Quantitative insights into the Winnipeg rental sector: A data-driven analytical approach using geographic and property metrics by Lahiru Wickramasinghe, Aditya Jain

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Classification of Incidental Carcinoma of the Prostate Using Learning Vector Quantization and Support Vector Machines by Torsten Mattfeldt, Danilo Trijic, Hans‐Werner Gottfried, Hans A. Kestler

“…Tumour vascularization (angiogenesis) and epithelial texture were investigated by quantitative stereology. Learning vector quantization (LVQ) and support vector machines (SVM) were used for the purpose of prediction of tumour category from a set of 10 input variables (age, Gleason score, preoperative PSA value, immunohistochemical scores for proliferation and p53‐overexpression, 3 stereological parameters of angiogenesis, 2 stereological parameters of epithelial texture). …”
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Quantitative 3D reconstruction of viral vector distribution in rodent and ovine brain following local delivery by Roberta Poceviciute, Kenneth Mitchell, Angeliki Maria Nikolakopoulou, Suehyun K. Cho, Xiaobo Ma, Phillip Chen, Samantha Figueroa, Ethan J. Sarmiento, Aryan Singh, Oren Hartstein, William G. Loudon, Florent Cros, Alexander S. Kiselyov

“…This pipeline, which combined existing and newly developed machine-learning and other computational tools, effectively removed false positive artifacts abundant in large-scale images of uncleared tissue sections, and subsampling adequately predicted the dispersion of model viral vectors from the point of local drug delivery. …”
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A Method to Detect Concealed Damage in Concrete Tunnels Using a Radar Feature Vector and Bayesian Analysis of Ground-Penetrating Radar Data by Junfang Wang, Heng Chen, Jianfu Lin, Xiangxiong Li

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Comparing and Optimizing Four Machine Learning Approaches to Radar-Based Quantitative Precipitation Estimation by Miaomiao Liu, Juncheng Zuo, Jianguo Tan, Dongwei Liu

“…The key findings are as follows: (1) For models with a single-variable input, the KAN deep learning model outperformed Random Forest, Gradient Boosting Decision Trees, Support Vector Machines, and the traditional Z-R relationship. (2) When six features were used as inputs, the accuracy of the machine learning models improved significantly, with the KAN deep learning model outperforming other machine learning methods. …”
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Bridging research and policy in China's energy sector: A semantic and reinforcement learning framework by Yang Liu

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Quantitative Assessment of Brix in Grafted Melon Cultivars: A Machine Learning and Regression-Based Approach by Uğur Ercan, Ilker Sonmez, Aylin Kabaş, Onder Kabas, Buşra Calık Zyambo, Muharrem Gölükcü, Gigel Paraschiv

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Machine-Learning Classification of Port Wine Stain With Quantitative Features of Optical Coherence Tomography Image by Shengnan Ai, Chengming Wang, Wenxin Zhang, Wenchao Liao, Juicheng Hsieh, Zhenyu Chen, Bin He, Xiao Zhang, Ning Zhang, Ying Gu, Ping Xue

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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

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The Awareness and Adoption of Artificial Intelligence for Effective Facilities Management in the Energy Sector by Jonathan Oluwapelumi Mobayo, Ayooluwa Femi Aribisala, Saheed Olanrewaju Yusuf, Usman Belgore

“…The aim of the study is primarily to assess the awareness of AI in facility management, and to identify the prospects and challenges of the adoption of AI in the energy sector. The study adopted the quantitative methodology approach, using a structured questionnaire to a sample size of 384 respondents. …”
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A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI. by Elizabeth M Sweeney, Joshua T Vogelstein, Jennifer L Cuzzocreo, Peter A Calabresi, Daniel S Reich, Ciprian M Crainiceanu, Russell T Shinohara

“…Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. …”
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THE E-LEARNING IN FRENCH LANGUAGE AND LITERATURE DEPARTMENT OF THE UNIVERSITY OF MASCARA DURING THE COVID-19 CRISIS: QUANTITATIVE STUDY by Aouda MAZOT

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REVOLUTIONIZING LUXURY: THE ROLE OF AI AND MACHINE LEARNING IN ENHANCING MARKETING STRATEGIES WITHIN THE TOURISM AND HOSPITALITY LUXURY SECTORS by Maria Nascimento CUNHA, Manuel PEREIRA, António CARDOSO, Jorge FIGUEIREDO, Isabel OLIVEIRA

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Coronavirus (COVID-19) Impacts on Malaysian Fisheries Sectors: Lesson Learned from the Movement Control Order (MCO) by Ameer Farhan Mohd Arzaman, Hayatul Safrah Salleh, Abdul Mutalib Embong, Kais Amir Kadhim, Norzamziah Afzainizam, Loi Hoang Huy Phuoc Pham, Nurul Ashikin Abdul-Kadir, Nur Yuhanis Mohd Nasir

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Solution to Challenges Faced by Teachers in Distance Learning to Improve the Quality and Accessibility of Education by Battsetseg Semjaan, Tungalagtuya Khuukhenduu, Munkhtuya Lkhagvasuren

“…The study explores the possibility of implementing distance learning in the general education sector in the future, measuring its interrelationships with national and local indicators. …”
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Quantitative Prediction of Protein Content in Corn Kernel Based on Near-Infrared Spectroscopy by Chenlong Fan, Ying Liu, Tao Cui, Mengmeng Qiao, Yang Yu, Weijun Xie, Yuping Huang

“…Near-infrared spectral data from different varieties of maize grain powder were collected, and quantitative analysis of protein content was conducted using Partial Least Squares Regression (PLSR), Support Vector Machine (SVM), and Extreme Learning Machine (ELM) models. …”
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Quantitative Analysis of the Acceptance and Learning Success Instead of Flipped Classroom Teaching in a Caries Diagnosis Course for Undergraduate Students by Mozhgan Bizhang, Stefan Zimmer, Jan P. Ehlers

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The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules by Zuhua Song, Qian Liu, Jie Huang, Dan Zhang, Jiayi Yu, Bi Zhou, Jiang Ma, Ya Zou, Yuwei Chen, Zhuoyue Tang

“…To explore the application value of various machine learning (ML) algorithms based on dual-layer spectral computed tomography (DLCT) quantitative parameters in distinguishing benign from malignant thyroid micro-nodules. …”
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STRATEGIC HUMAN RESOURCE DEVELOPMENT PRACTICES AND EMPLOYEE PERFORMANCE IN ETHIOPIAN PUBLIC SECTOR ORGANIZATIONS by Bonson Alemu Hambissa, Worku Mekonnen Tadesse

“…This study focuses on exploring the effect of Strategic Human Resource Development Practices (SHRDP) on employee performance as mediated by organizational learning in selected public sector organizations of Ethiopia. …”
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Enhancing quantitative capacity for the health sector in post-Ebola Liberia, a tracer study of a locally developed and owned coding and biostatistics program [version 1; peer revie... by Laura A. Skrip, George B. Davis, Mulbah K.A. Kromah, Trokon O. Yeabah, Snoyonoh T. Barcon

“…To address the gap, a local NGO, Quantitative-Data for Decision-Making (Q4D), was founded to enhance capacity and opportunities for analyzing quantitative data among Liberians. …”
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