Hawazen Alzahrani¹, Tarek Sheltami¹, Abdulaziz Barnawi², Muhammad Imam^2,*, Ansar Yaser³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4703-4728, 2024, DOI:10.32604/cmc.2024.054203 - 12 September 2024

Abstract The Internet of Things (IoT) links various devices to digital services and significantly improves the quality of our lives. However, as IoT connectivity is growing rapidly, so do the risks of network vulnerabilities and threats. Many interesting Intrusion Detection Systems (IDSs) are presented based on machine learning (ML) techniques to overcome this problem. Given the resource limitations of fog computing environments, a lightweight IDS is essential. This paper introduces a hybrid deep learning (DL) method that combines convolutional neural networks (CNN) and long short-term memory (LSTM) to build an energy-aware, anomaly-based IDS. We test this… More >

Juan Li¹, Tingting Xu^1,*, Yi Gu², Chuang Liu¹, Guiping Zhou², Guoliang Bian¹

Energy Engineering, Vol.121, No.10, pp. 2777-2795, 2024, DOI:10.32604/ee.2024.052331 - 11 September 2024

Abstract In fossil energy pollution is serious and the “double carbon” goal is being promoted, as a symbol of fresh energy in the electrical system, solar and wind power have an increasing installed capacity, only conventional units obviously can not solve the new energy as the main body of the scheduling problem. To enhance the system scheduling ability, based on the participation of thermal power units, incorporate the high energy-carrying load of electro-melting magnesium into the regulation object, and consider the effects on the wind unpredictability of the power. Firstly, the operating characteristics of high energy… More >

Saroj Lamichhane¹, Roseline Mostafa², Bhaskaran Gopalakrishnan^2,*, Dayakar G. Devaru³

Energy Engineering, Vol.121, No.10, pp. 2743-2767, 2024, DOI:10.32604/ee.2024.051035 - 11 September 2024

Abstract Building energy performance is a function of numerous building parameters. In this study, sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of buildings. Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool (eQUEST). The model is calibrated using the Normalized Mean Bias Error (NMBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)) method. The model satisfies the NMBE and CV(RMSE) criteria set by… More > Graphic Abstract

Wentao Li¹, Jiantao Liu², Yudun Li³, Guoxin Ming¹, Kaifeng Zhang¹, Kun Yuan^1,*

Energy Engineering, Vol.121, No.9, pp. 2479-2503, 2024, DOI:10.32604/ee.2024.050852 - 19 August 2024

Abstract With the large-scale development and utilization of renewable energy, industrial flexible loads, as a kind of load-side resource with strong regulation ability, provide new opportunities for the research on renewable energy consumption problem in power systems. This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning, aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy, and achieving the safe, stable and economical operation of power grids. Firstly, according to the evaluation index of renewable energy… More >

Mohammed Kaddi^1,*, Mohammed Omari², Moamen Alnatoor¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2611-2631, 2024, DOI:10.32604/cmc.2024.052048 - 15 August 2024

Abstract Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks (WSN). A sensor network comprises several micro-sensors deployed randomly in an area of interest. A micro-sensor is provided with an energy resource to supply electricity to all of its components. However, the disposed energy resource is limited and battery replacement is generally infeasible. With this restriction, the sensors must conserve energy to prolong their lifetime. Various energy conservation strategies for WSNs have been presented in the literature, from the application to the physical layer. Most of these solutions focus only on… More >

Ambika Aggarwal¹, Sunil Kumar^2,3, Ashok Bhansali⁴, Deema Mohammed Alsekait^5,*, Diaa Salama AbdElminaam^6,7,8

Computer Systems Science and Engineering, Vol.48, No.4, pp. 953-967, 2024, DOI:10.32604/csse.2024.050406 - 17 July 2024

Abstract Existing multiple workflow scheduling techniques focus on traditional Quality of Service (QoS) parameters such as cost, deadline, and makespan to find optimal solutions by consuming a large amount of electrical energy. Higher energy consumption decreases system efficiency, increases operational cost, and generates more carbon footprint. These major problems can lead to several problems, such as economic strain, environmental degradation, resource depletion, energy dependence, health impacts, etc. In a cloud computing environment, scheduling multiple workflows is critical in developing a strategy for energy optimization, which is an NP-hard problem. This paper proposes a novel, bi-phase Energy-Efficient… More >

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini³, Sahil Verma³, Kavita³, Ruba Abu Khurma^4,5, Pedro A. Castillo^6,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3757-3782, 2024, DOI:10.32604/cmc.2024.046516 - 20 June 2024

Abstract Cloud computing is a dynamic and rapidly evolving field, where the demand for resources fluctuates continuously. This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments. The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently. By adhering to the proposed resource allocation method, we aim to achieve a substantial reduction in energy consumption. This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most, aligning with the broader goal of… More >

Ming Liu¹, Pinghua Zhu^2,*, Xiancui Yan², Haichao Li², Xintong Chen²

Journal of Renewable Materials, Vol.12, No.2, pp. 329-347, 2024, DOI:10.32604/jrm.2023.045381 - 11 March 2024

Abstract As socioeconomic development continues, the issue of building energy consumption has attracted significant attention, and improving the thermal insulation performance of buildings has become a crucial strategic measure. Simultaneously, the application of solid waste in insulation materials has also become a hot topic. This paper reviews the sources and classifications of solid waste, focusing on research progress in its application as insulation materials in the domains of daily life, agriculture, and industry. The research shows that incorporating household solid waste materials, such as waste glass, paper, and clothing scraps into cementitious thermal insulation can significantly… More >

Noman Khan^1,2, Samee Ullah Khan^1,2, Sung Wook Baik^1,2,*

Computer Systems Science and Engineering, Vol.48, No.1, pp. 153-173, 2024, DOI:10.32604/csse.2023.039407 - 26 January 2024

Abstract Energy management systems for residential and commercial buildings must use an appropriate and efficient model to predict energy consumption accurately. To deal with the challenges in power management, the short-term Power Consumption (PC) prediction for household appliances plays a vital role in improving domestic and commercial energy efficiency. Big data applications and analytics have shown that data-driven load forecasting approaches can forecast PC in commercial and residential sectors and recognize patterns of electric usage in complex conditions. However, traditional Machine Learning (ML) algorithms and their features engineering procedure emphasize the practice of inefficient and ineffective… More >

Jian Ai¹, Jie Xue^1,*, Jiabang Yu^1,2, Xinyu Huang², Pan Wei^1,2, Xiaohu Yang², Bengt Sundén^3,*

Frontiers in Heat and Mass Transfer, Vol.21, pp. 47-63, 2023, DOI:10.32604/fhmt.2023.045134 - 30 November 2023

Abstract The calculation of heat and humidity load serves as the cornerstone of Heating, Ventilation, and Air Conditioning (HVAC) design. Nevertheless, as the heat and humidity load characteristics of underground structures differ substantially from those of above-ground structures, it is a challenge to derive their accurate calculation procedure through engineering experience. Therefore, it is particularly important to carry out quantitative research on heat and humidity load. This study used Design Builder software to study the influence of the design state point of air conditioning in underground buildings on energy consumption. The study showed that compared with More >