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  • Open Access

    ARTICLE

    A New Modified Inverse Lomax Distribution: Properties, Estimation and Applications to Engineering and Medical Data

    Abdullah M. Almarashi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 621-643, 2021, DOI:10.32604/cmes.2021.014407

    Abstract In this paper, a modified form of the traditional inverse Lomax distribution is proposed and its characteristics are studied. The new distribution which called modified logarithmic transformed inverse Lomax distribution is generated by adding a new shape parameter based on logarithmic transformed method. It contains two shape and one scale parameters and has different shapes of probability density and hazard rate functions. The new shape parameter increases the flexibility of the statistical properties of the traditional inverse Lomax distribution including mean, variance, skewness and kurtosis. The moments, entropies, order statistics and other properties are discussed. Six methods of estimation are… More >

  • Open Access

    ARTICLE

    Internet of Things: Protection of Medical Data through Decentralized Ledgers

    Abdalla Alameen*

    Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 593-602, 2021, DOI:10.32604/iasc.2021.016950

    Abstract It is forecasted that billions of Internet of Things (IoT) and sensor devices will be installed worldwide by 2020. These devices can provide infrastructure-based services for various applications such as in smart hospitals, smart industry, smart grids, and smart industrial towns. Among them, the hospital service system needs to authenticate devices, and medical data are recorded for diagnostic purposes. In general, digital signatures are employed, but the computational power and their huge numbers pose many challenges to the digital signature system. To solve such problems, we developed a ledger system for authenticating IoT medical devices. It is a centralized ledger… More >

  • Open Access

    ARTICLE

    IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

    Sarab AlMuhaideb*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576

    Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can be viewed as a fusion… More >

  • Open Access

    ARTICLE

    Memetic Optimization with Cryptographic Encryption for Secure Medical Data Transmission in IoT-Based Distributed Systems

    Srinath Doss1, Jothi Paranthaman2, Suseendran Gopalakrishnan3, Akila Duraisamy3, Souvik Pal4, Balaganesh Duraisamy5, Chung Le Van6,*, Dac-Nhuong Le7

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1577-1594, 2021, DOI:10.32604/cmc.2020.012379

    Abstract In the healthcare system, the Internet of Things (IoT) based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests. This datum is sensitive, and hence security is a must in transforming the sensational contents. In this paper, an Evolutionary Algorithm, namely the Memetic Algorithm is used for encrypting the text messages. The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels. The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the… More >

  • Open Access

    ARTICLE

    C5.0 Decision Tree Model Using Tsallis Entropy and Association Function for General and Medical Dataset

    Uma K.V1,*, Appavu alias Balamurugan S2

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 61-70, 2020, DOI:10.31209/2019.100000153

    Abstract Real world data consists of lot of impurities. Entropy measure will help to handle impurities in a better way. Here, data selection is done by using Naïve Bayes’ theorem. The sample which has posterior probability value greater than that of the threshold value is selected. C5.0 decision tree classifier is taken as base and modified the Gain calculation function using Tsallis entropy and Association function. The proposed classifier model provides more accuracy and smaller tree for general and Medical dataset. Precision value obtained for Medical dataset is more than that of existing method. More >

  • Open Access

    ARTICLE

    Secure Model of Medical Data Sharing for Complex Scenarios

    Wei She1, Yue Hu2, Zhao Tian1, Guoning Liu3, Bo Wang4, Wei Liu1, 2, *

    Journal of Cyber Security, Vol.1, No.1, pp. 11-17, 2019, DOI:10.32604/jcs.2019.05856

    Abstract In order to secure the massive heterogeneous medical data for the complex scenarios and improve the information sharing efficiency in healthcare system, a distributed medical data ledger model (DMDL) is proposed in this paper. This DMDL model has adopted the blockchain technology including the function decoupling, the distributed consensus, smart contract as well as multi-channel communication structure of consortium blockchain. The DMDL model not only has high adaptability, but also meets the requirements of the medical treatment processes which generally involve multi-entities, highly private information and secure transaction. The steps for processing the medical data are also introduced. Additionally, the… More >

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