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  • Open Access


    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 More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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.… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

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