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  • Open Access

    ARTICLE

    Autism Spectrum Disorder Prediction by an Explainable Deep Learning Approach

    Anupam Garg1, Anshu Parashar1, Dipto Barman2, Sahil Jain3, Divya Singhal3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1459-1471, 2022, DOI:10.32604/cmc.2022.022170

    Abstract Autism Spectrum Disorder (ASD) is a developmental disorder whose symptoms become noticeable in early years of the age though it can be present in any age group. ASD is a mental disorder which affects the communicational, social and non-verbal behaviors. It cannot be cured completely but can be reduced if detected early. An early diagnosis is hampered by the variation and severity of ASD symptoms as well as having symptoms commonly seen in other mental disorders as well. Nowadays, with the emergence of deep learning approaches in various fields, medical experts can be assisted in early diagnosis of ASD. It… More >

  • Open Access

    ARTICLE

    Identification of Anomalous Behavioral Patterns in Crowd Scenes

    Muhammad Asif Nauman*, Muhammad Shoaib

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 925-939, 2022, DOI:10.32604/cmc.2022.022147

    Abstract Real time crowd anomaly detection and analyses has become an active and challenging area of research in computer vision since the last decade. The emerging need of crowd management and crowd monitoring for public safety has widen the countless paths of deep learning methodologies and architectures. Although, researchers have developed many sophisticated algorithms but still it is a challenging and tedious task to manage and monitor crowd in real time. The proposed research work focuses on detection of local and global anomaly detection of crowd. Fusion of spatial-temporal features assist in differentiation of feature trained using Mask R-CNN with Resnet101… More >

  • Open Access

    ARTICLE

    Optimal Hybrid Precoding Based QoE for Partially Structured Massive MIMO System

    Farung Samklang, Peerapong Uthansakul, Monthippa Uthansakul*, Patikorn Anchuen

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1887-1902, 2022, DOI:10.32604/cmc.2022.022139

    Abstract Precoding is a beamforming technique that supports multi-stream transmission in which the RF chain plays a significant role as a digital precoding at the receiver for wireless communication. The traditional precoding contains only digital signal processing and each antenna connects to each RF chain, which provides high transmission efficiency but high cost and hardware complexity. Hybrid precoding is one of the most popular massive multiple input multiple output (MIMO) techniques that can save costs and avoid using complex hardware. At present, network services are currently in focus with a wide range of traffic volumes. In terms of the Quality of… More >

  • Open Access

    ARTICLE

    Cardiovascular Disease Prediction Among the Malaysian Cohort Participants Using Electrocardiogram

    Mohd Zubir Suboh1,2, Nazrul Anuar Nayan1,3,*, Noraidatulakma Abdullah4,5, Nurul Ain Mhd Yusof4, Mariatul Akma Hamid4, Azwa Shawani Kamalul Arinfin4, Syakila Mohd Abd Daud4, Mohd Arman Kamaruddin4, Rosmina Jaafar1, Rahman Jamal4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1111-1132, 2022, DOI:10.32604/cmc.2022.022123

    Abstract A comprehensive study was conducted to differentiate cardiovascular disease (CVD) subjects from non-CVD subjects using short recording electrocardiogram (ECG) of 244 Malaysian adults in The Malaysian Cohort project. An automated peak detection algorithm to detect nine fiducial points of electrocardiogram (ECG) was developed. Forty-eight features were extracted in both time and frequency domains, including statistical features obtained from heart rate variability and Poincare plot analysis. These include five new features derived from spectrum counts of five different frequency ranges. Feature selection was then made based on p-value and correlation matrix. Selected features were used as input for five classifiers of… More >

  • Open Access

    ARTICLE

    Deep Learning Enabled Predictive Model for P2P Energy Trading in TEM

    Pudi Sekhar1, T. J. Benedict Jose2, Velmurugan Subbiah Parvathy3, E. Laxmi Lydia4, Seifedine Kadry5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1473-1487, 2022, DOI:10.32604/cmc.2022.022110

    Abstract With the incorporation of distributed energy systems in the electric grid, transactive energy market (TEM) has become popular in balancing the demand as well as supply adaptively over the grid. The classical grid can be updated to the smart grid by the integration of Information and Communication Technology (ICT) over the grids. The TEM allows the Peer-to-Peer (P2P) energy trading in the grid that effectually connects the consumer and prosumer to trade energy among them. At the same time, there is a need to predict the load for effectual P2P energy trading and can be accomplished by the use of… More >

  • Open Access

    ARTICLE

    Design of Automatic Batch Calibration and Correction System for IMU

    Lihua Zhu1, Qifan Yun1, Zhiqiang Wu1,*, Cheire Cheng2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1489-1501, 2022, DOI:10.32604/cmc.2022.022091

    Abstract Thanks to its light weight, low power consumption, and low price, the inertial measurement units (IMUs) have been widely used in civil and military applications such as autopilot, robotics, and tactical weapons. The calibration is an essential procedure before the IMU is put in use, which is generally used to estimate the error parameters such as the bias, installation error, scale factor of the IMU. Currently, the manual one-by-one calibration is still the mostly used manner, which is low in efficiency, time-consuming, and easy to introduce mis-operation. Aiming at this issue, this paper designs an automatic batch calibration method for… More >

  • Open Access

    ARTICLE

    Software Defect Prediction Harnessing on Multi 1-Dimensional Convolutional Neural Network Structure

    Zuhaira Muhammad Zain1,*, Sapiah Sakri1, Nurul Halimatul Asmak Ismail2, Reza M. Parizi3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1521-1546, 2022, DOI:10.32604/cmc.2022.022085

    Abstract Developing successful software with no defects is one of the main goals of software projects. In order to provide a software project with the anticipated software quality, the prediction of software defects plays a vital role. Machine learning, and particularly deep learning, have been advocated for predicting software defects, however both suffer from inadequate accuracy, overfitting, and complicated structure. In this paper, we aim to address such issues in predicting software defects. We propose a novel structure of 1-Dimensional Convolutional Neural Network (1D-CNN), a deep learning architecture to extract useful knowledge, identifying and modelling the knowledge in the data sequence,… More >

  • Open Access

    ARTICLE

    Metric-Based Resolvability of Quartz Structure

    Muhammad Imran1,*, Ali Ahmad2, Muhammad Azeem3, Kashif Elahi4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2053-2071, 2022, DOI:10.32604/cmc.2022.022064

    Abstract Silica has three major varieties of crystalline. Quartz is the main and abundant ingredient in the crust of our earth. While other varieties are formed by the heating of quartz. Silica quartz is a rich chemical structure containing enormous properties. Any chemical network or structure can be transformed into a graph, where atoms become vertices and the bonds are converted to edges, between vertices. This makes a complex network easy to visualize to work on it. There are many concepts to work on chemical structures in terms of graph theory but the resolvability parameters of a graph are quite advance… More >

  • Open Access

    ARTICLE

    Binocular Vision Positioning Method for Safety Monitoring of Solitary Elderly

    Lihua Zhu1, Yan Zhang1, Yu Wang1,*, Cheire Cheng2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 593-609, 2022, DOI:10.32604/cmc.2022.022053

    Abstract In nowadays society, the safety of the elderly population is becoming a pressing concern, especially for those who live alone. There might be daily risks such as accidental falling or treatment attack on them. Aiming at these problems, indoor positioning could be a critical way to monitor their states. With the rapidly development of the imaging techniques, wearable and portable cameras are very popular, which could be set on human individual. And in view of the advantages of the visual positioning, the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor. In this paper, the imaging… More >

  • Open Access

    ARTICLE

    Ultra-Wideband Annular Ring Fed Rectangular Dielectric Resonator Antenna for Millimeter Wave 5G Applications

    Abinash Gaya1, Mohd. Haizal Jamaluddin1,*, Ayman A. Althuwayb2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1331-1348, 2022, DOI:10.32604/cmc.2022.022041

    Abstract In this article an ultra-wideband rectangular Dielectric Resonator Antenna is designed for millimeter wave 5G frequency band applications. Indoor 5G communications require antenna system with wide bandwidth and high efficiency to enhance the throughput in the channel. To fulfill such requirements a Dielectric Resonator Antenna (DRA) is designed here which has achieved an ultra-wide bandwidth of 20.15% (22.32–27.56 GHz) which is 5.24 GHz of bandwidth centered at 26 GHz as resonating frequency. This covers the complete band 30 (24.3–27.5 GHz) of 5G spectrum. 26 and 28 GHz are considered as most popular frequencies in millimeter wave 5G communications. The aperture… More >

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