Computer Systems Science and Engineering

About the Journal

The Computer Systems Science and Engineering journal is devoted to the publication of high quality papers on theoretical developments in computer systems science, and their applications in computer systems engineering. Original research papers, state-of-the-art reviews and technical notes are invited for publication. Computer Systems Science and Engineering is published monthly by Tech Science Press.

Indexing and Abstracting

Science Citation Index (Web of Science): 2020 Impact Factor 1.486; Scopus Cite Score (Impact per Publication 2020): 1.4; SNIP (Source Normalized Impact per Paper 2020): 0.382; ACM Digital Library;

Previously published by CRL Publishing (http://crl-publishing.co.uk/), Computer Systems Science and Engineering starts to be published by Tech Science Press from the fifth issue of 2020 and supports Open Access Policy.

  • Hybrid Active Contour Mammographic Mass Segmentation and Classification
  • Abstract This research implements a novel segmentation of mammographic mass. Three methods are proposed, namely, segmentation of mass based on iterative active contour, automatic region growing, and fully automatic mask selection-based active contour techniques. In the first method, iterative threshold is performed for manual cropped preprocessed image, and active contour is applied thereafter. To overcome manual cropping in the second method, an automatic seed selection followed by region growing is performed. Given that the result is only a few images owing to over segmentation, the third method uses a fully automatic active contour. Results of the segmentation techniques are compared with… More
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  • On Vertex-Edge-Degree Topological Descriptors for Certain Crystal Networks
  • Abstract Due to the combinatorial nature of graphs they are used easily in pure sciences and social sciences. The dynamical arrangement of vertices and their associated edges make them flexible (like liquid) to attain the shape of any physical structure or phenomenon easily. In the field of ICT they are used to reflect distributed component and communication among them. Mathematical chemistry is another interesting domain of applied mathematics that endeavors to display the structure of compounds that are formed in result of chemical reactions. This area attracts the researchers due to its applications in theoretical and organic chemistry. It also inspires… More
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  • Network Traffic Prediction Using Radial Kernelized-Tversky Indexes-Based Multilayer Classifier
  • Abstract Accurate cellular network traffic prediction is a crucial task to access Internet services for various devices at any time. With the use of mobile devices, communication services generate numerous data for every moment. Given the increasing dense population of data, traffic learning and prediction are the main components to substantially enhance the effectiveness of demand-aware resource allocation. A novel deep learning technique called radial kernelized LSTM-based connectionist Tversky multilayer deep structure learning (RKLSTM-CTMDSL) model is introduced for traffic prediction with superior accuracy and minimal time consumption. The RKLSTM-CTMDSL model performs attribute selection and classification processes for cellular traffic prediction. In… More
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  • IoT Wireless Intrusion Detection and Network Traffic Analysis
  • Abstract Enhancement in wireless networks had given users the ability to use the Internet without a physical connection to the router. Almost every Internet of Things (IoT) devices such as smartphones, drones, and cameras use wireless technology (Infrared, Bluetooth, IrDA, IEEE 802.11, etc.) to establish multiple inter-device connections simultaneously. With the flexibility of the wireless network, one can set up numerous ad-hoc networks on-demand, connecting hundreds to thousands of users, increasing productivity and profitability significantly. However, the number of network attacks in wireless networks that exploit such flexibilities in setting and tearing down networks has become very alarming. Perpetrators can launch… More
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  • Decision Making on Fuzzy Soft Simply* Continuous of Fuzzy Soft Multi-Function
  • Abstract Real world applications are dealing now with a huge amount of data, especially in the area of high dimensional features. In this article, we depict the simply*upper, the simply*lower continuous, we get several characteristics and other properties with respect to upper and lower simply*-continuous soft multi-functions. We also investigate the relationship between soft-continuous, simply*continuous multifunction. We also implement fuzzy soft multifunction between fuzzy soft topological spaces which is Akdag’s generation of the notion. We are introducing a new class of soft open sets, namely soft simply*open set deduce from soft topology, and we are using it to implement the new… More
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  • A Coordination-Based Algorithm for Dedicated Destination Vehicle Routing in B2B E-Commerce
  • Abstract This paper proposes a solution to the open vehicle routing problem with time windows (OVRPTW) considering third-party logistics (3PL). For the typical OVRPTW problem, most researchers consider time windows, capacity, routing limitations, vehicle destination, etc. Most researchers who previously investigated this problem assumed the vehicle would not return to the depot, but did not consider its final destination. However, by considering 3PL in the B2B e-commerce, the vehicle is required back to the nearest 3PL location with available space. This paper formulates the problem as a mixed integer linear programming (MILP) model with the objective of minimizing the total travel… More
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  • Tracking Dengue on Twitter Using Hybrid Filtration-Polarity and Apache Flume
  • Abstract The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights… More
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  • VacChain: A Blockchain-Based EMR System to Manage Child Vaccination Records
  • Abstract The digitalization of healthcare-related information service systems has become a trend across the world. However, several crucial services are still provided manually due to a lack of trust in digital solutions. One such service is keeping records of children’s vaccination, which still relies on a paper-based file system in most parts of the world. This approach causes serious data integrity problems. Recently, healthcare has become a potential application area of the blockchain, as it can preserve and protect highly sensitive private medical records while sharing these records in a decentralized manner without losing personal ownership. Therefore, we propose a new… More
  •   Views:46       Downloads:31        Download PDF
  • Prediction Model for Coronavirus Pandemic Using Deep Learning
  • Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may aid healthcare practitioners in making… More
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  • Integrated Approach to Detect Cyberbullying Text: Mobile Device Forensics Data
  • Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning (DL) algorithms to exploit suspicious… More
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  • Mining Syndrome Differentiating Principles from Traditional Chinese Medicine Clinical Data
  • Abstract Syndrome differentiation-based treatment is one of the key characteristics of Traditional Chinese Medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity and vagueness. Analyzing syndrome principles from historical records of TCM using data mining (DM) technology has been of high interest in recent years. Nevertheless, in most relevant studies, existing DM algorithms have been simply developed for TCM mining, while the combination of TCM theories or its characteristics with DM algorithms has rarely been reported. This paper presents a novel Symptom-Syndrome Topic Model (SSTM), which is a supervised probabilistic topic model with three-tier… More
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  • Identity Governance Framework for Privileged Users
  • Abstract Information technology companies have grown in size and recognized the need to protect their valuable assets. As a result, each IT application has its authentication mechanism, and an employee needs a username and password. As the number of applications increased, as a result, it became increasingly complex to manage all identities like the number of usernames and passwords of an employee. All identities had to be retrieved by users. Both the identities and the access rights associated with those identities had to be protected by an administrator. Management couldn’t even capture such access rights because they couldn’t verify things like… More
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  • I-Quiz: An Intelligent Assessment Tool for Non-Verbal Behaviour Detection
  • Abstract Electronic learning (e-learning) has become one of the widely used modes of pedagogy in higher education today due to the convenience and flexibility offered in comparison to traditional learning activities. Advancements in Information and Communication Technology have eased learner connectivity online and enabled access to an extensive range of learning materials on the World Wide Web. Post covid-19 pandemic, online learning has become the most essential and inevitable medium of learning in primary, secondary and higher education. In recent times, Massive Open Online Courses (MOOCs) have transformed the current education strategy by offering a technology-rich and flexible form of online… More
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  • Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations
  • Abstract Interactive learning tools can facilitate the learning process and increase student engagement, especially tools such as computer programs that are designed for human-computer interaction. Thus, this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback, visibility, affordance, consistency, and constraints. It also compares these methods by the number of iterations and time required to display the result. This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods. The tool is implemented using the MATLAB app and… More
  •   Views:134       Downloads:83        Download PDF
  • An Adaptive Fuzzy Control Model for Multi-Joint Manipulators
  • Abstract Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability… More
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  • Heuristic Scheduling of Job Orders in a Build-to-Order Manufacturing System
  • Abstract With the continuous development of technology, traditional manual work has been becoming more and more automated. Most large or medium-sized companies have applied Enterprise Resource Planning (ERP) software into their business and production activities. However, since many small firms cannot afford ERP because of its expensive cost, they often still employ manual work for the same tasks this software resolves, especially for scheduling. This paper aims to provide a possible solution for small businesses to try automated scheduling and discover whether it can help much. There are two main ways to make this determination: a mathematical model and a heuristic… More
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  • Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware
  • Abstract Wireless sensor network (WSN) is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings. The routing of the network is a challenging task. The routing of WSN is classified as proactive, reactive, and hybrid. Adhoc on-demand distance vector (AODV) routing is an example of reactive routing based on the demand route formations among different nodes in the network. The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language (VHDL) programming in Xilinx integrated synthesis environment (ISE) 14.7 software. The performance of the chip… More
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  • A Tradeoff Between Accuracy and Speed for K-Means Seed Determination
  • Abstract With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected… More
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  • Adaptive Sliding Mode Control Method for Onboard Supercapacitors System
  • Abstract Urban rail trains have undergone rapid development in recent years due to their punctuality, high capacity and energy efficiency. Urban trains require frequent start/stop operations and are, therefore, prone to high energy losses. As trains have high inertia, the energy that can be recovered from braking comes in short bursts of high power. To effectively recover such braking energy, an onboard supercapacitor system based on a radial basis function neural network-based sliding mode control system is proposed, which provides robust adaptive performance. The supercapacitor energy storage system is connected to a bidirectional DC/DC converter to provide traction energy or absorb… More
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  • Solvability of the Nonlocal Inverse Parabolic Problem and Numerical Results
  • Abstract In this paper, we consider the unique solvability of the inverse problem of determining the right-hand side of a parabolic equation whose leading coefficient depends on time variable under nonlocal integral overdetermination condition. We obtain sufficient conditions for the unique solvability of the inverse problem. The existence and uniqueness of the solution of the inverse parabolic problem upon the data are established using the fixed point theorem. This inverse problem appears extensively in the modelling of various phenomena in engineering and physics. For example, seismology, medicine, fusion welding, continuous casting, metallurgy, aircraft, oil and gas production during drilling and operation… More
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  • Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences
  • Abstract With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The quality of learning can be… More
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  • Impact of Human Vulnerabilities on Cybersecurity
  • Abstract Today, security is a major challenge linked with computer network companies that cannot defend against cyber-attacks. Numerous vulnerable factors increase security risks and cyber-attacks, including viruses, the internet, communications, and hackers. Internets of Things (IoT) devices are more effective, and the number of devices connected to the internet is constantly increasing, and governments and businesses are also using these technologies to perform business activities effectively. However, the increasing uses of technologies also increase risks, such as password attacks, social engineering, and phishing attacks. Humans play a major role in the field of cybersecurity. It is observed that more than 39%… More
  •   Views:195       Downloads:95        Download PDF
  • FPD Net: Feature Pyramid DehazeNet
  • Abstract We propose an end-to-end dehazing model based on deep learning (CNN network) and uses the dehazing model re-proposed by AOD-Net based on the atmospheric scattering model for dehazing. Compare to the previously proposed dehazing network, the dehazing model proposed in this paper make use of the FPN network structure in the field of target detection, and uses five feature maps of different sizes to better obtain features of different proportions and different sub-regions. A large amount of experimental data proves that the dehazing model proposed in this paper is superior to previous dehazing technologies in terms of PSNR, SSIM, and… More
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  • Miniaturized Novel UWB Band-Notch Textile Antenna for Body Area Networks
  • Abstract This paper presents the design and analysis of a miniaturized and novel wearable ultra-wideband (UWB) band-notch textile antenna for Body Area Networks (BANs). The major goal of building the antenna for wearable applications with band notch in X-band is to reject the downlink band (7.25 to 7.75 GHz) of satellite communication in the UWB frequency ranges of 3.1–10.6 GHz to keep away from interference. Computer Simulation Technology (CST) TM Microwave Studio, which is user-friendly and reliable, was used to model and simulate the antenna. The radiating element of the antenna is designed on Jeans’ textile substrate, which has a relative… More
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  • Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks
  • Abstract Internet of Things (IoT) devices work mainly in wireless mediums; requiring different Intrusion Detection System (IDS) kind of solutions to leverage 802.11 header information for intrusion detection. Wireless-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired networks. This survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods, IDS techniques, IDS placement strategies, and traffic data analysis techniques. This paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT specific intrusions. Specifically, the Knowledge… More
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  • A CPK-Based Identity Authentication Scheme for IoT
  • Abstract As the power Internet of Things (IoT) enters the security construction stage, the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and practicality. The existing public key infrastructure (PKI)-based security authentication scheme is currently difficult to apply in many terminals in IoT. Its key distribution and management costs are high, which hinders the development of power IoT security construction. Combined Public Key (CPK) technology uses a small number of seeds to generate unlimited public keys. It is very suitable for identity authentication in the power Internet of Things. In this paper, we… More
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  • Web Security: Emerging Threats and Defense
  • Abstract Web applications have become a widely accepted method to support the internet for the past decade. Since they have been successfully installed in the business activities and there is a requirement of advanced functionalities, the configuration is growing and becoming more complicated. The growing demand and complexity also make these web applications a preferred target for intruders on the internet. Even with the support of security specialists, they remain highly problematic for the complexity of penetration and code reviewing methods. It requires considering different testing patterns in both codes reviewing and penetration testing. As a result, the number of hacked… More
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