of next-generation computing architectures. …”
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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…By incorporating a service-level score algorithm based on the TextBlob NLP library, each post is accurately classified and utilized as a feature in a supervised machine-learning classification system. The model’s performance is evaluated using standard metrics, including F-measure, Precision, and Recall. …”
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Visualization of Moisture Distribution in Stacked Tea Leaves on Process Flow Line Using Hyperspectral Imaging by Yuying Zhang, Binhui Liao, Mostafa Gouda, Xuelun Luo, Xinbei Song, Yihang Guo, Yingjie Qi, Hui Zeng, Chuangchuang Zhou, Yujie Wang, Jingfei Zhang, Xiaoli Li

“…Visualizing this moisture distribution is crucial for optimizing processing parameters. In this study, we utilized hyperspectral imaging (HSI) technology combined with machine learning algorithms to evaluate the moisture content and its distribution in the stacked tea leaves in West Lake Longjing and Tencha green tea products during the processing flow line. …”
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Ways of Intensification of Grass Seed Production by Spirin A., Borysiuk D., Tsurkan O., Tverdokhlib I., Veselovska N., Edl M.

“…The article presents theoretical and experimental research results that allowed improving these devices based on rational design and operating parameters. Another way to intensify the production process of leguminous grass seeds is to combine the technological processes of wiping and separation in one machine. …”
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Understanding mushroom farm environment using TinyML-based monitoring devices by Segun Adebayo, Halleluyah Oluwatobi Aworinde, Oluranti Olayinka Olufemi, Christian Okechukwu Osueke, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba

“…A Smart Environmental Monitoring System for Mushroom Farms is presented in this paper that makes use of advanced Tiny Machine Learning (TinyML) and Internet of Things (IoT) technologies for evaluating and controlling key parameters that impact the growth of mushrooms. …”
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Joint and individual associations between multiple vitamins and sperm quality in adult men by Wen Yao, Juan Zhang, Weihong Yan, Di Xie, Ping Tuo, Jie Liu, Xiaoling Zhao, Yiwen Xiong, Yang Li, Tiejun Pan

“…We generally found null results between multiple vitamin levels and the parameters of sperm quality in the BKMR models.DiscussionThese research findings imply that vitamins could have a dose-dependent dual effect on sperm quality. …”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…The prediction and optimization of hydrogen production rates (HPRs) in PEMWE systems is difficult and still challenging because of the complexity of the system as well as the operational parameters. The integration of artificial intelligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. …”
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GPU Acceleration for FHEW/TFHE Bootstrapping by Yu Xiao, Feng-Hao Liu, Yu-Te Ku, Ming-Chien Ho, Chih-Fan Hsu, Ming-Ching Chang, Shih-Hao Hung, Wei-Chao Chen

“…With this, our accelerator can support a broader range of parameters, making it ideal for upcoming privacy-preserving applications. …”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…However, many current studies overlook the relationships between different growth parameters and their varying contributions to yield, leading to overlapping information and lower accuracy in monitoring crop growth. …”
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How do compression and flexion-compression injuries destabilize the spine? A novel in vitro protocol for analyzing three-dimensional biomechanical instability by Ann-Kathrin Greiner-Perth, Hans-Joachim Wilke, Christian Liebsch

“…This study aimed (1) to develop an in vitro protocol to generate standardized spinal compression injuries, (2) to establish a three-dimensional flexibility analysis to identify relevant biomechanical instability parameters, and (3) to examine effects of person-specific factors on vertebral fragility.MethodsMechanical fracture simulation was performed on twelve fresh-frozen human spine specimens (T9-11; 4 f/8 m; 40–60 years) using a material testing machine. …”
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Testing Bench for Reciprocating Hydraulic Cylinders with Energy Recovery: Structure, Simulation, and Calculation by A. R. Zenin, A. T. Rybak, A. N. Beskopylny, A. Yu. Pelipenko, Yu. A. Serdyukova

“…One of the ways of energy saving under testing of hydraulic machines is energy recovery. However, in papers devoted to energy recovery during testing of hydraulic machines, the problems of energy recovery during testing of rotary hydraulic machines were solved, and for reciprocating hydraulic machines, the problem of energy recovery during testing of plunger hydraulic cylinders was solved. …”
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Development of a model for detection and analysis of inclusions in tomographic images of iron castings using decision trees by Dorota Wilk-Kołodziejczyk, Aleksandra Nowotny, Izabela Krzak, Adam Tchórz, Krzysztof Jaśkowiec, Marcin Małysza, Adam Bitka, Mirosław Głowacki, Marzanna Książek, Łukasz Marcjan

“…The available (experimental) data make it possible to unequivocally identify belonging to one of these groups. The use of machine learning methods to recognize the relationships between the physical parameters of particles helps to improve the analysis process. …”
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