Klasifikasi Metode Data Mining untuk Prediksi Kelulusan Tepat Waktu Mahasiswa dengan Algoritma Naïve Bayes, Random Forest, Support Vector Machine (SVM) dan Artificial Neural Nerwor... by Satrio Junaidi, Rani Valicia Anggela, Delsi Kariman

“…So, to deal with this problem, data mining classification is carried out to predict student graduation on time to find patterns for student on-time graduation predictions. …”
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Regenerative Braking Systems in Electric Vehicles: A Comprehensive Review of Design, Control Strategies, and Efficiency Challenges by Emilia M. Szumska

“…Based on a systematic analysis of 89 peer-reviewed articles from Scopus, it highlights a shift from basic PID controllers to advanced predictive algorithms like Model Predictive Control (MPC) and machine learning approaches. …”
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Machine Learning Application for Improving Customer and Postal Logistics Operator Satisfaction in Urban Areas – A Review by Adisa MEDIĆ, Amel KOSOVAC, Ermin MUHAREMOVIĆ, Muhamed BEGOVIĆ

“…Machine learning (ML) is a crucial component of artificial intelligence that has recently attracted attention for its application in logistics. ML algorithms are used on large datasets. They create logic correlations among given data and provide predictions of specific values. …”
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Role of Machine Learning in Liquid Biopsy of Brain Tumours by Zanib Javed, Saqib Kamran Bakhshi, Saad Akhtar Khan, Muhammad Shahzad Shamim

“…Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. …”
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Realtime Precise Orbit Determination Technology for LEO Mega-Constellation by Zhen LI, Chuang SHI

“…Supported by GNSS, it analyzed the advantages and disadvantages of solving LEO satellite orbit on the ground or onboard the satellites.The high-fidelity non-conservative force models were applied to the real-time orbit determination algorithm.To separate the kinematic and dynamic orbit determination process had been a great advantage for LEO satellites with much frequent orbital maneuvers.The test results showed that the accuracy of accelerations computed from the radiation pressure and atmospheric drag non-conservation force models were around 5 nm/s².Use the broadcast ephemeris, the real-time orbit determination algorithm could get an accuracy of 0.8 m in the satellites′ positions and 1.1 mm/s accuracy in the satellites′ velocity.When the real-time precise ephemeris of GNSS satellites were provided, the algorithm could get an accuracy of 8 cm in the LEO satellites′ position and 0.1 mm/s in the velocity.The method for real-time orbit determination and orbit prediction in this paper could be used to support the construction of navigation system with the mega-constellations.…”
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Evaluating the spatiotemporal patterns of GPP and tree growth for their response to CO2 fertilization effects in mid-latitude forests of China by Bin Wang, Xiangqi Kong, Shaojie Bian, Ying Quan, Zechuan Wu, Jianyang Liu, Mingze Li

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Peer-to-peer energy trading with energy trading consistency in interconnected multi-energy microgrids: A multi-agent deep reinforcement learning approach by Yang Cui, Yang Xu, Yijian Wang, Yuting Zhao, Han Zhu, Dingran Cheng

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Real-time traffic enhancement scheduling for train communication networks based on TSN by Deqiang He, Zeqian Chen, Daliang Sun, Zhenzhen Jin, Yanjun Chen, Rui Ma, Chen Liang

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Magnetic resonance imaging of cruciate ligament disorders: current updates by Tanda Yang, Yexin Li, Longtao Yang, Qian Liu

“…AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.…”
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Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

“…We synthesise these modalities by combining predictions from convolutional and graph neural networks with a multilayer perceptron. …”
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Innovative approaches to optimizing the road safety monitoring system by Shevtsova A.G., Bychkova C.A., Podkopaev A.V., Nechaev O.Y.

“…The article presents a statistical analysis of innovative approaches to optimizing the system for monitoring the level of accidents and social risk, which is aimed at improving the predictive capabilities of the existing system for monitoring road safety indicators on the State Traffic Safety Inspectorate website. …”
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A peer-support lifestyle intervention for preventing type 2 diabetes in India: A cluster-randomized controlled trial of the Kerala Diabetes Prevention Program. by Kavumpurathu R Thankappan, Thirunavukkarasu Sathish, Robyn J Tapp, Jonathan E Shaw, Mojtaba Lotfaliany, Rory Wolfe, Pilvikki Absetz, Elezebeth Mathews, Zahra Aziz, Emily D Williams, Edwin B Fisher, Paul Z Zimmet, Ajay Mahal, Sajitha Balachandran, Fabrizio D'Esposito, Priyanka Sajeev, Emma Thomas, Brian Oldenburg

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Mathematical model of the formation of the basic statistical sample for evaluating the level of the digital competence of lecturers by Svetlana V. Avilkina, Marina A. Bakuleva, Nadezhda P. Kleynosova

“…Further researches are planned to be conducted in the sphere of automation of process of the statistical data analysis on digitalization of the population of the region, first of all in the sphere of professional education. On the basis of the mathematical model the algorithm of analytical processing of statistical data on monitoring of digital competences is developed.…”
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Two-Layer Intelligent Learning Control Using Output Recurrent Fuzzy Neural Long Short-Term Memory Broad Learning System With RMSprop by Ali Rospawan, Ching-Chih Tsai, Chi-Chih Hung

“…Simulation and experimental results validate that, compared to conventional PID, the proposed method achieves superior tracking accuracy, with the best case showing an 82% reduction in RMSE, and enhanced control efficiency, with an 85% reduction in ITAE. …”
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Quantification of evaporation water losses from nearly 5000 reservoirs in China by Yinuo Zhu, Aizhong Ye, Wei Tian

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A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation by Qinghe Hou, Hanwen Xu, Mingkun Xie, Pingjia Luo, Yuning Cheng

“…The optimized BGI allocation solutions achieved an average increase of 7.45 % in water bodies and 19.92 % in green stormwater infrastructures, alongside a 20.15 % reduction in impervious surfaces. These improvements corresponded to a 19.73 % increase in landscape objective, a 27.55 % improvement in hydrology performance, and a 26.59 % reduction in life-cycle cost (LCC). …”
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Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning by Prashanth Choppara, Bommareddy Lokesh

“…Comparative performance analysis indicated a 30% reduction in task completion times, a 40% reduction in operational latency, and a 25% improvement in fault tolerance relative to traditional scheduling approaches. …”
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Towards a New Taxonomy of Pattern-Making in the Visuo-Spatial Domain in Early Childhood Based on Zygonic Theory and the Sounds of Intent Framework of Musical Development by Adam Ockelford, Sarah McCarthy, Sue Gifford, Helen Thouless, Sharon Kirk, Michael Thorpe

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Artificial Neural Network Model for Monitoring Oil Film Regime in Spur Gear Based on Acoustic Emission Data by Yasir Hassan Ali, Roslan Abd Rahman, Raja Ishak Raja Hamzah

“…Feed-forward and recurrent Elman neural network algorithms were used to develop ANN models, which are subjected to training, testing, and validation process. …”
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Cotton T-Shirt Size Estimation Using Convolutional Neural Network by John King D. Alfonso, Ckyle Joshua G. Casumpang, Jocelyn F. Villaverde

“…The estimation accuracy was 70%. Inaccurate predictions were attributed to the precision of body measurements from computer vision and image quality, which needs to be solved in further studies.…”
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