INFORMATIONAL AND ALGORITHMIC SUPPORT FOR DISTRIBUTION AND MARkETING LOGISTICS CONTROL SySTEMS OF PHARMACEUTICAL ENTERPRISES by A. V. Kostrov, V. F. Kornyushko, S. Kaybullaeva, O. M. Nikolaeva

“…Informational models and control algorithms models for separate functional modules of the pharmaceutical enterprises distribution and supply logistics management are considered in the article. …”
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A Multi-Feature Fusion Algorithm for Fatigue Driving Detection Considering Individual Driver Differences by Meng Zhou, Xiaoyi Zhou, Zhijian Li, Xinyue Liu, Chengming Chen

“…This article presents a novel detection algorithm that utilizes facial multi-feature fusion, thoroughly considering the driver’s individual characteristics. …”
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An Algorithm of Factor Graph Optimization for 3D Map of Unmanned Exploration Vehicle in Tunnel Environment by Jian Xie, Rao Li, Jing Li, Aoshu Xu

“…Therefore, traditional LiDAR SLAM algorithms are difficult to apply in tunnels. To address this issue, this paper proposes a factor graph-optimized SLAM algorithm based on the fusion of iterative closest point (ICP) and normal distributions transform (NDT) algorithms. …”
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A Systematic Review of Machine Learning Algorithms for Soil Pollutant Detection Using Satellite Imagery by Amir TavallaieNejad, Maria Cristina Vila, Gustavo Paneiro, João Santos Baptista

“…Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search across three major databases yielded 47 articles from an initial pool of 1018 publications spanning the last eight years. …”
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BHT-QAOA: The Generalization of Quantum Approximate Optimization Algorithm to Solve Arbitrary Boolean Problems as Hamiltonians by Ali Al-Bayaty, Marek Perkowski

“…A new methodology is introduced to solve classical Boolean problems as Hamiltonians, using the quantum approximate optimization algorithm (QAOA). This methodology is termed the “Boolean-Hamiltonians Transform for QAOA” (BHT-QAOA). …”
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Radio environment map construction by adaptive ordinary Kriging algorithm based on affinity propagation clustering by Haiyang Xia, Song Zha, Jijun Huang, Jibin Liu

“…However, due to the constraint of limited resources when it comes to sensor networks, it is crucial to select a suitable scale of sensor measurements for radio environment map construction. This article proposes an adaptive ordinary Kriging algorithm based on affinity propagation clustering as a novel spatial interpolation method for the construction of the radio environment map, which can provide precise awareness of signal strength at locations where no measurements are available. …”
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Influence-Based Community Partition with DegreeRank Label Propagation (DRLP) Algorithm for Social Networks by Mingwu Li, Ailian Wang, Xuyang Gao, Bolin Li

“…Community detection is increasingly important in social networks with the rapid growth of big data, which provides a deep understanding of the mesoscopic structure of social networks. In this article, we propose a label improvement algorithm, DegreeRank Label Propagation (DRLP), which is based on the degree centrality of nodes and adopts a PageRank optimization strategy. …”
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Features of the Application of the Detection Algorithm Based on the Background Subtraction Method in the Scanning Optoelectronic Surveillance System by E. I. Mikhnionok, A. V. Khizniak

“…The article considers the approach developed by the authors to adapt the detection algorithm based on the background subtraction method to work in a scanning optoelectronic surveillance system. …”
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A Novel Azimuth Channel Errors Estimation Algorithm Based on Characteristic Clusters Statistical Treatment by Wensen Yang, Ran Tao, Hao Huan, Jing Feng, Longyong Chen, Yihao Xu, Junhua Yang

“…To address this issue, this article derives the formula expression in the two-dimensional time domain after single-channel processing under the assumption of an insufficient azimuth sampling rate and proposes a novel algorithm based on the statistical treatment of characteristic clusters. …”
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Improved classification algorithm for hyperspectral remote sensing images based on the hybrid spectral network model by Lv Deguo

“…In order to make better use of the spatial information and spectral information to improve the classification accuracy of hyperspectral remote sensing images, this article proposes an improved classification algorithm, a-HybridSN, based on the HybridSN (hybrid spectral network) model. …”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…Accurate and efficient predictive disease modeling is crucial in biomedical IoT for early detection and intervention, yet existing models like LSTM and XGBoost face limitations in handling the complexity and temporal nature of health data streams. The research article addresses this gap by introducing the Temporal Adaptive Neural Evolutionary Algorithm (TANEA), a novel approach designed to enhance the predictive capabilities in biomedical IoT systems. …”
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Multiple Experts-Based Decision Algorithm for the Analysis of Consumer Preferences in the Transformation of Creative Product Value by Jing Wang

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Investigation of urban land development and utilization using an intelligent AHP algorithm and decision support system by Yanlin Cui

“…In the optimization of urban land usage plans, this article investigates a decision-making framework based on the Analytical Hierarchy Process (AHP) combined with an intuitionistic fuzzy set (IFS) for a multi-criteria decision-making (MCDM) algorithm. …”
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Utilization of Stockwell Transform and Random Forest Algorithm for Efficient Detection and Classification of Power Quality Disturbances by T. Ravi, K. Sathish Kumar, C. Dhanamjayulu, Baseem Khan

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Optimization of the Hybrid Movie Recommendation System Based on Weighted Classification and User Collaborative Filtering Algorithm by Zhenning Yuan, Jong Han Lee, Sai Zhang

“…Experiments based on the Douban movie dataset verify that the recommendation algorithm proposed in this article solves the shortcomings of a single algorithm model to a certain extent and improves the recommendation effect.…”
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SENTIMENT ANALYSIS WITH LONG-SHORT TERM MEMORY (LSTM) AND GATED RECURRENT UNIT (GRU) ALGORITHMS by Muhammad Nazhif Abda Putera Khano, Dewi Retno Sari Saputro, Sutanto Sutanto, Antoni Wibowo

“…RNN itself has a weakness in Long-Term Memory (LTM). Therefore, this article examines the combination of Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms. …”
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Testing and Simulating a Simplified Precision Autonomous Landing Algorithm for Unmanned Aerial Vehicles (UAV) by Wacław WOSZCZYK (waclaw.woszczyk@student.wat.edu.pl), Kasjan PAWELEC (kasjan.pawelec@student.wat.edu.pl), Norbert SUPEŁO (norbert.supelo@student.wat.edu.pl), Tomasz PACANA (tomasz.pacana@student.wat.edu.pl), Maciej PAJUNK (maciej.pajunk@student.wat.edu.pl), Natalia DANIEL (natalia.daniel@wat.edu.pl)

“…However, their landing pad detection systems did not consistently perform as intended to environmental conditions, such as inclement weather or inadequate illumination. This article presents a simplified precision landing algorithm for unmanned aerial vehicles (UAV) with the objective of enhancing accuracy of the landing procedure. …”
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Position Accuracy Improvement of the Inertial Navigation System using LSTM Algorithm without GNSS Signals by Mohammad Sabzevari, MasoudReza Aghabozorgi Sahaf

“…According to the results of the experiments, the proposed algorithm has improved the position estimation by 60% on average during 30, 60, and 120 seconds without GNSS signals, compared to the inertial navigation system based on Extended Kalman filter.  …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. This article proposes a hybrid digital watermarking algorithm for medical images based on frequency domain transformation and deep learning convolutional neural networks. …”
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Spatiotemporal variable and parameter selection using sparse hybrid genetic algorithm for traffic flow forecasting by Xiaobo Chen, Zhongjie Wei, Xiang Liu, Yingfeng Cai, Zuoyong Li, Feng Zhao

“…Meanwhile, spatiotemporal variable selection and traffic flow prediction should be solved in a unified framework such that they can benefit from each other. In this article, we propose a novel sparse hybrid genetic algorithm by introducing sparsity constraint and real encoding scheme into genetic algorithm in order to optimize short-term traffic flow prediction model based on least squares support vector regression. …”
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