Predicting calorific value through proximate analysis of municipal solid waste using soft computing system by Saptarshi Mondal, Islam M. Rafizul

“…The research focused on proximate analysis parameters obtained from the laboratory and utilized the measured calorific value to develop predictive models. …”
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Determination of sub‐synchronous interactions between AC systems and Grid‐Forming converters in bipolar HVDC connections by Francesco Giacomo Puricelli, Pierre Rault, Carmen Cardozo, Jef Beerten

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A simplified and reproducible ex vivo model of cold and ischemia-reperfusion injury by Lele Zhang, Mingjie Ding, Ying Zhu, Zhiping Yan, Wenzhi Guo

“…We provide a detailed protocol for a straightforward technique that requires 20–30 min for harvesting, 24–48 h for static cold storage (SCS), and 2 h for normothermic machine perfusion (NMP) to induce LT-like stresses in the liver. …”
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Low-dimensional metal chalcogenides for wearable gas sensing by Yanyan Li, Yuxiang Zhang, Haiyun Ma, Yi Wan, Tianshuo Zhao

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FDRL: a data-driven algorithm for forecasting subsidence velocities in Himalayas using conventional and traditional soil features by Sahil Sankhyan, Ajoy Kumar, Praveen Kumar, Aaditya Sharma, K. V. Uday, Varun Dutt

“…Traditional subsidence velocity forecasting models, however, typically rely on either satellite remote sensing data or geotechnical parameters in isolation, which limits their predictive power and applicability. …”
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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

“…In this scenario, condition monitoring of the weld using machine learning algorithms is a remedy to detect the defects instantly. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…Wearable visitor BLE beacons provided cell-level location determined by a prototype tool (VTT), integrating in its architecture different functionalities: raw RSSI data smoothing with Kalman filters, hybrid positioning provision, temporal methods for visitor cell prediction, spatial filtering, and prediction based on popular machine learning classifiers. Visitor movement modeling, based on critical parameters influencing signal measurements, provided scenarios mapped to popular behavioral models. …”
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AMC With a BP-ANN Scheme for 5G Enhanced Mobile Broadband by Li-Sheng Chen, Wei-Ho Chung, Ing-Yi Chen, Sy-Yen Kuo

“…AMC technologies use channel state information to select the optimal modulation or coding scheme as well as transmission parameters to improve the transmission speed, transmission quality, and spectrum efficiency of links. …”
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Chamber shape optimization for ultra-high-pressure water-jet nozzle based on computational fluid dynamics method and a data-driven surrogate model by Wen-Tao Zhao, Zheng-Shou Chen, Yuan-Jie Chen, Jiang-Long Li

“…Then, to reduce CFD computational costs and accelerate calculation speed, a data-driven surrogate model based on IWOA-support vector machine (SVM) was proposed. Herein, the parameter gamma and the penalty coefficient in SVM model, are trained using IWOA. …”
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Forest canopy closure estimation in mountainous southwest China using multi-source remote sensing data by Wenwu Zhou, Wenwu Zhou, Qingtai Shu, Cuifen Xia, Li Xu, Qin Xiang, Lianjin Fu, Zhengdao Yang, Shuwei Wang

“…Forest canopy closure (FCC) is an important biological parameter to evaluate forest resources and biodiversity, and the use of multi-source remote sensing synergy to achieve high-accuracy estimate regional FCC at low cost is a current research hotspot. …”
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ESTIMATION OF DUST DISPERSE COMPOSITION OF FERROUS CASTING SECTION by I.A. IVANOVA, V.Y. MANOKHIN

“…Theoretical and experimental data on chemical, disperse composition of foundry dust are analyzed. Parameters of true density of dust coming out of sandblast machines and the section of castings shakeout from moulds of PLC “Rostvertol” have been determined experimentally. …”
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CONDITIONS FOR ENERGY CAPACITY REDUCING OF TREATMENT AT DIAMOND GRINDING by Feodor NOVIKOV, Cătălin IANCU, Vladimir POLYANSKY, Yury GUTSALENKO

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Modeling and Measurement of Tool Wear During Angular Positioning of a Round Cutting Insert of a Toroidal Milling Tool for Multi-Axis Milling by Michał Gdula, Lucia Knapčíková, Jozef Husár, Radoslav Vandžura

“…In addition, a tool life model was developed, taking into account the cutting blade work angle parameter, the laser marking method for the round cutting insert, and a wear measurement methodology. …”
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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

“…The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.…”
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Design and operation experiences of a multi-wire detector under high beam power environment by FENG Yongchun, CHEN Yucong, KANG Xincai, LI Weilong, TANG Kai, ZHAO Zulong, ZHAO Tiecheng, XU Zhiguo, MAO Ruishi, XIAO Guoqing

“…Then, verification experiments with various beam parameters and detector design of MW were performed in an ion source platform at Institute of Modern Physics (IMP), Chinese Academy of Sciences, and the wire deformation caused by temperature was reproduced and observed at HIMMWW (Heavy Ion Medical Machine at WuWei city, China) complex. …”
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DDoS Attack Detection in SDN-Assisted Federated Learning Environment Based on Contrastive Learning by Minghong Fan, Jinghua Lan, Yiyi Zhou, Mengshuang Pan, Junrong Li, Daqiang Zhang

“…In the SDN-assisted FL environment, the FL network requires the interaction of model parameters among multiple participants. During this process, DDoS attacks may target the SDN control plane, disrupt its normal operation, and thus affect the transmission of model parameters in FL. …”
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Automatic Grading of Emperor Apples Based on Image Processing and by Hadis Havaskhan, Hossein Javadikia, Sajad Sabzi, Yousef Abbaspour-gilandeh, Yousef Abbaspour-gılandeh, Hossein Javadıkıa, Hadis Havaskhan

“…So, a mass-based sorting system was proposed with machine visionsystem and using ANFIS method that could obtain apple mass without contact with the fruit. …”
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Efficiency Analysis and Optimization of Two-Speed-Region Operation of Permanent Magnet Synchronous Motor Taking into Account Iron Loss Based on Linear Non-Equilibrium Thermodynamic... by Ihor Shchur, Yurii Biletskyi, Bohdan Kopchak

“…A universal description of such a PC by a system of dimensionless parameters and characteristics made it possible to analyze the perfection of energy conversion in the object. …”
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MODERN TECHNOLOGIES AND SPECIAL EQUIPMENT FOR POTATO PRODUCTION (Following materials of the Potato Europe 2014 exhibition, part 1) by A. Yu. Izmaylov, N. N. Kolchin, Ya. P. Lobachevskiy, N. G. Kynev

“…More than 200 exponents, generally from the European countries presented all necessary for modern potato production: varieties, various production technologies, special technical machines (cultivators, potato planters, combines, vehicles, lines for postharvest processing of tubers, fragments of complexes for storage and commodity preparation of tubers and production of various potato products), laboratory equipment for determination of parameters of technologies, machines, working conditions, properties of soils, plants, tubers, the wide range of components and replacement parts. …”
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From Binary to Multi-Class: Neural Networks for Structural Damage Classification in Bridge Monitoring Under Static and Dynamic Loading by Andreas Kardoulias, Alexandros Arailopoulos, Panagiotis Seventekidis

“…The advantages of this process can be further enhanced by incorporating more numerical and statistical approaches into traditional methods, such as finite element analysis and Machine Learning. In this study, a truss bridge structure is examined, and neural networks are trained with data derived from finite element analyses under static loads and dynamic excitations. …”
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