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  • Open Access

    ARTICLE

    Detecting Malicious Uniform Resource Locators Using an Applied Intelligence Framework

    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 >

  • Open Access

    ARTICLE

    Synergizing Wind, Solar, and Biomass Power: Ranking Analysis of Off-Grid System for Different Weather Conditions of Iran

    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

    Synergizing Wind, Solar, and Biomass Power: Ranking Analysis of Off-Grid System for Different Weather Conditions of Iran

  • Open Access

    ARTICLE

    Multi-Criteria Decision-Making for Power Grid Construction Project Investment Ranking Based on the Prospect Theory Improved by Rewarding Good and Punishing Bad Linear Transformation

    Shun Ma1, Na Yu1, Xiuna Wang2, Shiyan Mei1, Mingrui Zhao2,*, Xiaoyu Han2

    Energy Engineering, Vol.120, No.10, pp. 2369-2392, 2023, DOI:10.32604/ee.2023.028727

    Abstract Using the improved prospect theory with the linear transformations of rewarding good and punishing bad (RGPBIT), a new investment ranking model for power grid construction projects (PGCPs) is proposed. Given the uncertainty of each index value under the market environment, fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones. Taking into account decision-maker’s subjective risk attitudes, a multi-criteria decision-making (MCDM) method based on improved prospect theory is proposed. First, the [−1, 1] RGPBIT operator is proposed to normalize the original data, to obtain the best and worst More >

  • Open Access

    ARTICLE

    Fusion of Feature Ranking Methods for an Effective Intrusion Detection System

    Seshu Bhavani Mallampati1, Seetha Hari2,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1721-1744, 2023, DOI:10.32604/cmc.2023.040567

    Abstract Expanding internet-connected services has increased cyberattacks, many of which have grave and disastrous repercussions. An Intrusion Detection System (IDS) plays an essential role in network security since it helps to protect the network from vulnerabilities and attacks. Although extensive research was reported in IDS, detecting novel intrusions with optimal features and reducing false alarm rates are still challenging. Therefore, we developed a novel fusion-based feature importance method to reduce the high dimensional feature space, which helps to identify attacks accurately with less false alarm rate. Initially, to improve training data quality, various preprocessing techniques are… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Optimization Algorithm for Materialized View Selection from Data Warehouse Environments

    Popuri Srinivasarao, Aravapalli Rama Satish*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1527-1547, 2023, DOI:10.32604/csse.2023.038951

    Abstract Responding to complex analytical queries in the data warehouse (DW) is one of the most challenging tasks that require prompt attention. The problem of materialized view (MV) selection relies on selecting the most optimal views that can respond to more queries simultaneously. This work introduces a combined approach in which the constraint handling process is combined with metaheuristics to select the most optimal subset of DW views from DWs. The proposed work initially refines the solution to enable a feasible selection of views using the ensemble constraint handling technique (ECHT). The constraints such as self-adaptive… More >

  • Open Access

    ARTICLE

    Modified Computational Ranking Model for Cloud Trust Factor Using Fuzzy Logic

    Lei Shen*, Ting Huang, Nishui Cai, Hao Wu

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 507-524, 2023, DOI:10.32604/iasc.2023.037640

    Abstract Through the use of the internet and cloud computing, users may access their data as well as the programmes they have installed. It is now more challenging than ever before to choose which cloud service providers to take advantage of. When it comes to the dependability of the cloud infrastructure service, those who supply cloud services, as well as those who seek cloud services, have an equal responsibility to exercise utmost care. Because of this, further caution is required to ensure that the appropriate values are reached in light of the ever-increasing need for correct… More >

  • Open Access

    ARTICLE

    Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

    P. Venkatesh1,*, N. Visali2

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1001-1012, 2023, DOI:10.32604/iasc.2023.036268

    Abstract In the conventional technique, in the evaluation of the severity index, clustering and loading suffer from more iteration leading to more computational delay. Hence this research article identifies, a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects. The polynomial load modelling or ZIP (constant impedances (Z), Constant Current (I) and Constant active power (P)) is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security. The process of finding the severity of the line using a Hybrid Line Stability Ranking… More >

  • Open Access

    ARTICLE

    Google Scholar University Ranking Algorithm to Evaluate the Quality of Institutional Research

    Noor Ul Sabah1, Muhammad Murad Khan1,*, Ramzan Talib1, Muhammad Anwar2, Muhammad Sheraz Arshad Malik3, Puteri Nor Ellyza Nohuddin4

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4955-4972, 2023, DOI:10.32604/cmc.2023.037436

    Abstract Education quality has undoubtedly become an important local and international benchmark for education, and an institute’s ranking is assessed based on the quality of education, research projects, theses, and dissertations, which has always been controversial. Hence, this research paper is influenced by the institutes ranking all over the world. The data of institutes are obtained through Google Scholar (GS), as input to investigate the United Kingdom’s Research Excellence Framework (UK-REF) process. For this purpose, the current research used a Bespoke Program to evaluate the institutes’ ranking based on their source. The bespoke program requires changes… More >

  • Open Access

    ARTICLE

    Advanced DAG-Based Ranking (ADR) Protocol for Blockchain Scalability

    Tayyaba Noreen1,*, Qiufen Xia1, Muhammad Zeeshan Haider2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2593-2613, 2023, DOI:10.32604/cmc.2023.036139

    Abstract In the past decade, blockchain has evolved as a promising solution to develop secure distributed ledgers and has gained massive attention. However, current blockchain systems face the problems of limited throughput, poor scalability, and high latency. Due to the failure of consensus algorithms in managing nodes’identities, blockchain technology is considered inappropriate for many applications, e.g., in IoT environments, because of poor scalability. This paper proposes a blockchain consensus mechanism called the Advanced DAG-based Ranking (ADR) protocol to improve blockchain scalability and throughput. The ADR protocol uses the directed acyclic graph ledger, where nodes are placed… More >

  • Open Access

    ARTICLE

    Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

    Weijun Li1, Xin Die2, Zhicheng Ma3, Jinping Zhang3, Haiying Dong1,*

    Energy Engineering, Vol.120, No.4, pp. 1001-1022, 2023, DOI:10.32604/ee.2023.024426

    Abstract Aiming at the problems of large-scale wind and solar grid connection, how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations, a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed. Firstly, the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output, obtains the optimal output value under the economic conditions of each new energy station, and then obtains the… More > Graphic Abstract

    Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

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