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  • Open Access

    ARTICLE

    Quantum Inspired Differential Evolution with Explainable Artificial Intelligence-Based COVID-19 Detection

    Abdullah M. Basahel, Mohammad Yamin*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 209-224, 2023, DOI:10.32604/csse.2023.034449 - 20 January 2023

    Abstract Recent advancements in the Internet of Things (Io), 5G networks, and cloud computing (CC) have led to the development of Human-centric IoT (HIoT) applications that transform human physical monitoring based on machine monitoring. The HIoT systems find use in several applications such as smart cities, healthcare, transportation, etc. Besides, the HIoT system and explainable artificial intelligence (XAI) tools can be deployed in the healthcare sector for effective decision-making. The COVID-19 pandemic has become a global health issue that necessitates automated and effective diagnostic tools to detect the disease at the initial stage. This article presents… More >

  • Open Access

    ARTICLE

    Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

    Imran Ali1, Zohaib Mushtaq2, Saad Arif3, Abeer D. Algarni4,*, Naglaa F. Soliman4, Walid El-Shafai5,6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 303-319, 2023, DOI:10.32604/csse.2023.034374 - 20 January 2023

    Abstract Hyperspectral imaging is gaining a significant role in agricultural remote sensing applications. Its data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third dimension. The classification accuracy of hyperspectral images (HSI) increases significantly by employing both spatial and spectral features. For this work, the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared (VNIR) range of 400 to 1000 nm wavelength within 180 spectral bands. The dataset is collected for nine different crops on… More >

  • Open Access

    ARTICLE

    Exploring High-Performance Architecture for Data Center Networks

    Deshun Li1, Shaorong Sun2, Qisen Wu2, Shuhua Weng1, Yuyin Tan2, Jiangyuan Yao1,*, Xiangdang Huang1, Xingcan Cao3

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 433-443, 2023, DOI:10.32604/csse.2023.034368 - 20 January 2023

    Abstract As a critical infrastructure of cloud computing, data center networks (DCNs) directly determine the service performance of data centers, which provide computing services for various applications such as big data processing and artificial intelligence. However, current architectures of data center networks suffer from a long routing path and a low fault tolerance between source and destination servers, which is hard to satisfy the requirements of high-performance data center networks. Based on dual-port servers and Clos network structure, this paper proposed a novel architecture to construct high-performance data center networks. Logically, the proposed architecture is constructed… More >

  • Open Access

    ARTICLE

    Weight Prediction Using the Hybrid Stacked-LSTM Food Selection Model

    Ahmed M. Elshewey1, Mahmoud Y. Shams2,*, Zahraa Tarek3, Mohamed Megahed4, El-Sayed M. El-kenawy5, Mohamed A. El-dosuky3,6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 765-781, 2023, DOI:10.32604/csse.2023.034324 - 20 January 2023

    Abstract Food choice motives (i.e., mood, health, natural content, convenience, sensory appeal, price, familiarities, ethical concerns, and weight control) have an important role in transforming the current food system to ensure the healthiness of people and the sustainability of the world. Researchers from several domains have presented several models addressing issues influencing food choice over the years. However, a multidisciplinary approach is required to better understand how various aspects interact with one another during the decision-making procedure. In this paper, four Deep Learning (DL) models and one Machine Learning (ML) model are utilized to predict the… More >

  • Open Access

    ARTICLE

    A Lightweight Deep Autoencoder Scheme for Cyberattack Detection in the Internet of Things

    Maha Sabir1, Jawad Ahmad2,*, Daniyal Alghazzawi1

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 57-72, 2023, DOI:10.32604/csse.2023.034277 - 20 January 2023

    Abstract The Internet of things (IoT) is an emerging paradigm that integrates devices and services to collect real-time data from surroundings and process the information at a very high speed to make a decision. Despite several advantages, the resource-constrained and heterogeneous nature of IoT networks makes them a favorite target for cybercriminals. A single successful attempt of network intrusion can compromise the complete IoT network which can lead to unauthorized access to the valuable information of consumers and industries. To overcome the security challenges of IoT networks, this article proposes a lightweight deep autoencoder (DAE) based… More >

  • Open Access

    ARTICLE

    Intelligent Digital Envelope for Distributed Cloud-Based Big Data Security

    S. Prince Chelladurai1,*, T. Rajagopalan2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 951-960, 2023, DOI:10.32604/csse.2023.034262 - 20 January 2023

    Abstract Cloud computing offers numerous web-based services. The adoption of many Cloud applications has been hindered by concerns about data security and privacy. Cloud service providers’ access to private information raises more security issues. In addition, Cloud computing is incompatible with several industries, including finance and government. Public-key cryptography is frequently cited as a significant advancement in cryptography. In contrast, the Digital Envelope that will be used combines symmetric and asymmetric methods to secure sensitive data. This study aims to design a Digital Envelope for distributed Cloud-based large data security using public-key cryptography. Through strategic design, More >

  • Open Access

    ARTICLE

    A Hybrid Approach for Plant Disease Detection Using E-GAN and CapsNet

    N. Vasudevan*, T. Karthick

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 337-356, 2023, DOI:10.32604/csse.2023.034242 - 20 January 2023

    Abstract Crop protection is a great obstacle to food safety, with crop diseases being one of the most serious issues. Plant diseases diminish the quality of crop yield. To detect disease spots on grape leaves, deep learning technology might be employed. On the other hand, the precision and efficiency of identification remain issues. The quantity of images of ill leaves taken from plants is often uneven. With an uneven collection and few images, spotting disease is hard. The plant leaves dataset needs to be expanded to detect illness accurately. A novel hybrid technique employing segmentation, augmentation,… More >

  • Open Access

    ARTICLE

    3D Object Detection with Attention: Shell-Based Modeling

    Xiaorui Zhang1,2,3,4,*, Ziquan Zhao1, Wei Sun4,5, Qi Cui6

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 537-550, 2023, DOI:10.32604/csse.2023.034230 - 20 January 2023

    Abstract LIDAR point cloud-based 3D object detection aims to sense the surrounding environment by anchoring objects with the Bounding Box (BBox). However, under the three-dimensional space of autonomous driving scenes, the previous object detection methods, due to the pre-processing of the original LIDAR point cloud into voxels or pillars, lose the coordinate information of the original point cloud, slow detection speed, and gain inaccurate bounding box positioning. To address the issues above, this study proposes a new two-stage network structure to extract point cloud features directly by PointNet++, which effectively preserves the original point cloud coordinate… More >

  • Open Access

    ARTICLE

    A Novel Gradient Boosted Energy Optimization Model (GBEOM) for MANET

    Neenavath Veeraiah1,*, Youseef Alotaibi2, Saleh Alghamdi3, Satish Thatavarti4

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 637-657, 2023, DOI:10.32604/csse.2023.034224 - 20 January 2023

    Abstract Mobile Ad Hoc Network (MANET) is an infrastructure-less network that is comprised of a set of nodes that move randomly. In MANET, the overall performance is improved through multipath multicast routing to achieve the quality of service (quality of service). In this, different nodes are involved in the information data collection and transmission to the destination nodes in the network. The different nodes are combined and presented to achieve energy-efficient data transmission and classification of the nodes. The route identification and routing are established based on the data broadcast by the network nodes. In transmitting… More >

  • Open Access

    ARTICLE

    Coot Optimization with Deep Learning-Based False Data Injection Attack Recognition

    T. Satyanarayana Murthy1, P. Udayakumar2, Fayadh Alenezi3, E. Laxmi Lydia4, Mohamad Khairi Ishak5,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 255-271, 2023, DOI:10.32604/csse.2023.034193 - 20 January 2023

    Abstract The recent developments in smart cities pose major security issues for the Internet of Things (IoT) devices. These security issues directly result from inappropriate security management protocols and their implementation by IoT gadget developers. Cyber-attackers take advantage of such gadgets’ vulnerabilities through various attacks such as injection and Distributed Denial of Service (DDoS) attacks. In this background, Intrusion Detection (ID) is the only way to identify the attacks and mitigate their damage. The recent advancements in Machine Learning (ML) and Deep Learning (DL) models are useful in effectively classifying cyber-attacks. The current research paper introduces… More >

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