Home / Journals / CSSE / Vol.41, No.3, 2022
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    ARTICLE

    Fuzzy Based Reliable Load Balanced Routing Approach for Ad hoc Sensor Networks

    J. V. Anchitaalagammai1,*, Rajesh Verma2, M. Kavitha3, A. R. Revathi4, S. R. Preethi5, Kiranmai Bellam6
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 861-874, 2022, DOI:10.32604/csse.2022.021049
    Abstract Energy management and packet delivery rate are the important factors in ad hoc networks. It is the major network where nodes share the information without administration. Due to the mobility of nodes, maximum energy is spent on transmission of packets. Mostly energy is wasted on packet dropping and false route discovery. In this research work, Fuzzy Based Reliable Load Balanced Routing Approach (RLRA) is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery mechanism. It contains three phases. In first phase, optimal multicast route discovery is initiated to resolve the link failures. In second… More >

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    ARTICLE

    Object Tracking-Based “Follow-Me” Unmanned Aerial Vehicle (UAV) System

    Olubukola D. Adekola1,*, Onyedikachi Kenny Udekwu2, Oluwatobi Tolulope Saliu2, Damilola Williams Dada2, Stephen O. Maitanmi1, Victor Odumuyiwa3, Olujimi Alao2, Monday Eze2, Funmilayo Abibat Kasali4, Ayokunle Omotunde2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 875-890, 2022, DOI:10.32604/csse.2022.021029
    (This article belongs to this Special Issue: Advances in Computational Intelligence and its Applications)
    Abstract The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies primarily due to the lack… More >

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    ARTICLE

    Software Reliability Assessment Using Hybrid Neuro-Fuzzy Model

    Parul Gandhi1, Mohammad Zubair Khan2, Ravi Kumar Sharma3, Omar H. Alhazmi2, Surbhi Bhatia4,*, Chinmay Chakraborty5
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943
    Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software reliability. The proposed algorithm is… More >

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    ARTICLE

    Profile and Rating Similarity Analysis for Recommendation Systems Using Deep Learning

    Lakshmi Palaniappan1,*, K. Selvaraj2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 903-917, 2022, DOI:10.32604/csse.2022.020670
    Abstract Recommendation systems are going to be an integral part of any E-Business in near future. As in any other E-business, recommendation systems also play a key role in the travel business where the user has to be recommended with a restaurant that best suits him. In general, the recommendations to a user are made based on similarity that exists between the intended user and the other users. This similarity can be calculated either based on the similarity between the user profiles or the similarity between the ratings made by the users. First phase of this work concentrates on experimentally analyzing… More >

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    ARTICLE

    Optimal Load Balancing in Cloud Environment of Virtual Machines

    Fuad A.M. Al-Yarimi1,*, Sami Althahabi1, Majdy Mohammed Eltayeb2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 919-932, 2022, DOI:10.32604/csse.2022.021272
    Abstract Cloud resource scheduling is gaining prominence with the increasing trends of reliance on cloud infrastructure solutions. Numerous sets of cloud resource scheduling models were evident in the literature. Cloud resource scheduling refers to the distinct set of algorithms or programs the service providers engage to maintain the service level allocation for various resources over a virtual environment. The model proposed in this manuscript schedules resources of virtual machines under potential volatility aspects, which can be applied for any priority metric chosen by the server administrators. Also, the model can be flexible for any time frame-based analysis of the load factor.… More >

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    ARTICLE

    A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus

    Hassan Al-Tarawneh1, Khalid Al-Kaabneh1, Aysh Alhroob2, Hazem Migdady3, Issam Alhadid4,*
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 933-944, 2022, DOI:10.32604/csse.2022.021078
    (This article belongs to this Special Issue: Advances in Computational Intelligence and its Applications)
    Abstract Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing these measures at universities is crucial and directly related to the physical attendance of the populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providing assistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints. First, a distance of two meters must be maintained between… More >

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    ARTICLE

    A Novel Post-Quantum Blind Signature for Log System in Blockchain

    Gang Xu1,2, Yibo Cao1, Shiyuan Xu1, Ke Xiao1, Xin Liu3, Xiubo Chen4,*, Mianxiong Dong5
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 945-958, 2022, DOI:10.32604/csse.2022.022100
    Abstract In recent decades, log system management has been widely studied for data security management. System abnormalities or illegal operations can be found in time by analyzing the log and provide evidence for intrusions. In order to ensure the integrity of the log in the current system, many researchers have designed it based on blockchain. However, the emerging blockchain is facing significant security challenges with the increment of quantum computers. An attacker equipped with a quantum computer can extract the user's private key from the public key to generate a forged signature, destroy the structure of the blockchain, and threaten the… More >

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    ARTICLE

    Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

    Abhishek Kumar Pandey1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Rajeev Kumar4,*, Raees Ahmad Khan1
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 959-974, 2022, DOI:10.32604/csse.2022.021443
    Abstract The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a decision making based methodology of… More >

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    ARTICLE

    An Effective and Secure Quality Assurance System for a Computer Science Program

    Mohammad Alkhatib*
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 975-995, 2022, DOI:10.32604/csse.2022.021398
    Abstract Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs) assessment and continuous quality improvement represent core components of the quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes for continuous improvement planning. Moreover, the absence of automation, and integration in QA processes forms a major obstacle towards developing efficient quality system. There is a pressing need to adopt security protocols that provide required security services to safeguard the valuable information processed by QAS as well. This research proposes an effective… More >

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    ARTICLE

    Smart COVID-3D-SCNN: A Novel Method to Classify X-ray Images of COVID-19

    Ahed Abugabah1,*, Atif Mehmood2, Ahmad Ali AL Zubi3, Louis Sanzogni4
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 997-1008, 2022, DOI:10.32604/csse.2022.021438
    Abstract The outbreak of the novel coronavirus has spread worldwide, and millions of people are being infected. Image or detection classification is one of the first application areas of deep learning, which has a significant contribution to medical image analysis. In classification detection, one or more images (detection) are usually used as input, and diagnostic variables (such as whether there is a disease) are used as output. The novel coronavirus has spread across the world, infecting millions of people. Early-stage detection of critical cases of COVID-19 is essential. X-ray scans are used in clinical studies to diagnose COVID-19 and Pneumonia early.… More >

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    ARTICLE

    Automated Teller Machine Authentication Using Biometric

    Shumukh M. Aljuaid*, Arshiya S. Ansari
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.020785
    Abstract This paper presents a novel method of a secured card-less Automated Teller Machine (ATM) authentication based on the three bio-metrics measures. It would help in the identification and authorization of individuals and would provide robust security enhancement. Moreover, it would assist in providing identification in ways that cannot be impersonated. To the best of our knowledge, this method of Biometric_ fusion way is the first ATM security algorithm that utilizes a fusion of three biometric features of an individual such as Fingerprint, Face, and Retina simultaneously for recognition and authentication. These biometric images have been collected as input data for… More >

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    ARTICLE

    Clustering Gene Expression Data Through Modified Agglomerative M-CURE Hierarchical Algorithm

    E. Kavitha1,*, R. Tamilarasan2, N. Poonguzhali3, M. K. Jayanthi Kannan4
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1027-141, 2022, DOI:10.32604/csse.2022.020634
    Abstract Gene expression refers to the process in which the gene information is used in the functional gene product synthesis. They basically encode the proteins which in turn dictate the functionality of the cell. The first step in gene expression study involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise and imprecision. For a biological system to function, the essential cellular molecules must interact with its surrounding including RNA, DNA, metabolites and proteins. Clustering methods will… More >

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    ARTICLE

    A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

    Xiaorui Zhang1,3,*, Wenfang Zhang1, Wei Sun2, Xingming Sun1, Sunil Kumar Jha4
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1043-1056, 2022, DOI:10.32604/csse.2022.022305
    Abstract In a telemedicine diagnosis system, the emergence of 3D imaging enables doctors to make clearer judgments, and its accuracy also directly affects doctors’ diagnosis of the disease. In order to ensure the safe transmission and storage of medical data, a 3D medical watermarking algorithm based on wavelet transform is proposed in this paper. The proposed algorithm employs the principal component analysis (PCA) transform to reduce the data dimension, which can minimize the error between the extracted components and the original data in the mean square sense. Especially, this algorithm helps to create a bacterial foraging model based on particle swarm… More >

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    ARTICLE

    Cost Effective Decentralized Key Management Framework for IoT

    Raja Lavanya*, K. Sundarakantham, S. Mercy Shalinie
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1057-1070, 2022, DOI:10.32604/csse.2022.021052
    Abstract Security is a primary concern in communication for reliable transfer of information between the authenticated members, which becomes more complex in a network of Internet of Things (IoT). To provide security for group communication a key management scheme incorporating Bilinear pairing technique with Multicast and Unicast key management protocol (BMU-IOT) for decentralized networks has been proposed. The first part of the proposed work is to divide the network into clusters where sensors are connected to and is administered by cluster head. Each sensor securely shares its secret keys with the cluster head using unicast. Based on these decryption keys, the… More >

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    ARTICLE

    Proportional Fairness Based Energy Efficient Routing in Wireless Sensor Network

    Abolfazl Mehbodniya1, Surbhi Bhatia2, Arwa Mashat3, Mohanraj Elangovan4,*, Sudhakar Sengan5
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1071-1082, 2022, DOI:10.32604/csse.2022.021529
    Abstract Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions, device monitoring, and collection of information. Due to limited energy resources available at SN, the primary issue is to present an energy-efficient framework and conserve the energy while constructing a route path along with each sensor node. However, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routing with minimal energy consumption in WSN. This paper presents an energy-efficient routing system called Energy-aware Proportional Fairness Multi-user Routing (EPFMR) framework in WSN.… More >

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    ARTICLE

    Emotion Recognition with Capsule Neural Network

    Loan Trinh Van1, Quang H. Nguyen1,*, Thuy Dao Thi Le2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1083-1098, 2022, DOI:10.32604/csse.2022.021635
    Abstract For human-machine communication to be as effective as human-to-human communication, research on speech emotion recognition is essential. Among the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsule neural network (CapsNet) with inputs and outputs that are not scalar quantities but vectors allows the network to determine the part-whole relationships that are specific 6 for an object. This paper performs speech emotion recognition based on CapsNet. The corpora for speech emotion recognition have been augmented by… More >

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    ARTICLE

    Digital Mammogram Inferencing System Using Intuitionistic Fuzzy Theory

    Susmita Mishra1,*, M. Prakash2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1099-1115, 2022, DOI:10.32604/csse.2022.020439
    Abstract In the medical field, the detection of breast cancer may be a mysterious task. Physicians must deduce a conclusion from a significantly vague knowledge base. A mammogram can offer early diagnosis at a low cost if the breasts' satisfactory mammogram images are analyzed. A multi-decision Intuitionistic Fuzzy Evidential Reasoning (IFER) approach is introduced in this paper to deal with imprecise mammogram classification efficiently. The proposed IFER approach combines intuitionistic trapezoidal fuzzy numbers and inclusion measures to improve representation and reasoning accuracy. The results of the proposed technique are approved through simulation. The simulation is created utilizing MATLAB software. The screening… More >

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    ARTICLE

    Defect Prediction Using Akaike and Bayesian Information Criterion

    Saleh Albahli1,*, Ghulam Nabi Ahmad Hassan Yar2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1117-1127, 2022, DOI:10.32604/csse.2022.021750
    (This article belongs to this Special Issue: Recent Trends in Software Engineering and Applications)
    Abstract Data available in software engineering for many applications contains variability and it is not possible to say which variable helps in the process of the prediction. Most of the work present in software defect prediction is focused on the selection of best prediction techniques. For this purpose, deep learning and ensemble models have shown promising results. In contrast, there are very few researches that deals with cleaning the training data and selection of best parameter values from the data. Sometimes data available for training the models have high variability and this variability may cause a decrease in model accuracy. To… More >

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    ARTICLE

    Towards Public Integrity Audition for Cloud-IoT Data Based on Blockchain

    Hao Yan1,2, Yanan Liu1, Shuo Qiu1, Shengzhou Hu3, Weijian Zhang4,*, Jinyue Xia5
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1129-1142, 2022, DOI:10.32604/csse.2022.022317
    Abstract With the rapidly developing of Internet of Things (IoT), the volume of data generated by IoT systems is increasing quickly. To release the pressure of data management and storage, more and more enterprises and individuals prefer to integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted, a variety of methods have been proposed to deal with the problem of data integrity checking. In traditional data integrity audition schemes, the task of data auditing is usually performed by Third Party Auditor (TPA) which is… More >

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    ARTICLE

    N-Body Simulation Inspired by Metaheuristics Optimization

    Muhammad Ali Ismail*, Maria Waqas, Farah Sadiq
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1143-1155, 2022, DOI:10.32604/csse.2022.021604
    Abstract The N-body problem in classical physics, is the calculation of force of gravitational attraction of heavenly bodies towards each other. Solving this problem for many heavenly bodies has always posed a challenge to physicists and mathematicians. Large number of bodies, huge masses, long distances and exponentially increasing number of equations of motion of the bodies have been the major hurdles in solving this problem for large and complex galaxies. Advent of high performance computational machines have mitigated the problem to much extent, but still for large number of bodies it consumes huge amount of resources and days for computation. Conventional… More >

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    ARTICLE

    Design of Miniature UWB-Based Antenna by Employing a Tri-Sectional SIR Feeder

    Ehab Dh. Hussein1,*, Yaqeen S. Mezaal2, Oguz Bayat1
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1157-1172, 2022, DOI:10.32604/csse.2022.021205
    (This article belongs to this Special Issue: Emergent Topics in Intelligent Computing and Communication Engineering)
    Abstract A novel ultra-wideband (UWB)-based microstrip antenna is presented in this work by using a slotted patch resonator, a tri-sectional stepped impedance resonator (SIR) feeder, as well as a reduced ground plane. The whole structure was realized on an FR4 substrate. The impact of incorporating several cases of ground planes on the input reflection has been thoroughly investigated under the same tri-sectional SIR feeder and by employing a slotted patch radiator. Since the complete ground plane presents an inadequate frequency response, by reducing the ground plane, the induced UWB responses are apparent while the antenna exhibits higher impedance bandwidth. The impact… More >

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    ARTICLE

    Energy Efficient QoS Aware Cluster Based Multihop Routing Protocol for WSN

    M.S. Maharajan1,*, T. Abirami2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1173-1189, 2022, DOI:10.32604/csse.2022.020312
    Abstract Wireless sensor networks (WSN) have become a hot research area owing to the unique characteristics and applicability in diverse application areas. Clustering and routing techniques can be considered as an NP hard optimization problem, which can be addressed by metaheuristic optimization algorithms. With this motivation, this study presents a chaotic sandpiper optimization algorithm based clustering with groundwater flow optimization based routing technique (CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensor nodes in WSN and elect an optimal set of routes with an intention of achieving energy efficiency and maximizing network lifetime. The CSPOC algorithm is derived… More >

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    ARTICLE

    System Dynamics Forecasting on Taiwan Power Supply Chain

    Zhiqiu Yu1,*, Shuo-Yan Chou1, Phan Nguyen Ky Phuc2, Tiffany Hui-Kuang Yu3
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1191-1205, 2022, DOI:10.32604/csse.2022.021239
    (This article belongs to this Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)
    Abstract This research aims to study the sustainability of Taiwan power supply chain based on system dynamics forecasting. The paper tries to investigate electricity shortage effects not only on the industrial side, but also from the standpoint of society. In our model, different forecasting methods such as linear regression, time series analysis, and gray forecasting are also considered to predict the parameters. Further tests such as the structure, dimension, historical fit, and sensitivity of the model are also conducted in this paper. Through analysis forecasting result, we believe that the demand for electricity in Taiwan will continue to increase to a… More >

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    ARTICLE

    LogUAD: Log Unsupervised Anomaly Detection Based on Word2Vec

    Jin Wang1, Changqing Zhao1, Shiming He1,*, Yu Gu2, Osama Alfarraj3, Ahed Abugabah4
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1207-1222, 2022, DOI:10.32604/csse.2022.022365
    Abstract System logs record detailed information about system operation and are important for analyzing the system's operational status and performance. Rapid and accurate detection of system anomalies is of great significance to ensure system stability. However, large-scale distributed systems are becoming more and more complex, and the number of system logs gradually increases, which brings challenges to analyze system logs. Some recent studies show that logs can be unstable due to the evolution of log statements and noise introduced by log collection and parsing. Moreover, deep learning-based detection methods take a long time to train models. Therefore, to reduce the computational… More >

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    ARTICLE

    Prediction of Covid-19 Based on Chest X-Ray Images Using Deep Learning with CNN

    Anika Tahsin Meem1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Sultan Aljahdali2
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1223-1240, 2022, DOI:10.32604/csse.2022.021563
    Abstract The COVID-19 pandemic has caused trouble in people’s daily lives and ruined several economies around the world, killing millions of people thus far. It is essential to screen the affected patients in a timely and cost-effective manner in order to fight this disease. This paper presents the prediction of COVID-19 with Chest X-Ray images, and the implementation of an image processing system operated using deep learning and neural networks. In this paper, a Deep Learning, Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed. In this study, machine learning… More >

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    ARTICLE

    Interactive Middleware Services for Heterogeneous Systems

    Vasanthi Raghupathy1,*, Osamah Ibrahim Khalaf2, Carlos Andrés Tavera Romero3, Sudhakar Sengan4, Dilip Kumar Sharma5
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1241-1253, 2022, DOI:10.32604/csse.2022.021997
    Abstract Computing has become more invisible, widespread and ubiquitous since the inception of the Internet of Things (IoT) and Web of Things. Multiple devices that surround us meet user’s requirements everywhere. Multiple Middleware Framework (MF) designs have come into existence because of the rapid development of interactive services in Heterogeneous Systems. This resulted in the delivery of interactive services throughout Heterogeneous Environments (HE). Users are given free navigation between devices in a widespread environment and continuously interact with each other from any chosen device. Numerous interactive devices with recent interactive platforms (for example, Smart Phones, Mobile Phones, Personal Computer (PC) and… More >

  • Open AccessOpen Access

    ARTICLE

    X-Ray Covid-19 Detection Based on Scatter Wavelet Transform and Dense Deep Neural Network

    Ali Sami Al-Itbi*, Ahmed Bahaaulddin A. Alwahhab, Ali Mohammed Sahan
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1255-1271, 2022, DOI:10.32604/csse.2022.021980
    Abstract Notwithstanding the discovery of vaccines for Covid-19, the virus's rapid spread continues due to the limited availability of vaccines, especially in poor and emerging countries. Therefore, the key issues in the present COVID-19 pandemic are the early identification of COVID-19, the cautious separation of infected cases at the lowest cost and curing the disease in the early stages. For that reason, the methodology adopted for this study is imaging tools, particularly computed tomography, which have been critical in diagnosing and treating the disease. A new method for detecting Covid-19 in X-rays and CT images has been presented based on the… More >

  • Open AccessOpen Access

    ARTICLE

    Heart Disease Classification Using Multiple K-PCA and Hybrid Deep Learning Approach

    S. Kusuma*, Dr. Jothi K. R
    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1273-1289, 2022, DOI:10.32604/csse.2022.021741
    Abstract One of the severe health problems and the most common types of heart disease (HD) is Coronary heart disease (CHD). Due to the lack of a healthy lifestyle, HD would cause frequent mortality worldwide. If the heart attack occurs without any symptoms, it cannot be cured by an intelligent detection system. An effective diagnosis and detection of CHD should prevent human casualties. Moreover, intelligent systems employ clinical-based decision support approaches to assist physicians in providing another option for diagnosing and detecting HD. This paper aims to introduce a heart disease prediction model including phases like (i) Feature extraction, (ii) Feature… More >

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