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  • Open Access


    Decision Making Based on Valued Fuzzy Superhypergraphs

    Mohammad Hamidi1,*, Florentin Smarandache2, Mohadeseh Taghinezhad1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1907-1923, 2024, DOI:10.32604/cmes.2023.030284

    Abstract This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept. We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole to the whole group of objects at the same time.… More >

  • Open Access


    Experimental and Numerical Investigation on the Aerodynamic Characteristics of High-Speed Pantographs with Supporting Beam Wind Deflectors

    Shiyang Song1,*, Tongxin Han2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 127-145, 2024, DOI:10.32604/fdmp.2023.030137

    Abstract Aiming to mitigate the aerodynamic lift force imbalance between pantograph strips, which exacerbates wear and affects the current collection performance of the pantograph-catenary system, a study has been conducted to support the beam deflector optimization using a combination of experimental measurements and computational fluid dynamics (CFD) simulations. The results demonstrate that the size, position, and installation orientation of the wind deflectors significantly influence the amount of force compensation. They also indicate that the front strip deflectors should be installed downwards and the rear strip deflectors upwards, thereby forming a “π” shape. Moreover, the lift force compensation provided by the wind… More >

  • Open Access


    Graph-Based Feature Learning for Cross-Project Software Defect Prediction

    Ahmed Abdu1, Zhengjun Zhai1,2, Hakim A. Abdo3, Redhwan Algabri4,*, Sungon Lee5,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 161-180, 2023, DOI:10.32604/cmc.2023.043680

    Abstract Cross-project software defect prediction (CPDP) aims to enhance defect prediction in target projects with limited or no historical data by leveraging information from related source projects. The existing CPDP approaches rely on static metrics or dynamic syntactic features, which have shown limited effectiveness in CPDP due to their inability to capture higher-level system properties, such as complex design patterns, relationships between multiple functions, and dependencies in different software projects, that are important for CPDP. This paper introduces a novel approach, a graph-based feature learning model for CPDP (GB-CPDP), that utilizes NetworkX to extract features and learn representations of program entities… More >

  • Open Access


    An Innovative Technique for Constructing Highly Non-Linear Components of Block Cipher for Data Security against Cyber Attacks

    Abid Mahboob1, Muhammad Asif2, Rana Muhammad Zulqarnain3,*, Imran Siddique4, Hijaz Ahmad5, Sameh Askar6, Giovanni Pau7

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2547-2562, 2023, DOI:10.32604/csse.2023.040855

    Abstract The rapid advancement of data in web-based communication has created one of the biggest issues concerning the security of data carried over the internet from unauthorized access. To improve data security, modern cryptosystems use substitution-boxes. Nowadays, data privacy has become a key concern for consumers who transfer sensitive data from one place to another. To address these problems, many companies rely on cryptographic techniques to secure data from illegal activities and assaults. Among these cryptographic approaches, AES is a well-known algorithm that transforms plain text into cipher text by employing substitution box (S-box). The S-box disguises the relationship between cipher… More >

  • Open Access


    Chest Radiographs Based Pneumothorax Detection Using Federated Learning

    Ahmad Almadhor1,*, Arfat Ahmad Khan2, Chitapong Wechtaisong3,*, Iqra Yousaf4, Natalia Kryvinska5, Usman Tariq6, Haithem Ben Chikha1

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1775-1791, 2023, DOI:10.32604/csse.2023.039007

    Abstract Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse, causing air to enter the pleural cavity, the area close to the lungs and chest wall. The most persistent disease, as well as one that necessitates particular patient care and the privacy of their health records. The radiologists find it challenging to diagnose pneumothorax due to the variations in images. Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems. However, it is challenging to employ it in the medical field due to privacy issues and a lack of data. To address this issue, a… More >

  • Open Access


    Leveraging Multimodal Ensemble Fusion-Based Deep Learning for COVID-19 on Chest Radiographs

    Mohamed Yacin Sikkandar1,*, K. Hemalatha2, M. Subashree3, S. Srinivasan4, Seifedine Kadry5,6,7, Jungeun Kim8, Keejun Han9

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 873-889, 2023, DOI:10.32604/csse.2023.035730

    Abstract Recently, COVID-19 has posed a challenging threat to researchers, scientists, healthcare professionals, and administrations over the globe, from its diagnosis to its treatment. The researchers are making persistent efforts to derive probable solutions for managing the pandemic in their areas. One of the widespread and effective ways to detect COVID-19 is to utilize radiological images comprising X-rays and computed tomography (CT) scans. At the same time, the recent advances in machine learning (ML) and deep learning (DL) models show promising results in medical imaging. Particularly, the convolutional neural network (CNN) model can be applied to identifying abnormalities on chest radiographs.… More >

  • Open Access


    MoGUS, un outil de modélisation et d’analyse comparative des trames urbaines

    Dominique Badariotti, Cyril Meyer, Yasmina Ramrani

    Revue Internationale de Géomatique, Vol.30, No.2, pp. 181-213, 2020, DOI:10.3166/rig.2021.00109

    Abstract In this paper, we propose a model and a methodology for the analysis of urban fabrics, sets of built morphological units articulated together by urban networks. The core of the paper presents the MoGUS model (Model Generator & analyser for Urban Simulation) and its formalization. This model jointly represents the buildings and the viaires networks of a city in a graph, and allows a comparative analysis of the properties of different urban fabrics, using derived indicators. A study plan applied to four types of archetypal urban fabrics (Hippodamean, medieval, radio-concentric, Haussmannic) generated with the MoGUS tool is presented to illustrate… More >

  • Open Access


    Pythagorean Neutrosophic Planar Graphs with an Application in Decision-Making

    P. Chellamani1,2,*, D. Ajay1, Mohammed M. Al-Shamiri3,4, Rashad Ismail3,4

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4935-4953, 2023, DOI:10.32604/cmc.2023.036321

    Abstract Graph theory has a significant impact and is crucial in the structure of many real-life situations. To simulate uncertainty and ambiguity, many extensions of graph theoretical notions were created. Planar graphs play a vital role in modelling which has the property of non-crossing edges. Although crossing edges benefit, they have some drawbacks, which paved the way for the introduction of planar graphs. The overall purpose of the study is to contribute to the conceptual development of the Pythagorean Neutrosophic graph. The basic methodology of our research is the incorporation of the analogous concepts of planar graphs in the Pythagorean Neutrosophic… More >

  • Open Access


    The Correlation Coefficient of Hesitancy Fuzzy Graphs in Decision Making

    N. Rajagopal Reddy, S. Sharief Basha*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 579-596, 2023, DOI:10.32604/csse.2023.034527

    Abstract The hesitancy fuzzy graphs (HFGs), an extension of fuzzy graphs, are useful tools for dealing with ambiguity and uncertainty in issues involving decision-making (DM). This research implements a correlation coefficient measure (CCM) to assess the strength of the association between HFGs in this article since CCMs have a high capacity to process and interpret data. The CCM that is proposed between the HFGs has better qualities than the existing ones. It lowers restrictions on the hesitant fuzzy elements’ length and may be used to establish whether the HFGs are connected negatively or favorably. Additionally, a CCM-based attribute DM approach is… More >

  • Open Access


    Computing Connected Resolvability of Graphs Using Binary Enhanced Harris Hawks Optimization

    Basma Mohamed1,*, Linda Mohaisen2, Mohamed Amin1

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2349-2361, 2023, DOI:10.32604/iasc.2023.032930

    Abstract In this paper, we consider the NP-hard problem of finding the minimum connected resolving set of graphs. A vertex set B of a connected graph G resolves G if every vertex of G is uniquely identified by its vector of distances to the vertices in B. A resolving set B of G is connected if the subgraph induced by B is a nontrivial connected subgraph of G. The cardinality of the minimal resolving set is the metric dimension of G and the cardinality of minimum connected resolving set is the connected metric dimension of G. The problem is solved heuristically… More >

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