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  • Open Access

    ARTICLE

    Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

    Hsin-Pin Fu1,*, Tsung-Sheng Chang2, Chien-Hung Liu3, Li-Chun Liu1

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 213-227, 2022, DOI:10.32604/csse.2022.021767

    Abstract The advantages of a cloud computing service are cost advantages, availability, scalability, flexibility, reduced time to market, and dynamic access to computing resources. Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework. Then, a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical… More >

  • Open Access

    ARTICLE

    Automated Deep Learning Based Cardiovascular Disease Diagnosis Using ECG Signals

    S. Karthik1, M. Santhosh1,*, M. S. Kavitha1, A. Christopher Paul2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 183-199, 2022, DOI:10.32604/csse.2022.021698

    Abstract Automated biomedical signal processing becomes an essential process to determine the indicators of diseased states. At the same time, latest developments of artificial intelligence (AI) techniques have the ability to manage and analyzing massive amounts of biomedical datasets results in clinical decisions and real time applications. They can be employed for medical imaging; however, the 1D biomedical signal recognition process is still needing to be improved. Electrocardiogram (ECG) is one of the widely used 1-dimensional biomedical signals, which is used to diagnose cardiovascular diseases. Computer assisted diagnostic models find it difficult to automatically classify the 1D ECG signals owing to… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Pruning Technique for Low Power Approximate Computing

    B. Sakthivel1,*, K. Jayaram2, N. Manikanda Devarajan3, S. Mahaboob Basha4, S. Rajapriya5

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 397-406, 2022, DOI:10.32604/csse.2022.021637

    Abstract Approximate Computing is a low power achieving technique that offers an additional degree of freedom to design digital circuits. Pruning is one of the types of approximate circuit design technique which removes logic gates or wires in the circuit to reduce power consumption with minimal insertion of error. In this work, a novel machine learning (ML) -based pruning technique is introduced to design digital circuits. The machine-learning algorithm of the random forest decision tree is used to prune nodes selectively based on their input pattern. In addition, an error compensation value is added to the original output to reduce an… More >

  • Open Access

    ARTICLE

    Prediction Model Using Reinforcement Deep Learning Technique for Osteoarthritis Disease Diagnosis

    R. Kanthavel1,*, R. Dhaya2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 257-269, 2022, DOI:10.32604/csse.2022.021606

    Abstract Osteoarthritis is the most common class of arthritis that involves tears down the soft cartilage between the joints of the knee. The regeneration of this cartilage tissue is not possible, and thus physicians typically suggest therapeutic measures to prevent further deterioration over time. Normally, bringing about joint replacement is a remedial course of action. Expose itself in joint pain recognized with a normal X-ray. Deep learning plays a vital role in predicting the early stages of osteoarthritis by using the MRI pictures of muscles of the knee muscle. It can be used to accurately measure the shape and texture of… More >

  • Open Access

    ARTICLE

    An Effective Secure MAC Protocol for Cognitive Radio Networks

    Bayan Al-Amri1, Gofran Sami2, Wajdi Alhakami1,*

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 133-148, 2022, DOI:10.32604/csse.2022.021543

    Abstract The vast revolution in networking is increasing rapidly along with technology advancements, which requires more effort from all cyberspace professionals to cope with the challenges that come with advanced technology privileges and services. Hence, Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utilization of idle spectrum portions of wireless communications. However, it is vulnerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure communication environment. This paper presents an effective secure MAC protocol for cognitive radio… More >

  • Open Access

    ARTICLE

    Development of Efficient Classification Systems for the Diagnosis of Melanoma

    S. Palpandi1,*, T. Meeradevi2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 361-371, 2022, DOI:10.32604/csse.2022.021412

    Abstract Skin cancer is usually classified as melanoma and non-melanoma. Melanoma now represents 75% of humans passing away worldwide and is one of the most brutal types of cancer. Previously, studies were not mainly focused on feature extraction of Melanoma, which caused the classification accuracy. However, in this work, Histograms of orientation gradients and local binary patterns feature extraction procedures are used to extract the important features such as asymmetry, symmetry, boundary irregularity, color, diameter, etc., and are removed from both melanoma and non-melanoma images. This proposed Efficient Classification Systems for the Diagnosis of Melanoma (ECSDM) framework consists of different schemes… More >

  • Open Access

    ARTICLE

    Enhancement of E-commerce Service by Designing Last Mile Delivery Platform

    Ali Alkhalifah*, Fadwa Alorini, Reef Alturki

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 49-67, 2022, DOI:10.32604/csse.2022.021326

    Abstract The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce. Last mile delivery, for which different app-based delivery services have recently emerged, is a new area of research that is not thoroughly addressed. Delivery service is one of the supporting platforms of e-commerce. One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service. This challenge is emphasized in this study which introduces a new system to facilitate communication and coordination between customers and… More >

  • Open Access

    ARTICLE

    Hybridized Wrapper Filter Using Deep Neural Network for Intrusion Detection

    N. Venkateswaran1,*, K. Umadevi2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 1-14, 2022, DOI:10.32604/csse.2022.021217

    Abstract Huge data over the cloud computing and big data are processed over the network. The data may be stored, send, altered and communicated over the network between the source and destination. Once data send by source to destination, before reaching the destination data may be attacked by any intruders over the network. The network has numerous routers and devices to connect to internet. Intruders may attack any were in the network and breaks the original data, secrets. Detection of attack in the network became interesting task for many researchers. There are many intrusion detection feature selection algorithm has been suggested… More >

  • Open Access

    ARTICLE

    Aero-Engine Surge Fault Diagnosis Using Deep Neural Network

    Kexin Zhang1, Bin Lin2,*, Jixin Chen1, Xinlong Wu1, Chao Lu3, Desheng Zheng1, Lulu Tian4

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 351-360, 2022, DOI:10.32604/csse.2022.021132

    Abstract Deep learning techniques have outstanding performance in feature extraction and model fitting. In the field of aero-engine fault diagnosis, the introduction of deep learning technology is of great significance. The aero-engine is the heart of the aircraft, and its stable operation is the primary guarantee of the aircraft. In order to ensure the normal operation of the aircraft, it is necessary to study and diagnose the faults of the aero-engine. Among the many engine failures, the one that occurs more frequently and is more hazardous is the wheeze, which often poses a great threat to flight safety. On the basis… More >

  • Open Access

    ARTICLE

    Grey Hole Attack Detection and Prevention Methods in Wireless Sensor Networks

    Gowdham Chinnaraju*, S. Nithyanandam

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 373-386, 2022, DOI:10.32604/csse.2022.020993

    Abstract Wireless Sensor Networks (WSNs) gained wide attention in the past decade, thanks to its attractive features like flexibility, monitoring capability, and scalability. It overcomes the crucial problems experienced in network management and facilitates the development of diverse network architectures. The existence of dynamic and adaptive routing features facilitate the quick formation of such networks. But flexible architecture also makes it highly vulnerable to different sorts of attacks, for instance, Denial of Service (DoS). Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of… More >

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