Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

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Edge-level multi-constranint graph pattern matching with lung cancer knowledge graph by Houdie Tu, Lei Li, Lei Li, Zhenchao Tao, Zhenchao Tao, Zan Zhang, Zan Zhang

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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…The selected system emerged as the most favorable, offering a robust framework for the development and delivery of educational content. To demonstrate the system's effectiveness, a curriculum was crafted for a specialized field of study - Artificial Intelligence (AI), with a specific focus on the practical application of Machine Learning algorithms. …”
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A Comparison Between the Use of an Infrared Contact Mat and an IMU During Kinematic Analysis of Horizontal Jumps by Bjørn Johansen, Jono Neville, Roland van den Tillaar

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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Existing object detection algorithms are often constrained by the high computational costs associated with large network structures in practical applications. …”
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Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects by G Divya Deepak, Subraya Krishna Bhat

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Deep learning for COVID-19 by X-ray images Analysis and Designing Diagnostic Application by Thamer Khaleel, Ali Kalakech

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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

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Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments by Mangali Sravanthi, Sravan Kumar Gunturi, Mangali Chinna Chinnaiah, Siew-Kei Lam, G. Divya Vani, Mudasar Basha, Narambhatla Janardhan, Dodde Hari Krishna, Sanjay Dubey

“…This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. …”
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Risk assessment of oral leukoplakia by DNA content enhanced by machine learning models by Matheus Henrique Lopes Dominguete, Vera Cavalcanti de Araújo, Fernanda Viviane Mariano, Carmen Silvia Passos Lima, João Figueira Scarini, Paulo de Camargo Moraes, Victor Angelo Martins Montalli, Larissa Agatti, Zuraiza Mohamad Zaini, Luíza Hellmeister, Marcelo Sperandio

“…A 3-step algorithm using these two parameters to classify lesions into low risk and high risk resulted in 52% positive predictive value (PPV) and 93% negative predictive value (NPV). …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. …”
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Control system design for azimuth position of earth station antennas by Auday Al-Mayyahi, Ammar Aldair, Zainab A. Khalaf, William Wang

“…It also introduces a new methodology based on model predictive control (MPC). The manuscript provides the core design for each of these controllers and provides insight into the performance of each controller even in the presence of disturbance. …”
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Using Artificial Intelligence to Enhance Myelodysplastic Syndrome Diagnosis, Prognosis, and Treatment by Fabio Stagno, Giuseppe Mirabile, Patricia Rizzotti, Adele Bottaro, Antonio Pagana, Sebastiano Gangemi, Alessandro Allegra

“…Artificial intelligence (AI) can improve risk assessment and diagnosis, as well as boost the precision of clinical outcome prediction and illness classification. Algorithms based on artificial intelligence may be potentially helpful in discovering new needs for myelodysplastic syndrome-affected patients, choosing treatment and assessing minimal residual disease. …”
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CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…By doing so, it provides more accurate time series modeling, optimizes algorithmic trading strategies, and facilitates investment portfolio risk warnings.ResultsExperiments conducted on four real-world financial datasets demonstrate that CMDMamba achieves a 10.4% improvement in prediction accuracy for multivariate forecasting tasks compared to state-of-the-art models.DiscussionMoreover, CMDMamba excels in both predictive accuracy and computational efficiency, setting a new benchmark in the field of financial time series forecasting.…”
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Analysis of Communication Compression and Transmission in a Multimedia and Internet of Things Environment Integrating Scene Elements by Jia Jia, Guohua Wu

“…Moreover, this paper proposes a reversible information hiding algorithm for encrypted images based on pixel sorting and grouping prediction and discusses how to improve the prediction accuracy through the histogram of prediction errors. …”
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Joint Allocation of Power and Subcarrier for Low Delay and Stable Power Line Communication by Zhixiong Chen, Zhihui Yang, Zeng Dou

“…To meet the requirements of low-latency services such as remote control and demand-side response, a joint optimal allocation algorithm of subcarriers and their power based on diversity grouping and channel prediction is proposed. …”
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Integrating Multi-Variable Driving Factors to Improve Land Use & Land Cover Classification Accuracy using Machine Learning Approaches: A Case Study from Lombok Island by Miftahul Irsyadi Purnama, Hüseyin Oğuz Çoban

“…In field validation assessments, comparing the predictions of these machine learning models with ground truth data, Random Forest was the most reliable, achieving an overall accuracy of 88%. …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…Additionally, SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) were employed to elucidate model predictions, improving transparency and trustworthiness. …”
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History of Location Objectives (Hilal Tracker): Development of Astronomical Observations from 2015-Present by Marataon Ritonga, Alya Fathi Muhammad Hasibuan, Rizqan Arya Perdana Nazara

“…This article explains the history of the development of hilal Tracker technology and methods, including integrating astronomical data, using satellite imagery, algorithms for predicting hilal visibility, and cooperation with various local and international institutions. …”
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Knowledge graph convolutional networks with user preferences for course recommendation by Zhong Hua, Jianbai Yang, Weidong Ji

“…This paper introduces KGCN-UP (Knowledge Graph Convolutional Networks with User Preferences), a novel model for predicting the likelihood of a user interacting with a course based on user preferences and item relationships within a knowledge graph. …”
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