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  • Open Access

    ARTICLE

    Optimizing Optical Fiber Faults Detection: A Comparative Analysis of Advanced Machine Learning Approaches

    Kamlesh Kumar Soothar1,2, Yuanxiang Chen1,2,*, Arif Hussain Magsi3, Cong Hu1, Hussain Shah1

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2697-2721, 2024, DOI:10.32604/cmc.2024.049607

    Abstract Efficient optical network management poses significant importance in backhaul and access network communication for preventing service disruptions and ensuring Quality of Service (QoS) satisfaction. The emerging faults in optical networks introduce challenges that can jeopardize the network with a variety of faults. The existing literature witnessed various partial or inadequate solutions. On the other hand, Machine Learning (ML) has revolutionized as a promising technique for fault detection and prevention. Unlike traditional fault management systems, this research has three-fold contributions. First, this research leverages the ML and Deep Learning (DL) multi-classification system and evaluates their accuracy… More >

  • Open Access

    ARTICLE

    Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

    Umer Nauman1, Yuhong Zhang2, Zhihui Li3, Tong Zhen1,3,*

    Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 15-34, 2024, DOI:10.32604/jimh.2024.048784

    Abstract The convergence of handheld devices and cloud-based computing has transformed how Electronic Health Records (EHRs) are stored in mobile cloud paradigms, offering benefits such as affordability, adaptability, and portability. However, it also introduces challenges regarding network security and data confidentiality, as it aims to exchange EHRs among mobile users while maintaining high levels of security. This study proposes an innovative blockchain-based solution to these issues and presents secure cloud storage for healthcare data. To provide enhanced cryptography, the proposed method combines an enhanced Blowfish encryption method with a new key generation technique called Elephant Herding… More >

  • Open Access

    ARTICLE

    Comparative Analysis of Reaction to Fire and Flammability of Hemp Shives Insulation Boards with Incorporated Microencapsulated Phase Change Materials

    Inga Zotova1,*, Edgars Kirilovs1, Laura Ziemele2

    Journal of Renewable Materials, Vol.12, No.3, pp. 603-613, 2024, DOI:10.32604/jrm.2024.047607

    Abstract Nowadays buildings contain innovative materials, materials from local resources, production surpluses and rapidly renewable natural resources. Phase Change Materials (PCM) are one such group of novel materials which reduce building energy consumption. With the wider availability of microencapsulated PCM, there is an opportunity to develop a new type of insulating materials, combinate PCM with traditional insulation materials for latent heat energy storage. These materials are typically flammable and are located on the interior wall finishing yet there has been no detailed assessment of their fire performance. In this research work prototypes of low-density insulating boards… More > Graphic Abstract

    Comparative Analysis of Reaction to Fire and Flammability of Hemp Shives Insulation Boards with Incorporated Microencapsulated Phase Change Materials

  • Open Access

    ARTICLE

    Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

    Qing Ai1,2, Hao Tian2,3,*, Hui Wang1,*, Qing Lang1, Xingchun Huang1, Xinghong Jiang4, Qiang Jing5

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1797-1827, 2024, DOI:10.32604/cmes.2023.045251

    Abstract Structural Health Monitoring (SHM) systems have become a crucial tool for the operational management of long tunnels. For immersed tunnels exposed to both traffic loads and the effects of the marine environment, efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge. This study proposed a model-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel. Firstly, a dynamic predictive model-based anomaly detection method is proposed, which utilizes a rolling time window for modeling to achieve… More >

  • Open Access

    ARTICLE

    Comparative Analysis of the Transcriptome and Metabolome in Leaves of Diploid and Tetraploid Fagopyrum tataricum

    Xiaodong Shi1,*, Yue Qi1, Liangzhu Lin1, Jia Wang1, Xiaobo Qin2, Bei Niu3,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 3149-3162, 2023, DOI:10.32604/phyton.2023.027324

    Abstract Tartary buckwheat (Fagopyrum tataricum) is a dual-purpose medicinal and food crop grown for its high contents of functional compounds and abundant nutrients. Although studies have shown the differences of total flavonoid content in Tartary buckwheat at different ploidy levels, the composition of flavonoid and its regulatory mechanisms are largely unknown. In this study, the leaf metabolome and transcriptome of diploid and tetraploid accessions of Tartary buckwheat were analyzed to gain insight into the impact of polyploidization on comparative secondary metabolite composition and molecular regulatory mechanism. Based on a widely targeted metabolomics analysis, a total of 792… More >

  • Open Access

    ARTICLE

    Comparative Analysis of Machine Learning Models for PDF Malware Detection: Evaluating Different Training and Testing Criteria

    Bilal Khan1, Muhammad Arshad2, Sarwar Shah Khan3,4,*

    Journal of Cyber Security, Vol.5, pp. 1-11, 2023, DOI:10.32604/jcs.2023.042501

    Abstract The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks. Portable Document Format (PDF) files have emerged as a major attack vector for malware due to their adaptability and wide usage. Detecting malware in PDF files is challenging due to its ability to include various harmful elements such as embedded scripts, exploits, and malicious URLs. This paper presents a comparative analysis of machine learning (ML) techniques, including Naive Bayes (NB), K-Nearest Neighbor (KNN), Average One Dependency Estimator (A1DE), Random Forest (RF), and Support Vector Machine (SVM) for More >

  • Open Access

    ARTICLE

    Comparative Analysis of COVID-19 Detection Methods Based on Neural Network

    Inès Hilali-Jaghdam1,*, Azhari A Elhag2, Anis Ben Ishak3, Bushra M. Elamin Elnaim4, Omer Eltag Mohammed Elhag5, Feda Muhammed Abuhaimed1, S. Abdel-Khalek2,6

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1127-1150, 2023, DOI:10.32604/cmc.2023.038915

    Abstract In 2019, the novel coronavirus disease 2019 (COVID-19) ravaged the world. As of July 2021, there are about 192 million infected people worldwide and 4.1365 million deaths. At present, the new coronavirus is still spreading and circulating in many places around the world, especially since the emergence of Delta variant strains has increased the risk of the COVID-19 pandemic again. The symptoms of COVID-19 are diverse, and most patients have mild symptoms, with fever, dry cough, and fatigue as the main manifestations, and about 15.7% to 32.0% of patients will develop severe symptoms. Patients are… More >

  • Open Access

    ARTICLE

    Comparative Analysis for Evaluating Wind Energy Resources Using Intelligent Optimization Algorithms and Numerical Methods

    Musaed Alrashidi*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 491-513, 2023, DOI:10.32604/csse.2023.038628

    Abstract Statistical distributions are used to model wind speed, and the two-parameters Weibull distribution has proven its effectiveness at characterizing wind speed. Accurate estimation of Weibull parameters, the scale (c) and shape (k), is crucial in describing the actual wind speed data and evaluating the wind energy potential. Therefore, this study compares the most common conventional numerical (CN) estimation methods and the recent intelligent optimization algorithms (IOA) to show how precise estimation of c and k affects the wind energy resource assessments. In addition, this study conducts technical and economic feasibility studies for five sites in the northern… More >

  • Open Access

    ARTICLE

    Comparative Analysis of Execution of CNN-Based Sanguine Data Transmission with LSB-SS and PVD-SS

    Alaknanda S. Patil1,*, G. Sundari1, Arun Kumar Sivaraman2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1707-1721, 2023, DOI:10.32604/csse.2023.034270

    Abstract The intact data transmission to the authentic user is becoming crucial at every moment in the current era. Steganography; is a technique for concealing the hidden message in any cover media such as image, video; and audio to increase the protection of data. The resilience and imperceptibility are improved by choosing an appropriate embedding position. This paper gives a novel system to immerse the secret information in different videos with different methods. An audio and video steganography with novel amalgamations are implemented to immerse the confidential auditory information and the authentic user’s face image. A… More >

  • Open Access

    ARTICLE

    Structural characterization of four Rhododendron spp. chloroplast genomes and comparative analyses with other azaleas

    XIAOJUN ZHOU1,*, MENGXUE LIU1, LINLIN SONG2

    BIOCELL, Vol.47, No.3, pp. 657-668, 2023, DOI:10.32604/biocell.2023.026781

    Abstract Azalea is a general designation of Rhododendron in the Ericaceae family. Rhododendron not only has high ornamental value but also has application value in ecological protection, medicine, and scientific research. In this study, we used Illumina and PacBio sequencing to assemble and annotate the entire chloroplast genomes (cp genomes) of four Rhododendron species. The chloroplast genomes of R. concinnum, R. henanense subsp. lingbaoense, R. micranthum, and R. simsii were assembled into 207,236, 208,015, 207,233, and 206,912 bp, respectively. All chloroplast genomes contain eight rRNA genes, with either 88 or 89 protein-coding genes. The four cp genomes were compared and analyzed by More >

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