Zhang Yunzuo^1,*, Zhang Jiayu¹, Cai Zhaoquan²

Journal of New Media, Vol.4, No.1, pp. 1-11, 2022, DOI:10.32604/jnm.2022.027054

Abstract With the improvement of people's security awareness, numerous monitoring equipment has been put into use, resulting in the explosive growth of surveillance video data. Key frame extraction technology is a paramount technology for improving video storage efficiency and enhancing the accuracy of video retrieval. It can extract key frame sets that can express video content from massive videos. However, the existing key frame extraction algorithms of surveillance video still have deficiencies, such as the destruction of image information integrity and the inability to extract key frames accurately. To this end, this paper proposes a key frame extraction algorithm of surveillance… More >

Yingnan Zhao^1,*, 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 >

Hang He^1,*, 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 >

Jian Geng^1,*, 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 >

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 >

Hosam El- El-Sofany^1,2,*

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 >

D. Venugopal¹, V. Mohan², S. Ramesh³, S. Janupriya⁴, Sangsoon Lim^5,*, 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 >

Ravindra Parshuram Bachate¹, Ashok Sharma², Amar Singh³, Ayman A. Aly⁴, Abdulaziz H. Alghtani⁴, Dac-Nhuong Le^5,6,*

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 >

R. Madhumathi^1,*, 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 >

Rashed Iqbal¹, Hazlie Mokhlis¹, Anis Salwa Mohd Khairuddin^1,*, 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 >