Radiofrequency Technologies of Local Positioning in Healthcare by D. S. Bragin, I. V. Pospelova, I. V. Cherepanova, V. N. Serebryakova

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Adaptation of local work organization to modern conditions by D. Yu. Levin

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FEATURES OF LOCAL IMMUNITY IN PATIENTS WITH OROPHARYNGEAL CANCER by O. I. Keith, M. N. Tilliashaihov, P. V. Svetitsky, E. Yu. Zlatnik, G. I. Zakora, A. A. Ganiev, G. P. Nistratov

“…We explored the experience of the Rostov Research Institute of Oncology and the Republican Specialized Scientific and Practical Medical Center of Oncology and Radiology of the Ministry of Health of the Republic of Uzbekistan.Materials and methods. …”
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An effective algorithm for measuring diastolic artery diameters by A.P.G. HOEKS, Xu DI, P.J. BRANDS, R.S. RENEMAN

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Enhanced Gaining-Sharing Knowledge-based algorithm by Mohammed Adnan Jawad, Heba Sayed Mohamed Roshdy, Ali Wagdy Mohamed

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Improved Firefly Algorithm Based on Heuristic Information by CUI Jia-rui, LI Qing, YANG Liu-yi, WANG Heng, ZHANG Bo-yu

“…Firefly Algorithm (FA) is an optimization algorithm based on swarm intelligence which mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies With the aim to address the disadvantages of the firefly algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process, the firefly algorithm is improved herein Two kinds of heuristic information are proposed into the algorithm to guide the convergence of the algorithm The first one takes the current global best as the heuristic information referencing the “global optimal” idea in particle swarm optimization, therefore, an algorithm called FAGO (Firefly Algorithm based on Global Optimization) is formed The second one is called FABE (Firefly Algorithm based on Bayesian Estimation) using the optimal moving direction calculated by Bayesian estimation as heuristic information The improved algorithms in this study are applied to numerical simulations of several classical test functions and compared with traditional FA and some other′s research are carried out The simulation results show that the proposed algorithms can well accelerate the convergence speed and improve the convergence accuracy…”
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COMPARATIVE ANALYSIS OF COLORING ALGORITHMS FOR ORDINARY WEIGHTED GRAPH by Andrey Sergeyevich Merzlenko, Valery Grigoryevich Kobak

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A review of acupoint localization based on deep learning by Jiahao Li, Zhennan Fei, Yingjiang Xie, Da Deng, Xingcheng Ming, Fu Niu

“…We comprehensively review and analyze relevant research in this field in recent years, and examine the principles, classifications, commonly used datasets, evaluation metrics and application fields of acupoint localization algorithms based on deep learning. …”
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Solving the Traveling Salesman Problem Using the IDINFO Algorithm by Yichun Su, Yunbo Ran, Zhao Yan, Yunfei Zhang, Xue Yang

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Modified Meerkat Clan Algorithm for Association Rules Mining by Mohamad Ab. Saleh, Ahmed T. Sadiq Sadiq

“…In addition, the MCC-ARM uses condensation method in the adjacency search process to prevent the algorithm from falling into the local mode. In order to prove their efficiency, it should be applied on four reliable datasets (i.e. …”
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Advancing wildfire prediction in Nepal using machine learning algorithms by Saugat Sapkota, Khagendra Prasad Joshi, Sajesh Kuikel, Dipesh Kuinkel, Biplov Bhandari, Yanhong Wu, Haijian Bing, Suresh Marahatta, Deepak Aryal, S-Y Simon Wang, Binod Pokharel

“…Wildfires are increasingly threatening Nepal, particularly during the dry pre-monsoon months (March-May), leading to severe ecological impacts and disruptions to local communities. To improve wildfire prediction and preparedness, this study evaluated four advanced machine learning algorithms—Random Forest, Radial Basis Function Neural Network, Artificial Neural Network, and Support Vector Machine—using comprehensive dataset (2001–2023) of meteorological, topographical, anthropogenic, locational, and vegetation variables. …”
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Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics by Dawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra, Krunal Vaghela, Ashish Singh, K. S. Ravi Kumar, Durga Prasad Bavirisetti

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Mining Local Specialties for Travelers by Leveraging Structured and Unstructured Data by Kai Jiang, Like Liu, Rong Xiao, Nenghai Yu

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Deep Learning-Based Sound Source Localization: A Review by Kunbo Xu, Zekai Zong, Dongjun Liu, Ran Wang, Liang Yu

“…Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. …”
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Analysis of macroeconomic factors influencing on local passenger traffic volume by S. V. Muktepavel

“…The article gives reasons of choice of local service as an object of this research. The author took information about railway transport from ACS Express-3 and information about macroeconomic factors from Federal State Statistics Service to make an economical and statistical analysis for this article. …”
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Survey of node localization scheme in underwater wireless sensor network by YANG Qiuling, ZHU Rongxin, TANG Zhichao, LI Wenjie, HUANG Xiangdang

“…To address this issue, the research progress of current underwater localization technologies was systematically reviewed. …”
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An Adaptive Chaotic Sine Cosine Algorithm for Constrained and Unconstrained Optimization by Yetao Ji, Jiaze Tu, Hanfeng Zhou, Wenyong Gui, Guoxi Liang, Huiling Chen, Mingjing Wang

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Comparison of methods for resolving the contributions of local emissions to measured concentrations by T. D. Edwards, Y. K. Wong, C.-H. Jeong, J. M. Wang, Y. Su, G. J. Evans

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Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials by Jinqiu Shang

“…The configuration and scheduling of air materials are the basis of maintenance and logistics. This research establishes the model of air material scheduling problem and introduces NSGA-II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. …”
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Memetic Salp Swarm Algorithm for economic load dispatch problems by Mohammed A. Awadallah, Mohammed Azmi Al-Betar, Malik Braik, Raed Abu Zitar, Khaled Assaleh, Mahmud Alkoffash, Qusai Yousef Shambour

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