CRITICAL CONTROL POINT IDENTIFICATION THROUGH TROPHOLOGICAL MEAT PRODUCTION CHAINFROM FIELD TO FORK by A. V. Borodin, I. M. Chernukha, M. A. Nikitina

“…The article describes methodological bases for IT-approach to the CCP identification in the trophological meat production chain from field to fork. The algorithmic support and soſtware for the «Decision tree», which allows detecting existing hazards, identifying risks, determining CCPs and describing them, has been developed.…”
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Worst-case energy consumption minimization based on interference analysis and bank mapping in multicore systems by Zhihua Gan, Zhimin Gu, Hai Tan, Mingquan Zhang, Jizan Zhang

“…The bank-to-core mapping provides significant benefits in worst-case energy consumption reduction with 7.23%.…”
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Optimization of connection patterns between mobile phones and base stations using quantum annealing by Taisei Takabayashi, Shoichi Sudo, Toshihiro Aoki, Shun Seo, Masayuki Ohzeki

“…By adopting a variable reduction formulation, we significantly reduce the qubit requirements compared to the naive formulation that is typically used when considering pattern-matching problems. …”
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Perspectives on land use and plant cover in Pucallpa (Perú) between 2000 and 2023 by Indara Venecia Dávila del Valle, Renato Edu Barzola Gomez, Ciza Zarvia Rosario Ramon

“…Finally, a significant land-use transformation was evident, marked by a reduction in vegetation cover and an increase in areas dedicated to crops and pastures. …”
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Dealing with Energy-QoE Trade-Offs in Mobile Video by Fidel Liberal, Ianire Taboada, Jose-Oscar Fajardo

“…Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.…”
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Pathogen-specific epitopes as epidemiological tools for defining the magnitude of Mycobacterium leprae transmission in areas endemic for leprosy. by Marcia V S B Martins, Marjorie M da S Guimarães, John S Spencer, Mariana A V B Hacker, Luciana S Costa, Fernanda M Carvalho, Annemieke Geluk, Jolien J van der Ploeg-van Schip, Maria A A Pontes, Heitor S Gonçalves, Janvier P de Morais, Tereza J P G Bandeira, Maria C V Pessolani, Patrick J Brennan, Geraldo M B Pereira

“…The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a new tool for predicting the magnitude of M. leprae transmission in a given population.…”
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Real-Time Caterpillar Detection and Tracking in Orchard Using YOLO-NAS Plus SORT by Sumesh Nair, Guo-Fong Hong, Chia-Wei Hsu, Chun-Yu Lin, Shean-Jen Chen

“…The integration of YOLO-NAS with SORT enhanced detection performance, achieving a ~9% increase in true positive detections and an ~8% reduction in false positives compared to YOLO-NAS alone. …”
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A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization by Lizhi Cui, Zhihao Ling, Josiah Poon, Simon K. Poon, Junbin Gao, Paul Kwan

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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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Enhancing energy efficiency of industrial boiler application by the integration of ground-source heat pumps and photovoltaic-thermal solar water collectors by Praveen Barmavatu, Baburao Gaddala, Sharun Mendonca, Sonali Anant Deshmukh, Marco Rosales-Vera, Hussein Togun, Ramalinga Viswanathan Mangalaraja, Vineet Singh Sikarwar

“…Optimization was achieved using a hybrid approach that combined Genetic Algorithms (GA) and machine learning (ML) techniques, which iteratively improved system design and operational strategies. …”
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Thorough Understanding and 3D Super-Resolution Imaging for Forward-Looking Missile-Borne SAR via a Maneuvering Trajectory by Tong Gu, Yifan Guo, Chen Zhao, Jian Zhang, Tao Zhang, Guisheng Liao

“…The proposed algorithm first focuses on the track-vertical plane to extract 2D position parameters. …”
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Toward sustainable machining of hardened SKD11: Machine learning-based evaluation and optimization of surface roughness, tool wear, and CO2 emissions by Van-Canh Nguyen, Dung Hoang Tien, Van-Hung Pham, Thinh-Viet Nguyen, Thuy-Duong Nguyen

“…Results indicated that the second-order model demonstrated superior predictive accuracy for Ra (R² = 0.997) and CE (R² = 0.994), whereas the Vb prediction model failed to achieve sufficient reliability. …”
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An Open Data Platform for Traffic Parameters Measurement via Multirotor Unmanned Aerial Vehicles Video by Yuchuan Du, Cong Zhao, Feng Li, Xuefeng Yang

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Constipation in Children: Assisting Paediatricians by I. N. Zakharova, N. G Sugyan, I. D. Maykova, I. V. Berezhnaya, I. М. Kolobashkina

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Efficient Simulation of LWD Azimuthal Propagation Resistivity Tool in Layered TI Formation Based on 3-D Finite Volume Method of Coupled Potentials in the Half Space and Continuatio... by Haosen Wang, Shouwen Yang, Hongnian Wang

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Neutrosophic OWA-TOPSIS Model for Decision-Making in AI Systems with Large Volumes of Data by Juan Roberto Pereira Salcedo, Karla Melissa Ruiz Quezada, Edison Luis Cruz Navarrete, Pedro Manuel García Arias

“…This is problematic when engaging multi-criteria decision making with big datadriven projects like infiltration of personalized suggestions, AI-based medical diagnostics, and risk reduction efforts where any decision making with deficient data can reduce effective capabilities. …”
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Use of electrochemical energy storage systems in autonomous power supply systems to reduce fuel consumption of power installations by A. I. Fedotov, E. A. Fedotov, A. F. Abdullazyanov

“…In the context of predicted changes in power profiles (work / weekend days), optimal control scenarios are calculated individually. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…To leverage the strengths of these individual models, three ensemble methods are explored, that includes supervised ensembling with XGBoost, unsupervised ensembling with the DBSCAN algorithm, and mathematical aggregation using weighted averaging. …”
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The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

“…Ridge regression was used in combination with an algorithm for sequential reduction of attribute space.Results. …”
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Multi-fidelity modelling of a high bypass ratio turbofan engine with variable area nozzle by Andrea Magrini, Ernesto Benini

“…Low-speed mission points are confirmed to be those that benefit the most from an enlarged fan nozzle area, with a possible improvement of 3% in terms of thrust and specific fuel consumption at take-off and approach using a 10% larger area, similarly predicted by both 2D and 3D models. A preliminary acoustic evaluation based on semi-empirical noise models indicates a modest effect on noise emissions, with up to 1 dB reduction in microphone signature at the sideline for a nozzle area increased by 10%.…”
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