Home / Journals / CSSE / Vol.45, No.3, 2023
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    ARTICLE

    Tricube Weighted Linear Regression and Interquartile for Cloud Infrastructural Resource Optimization

    Neema George1,*, B. K. Anoop1, Vinodh P. Vijayan2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2281-2297, 2023, DOI:10.32604/csse.2023.028117
    Abstract Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application. When workload execution, accuracy, and cost are accurately stabilized in opposition to the best possible framework in real-time, efficiency is attained. In addition, every workload or application required for the framework is characteristic and these essentials change over time. But, the existing method was failed to ensure the high Quality of Service (QoS). In order to address this issue, a Tricube Weighted Linear Regression-based Inter Quartile (TWLR-IQ) for Cloud Infrastructural Resource Optimization is introduced. A Tricube Weighted Linear Regression… More >

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    ARTICLE

    Performance Analysis of Hybrid RR Algorithm for Anomaly Detection in Streaming Data

    L. Amudha1,*, R. PushpaLakshmi2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2299-2312, 2023, DOI:10.32604/csse.2023.031169
    Abstract Automated live video stream analytics has been extensively researched in recent times. Most of the traditional methods for video anomaly detection is supervised and use a single classifier to identify an anomaly in a frame. We propose a 3-stage ensemble-based unsupervised deep reinforcement algorithm with an underlying Long Short Term Memory (LSTM) based Recurrent Neural Network (RNN). In the first stage, an ensemble of LSTM-RNNs are deployed to generate the anomaly score. The second stage uses the least square method for optimal anomaly score generation. The third stage adopts award-based reinforcement learning to update the model. The proposed Hybrid Ensemble… More >

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    ARTICLE

    Software Defect Prediction Based Ensemble Approach

    J. Harikiran1,*, B. Sai Chandana1, B. Srinivasarao1, B. Raviteja2, Tatireddy Subba Reddy3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2313-2331, 2023, DOI:10.32604/csse.2023.029689
    Abstract Software systems have grown significantly and in complexity. As a result of these qualities, preventing software faults is extremely difficult. Software defect prediction (SDP) can assist developers in finding potential bugs and reducing maintenance costs. When it comes to lowering software costs and assuring software quality, SDP plays a critical role in software development. As a result, automatically forecasting the number of errors in software modules is important, and it may assist developers in allocating limited resources more efficiently. Several methods for detecting and addressing such flaws at a low cost have been offered. These approaches, on the other hand,… More >

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    ARTICLE

    Graph Ranked Clustering Based Biomedical Text Summarization Using Top k Similarity

    Supriya Gupta*, Aakanksha Sharaff, Naresh Kumar Nagwani
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2333-2349, 2023, DOI:10.32604/csse.2023.030385
    Abstract Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and effort. Evaluating and selecting the most informative sentences from biomedical articles is always challenging. This study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and information. The research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization model. The input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between them. The proposed framework utilizes the top… More >

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    ARTICLE

    Face Attribute Convolutional Neural Network System for Data Security with Improved Crypto Biometrics

    S. Aanjanadevi1,*, S. Aanjankumar2, K. R. Ramela3, V. Palanisamy4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2351-2362, 2023, DOI:10.32604/csse.2023.031893
    Abstract Due to the enormous usage of the internet for transmission of data over a network, security and authenticity become major risks. Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server. To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical (Face, fingerprint, Ear etc.) and behavioural (Gesture, Voice, tying etc.) by means of matching and verification process. In this work, biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to… More >

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    ARTICLE

    Authentication of WSN for Secured Medical Data Transmission Using Diffie Hellman Algorithm

    A. Jenice Prabhu1,*, D. Hevin Rajesh2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2363-2376, 2023, DOI:10.32604/csse.2023.028089
    Abstract The applications of wireless sensor network (WSN) exhibits a significant rise in recent days since it is enveloped with various advantageous benefits. In the medical field, the emergence of WSN has created marvelous changes in monitoring the health conditions of the patients and so it is attracted by doctors and physicians. WSN assists in providing health care services without any delay and so it plays predominant role in saving the life of human. The data of different persons, time, places and networks have been linked with certain devices, which are collectively known as Internet of Things (IOT); it is regarded… More >

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    ARTICLE

    Deep Forest-Based Fall Detection in Internet of Medical Things Environment

    Mohamed Esmail Karar1,2,*, Omar Reyad1,3, Hazem Ibrahim Shehata1,4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2377-2389, 2023, DOI:10.32604/csse.2023.032931
    Abstract This article introduces a new medical internet of things (IoT) framework for intelligent fall detection system of senior people based on our proposed deep forest model. The cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural networks. Moreover, the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated layer. The suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset, which is acquired from three-axis accelerometer in a smartwatch. It… More >

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    ARTICLE

    Method for Fault Diagnosis and Speed Control of PMSM

    Smarajit Ghosh*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2391-2404, 2023, DOI:10.32604/csse.2023.028931
    Abstract In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of permanent magnet synchronous motor. Both… More >

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    ARTICLE

    Complete Cototal Roman Domination Number of a Graph for User Preference Identification in Social Media

    J. Maria Regila Baby*, K. Uma Samundesvari
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2405-2415, 2023, DOI:10.32604/csse.2023.032240
    Abstract Many graph domination applications can be expanded to achieve complete cototal domination. If every node in a dominating set is regarded as a record server for a PC organization, then each PC affiliated with the organization has direct access to a document server. It is occasionally reasonable to believe that this gateway will remain available even if one of the scrape servers fails. Because every PC has direct access to at least two documents’ servers, a complete cototal dominating set provides the required adaptability to non-critical failure in such scenarios. In this paper, we presented a method for calculating a… More >

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    ARTICLE

    Human Stress Recognition by Correlating Vision and EEG Data

    S. Praveenkumar*, T. Karthick
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2417-2433, 2023, DOI:10.32604/csse.2023.032480
    Abstract Because stress has such a powerful impact on human health, we must be able to identify it automatically in our everyday lives. The human activity recognition (HAR) system use data from several kinds of sensors to try to recognize and evaluate human actions automatically recognize and evaluate human actions. Using the multimodal dataset DEAP (Database for Emotion Analysis using Physiological Signals), this paper presents deep learning (DL) technique for effectively detecting human stress. The combination of vision-based and sensor-based approaches for recognizing human stress will help us achieve the increased efficiency of current stress recognition systems and predict probable actions… More >

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    ARTICLE

    Spatio Temporal Tourism Tracking System Based on Adaptive Convolutional Neural Network

    L. Maria Michael Visuwasam1,*, D. Paul Raj2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2435-2446, 2023, DOI:10.32604/csse.2023.024742
    Abstract Technological developments create a lot of impacts in the tourism industry. Emerging big data technologies and programs generate opportunities to enhance the strategy and results for transport security. However, there is a difference between technological advances and their integration into the methods of tourism study. The rising popularity of Freycinet National Park led to a master plan that would not address cultural and environmental issues. This study addresses the gap by using a synthesized application (app) for demographic surveys and Global Navigation Satellite System (GNSS) technology to implement research processes. This article focuses on managing visitors within the famous Freycinet… More >

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    ARTICLE

    Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence

    Ahmed Zohair Ibrahim1,*, P. Prakash2, V. Sakthivel2, P. Prabu3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2447-2460, 2023, DOI:10.32604/csse.2023.030134
    Abstract In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brainfunction is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer’s disease, Schizophrenia and Parkinson’s diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks (DBN). Images are stored in… More >

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    ARTICLE

    A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

    Abdulaziz Alhubaishy1,*, Abdulmajeed Aljuhani2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2461-2481, 2023, DOI:10.32604/csse.2023.032217
    Abstract In a cloud environment, consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost. On the other hand, Cloud Service Providers (CSPs) seek to maximize their profits by attracting and serving more consumers based on their resource capabilities. The literature has discussed the problem by considering either consumers’ needs or CSPs’ capabilities. A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task scheduling in a more efficient… More >

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    ARTICLE

    3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

    K. Sreelakshmy1, Himanshu Gupta1, Om Prakash Verma1, Kapil Kumar2, Abdelhamied A. Ateya3, Naglaa F. Soliman4,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737
    Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general acceptability. To address this issue,… More >

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    ARTICLE

    Fusing Spatio-Temporal Contexts into DeepFM for Taxi Pick-Up Area Recommendation

    Yizhi Liu1,3, Rutian Qing1,3, Yijiang Zhao1,3,*, Xuesong Wang1,3, Zhuhua Liao1,3, Qinghua Li1,2, Buqing Cao1,3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2505-2519, 2023, DOI:10.32604/csse.2023.021615
    Abstract Short-term GPS data based taxi pick-up area recommendation can improve the efficiency and reduce the overheads. But how to alleviate sparsity and further enhance accuracy is still challenging. Addressing at these issues, we propose to fuse spatio-temporal contexts into deep factorization machine (STC_DeepFM) offline for pick-up area recommendation, and within the area to recommend pick-up points online using factorization machine (FM). Firstly, we divide the urban area into several grids with equal size. Spatio-temporal contexts are destilled from pick-up points or points-of-interest (POIs) belonged to the preceding grids. Secondly, the contexts are integrated into deep factorization machine (DeepFM) to mine… More >

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    ARTICLE

    Improved Multi-Path Routing for QoS on MANET

    M. Vargheese1,*, Surbhi Bhatia2, Shakila Basheer3, Pankaj Dadheech4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2521-2536, 2023, DOI:10.32604/csse.2023.031476
    Abstract A Mobile Ad hoc NETwork (MANET) is a self-configuring network that is not reliant on infrastructure. This paper introduces a new multipath routing method based on the Multi-Hop Routing (MHR) technique. MHR is the consecutive selection of suitable relay nodes to send information across nodes that are not within direct range of each other. Failing to ensure good MHR leads to several negative consequences, ultimately causing unsuccessful data transmission in a MANET. This research work consists of three portions. The first to attempt to propose an efficient MHR protocol is the design of Priority Based Dynamic Routing (PBDR) to adapt… More >

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    ARTICLE

    Development of Energy Management System for Micro Grid Operation

    S. Jayaprakash1,*, B. Gopi2, Murugananth Gopal Raj3, S. Sujith4, S. Deepa5, S. Swapna6
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2537-2551, 2023, DOI:10.32604/csse.2023.032038
    Abstract The introduction of several small and large-scale industries, malls, shopping complexes, and domestic applications has significantly increased energy consumption. The aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential buildings. The proposed micro-grid model includes four power generators: solar power, wind power, Electricity Board (EB) source, and a Diesel Generator (DG) set, with solar and wind power performing as major sources and the EB supply and DG set serving as backup sources. The core issue in direct current to alternate current conversion is harmonics distortion, a five-stage multilevel inverter is employed… More >

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    ARTICLE

    A Novel Framework for DDoS Attacks Detection Using Hybrid LSTM Techniques

    Anitha Thangasamy*, Bose Sundan, Logeswari Govindaraj
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2553-2567, 2023, DOI:10.32604/csse.2023.032078
    Abstract The recent development of cloud computing offers various services on demand for organization and individual users, such as storage, shared computing space, networking, etc. Although Cloud Computing provides various advantages for users, it remains vulnerable to many types of attacks that attract cyber criminals. Distributed Denial of Service (DDoS) is the most common type of attack on cloud computing. Consequently, Cloud computing professionals and security experts have focused on the growth of preventive processes towards DDoS attacks. Since DDoS attacks have become increasingly widespread, it becomes difficult for some DDoS attack methods based on individual network flow features to distinguish… More >

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    ARTICLE

    Automatic Optic Disc Detection in Retinal Images Using FKMT‒MOPDF

    Kittipol Wisaeng*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2569-2586, 2023, DOI:10.32604/csse.2023.033226
    Abstract In recent days, detecting Optic Disc (OD) in retinal images has been challenging and very important to the early diagnosis of eye diseases. The process of detecting the OD is challenging due to the diversity of color, intensity, brightness and shape of the OD. Moreover, the color similarities of the neighboring organs of the OD create difficulties during OD detection. In the proposed Fuzzy K‒Means Threshold (FKMT) and Morphological Operation with Pixel Density Feature (MOPDF), the input retinal images are coarsely segmented by fuzzy K‒means clustering and thresholding, in which the OD is classified from its neighboring organs with intensity… More >

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    ARTICLE

    CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

    Sayyed Mudassar Shah1, Tariq Hussain2, Babar Shah3, Farman Ali4, Khalid Zaman1, Kyung-Sup Kwak5,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2587-2602, 2023, DOI:10.32604/csse.2023.034489
    Abstract Underwater acoustic sensor networks (UWASNs) aim to find varied offshore ocean monitoring and exploration applications. In most of these applications, the network is composed of several sensor nodes deployed at different depths in the water. Sensor nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level; these nodes need multi-hop communication facilitated by a suitable routing scheme. In this research work, a Cluster-based Cooperative Energy Efficient Routing (CEER) mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH mechanisms. The optimal role of clustering and cooperation provides load balancing… More >

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    ARTICLE

    A Personalized Video Synopsis Framework for Spherical Surveillance Video

    S. Priyadharshini*, Ansuman Mahapatra
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2603-2616, 2023, DOI:10.32604/csse.2023.032506
    Abstract Video synopsis is an effective way to easily summarize long-recorded surveillance videos. The omnidirectional view allows the observer to select the desired fields of view (FoV) from the different FoV available for spherical surveillance video. By choosing to watch one portion, the observer misses out on the events occurring somewhere else in the spherical scene. This causes the observer to experience fear of missing out (FOMO). Hence, a novel personalized video synopsis approach for the generation of non-spherical videos has been introduced to address this issue. It also includes an action recognition module that makes it easy to display necessary… More >

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    ARTICLE

    Stable Computer Method for Solving Initial Value Problems with Engineering Applications

    Mudassir Shams1, Nasreen Kausar2, Ebru Ozbilge3,*, Alper Bulut3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2617-2633, 2023, DOI:10.32604/csse.2023.034370
    Abstract Engineering and applied mathematics disciplines that involve differential equations in general, and initial value problems in particular, include classical mechanics, thermodynamics, electromagnetism, and the general theory of relativity. A reliable, stable, efficient, and consistent numerical scheme is frequently required for modelling and simulation of a wide range of real-world problems using differential equations. In this study, the tangent slope is assumed to be the contra-harmonic mean, in which the arithmetic mean is used as a correction instead of Euler’s method to improve the efficiency of the improved Euler’s technique for solving ordinary differential equations with initial conditions. The stability, consistency,… More >

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    ARTICLE

    Logistic Regression with Elliptical Curve Cryptography to Establish Secure IoT

    J. R. Arunkumar1,*, S. Velmurugan2, Balarengadurai Chinnaiah3, G. Charulatha4, M. Ramkumar Prabhu4, A. Prabhu Chakkaravarthy5
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2635-2645, 2023, DOI:10.32604/csse.2023.031605
    Abstract Nowadays, Wireless Sensor Network (WSN) is a modern technology with a wide range of applications and greatly attractive benefits, for example, self-governing, low expenditure on execution and data communication, long-term function, and unsupervised access to the network. The Internet of Things (IoT) is an attractive, exciting paradigm. By applying communication technologies in sensors and supervising features, WSNs have initiated communication between the IoT devices. Though IoT offers access to the highest amount of information collected through WSNs, it leads to privacy management problems. Hence, this paper provides a Logistic Regression machine learning with the Elliptical Curve Cryptography technique (LRECC) to… More >

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    ARTICLE

    Particle Swarm Optimization for Solving Sine-Gordan Equation

    Geeta Arora1, Pinkey Chauhan2, Muhammad Imran Asjad3, Varun Joshi1, Homan Emadifar4, Fahd Jarad5,6,7,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2647-2658, 2023, DOI:10.32604/csse.2023.032404
    Abstract The term ‘optimization’ refers to the process of maximizing the beneficial attributes of a mathematical function or system while minimizing the unfavorable ones. The majority of real-world situations can be modelled as an optimization problem. The complex nature of models restricts traditional optimization techniques to obtain a global optimal solution and paves the path for global optimization methods. Particle Swarm Optimization is a potential global optimization technique that has been widely used to address problems in a variety of fields. The idea of this research is to use exponential basis functions and the particle swarm optimization technique to find a… More >

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    ARTICLE

    Performance Measurement of Energy Efficient and Highly Scalable Hybrid Adder

    B. Annapoorani*, P. Marikkannu
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2659-2672, 2023, DOI:10.32604/csse.2023.025075
    Abstract The adders are the vital arithmetic operation for any arithmetic operations like multiplication, subtraction, and division. Binary number additions are performed by the digital circuit known as the adder. In VLSI (Very Large Scale Integration), the full adder is a basic component as it plays a major role in designing the integrated circuits applications. To minimize the power, various adder designs are implemented and each implemented designs undergo defined drawbacks. The designed adder requires high power when the driving capability is perfect and requires low power when the delay occurred is more. To overcome such issues and to obtain better… More >

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    ARTICLE

    Secured Health Data Transmission Using Lagrange Interpolation and Artificial Neural Network

    S. Vidhya1,*, V. Kalaivani2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2673-2692, 2023, DOI:10.32604/csse.2023.027724
    Abstract In recent decades, the cloud computing contributes a prominent role in health care sector as the patient health records are transferred and collected using cloud computing services. The doctors have switched to cloud computing as it provides multiple advantageous measures including wide storage space and easy availability without any limitations. This necessitates the medical field to be redesigned by cloud technology to preserve information about patient’s critical diseases, electrocardiogram (ECG) reports, and payment details. The proposed work utilizes a hybrid cloud pattern to share Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) resources over the private and public cloud. The stored… More >

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    ARTICLE

    Cactus-Shaped Frequency Reconfigurable Antenna for Sub 10 GHz Wireless Applications

    Muhammad Irfan1, Wasi Ur Rehman Khan2, Sadiq Ullah2, Naveed Mufti2, Muhammad Fawad Khan2, Rizwan Ullah2, Usman Ali2, Fazal Muhammad3,*, Faisal Althobiani4, Mohammed Alshareef5, Shadi Alghaffari6, Saifur Rehman1, V. R. Shamji4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2693-2704, 2023, DOI:10.32604/csse.2023.032778
    Abstract This paper presents, a novel cactus shaped frequency reconfigurable antenna for sub 10 GHz wireless applications. PIN diode is utilized as an electrical switch to achieve reconfigurability, enabling operation in four different frequency ranges. In the switch ON state mode, the antenna supports 2177–3431 and 6301–8467 MHz ranges. Alternatively, the antenna resonates within 2329–3431 and 4951–6718 MHz while in the OFF state mode. Radiation efficiency values, ranging from 68% to 84%, and gain values, ranging from 1.6 to 4 dB, in the operating frequency bands. the proposed antenna satisfy the practical requirements and expectations. The overall planner dimensions of the proposed antenna model… More >

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    ARTICLE

    A Universal BIST Approach for Virtex-Ultrascale Architecture

    N. Sathiabama1,*, S. Anila2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2705-2720, 2023, DOI:10.32604/csse.2023.025941
    Abstract Interconnected cells, Configurable Logic Blocks (CLBs), and input/output (I/O) pads are all present in every Field Programmable Gate Array (FPGA) structure. The interconnects are formed by the physical paths for connecting the blocks . The combinational and sequential circuits are used in the logic blocks to execute logical functions. The FPGA includes two different tests called interconnect testing and logical testing. Instead of using an additional circuitry, the Built-in-Self-Test (BIST) logic is coded into an FPGA, which is then reconfigured to perform its specific operation after the testing is completed. As a result, additional test circuits for the FPGA board… More >

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    ARTICLE

    Selective Harmonics Elimination Technique for Artificial Bee Colony Implementation

    T. DeepikaVinothini1,*, R. Karthigaivel2, J. BarsanaBanu3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2721-2740, 2023, DOI:10.32604/csse.2023.028662
    Abstract In this research, an Artificial Bee Colony (ABC) algorithm based Selective Harmonics Elimination (SHE) technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system. Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics. A high gain DC-DC-SEPIC converter keeps the photovoltaic (PV) panel’s output voltage constant. The Grey Wolf Optimization (GWO) filter removes far more Photovoltaic panel energy from the sunlight frame. To eliminate voltage harmonics, this unique inverter architecture employs a multi-carrier duty cycle, a high-frequency modulation approach. The proposed ABC harmonics… More >

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    ARTICLE

    Applying Wide & Deep Learning Model for Android Malware Classification

    Le Duc Thuan1,2,*, Pham Van Huong2, Hoang Van Hiep1, Nguyen Kim Khanh1
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2741-2759, 2023, DOI:10.32604/csse.2023.033420
    Abstract Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can… More >

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    ARTICLE

    Photovoltaic Cell Panels Soiling Inspection Using Principal Component Thermal Image Processing

    A. Sriram1,*, T. D. Sudhakar2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2761-2772, 2023, DOI:10.32604/csse.2023.028559
    Abstract Intended for good productivity and perfect operation of the solar power grid a failure-free system is required. Therefore, thermal image processing with the thermal camera is the latest non-invasive (without manual contact) type fault identification technique which may give good precision in all aspects. The soiling issue, which is major productivity affecting factor may import from several reasons such as dust on the wind, bird mucks, etc. The efficient power production sufferers due to accumulated soil deposits reaching from 1%–7% in the county, such as India, to more than 25% in middle-east countries country, such as Dubai, Kuwait, etc. This… More >

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    ARTICLE

    Small-World Networks with Unitary Cayley Graphs for Various Energy Generation

    C. Thilaga*, P. B. Sarasija
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2773-2782, 2023, DOI:10.32604/csse.2023.032303
    Abstract Complex networks have been a prominent topic of research for several years, spanning a wide range of fields from mathematics to computer science and also to social and biological sciences. The eigenvalues of the Seidel matrix, Seidel Signless Laplacian matrix, Seidel energy, Seidel Signless Laplacian energy, Maximum and Minimum energy, Degree Sum energy and Distance Degree energy of the Unitary Cayley graphs [UCG] have been calculated. Low-power devices must be able to transfer data across long distances with low delay and reliability. To overcome this drawback a small-world network depending on the unitary Cayley graph is proposed to decrease the… More >

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    ARTICLE

    Quantum Fuzzy Support Vector Machine for Binary Classification

    Xi Huang1,2, Shibin Zhang1,2,*, Chen Lin1,2, Jinyue Xia3
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2783-2794, 2023, DOI:10.32604/csse.2023.032190
    Abstract In the objective world, how to deal with the complexity and uncertainty of big data efficiently and accurately has become the premise and key to machine learning. Fuzzy support vector machine (FSVM) not only deals with the classification problems for training samples with fuzzy information, but also assigns a fuzzy membership degree to each training sample, allowing different training samples to contribute differently in predicting an optimal hyperplane to separate two classes with maximum margin, reducing the effect of outliers and noise, Quantum computing has super parallel computing capabilities and holds the promise of faster algorithmic processing of data. However,… More >

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    ARTICLE

    Enhanced Security with Improved Defensive Routing Mechanism in Wireless Sensor Networks

    R. Sabitha1,*, C. Gokul Prasad2, S. Karthik1
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2795-2810, 2023, DOI:10.32604/csse.2023.026465
    Abstract In recent scenario of Wireless Sensor Networks (WSNs), there are many application developed for handling sensitive and private data such as military information, surveillance data, tracking, etc. Hence, the sensor nodes of WSNs are distributed in an intimidating region, which is non-rigid to attacks. The recent research domains of WSN deal with models to handle the WSN communications against malicious attacks and threats. In traditional models, the solution has been made for defending the networks, only to specific attacks. However, in real-time applications, the kind of attack that is launched by the adversary is not known. Additionally, on developing a… More >

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    ARTICLE

    DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

    S. Pandeeswari1,*, S. Jaganathan2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2811-2825, 2023, DOI:10.32604/csse.2023.029945
    Abstract The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source… More >

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    ARTICLE

    A Novel Approximate Message Passing Detection for Massive MIMO 5G System

    Nidhi Gour1, Rajneesh Pareek1, Karthikeyan Rajagopal2,3, Himanshu Sharma1, Mrim M. Alnfiai4, Mohammed A. AlZain4, Mehedi Masud5, Arun Kumar6,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2827-2835, 2023, DOI:10.32604/csse.2023.033341
    Abstract Massive-Multiple Inputs and Multiple Outputs (M-MIMO) is considered as one of the standard techniques in improving the performance of Fifth Generation (5G) radio. 5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of 5G. The evaluation of 5G promises a high quality of service (QoS), a high data rate, low latency, and spectral efficiency, ensuring several applications that will improve the services in every sector. The existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their implementation.… More >

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    ARTICLE

    Evaluation of Grid-Connected Photovoltaic Plants Based on Clustering Methods

    Amr A. Munshi*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2837-2852, 2023, DOI:10.32604/csse.2023.033168
    Abstract Photovoltaic (PV) systems are electric power systems designed to supply usable solar power by means of photovoltaics, which is the conversion of light into electricity using semiconducting materials. PV systems have gained much attention and are a very attractive energy resource nowadays. The substantial advantage of PV systems is the usage of the most abundant and free energy from the sun. PV systems play an important role in reducing feeder losses, improving voltage profiles and providing ancillary services to local loads. However, large PV grid-connected systems may have a destructive impact on the stability of the electric grid. This is… More >

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    ARTICLE

    IOT Assisted Biomedical Monitoring Sensors for Healthcare in Human

    S. Periyanayagi1, V. Nandini2,*, K. Basarikodi3, V. Sumathy4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2853-2868, 2023, DOI:10.32604/csse.2023.030538
    Abstract The Internet of Things (IoT) is a concept that refers to the deployment of Internet Protocol (IP) address sensors in health care systems to monitor patients’ health. It has the ability to access the Internet and collect data from sensors. Automated decisions are made after evaluating the information of illness people records. Patients’ health and well-being can be monitored through IoT medical devices. It is possible to trace the origins of biological, medical equipment and processes. Human reliability is a major concern in user activity and fitness trackers in day-to-day activities. The fundamental challenge is to measure the efficiency of… More >

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    ARTICLE

    Graph-Based Replication and Two Factor Authentication in Cloud Computing

    S. Lavanya1,*, N. M. Saravanakumar2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2869-2883, 2023, DOI:10.32604/csse.2023.029040
    Abstract Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms. By incorporating new, cutting-edge technologies to a larger extent without using more infrastructures, the information technology platform is anticipating a completely new level of development. The following concepts are proposed in this research paper: 1) A reliable authentication method Data replication that is optimised; graph-based data encryption and packing colouring in Redundant Array of Independent Disks (RAID) storage. At the data centre, data is encrypted using crypto keys called Key Streams. These keys are produced using the packing colouring method in the… More >

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    ARTICLE

    Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

    El-Sayed M. El-kenawy1, Abdelaziz A. Abdelhamid2,3, Fadwa Alrowais4,*, Mostafa Abotaleb5, Abdelhameed Ibrahim6, Doaa Sami Khafaga4
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2885-2899, 2023, DOI:10.32604/csse.2023.034206
    Abstract Rainfall plays a significant role in managing the water level in the reservoir. The unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the reservoir. Many individuals, especially those in the agricultural sector, rely on rain forecasts. Forecasting rainfall is challenging because of the changing nature of the weather. The area of Jimma in southwest Oromia, Ethiopia is the subject of this research, which aims to develop a rainfall forecasting model. To estimate Jimma’s daily rainfall, we propose a novel approach based on optimizing the parameters of long short-term memory (LSTM) using Al-Biruni… More >

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    ARTICLE

    N×N Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

    Amita Asthana1,*, Anil Kumar1, Preeta Sharan2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2901-2917, 2023, DOI:10.32604/csse.2023.030548
    Abstract Quantum dot cellular automata (QCA) technology is emerging as a future technology which designs the digital circuits at quantum levels. The technology has gained popularity in terms of designing digital circuits, which occupy very less area and less power dissipation in comparison to the present complementary metal oxide semiconductor (CMOS) technology. For designing the routers at quantum levels with non-blocking capabilities various multi-stage networks have been proposed. This manuscript presents the design of the N×N Clos switch matrix as a multistage interconnecting network using quantum-dot cellular automata technology. The design of the Clos switch matrix presented in the article uses… More >

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    ARTICLE

    An Efficient Hybrid Optimization for Skin Cancer Detection Using PNN Classifier

    J. Jaculin Femil1,*, T. Jaya2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2919-2934, 2023, DOI:10.32604/csse.2023.032935
    Abstract The necessity of on-time cancer detection is extremely high in the recent days as it becomes a threat to human life. The skin cancer is considered as one of the dangerous diseases among other types of cancer since it causes severe health impacts on human beings and hence it is highly mandatory to detect the skin cancer in the early stage for providing adequate treatment. Therefore, an effective image processing approach is employed in this present study for the accurate detection of skin cancer. Initially, the dermoscopy images of skin lesions are retrieved and processed by eliminating the noises with… More >

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    ARTICLE

    New Trends in the Modeling of Diseases Through Computational Techniques

    Nesreen Althobaiti1, Ali Raza2,*, Arooj Nasir3,4, Jan Awrejcewicz5, Muhammad Rafiq6, Nauman Ahmed7, Witold Pawłowski8, Muhammad Jawaz7, Emad E. Mahmoud1
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2935-2951, 2023, DOI:10.32604/csse.2023.033935
    Abstract The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance. The handling strategies of real-world problems are artificial neural networks (ANN), evolutionary computing (EC), and many more. An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually, with only 25% to 45% reported to the World Health Organization (WHO). It remains one of the top parasitic diseases with outbreak and mortality potential. In 2020, more than ninety percent of new cases reported to World Health Organization (WHO) occurred in ten countries: Brazil, China, Ethiopia, Eritrea, India, Kenya, Somalia, South… More >

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    ARTICLE

    A Duty Cycle-Based Gateway Selection Algorithm for LoRaWAN Downlink Communication

    Mohammad Al Mojamed*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2953-2970, 2023, DOI:10.32604/csse.2023.032965
    Abstract Long Range Wide Area Network (LoRaWAN) has been developed to meet the requirements for the enormous device-to-device communication of Internet of Things (IoT) networks, which consist of a large number of participating devices spread over large coverage areas with low data rates and low power consumption. It supports communications in both directions, uplink, and downlink directions. However, the downlink communication in the current LoRaWAN raises the bottleneck issue at gateways due to the used gateway selection algorithm. This paper proposes a novel gateway selection algorithm based on the duty cycle time-off values for the existing gateways, Duty Cycle Gateway Selection… More >

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    ARTICLE

    3D Echocardiogram Reconstruction Employing a Flip Directional Texture Pyramid

    C. Preethi*, M. Mohamed Sathik, S. Shajun Nisha
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2971-2988, 2023, DOI:10.32604/csse.2023.033423
    Abstract Three dimensional (3D) echocardiogram enables cardiologists to visualize suspicious cardiac structures in detail. In recent years, this three-dimensional echocardiogram carries important clinical value in virtual surgical simulation. However, this 3D echocardiogram involves a trade-off difficulty between accuracy and efficient computation in clinical diagnosis. This paper presents a novel Flip Directional 3D Volume Reconstruction (FD-3DVR) method for the reconstruction of echocardiogram images. The proposed method consists of two main steps: multiplanar volumetric imaging and 3D volume reconstruction. In the creation of multiplanar volumetric imaging, two-dimensional (2D) image pixels are mapped into voxels of the volumetric grid. As the obtained slices are… More >

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    ARTICLE

    Android IoT Lifelog System and Its Application to Motion Inference

    Munkhtsetseg1, Jeongwook Seo2,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2989-3003, 2023, DOI:10.32604/csse.2023.033342
    Abstract In social science, health care, digital therapeutics, etc., smartphone data have played important roles to infer users’ daily lives. However, smartphone data collection systems could not be used effectively and widely because they did not exploit any Internet of Things (IoT) standards (e.g., oneM2M) and class labeling methods for machine learning (ML) services. Therefore, in this paper, we propose a novel Android IoT lifelog system complying with oneM2M standards to collect various lifelog data in smartphones and provide two manual and automated class labeling methods for inference of users’ daily lives. The proposed system consists of an Android IoT client… More >

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    ARTICLE

    Multi-label Emotion Classification of COVID–19 Tweets with Deep Learning and Topic Modelling

    K. Anuratha1,*, M. Parvathy2
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3005-3021, 2023, DOI:10.32604/csse.2023.031553
    Abstract The COVID-19 pandemic has become one of the severe diseases in recent years. As it majorly affects the common livelihood of people across the universe, it is essential for administrators and healthcare professionals to be aware of the views of the community so as to monitor the severity of the spread of the outbreak. The public opinions are been shared enormously in microblogging media like twitter and is considered as one of the popular sources to collect public opinions in any topic like politics, sports, entertainment etc., This work presents a combination of Intensity Based Emotion Classification Convolution Neural Network… More >

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    ARTICLE

    RMCARTAM For DDoS Attack Mitigation in SDN Using Machine Learning

    M. Revathi, V. V. Ramalingam*, B. Amutha
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3023-3036, 2023, DOI:10.32604/csse.2023.033600
    Abstract The impact of a Distributed Denial of Service (DDoS) attack on Software Defined Networks (SDN) is briefly analyzed. Many approaches to detecting DDoS attacks exist, varying on the feature being considered and the method used. Still, the methods have a deficiency in the performance of detecting DDoS attacks and mitigating them. To improve the performance of SDN, an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model (RMCARTAM) is sketched in this article. The RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming packets. The model is designed with multiple controllers to handle network traffic… More >

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    ARTICLE

    Enhanced Gorilla Troops Optimizer with Deep Learning Enabled Cybersecurity Threat Detection

    Fatma S. Alrayes1, Najm Alotaibi2, Jaber S. Alzahrani3, Sana Alazwari4, Areej Alhogail5, Ali M. Al-Sharafi6, Mahmoud Othman7, Manar Ahmed Hamza8,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3037-3052, 2023, DOI:10.32604/csse.2023.033970
    Abstract Recent developments in computer networks and Internet of Things (IoT) have enabled easy access to data. But the government and business sectors face several difficulties in resolving cybersecurity network issues, like novel attacks, hackers, internet criminals, and so on. Presently, malware attacks and software piracy pose serious risks in compromising the security of IoT. They can steal confidential data which results in financial and reputational losses. The advent of machine learning (ML) and deep learning (DL) models has been employed to accomplish security in the IoT cloud environment. This article presents an Enhanced Artificial Gorilla Troops Optimizer with Deep Learning… More >

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    ARTICLE

    Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

    Ernesto Lee1, Furqan Rustam2, Hina Fatima Shahzad2, Patrick Bernard Washington3, Abid Ishaq3, Imran Ashraf4,*
    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3053-3077, 2023, DOI:10.32604/csse.2023.029059
    Abstract With the increasing usage of drugs to remedy different diseases, drug safety has become crucial over the past few years. Often medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different formulae. Such diversification is both helpful and dangerous as such medicine proves to be more effective or shows side effects to different patients. Despite clinical trials, side effects are reported when the medicine is used by the mass public, of which several such experiences are shared on social media platforms. A system capable of analyzing such reviews could be very helpful… More >

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