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  • Open Access

    ARTICLE

    Automated Service Search Model for the Social Internet of Things

    Farhan Amin, Seong Oun Hwang*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5871-5888, 2022, DOI:10.32604/cmc.2022.028342

    Abstract The social internet of things (SIoT) is one of the emerging paradigms that was proposed to solve the problems of network service discovery, navigability, and service composition. The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings. In IoT, an object can offer multiple services and different objects can offer the same services with different parameters and interest factors. The proliferation of offered services led to difficulties during service customization and service filtering. This problem is known as service explosion. The selection of suitable service that fits the requirements… More >

  • Open Access

    ARTICLE

    Efficient Feature Selection and Machine Learning Based ADHD Detection Using EEG Signal

    Md. Maniruzzaman1, Jungpil Shin1,*, Md. Al Mehedi Hasan1, Akira Yasumura2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5179-5195, 2022, DOI:10.32604/cmc.2022.028339

    Abstract Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric and neurobehavioral disorders in children, affecting 11% of children worldwide. This study aimed to propose a machine learning (ML)-based algorithm for discriminating ADHD from healthy children using their electroencephalography (EEG) signals. The study included 61 children with ADHD and 60 healthy children aged 7–12 years. Different morphological and time-domain features were extracted from EEG signals. The t-test (p-value < 0.05) and least absolute shrinkage and selection operator (LASSO) were used to select potential features of children with ADHD and enhance the classification accuracy. The selected potential features were… More >

  • Open Access

    ARTICLE

    Handling Big Data in Relational Database Management Systems

    Kamal ElDahshan1, Eman Selim2, Ahmed Ismail Ebada2, Mohamed Abouhawwash3,4, Yunyoung Nam5,*, Gamal Behery2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5149-5164, 2022, DOI:10.32604/cmc.2022.028326

    Abstract Currently, relational database management systems (RDBMSs) face different challenges in application development due to the massive growth of unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, which do not adhere to the relational model. The migration from relational databases to NoSQL databases is challenging due to the data complexity. This study aims to enhance the storage performance of RDBMSs in handling a variety of data. The paper presents two approaches. The first approach proposes a convenient representation of unstructured data storage. Several extensive experiments were implemented to assess the efficiency… More >

  • Open Access

    ARTICLE

    A Blockchain-Based Framework for Secure Storage and Sharing of Resumes

    Huanrong Tang1, Changlin Hu1, Tianming Liu2, Jianquan Ouyang1,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5395-5413, 2022, DOI:10.32604/cmc.2022.028284

    Abstract In response to problems in the centralized storage of personal resumes on third-party recruitment platforms, such as inadequate privacy protection, inability of individuals to accurately authorize downloads, and inability to determine who downloaded the resume and when, this study proposes a blockchain-based framework for secure storage and sharing of resumes. Users can employ an authorized access mechanism to protect their privacy rights. The proposed framework uses smart contracts, interplanetary file system, symmetric encryption, and digital signatures to protect, verify, and share resumes. Encryption keys are split and stored in multiple depositories through secret-sharing technology to improve the security of these… More >

  • Open Access

    ARTICLE

    Triple Key Security Algorithm Against Single Key Attack on Multiple Rounds

    Muhammad Akram1, Muhammad Waseem Iqbal2,*, Syed Ashraf Ali3, Muhammad Usman Ashraf4, Khalid Alsubhi5, Hani Moaiteq Aljahdali6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6061-6077, 2022, DOI:10.32604/cmc.2022.028272

    Abstract In cipher algorithms, the encryption and decryption are based on the same key. There are some limitations in cipher algorithms, for example in polyalphabetic substitution cipher the key size must be equal to plaintext otherwise it will be repeated and if the key is known then encryption becomes useless. This paper aims to improve the said limitations by designing of Triple key security algorithm (TKS) in which the key is modified on polyalphabetic substitution cipher to maintain the size of the key and plaintext. Each plaintext character is substituted by an alternative message. The mode of substitution is transformed cyclically… More >

  • Open Access

    ARTICLE

    UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

    Rania M Tawfik1, Hazem A. A. Nomer2, M. Saeed Darweesh1,*, Ali Wagdy Mohamed3,4, Hassan Mostafa5,6

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5999-6013, 2022, DOI:10.32604/cmc.2022.028234

    Abstract Unmanned Aerial Vehicles (UAVs) provide a reliable and energy-efficient solution for data collection from the Narrowband Internet of Things (NB-IoT) devices. However, the UAV’s deployment optimization, including locations of the UAV’s stop points, is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection efficiently. In this regard, this paper proposes Gaining-Sharing Knowledge (GSK) algorithm for optimizing the UAV’s deployment. In GSK, the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire deployment. The superiority of… More >

  • Open Access

    ARTICLE

    Improved Dijkstra Algorithm for Mobile Robot Path Planning and Obstacle Avoidance

    Shaher Alshammrei1, Sahbi Boubaker2,*, Lioua Kolsi1,3

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5939-5954, 2022, DOI:10.32604/cmc.2022.028165

    Abstract Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots (MRs) in both research and education. In this paper, an optimal collision-free algorithm is designed and implemented practically based on an improved Dijkstra algorithm. To achieve this research objectives, first, the MR obstacle-free environment is modeled as a diagraph including nodes, edges and weights. Second, Dijkstra algorithm is used offline to generate the shortest path driving the MR from a starting point to a target point. During its movement, the robot should follow the previously obtained path and stop at each node to test if there… More >

  • Open Access

    ARTICLE

    Iterative Semi-Supervised Learning Using Softmax Probability

    Heewon Chung, Jinseok Lee*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5607-5628, 2022, DOI:10.32604/cmc.2022.028154

    Abstract For the classification problem in practice, one of the challenging issues is to obtain enough labeled data for training. Moreover, even if such labeled data has been sufficiently accumulated, most datasets often exhibit long-tailed distribution with heavy class imbalance, which results in a biased model towards a majority class. To alleviate such class imbalance, semi-supervised learning methods using additional unlabeled data have been considered. However, as a matter of course, the accuracy is much lower than that from supervised learning. In this study, under the assumption that additional unlabeled data is available, we propose the iterative semi-supervised learning algorithms, which… More >

  • Open Access

    ARTICLE

    Securing Copyright Using 3D Objects Blind Watermarking Scheme

    Hussein Abulkasim1,*, Mona Jamjoom2, Safia Abbas2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5969-5983, 2022, DOI:10.32604/cmc.2022.027999

    Abstract Recently, securing Copyright has become a hot research topic due to rapidly advancing information technology. As a host cover, watermarking methods are used to conceal or embed sensitive information messages in such a manner that it was undetectable to a human observer in contemporary times. Digital media covers may often take any form, including audio, video, photos, even DNA data sequences. In this work, we present a new methodology for watermarking to hide secret data into 3-D objects. The technique of blind extraction based on reversing the steps of the data embedding process is used. The implemented technique uses the… More >

  • Open Access

    ARTICLE

    Swarming Computational Approach for the Heartbeat Van Der Pol Nonlinear System

    Muhammad Umar1, Fazli Amin1, Soheil Salahshour2, Thongchai Botmart3, Wajaree Weera3, Prem Junswang4,*, Zulqurnain Sabir1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6185-6202, 2022, DOI:10.32604/cmc.2022.027970

    Abstract The present study is related to design a stochastic framework for the numerical treatment of the Van der Pol heartbeat model (VP-HBM) using the feedforward artificial neural networks (ANNs) under the optimization of particle swarm optimization (PSO) hybridized with the active-set algorithm (ASA), i.e., ANNs-PSO-ASA. The global search PSO scheme and local refinement of ASA are used as an optimization procedure in this study. An error-based merit function is defined using the differential VP-HBM form as well as the initial conditions. The optimization of the merit function is accomplished using the hybrid computing performances of PSO-ASA. The designed performance of… More >

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