Home / Journals / CSSE / Vol.40, No.1, 2022
  • Open Access

    ARTICLE

    An IoT-Aware System for Managing Patients’ Waiting Time Using Bluetooth Low-Energy Technology

    Reham Alabduljabbar*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 1-16, 2022, DOI:10.32604/csse.2022.018102
    (This article belongs to this Special Issue: Sensors and Nano-sensors Technologies for Health-Care Applications)
    Abstract It is a common observation that whenever patients arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, concerning health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology is presented to solve the problem. Recently, a technology-oriented method, the Internet of Things (IoT), has been gaining popularity in helping to solve some of the healthcare sector’s problems.… More >

  • Open Access

    ARTICLE

    Scheduling Flexible Flow Shop in Labeling Companies to Minimize the Makespan

    Chia-Nan Wang1, Hsien-Pin Hsu2, Hsin-Pin Fu3,*, Nguyen Ky Phuc Phan4, Van Thanh Nguyen5
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 17-36, 2022, DOI:10.32604/csse.2022.016992
    (This article belongs to this Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)
    Abstract In the competitive global marketplace, production scheduling plays a vital role in planning in manufacturing. Scheduling deals directly with the time to output products quickly and with a low production cost. This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison. The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders. This study analyzes the flexible flow shop scheduling problem with a sequence dependent… More >

  • Open Access

    ARTICLE

    Blockchain: Secured Solution for Signature Transfer in Distributed Intrusion Detection System

    Shraddha R. Khonde1,2,*, Venugopal Ulagamuthalvi1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 37-51, 2022, DOI:10.32604/csse.2022.017130
    Abstract Exchange of data in networks necessitates provision of security and confidentiality. Most networks compromised by intruders are those where the exchange of data is at high risk. The main objective of this paper is to present a solution for secure exchange of attack signatures between the nodes of a distributed network. Malicious activities are monitored and detected by the Intrusion Detection System (IDS) that operates with nodes connected to a distributed network. The IDS operates in two phases, where the first phase consists of detection of anomaly attacks using an ensemble of classifiers such as Random forest, Convolutional neural network,… More >

  • Open Access

    ARTICLE

    Repeated Attribute Optimization for Big Data Encryption

    Abdalla Alameen*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 53-64, 2022, DOI:10.32604/csse.2022.017597
    Abstract Big data denotes the variety, velocity, and massive volume of data. Existing databases are unsuitable to store big data owing to its high volume. Cloud computing is an optimal solution to process and store big data. However, the significant issue lies in handling access control and privacy, wherein the data should be encrypted and unauthorized user access must be restricted through efficient access control. Attribute-based encryption (ABE) permits users to encrypt and decrypt data. However, for the policy to work in practical scenarios, the attributes must be repeated. In the case of specific policies, it is not possible to avoid… More >

  • Open Access

    ARTICLE

    Optimizing Traffic Signals in Smart Cities Based on Genetic Algorithm

    Nagham A. Al-Madi*, Adnan A. Hnaif
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 65-74, 2022, DOI:10.32604/csse.2022.016730
    Abstract Current traffic signals in Jordan suffer from severe congestion due to many factors, such as the considerable increase in the number of vehicles and the use of fixed timers, which still control existing traffic signals. This condition affects travel demand on the streets of Jordan. This study aims to improve an intelligent road traffic management system (IRTMS) derived from the human community-based genetic algorithm (HCBGA) to mitigate traffic signal congestion in Amman, Jordan’s capital city. The parameters considered for IRTMS are total time and waiting time, and fixed timers are still used for control. By contrast, the enhanced system, called… More >

  • Open Access

    ARTICLE

    Stochastic Programming For Order Allocation And Production Planning

    Phan Nguyen Ky Phuc*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 75-85, 2022, DOI:10.32604/csse.2022.017793
    (This article belongs to this Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)
    Abstract Stochastic demand is an important factor that heavily affects production planning. It influences activities such as purchasing, manufacturing, and selling, and quick adaption is required. In production planning, for reasons such as reducing costs and obtaining supplier discounts, many decisions must be made in the initial stage when demand has not been realized. The effects of non-optimal decisions will propagate to later stages, which can lead to losses due to overstocks or out-of-stocks. To find the optimal solutions for the initial and later stage regarding demand realization, this study proposes a stochastic two-stage linear programming model for a multi-supplier, multi-material,… More >

  • Open Access

    REVIEW

    Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges

    Salam Al-E’mari1, Mohammed Anbar1,*, Yousef Sanjalawe1,2, Selvakumar Manickam1, Iznan Hasbullah1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 87-112, 2022, DOI:10.32604/csse.2022.017941
    (This article belongs to this Special Issue: Emerging Trends in Intelligent Communication and Wireless Technologies)
    Abstract Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches. However, the current approaches have challenges in detecting intrusions, which may affect the performance of the overall detection system as well as network performance. For the time being, one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter… More >

  • Open Access

    ARTICLE

    Effective Hybrid Content-Based Collaborative Filtering Approach for Requirements Engineering

    Qusai Y. Shambour*, Abdelrahman H. Hussein, Qasem M. Kharma, Mosleh M. Abualhaj
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 113-125, 2022, DOI:10.32604/csse.2022.017221
    Abstract Requirements engineering (RE) is among the most valuable and critical processes in software development. The quality of this process significantly affects the success of a software project. An important step in RE is requirements elicitation, which involves collecting project-related requirements from different sources. Repositories of reusable requirements are typically important sources of an increasing number of reusable software requirements. However, the process of searching such repositories to collect valuable project-related requirements is time-consuming and difficult to perform accurately. Recommender systems have been widely recognized as an effective solution to such problem. Accordingly, this study proposes an effective hybrid content-based collaborative… More >

  • Open Access

    ARTICLE

    A Coordinated Search Algorithm for a Lost Target on the Plane

    Sundus Naji Al-Aziz1,*, Abd Al-Aziz Hosni El-Bagoury2, W. Afifi2,3
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 127-137, 2022, DOI:10.32604/csse.2022.016007
    Abstract Concepts in search theory have developed since World War II. The study of search plans has found considerable interest among searchers due to its wide applications in our life. Searching for lost targets either located or moved is often a time-critical issue, especially when the target is very important . In many commercial and scientific missions at sea, it is of crucial importance to find lost targets underwater. We illustrate a technique known as coordinated search, that completely characterizes the search for a randomly located target on a plane. The idea is to avoid wasting time looking for a missing… More >

  • Open Access

    ARTICLE

    Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

    Lei Ren1, Jing Hu2, Mei Li1,*, Ling Zhang2, Jinyue Xia3
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 139-150, 2022, DOI:10.32604/csse.2022.018640
    Abstract Lung rehabilitation is safe and feasible, and it has positive benefits in weaning the machine as soon as possible, shortening the time of hospitalization and improving the prognosis of children with mechanical ventilation. However, at present, the traditional medical concept is deep-rooted, and doctors' understanding of early rehabilitation is inadequate. It is necessary to make in-depth exploration in the relevant guidelines and expert consensus to formulate standardized early rehabilitation diagnosis and treatment procedures and standards for mechanically ventilated children. In the paper, a structured graded lung rehabilitation program is constructed for children with mechanical ventilation to improve their respiratory function,… More >

  • Open Access

    ARTICLE

    Dates Fruit Recognition: From Classical Fusion to Deep Learning

    Khaled Marji Alresheedi1, Suliman Aladhadh2, Rehan Ullah Khan2, Ali Mustafa Qamar1,3,*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 151-166, 2022, DOI:10.32604/csse.2022.017931
    Abstract There are over 200 different varieties of dates fruit in the world. Interestingly, every single type has some very specific features that differ from the others. In recent years, sorting, separating, and arranging in automated industries, in fruits businesses, and more specifically in dates businesses have inspired many research dimensions. In this regard, this paper focuses on the detection and recognition of dates using computer vision and machine learning. Our experimental setup is based on the classical machine learning approach and the deep learning approach for nine classes of dates fruit. Classical machine learning includes the Bayesian network, Support Vector… More >

  • Open Access

    ARTICLE

    Recent Techniques for Harvesting Energy from the Human Body

    Nidal M. Turab1, Hamza Abu Owida2, Jamal I. Al-Nabulsi2,*, Mwaffaq Abu-Alhaija1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 167-177, 2022, DOI:10.32604/csse.2022.017973
    (This article belongs to this Special Issue: Sensors and Nano-sensors Technologies for Health-Care Applications)
    Abstract The human body contains a near-infinite supply of energy in chemical, thermal, and mechanical forms. However, the majority of implantable and wearable devices are still operated by batteries, whose insufficient capacity and large size limit their lifespan and increase the risk of hazardous material leakage. Such energy can be used to exceed the battery power limits of implantable and wearable devices. Moreover, novel materials and fabrication methods can be used to create various medical therapies and life-enhancing technologies. This review paper focuses on energy-harvesting technologies used in medical and health applications, primarily power collectors from the human body. Current approaches… More >

  • Open Access

    ARTICLE

    Secure and Light Weight Elliptic Curve Cipher Suites in SSL/TLS

    B. Arunkumar*, G. Kousalya
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 179-190, 2022, DOI:10.32604/csse.2022.018166
    Abstract In the current circumstance, e-commerce through an online banking system plays a significant role. Customers may either buy goods from E-Commerce websites or use online banking to move money to other accounts. When a user participates in these types of behaviors, their sensitive information is sent to an untrustworthy network. As a consequence, when transmitting data from an internal browser to an external E-commerce web server using the cryptographic protocol SSL/TLS, the E-commerce web server ensures the security of the user’s data. The user should be pleased with the confidentiality, authentication, and authenticity properties of the SSL/TLS on both the… More >

  • Open Access

    ARTICLE

    Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

    A. Thasil Mohamed, Sundar Santhoshkumar*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 191-205, 2022, DOI:10.32604/csse.2022.016754
    Abstract Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it… More >

  • Open Access

    ARTICLE

    A New Random Forest Applied to Heavy Metal Risk Assessment

    Ziyan Yu1, Cong Zhang1,*, Naixue Xiong2, Fang Chen1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 207-221, 2022, DOI:10.32604/csse.2022.018301
    Abstract As soil heavy metal pollution is increasing year by year, the risk assessment of soil heavy metal pollution is gradually gaining attention. Soil heavy metal datasets are usually imbalanced datasets in which most of the samples are safe samples that are not contaminated with heavy metals. Random Forest (RF) has strong generalization ability and is not easy to overfit. In this paper, we improve the Bagging algorithm and simple voting method of RF. A W-RF algorithm based on adaptive Bagging and weighted voting is proposed to improve the classification performance of RF on imbalanced datasets. Adaptive Bagging enables trees in… More >

  • Open Access

    ARTICLE

    A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification

    Adi Alhudhaif1,*, Ammar Saeed2, Talha Imran2, Muhammad Kamran3, Ahmed S. Alghamdi3, Ahmed O. Aseeri1, Shtwai Alsubai1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 223-235, 2022, DOI:10.32604/csse.2022.018430
    Abstract Image classification is a core field in the research area of image processing and computer vision in which vehicle classification is a critical domain. The purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security, traffic analysis, and self-driving and autonomous vehicles. The recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional, and handcrafted means of solving image analysis problems. In this paper, a combination of pre-trained CNN GoogleNet and a… More >

  • Open Access

    ARTICLE

    Stock-Price Forecasting Based on XGBoost and LSTM

    Pham Hoang Vuong1, Trinh Tan Dat1, Tieu Khoi Mai1, Pham Hoang Uyen2, Pham The Bao1,*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 237-246, 2022, DOI:10.32604/csse.2022.017685
    (This article belongs to this Special Issue: Data Analytics in Industry 4.0)
    Abstract Using time-series data analysis for stock-price forecasting (SPF) is complex and challenging because many factors can influence stock prices (e.g., inflation, seasonality, economic policy, societal behaviors). Such factors can be analyzed over time for SPF. Machine learning and deep learning have been shown to obtain better forecasts of stock prices than traditional approaches. This study, therefore, proposed a method to enhance the performance of an SPF system based on advanced machine learning and deep learning approaches. First, we applied extreme gradient boosting as a feature-selection technique to extract important features from high-dimensional time-series data and remove redundant features. Then, we… More >

  • Open Access

    ARTICLE

    Vertex-Edge Degree Based Indices of Honey Comb Derived Network

    Muhammad Ibrahim1,*, Sadia Husain2, Nida Zahra1, Ali Ahmad2
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 247-258, 2022, DOI:10.32604/csse.2022.018227
    Abstract Chemical graph theory is a branch of mathematics which combines graph theory and chemistry. Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks. It pulled the research community due to its applications in theoretical and organic chemistry since 1960. Additionally, it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved. The structure of an interconnection network can be represented by a graph. In the network, vertices represent the processor nodes and edges represent the links between the processor nodes. Graph invariants play… More >

  • Open Access

    ARTICLE

    Smart Mina: LoRaWAN Technology for Smart Fire Detection Application for Hajj Pilgrimage

    Mohammad Al Mojamed*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 259-272, 2022, DOI:10.32604/csse.2022.018458
    Abstract The Long-Range Wide Area Network (LoRaWAN) is one of the used communication systems that serve and enables the deployment of the Internet of Things (IoT), which occasionally transmit small size data. As part of the Low Power Wide Area Network (LPWAN), LoRaWAN is characterized by its ability for low power consumption. In addition, it is built to provide more extended coverage and higher capacity with minimum cost. In this paper, we investigate the feasibility and scalability of LoRaWAN for the Mina area using a realistic network model. Mina, known as the world’s largest tent city, is a valley located in… More >

  • Open Access

    ARTICLE

    Timing Error Aware Register Allocation in TS

    Sheng Xiao1,2,*, Jing He3, Xi Yang4, Heng Zhou1, Yujie Yuan1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 273-286, 2022, DOI:10.32604/csse.2022.019106
    Abstract Timing speculative (TS) architecture is promising for improving the energy efficiency of microprocessors. Error recovery units, designed for tolerating occasional timing errors, have been used to support a wider range of voltage scaling, therefore to achieve a better energy efficiency. More specifically, the timing error rate, influenced mainly by data forwarding, is the bottleneck for voltage down-scaling in TS processors. In this paper, a new Timing Error Aware Register Allocation method is proposed. First, we designed the Dependency aware Interference Graph (DIG) construction to get the information of Read after Write (RAW) in programs. To build the construction, we get… More >

  • Open Access

    ARTICLE

    Efficient Process Monitoring Under General Weibull Distribution

    Saman Hanif Shahbaz, Muhammad Qaiser Shahbaz*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 287-297, 2022, DOI:10.32604/csse.2022.018219
    (This article belongs to this Special Issue: Data Analytics in Industry 4.0)
    Abstract Product testing is a key ingredient in maintaining the quality of a production process. The production process is considered an efficient process if it is capable of quick identification of faulty products. The items produced by any production process are usually packed and acceptance or rejection of the pack depends upon its conformity to some specified quality level. Generally, the specified quality level is based upon the number of defective items found in the inspected number of items. Such decisions are based upon some rules and usually acceptance of the pack is based upon a fewer number of defective items… More >

  • Open Access

    ARTICLE

    An Automated Brain Image Analysis System for Brain Cancer using Shearlets

    R. Muthaiyan1,*, Dr M. Malleswaran2
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 299-312, 2022, DOI:10.32604/csse.2022.018034
    Abstract In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification of MRI images into normal or low grade or high grade plays a vital role for the early diagnosis. The Non-Subsampled Shearlet Transform (NSST) that captures more visual information than conventional wavelet transforms is employed for feature extraction. As the feature space of NSST is very high, a statistical t-test is applied to select the dominant directional sub-bands at each level of NSST decomposition based on sub-band energies. A combination of features that includes Gray Level… More >

  • Open Access

    ARTICLE

    Ensemble Classifier Technique to Predict Gestational Diabetes Mellitus (GDM)

    A. Sumathi*, S. Meganathan
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 313-325, 2022, DOI:10.32604/csse.2022.017484
    Abstract Gestational Diabetes Mellitus (GDM) is an illness that represents a certain degree of glucose intolerance with onset or first recognition during pregnancy. In the past few decades, numerous investigations were conducted upon early identification of GDM. Machine Learning (ML) methods are found to be efficient prediction techniques with significant advantage over statistical models. In this view, the current research paper presents an ensemble of ML-based GDM prediction and classification models. The presented model involves three steps such as preprocessing, classification, and ensemble voting process. At first, the input medical data is preprocessed in four levels namely, format conversion, class labeling,… More >

  • Open Access

    REVIEW

    Ensemble Learning Models for Classification and Selection of Web Services: A Review

    Muhammad Hasnain1, Imran Ghani2, Seung Ryul Jeong3,*, Aitizaz Ali1
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 327-339, 2022, DOI:10.32604/csse.2022.018300
    Abstract This paper presents a review of the ensemble learning models proposed for web services classification, selection, and composition. Web service is an evolutionary research area, and ensemble learning has become a hot spot to assess web services’ earlier mentioned aspects. The proposed research aims to review the state of art approaches performed on the interesting web services area. The literature on the research topic is examined using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) as a research method. The study reveals an increasing trend of using ensemble learning in the chosen papers within the last ten years.… More >

  • Open Access

    ARTICLE

    Vibration-Based Pattern Password Approach for Visually Impaired People

    Suliman A. Alsuhibany*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 341-356, 2022, DOI:10.32604/csse.2022.018563
    Abstract The pattern password method is amongst the most attractive authentication methods and involves drawing a pattern; this is seen as easier than typing a password. However, since people with visual impairments have been increasing their usage of smart devices, this method is inaccessible for them as it requires them to select points on the touch screen. Therefore, this paper exploits the haptic technology by introducing a vibration-based pattern password approach in which the vibration feedback plays an important role. This approach allows visually impaired people to use a pattern password through two developed vibration feedback: pulses, which are counted by… More >

  • Open Access

    ARTICLE

    Empirically Modeling Enterprise Architecture Using ArchiMate

    Qiang Zhi1,*, Zhengshu Zhou2,3
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 357-374, 2022, DOI:10.32604/csse.2022.018759
    Abstract Enterprise Architecture (EA) has evolved based on the practice of information systems architecture design and implementation. EA is a rigorous description of a structure, and the objectives of EA modeling not only include clarifying corporate strategies, visualizing business processes, and modeling information systems to manage resources but also include improving organizational structures, adjusting information strategies, and creating new business value. Therefore, EA models cover a wide scope that includes both IT and business architectures. Typically, EA modeling is the initial and most important analysis step for researchers, architects, and developers. ArchiMate is the dominant modeling language for EA and it… More >

  • Open Access

    ARTICLE

    An Optimized CNN Model Architecture for Detecting Coronavirus (COVID-19) with X-Ray Images

    Anas Basalamah1, Shadikur Rahman2,*
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 375-388, 2022, DOI:10.32604/csse.2022.016949
    Abstract This paper demonstrates empirical research on using convolutional neural networks (CNN) of deep learning techniques to classify X-rays of COVID-19 patients versus normal patients by feature extraction. Feature extraction is one of the most significant phases for classifying medical X-rays radiography that requires inclusive domain knowledge. In this study, CNN architectures such as VGG-16, VGG-19, RestNet50, RestNet18 are compared, and an optimized model for feature extraction in X-ray images from various domains involving several classes is proposed. An X-ray radiography classifier with TensorFlow GPU is created executing CNN architectures and our proposed optimized model for classifying COVID-19 (Negative or Positive).… More >

  • Open Access

    ARTICLE

    Implementing Effective Learning with Ubiquitous Learning Technology During Coronavirus Pandemic

    Hosam F. El-Sofany1,2,*, Samir A. El-Seoud3
    Computer Systems Science and Engineering, Vol.40, No.1, pp. 389-404, 2022, DOI:10.32604/csse.2022.018619
    Abstract Ubiquitous computing supports U-learning to develop and implement a new educational environment that provides effective and interactive learning to students wherever they are. This study aims to present a qualitative evaluation for using U-learning instead of traditional education to avoid the spread of the Coronavirus pandemic. The authors introduce a UTAUT (Unified Theory of Acceptance and Use of Technology) model to assess the capability of the given factors that are expected to affect the learners’ intention and behavior for accepting the U-learning technology for full E-learning. The research study shows a promising impact on the use of U-learning apps for… More >

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