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  • Open Access

    ARTICLE

    A New Enhanced Arabic Light Stemmer for IR in Medical Documents

    Ra’ed M. Al-Khatib1,*, Taha Zerrouki2, Mohammed M. Abu Shquier3, Amar Balla4, Asef Al-Khateeb5

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1255-1269, 2021, DOI:10.32604/cmc.2021.016155

    Abstract This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem, especially in medical documents. Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data. One of the main challenges facing the light stemming algorithm is cutting off the input word, to extract the initial segments. When initiating the light stemmer with strong initial segments, the final extracting stems and roots will be more accurate. Therefore, a new enhanced segmentation based on deploying the Direct Acyclic Graph (DAG) model is utilized. In addition to extracting the powerful initial segments,… More >

  • Open Access

    ARTICLE

    Rasch Model Assessment for Bloom Digital Taxonomy Applications

    Mohd Effendi Ewan Mohd Matore*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1235-1253, 2021, DOI:10.32604/cmc.2021.016143

    Abstract Assessment using Bloom’s taxonomy levels has evolved in a variety of contexts and uses. In the era of the COVID-19 pandemic, which necessitates use of online assessment, the need for teachers to use digital-based taxonomy skills or Bloom’s Digital Taxonomy (BDT) has increased even more. However, the existing studies on validity and reliability of BDT items are limited. To overcome this limitation, this study aims to test whether BDT has good psychometric characteristics as a teacher’s self-assessment tool using the Rasch model analysis and to investigate the pattern of BDT usage in teaching and learning. By using a quantitative online… More >

  • Open Access

    ARTICLE

    A Compact Dual-Port Multi-Band Rectifier Circuit for RF Energy Harvesting

    Surajo Muhammad1,*, Jun Jiat Tiang1, Sew Kin Wong1, Amjad Iqbal1, Amor Smida2, Mohamed Karim Azizi3

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 167-184, 2021, DOI:10.32604/cmc.2021.016133

    Abstract This paper presents a compact multi-band rectifier with an improved impedance matching bandwidth. It uses a combination of п–matching network (MN) at Port-1, with a parallel connection of three cell branch MN at Port-2. The proposed impedance matching network (IMN) is adopted to reduce circuit complexity, to improve circuit performance, and power conversion efficiency (PCE) of the rectifier at low input power. The fabricated rectifier prototype operates at 0.92, 1.82, 2.1, 2.46 and 2.65 GHz covering GSM/900, GSM/1800, UMTS2100, and Wi-Fi/2.45–LTE2600. The size of the compact rectifier on the PCB board is 0.13λg × 0.1λg. The fabricated rectifier achieved an… More >

  • Open Access

    ARTICLE

    Multimodal Medical Image Registration and Fusion for Quality Enhancement

    Muhammad Adeel Azam1, Khan Bahadar Khan2,*, Muhammad Ahmad3, Manuel Mazzara4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 821-840, 2021, DOI:10.32604/cmc.2021.016131

    Abstract For the last two decades, physicians and clinical experts have used a single imaging modality to identify the normal and abnormal structure of the human body. However, most of the time, medical experts are unable to accurately analyze and examine the information from a single imaging modality due to the limited information. To overcome this problem, a multimodal approach is adopted to increase the qualitative and quantitative medical information which helps the doctors to easily diagnose diseases in their early stages. In the proposed method, a Multi-resolution Rigid Registration (MRR) technique is used for multimodal image registration while Discrete Wavelet… More >

  • Open Access

    ARTICLE

    A Fault-Handling Method for the Hamiltonian Cycle in the Hypercube Topology

    Adnan A. Hnaif*, Abdelfatah A. Tamimi, Ayman M. Abdalla, Iqbal Jebril

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 505-519, 2021, DOI:10.32604/cmc.2021.016123

    Abstract Many routing protocols, such as distance vector and link-state protocols are used for finding the best paths in a network. To find the path between the source and destination nodes where every node is visited once with no repeats, Hamiltonian and Hypercube routing protocols are often used. Nonetheless, these algorithms are not designed to solve the problem of a node failure, where one or more nodes become faulty. This paper proposes an efficient modified Fault-free Hamiltonian Cycle based on the Hypercube Topology (FHCHT) to perform a connection between nodes when one or more nodes become faulty. FHCHT can be applied… More >

  • Open Access

    ARTICLE

    Imperative Dynamic Routing Between Capsules Network for Malaria Classification

    G. Madhu1,*, A. Govardhan2, B. Sunil Srinivas3, Kshira Sagar Sahoo4, N. Z. Jhanjhi5, K. S. Vardhan1, B. Rohit6

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 903-919, 2021, DOI:10.32604/cmc.2021.016114

    Abstract Malaria is a severe epidemic disease caused by Plasmodium falciparum. The parasite causes critical illness if persisted for longer durations and delay in precise treatment can lead to further complications. The automatic diagnostic model provides aid for medical practitioners to avail a fast and efficient diagnosis. Most of the existing work either utilizes a fully connected convolution neural network with successive pooling layers which causes loss of information in pixels. Further, convolutions can capture spatial invariances but, cannot capture rotational invariances. Hence to overcome these limitations, this research, develops an Imperative Dynamic routing mechanism with fully trained capsule networks for… More >

  • Open Access

    ARTICLE

    A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

    Omar Almomani*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

    Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… More >

  • Open Access

    ARTICLE

    An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

    Park Chan-Yeob, Hyun-Ro Jae, Jun-Yong Jang, Song Hyoung-Kyu*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 137-148, 2021, DOI:10.32604/cmc.2021.016108

    Abstract Linear precoding methods such as zero-forcing (ZF) are near optimal for downlink massive multi-user multiple input multiple output (MIMO) systems due to their asymptotic channel property. However, as the number of users increases, the computational complexity of obtaining the inverse matrix of the gram matrix increases. For solving the computational complexity problem, this paper proposes an improved Jacobi (JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO systems. The conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel implementation. However, the conventional JC… More >

  • Open Access

    ARTICLE

    Diagnosis of Various Skin Cancer Lesions Based on Fine-Tuned ResNet50 Deep Network

    Sameh Abd ElGhany1,2, Mai Ramadan Ibraheem3, Madallah Alruwaili4, Mohammed Elmogy5,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 117-135, 2021, DOI:10.32604/cmc.2021.016102

    Abstract With the massive success of deep networks, there have been significant efforts to analyze cancer diseases, especially skin cancer. For this purpose, this work investigates the capability of deep networks in diagnosing a variety of dermoscopic lesion images. This paper aims to develop and fine-tune a deep learning architecture to diagnose different skin cancer grades based on dermatoscopic images. Fine-tuning is a powerful method to obtain enhanced classification results by the customized pre-trained network. Regularization, batch normalization, and hyperparameter optimization are performed for fine-tuning the proposed deep network. The proposed fine-tuned ResNet50 model successfully classified 7-respective classes of dermoscopic lesions… More >

  • Open Access

    ARTICLE

    Interference Mitigation in D2D Communication Underlying Cellular Networks: Towards Green Energy

    Rana Zeeshan Ahamad1, Abdul Rehman Javed2,*, Shakir Mehmood3, Mohammad Zubair Khan4, Abdulfattah Noorwali5, Muhammad Rizwan6

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 45-58, 2021, DOI:10.32604/cmc.2021.016082

    Abstract Device to Device (D2D) communication is emerging as a new participant promising technology in 5G cellular networks to promote green energy networks. D2D communication can improve communication delays, spectral efficiency, system capacity, data off-loading, and many other fruitful scenarios where D2D can be implemented. Nevertheless, induction of D2D communication in reuse mode with the conventional cellular network can cause severe interference issues, which can significantly degrade network performance. To reap all the benefits of induction of D2D communication with conventional cellular communication, it is imperative to minimize interference’s detrimental effects. Efficient power control can minimize the negative effects of interference… More >

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