Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment by Alp Gokhan Hossucu, Suat Ozdemir

“…The results of the experiment proved the superiority of the proposed system over the existing round-robin heuristic-based algorithms and the offloading of policy baselines with an overall increase in precision 28%. …”
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Artificial Intelligence in Gastroenterology: A Comprehensive Review by Raju Vaishya, Mahesh Kumar Goenka, Anupam Sibal, Sujoy Kar, Sangita Reddy

“…Through advanced technologies like Computer-Aided detection (CADe) and Computer-Aided diagnosis (CADx) using deep learning models, AI significantly improves polyp detection rates and reduces miss rates, with reported performances of 95% detection and 50% miss rate reduction. In capsule endoscopy, AI can significantly reduce reading time with improved algorithms to increase sensitivity and specificity in identifying gastrointestinal abnormalities. …”
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Advanced 5G Channel Estimation in mmWave MIMO Systems: Leveraging Compressive Sensing for Enhanced Performance by Zaid Albataineh, Mohammad Al Bataineh, Khaled Farouq Hayajneh, Raed Al Athamneh

“…The proposed approach combines compressive sampling matching pursuit (CoSaMP) and sparsity adaptive matching pursuit (SAMP) algorithms, augmented by a novel iterative reweighting strategy and adaptive thresholding mechanism. …”
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Q-Learning based VM Consolidation Approach for Enhancing Cloud Data Centres Power Efficiency by Baikani Sreenithya, Bharde Hitesh Dutt, Chennamaneni Jashwanth, R Karthikeyan, MA Jabbar, Majjari Sudhakar

“…Furtherly, we will execute the model on using the algorithm chosen to build the model. The inputs we take are VM numbers, power utilization, scalability of VMs, CPU utilization time etc. and finds out what percentage of these values we are getting as an output which highlights the effectiveness of our approach, improvement in energy efficiency and service reduction etc.…”
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A Data-Driven Machine Vision Framework for Quality Management in Photovoltaic Module Manufacturing by In-Bae Lee, Youngjin Kim, Sojung Kim

“…Autonomous decision-making algorithms are devised to recognize incorrect patterns of PV modules in terms of product quality. …”
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Automatic Tuning of Extended Kalman Filter in Sensorless Synchronous Reluctance Motor Drives by Saverio Rigon, Benedikt Haus, Paolo Mercorelli, Mauro Zigliotto

“…A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). …”
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Fault Type Identification and Fault Refinement Diagnosis Model of Variable Refrigerant Flow System by Liu Qian, Li Zhengfei, Ding Xinlei, Chen Huanxin, Wang Yuzhou, Xu Chang

“…The training set after the dimension reduction was used to establish a fault refinement diagnostic model. …”
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Modified method of vacuum therapy in the treatment of infected poststernotomy wounds by A. L. Charyshkin, A. A. Guryanov

“…The modified method of vacuum therapy in combination with effective algorithms for treating purulent-septic complications of post-sternotomy wounds allows physicians to avoid fatal complications and achieve good clinical results.…”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…The qSepsis was derived by three ML algorithms, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). …”
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Retrospective analysis of COVID-19 clinical and laboratory data: Constructing a multivariable model across different comorbidities by Mahdieh Shokrollahi Barough, Mohammad Darzi, Masoud Yunesian, Danesh Amini Panah, Yekta Ghane, Sam Mottahedan, Sohrab Sakinehpour, Tahereh Kowsarirad, Zahra Hosseini-Farjam, Mohammad Reza Amirzargar, Samaneh Dehghani, Fahimeh Shahriyary, Mohammad Mahdi Kabiri, Marzieh Nojomi, Neda Saraygord-Afshari, Seyedeh Ghazal Mostofi, Zeynab Yassin, Nazanin Mojtabavi

“…Clinical and laboratory data, along with comorbidity information, were collected and analyzed using advanced coding, data alignment, and regression analyses. Machine learning algorithms were employed to identify relevant features and calculate predictive probability scores. …”
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Edges are all you need: Potential of medical time series analysis on complete blood count data with graph neural networks. by Daniel Walke, Daniel Steinbach, Sebastian Gibb, Thorsten Kaiser, Gunter Saake, Paul C Ahrens, David Broneske, Robert Heyer

“…<h4>Purpose</h4>Machine learning is a powerful tool to develop algorithms for clinical diagnosis. However, standard machine learning algorithms are not perfectly suited for clinical data since the data are interconnected and may contain time series. …”
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Concise and Accessible Representations for Multidimensional Datasets: Introducing a Framework Based on the nD-EVM and Kohonen Networks by Ricardo Pérez-Aguila, Ricardo Ruiz-Rodríguez

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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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