E. Kavitha^1,*, R. Tamilarasan², N. Poonguzhali³, M. K. Jayanthi Kannan⁴

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1027-141, 2022, DOI:10.32604/csse.2022.020634

Abstract Gene expression refers to the process in which the gene information is used in the functional gene product synthesis. They basically encode the proteins which in turn dictate the functionality of the cell. The first step in gene expression study involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise and imprecision. For a biological system to function, the essential cellular molecules must interact with its surrounding including RNA, DNA, metabolites and proteins. Clustering methods will… More >

Susmita Mishra^1,*, M. Prakash²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1099-1115, 2022, DOI:10.32604/csse.2022.020439

Abstract In the medical field, the detection of breast cancer may be a mysterious task. Physicians must deduce a conclusion from a significantly vague knowledge base. A mammogram can offer early diagnosis at a low cost if the breasts' satisfactory mammogram images are analyzed. A multi-decision Intuitionistic Fuzzy Evidential Reasoning (IFER) approach is introduced in this paper to deal with imprecise mammogram classification efficiently. The proposed IFER approach combines intuitionistic trapezoidal fuzzy numbers and inclusion measures to improve representation and reasoning accuracy. The results of the proposed technique are approved through simulation. The simulation is created utilizing MATLAB software. The screening… More >

M.S. Maharajan^1,*, T. Abirami²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1173-1189, 2022, DOI:10.32604/csse.2022.020312

Abstract Wireless sensor networks (WSN) have become a hot research area owing to the unique characteristics and applicability in diverse application areas. Clustering and routing techniques can be considered as an NP hard optimization problem, which can be addressed by metaheuristic optimization algorithms. With this motivation, this study presents a chaotic sandpiper optimization algorithm based clustering with groundwater flow optimization based routing technique (CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensor nodes in WSN and elect an optimal set of routes with an intention of achieving energy efficiency and maximizing network lifetime. The CSPOC algorithm is derived… More >

Parul Gandhi¹, Mohammad Zubair Khan², Ravi Kumar Sharma³, Omar H. Alhazmi², Surbhi Bhatia^4,*, Chinmay Chakraborty⁵

Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943

Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software reliability. The proposed algorithm is… More >

Xiaoying Chen^1,*, Jie Kang¹, Cong Hu²

Journal of New Media, Vol.3, No.4, pp. 151-180, 2021, DOI:10.32604/jnm.2021.024665

Abstract The texture of ground-based nephogram is abundant and multiplicity. Many cloud textures are not as clear as artificial textures. A nephogram enhancement algorithm based on Adaptive Fractional Differential is established to extract the natural texture of visible ground-based cloud image. GrunwaldLentikov (G-L) and Grunwald-Lentikov (R-L) fractional differential operators are applied to the enhancement algorithm of ground-based nephogram. An operator mask based on adaptive differential order is designed. The corresponding mask template is used to process each pixel. The results show that this method can extract image texture and edge details and simplify the process of differential order selection. More >

Meimin Wang, Zhili Zhou^*, Chun Ding

Journal of New Media, Vol.3, No.4, pp. 137-150, 2021, DOI:10.32604/jnm.2021.024543

Abstract Internet of Everything (IoE) has emerged as a promising paradigm for the purpose of connecting and exchanging data among physical objects and humans over the Internet, and it can be widely applied in the fields of industry, transportation, commerce, and education. Recently, the emergence of 6G-enabled cybertwin network architecture provides the technical and theoretical foundation for the realization of IoE paradigm. However, the IoE has three open issues in the 6G-enabled cybertwin architecture, i.e., data authenticity, data storage and node reliability. To address these issues, we propose a blockchain-based decentralized reputation management system (BC-DRMS) for IoE in 6G-enabled Cybertwin architecture.… More >

Yang Dai^*, Zhiyuan Luo

Journal of New Media, Vol.3, No.4, pp. 129-136, 2021, DOI:10.32604/jnm.2021.023981

Abstract Person re-identification (re-ID) aims to match images of the same pedestrian across different cameras. It plays an important role in the field of security and surveillance. Although it has been studied for many years, it is still considered as an unsolved problem. Since the rise of deep learning, the accuracy of supervised person re-ID on public datasets has reached the highest level. However, these methods are difficult to apply to real-life scenarios because a large number of labeled training data is required in this situation. Pedestrian identity labeling, especially cross-camera pedestrian identity labeling, is heavy and expensive. Why we cannot… More >

Yingchao Wang¹, Yuanhao Zhu¹, Zongtian Zhang¹, Huihuang Liu^1,* , Peng Guo²

Journal of New Media, Vol.3, No.4, pp. 119-128, 2021, DOI:10.32604/jnm.2021.016655

Abstract In order to improve user satisfaction and loyalty on e-commerce websites, recommendation algorithms are used to recommend products that may be of interest to users. Therefore, the accuracy of the recommendation algorithm is a primary issue. So far, there are three mainstream recommendation algorithms, content-based recommendation algorithms, collaborative filtering algorithms and hybrid recommendation algorithms. Content-based recommendation algorithms and collaborative filtering algorithms have their own shortcomings. The contentbased recommendation algorithm has the problem of the diversity of recommended items, while the collaborative filtering algorithm has the problem of data sparsity and scalability. On the basis of these two algorithms, the hybrid… More >

Dong Wang^1,*, Siwei Chen¹, Weigong Zhang¹, Danjie Du²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1837-1848, 2022, DOI:10.32604/cmc.2022.023033

Abstract It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance, and that may cause serious accidents. Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation, how to make an effective early warning of rollover is still unsolved in practice. The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining. The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle. Unfortunately, the… More >

Chih-Ta Yen^1,*, Cheng-Hong Liao²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679

Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of PPG signals and how to… More >