Regression machine learning-based highly efficient dual band MIMO antenna design for mm-Wave 5G application and gain prediction by Redwan A. Ananta, Md. Ashraful Haque, Geamel Alyami, Md Sharif Ahammed, Md. Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Md Afzalur Rahman, Hussein Shaman, Hanaa A. Abdallah, Abdelhamied A. Ateya

“…Abstract With the exponential growth of wireless communication systems, the need for compact, high-performance antennas operating at millimeter-wave (mm-Wave) frequencies has become increasingly critical. …”
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Analysis of the effect of infection control strategy in preventing and controlling infectious endophthalmitis after cataract surgery by Na Liu, Xiao Yang, Dongyan Guo, Qi Wang, Jianhua Zhang, Xiaoming Wang

“…After in-depth investigation and analysis of the reasons for the increase in the incidence of endophthalmitis for three times, a series of effective prevention and control measures were proposed for the root causes of the problems, including optimizing the key link system, implementing closed-loop management of sensory control measures, designing personalized children’s surgery plan, strengthening perioperative treatment, comprehensively monitoring the operating room clean system, strengthening the cleaning and disinfection treatment between consecutive operations to ensure the safety of the operating environment, etc. …”
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基于Shannon熵的LCD-SVM方法在齿轮故障分类中的研究 by 李鹏宇, 邵忍平, 汪亚运

“…Local feature scale decomposition（Local characteristic scale decomposition,LCD）is a new adaptive time-frequency analysis method,which can adaptively decompose a complex signal into a number of ISC（Intrinsic scale component,ISC）components.SVM（support vector machine,SVM）is a kind of intelligent classification methods of machine learning,Shannon entropy is a nonlinear statistical learning methods.The LCD and SVM are introduced to the fault classification of mechanical transmission system.The Hilbert demodulation algorithm is used to strike the envelope signal of ISC components,through which the Shannon entropy is structured.After an in-depth analysis on the basis,it is combined with SVM in good relationship.The result is input vectors of SVM classifier,the trained SVM is used to determine the fault location,the type or degree of the test sample.Through the experimental analysis and verification,using this combining method,the recognition rate of four operating states which contains the normal state,the root crack of tooth,the wear of tooth surface,the composite fault is up to 97.5%.…”
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Chicane-based beam loading compensation for high average current electron bunch trains by Xiaoyang Zhang, Pengwei Huang, Yingchao Du, Renkai Li, Chuanxiang Tang

“…Simulation results for an electron injector design show a root mean square energy spread of less than 2×10^{−4} and a transverse normalized emittance below 0.5 mm mrad for a 1 A bunch train.…”
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Methane/Air Flame Control in Non-Premixed Bluff Body Burners Using Ring-Type Plasma Actuators by Fatemeh Bagherighajari, Mohammadmahdi Abdollahzadehsangroudi, José C. Páscoa

“…Enhancing the combustion efficiency and flame stability in conventional systems is essential for reducing carbon emissions and advancing sustainable energy solutions. …”
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Failure analysis of solar wheel broken teeth of wind turbine yaw drives by LI Xuwang, HUANG Chengyan, LI Guifang, FAN Huan, WANG Han, WEI Yufeng

“…By studying and analyzing these patterns, the cause of tooth breakage in the output teeth of the sun gear in the yaw drive gearbox of onshore wind turbines can be identified, providing technical support for the subsequent research and design of wind turbine yaw systems.MethodsThrough physical and chemical performance testing of failed output teeth and SEM fracture analysis, the gear structure design and unit operating status were investigated to determine the cause of tooth breakage.ResultsThe results show that the abnormal decomposition of the martensitic structure on the surface layer of the output tooth resulted in a surface hardness below 58 HRC and a shallower hardening layer depth by 10%, which reduced the surface contact strength of the tooth. …”
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Enhancing production planning and control of semi-finished products: a case study combining Business Process Management and Lean Manufacturing by Sofia Bernardino, Liliana Ávila

“…Once the problem was characterized and the root causes identified, the communication between the planning and production departments was improved using process modeling with BPMN (Business Process Modeling and Notation), and a dynamic Kanban system was implemented in the most critical area to align production with demand, based on the principles of Lean Manufacturing. …”
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Fault Detection and Classification of Power Plant Using Neural Networks by Rawaa J. Hussein, Khalaf S. Gaeid, Amin Al-Habaibeh

“… This study focuses on the root causes of power station problems that result in system shutdown. …”
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Event-triggered predictive control of high-speed trains under virtual coupling by Jianliang Xu, Zhen Sui, Xiaohua Wei, Feng Xu

“…To address the control problem of high-speed trains operating under virtual coupling in actual communication environments, an event-triggered multi-trains cooperative tracking predictive control method is proposed considering the limited available resources of the system. …”
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High isolation integrated four-port MIMO Antenna for terahertz communication by Youssef Amraoui, Imane Halkhams, Rachid El Alami, Mohammed Ouazzani Jamil, Hassan Qjidaa

“…Moreover, the range of TARC values at the operating frequencies (0.445 THz and 0.540 THz) verifies the effectiveness of the 4-port MIMO antenna for an advanced THz communication system, achieving a maximum diversity gain of 10 dB. …”
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A Drone-Deployable Remote Current Sensor for Non-Invasive Overhead Transmission Lines Monitoring by Khaled Osmani, Detlef Schulz

“…Laboratory tests demonstrated a maximum average error of 5.22% under extreme conditions (e.g., Total Harmonic Distortions (THD) of 40% in the injected current signals) and a minimum error of 2.54% under standard TL operating conditions. The system supports current measurements up to 5 kA RMS and allows for 6 hours of continuous second-wise data recording on a single battery charge. …”
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Analyzing Impact and Systemwide Effects of the SlowROS Attack in an Industrial Automation Scenario by Ivan Cibrario Bertolotti, Luca Durante, Enrico Cambiaso

“…The ongoing adoption of Robot Operating Systems (ROSs) not only for research-oriented projects but also for industrial applications demands a more thorough assessment of its security than in the past. …”
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Comparison of Forecasting Performance of ARIMA LSTM and HYBRID Models for The Sales Volume Budget of a Manufacturing Enterprise by Ayşe Soy Temür, Şule Yıldız

“…This study aims to create a monthly sales quantity budget by making use of the previous income data of an enterprise operating within the construction sector, which is considered the locomotive of the economy. …”
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Lithium-Ion Battery Health Management and State of Charge (SOC) Estimation Using Adaptive Modelling Techniques by Houda Bouchareb, Khadija Saqli, Nacer Kouider M’sirdi, Mohammed Oudghiri Bentaie

“…An improved online battery model (IOBM) is developed to enhance SOC estimation accuracy. The system utilises forgetting factor recursive least squares (FFRLS) for real-time parameter updates, an adaptive nonlinear sliding mode observer (ANSMO) for SOC estimation, and a long short-term memory (LSTM) network to dynamically adjust capacity based on operating conditions. …”
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Power and data simultaneous transmission using double-clad fibers towards 6G by Letícia Carneiro de Souza, Felipe Batista Faro Pinto, Tomas Powell Villena Andrade, Arismar Cerqueira Sodré Junior

“…Abstract To the best of our knowledge, this work represents the first report in the literature on the implementation of a radio- and power-over-fiber (RPoF) system utilizing double-clad fiber (DCF) aimed at the sixth generation of mobile communications networks (6G) operating in millimeter-waves (mm-waves). …”
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Multiphysics Feature-Based State-of-Energy Estimation for LiFePO4 Batteries Using Bidirectional Long Short-Term Memory and Particle Swarm-Optimized Kalman Filter by Zhengpu Wu, Xu He, Haisen Chen, Lu Lv, Jiuchun Jiang, Lujun Wang

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Anatomical evaluation of the major apical foramen of extracted maxillary and mandibular human teeth in an Iraqi subpopulation: a cross-sectional study by Ubaydah Falah Algailani, Abdulsalam Rashid Khudid, Ranjdar Mahmood Talabani, Hawzhen Masoud Mohammed Saeed, Dya Dlshad, Sazho Nawzad, Sewa Ali

“…Abstract Accurate knowledge of the root canal system is essential for successful endodontic treatment. …”
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Exploring the Impact of Access Cavity Designs on Canal Orifice Localization and Debris Presence: A Scoping Review by Mario Dioguardi, Davide La Notte, Diego Sovereto, Cristian Quarta, Andrea Ballini, Vito Crincoli, Riccardo Aiuto, Mario Alovisi, Angelo Martella, Lorenzo Lo Muzio

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Machine learning based prediction of geotechnical parameters affecting slope stability in open-pit iron ore mines in high precipitation zone by John Gladious, Partha Sarathi Paul, Manas Mukhopadhyay

“…To quantify these impacts, the system calculates the percentage changes in these properties. …”
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Modeling the interrupt transmission process of SR-IOV cryptographic device by Lei SUN, Shuai LI, Songhui GUO

“…The SR-IOV cryptographic device generates a large number of I/O interrupts when performing operations in a virtualized environment,causing the CPU to frequently switch between the Root mode and the Non-Root mode,which brings huge system performance overhead and affects the operational performance of SR-IOV cryptographic device.Aiming at this problem,the I/O interrupt of SR-IOV cryptographic device was analyzed,and a M/M/1 queuing model according to the cryptographic task first-come-first-served rules was constructed.What’s more,the key factors affecting system performance were analyzed,and the validity of the model via simulation and experiment was verified,and finally the system performance was tested.The results show that the model can quantitatively analyze the impact of the interrupt frequency on the interrupt response time and system queue length.…”
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