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  • Open Access

    ARTICLE

    Data Security Storage Mechanism Based on Blockchain Network

    Jin Wang1, Wei Ou1, Wenhai Wang2, R. Simon Sherratt3, Yongjun Ren4, Xiaofeng Yu5,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4933-4950, 2023, DOI:10.32604/cmc.2023.034148

    Abstract With the rapid development of information technology, the development of blockchain technology has also been deeply impacted. When performing block verification in the blockchain network, if all transactions are verified on the chain, this will cause the accumulation of data on the chain, resulting in data storage problems. At the same time, the security of data is also challenged, which will put enormous pressure on the block, resulting in extremely low communication efficiency of the block. The traditional blockchain system uses the Merkle Tree method to store data. While verifying the integrity and correctness of the data, the amount of… More >

  • Open Access

    ARTICLE

    An Efficient Long Short-Term Memory Model for Digital Cross-Language Summarization

    Y. C. A. Padmanabha Reddy1, Shyam Sunder Reddy Kasireddy2, Nageswara Rao Sirisala3, Ramu Kuchipudi4, Purnachand Kollapudi5,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6389-6409, 2023, DOI:10.32604/cmc.2023.034072

    Abstract The rise of social networking enables the development of multilingual Internet-accessible digital documents in several languages. The digital document needs to be evaluated physically through the Cross-Language Text Summarization (CLTS) involved in the disparate and generation of the source documents. Cross-language document processing is involved in the generation of documents from disparate language sources toward targeted documents. The digital documents need to be processed with the contextual semantic data with the decoding scheme. This paper presented a multilingual cross-language processing of the documents with the abstractive and summarising of the documents. The proposed model is represented as the Hidden Markov… More >

  • Open Access

    ARTICLE

    Optimization Techniques in University Timetabling Problem: Constraints, Methodologies, Benchmarks, and Open Issues

    Abeer Bashab1, Ashraf Osman Ibrahim2,*, Ibrahim Abakar Tarigo Hashem3, Karan Aggarwal4, Fadhil Mukhlif5, Fuad A. Ghaleb5, Abdelzahir Abdelmaboud6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6461-6484, 2023, DOI:10.32604/cmc.2023.034051

    Abstract University timetabling problems are a yearly challenging task and are faced repeatedly each semester. The problems are considered non-polynomial time (NP) and combinatorial optimization problems (COP), which means that they can be solved through optimization algorithms to produce the aspired optimal timetable. Several techniques have been used to solve university timetabling problems, and most of them use optimization techniques. This paper provides a comprehensive review of the most recent studies dealing with concepts, methodologies, optimization, benchmarks, and open issues of university timetabling problems. The comprehensive review starts by presenting the essence of university timetabling as NP-COP, defining and clarifying the… More >

  • Open Access

    ARTICLE

    A GDPR Compliant Approach to Assign Risk Levels to Privacy Policies

    Abdullah R. Alshamsan1, Shafique A. Chaudhry1,2,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4631-4647, 2023, DOI:10.32604/cmc.2023.034039

    Abstract Data privacy laws require service providers to inform their customers on how user data is gathered, used, protected, and shared. The General Data Protection Regulation (GDPR) is a legal framework that provides guidelines for collecting and processing personal information from individuals. Service providers use privacy policies to outline the ways an organization captures, retains, analyzes, and shares customers’ data with other parties. These policies are complex and written using legal jargon; therefore, users rarely read them before accepting them. There exist a number of approaches to automating the task of summarizing privacy policies and assigning risk levels. Most of the… More >

  • Open Access

    ARTICLE

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    Noureen Talpur1,*, Said Jadid Abdulkadir1, Mohd Hilmi Hasan1, Hitham Alhussian1, Ayed Alwadain2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5799-5820, 2023, DOI:10.32604/cmc.2023.034025

    Abstract Machine learning (ML) practices such as classification have played a very important role in classifying diseases in medical science. Since medical science is a sensitive field, the pre-processing of medical data requires careful handling to make quality clinical decisions. Generally, medical data is considered high-dimensional and complex data that contains many irrelevant and redundant features. These factors indirectly upset the disease prediction and classification accuracy of any ML model. To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. However, the majority of such techniques frequently suffer from local minima issues… More >

  • Open Access

    ARTICLE

    Impact of Artificial Compressibility on the Numerical Solution of Incompressible Nanofluid Flow

    Tohid Adibi1, Shams Forruque Ahmed2,*, Seyed Esmail Razavi3, Omid Adibi4, Irfan Anjum Badruddin5, Syed Javed5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5123-5139, 2023, DOI:10.32604/cmc.2023.034008

    Abstract The numerical solution of compressible flows has become more prevalent than that of incompressible flows. With the help of the artificial compressibility approach, incompressible flows can be solved numerically using the same methods as compressible ones. The artificial compressibility scheme is thus widely used to numerically solve incompressible Navier-Stokes equations. Any numerical method highly depends on its accuracy and speed of convergence. Although the artificial compressibility approach is utilized in several numerical simulations, the effect of the compressibility factor on the accuracy of results and convergence speed has not been investigated for nanofluid flows in previous studies. Therefore, this paper… More >

  • Open Access

    ARTICLE

    An Automatic Threshold Selection Using ALO for Healthcare Duplicate Record Detection with Reciprocal Neuro-Fuzzy Inference System

    Ala Saleh Alluhaidan1,*, Pushparaj2, Anitha Subbappa3, Ved Prakash Mishra4, P. V. Chandrika5, Anurika Vaish6, Sarthak Sengupta6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5821-5836, 2023, DOI:10.32604/cmc.2023.033995

    Abstract ESystems based on EHRs (Electronic health records) have been in use for many years and their amplified realizations have been felt recently. They still have been pioneering collections of massive volumes of health data. Duplicate detections involve discovering records referring to the same practical components, indicating tasks, which are generally dependent on several input parameters that experts yield. Record linkage specifies the issue of finding identical records across various data sources. The similarity existing between two records is characterized based on domain-based similarity functions over different features. De-duplication of one dataset or the linkage of multiple data sets has become… More >

  • Open Access

    ARTICLE

    CE-EEN-B0: Contour Extraction Based Extended EfficientNet-B0 for Brain Tumor Classification Using MRI Images

    Abishek Mahesh1, Deeptimaan Banerjee1, Ahona Saha1, Manas Ranjan Prusty2,*, A. Balasundaram2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5967-5982, 2023, DOI:10.32604/cmc.2023.033920

    Abstract A brain tumor is the uncharacteristic progression of tissues in the brain. These are very deadly, and if it is not diagnosed at an early stage, it might shorten the affected patient’s life span. Hence, their classification and detection play a critical role in treatment. Traditional Brain tumor detection is done by biopsy which is quite challenging. It is usually not preferred at an early stage of the disease. The detection involves Magnetic Resonance Imaging (MRI), which is essential for evaluating the tumor. This paper aims to identify and detect brain tumors based on their location in the brain. In… More >

  • Open Access

    ARTICLE

    Convolutional Neural Network for Overcrowded Public Transportation Pickup Truck Detection

    Jakkrit Suttanuruk1, Sajjakaj Jomnonkwao1,*, Vatanavong Ratanavaraha1, Sarunya Kanjanawattana2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5573-5588, 2023, DOI:10.32604/cmc.2023.033900

    Abstract Thailand has been on the World Health Organization (WHO)’s notorious deadliest road list for several years, currently ranking eighth on the list. Among all types of road fatalities, pickup trucks converted into vehicles for public transportation are found to be the most problematic due to their high occupancy and minimal passenger safety measures, such as safety belts. Passenger overloading is illegal, but it is often overlooked. The country often uses police checkpoints to enforce traffic laws. However, there are few or no highway patrols to apprehend offending drivers. Therefore, in this study, we propose the use of existing closed-circuit television… More >

  • Open Access

    ARTICLE

    Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature Selection

    Muhammad Umair1,*, Zafar Saeed1, Faisal Saeed2, Hiba Ishtiaq1, Muhammad Zubair1, Hala Abdel Hameed3,4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5431-5446, 2023, DOI:10.32604/cmc.2023.033884

    Abstract As big data, its technologies, and application continue to advance, the Smart Grid (SG) has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology (ICT) and cloud computing. As a result of the complicated architecture of cloud computing, the distinctive working of advanced metering infrastructures (AMI), and the use of sensitive data, it has become challenging to make the SG secure. Faults of the SG are categorized into two main categories, Technical Losses (TLs) and Non-Technical Losses (NTLs). Hardware failure, communication issues, ohmic losses, and… More >

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