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Search Results (115)
  • Open Access


    Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

    Norah Abdullah Al-Johany1,*, Sanaa Abdullah Sharaf1,2, Fathy Elbouraey Eassa1,2, Reem Abdulaziz Alnanih1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3139-3173, 2024, DOI:10.32604/cmc.2024.047392

    Abstract The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memory systems. However, MPI implementations can contain defects that impact the reliability and performance of parallel applications. Detecting and correcting these defects is crucial, yet there is a lack of published models specifically designed for correcting MPI defects. To address this, we propose a model for detecting and correcting MPI defects (DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blocking point-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defects addressed by… More >

  • Open Access


    Machine learning and bioinformatics to identify biomarkers in response to Burkholderia pseudomallei infection in mice


    BIOCELL, Vol.48, No.4, pp. 613-621, 2024, DOI:10.32604/biocell.2024.031539

    Abstract Objective: In the realm of Class I pathogens, Burkholderia pseudomallei (BP) stands out for its propensity to induce severe pathogenicity. Investigating the intricate interactions between BP and host cells is imperative for comprehending the dynamics of BP infection and discerning biomarkers indicative of the host cell response process. Methods: mRNA extraction from BP-infected mouse macrophages constituted the initial step of our study. Employing gene expression arrays, the extracted RNA underwent conversion into digital signals. The percentile shift method facilitated data processing, with the identification of genes manifesting significant differences accomplished through the application of the t-test. Subsequently,… More >

  • Open Access


    Bronchoalveolar lavage fluid metagenomic next-generation sequencing assay for identifying pathogens in lung cancer patients


    BIOCELL, Vol.48, No.4, pp. 623-637, 2024, DOI:10.32604/biocell.2024.030420

    Abstract Background: For patients with lung cancer, timely identification of new lung lesions as infectious or non-infectious, and accurate identification of pathogens is very important in improving OS of patients. As a new auxiliary examination, metagenomic next-generation sequencing (mNGS) is believed to be more accurate in diagnosing infectious diseases in patients without underlying diseases, compared with conventional microbial tests (CMTs). We designed this study to find out whether mNGS has better performance in distinguishing infectious and non-infectious diseases in lung cancer patients using bronchoalveolar lavage fluid (BALF). Materials and Methods: This study was a real-world retrospective review… More >

  • Open Access


    Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

    Chanumolu Kiran Kumar, Nandhakumar Ramachandran*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3151-3176, 2024, DOI:10.32604/cmc.2023.043534

    Abstract Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions, vulnerabilities, and assaults. Complex security systems, such as Intrusion Detection Systems (IDS), are essential due to the limitations of simpler security measures, such as cryptography and firewalls. Due to their compact nature and low energy reserves, wireless networks present a significant challenge for security procedures. The features of small cells can cause threats to the network. Network Coding (NC) enabled small cells are vulnerable to various types of attacks. Avoiding attacks and performing secure “peer” to “peer” data transmission is… More >

  • Open Access


    Effet modérateur de la perception de menace du cancer du sein sur la relation entre les connaissances et l’autopalpation

    Carolle Annie Njopvoui*, Armel Valdin Teague Tsopgny, Henri Rodrigue Njengoue Ngamaleu

    Psycho-Oncologie, Vol.18, No.1, pp. 59-68, 2024, DOI:10.32604/po.2023.047499

    Abstract Estimated at more than 2.2 million cases worldwide, most breast cancer cases and deaths from breast cancer occur in low and middle-income countries. In Cameroon, many studies have underlined the effect of knowledge of breast cancer on screening measures such as self-examination and, to a lesser extent, the perception of the threat of this disease. This research aims to assess according to the Health Belief Model (HBM), the moderating effect of perceived threat of breast cancer on the relation between knowledge and breast self-examination. A questionnaire survey was conducted among 517 Cameroonian women to assess… More >

  • Open Access


    Démocratie en santé et narration : une synthèse des connaissances

    Rossi Silvia1,2,*, Sandrine de Montgolfier1,3, Joëlle Kivits4

    Psycho-Oncologie, Vol.18, No.1, pp. 33-41, 2024, DOI:10.32604/po.2024.042709

    Abstract Objectif: La démocratie en santé nécessite de disposer d’outils et de méthodologies pour impliquer les acteurs non scientifiques dans l’élaboration et la mise en œuvre des politiques de santé. La narration pourrait être un des outils qui permettent de rendre la démocratie en santé effective. Notre objectif est de voir comment la narration est mobilisée en lien avec la démocratie en santé, de décrire les objectifs de son usage, la méthodologie adoptée et les résultats obtenus. Matériel et méthodes: Nous avons réalisé une revue de la littérature narrative. Notre équation de recherche a été composée par le… More >

  • Open Access


    Editorial: Welcome Message from Editor-in-Chief, Xuming Mo

    Xuming Mo*

    Congenital Heart Disease, Vol.19, No.1, pp. 1-3, 2024, DOI:10.32604/chd.2024.051192

    Abstract This article has no abstract. More >

  • Open Access


    Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNN Model

    Qi Zhuang1,*, Dong Liu2, Zhuo Chen3

    Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054

    Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets More >

  • Open Access


    A Time Series Intrusion Detection Method Based on SSAE, TCN and Bi-LSTM

    Zhenxiang He*, Xunxi Wang, Chunwei Li

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 845-871, 2024, DOI:10.32604/cmc.2023.046607

    Abstract In the fast-evolving landscape of digital networks, the incidence of network intrusions has escalated alarmingly. Simultaneously, the crucial role of time series data in intrusion detection remains largely underappreciated, with most systems failing to capture the time-bound nuances of network traffic. This leads to compromised detection accuracy and overlooked temporal patterns. Addressing this gap, we introduce a novel SSAE-TCN-BiLSTM (STL) model that integrates time series analysis, significantly enhancing detection capabilities. Our approach reduces feature dimensionality with a Stacked Sparse Autoencoder (SSAE) and extracts temporally relevant features through a Temporal Convolutional Network (TCN) and Bidirectional Long… More >

  • Open Access


    An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

    Syeda Wajiha Zahra1, Muhammad Nadeem2, Ali Arshad3,*, Saman Riaz3, Muhammad Abu Bakr4, Ashit Kumar Dutta5, Zaid Alzaid6, Badr Almutairi7, Sultan Almotairi8

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 589-616, 2024, DOI:10.32604/cmc.2023.042386

    Abstract Various organizations store data online rather than on physical servers. As the number of user’s data stored in cloud servers increases, the attack rate to access data from cloud servers also increases. Different researchers worked on different algorithms to protect cloud data from replay attacks. None of the papers used a technique that simultaneously detects a full-message and partial-message replay attack. This study presents the development of a TKN (Text, Key and Name) cryptographic algorithm aimed at protecting data from replay attacks. The program employs distinct ways to encrypt plain text [P], a user-defined Key… More >

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