Home / Journals / CSSE / Vol.43, No.2, 2022
  • Open Access

    ARTICLE

    Design of Hybrid True Random Number Generator for Cryptographic Applications

    S. Nithya Devi1,*, S. Sasipriya2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 423-437, 2022, DOI:10.32604/csse.2022.022280
    Abstract In real-time applications, unpredictable random numbers play a major role in providing cryptographic and encryption processes. Most of the existing random number generators are embedded with the complex nature of an amplifier, ring oscillators, or comparators. Hence, this research focused more on implementing a Hybrid Nature of a New Random Number Generator. The key objective of the proposed methodology relies on the utilization of True random number generators. The randomness is unpredictable. The additions of programmable delay lines will reduce the processing time and maintain the quality of randomizing. The performance comparisons are carried out with power, delay, and lookup… More >

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    ARTICLE

    Enhanced Marathi Speech Recognition Facilitated by Grasshopper Optimisation-Based Recurrent Neural Network

    Ravindra Parshuram Bachate1, Ashok Sharma2, Amar Singh3, Ayman A. Aly4, Abdulaziz H. Alghtani4, Dac-Nhuong Le5,6,*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 439-454, 2022, DOI:10.32604/csse.2022.024214
    Abstract Communication is a significant part of being human and living in the world. Diverse kinds of languages and their variations are there; thus, one person can speak any language and cannot effectively communicate with one who speaks that language in a different accent. Numerous application fields such as education, mobility, smart systems, security, and health care systems utilize the speech or voice recognition models abundantly. Though, various studies are focused on the Arabic or Asian and English languages by ignoring other significant languages like Marathi that leads to the broader research motivations in regional languages. It is necessary to understand… More >

  • Open Access

    ARTICLE

    Soil Nutrient Detection and Recommendation Using IoT and Fuzzy Logic

    R. Madhumathi1,*, T. Arumuganathan2, R. Shruthi1
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 455-469, 2022, DOI:10.32604/csse.2022.023792
    Abstract Precision agriculture is a modern farming practice that involves the usage of Internet of Things (IoT) to provide an intelligent farm management system. One of the important aspects in agriculture is the analysis of soil nutrients and balancing these inputs are essential for proper crop growth. The crop productivity and the soil fertility can be improved with effective nutrient management and precise application of fertilizers. This can be done by identifying the deficient nutrients with the help of an IoT system. As traditional approach is time consuming, an IoT-enabled system is developed using the colorimetry principle which analyzes the amount… More >

  • Open Access

    ARTICLE

    Incremental Linear Discriminant Analysis Dimensionality Reduction and 3D Dynamic Hierarchical Clustering WSNs

    G. Divya Mohana Priya1,*, M. Karthikeyan1, K. Murugan2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 471-486, 2022, DOI:10.32604/csse.2022.021023
    Abstract Optimizing the sensor energy is one of the most important concern in Three-Dimensional (3D) Wireless Sensor Networks (WSNs). An improved dynamic hierarchical clustering has been used in previous works that computes optimum clusters count and thus, the total consumption of energy is optimal. However, the computational complexity will be increased due to data dimension, and this leads to increase in delay in network data transmission and reception. For solving the above-mentioned issues, an efficient dimensionality reduction model based on Incremental Linear Discriminant Analysis (ILDA) is proposed for 3D hierarchical clustering WSNs. The major objective of the proposed work is to… More >

  • Open Access

    ARTICLE

    Efficient Single-Stage Bridgeless AC to DC Converter Using Grey Wolf Optimization

    Prema Kandasamy1,*, K. Prem Kumar2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 487-499, 2022, DOI:10.32604/csse.2022.021693
    Abstract Bridgeless single-stage converters are used for efficient (alternative current) AC-(direct current) DC conversion. These converters control generators, like electromagnetic meso- and micro-scale generators with low voltage. Power factor correction helps increase the factor of the power supply. The main advantage of the power factor is it shapes the input current for increasing the real power of the AC supply. In this paper, a two-switch bridgeless rectifier topology is designed with a power factor correction capability. For the proposed converter topology to have good power quality parameters, the closed loop scheme, which uses the grey wolf optimization (GWO) algorithm, is implemented.… More >

  • Open Access

    ARTICLE

    Capacitive Coupled Wide-Notch Stepped Impedance Narrow-Band Bandpass Filter for WiMax Application

    A. Kayalvizhi*, G. Sankara Malliga
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 501-514, 2022, DOI:10.32604/csse.2022.022855
    Abstract The development of wireless communication standards necessitates optimal filter design for the selection of appropriate bands of frequencies. In this work, a compact in size pair of parallel coupled symmetric stepped impedance-based resonator is designed with supporting to the WiMAX communication standards. The coupled resonator is tuned to allow the frequency band between 3.4 GHz and 3.8 GHz, which is centered at 3.6 GHz. A parasitic effect of capacitively coupled feed structure is used for exciting the two symmetrical stepped impedance resonators. The bandwidth and selectivity of the filter are enhanced with the change of characteristic impedances and controlling the coupling gap between… More >

  • Open Access

    ARTICLE

    An Efficient Video Inpainting Approach Using Deep Belief Network

    M. Nuthal Srinivasan1,*, M. Chinnadurai2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 515-529, 2022, DOI:10.32604/csse.2022.023109
    Abstract The video inpainting process helps in several video editing and restoration processes like unwanted object removal, scratch or damage rebuilding, and retargeting. It intends to fill spatio-temporal holes with reasonable content in the video. Inspite of the recent advancements of deep learning for image inpainting, it is challenging to outspread the techniques into the videos owing to the extra time dimensions. In this view, this paper presents an efficient video inpainting approach using beetle antenna search with deep belief network (VIA-BASDBN). The proposed VIA-BASDBN technique initially converts the videos into a set of frames and they are again split into… More >

  • Open Access

    ARTICLE

    QoS Constrained Network Coding Technique to Data Transmission Using IoT

    A. Sathishkumar1,*, T. Rammohan2, S. Sathish Kumar3, J. Uma3, K. Srujan Raju4, Aarti Sangwan5, M. Sivachitra6, M. Prabu7
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 531-544, 2022, DOI:10.32604/csse.2022.021694
    Abstract The research work presents, constrained network coding technique to ensure the successful data transmission based composite channel cmos technology using dielectric properties. The charge fragmentation and charge splitting are two components of the filtered switch domino (FSD) technique. Further behavior of selected switching is achieved using generator called conditional pulse generator which is employed in Multi Dynamic Node Domino (MDND) technique. Both FSD and MDND technique need wide area compared to existing single node-keeper domino technique. The aim of this research is to minimize dissipation of power and to achieve less consumption of power. The proposed research, works by introducing… More >

  • Open Access

    ARTICLE

    Pattern Recognition of Modulation Signal Classification Using Deep Neural Networks

    D. Venugopal1, V. Mohan2, S. Ramesh3, S. Janupriya4, Sangsoon Lim5,*, Seifedine Kadry6
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 545-558, 2022, DOI:10.32604/csse.2022.024239
    Abstract In recent times, pattern recognition of communication modulation signals has gained significant attention in several application areas such as military, civilian field, etc. It becomes essential to design a safe and robust feature extraction (FE) approach to efficiently identify the various signal modulation types in a complex platform. Several works have derived new techniques to extract the feature parameters namely instant features, fractal features, and so on. In addition, machine learning (ML) and deep learning (DL) approaches can be commonly employed for modulation signal classification. In this view, this paper designs pattern recognition of communication signal modulation using fractal features… More >

  • Open Access

    ARTICLE

    Evidence Mechanism of Power Dispatching Instruction Based on Blockchain

    Jian Geng1,*, Shaoyuan Yu1, Ailin Chen1, Hao Wang2, Bo Yan3, Liang Li3, Lei Song3, Qirun Wang4
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 559-571, 2022, DOI:10.32604/csse.2022.026948
    Abstract With the development and application of energy Internet technology, the collaborative interaction of “source network, load and storage” has become the development trend of power grid dispatching. The large-scale access of renewable energy on the load side, the unified management of adjustable loads, and the participation of multiple parties in energy operations have put forward requirements for the safety, credibility, openness, and transparency of the load dispatching environment. Under the environment of carbon emission reduction, the paper proposed an architecture of the scheduling data blockchain, based on the in-depth study of blockchain. Moreover, smart contracts are used to realize the… More >

  • Open Access

    ARTICLE

    A Proposed Biometric Authentication Model to Improve Cloud Systems Security

    Hosam El- El-Sofany1,2,*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 573-589, 2022, DOI:10.32604/csse.2022.024302
    Abstract Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password. Unfortunately, this approach has many security problems because personal data can be stolen or recognized by hackers. This paper aims to present a cloud-based biometric authentication model (CBioAM) for improving and securing cloud services. The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system (CBioAS), where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the users’ information. The paper… More >

  • Open Access

    ARTICLE

    Blockchain for Education: Verification and Management of Lifelong Learning Data

    Ba-Lam Do*, Van-Thanh Nguyen, Hoang-Nam Dinh, Thanh-Chung Dao, BinhMinh Nguyen
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 591-604, 2022, DOI:10.32604/csse.2022.023508
    Abstract In recent years, blockchain technology has been applied in the educational domain because of its salient advantages, i.e., transparency, decentralization, and immutability. Available systems typically use public blockchain networks such as Ethereum and Bitcoin to store learning results. However, the cost of writing data on these networks is significant, making educational institutions limit data sent to the target network, typically containing only hash codes of the issued certificates. In this paper, we present a system based on a private blockchain network for lifelong learning data authentication and management named B4E (Blockchain For Education). B4E stores not only certificates but also… More >

  • Open Access

    ARTICLE

    Kalman Filter and H Filter Based Linear Quadratic Regulator for Furuta Pendulum

    N. Arulmozhi1,*, T. Aruldoss Albert Victorie2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 605-623, 2022, DOI:10.32604/csse.2022.023376
    Abstract This paper deals with Furuta Pendulum (FP) or Rotary Inverted Pendulum (RIP), which is an under-actuated non-minimum unstable non-linear process. The process considered along with uncertainties which are unmodelled and analyses the performance of Linear Quadratic Regulator (LQR) with Kalman filter and H filter as two filter configurations. The LQR is a technique for developing practical feedback, in addition the desired x shows the vector of desirable states and is used as the external input to the closed-loop system. The effectiveness of the two filters in FP or RIP are measured and contrasted with rise time, peak time, settling time… More >

  • Open Access

    ARTICLE

    Provisioning Intelligent Water Wave Optimization Approach for Underwater Acoustic Wireless Sensor Networks

    M. Manikandan1,*, A. Rajiv Kannan
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 625-641, 2022, DOI:10.32604/csse.2022.022662
    Abstract In the Acoustics channel, it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay. Subsequently, conventional re-transmission over any failure generally initiates significantly larger end-to-end delay, and therefore it is not probable for time-based services. Moreover, standard techniques without any re-transmission consume enormous energy. This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy. It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay. It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the… More >

  • Open Access

    ARTICLE

    Vulnerability of Regional Aviation Networks Based on DBSCAN and Complex Networks

    Hang He1,*, Wanggen Liu1, Zhenhan Zhao1, Shan He1, Jinghui Zhang2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 643-655, 2022, DOI:10.32604/csse.2022.027211
    Abstract To enhance the accuracy of performance analysis of regional airline network, this study applies complex network theory and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to investigate the topology of regional airline network, constructs node importance index system, and clusters 161 airport nodes of regional airline network. Besides, entropy power method and approximating ideal solution method (TOPSIS) is applied to comprehensively evaluate the importance of airport nodes and complete the classification of nodes and identification of key points; adopt network efficiency, maximum connectivity subgraph and network connectivity as vulnerability measurement indexes, and observe the changes of vulnerability indexes… More >

  • Open Access

    ARTICLE

    Efficient Energy-Aware Resource Management Model (EEARMM) Based Dynamic VM Migration

    V. Roopa1,*, K. Malarvizhi2, S. Karthik3
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 657-669, 2022, DOI:10.32604/csse.2022.022173
    Abstract In cloud environment, an efficient resource management establishes the allocation of computational resources of cloud service providers to the requests of users for meeting the user’s demands. The proficient resource management and work allocation determines the accomplishment of the cloud infrastructure. However, it is very difficult to persuade the objectives of the Cloud Service Providers (CSPs) and end users in an impulsive cloud domain with random changes of workloads, huge resource availability and complicated service policies to handle them, With that note, this paper attempts to present an Efficient Energy-Aware Resource Management Model (EEARMM) that works in a decentralized manner.… More >

  • Open Access

    ARTICLE

    X-ray Image-Based COVID-19 Patient Detection Using Machine Learning-Based Techniques

    Shabana Habib1, Saleh Alyahya2, Aizaz Ahmed3, Muhammad Islam2,*, Sheroz Khan2, Ishrat Khan4, Muhammad Kamil5
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 671-682, 2022, DOI:10.32604/csse.2022.021812
    Abstract In early December 2019, the city of Wuhan, China, reported an outbreak of coronavirus disease (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). On January 30, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic crisis. In the face of the COVID-19 pandemic, the most important step has been the effective diagnosis and monitoring of infected patients. Identifying COVID-19 using Machine Learning (ML) technologies can help the health care unit through assistive diagnostic suggestions, which can reduce the health unit's burden to a certain extent. This paper investigates the possibilities of ML techniques in… More >

  • Open Access

    ARTICLE

    An Efficient Deep Learning-based Content-based Image Retrieval Framework

    M. Sivakumar1,*, N. M. Saravana Kumar2, N. Karthikeyan1
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 683-700, 2022, DOI:10.32604/csse.2022.021459
    Abstract The use of massive image databases has increased drastically over the few years due to evolution of multimedia technology. Image retrieval has become one of the vital tools in image processing applications. Content-Based Image Retrieval (CBIR) has been widely used in varied applications. But, the results produced by the usage of a single image feature are not satisfactory. So, multiple image features are used very often for attaining better results. But, fast and effective searching for relevant images from a database becomes a challenging task. In the previous existing system, the CBIR has used the combined feature extraction technique using… More >

  • Open Access

    ARTICLE

    Transfer Learning on Deep Neural Networks to Detect Pornography

    Saleh Albahli*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 701-717, 2022, DOI:10.32604/csse.2022.022723
    Abstract While the internet has a lot of positive impact on society, there are negative components. Accessible to everyone through online platforms, pornography is, inducing psychological and health related issues among people of all ages. While a difficult task, detecting pornography can be the important step in determining the porn and adult content in a video. In this paper, an architecture is proposed which yielded high scores for both training and testing. This dataset was produced from 190 videos, yielding more than 19 h of videos. The main sources for the content were from YouTube, movies, torrent, and websites that hosts… More >

  • Open Access

    ARTICLE

    Spatio-Temporal Wind Speed Prediction Based on Variational Mode Decomposition

    Yingnan Zhao1,*, Guanlan Ji1, Fei Chen1, Peiyuan Ji1, Yi Cao2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 719-735, 2022, DOI:10.32604/csse.2022.027288
    Abstract Improving short-term wind speed prediction accuracy and stability remains a challenge for wind forecasting researchers. This paper proposes a new variational mode decomposition (VMD)-attention-based spatio-temporal network (VASTN) method that takes advantage of both temporal and spatial correlations of wind speed. First, VASTN is a hybrid wind speed prediction model that combines VMD, squeeze-and-excitation network (SENet), and attention mechanism (AM)-based bidirectional long short-term memory (BiLSTM). VASTN initially employs VMD to decompose the wind speed matrix into a series of intrinsic mode functions (IMF). Then, to extract the spatial features at the bottom of the model, each IMF employs an improved convolutional… More >

  • Open Access

    ARTICLE

    Grid Search for Predicting Coronary Heart Disease by Tuning Hyper-Parameters

    S. Prabu1,*, B. Thiyaneswaran2, M. Sujatha3, C. Nalini4, Sujatha Rajkumar5
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 737-749, 2022, DOI:10.32604/csse.2022.022739
    Abstract Diagnosing the cardiovascular disease is one of the biggest medical difficulties in recent years. Coronary cardiovascular (CHD) is a kind of heart and blood vascular disease. Predicting this sort of cardiac illness leads to more precise decisions for cardiac disorders. Implementing Grid Search Optimization (GSO) machine training models is therefore a useful way to forecast the sickness as soon as possible. The state-of-the-art work is the tuning of the hyperparameter together with the selection of the feature by utilizing the model search to minimize the false-negative rate. Three models with a cross-validation approach do the required task. Feature Selection based… More >

  • Open Access

    ARTICLE

    Cognitive Radio Networks Using Intelligent Reflecting Surfaces

    Raed Alhamad*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.021932
    Abstract In this article, we optimize harvesting and sensing duration for Cognitive Radio Networks (CRN) using Intelligent Reflecting Surfaces (IRS). The secondary source harvests energy using the received signal from node A. Then, it performs spectrum sensing to detect Primary Source PS activity. When PS activity is not detected, The Secondary Source SS transmits data to Secondary Destination SD where all reflected signals on IRS are in phase at SD. We show that IRS offers 14, 20, 26, 32, 38, 44, 50 dB enhancement in throughput using M = 8, 16, 32, 64, 128, 256, 512 reflectors with respect to CRN without IRS. We… More >

  • Open Access

    ARTICLE

    Binary Representation of Polar Bear Algorithm for Feature Selection

    Amer Mirkhan1, Numan Çelebi2,*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 767-783, 2022, DOI:10.32604/csse.2022.023249
    Abstract In most of the scientific research feature selection is a challenge for researcher. Selecting all available features is not an option as it usually complicates the research and leads to performance drop when dealing with large datasets. On the other hand, ignoring some features can compromise the data accuracy. Here the rough set theory presents a good technique to identify the redundant features which can be dismissed without losing any valuable information, however, exploring all possible combinations of features will end with NP-hard problem. In this research we propose adopting a heuristic algorithm to solve this problem, Polar Bear Optimization… More >

  • Open Access

    ARTICLE

    Improved Secure Identification-Based Multilevel Structure of Data Sharing in Cloud Environments

    Saraswathi Shunmuganathan1,*, Sridharan Kannan2, T. V. Madhusudhana Rao3, K. Ambika4, T. Jayasankar5
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 785-801, 2022, DOI:10.32604/csse.2022.022424
    Abstract The Cloud Computing Environment (CCE) developed for using the dynamic cloud is the ability of software and services likely to grow with any business. It has transformed the methodology for storing the enterprise data, accessing the data, and Data Sharing (DS). Big data frame a constant way of uploading and sharing the cloud data in a hierarchical architecture with different kinds of separate privileges to access the data. With the requirement of vast volumes of storage area in the CCEs, capturing a secured data access framework is an important issue. This paper proposes an Improved Secure Identification-based Multilevel Structure of… More >

  • Open Access

    ARTICLE

    An FPGA Design for Real-Time Image Denoising

    Ahmed Ben Atitallah*
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 803-816, 2022, DOI:10.32604/csse.2022.024393
    Abstract The increasing use of images in miscellaneous applications such as medical image analysis and visual quality inspection has led to growing interest in image processing. However, images are often contaminated with noise which may corrupt any of the following image processing steps. Therefore, noise filtering is often a necessary preprocessing step for the most image processing applications. Thus, in this paper an optimized field-programmable gate array (FPGA) design is proposed to implement the adaptive vector directional distance filter (AVDDF) in hardware/software (HW/SW) codesign context for removing noise from the images in real-time. For that, the high-level synthesis (HLS) flow is… More >

  • Open Access

    ARTICLE

    Optimized Gated Recurrent Unit for Mid-Term Electricity Price Forecasting

    Rashed Iqbal1, Hazlie Mokhlis1, Anis Salwa Mohd Khairuddin1,*, Syafiqah Ismail1, Munir Azam Muhammad2
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 817-832, 2022, DOI:10.32604/csse.2022.023617
    Abstract Electricity price forecasting (EPF) is important for energy system operations and management which include strategic bidding, generation scheduling, optimum storage reserves scheduling and systems analysis. Moreover, accurate EPF is crucial for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market. Nevertheless, accurate time-series prediction of electricity price is very challenging due to complex nonlinearity in the trend of electricity price. This work proposes a mid-term forecasting model based on the demand and price data, renewable and non-renewable energy supplies, the seasonality and peak and off-peak hours of working and non-working days. An… More >

  • Open Access

    ARTICLE

    Fingerprint Agreement Using Enhanced Kerberos Authentication Protocol on M-Health

    A. S. Anakath1,*, S. Ambika2, S. Rajakumar3, R. Kannadasan4, K. S. Sendhil Kumar5
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 833-847, 2022, DOI:10.32604/csse.2022.022329
    Abstract Cloud computing becomes an important application development platform for processing user data with high security. Service providers are accustomed to providing storage centers outside the trusted location preferred by the data owner. Thus, ensuring the security and confidentiality of the data while processing in the centralized network is very difficult. The secured key transmission between the sender and the receiver in the network is a huge challenge in managing most of the sensitive data transmission among the cloud network. Intruders are very active over the network like real authenticated user to hack the personal sensitive data, such as bank balance,… More >

  • Open Access

    ARTICLE

    Assessment of Sentiment Analysis Using Information Gain Based Feature Selection Approach

    R. Madhumathi1,*, A. Meena Kowshalya2, R. Shruthi1
    Computer Systems Science and Engineering, Vol.43, No.2, pp. 849-860, 2022, DOI:10.32604/csse.2022.023568
    Abstract Sentiment analysis is the process of determining the intention or emotion behind an article. The subjective information from the context is analyzed by the sentimental analysis of the people’s opinion. The data that is analyzed quantifies the reactions or sentiments and reveals the information’s contextual polarity. In social behavior, sentiment can be thought of as a latent variable. Measuring and comprehending this behavior could help us to better understand the social issues. Because sentiments are domain specific, sentimental analysis in a specific context is critical in any real-world scenario. Textual sentiment analysis is done in sentence, document level and feature… More >

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