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Will the fibers of the future be considered fibers?

National science Review 2024年第10期11卷 15-17页

作者： Dewen Xu Ya Liu Hailiang Wang Wei Yan Changjun Jiang Meifang Zhu State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Department of Computer Science and Technology Tongji University

Fiber materials are key materials that have changed human history and promoted the progress of human civilization. In ancient times, humans used feathers and animal skins for clothing, and later they widely employed natural fibers such as cotton, hemp, silk and wool to make fabrics(Fig. 1a). Chinese ancestors had mastered the art of natural fiber weaving as early as the Neolithic *** thousand years ago, people were already familiar with and adept at techniques for spinning natural fibers [1].

关键词： future will considered fibers

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Early Parkinson's Disease Detection and Classification using Machine Learning and Neutrosophic Sets

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Neutrosophic Sets and systems 2025年 82卷 873-886页

作者： Oudah, Hasan H. Metwaly, Ahmed A. Eassa, Mohamed Abdelhafeez, Ahmed Nagm, Ahmad M. Salama, Ahmed S. College of Arts Department of Journalism Ahl Al Bayt University Karbala Iraq Department of Computer Science Faculty of Computers and Informatics Zagazig University Zagazig44519 Egypt Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Engineering and Electronics Cairo Higher Institute for Engineering Computer Science and Management New Cairo Egypt

Optimizing therapy and rehabilitation for Parkinson's disease (PD) requires early identification and precise evaluation of the illness's course. However, there is disagreement about the best way to use gait analysis to categorize the severity of motor symptoms and identify early-stage Parkinson's disease. The precision of machine learning (ML) models in identifying early and intermediate stages of Parkinson's disease was assessed in this study. Six ML models are used in this study for the prediction of PD. Different metrics are used to evaluate ML models such as accuracy, precision, recall, f1-score, and AUC score. Then we propose a multi-criteria decision-making methodology (MCDM) to evaluate the ML models and select the best one. Two MCDM methods are used such as CRITIC method to compute the criteria weights and the TOPSIS method to rank the alternatives. These methods are used under the bipolar neutrosophic sets (BNSs) to deal with uncertainty information. The results show the support vector machine is the best ML model for the prediction of PD. © 2025, University of New Mexico. All rights reserved.

关键词： Neurodegenerative diseases

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Performance Analysis of ZF and RZF in Low-Resolution ADC/DAC Massive MIMO systems

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China Communications 2024年第8期21卷 115-126页

作者： Talha Younas Shen Jin Muluneh Mekonnen Gao Mingliang Saqib Saleem Sohaib Tahir Mahrukh Liaqat School of Electrical and Electronic Engineering Shandong University of TechnologyZibo 255000China Department of Electrical and Computer Engineering COMSATS University IslamabadSahiwal Campus Department of Electrical and Computer Engineering College of EngineeringDhofar UniversitySalalah 211Oman Department of Electrical and Computer Engineering Addis Ababa Science and Technology UniversityAddis AbabaEthiopia Department of Electrical Engineering College of Electrical and Mechanical EngineeringNUSTIslamabadPakistan

Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power *** power consumption at the receiver radio frequency(RF)circuits can be significantly reduced by the application of analog-to-digital converter(ADC)of low *** this paper we investigate bandwidth efficiency(BE)of massive MIMO with perfect channel state information(CSI)by applying low resolution ADCs with Rician *** start our analysis by deriving the additive quantization noise model,which helps to understand the effects of ADC resolution on BE by keeping the power constraint at the receiver in *** also investigate deeply the effects of using higher bit rates and the number of BS antennas on bandwidth efficiency(BE)of the *** emphasize that good bandwidth efficiency can be achieved by even using low resolution ADC by using regularized zero-forcing(RZF)combining *** also provide a generic analysis of energy efficiency(EE)with different options of bits by calculating the energy efficiencies(EE)using the achievable *** emphasize that satisfactory BE can be achieved by even using low-resolution ADC/DAC in massive MIMO.

关键词： low-bit analog-digital converter massive(multiple-input-multiple-output)MIMO minimum mean square error(MMSE) regularized zero forcing zero forcing

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Optimizing EDM parameters for enhanced mechanical properties of aged AA2024/SiC composite using Taguchi-GRA approach

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Interactions 2024年第1期245卷 1-19页

作者： Bhagat, Madhuri S. Seenivasan, S. Satishkumar, P. Saminathan, Rajasekaran Ishwarya, T. Department of Civil Engineering Yeshwantrao Chavan College of Engineering Maharashtra Nagpur India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jizan Saudi Arabia Faculty of Mathematics Department of Science & ampHumanities Rathinam Technical Campus Tamilnadu Coimbatore India

Enhancing the process parameters is crucial for dealing with aged AA2024 matrix composites as they affect various elements including mechanical properties, TWR, surface finish, and accuracy. AA2024 is selected as matrix in this study to enhance mechanical characteristics. Reinforcing material Silicon Carbide (SiC) was selected because of its exceptional mechanical qualities. So, SiC can enhance AA2024's mechanical properties. Easy fabrication, consistent reinforcement distribution, reduced oxidation and porosity susceptibility led to the stir cast method's selection for AA2024/SiC (0, 3, 6, 9, and 12 wt.%) manufacturing. The AA2024/9 wt.%SiC MMC was aged by heating it to 520 °C for 180 min and then cooling it in the furnace. The AA2024/9 wt.%SiC MMC was aged by heating it to 525 °C for 190 min and then cooling within furnace. The density of both composites was ascertained by means of a density test that was based on Archimedes' principle. The non-aged and aged AA2024 matrix composites were analyzed for their microhardness using a Vickers microhardness tester. Utilizing UTM, the tensile and compressive strengths of the composites were obtained. Their mechanical properties were used to identify the best combination of the manufactured AA2024/SiC MMCs. When comparing other combinations, the one with the best density, compressive and tensile strength, and hardness was found to be AA2024/9 wt.%SiC MMC. The objective of the aging procedure is to enhance the mechanical characteristics without incorporating reinforcements. EDM process parameters for an aged AA2024/9 wt.%SiC composite were optimized using the GRA approach, which is based on Taguchi design statistics. The optimization process utilized chromium concentration, current, and pulse-on time as input variables. SR and TWR were selected as optimization parameters. The sequence of input parameters listed as concentration of chromium, current and pulse on time. © The Author(s), under exclusive licence to Springer Natur

关键词： Microhardness

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A Hybrid WSVM-Levy Approach for Energy-Efficient Manufacturing Using Big Data and IoT

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computers, Materials & Continua 2024年第12期81卷 4895-4914页

作者： Surbhi Bhatia Khan Mohammad Alojail Mahesh Thyluru Ramakrishna Hemant Sharma School of Science Engineering and EnvironmentUniversity of SalfordManchesterM68HDUK University Centre for Research and Development Chandigarh UniversityMohali140307India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering JAIN(Deemed-to-be University)Bangalore560030India Department of Computer Science and Engineering IES College of TechnologyBhopal462044India

In Intelligent Manufacturing,Big Data and industrial information enable enterprises to closely monitor and respond to precise changes in both internal processes and external environmental factors,ensuring more informed decision-making and adaptive system *** also promotes decision making and provides scientific analysis to enhance the efficiency of the operation,cost reduction,maximizing the process of production and so *** methods are employed to enhance productivity,yet achieving sustainable manufacturing remains a complex challenge that requires careful *** study aims to develop a methodology for effective manufacturing sustainability by proposing a novel Hybrid Weighted Support Vector-based Lévy flight(HWS-LF)*** objective of the HWS-LF method is to improve the environmental,economic,and social aspects of manufacturing *** this approach,Support Vector Machines(SVM)are used to classify data points by identifying the optimal hyperplane to separate different classes,thereby supporting predictive maintenance and quality control in *** Forest is applied to boost efficiency,resource allocation,and production optimization.A Weighted Average Ensemble technique is employed to combine predictions from multiple models,assigning different weights to ensure an accurate system for evaluating manufacturing ***,Lévy flight Optimization is incorporated to enhance the performance of the HWS-LF method *** method’s effectiveness is assessed using various evaluation metrics,including accuracy,precision,recall,F1-score,and *** show that the proposed HWS-LF method outperforms other state-of-the-art techniques,demonstrating superior productivity and system performance.

关键词： Sustainable manufacturing support vector machine random forest levy flight optimization weighted average ensemble

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Comparison of Tribological Behavior of Hard Faced Fe-Based Metallic Composite Coatings Sprayed Using HVOF

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Journal of Bio- and Tribo-Corrosion 2025年第1期11卷 1-18页

作者： Soni, Piyush Kumar Prasad, C. Durga Manjunath, H.R. Tiwari, Amit Raju, Vadali Pitchi Athithan, Senthil Deshmukh, Khemraj Kumar, Anjani Department of Mechanical Engineering New Horizon College of Engineering Karnataka Bengaluru India Department of Mechanical Engineering RV Institute of Technology and Management Karnataka Bengaluru India Department of Mechanical Engineering Ramaiah Institute of Technology Karnataka Bengaluru560054 India Department of Mechanical Engineering Suresh Gyan Vihar University Jaipur India Mechanical Engineering Department & amp Principal Indur Institute of Engineering and Technology Siddipet India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Biomedical Engineering Parul University Gujarat Vadodara India Mechanical Engineering Department Government Engineering College Arwal India

Fe-based alloys have recently become well-known for their ability to resist wear and corrosion. Iron, the primary component of alloys, is a cheaper option than alloys made from Co and Ni. There is a need for affordable and easily obtainable coatings based on iron. Coatings in the Fe–Ni–Cr system have demonstrated superior wear resistance compared to other commonly used Fe-based metallic coatings. The Fe-12Ni17Cr2.5Mo2.3Si0.03C based (Metco 41C) metallic coatings were applied onto boiler steel substrates using the High Velocity Oxy-Fuel (HVOF) spraying method. The coatings were examined using X-ray diffraction (XRD), a scanning electron microscope (SEM), and a microhardness tester to determine their density, porosity, microstructure, hardness, and surface roughness. The sliding wear behavior of the substrate and coatings was studied using the pin-on-disk tribometer. Figuring out the wear loss and coefficient of friction. Comparison was made of wear results between the substrate, coatings, and composite coatings. By combining these carbide powders with 30% SiC and WC-12Co particles, the coating’s wear resistance is enhanced in comparison to the Metco 41C coating. In comparison to boiler steel, the Metco 41C + SiC and Metco 41C + WC–Co coatings exhibited a roughly 70% and 40% reduction in volume loss compared with boiler steel respectively. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： HVOF thermal spraying

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Upcycling end of lithium cobalt oxide batteries to electrocatalyst for oxygen reduction reaction in direct methanol fuel cell via sustainable approach

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Journal of Energy Chemistry 2023年第7期82卷 148-157,I0004页

作者： Keyru Serbara Bejigo Kousik Bhunia Jungho Kim Chaehyeon Lee Seoin Back Sang-Jae Kim Nanomaterials&System Lab Major of Mechatronics EngineeringFaculty of Applied Energy SystemJeju National UniversityJeju 63243Republic of Korea Nanomaterials&System Lab Major of Mechanical System EngineeringCollege of EngineeringJeju National UniversityJeju 63243Republic of Korea Research Institute of New Energy Industry(RINEI) Jeju National UniversityJeju 63243Republic of Korea Department of Chemical and Biomolecular Engineering Institute of Emergent MaterialsSogang UniversitySeoul 04107Republic of Korea

Recycling spent lithium-ion batteries(SLIBs)has become essential to preserve the environment and reclaim vital resources for sustainable *** typical SLIBs recycling concentrated on separating valuable components had limitations,including high energy consumption and complicated separation *** work suggests a safe hydrometallurgical process to recover usable metallic cobalt from depleted LiCoO_(2)batteries by utilizing citric acid as leachant and hydrogen peroxide as an oxidizing agent,with ethanol as a selective precipitating *** anode graphite was also recovered and converted to graphene oxide(GO).The above components were directly resynthesized to cobaltintegrated nitrogen-doped graphene(Co@NG).The Co@NG showed a decent activity towards oxygen reduction reaction(ORR)with a half-wave potential of 0.880 V ***,almost similar to Pt/C(0.888 V ***)and with an onset potential of 0.92 V *** metal-nitrogen-carbon(Co-N-C)having the highest nitrogen content has decreased the barrier for ORR since the reaction was enhanced for Co@NG-800,as confirmed by density functional theory(DFT)*** Co@NG cathode catalyst coupled with commercial Pt-Ru/C as anode catalyst exhibits excellent performance for direct methanol fuel cell(DMFC)with a peak power density of 34.7 mW cm^(-2)at a discharge current density of120 m A cm^(-2)and decent stability,indicating the promising utilization of spent battery materials in DMFC ***,lithium was recovered from supernatant as lithium carbonate by coprecipitation *** work avoids sophisticated elemental separation by utilizing SLIBs for other renewable energy applications,lowering the environmental concerns associated with recycling.

关键词： Density functional theory(DFT) Direct methanol fuel cell Leaching Nitrogen doping Oxygen reduction reaction Recycling Spent lithium-ion batteries

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Enhancing tensile properties of pulsed CMT–MIG welded high strength AA2014-T6 alloy joints: Effect of post weld heat treatment

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International Journal of Lightweight Materials and Manufacture 2024年第2期7卷 344-352页

作者： Rajendran, C. Sonar, Tushar Ivanov, Mikhail Sandeep, Ch. Shanthi, C. Gurajala, Naveen Kumar Balachandar, K. Xu, Jinyang Department of Mechanical Engineering Sri Krishna College of Engineering and Technology Tamil Nadu Coimbatore641008 India Chelyabinsk454080 Russia Department of Mechanical Engineering Institute of Aeronautical Engineering Telangana Hyderabad500043 India Department of Physics Sona College of Technology Tamil Nadu Salem636005 India Mechanical Engineering CMR College of Engineering and Technology Telangana Hyderabad501401 India Department of Mechatronics Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

The main objective of this investigation is to study the effect of post weld heat treatments (PWHTs) on tensile properties, hardness, and microstructure of pulsed CMT–MIG (cold metal transfer arc–metal inert gas) welded AA20214-T6 aluminum alloy joints. The welded joints were subjected to PWHT of artificial aging (AA), solution annealing treatment (ST) and ST + aging (STA). The tensile properties and microhardness of joints were evaluated. The microstructure of joints was studied using optical microscope (OM) and transmission electron microscope (TEM). The fractured surface of tensile specimens was analyzed using scanning electron microscope (SEM). Results showed that the tensile properties and hardness of as welded and PWHT joints are inferior compared to base metal (BM). This mainly refers to the microstructural heterogeneity in different regions of joints and softening of heat affected zone (HAZ) induced by the weld thermal cycle. The PWHTs of AA and ST did not show significant effect on tensile strength and hardness of AW joints. However, the slight reduction in elongation was observed in AA and ST joints. The STA joints showed higher joint efficiency of 71.6%, than other joints by compromising on the elongation. This refers to the greater precipitation of hardening precipitates in STA joints compared to AA and ST joints. It exhibited the higher tensile and yield strength of 326 MPa and 266 MPa and the lowest elongation of 3.8%. The STA joints showed 28.35%, 38.28% and 57.77% reduction in tensile strength, yield strength and elongation compared to BM respectively. All the tensile specimens of joints failed in HAZ owing to the lower hardness. This refers to dissolution of precipitates in HAZ. However, the HAZ softening is less severe in STA joints than AW, AA, and ST joints. © 2023 The Authors

关键词： Microstructure

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Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

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Australian Journal of Electrical and Electronics engineering 2024年第3期21卷 213-227页

作者： Shirley, C.P. Pattar, Jagannath Kavitha Rani, P. Saini, Sumit Ranga, Jarabala Elangovan, D. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Madanapalle Institute of Technology & Science Madanapalle India Department of M.Tech Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electrical Engineering School of Engineering & Technology Central University of Haryana Mahendergarh India Detartment of Electrical and Electronics Engineering Ramachandra College of Engineering Eluru India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Electrical and Electronics Engineering Chaitanya Bharathi institute of technology Hyderabad India

By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO). ©, Engineers Australia.

关键词： Energy utilization

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Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

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computers, Materials & Continua 2023年第5期75卷 4593-4609页

作者： Baraa Wasfi Salim Bzar Khidir Hussan Zainab Salih Ageed Subhi R.M.Zeebaree ITM Department Technical College of AdministrationDuhok Polytechnic UniversityDuhokIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Recently,human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare *** though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs,physical human action recognition(HAR)through body sensors gives useful information about the lifestyle and functionality of an *** article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based BehaviorRecognition(ITSOMLBR)technique using body sensor *** presented ITSOML-BR technique collects data from different body sensors namely electrocardiography(ECG),accelerometer,and *** addition,the ITSOML-BR technique extract features like variance,mean,skewness,and standard ***,the presented ITSOML-BR technique executes a micro neural network(MNN)which can be employed for long term healthcare monitoring and ***,the parameters related to the MNN model are optimally selected via the ITSO *** experimental result analysis of the ITSOML-BR technique is tested on the MHEALTH *** comprehensive comparison study reported a higher result for the ITSOMLBR approach over other existing approaches with maximum accuracy of 99.60%.

关键词： Behavior recognition transient search optimization machine learning healthcare sensors wearables

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