Musaed Alrashidi^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 371-387, 2023, DOI:10.32604/csse.2023.034739 - 20 January 2023

Abstract The tendency toward achieving more sustainable and green buildings turned several passive buildings into more dynamic ones. Mosques are the type of buildings that have a unique energy usage pattern. Nevertheless, these types of buildings have minimal consideration in the ongoing energy efficiency applications. This is due to the unpredictability in the electrical consumption of the mosques affecting the stability of the distribution networks. Therefore, this study addresses this issue by developing a framework for a short-term electricity load forecast for a mosque load located in Riyadh, Saudi Arabia. In this study, and by harvesting… More >

S. Prince Chelladurai^1,*, T. Rajagopalan²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 951-960, 2023, DOI:10.32604/csse.2023.034262 - 20 January 2023

Abstract Cloud computing offers numerous web-based services. The adoption of many Cloud applications has been hindered by concerns about data security and privacy. Cloud service providers’ access to private information raises more security issues. In addition, Cloud computing is incompatible with several industries, including finance and government. Public-key cryptography is frequently cited as a significant advancement in cryptography. In contrast, the Digital Envelope that will be used combines symmetric and asymmetric methods to secure sensitive data. This study aims to design a Digital Envelope for distributed Cloud-based large data security using public-key cryptography. Through strategic design, More >

R. Shanthakumari¹, Yun-Cheol Nam², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1991-2005, 2023, DOI:10.32604/iasc.2023.033696 - 05 January 2023

Abstract Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The… More >

Muhammad Umair^1,*, Zafar Saeed¹, Faisal Saeed², Hiba Ishtiaq¹, Muhammad Zubair¹, Hala Abdel Hameed^3,4

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5431-5446, 2023, DOI:10.32604/cmc.2023.033884 - 28 December 2022

Abstract As big data, its technologies, and application continue to advance, the Smart Grid (SG) has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology (ICT) and cloud computing. As a result of the complicated architecture of cloud computing, the distinctive working of advanced metering infrastructures (AMI), and the use of sensitive data, it has become challenging to make the SG secure. Faults of the SG are categorized into two main categories, Technical Losses (TLs) and Non-Technical Losses (NTLs). Hardware failure,… More >

E. Susi^*, A. P. Shanthi

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3231-3246, 2023, DOI:10.32604/csse.2023.032104 - 21 December 2022

Abstract Handling sentiment drifts in real time twitter data streams are a challenging task while performing sentiment classifications, because of the changes that occur in the sentiments of twitter users, with respect to time. The growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real time. This work proposes an adaptive learning algorithm-based framework, Twitter Sentiment Drift Analysis-Bidirectional Encoder Representations from Transformers (TSDA-BERT), which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the… More >

G. Sharmila^1,*, M. K. Kavitha Devi²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1743-1758, 2023, DOI:10.32604/csse.2023.032127 - 03 November 2022

Abstract Over the past era, subgraph mining from a large collection of graph database is a crucial problem. In addition, scalability is another big problem due to insufficient storage. There are several security challenges associated with subgraph mining in today’s on-demand system. To address this downside, our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs (BCCA-LSDG). The two-fold process is handled in the proposed BCCA-LSDG: graph indexing and authenticated query search (query processing). A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of… More >

M. Priyadharsini^1,*, K. Karuppasamy²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2187-2205, 2023, DOI:10.32604/csse.2023.031115 - 03 November 2022

Abstract Big Data applications face different types of complexities in classifications. Cleaning and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discriminative features in processed data. The existing scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. Recently ensemble methods have made a mark in classification tasks as combine multiple results into a single representation. When comparing to a single model, this technique offers for improved prediction. Ensemble based feature selections parallel… More >

Iram Arshad^1,*, Saeed Hamood Alsamhi¹, Wasif Afzal²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2739-2770, 2023, DOI:10.32604/cmc.2023.030266 - 31 October 2022

Abstract Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques’ evidence occurring in the period 2010–2021. This… More >

Lin Lang¹, Shuang Zhou¹, Minjuan Zhong^1,*, Guang Sun¹, Bin Pan¹, Peng Guo^1,2

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3503-3513, 2023, DOI:10.32604/cmc.2023.023596 - 31 October 2022

Abstract Using the RFM (Recency, Frequency, Monetary value) model can provide valuable insights about customer clusters which is the core of customer relationship management. Due to accurate customer segment coming from dynamic weighted applications, in-depth targeted marketing may also use type of dynamic weight of R, F and M as factors. In this paper, we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights. Our dynamic weight approach is a kind of Custom method in essential which roots in… More >

Jie Ren^1,2, Chuqiao Xu³, Junliang Wang^2,4, Jie Zhang^2,*, Xinhua Mao⁴, Wei Shen⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 599-618, 2023, DOI:10.32604/cmes.2022.022415 - 29 September 2022

Abstract The prognostics health management (PHM) from the systematic view is critical to the healthy continuous operation of process manufacturing systems (PMS), with different kinds of dynamic interference events. This paper proposes a three leveled digital twin model for the systematic PHM of PMSs. The unit-leveled digital twin model of each basic device unit of PMSs is constructed based on edge computing, which can provide real-time monitoring and analysis of the device status. The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters, which are deployed for the manufacturing… More >