Collaborative Filtering Techniques for Predicting Web Service QoS Values in Static and Dynamic Environments: A Systematic and Thorough Analysis by Ghizlane Khababa, Sadik Bessou, Fateh Seghir, Nor Hazlyna Harun, Abdulaziz S. Almazyad, Pradeep Jangir, Ali Wagdy Mohamed

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DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…DynBlock leverages Tofoli gates and XOR operations to reduce the number of computation operations required to achieve optimal throughput and energy efficiency. …”
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Congestion Control Prediction Model for 5G Environment Based on Supervised and Unsupervised Machine Learning Approach by Mohammed B. Alshawki, Ihab Ahmed Najm, Alaa Khalaf Hamoud

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High-Dimensional Projected Clustering for Learner Competency Analysis in Medical Training Programs by Sandhya Harikumar, C. S. Jayamohan Pillai, V. Vani Chithra, Raghu Raman, Mr Kaimal, Kai-Yu Tang, Prema Nedungadi

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Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning. by Jiayi Wu, Yong-Bei Ma, Charles Congdon, Bevin Brett, Shuobing Chen, Yaofang Xu, Qi Ouyang, Youdong Mao

“…However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. …”
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Improving Portfolio Management Using Clustering and Particle Swarm Optimisation by Vivek Bulani, Marija Bezbradica, Martin Crane

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Data‐sharing strategies in medical consortium based on master‐slave multichain and federated learning by Bohan Kang, Ning Zhang, Jianming Zhu

“…According to the different computing resources and the responsibility of participants, the adaptive Proof of Liveness and Quality consensus and hierarchical federated learning algorithm for master‐slave multichain are proposed. …”
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Progressive Pruning of Light Dehaze Networks for Static Scenes by Byeongseon Park, Heekwon Lee, Yong-Kab Kim, Sungkwan Youm

“…We develop a progressive pruning algorithm that aims to reduce computational complexity while maintaining dehazing quality within a specified threshold. …”
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Fuzzy One-Class Classification Model Using Contamination Neighborhoods by Lev V. Utkin

“…It is shown that an algorithm for computing the classification parameters is reduced to a set of standard support vector machine tasks with weighted data points. …”
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Reinforcement Learning With Selective Exploration for Interference Management in mmWave Networks by Son Dinh-van, van-Linh Nguyen, Berna Bulut Cebecioglu, Antonino Masaracchia, Matthew D. Higgins

“…Numerical results demonstrate that selective exploration improves per-user spectral efficiency by up to 22.5% compared to scenarios without it. Additionally, our algorithms significantly outperform existing methods by 50% in terms of per-user spectral effciency and achieve 90% of the per-user spectral efficiency of the exhaustive search approach while requiring only 0.1% of its computational runtime.…”
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A Stochastic-Variational Model for Soft Mumford-Shah Segmentation by Jianhong (Jackie) Shen

“…In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

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Parameter Estimation of Polynomial-Phase Signals by A. A. Monakov

“…These strategies are very close to optimal. Among them one can single out the HAF-algorithm based on the computation of the High order Ambiguity Function and the CPF algorithm, which uses the computation of the Cubic Phase Function and produces very accurate estimates for signals with the quadratic frequency modulation. …”
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An interpretable machine learning model to predict hospitalizations by Hagar Elbatanouny, Hissam Tawfik, Tarek Khater, Anatoliy Gorbenko

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SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions by De-yu Tang, Yi-jun Mao, Jie Zhao, Jin Yang, Shi-yin Li, Fu-xiang Ren, Junxi Zheng

“…Conclusions Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. …”
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Overview of Agricultural Machinery Automation Technology for Sustainable Agriculture by Li Jiang, Boyan Xu, Naveed Husnain, Qi Wang

“…., RTK-GNSS/LiDAR), intelligent perception systems utilizing multispectral imaging and deep learning algorithms, adaptive control through modular robotic systems and bio-inspired algorithms, and AI-driven data analytics for resource optimization. …”
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Text Detection Method With Emphasis on Text Component Importance and Lightweight Design by Lanlan Yin, Qiming Wu

“…Therefore, this study proposes an image scene text detection method based on a lightweight deep relation inference scene text detection algorithm. This algorithm simplifies the network of detection algorithms that consider the importance of text components, aiming to reduce computational complexity while addressing issues such as excessive smoothing. …”
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Dynamic Adaptation for Independent Task Scheduling Using Dynamic Programming in Multiprocessor Systems by Lotfi BENDIAF, Ahmed HARBOUCHE, Mohammed Amin TAHRAOUI

“…The results demonstrate that DyTAg achieves superior performance, particularly in scenarios involving independent tasks and small task sets, showcasing its potential to enhance dynamic adaptation and optimize performance in heterogeneous computing systems. …”
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Simplified Pedestrian Tracking Filters with Positioning and Foot-Mounted Inertial Sensors by Henar Martin, Juan A. Besada, Ana M. Bernardos, Eduardo Metola, José R. Casar

“…Pedestrian tracking is one of the bases for many ubiquitous context-aware services, but it is still an open issue in indoor environments or when GPS estimations are not optimal. In this paper, we propose two novel different data fusion algorithms to track a pedestrian using current positioning technologies (i.e., GPS, received signal strength localization from Wi-Fi or Bluetooth networks, etc.) and low cost inertial sensors. …”
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MODEL BASED FAULT DETECTION FOR SAFETY MANAGEMENT OF THE INDUSTRIAL PROCESSES by Dumitru POPESCU, Pierre BORNE, Crina TOROUS

“…This approach is recommended of the modern supervision and optimization systems, for the industrial processes.…”
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