Optimising test intervals for individuals with type 2 diabetes: A machine learning approach. by Sasja Maria Pedersen, Nicolai Damslund, Trine Kjær, Kim Rose Olsen

“…<h4>Background</h4>Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) developments offer new opportunities for personalised medicine in clinical practice.…”
Get full text

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen by Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

“…Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. …”
Get full text

A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…The results demonstrate that the proposed method improves predictive accuracy over the manufacturer’s power curve, achieving a reduction in error measurements of around 1%. …”
Get full text

Dynamic response of single pile induced by the vibration of tunnel boring machine in hard rock strata by Rui Wang, You Wang, Bin Yan, Bosong Ding

“…Numerical simulation data based on the DEM-FDM coupling method indicates a negative exponential relationship between peak acceleration and frequency of piles, with a linear positive correlation with amplitude. …”
Get full text

Research on Multi-Machine Pre-Synchronization Control and Optimization Based on Parallel Recovery Black Start by Zhongping Ruan, Shuye Ding, Yizhi Chen

Get full text

Application of HS Motion Law in Cam Design of Super High-speed Tobacco Packaging Machine by Ren Ziwen, Ge Zhenghao, Wang Gang

Get full text

Machine Learning and Metaheuristic Algorithms for Voice-Based Authentication: A Mobile Banking Case Study by Leili Nosrati, Amir Massoud Bidgoli, Hamid Haj Seyyed Javadi

“…On the other hand, by employing the frequency and phase properties to compare the target's voice to the discovered password key, this method will prevent speech forgeries. …”
Get full text

Intelligent identification of electromagnetic radiation signals induced by coal rock fractures using machine learning by LI Baolin, FENG Jiaqi, WANG Enyuan, SUN Xinyu, WANG Shuowei

“…Machine learning algorithms, such as linear discriminant analysis, support vector machines, and ensemble learning methods, were utilized to develop intelligent identification models for effective and interference signals. …”
Get full text

Risk assessment of the human factor in ‘staff - hoists - production environment’ system at machine-building enterprises by Elena Vladimirovna Yegelskaya, Anatoly Arkadyevich Korotkiy

“…The research objective is to develop the technique of assessing a human factor risk in the ‘staff - hoists - production environment’ system. The proposed method allows evaluating the degree of staff training and of the appropriate managerial solutions at the machine-building enterprises operating hoists. …”
Get full text

ONBOARD FUEL PUMP FAULT DIAGNOSIS BASED ON IMPROVED SUPPORT VECTOR MACHINE AND EXPERIMENTAL RESEARCH by LIANG Wei, JING Bo, JIAO XiaoXuan, QIANG XiaoQing, LIU XiaoDong

“…Aiming at solving lacking of failure data and inefficiency,high-cost of now available fault diagnosis methods,a experimental platform of fuel transfer system is developed and a fault diagnosis method based on wavelet packet analysis and improved support vector machine（ ISVM） is presented. …”
Get full text

Static Topology Optimization and Dynamic Characteristics Analysis of 6000T Compression-Shear Test Machine Frame by Genshang Wu, Beibei Cui, Yanmin Li, Jinggan Shao, Zhanshu He, Shusen Zhao, Chao Li, Jinlong Yu

“…Then, taking the volume of the frame of the compression-shear testing machine as the constraint condition, the topology optimization of the compression-shear testing machine frame is performed using the variable density method of topology optimization, and the model is reconstructed accordingly. …”
Get full text

Machine learning‐driven design of dual‐band antennas using PGGAN and enhanced feature mapping by Lung‐Fai Tuen, Ching‐Lieh Li, Yu‐Jen Chi, Chien‐Ching Chiu, Po Hsiang Chen

“…This labelling method strengthens the relationship between antenna frequency and wavelength characteristics. …”
Get full text

Classification Analytics for Wind Turbine Blade Faults: Integrated Signal Analysis and Machine Learning Approach by Waqar Ali, Idriss El-Thalji, Knut Erik Teigen Giljarhus, Andreas Delimitis

“…Several studies have used time-domain and frequency-domain features alongside machine learning techniques to predict faults in wind turbine blades, such as erosion and cracks. …”
Get full text

Energy‐Efficient Hardware Implementation of Spiking‐Restricted Boltzmann Machines Using Pseudo‐Synaptic Sampling by Hyunwoo Kim, Suyeon Jang, Uicheol Shin, Masatoshi Ishii, Atsuya Okazaki, Megumi Ito, Akiyo Nomura, Kohji Hosokawa, Sungmin Lee, Matthew BrightSky, Sangbum Kim

“…In this study, a new approach, pseudo‐synaptic sampling (PS2) method, which approximates the conventional synaptic sampling machine (S2M) method through a hardware‐friendly implementation while demonstrating superior efficiency, is introduced. …”
Get full text

Evaluating Label Encoding and Preprocessing Techniques for Breast Cancer Prediction Using Machine Learning Algorithms by Mukesh Kumar, Vivek Bhardwaj

“…The results show that out of all the ML techniques tested, the k-NN method gives the most accurate predictions, which is close to 94.00%.…”
Get full text

Performance and reliability evaluation of an improved machine learning‐based pure‐tone audiometry with automated masking by Nicolas Wallaert, Antoine Perry, Sandra Quarino, Hadrien Jean, Gwenaelle Creff, Benoit Godey, Nihaad Paraouty

“…Furthermore, the test–retest difference was not significant with the automated improved ML method for each audiometric frequency tested. Finally, when examining cross‐clinic reliability measures, significant differences were found for most audiometric frequencies tested. …”
Get full text

RESEARCH ON CHARACTERISTICS OF DAMPING PARAMETERS OF SANDWICH STRUCTURE OF MACHINE TOOL COMPONENTS BASED ON MODAL ANALYSIS by HU Jun, ZHU WenFeng, XU KaiLe, MA ZhuangZhuang

“…The dynamic characteristics are important factors that affect the accuracy of machine tools. Currently,the material combinations are an effective method that is often used. …”
Get full text

A mathematical PAPR estimation of OTFS network using a machine learning SVM algorithm by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…The article presents a Support Vector Machine (SVM) algorithm to lower the peak-to-average power ratio (PAPR) in networks that work in orthogonal time frequency space (OTFS). …”
Get full text

A machine learning approach for mapping susceptibility to land subsidence caused by ground water extraction by Diana Orlandi, Esteban Díaz, Roberto Tomás, Federico A. Galatolo, Mario G.C.A. Cimino, Carolina Pagli, Nicola Perilli

“…In this study, we use the conventional Frequency Ratio (FR) method and ML models to generate LSSI maps of the region of Murcia (Spain) where land subsidence occurred in the past due to groundwater overdraft. …”
Get full text

Planning for gold: identifying opportunities for public transport interventions through machine learning and appraisal automation by David Arquati, Liam McGrath

“…Using an origin-destination matrix for Greater London covering approximately 1200 activity centres, our method applies trajectory clustering to identify potential high-demand corridors with poor public transport quality.Our prototype automatically generates multiple public transport scheme options (local bus, express bus, metro) within these corridors along with approximate operating costs. …”
Get full text