Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…However, traditional spatial partitioning approaches, which divide cities into predefined police districts based on geographic and operational considerations, often fail to account for variations in crime patterns. In contrast, machine learning-based approaches could dynamically adapt to areas with differing crime frequencies and densities, making them particularly effective in cities characterized by diverse population distributions and crime activity levels. …”
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Chronic stress in practice assistants: An analytic approach comparing four machine learning classifiers with a standard logistic regression model. by Arezoo Bozorgmehr, Anika Thielmann, Birgitta Weltermann

“…<h4>Methods</h4>We applied four machine learning classifiers (random forest, support vector machine, K-nearest neighbors', and artificial neural network) and logistic regression as standard approach to analyze factors contributing to chronic stress in practice assistants. …”
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Implementation Method of GEO and LEO Satellite Tracking Compatible Flat-Plate Antenna by Jian CHEN, Zhengqian ZHANG, Xinsheng MA, Ting CHAO, Gangtao GUO

“…In order to improve the portability, disassembly and usability of the satellite communication antenna products in the fi eld, a GEO and LEO satellite tracking compatible fl at-plate antenna implementation method was proposed, the micro strip array antenna was integrated with the radio frequency channel, and the radio frequency of the antenna was fl at and integrated, combined with the high density multi-layer vertical interconnection technology, the whole machine was small in size, light in weight and low in power consumption, and the tracking control unit could satisfi ed the requirements of GEO Beacon and carrier tracking, also could satisfi ed the LEO analysis and the program guidance tracking.The antenna did not need manual assembly and disassembly, and could be used for satellite communication with onebutton deployment.high-precision tracking and stable communication could be achieved for GEO, MEO and LEO satellite.…”
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Penerapan SMOTE untuk Mengatasi Imbalance Class dalam Klasifikasi Kepribadian MBTI Menggunakan Naive Bayes Classifier by Mutiara Persada Pulungan, Andi Purnomo, Aliyah Kurniasih

“…Additionally, the Term Frequency-Inverse Document Frequency (TF-IDF) method is used to extract important features from text. …”
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BEARING FAULT DIAGNOSIS METHOD BASED ON WINGER DISTRIBUTION AND SINGULAR VALUE DECOMPOSITION by QIN HongMao, SUN JiaBing, SUN Ning

“…Firstly,winger distribution is applied to analyze the original vibration signal,then,analysis to winger spectral matrix based on singular value decomposition is conducted,and characteristic sequences which reflect the mechanical fault state is achieved,finally,taking the singular value of winger spectral as eigenvector to do the fault diagnosis with Support Vector Machine（ SVM）. The experimental results show that this method can effectively extract fault features.…”
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Supervised Sentiment Analysis of Indirect Qualitative Student Feedback for Unbiased Opinion Mining by Smitha Bidadi Anjan Prasad, Raja Praveen Kumar Nakka

“…To address the problem of the manual annotation of large volumes of data, this paper proposes a machine learning method that uses the sentiment 140 dataset as the training set to automate the process of annotations of tweets. …”
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Vibration, current, torque, RPM dataset for multiple fault conditions in industrial-scale electric motors under randomized speed and load variationsMendeley DataMendeley DataMendel... by Wonho Jung, Junho Kim, Kangmin Jang, Sung-Hyun Yun, Daeguen Lim, Minje Jin, Yong-Hwa Park

“…The dataset was collected to support the development and validation of data-driven fault detection methods across diverse mechanical and electrical systems. …”
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Multiple-Fault Diagnosis Method Based on Multiscale Feature Extraction and MSVM_PPA by Min Zhang, Zhenyu Cai, Wenming Cheng

“…In this paper, a novel method called multiscale feature extraction (MFE) and multiclass support vector machine (MSVM) with particle parameter adaptive (PPA) is proposed. …”
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Inverse-design topology optimization of magnonic devices using level-set method by Andrey A. Voronov, Marcos Cuervo Santos, Florian Bruckner, Dieter Suess, Andrii V. Chumak, Claas Abert

“…Abstract The inverse design approach in magnonics exploits the wave nature of magnons and machine learning to develop logical devices with functionalities that exceed the capabilities of analytical methods. …”
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A Micro-Topography Enhancement Method for DEMs: Advancing Geological Hazard Identification by Qiulin He, Xiujun Dong, Haoliang Li, Bo Deng, Jingsong Sima

“…Geological hazards in densely vegetated mountainous regions are challenging to detect due to terrain concealment and the limitations of traditional visualization methods. This study introduces the LiDAR image highlighting algorithm (LIHA), a novel approach for enhancing micro-topographical features in digital elevation models (DEMs) derived from airborne LiDAR data. …”
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Feasibility Assessment of Novel Multi-Mode Camshaft Design Through Modal Analysis by Merve Üngör, Osman Taha Sen, Akif Yavuz, Cemal Baykara

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The determination of optimal cells disintegration method of Candida albicans and Candida tropicalis fungals by M. V. Rybalkyn

“…Many researchers to highlight cytoplasm antigens and all the other layers of the cell use the following methods: grinding cells with quartz sand, destroying them in different machine disintegrating, freezing and thawing a multi others. …”
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Prediction of traditional Chinese medicine for diabetes based on the multi-source ensemble method by Bin Yang, Qingyun Chi, Xiang Li, Jinglong Wang

“…IntroductionTraditional Chinese medicine (TCM) prescriptions are generally formulated by experienced TCM researchers based on their expertise and data statistical methods.MethodsIn order to predict TCM formulas for diabetes more accurately, this paper proposes a novel multi-source ensemble prediction method that combines machine learning ensemble techniques and multi-source data. …”
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Experimental Study on a New Reinforcement Method for Multilayer Industrial Building’s Vibration by Kaizhong Xie, Hongwei Wang, Jianxi Zhou, Xiao Luo, Miao Yue

“…The results show that the new reinforcement method has a good reinforcement effect. Strength and stiffness of multilayer industrial building were obviously improved, and natural frequency of industrial building in the length direction increased from 2.45 Hz to 5.87 Hz, natural frequency of industrial building in the width direction increased from 2.94 Hz to 7.83 Hz, frequencies of machines and frequencies of multilayer industrial building were not in resonance range, acceleration and velocity vibration characteristics of multilayer industrial building were improved, which can provide reference for the reinforcement of multilayer industrial building with a similar structural configuration.…”
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Mathematical and Machine Learning Innovations for Power Systems: Predicting Transformer Oil Temperature with Beluga Whale Optimization-Based Hybrid Neural Networks by Jingrui Liu, Zhiwen Hou, Bowei Liu, Xinhui Zhou

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From prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers by Heather Shaw, Pinkie Chambers, Matthew Watson, Luke Steventon, James Harmsworth King, Angelo Ercia, Noura Al Moubayed

“…Objectives Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. …”
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Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study by Audêncio Victor, Francielly Almeida, Sancho Pedro Xavier, Patrícia H.C. Rondó

“…Methods We analyzed data from 1,579 pregnant women enrolled in the Araraquara Cohort, a population-based longitudinal study. …”
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Stability analysis method of high-speed milling considering feed rate influence by HAN Chentong, GUO Miaoxian, JIANG Xiaohui, WEI Shouheng, LUO Shijin

“…The results show that the proposed method can determine milling stability more accurately for high-speed machining with small radial cutting depth. …”
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The Comprehensive Effect of Depression, Anxiety, and Headache on Pain Intensity and Painkiller Use in Patients with Headache Analyzed by Unsupervised Clustering Using Machine Learn... by Jong-Ho Kim, Minha Ahn, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

“…<b>Background/Objectives</b>: Patients with headache experience depression, anxiety, and reduced quality of life, which are individually associated with pain intensity and painkiller use, but their comprehensive combined effect remains unclear. <b>Methods</b>: Comprehensive patient groups were formed based on unsupervised clustering using machine learning algorithms, and their associations were analyzed via ordinary least square regression. …”
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Machine learning based compact MIMO antenna array for 38 GHz millimeter wave application with robust isolation and high efficiency performance by Md. Ashraful Haque, Md. Sharif Ahammed, Soeung Socheatra, Redwan A. Ananta, Md. Jamal Hossain Nirob, Narinderjit Singh Sawaran Singh, Noorlindawaty Md. Jizat, Saeed Alsowail, Samir Salem Al-Bawri

“…Besides being compact (measuring 37 mm × 24 mm), it boasts an impressive maximum gain of 8.09 dB and an efficiency level of 98.2 %. The methods explored in this research are the RLC equivalent circuit model and simulations with validated measurements. …”
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