Ting Wang¹, Zhiqiang Wang^1,*, Yin Yang¹, Jianhui Zhou^2,*

Journal of Renewable Materials, Vol.10, No.2, pp. 527-540, 2022, DOI:10.32604/jrm.2022.017955 - 30 August 2021

Abstract The acoustic emission (AE) technique can perform non-destructive monitoring of the internal damage development of bamboo and wood materials. In this experiment, the mechanical properties of different bamboo and wood (bamboo scrimber, bamboo plywood and SPF (Spruce-pine-fir) dimension lumber) during four-point loading tests were compared. The AE activities caused by loadings were investigated through the single parameter analysis and K-means cluster analysis. Results showed that the bending strength of bamboo scrimber was 3.6 times that of bamboo plywood and 2.7 times that of SPF dimension lumber, respectively. Due to the high strength and toughness of… More > Graphic Abstract

Chintakindi Balaram Murthy¹, Mohammad Farukh Hashmi¹, Ghulam Muhammad^2,3,*, Salman A. AlQahtani^2,3

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3015-3031, 2021, DOI:10.32604/cmc.2021.018781 - 24 August 2021

Abstract Real-time pedestrian detection is an important task for unmanned driving systems and video surveillance. The existing pedestrian detection methods often work at low speed and also fail to detect smaller and densely distributed pedestrians by losing some of their detection accuracy in such cases. Therefore, the proposed algorithm YOLOv2 (“YOU ONLY LOOK ONCE Version 2”)-based pedestrian detection (referred to as YOLOv2PD) would be more suitable for detecting smaller and densely distributed pedestrians in real-time complex road scenes. The proposed YOLOv2PD algorithm adopts a Multi-layer Feature Fusion (MLFF) strategy, which helps to improve the model’s feature… More >

Mahmood ul Hassan^1,*, Amin Al-Awady¹, Khalid Mahmood², Shahzad Ali³, Ibrahim Algamdi¹, Muhammad Kashif Saeed⁴, Safdar Zaman⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3413-3427, 2021, DOI:10.32604/cmc.2021.018544 - 24 August 2021

Abstract Wireless Sensor Networks (WSNs) are an integral part of the Internet of Things (IoT) and are widely used in a plethora of applications. Typically, sensor networks operate in harsh environments where human intervention is often restricted, which makes battery replacement for sensor nodes impractical. Node failure due to battery drainage or harsh environmental conditions poses serious challenges to the connectivity of the network. Without a connectivity restoration mechanism, node failures ultimately lead to a network partition, which affects the basic function of the sensor network. Therefore, the research community actively concentrates on addressing and solving… More >

A. Sumathi^1,*, S. Meganathan¹, B. Vijila Ravisankar²

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3109-3126, 2021, DOI:10.32604/cmc.2021.017612 - 24 August 2021

Abstract Gestational Diabetes Mellitus (GDM) is one of the commonly occurring diseases among women during pregnancy. Oral Glucose Tolerance Test (OGTT) is followed universally in the diagnosis of GDM diagnosis at early pregnancy which is costly and ineffective. So, there is a need to design an effective and automated GDM diagnosis and classification model. The recent developments in the field of Deep Learning (DL) are useful in diagnosing different diseases. In this view, the current research article presents a new outlier detection with deep-stacked Autoencoder (OD-DSAE) model for GDM diagnosis and classification. The goal of the… More >

Vikram Rajpoot¹, Vivek Tiwari², Akash Saxena³, Prashant Chaturvedi⁴, Dharmendra Singh Rajput⁵, Mohammed Alkahtani^6,7, Mustufa Haider Abidi^7,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3917-3930, 2021, DOI:10.32604/cmc.2021.015826 - 24 August 2021

Abstract Wireless sensor networks (WSN) are designed to monitor the physical properties of the target area. The received signal strength (RSS) plays a significant role in reducing sensor node power consumption during data transmission. Proper utilization of RSS values with clustering is required to harvest the energy of each network node to prolong the network life span. This paper introduces the RSS-based energy-efficient selective clustering technique using a master node (RESCM) to improve energy utilization using a master node. The master node positioned at the center of the network area and base station (BS) is placed More >

Taher M. Ghazal^1,2, Muhammad Zahid Hussain³, Raed A. Said⁵, Afrozah Nadeem⁶, Mohammad Kamrul Hasan¹, Munir Ahmad⁷, Muhammad Adnan Khan^3,4,*, Muhammad Tahir Naseem³

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 735-742, 2021, DOI:10.32604/iasc.2021.019067 - 11 August 2021

Abstract Clustering is the process of grouping the data based on their similar properties. Meanwhile, it is the categorization of a set of data into similar groups (clusters), and the elements in each cluster share similarities, where the similarity between elements in the same cluster must be smaller enough to the similarity between elements of different clusters. Hence, this similarity can be considered as a distance measure. One of the most popular clustering algorithms is K-means, where distance is measured between every point of the dataset and centroids of clusters to find similar data objects and More >

Lin Zhou^1,*, Kun Feng¹, Tianyi Wang¹, Yue Xu¹, Jingang Shi²

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 527-537, 2021, DOI:10.32604/iasc.2021.018414 - 11 August 2021

Abstract Neutral network (NN) and clustering are the two commonly used methods for speech separation based on supervised learning. Recently, deep clustering methods have shown promising performance. In our study, considering that the spectrum of the sound source has time correlation, and the spatial position of the sound source has short-term stability, we combine the spectral and spatial features for deep clustering. In this work, the logarithmic amplitude spectrum (LPS) and the interaural phase difference (IPD) function of each time frequency (TF) unit for the binaural speech signal are extracted as feature. Then, these features of… More >

Lina Wang^1,2,*, Jie Wang³, Yongjun Ren⁴, Zimeng Xing¹, Tao Li¹, Jinyue Xia⁵

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 31-47, 2021, DOI:10.32604/iasc.2021.018577 - 26 July 2021

Abstract Intrusion detection has been widely used in many application domains; thus, it has caught significant attention in academic fields these years. Assembled with more and more sub-systems, the network is more vulnerable to multiple attacks aiming at the network security. Compared with the other issues such as complex environment and resources-constrained devices, network security has been the biggest challenge for Internet construction. To deal with this problem, a fundamental measure for safeguarding network security is to select an intrusion detection algorithm. As is known, it is less effective to determine the abnormal behavior as an… More >

C. Rajinikanth¹, P. Selvaraj², Mohamed Yacin Sikkandar³, T. Jayasankar⁴, Seifedine Kadry⁵, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2013-2029, 2021, DOI:10.32604/cmc.2021.018719 - 21 July 2021

Abstract Internet of Things (IoT) has become a major technological development which offers smart infrastructure for the cloud-edge services by the interconnection of physical devices and virtual things among mobile applications and embedded devices. The e-healthcare application solely depends on the IoT and cloud computing environment, has provided several characteristics and applications. Prior research works reported that the energy consumption for transmission process is significantly higher compared to sensing and processing, which led to quick exhaustion of energy. In this view, this paper introduces a new energy efficient cluster enabled clinical decision support system (EEC-CDSS) for… More >

Qian Sun^1,2, Gongxue Cheng^1,2, Xiaoyi Wang^1,2,*, Jiping Xu^1,2, Li Wang^1,2, Huiyan Zhang^1,2, Jiabin Yu^1,2, Ning Cao³, Ruichao Wang⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2749-2759, 2021, DOI:10.32604/cmc.2021.018633 - 21 July 2021

Abstract Water quality sensor networks are widely used in water resource monitoring. However, due to the fact that the energy of these networks cannot be supplemented in time, it is necessary to study effective routing protocols to extend their lifecycle. To address the problem of limited resources, a routing optimization algorithm based on a small-world network model is proposed. In this paper, a small-world network model is introduced for water quality sensor networks, in which the short average path and large clustering coefficient of the model are used to construct a super link. A short average… More >