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  • Open Access

    ARTICLE

    Condition Monitoring of Roller Bearing by K-Star Classifier and K-Nearest Neighborhood Classifier Using Sound Signal.

    Rahul Kumar Sharma*1, V. Sugumaran1, Hemantha Kumar2, Amarnath M3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

    Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone) is less than the cost… More >

  • Open Access

    ARTICLE

    A Multi-Objective Decision-Making Approach for the Optimal Location of Electric Vehicle Charging Facilities

    Weiwei Liu1, Yang Tang2, Fei Yang2, Yi Dou3, Jin Wang4,*

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 813-834, 2019, DOI:10.32604/cmc.2019.06754

    Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More >

  • Open Access

    ARTICLE

    Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple

    Tiejun Wang1, Tao Wu1,*, Amir Homayoon Ashrafzadeh2, Jia He1

    CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 81-96, 2018, DOI:10.32604/cmc.2018.03259

    Abstract Crowdsourcing is widely used in various fields to collect goods and services from large participants. Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate. In this paper, we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’ questionnaires described by linguistic 2-tuple terms. Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’ impact on the evaluation. The crowd grade would be updated at the end of… More >

  • Open Access

    ARTICLE

    A Fuzzy Approach for an IoT-based Automated Employee Performance Appraisal

    Jaideep Kaur1, Kamaljit Kaur2

    CMC-Computers, Materials & Continua, Vol.53, No.1, pp. 23-36, 2017, DOI:10.3970/cmc.2017.053.024

    Abstract The ubiquitous Internet of Things (IoT) through RFIDs, GPS, NFC and other wireless devices is capable of sensing the activities being carried around Industrial environment so as to automate industrial processes. In almost every industry, employee performance appraisal is done manually which may lead to favoritisms. This paper proposes a framework to perform automatic employee performance appraisal based on data sensed from IoT. The framework classifies raw IoT data into three activities (Positive, Negative, Neutral), co-locates employee and activity in order to calculate employee implication and then performs cognitive decision making using fuzzy logic. From the experiments carried out it… More >

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