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  • Open Access

    ARTICLE

    COVID-19 Classification from X-Ray Images: An Approach to Implement Federated Learning on Decentralized Dataset

    Ali Akbar Siddique1, S. M. Umar Talha1, M. Aamir1, Abeer D. Algarni2, Naglaa F. Soliman2,*, Walid El-Shafai3,4

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3883-3901, 2023, DOI:10.32604/cmc.2023.037413

    Abstract The COVID-19 pandemic has devastated our daily lives, leaving horrific repercussions in its aftermath. Due to its rapid spread, it was quite difficult for medical personnel to diagnose it in such a big quantity. Patients who test positive for Covid-19 are diagnosed via a nasal PCR test. In comparison, polymerase chain reaction (PCR) findings take a few hours to a few days. The PCR test is expensive, although the government may bear expenses in certain places. Furthermore, subsets of the population resist invasive testing like swabs. Therefore, chest X-rays or Computerized Vomography (CT) scans are… More >

  • Open Access

    ARTICLE

    DDoS Attack Detection in Cloud Computing Based on Ensemble Feature Selection and Deep Learning

    Yousef Sanjalawe1,2,*, Turke Althobaiti3,4

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3571-3588, 2023, DOI:10.32604/cmc.2023.037386

    Abstract Intrusion Detection System (IDS) in the cloud Computing (CC) environment has received paramount interest over the last few years. Among the latest approaches, Deep Learning (DL)-based IDS methods allow the discovery of attacks with the highest performance. In the CC environment, Distributed Denial of Service (DDoS) attacks are widespread. The cloud services will be rendered unavailable to legitimate end-users as a consequence of the overwhelming network traffic, resulting in financial losses. Although various researchers have proposed many detection techniques, there are possible obstacles in terms of detection performance due to the use of insignificant traffic… More >

  • Open Access

    ARTICLE

    Improving Speech Enhancement Framework via Deep Learning

    Sung-Jung Hsiao1, Wen-Tsai Sung2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3817-3832, 2023, DOI:10.32604/cmc.2023.037380

    Abstract Speech plays an extremely important role in social activities. Many individuals suffer from a “speech barrier,” which limits their communication with others. In this study, an improved speech recognition method is proposed that addresses the needs of speech-impaired and deaf individuals. A basic improved connectionist temporal classification convolutional neural network (CTC-CNN) architecture acoustic model was constructed by combining a speech database with a deep neural network. Acoustic sensors were used to convert the collected voice signals into text or corresponding voice signals to improve communication. The method can be extended to modern artificial intelligence techniques, More >

  • Open Access

    ARTICLE

    Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

    Mohammed Jasim Mohammed Jasim1, Bzar Khidir Hussan2, Subhi R. M. Zeebaree3,*, Zainab Salih Ageed4

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3677-3693, 2023, DOI:10.32604/cmc.2023.037363

    Abstract The major mortality factor relevant to the intestinal tract is the growth of tumorous cells (polyps) in various parts. More specifically, colonic polyps have a high rate and are recognized as a precursor of colon cancer growth. Endoscopy is the conventional technique for detecting colon polyps, and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate. The automated diagnosis of polyps in a computer-aided diagnosis (CAD) method is implemented using statistical analysis. Nowadays, Deep Learning,… More >

  • Open Access

    ARTICLE

    MSCNN-LSTM Model for Predicting Return Loss of the UHF Antenna in HF-UHF RFID Tag Antenna

    Zhao Yang1, Yuan Zhang1, Lei Zhu2,*, Lei Huang1, Fangyu Hu3, Yanping Du1, Xiaowei Li1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2889-2904, 2023, DOI:10.32604/cmc.2023.037297

    Abstract High-frequency (HF) and ultrahigh-frequency (UHF) dual-band radio frequency identification (RFID) tags with both near-field and far-field communication can meet different application scenarios. However, it is time-consuming to calculate the return loss of a UHF antenna in a dual-band tag antenna using electromagnetic (EM) simulators. To overcome this, the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory (MSCNN-LSTM) for predicting the return loss of UHF antennas instead of EM simulators. In the proposed MSCNN-LSTM, the MSCNN has three branches, which include three convolution layers with different kernel… More >

  • Open Access

    ARTICLE

    An Improved Calibration Method of Grating Projection Measurement System

    Qiucheng Sun*, Weiyu Dai, Mingyu Sun, Zeming Ren, Mingze Wang

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3957-3970, 2023, DOI:10.32604/cmc.2023.037254

    Abstract In the traditional fringe projection profilometry system, the projector and the camera light center are both spatially virtual points. The spatial position relationships specified in the model are not easy to obtain, leading to inaccurate system parameters and affecting measurement accuracy. This paper proposes a method for solving the system parameters of the fringe projection profilometry system, and the spatial position of the camera and projector can be adjusted in accordance with the obtained calibration parameters. The steps are as follows: First, in accordance with the conversion relationship of the coordinate system in the calibration… More >

  • Open Access

    ARTICLE

    Image Splicing Detection Using Generalized Whittaker Function Descriptor

    Dumitru Baleanu1,2,3, Ahmad Sami Al-Shamayleh4, Rabha W. Ibrahim5,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3465-3477, 2023, DOI:10.32604/cmc.2023.037162

    Abstract Image forgery is a crucial part of the transmission of misinformation, which may be illegal in some jurisdictions. The powerful image editing software has made it nearly impossible to detect altered images with the naked eye. Images must be protected against attempts to manipulate them. Image authentication methods have gained popularity because of their use in multimedia and multimedia networking applications. Attempts were made to address the consequences of image forgeries by creating algorithms for identifying altered images. Because image tampering detection targets processing techniques such as object removal or addition, identifying altered images remains… More >

  • Open Access

    ARTICLE

    Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

    Siling Feng1, Yinjie Chen1, Mengxing Huang1,2,*, Feng Shu1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4341-4355, 2023, DOI:10.32604/cmc.2023.037154

    Abstract Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks… More >

  • Open Access

    ARTICLE

    Enhancing Security by Using GIFT and ECC Encryption Method in Multi-Tenant Datacenters

    Jin Wang1, Ying Liu1, Shuying Rao1, R. Simon Sherratt2, Jinbin Hu1,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3849-3865, 2023, DOI:10.32604/cmc.2023.037150

    Abstract Data security and user privacy have become crucial elements in multi-tenant data centers. Various traffic types in the multi-tenant data center in the cloud environment have their characteristics and requirements. In the data center network (DCN), short and long flows are sensitive to low latency and high throughput, respectively. The traditional security processing approaches, however, neglect these characteristics and requirements. This paper proposes a fine-grained security enhancement mechanism (SEM) to solve the problem of heterogeneous traffic and reduce the traffic completion time (FCT) of short flows while ensuring the security of multi-tenant traffic transmission. Specifically, More >

  • Open Access

    ARTICLE

    Stackelberg Game-Based Resource Allocation with Blockchain for Cold-Chain Logistics System

    Yang Zhang1, Chaoyang Li2,*, Xiangjun Xin2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2429-2442, 2023, DOI:10.32604/cmc.2023.037139

    Abstract Cold-chain logistics system (CCLS) plays the role of collecting and managing the logistics data of frozen food. However, there always exist problems of information loss, data tampering, and privacy leakage in traditional centralized systems, which influence frozen food security and people’s health. The centralized management form impedes the development of the cold-chain logistics industry and weakens logistics data availability. This paper first introduces a distributed CCLS based on blockchain technology to solve the centralized management problem. This system aggregates the production base, storage, transport, detection, processing, and consumer to form a cold-chain logistics union. The… More >

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