Abdul Sattar Laghari¹, Mohammad Waqas Chandio¹, Laveet Kumar^2,*, Mamdouh El Haj Assad³

Energy Engineering, Vol.121, No.8, pp. 2023-2038, 2024, DOI:10.32604/ee.2024.051082

Abstract The selection of working fluid significantly impacts the geothermal ORC’s Efficiency. Using a mixture as a working fluid is a strategy to improve the output of geothermal ORC. In the current study, modelling and thermodynamic analysis of ORC, using geothermal as a heat source, is carried out at fixed operating conditions. The model is simulated in the Engineering Equation Solver (EES). An environment-friendly mixture of fluids, i.e., R245fa/R600a, with a suitable mole fraction, is used as the operating fluid. The mixture provided the most convenient results compared to the pure working fluid under fixed operating More >

Yongguo Li^1,2, Caiyin Xu^1,2,*, Can Qin^1,2, Dingjian Zheng^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1251-1263, 2024, DOI:10.32604/fdmp.2023.044804

Abstract The so-called ORC (Organic Rankine Cycle) heat recovery technology has attracted much attention with regard to medium and low temperature waste heat recovery. In the present study, it is applied to a Tesla turbine. At the same time, the effects of the disc speed, diameter and inter-disc gap on the internal flow field and output power of the turbine are also investigated by means of CFD (Computational Fluid Dynamics) numerical simulation, by which the pressure, velocity, and output efficiency of the internal flow field are obtained under different internal and external conditions. The highest efficiency More >

Simona-Vasilica Oprea^*, Adela Bâra

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3827-3853, 2024, DOI:10.32604/cmc.2024.051598

Abstract The potential of text analytics is revealed by Machine Learning (ML) and Natural Language Processing (NLP) techniques. In this paper, we propose an NLP framework that is applied to multiple datasets to detect malicious Uniform Resource Locators (URLs). Three categories of features, both ML and Deep Learning (DL) algorithms and a ranking schema are included in the proposed framework. We apply frequency and prediction-based embeddings, such as hash vectorizer, Term Frequency-Inverse Dense Frequency (TF-IDF) and predictors, word to vector-word2vec (continuous bag of words, skip-gram) from Google, to extract features from text. Further, we apply more… More >

Gamal A. Elfar^*†, Mohamed A. Ebrahim^‡, Nehal M. Elsherbiny^*, Laila A. Eissa^*

Oncology Research, Vol.25, No.4, pp. 641-650, 2017, DOI:10.3727/096504016X14768398678750

Abstract Osteoprotegerin (OPG) is a robust antiresorptive molecule that acts as a decoy receptor for the receptor activator of nuclear factor kB ligand (RANKL), the mediator of osteoclastogenesis. This study was designed to explore the possible role of serum OPG and RANKL in detecting bone metastasis in breast cancer and its interaction with clinicopathologic parameters. Serum levels of RANKL and OPG were estimated in 44 metastatic and 36 nonmetastatic breast cancer patients using ELISA kits. Serum OPG levels were significantly reduced in patients with bone metastasis and correlated negatively with the number of bone lesions and… More >

Razieh Keshavarzi, Mehdi Jahangiri^*

Energy Engineering, Vol.121, No.6, pp. 1381-1401, 2024, DOI:10.32604/ee.2024.050029

Abstract Nowadays, the use of renewable energies, especially wind, solar, and biomass, is essential as an effective solution to address global environmental and economic challenges. Therefore, the current study examines the energy-economic-environmental analysis of off-grid electricity generation systems using solar panels, wind turbines, and biomass generators in various weather conditions in Iran. Simulations over 25 years were conducted using HOMER v2.81 software, aiming to determine the potential of each region and find the lowest cost of electricity production per kWh. In the end, to identify the most suitable location, the Technique for Order Preference by Similarity… More > Graphic Abstract

Zhonghao Guo^*, Xinyue Xu, Xiangxian Chen

Computer Systems Science and Engineering, Vol.48, No.2, pp. 479-509, 2024, DOI:10.32604/csse.2023.043932

Abstract In software testing, the quality of test cases is crucial, but manual generation is time-consuming. Various automatic test case generation methods exist, requiring careful selection based on program features. Current evaluation methods compare a limited set of metrics, which does not support a larger number of metrics or consider the relative importance of each metric to the final assessment. To address this, we propose an evaluation tool, the Test Case Generation Evaluator (TCGE), based on the learning to rank (L2R) algorithm. Unlike previous approaches, our method comprehensively evaluates algorithms by considering multiple metrics, resulting in… More >

Amal Hkiri^1,*, Mouna Karmani¹, Omar Ben Bahri², Ahmed Mohammed Murayr², Fawaz Hassan Alasmari², Mohsen Machhout¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 227-247, 2024, DOI:10.32604/cmc.2023.047087

Abstract The RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) protocol is essential for efficient communication within the Internet of Things (IoT) ecosystem. Despite its significance, RPL’s susceptibility to attacks remains a concern. This paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the decreased rank attack in both static and mobile network environments. We employ the Random Direction Mobility Model (RDM) for mobile scenarios within the Cooja simulator. Our systematic evaluation focuses on critical performance metrics, including Packet Delivery Ratio (PDR), Average End to End Delay (AE2ED), throughput, Expected Transmission Count More >

Liufeng Du^1,*, Shaoru Shang¹, Linghua Zhang², Chong Li¹, Jianing Yang³, Xiyan Tian¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1749-1767, 2024, DOI:10.32604/cmes.2023.030144

Abstract Due to the fine-grained communication scenarios characterization and stability, Wi-Fi channel state information (CSI) has been increasingly applied to indoor sensing tasks recently. Although spatial variations are explicitly reflected in CSI measurements, the representation differences caused by small contextual changes are easily submerged in the fluctuations of multipath effects, especially in device-free Wi-Fi sensing. Most existing data solutions cannot fully exploit the temporal, spatial, and frequency information carried by CSI, which results in insufficient sensing resolution for indoor scenario changes. As a result, the well-liked machine learning (ML)-based CSI sensing models still struggling with stable More >

Jebran Khan¹, Kashif Ahmad², Kyung-Ah Sohn^1,3,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2869-2894, 2023, DOI:10.32604/csse.2023.040159

Abstract In recent years, the growing popularity of social media platforms has led to several interesting natural language processing (NLP) applications. However, these social media-based NLP applications are subject to different types of adversarial attacks due to the vulnerabilities of machine learning (ML) and NLP techniques. This work presents a new low-level adversarial attack recipe inspired by textual variations in online social media communication. These variations are generated to convey the message using out-of-vocabulary words based on visual and phonetic similarities of characters and words in the shortest possible form. The intuition of the proposed scheme… More >

T. E. Boukelia^1,2,*, A. Bourouis¹, M. E. Abdesselem³, M. S. Mecibah³

Energy Engineering, Vol.120, No.11, pp. 2449-2467, 2023, DOI:10.32604/ee.2023.030183

Abstract Concentrating Solar Power (CSP) plants offer a promising way to generate low-emission energy. However, these plants face challenges such as reduced sunlight during winter and cloudy days, despite being located in high solar radiation areas. Furthermore, their dispatch capacities and yields can be affected by high electricity consumption, particularly at night. The present work aims to develop an off-design model that evaluates the hourly and annual performances of a parabolic trough power plant (PTPP) equipped with a waste heat recovery system. The study aims to compare the performances of this new layout with those of… More >