Pengfei Duan^1,*, Luling Li¹, Jianhui Liu¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012431

Abstract The supply of hydrogen-blended natural gas to civil and industrial users can assist downstream firm to achieve carbon emission reduction, and ensure energy security as an alternative gas source. This application mode has been widely concerned by urban gas enterprises. This paper focuses on the leakage problem of hydrogen-blended pipelines in utility tunnel due to corrosion and other reasons. Using dimensional analysis method, a model experiment is designed to verify that the three-dimensional compressible fluid model coupled with transport equations can effectively simulate the concentration change of hydrogen-blended natural gas after leakage in the utility… More >

Cuiwei Peng¹, Jiahui Chen^2,*, Shicheng Wan³, Guotao Xu⁴

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4341-4360, 2024, DOI:10.32604/cmc.2024.054109 - 12 September 2024

Abstract In today’s highly competitive retail industry, offline stores face increasing pressure on profitability. They hope to improve their ability in shelf management with the help of big data technology. For this, on-shelf availability is an essential indicator of shelf data management and closely relates to customer purchase behavior. RFM (recency, frequency, and monetary) pattern mining is a powerful tool to evaluate the value of customer behavior. However, the existing RFM pattern mining algorithms do not consider the quarterly nature of goods, resulting in unreasonable shelf availability and difficulty in profit-making. To solve this problem, we… More >

Teng Wang, Yao Zhang, Jiangguo Liang, Shuai Wang, Shuanggen Liu^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3891-3907, 2024, DOI:10.32604/cmc.2024.048115 - 26 March 2024

Abstract With the widespread data collection and processing, privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals. Support vector machine (SVM) is one of the most elementary learning models of machine learning. Privacy issues surrounding SVM classifier training have attracted increasing attention. In this paper, we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction, called Fed_DPDR-DPML, which greatly improves data utility while providing strong privacy guarantees. Considering in distributed learning scenarios, multiple participants usually hold unbalanced or small amounts of data. Therefore, Fed_DPDR-DPML enables multiple participants to collaboratively learn a global… More >

Chien-Ming Chen¹, Zhenzhou Zhang¹, Jimmy Ming-Tai Wu¹, Kuruva Lakshmanna^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 733-759, 2023, DOI:10.32604/cmes.2023.027463 - 23 April 2023

Abstract Periodic pattern mining has become a popular research subject in recent years; this approach involves the discovery of frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic pattern mining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodic patterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequences is more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences is important. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. More >

Rupali Gangarde^1,2,*, Amit Sharma³, Ambika Pawar⁴

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2171-2190, 2023, DOI:10.32604/cmc.2023.035559 - 06 February 2023

Abstract Online Social Networks (OSN) sites allow end-users to share a great deal of information, which may also contain sensitive information, that may be subject to commercial or non-commercial privacy attacks. As a result, guaranteeing various levels of privacy is critical while publishing data by OSNs. The clustering-based solutions proved an effective mechanism to achieve the privacy notions in OSNs. But fixed clustering limits the performance and scalability. Data utility degrades with increased privacy, so balancing the privacy utility trade-off is an open research issue. The research has proposed a novel privacy preservation model using the… More >

Salman Naseer¹, Raheela Saleem², Muhammad Mudasar Ghafoor³, Shahzada Khurram⁴, Shafiq Ahmad⁵, Abdelaty Edrees Sayed⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1699-1714, 2023, DOI:10.32604/iasc.2023.034032 - 05 January 2023

Abstract The residential sector contributes a large part of the energy to the global energy balance. To date, housing demand has mostly been uncontrollable and inelastic to grid conditions. Analyzing the performance of a home energy management system requires the creation of various profiles of real-world residential demand, as residential demand is complex and includes multiple factors such as occupancy, climate, user preferences, and appliance types. Average Peak Ratio (A2P) is one of the most important parameters when managing an efficient and cost-effective energy system. At the household level, the larger relative magnitudes of certain energy… More >

V. A. Vijayakumar^*, J. Shanthini, S. Karthik, K. Srihari

Computer Systems Science and Engineering, Vol.45, No.1, pp. 659-669, 2023, DOI:10.32604/csse.2023.028400 - 16 August 2022

Abstract The autonomous driving aims at ensuring the vehicle to effectively sense the environment and use proper strategies to navigate the vehicle without the interventions of humans. Hence, there exist a prediction of the background scenes and that leads to discontinuity between the predicted and planned outputs. An optimal prediction engine is required that suitably reads the background objects and make optimal decisions. In this paper, the author(s) develop an autonomous model for vehicle driving using ensemble model for large Sport Utility Vehicles (SUVs) that uses three different modules involving (a) recognition model, (b) planning model… More >

Yiding Cao

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-16, 2022, DOI:10.5098/hmt.19.2

Abstract This paper introduces a novel air-water thermal power plant working at low temperatures and employing hot water as a heat-supply fluid to produce utility-scale power with high second-law efficiency. The air-water power plant uses both air and water as working fluids and employs a direct-contact mass and heat transfer packing to facilitate latent heat (in terms of vapor) and sensible heat transfer from the hot water to moist air for expansion in a gas turbine to produce power. A cycle analysis indicates that with a heat source temperature of around 100o C, the power plant… More >

Yiding Cao

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-12, 2022, DOI:10.5098/hmt.19.1

Abstract This paper introduces utility-scale underground hot water storage (USUHWS) systems and evaluates their performance to enable renewable energy sources to produce dispatchable utility-scale power or supply heat with minimized interruption and impact by weather conditions. The USUHWS systems could retain the thermal energy content of the stored hot water for years so that renewable energy can be extracted and stored at any time year-round and be used whenever needed. Another major objective of this paper is to introduce hot-water power and heat internets to interconnect storage systems, power plants, energy sources, and various water and More >

S. K. Janarthanan^*, C. Kathirvel

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 33-50, 2022, DOI:10.32604/iasc.2022.023165 - 15 April 2022

Abstract Renewable energy-based power generation, particularly photovoltaic (PV)-connected grid systems, has gained popularity in recent years due to its widespread adoption for residential and commercial customers of all sizes, from kilowatt (KW) to megawatt (MW). The purpose of this work is to demonstrate how an efficient CUK-integrated boost converter with continuous current flow may be used to maximise the output of solar arrays. The constant voltage at the converter output is maintained with increased dynamic performance using a Proportional Integral (PI) controller based on a hybrid optimization technique GWO-PSO (Grey Wolf Optimization-Particle Swarm Optimization). This hybrid More >