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.

  • Contrast Enhancement Based Image Detection Using Edge Preserved Key Pixel Point Filtering
  • Abstract In existing methods for segmented images, either edge point extraction or preservation of edges, compromising contrast images is so sensitive to noise. The Degeneration Threshold Image Detection (DTID) framework has been proposed to improve the contrast of edge filtered images. Initially, DTID uses a Rapid Bilateral Filtering process for filtering edges of contrast images. This filter decomposes input images into base layers in the DTID framework. With minimal filtering time, Rapid Bilateral Filtering handles high dynamic contrast images for smoothening edge preservation. In the DTID framework, Rapid Bilateral Filtering with Shift-Invariant Base Pass Domain Filter is insensitive to noise. This… More
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  • Modeling Rogowski Coils for Monitoring Surge Arrester Discharge Currents
  • Abstract Rogowski coils (RCs) are widely used to measure power or high frequency currents based on their design. In this paper, two types of RCs that are circular (traditional) and cylindrical shapes wound using wire covered by varnish are constructed. This construction is carried out to be suitable for monitoring the discharge current of the surge arrester installed in the distribution system. Concerning high frequency RC modeling for both types considering transfer function is introduced. Self-integrating for both types is attained. Therefore, the experimental tests using function generator for both coils are carried out to identify the parameters of the transfer… More
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  • SOINN-Based Abnormal Trajectory Detection for Efficient Video Condensation
  • Abstract With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the… More
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  • Evaluation of Deep Learning Models for Person Authentication Based on Touch Gesture
  • Abstract Touch gesture biometrics authentication system is the study of user's touching behavior on his touch device to identify him. The features traditionally used in touch gesture authentication systems are extracted using hand-crafted feature extraction approach. In this work, we investigate the ability of Deep Learning (DL) to automatically discover useful features of touch gesture and use them to authenticate the user. Four different models are investigated Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN) combined with LSTM (CNN-LSTM), and CNN combined with GRU(CNN-GRU). In addition, different regularization techniques are investigated such as Activity Regularizer, Batch Normalization… More
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  • PAPR Reduction Using Advanced Partial Transmission Scheme for 5G Waveforms
  • Abstract The implementation of Peak Average to Power Ratio (PAPR) reduction technologies will play an important role in the regularization of Fifth Generation (5G) radio communication. PAPR reduction in the advanced waveform will be the key part of designing a 5G network for different applications. This work introduces the simulation of an Advanced Partial Transmission Sequence (A-PTS) reduction techniques for Orthogonal Frequency Division Multiplexing (OFDM) and Filter Bank Multi-Carrier (FBMC) transmission schemes. In the projected A-PTS, the FBMC signals are mapped into the number of sub-blocks and Inverse Fast Fourier transform (IFFT) is performed to estimate the high peak power in… More
  •   Views:138       Downloads:92        Download PDF
  • Inter-Purchase Time Prediction Based on Deep Learning
  • Abstract Inter-purchase time is a critical factor for predicting customer churn. Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points, operation issues, as well as customer expectations to proactively reduce reasons for churn. Although remarkable progress has been made, classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-, medium-, and long-term data are likely to interfere with each other sequentially. Different from literature, this study proposed a hybrid inter-purchase time prediction model for customers of on-line retailers. Moreover, the analysis… More
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  • Diabetic Retinopathy Diagnosis Using ResNet with Fuzzy Rough C-Means Clustering
  • Abstract

    Diabetic Retinopathy (DR) is a vision disease due to the long-term prevalence of Diabetes Mellitus. It affects the retina of the eye and causes severe damage to the vision. If not treated on time it may lead to permanent vision loss in diabetic patients. Today’s development in science has no medication to cure Diabetic Retinopathy. However, if diagnosed at an early stage it can be controlled and permanent vision loss can be avoided. Compared to the diabetic population, experts to diagnose Diabetic Retinopathy are very less in particular to local areas. Hence an automatic computer-aided diagnosis for DR detection is… More

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  • Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks
  • Abstract Cognitive Radio Networks (CRN) are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems. CRN is a promising alternative approach that allows spectrum sharing in many applications. The licensed users considered Primary Users (PU) and unlicensed users as Secondary Users (SU). Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service (QoS). Irrespective of using different optimization techniques, the same methodology is to be updated for the task. So that, learning and optimization go hand in hand. It ensures the security in CRN, risk factors in… More
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  • Efficient User Pairing for Performance Enhancement of Downlink NOMA Systems
  • Abstract In this paper, the resource allocation problem for user pairing (UP) in downlink non-orthogonal multiple access (NOMA) systems is investigated. NOMA allows the use of one subcarrier for more than one user at the same time, thus increases the total capacity of the wireless communication system. However, users pairing is a challenging task in the NOMA systems, because a good channel quality subcarrier should be selected and allocated for the user to enhance the performance of NOMA systems. The proposed UP algorithm aims to enhance the sum rate of the paired users per subcarrier and consequently enhance the total sum… More
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  • Industrial Centric Node Localization and Pollution Prediction Using Hybrid Swarm Techniques
  • Abstract Major fields such as military applications, medical fields, weather forecasting, and environmental applications use wireless sensor networks for major computing processes. Sensors play a vital role in emerging technologies of the 20th century. Localization of sensors in needed locations is a very serious problem. The environment is home to every living being in the world. The growth of industries after the industrial revolution increased pollution across the environment. Owing to recent uncontrolled growth and development, sensors to measure pollution levels across industries and surroundings are needed. An interesting and challenging task is choosing the place to fit the sensors. Many… More
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  • Decision Tree Based Key Management for Secure Group Communication
  • Abstract Group communication is widely used by most of the emerging network applications like telecommunication, video conferencing, simulation applications, distributed and other interactive systems. Secured group communication plays a vital role in case of providing the integrity, authenticity, confidentiality, and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the group. In secure group communications, the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service, particularly in the large groups with highly active… More
  •   Views:106       Downloads:70        Download PDF
  • Improved Key Agreement Based Kerberos Protocol for M-Health Security
  • Abstract The development of wireless sensor network with Internet of Things (IoT) predicts various applications in the field of healthcare and cloud computing. This can give promising results on mobile health care (M-health) and Telecare medicine information systems. M-health system on cloud Internet of Things (IoT) through wireless sensor network (WSN) becomes the rising research for the need of modern society. Sensor devices attached to the patients’ body which is connected to the mobile device can ease the medical services. Security is the key connect for optimal performance of the m-health system that share the data of patients in wireless networks… More
  •   Views:171       Downloads:69        Download PDF
  • The Double Edge Sword Based Distributed Executor Service
  • Abstract Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate… More
  •   Views:86       Downloads:62        Download PDF
  • User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains
  • Abstract Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner. The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation (RMI). The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user. Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service. To improve the performance in data security, the block chains… More
  •   Views:95       Downloads:89        Download PDF
  • Design of Precise Multiplier Using Inexact Compressor for Digital Signal Processing
  • Abstract In the recent years, error recovery circuits in optimized data path units are adopted with approximate computing methodology. In this paper the novel multipliers have effective utilization in the newly proposed two different 4:2 approximate compressors that generate Error free Sum (ES) and Error free Carry (EC). Proposed ES and Proposed EC in 4:2 compressors are used for performing Partial Product (PP) compression. The structural arrangement utilizes Dadda structure based PP. Due to the regularity of PP arrangement Dadda multiplier is chosen for compressor implementation that favors easy standard cell ASIC design. In this, the proposed compression idealogy are more… More
  •   Views:99       Downloads:73        Download PDF
  • Predicting Mobile Cross-Platform Adaptation Using a Hybrid Sem–ANN Approach
  • Abstract Owing to constant changes in user needs, new technologies have been introduced to keep pace by building sustainable applications. Researchers and practitioners are keen to understand the factors that create an attractive user interface. Although the use of cross-platform applications and services is increasing, limited research has examined and evaluated cross-platforms for developing mobile applications for different operating systems. This study evaluates cross-platform features, identifying the main factors that help to create an attractive user adaptation when building sustainable applications for both Android and iOS. Flutter and React Native were selected so end-users could test their features using the cross-platform… More
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  • Solving the Task Starvation and Resources Problem Using Optimized SMPIA in Cloud
  • Abstract In this study, a new feature is added to the smart message passing interface (SMPI) approach (SMPIA) based on the prioritization method, which can completely eliminate the task starvation and lack of sufficient resources problems through prioritizing the tasks. The proposed approach is based on prioritizing the tasks and the urgency of implementation. Tasks are prioritized based on execution time, workload, the task with a more sensitive priority is executed earlier by the free source. The idea of demand-bound functions (DBFs) was extended to the SMPIA setting based on partitions and caps. For each task, two DBFs are constructed, DBFLO and… More
  •   Views:93       Downloads:83        Download PDF
  • Modelling of the Slope Solute Loss Based on Fuzzy Neural Network Model
  • Abstract In regards to soil macropores, the solute loss carried by overland flow is a very complex process. In this study, a fuzzy neural network (FNN) model was used to analyze the solute loss on slopes, taking into account the soil macropores. An artificial rainfall simulation experiment was conducted in indoor experimental tanks, and the verification of the model was based on the results. The characteristic scale of the macropores, the rainfall intensity and duration, the slope and the adsorption coefficient of ions, were chosen as the input variables to the Sugeno FNN model. The cumulative solute loss quantity on the… More
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  • Computer Oriented Numerical Scheme for Solving Engineering Problems
  • Abstract In this study, we construct a family of single root finding method of optimal order four and then generalize this family for estimating of all roots of non-linear equation simultaneously. Convergence analysis proves that the local order of convergence is four in case of single root finding iterative method and six for simultaneous determination of all roots of non-linear equation. Some non-linear equations are taken from physics, chemistry and engineering to present the performance and efficiency of the newly constructed method. Some real world applications are taken from fluid mechanics, i.e., fluid permeability in biogels and biomedical engineering which includes… More
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  • Secure and Anonymous Three-Factor Authentication Scheme for Remote Healthcare Systems
  • Abstract Wireless medical sensor networks (WMSNs) play a significant role in increasing the availability of remote healthcare systems. The vital and physiological data of the patient can be collected using the WMSN via sensor nodes that are placed on his/her body and then transmitted remotely to a healthcare professional for proper diagnosis. The protection of the patient’s privacy and their data from unauthorized access is a major concern in such systems. Therefore, an authentication scheme with a high level of security is one of the most effective mechanisms by which to address these security concerns. Many authentication schemes for remote patient… More
  •   Views:133       Downloads:114        Download PDF
  • Roosters Algorithm: A Novel Nature-Inspired Optimization Algorithm
  • Abstract Some species of females, e.g., chicken, bird, fish etc., might mate with more than one males. In the mating of these polygamous creatures, there is competition between males as well as among their offspring. Thus, male reproductive success depends on both male competition and sperm rivalry. Inspired by this type of sexual life of roosters with chickens, a novel nature-inspired optimization algorithm called Roosters Algorithm (RA) is proposed. The algorithm was modelled and implemented based on the sexual behavior of roosters. 13 well-known benchmark optimization functions and 10 IEEE CEC 2018 test functions are utilized to compare the performance of… More
  •   Views:128       Downloads:117        Download PDF
  • Optimal Algorithms for Load Balancing in Optical Burst Switching Networks
  • Abstract Data packet drop can happen in Optical Burst-Switched (OBS) when two data bursts are competing on the same wavelength. Recently, many techniques have been developed to solve this problem but they do not consider the congestion. Also, it is necessary to balance the load system in the OBS network. The Ant Colony Optimization (ACO) technique can be applied to determine the straight and the safest route. However, the ACO technique raises both power utilization as well as the execution time. In this study, Cuckoo Search (CS) and ACO methods based approach is proposed to avoid the congestion and load balancing… More
  •   Views:94       Downloads:63        Download PDF
  • Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection
  • Abstract Knowledge Management (KM) has become a dynamic concept for inquiry in research. The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline, several KM frameworks have been designed to serve this purpose. This research aims to propose a Collaborative Knowledge Management (CKM) Framework that bridges gaps and overcomes weaknesses in existing frameworks. The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan. A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF… More
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  • An Improved Method for Extractive Based Opinion Summarization Using Opinion Mining
  • Abstract Opinion summarization recapitulates the opinions about a common topic automatically. The primary motive of summarization is to preserve the properties of the text and is shortened in a way with no loss in the semantics of the text. The need of automatic summarization efficiently resulted in increased interest among communities of Natural Language Processing and Text Mining. This paper emphasis on building an extractive summarization system combining the features of principal component analysis for dimensionality reduction and bidirectional Recurrent Neural Networks and Long Short-Term Memory (RNN-LSTM) deep learning model for short and exact synopsis using seq2seq model. It presents a… More
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  • Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems
  • Abstract The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as communication channel, computation unit, robot… More
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  • Modified Visual Geometric Group Architecture for MRI Brain Image Classification
  • Abstract The advancement of automated medical diagnosis in biomedical engineering has become an important area of research. Image classification is one of the diagnostic approaches that do not require segmentation which can draw quicker inferences. The proposed non-invasive diagnostic support system in this study is considered as an image classification system where the given brain image is classified as normal or abnormal. The ability of deep learning allows a single model for feature extraction as well as classification whereas the rational models require separate models. One of the best models for image localization and classification is the Visual Geometric Group (VGG)… More
  •   Views:107       Downloads:78        Download PDF
  • CNN Based Automated Weed Detection System Using UAV Imagery
  • Abstract The problem of weeds in crops is a natural problem for farmers. Machine Learning (ML), Deep Learning (DL), and Unmanned Aerial Vehicles (UAV) are among the advanced technologies that should be used in order to reduce the use of pesticides while also protecting the environment and ensuring the safety of crops. Deep Learning-based crop and weed identification systems have the potential to save money while also reducing environmental stress. The accuracy of ML/DL models has been proven to be restricted in the past due to a variety of factors, including the selection of an efficient wavelength, spatial resolution, and the… More
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