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  • Open Access

    ARTICLE

    Dynamic Modeling of the Feed Drive System of a CNC Metal Cutting Machine

    H. Heydarnia1,*, I. A. Kiselev1, M. M. Ermolaev2, S. Nikolaev3

    Sound & Vibration, Vol.55, No.1, pp. 19-30, 2021, DOI:10.32604/sv.2021.04410

    Abstract Studying the vibrational behavior of feed drive systems is important for enhancing the structural performance of computer numerical control (CNC) machines. The preload on the screw and nut position have a great influence on the vibration characteristics of the feed drive as two very important operational conditions. Rotational acceleration of the screw also affects the performance of the CNC feed drive when machining small parts. This paper investigates the influence of preload and nut position on the vibration characteristics of the feed drive system of a CNC metal cutting machine in order to be able to eliminate an observed resonance… More >

  • Open Access

    ARTICLE

    Experimental Study of Effect of Temperature Variations on the Impedance Signature of PZT Sensors for Fatigue Crack Detection

    Saqlain Abbas1,2,*, Fucai Li1, Zulkarnain Abbas3,4, Taufeeq Ur Rehman Abbasi5, Xiaotong Tu6, Riffat Asim Pasha7

    Sound & Vibration, Vol.55, No.1, pp. 1-18, 2021, DOI:10.32604/sv.2021.013754

    Abstract Structural health monitoring (SHM) is recognized as an efficient tool to interpret the reliability of a wide variety of infrastructures. To identify the structural abnormality by utilizing the electromechanical coupling property of piezoelectric transducers, the electromechanical impedance (EMI) approach is preferred. However, in real-time SHM applications, the monitored structure is exposed to several varying environmental and operating conditions (EOCs). The previous study has recognized the temperature variations as one of the serious EOCs that affect the optimal performance of the damage inspection process. In this framework, an experimental setup is developed in current research to identify the presence of fatigue… More >

  • Open Access

    ARTICLE

    Assessment of Noise Exposure of Sawmill Workers in Southwest, Nigeria

    Abiola O. Ajayeoba1,*, Adewoye A. Olanipekun2, Wasiu A. Raheem3, Oluwaseun O. Ojo4, Ayowumi R. Soji–Adekunle4

    Sound & Vibration, Vol.55, No.1, pp. 69-85, 2021, DOI:10.32604/sv.2021.011639

    Abstract Economic wood processing employs the use of industrial machines for cutting, shaping, milling, and sawing timber, thereby leading to the generation of high levels of noise. Published data from empirical studies have categorized noise as an environmental hazard of global significance. Furthermore, noise exposure limits for different industries and all the industrial machines available has not been formally established as it presently exists in developed nations around the world. Therefore, this study assessed the daily exposure of sawmills workers to noise in Southwestern Nigeria. Reconnaissance surveys were first carried out in Osun, Oyo, Ondo, Ekiti, Lagos, and Ogun States to… More >

  • Open Access

    ARTICLE

    Prediction and Limitations of Noise Maps Developed for Heterogeneous Urban Road Traffic Condition: A Case Study of Surat City, India

    Dipeshkumar R. Sonaviya*, Bhaven N. Tandel

    Sound & Vibration, Vol.55, No.1, pp. 57-68, 2021, DOI:10.32604/sv.2021.010715

    Abstract Road traffic noise pollution has been recognized as a serious issue which affects human health as well as affects urban regions. Noise maps are very beneficial to identify the impact of noise pollution. A noise mapping study performed to study the propagation of noise in tier-II city along with field measurements. The noise maps are developed using a computer simulation model (SoundPLAN essential 4.0 software). The noise prediction models like U.K’s CoRTN, Germany’s RLS-90, and their modified versions, which can be used for homogenous road traffic conditions, cannot be successfully applied in heterogeneous road traffic conditions of India. In developing… More >

  • Open Access

    ARTICLE

    COVID-19 Pandemic Data Predict the Stock Market

    Abdulaziz Almehmadi*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 451-460, 2021, DOI:10.32604/csse.2021.015309

    Abstract Unlike the 2007–2008 market crash, which was caused by a banking failure and led to an economic recession, the 1918 influenza pandemic triggered a worldwide financial depression. Pandemics usually affect the global economy, and the COVID-19 pandemic is no exception. Many stock markets have fallen over 40%, and companies are shutting down, ending contracts, and issuing voluntary and involuntary leaves for thousands of employees. These economic effects have led to an increase in unemployment rates, crime, and instability. Studying pandemics’ economic effects, especially on the stock market, has not been urgent or feasible until recently. However, with advances in artificial… More >

  • Open Access

    REVIEW

    A Review of Dynamic Resource Management in Cloud Computing Environments

    Mohammad Aldossary*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 461-476, 2021, DOI:10.32604/csse.2021.014975

    Abstract In a cloud environment, Virtual Machines (VMs) consolidation and resource provisioning are used to address the issues of workload fluctuations. VM consolidation aims to move the VMs from one host to another in order to reduce the number of active hosts and save power. Whereas resource provisioning attempts to provide additional resource capacity to the VMs as needed in order to meet Quality of Service (QoS) requirements. However, these techniques have a set of limitations in terms of the additional costs related to migration and scaling time, and energy overhead that need further consideration. Therefore, this paper presents a comprehensive… More >

  • Open Access

    ARTICLE

    Efficient Training of Multi-Layer Neural Networks to Achieve Faster Validation

    Adel Saad Assiri*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 435-450, 2021, DOI:10.32604/csse.2021.014894

    Abstract Artificial neural networks (ANNs) are one of the hottest topics in computer science and artificial intelligence due to their potential and advantages in analyzing real-world problems in various disciplines, including but not limited to physics, biology, chemistry, and engineering. However, ANNs lack several key characteristics of biological neural networks, such as sparsity, scale-freeness, and small-worldness. The concept of sparse and scale-free neural networks has been introduced to fill this gap. Network sparsity is implemented by removing weak weights between neurons during the learning process and replacing them with random weights. When the network is initialized, the neural network is fully… More >

  • Open Access

    ARTICLE

    On Edge Irregular Reflexive Labeling of Categorical Product of Two Paths

    Muhammad Javed Azhar Khan1, Muhammad Ibrahim1,*, Ali Ahmad2

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 485-492, 2021, DOI:10.32604/csse.2021.014810

    Abstract Among the huge diversity of ideas that show up while studying graph theory, one that has obtained a lot of popularity is the concept of labelings of graphs. Graph labelings give valuable mathematical models for a wide scope of applications in high technologies (cryptography, astronomy, data security, various coding theory problems, communication networks, etc.). A labeling or a valuation of a graph is any mapping that sends a certain set of graph elements to a certain set of numbers subject to certain conditions. Graph labeling is a mapping of elements of the graph, i.e., vertex and/or edges to a set… More >

  • Open Access

    ARTICLE

    ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

    Yanyun Jiang1, Yuanjie Zheng1,2,*, Xiaodan Sui1, Wanzhen Jiao3, Yunlong He4, Weikuan Jia1

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 537-549, 2021, DOI:10.32604/csse.2021.014578

    Abstract Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep learning framework called “Adversarial Segmentation… More >

  • Open Access

    ARTICLE

    A Storage Optimization Scheme for Blockchain Transaction Databases

    Jingyu Zhang1,2, Siqi Zhong1, Jin Wang1,3, Xiaofeng Yu4,*, Osama Alfarraj5

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 521-535, 2021, DOI:10.32604/csse.2021.014530

    Abstract As the typical peer-to-peer distributed networks, blockchain systems require each node to copy a complete transaction database, so as to ensure new transactions can by verified independently. In a blockchain system (e.g., bitcoin system), the node does not rely on any central organization, and every node keeps an entire copy of the transaction database. However, this feature determines that the size of blockchain transaction database is growing rapidly. Therefore, with the continuous system operations, the node memory also needs to be expanded to support the system running. Especially in the big data era, the increasing network traffic will lead to… More >

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