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  • Open Access

    ARTICLE

    An Experimental Study and Analysis of Different Dielectrics in Electrical Discharge Machining of Al 6063 Alloy

    B. MOULIPRASANTHA, P. HARIHARANB

    Journal of Polymer Materials, Vol.36, No.4, pp. 351-369, 2019, DOI:10.32381/JPM.2019.36.04.5

    Abstract Electrical discharge machining is a non-traditional machining processes in which it is based upon thermal and electrical energy source as an interval energy pulse discharge in-between the work piece and tool electrode so as to remove the material. A systematical investigation of melting and vaporising of aluminium to find the output responses such as Material removal rate (MRR), Electrode wear rate (Ra), and Surface finish (EWR) in EDM using two different dielectrics was conducted as experimental work. The working fluids are Polyethylene glycol (PEG 600) and kerosene. It is the hour of need to get the maximum MRR and surface… More >

  • Open Access

    ARTICLE

    Studies on Compressive Loading-characteristics of PU Foam Materials Used in Footwear for Obese

    S. MATHIVANAN*, R. MOHAN, RAMES C PANDA, P. BALACHANDER1

    Journal of Polymer Materials, Vol.39, No.3-4, pp. 195-204, 2022, DOI:10.32381/JPM.2022.39.3-4.2

    Abstract Optimum-designed footwear with polyurethane (PU) material for comfort is an important requirement for obese. Investigations on compressive behavior of varied designed footwear using 120 D PU material have been carried out. The energy absorption primarily depends on heel height, slope angle and load applied or body mass index of obese. Statistical analysis has been used to formulate the prediction of absorbed energy wherein a heel height of 30 mm with 20-degree angle provides optimum value with the incorporation of 120 D PU material. A coefficientof-determination (R2 ) value of 0.9406 confirms the suitability of the statistical regression model. Hence, the… More >

  • Open Access

    ARTICLE

    Application of Machine Learning For Prediction Dental Material Wear

    ABHIJEET SURYAWANSHI1, NIRANJANA BEHERA2,*

    Journal of Polymer Materials, Vol.40, No.3-4, pp. 305-316, 2023, DOI:10.32381/JPM.2023.40.3-4.11

    Abstract Resin composites are commonly applied as the material for dental restoration. Wear of these materials is a major issue. In this study specimens made of dental composite materials were subjected to an in-vitro test in a pin-on-disc tribometer. Four different dental composite materials applied in the experiment were soaked in a solution of chewing tobacco for certain days before being removed and put through a wear test. Subsequently, four different machine learning (ML) algorithms (AdaBoost, CatBoost, Gradient Boosting, Random Forest) were implemented for developing models for the prediction of wear of dental materials. AdaBoost, CatBoost, Gradient Boosting and Random Forest… More >

  • Open Access

    ARTICLE

    Interface and Friction Properties of Copper-embedded Polyethylene Terephthalate Filament

    FOUED KHOFFI1,*, OMAR HARZALLAH2, JEAN YVES DREAN2

    Journal of Polymer Materials, Vol.40, No.1-2, pp. 59-69, 2023, DOI:10.32381/JPM.2023.40.1-2.5

    Abstract The aim of this study is to analyze the interfacial and the frictional properties of copper (Cu) reinforced polyethylene terephthalate (PET) filament. This Cu-Embedded PET filament will be used as an information transmitter. This filament was prepared by a co-extrusion process. Mechanical properties of these filaments have been quantified by tensile and pull-out analyses. It is shown that the mechanical properties of composite filament were improved by adding the copper filament (from 0.82 to 1.2 GPa). The results of the pull-out test revealed some adhesion between the copper and the PET despite the existence of a slippage of the copper… More >

  • Open Access

    ARTICLE

    Driving Activity Classification Using Deep Residual Networks Based on Smart Glasses Sensors

    Narit Hnoohom1, Sakorn Mekruksavanich2, Anuchit Jitpattanakul3,4,*

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 139-151, 2023, DOI:10.32604/iasc.2023.033940

    Abstract Accidents are still an issue in an intelligent transportation system, despite developments in self-driving technology (ITS). Drivers who engage in risky behavior account for more than half of all road accidents. As a result, reckless driving behaviour can cause congestion and delays. Computer vision and multimodal sensors have been used to study driving behaviour categorization to lessen this problem. Previous research has also collected and analyzed a wide range of data, including electroencephalography (EEG), electrooculography (EOG), and photographs of the driver’s face. On the other hand, driving a car is a complicated action that requires a wide range of body… More >

  • Open Access

    ARTICLE

    Influence of Anteroposterior Symmetrical Aero-Wings on the Aerodynamic Performance of High-Speed Train

    Peiheng He, Jiye Zhang*, Lan Zhang, Jiaqi Wang, Yuzhe Ma

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 937-953, 2024, DOI:10.32604/cmes.2023.043700

    Abstract The running stability of high-speed train is largely constrained by the wheel-rail coupling relationship, and the continuous wear between the wheel and rail surfaces will profoundly affect the dynamic performance of the train. In recent years, under the background of increasing train speed, some scientific researchers have proposed a new idea of using the lift force generated by the aerodynamic wings (aero-wing) installed on the roof to reduce the sprung load of the carriage in order to alleviate the wear and tear of the wheel and rail. Based on the bidirectional running characteristics of high-speed train, this paper proposes a… More >

  • Open Access

    ARTICLE

    Detection of Safety Helmet-Wearing Based on the YOLO_CA Model

    Xiaoqin Wu, Songrong Qian*, Ming Yang

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3349-3366, 2023, DOI:10.32604/cmc.2023.043671

    Abstract Safety helmets can reduce head injuries from object impacts and lower the probability of safety accidents, as well as being of great significance to construction safety. However, for a variety of reasons, construction workers nowadays may not strictly enforce the rules of wearing safety helmets. In order to strengthen the safety of construction site, the traditional practice is to manage it through methods such as regular inspections by safety officers, but the cost is high and the effect is poor. With the popularization and application of construction site video monitoring, manual video monitoring has been realized for management, but the… More >

  • Open Access

    ARTICLE

    Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

    Qixin Lan1, Binqiang Chen1,*, Bin Yao1, Wangpeng He2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2825-2844, 2024, DOI:10.32604/cmes.2023.030378

    Abstract The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the tool will generate significant noise and vibration, negatively impacting the accuracy of the forming and the surface integrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wear state and promptly replace any heavily worn tools to guarantee the quality of the cutting. The conventional tool wear monitoring models, which are based on machine learning, are specifically built for the intended cutting conditions. However, these models require retraining when the cutting conditions undergo any… More >

  • Open Access

    ARTICLE

    Influence of Trailing-Edge Wear on the Vibrational Behavior of Wind Turbine Blades

    Yuanjun Dai1,2,*, Xin Wei1, Baohua Li1, Cong Wang1, Kunju Shi1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.2, pp. 337-348, 2024, DOI:10.32604/fdmp.2023.042434

    Abstract To study the impact of the trailing-edge wear on the vibrational behavior of wind-turbine blades, unworn blades and trailing-edge worn blades have been assessed through relevant modal tests. According to these experiments, the natural frequencies of trailing-edge worn blades −1, −2, and −3 increase the most in the second to fourth order, the fifth order increases in the middle, and the first order increases the least. The damping ratio data indicate that, in general, the first five-order damping ratios of trailing-edge worn blades −1 and trailing-edge worn blades −2 are reduced, and the first five-order damping ratios of trailing-edge worn… More >

  • Open Access

    ARTICLE

    Intelligence COVID-19 Monitoring Framework Based on Deep Learning and Smart Wearable IoT Sensors

    Fadhil Mukhlif1,*, Norafida Ithnin1, Roobaea Alroobaea2, Sultan Algarni3, Wael Y. Alghamdi2, Ibrahim Hashem4

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 583-599, 2023, DOI:10.32604/cmc.2023.038757

    Abstract The World Health Organization (WHO) refers to the 2019 new coronavirus epidemic as COVID-19, and it has caused an unprecedented global crisis for several nations. Nearly every country around the globe is now very concerned about the effects of the COVID-19 outbreaks, which were previously only experienced by Chinese residents. Most of these nations are now under a partial or complete state of lockdown due to the lack of resources needed to combat the COVID-19 epidemic and the concern about overstretched healthcare systems. Every time the pandemic surprises them by providing new values for various parameters, all the connected research… More >

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