Implementation of the C4.5 Algorithm in Predicting the Interest of Prospective Students in Choosing Higher Education by Bambang Triraharjo, Prilian Ayu Minarni, Baskoro

“…In our contribution, we explain how Fuzzy c - means based machine learning can be used for oil data governance. This deep artificial intelligence concept, which we will use in addition to fuzzy logic, by applying Fuzzy c - means for good training can enable the decision-maker a better governance policy.…”
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Application of Intelligent Signal Reflection in the Communication Model of an Electronic Controller by Lan Lan

“…It combines the GAMP algorithm with machine learning, so it can achieve similar performance with much lower computational complexity than the traditional block sparse Bayesian learning algorithm. …”
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Nuove esplorazioni verbovisive. Forme e applicazioni di scrittura visuale negli artefatti contemporanei by Ludovica Polo

“…This essay aims to explore and highlight the contemporary directions of the word-image dualism, developed both through the use of analog tools - as for some forms of asemic writing - and, mostly, through the applications of new technologies - including e-poetry, variable fonts, and machine learning applied to typography.…”
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Use of Active Learning to Design Wind Tunnel Runs for Unsteady Cavity Pressure Measurements by Ankur Srivastava, Andrew J. Meade

“…In this work, the feasibility of an active machine learning technique to design wind tunnel runs using proxy data is tested. …”
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The Use of Big Data to Improve Human Health: How Experience From other Industries Will Shape the Future by Timothy E Hewett, Greg Olsen, Mark Atkinson

“…This commentary discusses what those differences are (Project vs Product Focus, Independent vs Integrated Efforts, Causality vs Prediction Driven, Statistical vs Machine Learning Centricity) why they exist, and the future convergence that we believe is on the horizon. …”
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Paris dans les récits de voyage d’écrivains arabes : repérage, analyse sémantique et cartographie de toponymes by Motasem Alrahabi, Carmen Brando, Muhamed AlKhalil, Joseph Dichy

“…We evaluate rule-based and machine-learning approaches for their efficacy in named entity recognition and semantic analysis. …”
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Cool Neighbors: Combining Artificial Intelligence and Citizen Science to Chart the Sun’s Cosmic Neighborhood by Aaron Meisner, Dan Caselden, Austin Humphreys, Grady Robbins, Eden Schapera, J. Davy Kirkpatrick, Adam Schneider, L. Clifton Johnson, Marc Kuchner, Jacqueline Faherty, Sarah Casewell, Federico Marocco, Adam Burgasser, Daniella Bardalez Gagliuffi

“…Specifically, Cool Neighbors uses machine learning to pre-select the sky images shown to volunteers. …”
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The role of Artificial Intelligence in detecting breast lesions using ultrasound by Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Elżbieta Tokarczyk, Martyna Michalska, Adam Łabuda

“…Driven by advancements in machine learning (ML) and deep learning (DL), AI excels in analyzing complex datasets. …”
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Advancements, Trends and Future Prospects of Lower Limb Prosthesis by Muhammad Asif, Mohsin Islam Tiwana, Umar Shahbaz Khan, Waqar Shahid Qureshi, Javaid Iqbal, Nasir Rashid, Noman Naseer

“…This review presents for lower limb prosthesis; the study of lower limb amputation, design & development, control strategies & machine learning algorithms, the psycho-social impact of prosthetic users, and design trends in patents. …”
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OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer by Qihui Sun, Xiaoqi Zhu, Qi Zou, Yang Chen, Tingting Wen, Tingting Jiang, Xiaojia Li, Fang Wei, Keping Xie, Jia Liu

“…Results Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. …”
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A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD... by Louisa Jorm, Daniel Moses, Dona Adikari, Ramtin Gharleghi, Shisheng Zhang, Arcot Sowmya, Sze-Yuan Ooi, Susann Beier

“…We propose a new risk prediction method predicated on CT coronary angiography (CTCA) data and state-of-the-art machine learning methods based on a better understanding of anatomical risk for CAD. …”
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Determination of the quantitative content of chlorophylls in leaves by reflection spectra using the random forest algorithm by E. A. Urbanovich, D. A. Afonnikov, S. V. Nikolaev

“…The article provides the analysis of the results, as well as recommendations for using this machine learning method to assess the quantitative content of chlorophylls in leaves.…”
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A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays by Farkhanda Aziz, Azhar Ul Haq, Shahzor Ahmad, Yousef Mahmoud, Marium Jalal, Usman Ali

“…An in-depth quantitative evaluation of the proposed approach is presented and compared with previous classification methods for PV array faults – both classical machine learning based and deep learning based. Unlike contemporary work, five different faulty cases (including faults in PS – on which no work has been done before in the machine learning domain) have been considered in our study, along with the incorporation of MPPT. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…This data are processed and interpreted using machine learning algorithms, which find correlations, trends, and patterns that affect outdoor activities. …”
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Statistical analysis based on a two-staged SEM-SVM approach for environmental noise annoyance prediction and identification of influencing factors by M. Rehman, M. Kamal, S. Tiwari

“…This study aimed to develop a machine-learning model for predicting traffic-induced noise annoyance in Riyadh, Saudi Arabia. …”
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A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer by Chenxi Lv, Tianwei Chen, Jiangtao Li, Yuqiang Shan, Hong Zhou

“…Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. …”
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A Mitochondria‐Related Signature in Diffuse Large B‐Cell Lymphoma: Prognosis, Immune and Therapeutic Features by Zhen‐Zhong Zhou, Jia‐Chen Lu, Song‐Bin Guo, Xiao‐Peng Tian, Hai‐Long Li, Hui Zhou, Wei‐Juan Huang

“…Conclusions We established a novel prognostic mitochondria‐related signature by machine learning algorithm, which also demonstrated outstanding predictive value in tumor microenvironment and responses to therapies.…”
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Analisis Sentimen Wacana Pemindahan Ibu Kota Indonesia Menggunakan Algoritma Support Vector Machine (SVM) by Primandani Arsi, Retno Waluyo

“…Dalam penerapan analisis sentimen menggunakan metode machine learning terdapat beberapa metode yang sering digunakan. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…We address the limitations of classical machine learning models in processing the intrinsic linkage relationships of high-dimensional data. …”
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Seleksi Fitur dengan Particle Swarm Optimization pada Klasifikasi Penyakit Parkinson Menggunakan XGBoost by Deni Kurnia, Muhammad Itqan Mazdadi, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi

“…Saat ini diagnosa dapat dilakukan menggunakan machine learning dengan memanfaatkan rekaman suara pasien. …”
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