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  • Open Access

    PROCEEDINGS

    How to Design Engineered Organs to Enhance Physiological Function

    Qi Gu1,2,3,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012648

    Abstract In the complex field of organ fabrication, which combines developmental biology, bioinspired engineering, and regenerative medicine, the main goal is to closely mimic the detailed structure and function of natural organs. While advanced techniques like 3D bioprinting have made significant strides but often fall short in accurately emulating the dynamic, self-organizing processes fundamental to organogenesis, particularly the nuanced patterns of cellular motility and spatial organization [1]. This issue highlights a big challenge in tissue engineering: making synthetic organs that truly match their natural models. Our work aims to bring together principles of developmental biology with… More >

  • Open Access

    REVIEW

    A Systematic Review of Automated Classification for Simple and Complex Query SQL on NoSQL Database

    Nurhadi, Rabiah Abdul Kadir*, Ely Salwana Mat Surin, Mahidur R. Sarker*

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1405-1435, 2024, DOI:10.32604/csse.2024.051851 - 22 November 2024

    Abstract A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of data. It accumulates substantial volumes of data and employs advanced analytics to correlate data from diverse origins containing various forms of semi-structured, structured, and unstructured information. These systems use a flat architecture and run different types of data analytics. NoSQL databases are nontabular and store data in a different manner than the relational table. NoSQL databases come in various forms, including key-value pairs, documents, wide columns, and graphs, each based on its data model. They offer simpler scalability and generally outperform… More >

  • Open Access

    ARTICLE

    Classification of Cybersecurity Threats, Vulnerabilities and Countermeasures in Database Systems

    Mohammed Amin Almaiah1,*, Leen Mohammad Saqr1, Leen Ahmad Al-Rawwash1, Layan Ahmed Altellawi1, Romel Al-Ali2,*, Omar Almomani3

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3189-3220, 2024, DOI:10.32604/cmc.2024.057673 - 18 November 2024

    Abstract Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store. Despite the increasing reliance on database management systems, this field continues to face numerous cyber-attacks. Database management systems serve as the foundation of any information system or application. Any cyber-attack can result in significant damage to the database system and loss of sensitive data. Consequently, cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats. Risk assessment aids in understanding… More >

  • Open Access

    ARTICLE

    Enhancing AI System Privacy: An Automatic Tool for Achieving GDPR Compliance in NoSQL Databases

    Yifei Zhao, Zhaohui Li, Siyi Lv*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 217-234, 2024, DOI:10.32604/cmc.2024.052310 - 18 July 2024

    Abstract The EU’s Artificial Intelligence Act (AI Act) imposes requirements for the privacy compliance of AI systems. AI systems must comply with privacy laws such as the GDPR when providing services. These laws provide users with the right to issue a Data Subject Access Request (DSAR). Responding to such requests requires database administrators to identify information related to an individual accurately. However, manual compliance poses significant challenges and is error-prone. Database administrators need to write queries through time-consuming labor. The demand for large amounts of data by AI systems has driven the development of NoSQL databases.… More >

  • Open Access

    ARTICLE

    Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

    Shuming Sha1,2, Naiwang Guo3, Wang Luo1,2, Yong Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5105-5124, 2024, DOI:10.32604/cmc.2024.049584 - 20 June 2024

    Abstract This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies. Unlike independent batch tasks, workflows typically consist of multiple subtasks with intrinsic correlations and dependencies. It necessitates the distribution of various computational tasks to appropriate computing node resources in accordance with task dependencies to ensure the smooth completion of the entire workflow. Workflow scheduling must consider an array of factors, including task dependencies, availability of computational resources, and the schedulability of tasks. Therefore, this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based… More >

  • Open Access

    REVIEW

    Computational and bioinformatics tools for understanding disease mechanisms

    MOHD ATHAR1,*, ANU MANHAS2, NISARG RANA2, AHMAD IRFAN3

    BIOCELL, Vol.48, No.6, pp. 935-944, 2024, DOI:10.32604/biocell.2024.049891 - 10 June 2024

    Abstract Computational methods have significantly transformed biomedical research, offering a comprehensive exploration of disease mechanisms and molecular protein functions. This article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease states. The utilization of protein/gene interaction and genetic variation databases, coupled with pathway analysis can facilitate the identification of potential drug targets. By bridging the gap between molecular-level information and disease understanding, this review contributes insights into the impactful utilization of computational methods, paving the way for More >

  • Open Access

    ARTICLE

    A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

    Hao Jiang1, Yuerong Liao1, Dongdong Zhao2, Wenjian Luo3, Xingyi Zhang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1045-1075, 2024, DOI:10.32604/cmes.2024.048653 - 16 April 2024

    Abstract Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the… More >

  • Open Access

    ARTICLE

    A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

    Nilkanth Mukund Deshpande1,2, Shilpa Gite3,4,*, Biswajeet Pradhan5,6, Abdullah Alamri7, Chang-Wook Lee8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 593-631, 2024, DOI:10.32604/cmes.2023.030704 - 30 December 2023

    Abstract Infection of leukemia in humans causes many complications in its later stages. It impairs bone marrow’s ability to produce blood. Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case. The binary classification is employed to distinguish between normal and leukemia-infected cells. In addition, various subtypes of leukemia require different treatments. These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia. This entails using multi-class classification to determine the leukemia subtype. This is usually done using a microscopic examination of these blood… More > Graphic Abstract

    A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

  • Open Access

    ARTICLE

    CHDTEPDB: Transcriptome Expression Profile Database and Interactive Analysis Platform for Congenital Heart Disease

    Ziguang Song1,2, Jiangbo Yu1, Mengmeng Wang3, Weitao Shen4, Chengcheng Wang1, Tianyi Lu1, Gaojun Shan1, Guo Dong1, Yiru Wang1, Jiyi Zhao1,*

    Congenital Heart Disease, Vol.18, No.6, pp. 693-701, 2023, DOI:10.32604/chd.2024.048081 - 19 January 2024

    Abstract CHDTEPDB (URL: ) is a manually integrated database for congenital heart disease (CHD) that stores the expression profiling data of CHD derived from published papers, aiming to provide rich resources for investigating a deeper correlation between human CHD and aberrant transcriptome expression. The development of human diseases involves important regulatory roles of RNAs, and expression profiling data can reflect the underlying etiology of inherited diseases. Hence, collecting and compiling expression profiling data is of critical significance for a comprehensive understanding of the mechanisms and functions that underpin genetic diseases. CHDTEPDB stores the expression profiles of… More >

  • Open Access

    ARTICLE

    Fusion of Hash-Based Hard and Soft Biometrics for Enhancing Face Image Database Search and Retrieval

    Ameerah Abdullah Alshahrani*, Emad Sami Jaha, Nahed Alowidi

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3489-3509, 2023, DOI:10.32604/cmc.2023.044490 - 26 December 2023

    Abstract The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade, owing to the continuing advances in image processing and computer vision approaches. In multiple real-life applications, for example, social media, content-based face picture retrieval is a well-invested technique for large-scale databases, where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of pictures. Humans widely employ faces for recognizing and identifying people. Thus, face recognition through formal or personal pictures is increasingly used in various real-life applications,… More >

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