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  • Open Access

    ARTICLE

    Image Inpainting Detection Based on High-Pass Filter Attention Network

    Can Xiao1,2, Feng Li1,2,*, Dengyong Zhang1,2, Pu Huang1,2, Xiangling Ding3, Victor S. Sheng4

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1145-1154, 2022, DOI:10.32604/csse.2022.027249 - 09 May 2022

    Abstract Image inpainting based on deep learning has been greatly improved. The original purpose of image inpainting was to repair some broken photos, such as inpainting artifacts. However, it may also be used for malicious operations, such as destroying evidence. Therefore, detection and localization of image inpainting operations are essential. Recent research shows that high-pass filtering full convolutional network (HPFCN) is applied to image inpainting detection and achieves good results. However, those methods did not consider the spatial location and channel information of the feature map. To solve these shortcomings, we introduce the squeezed excitation blocks More >

  • Open Access

    ARTICLE

    Improved Density Peaking Algorithm for Community Detection Based on Graph Representation Learning

    Jiaming Wang2, Xiaolan Xie1,2,*, Xiaochun Cheng3, Yuhan Wang2

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 997-1008, 2022, DOI:10.32604/csse.2022.027005 - 09 May 2022

    Abstract

    There is a large amount of information in the network data that we can exploit. It is difficult for classical community detection algorithms to handle network data with sparse topology. Representation learning of network data is usually paired with clustering algorithms to solve the community detection problem. Meanwhile, there is always an unpredictable distribution of class clusters output by graph representation learning. Therefore, we propose an improved density peak clustering algorithm (ILDPC) for the community detection problem, which improves the local density mechanism in the original algorithm and can better accommodate class clusters of different

    More >

  • Open Access

    ARTICLE

    Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

    Zubair Nabi1, Ramzan Talib1,*, Muhammad Kashif Hanif1, Muhammad Awais2

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1357-1374, 2022, DOI:10.32604/csse.2022.025712 - 09 May 2022

    Abstract Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents More >

  • Open Access

    ARTICLE

    Deep Convolutional Neural Network Based Churn Prediction for Telecommunication Industry

    Nasebah Almufadi1, Ali Mustafa Qamar1,2,*

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1255-1270, 2022, DOI:10.32604/csse.2022.025029 - 09 May 2022

    Abstract Currently, mobile communication is one of the widely used means of communication. Nevertheless, it is quite challenging for a telecommunication company to attract new customers. The recent concept of mobile number portability has also aggravated the problem of customer churn. Companies need to identify beforehand the customers, who could potentially churn out to the competitors. In the telecommunication industry, such identification could be done based on call detail records. This research presents an extensive experimental study based on various deep learning models, such as the 1D convolutional neural network (CNN) model along with the recurrent More >

  • Open Access

    ARTICLE

    Low-Cost IMU Sensors for Satellite Maturity Improvement

    Omar Ben Bahri*, Abdullah Alhumaidi Alotaibi

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1315-1326, 2022, DOI:10.32604/csse.2022.024979 - 09 May 2022

    Abstract The satellite technology proves its impact in the modern era with its wide benefits and applications. However, the cost of the development in this field presents gaps in many countries, almost the developed countries. Therefore, this paper provides a rich platform around low-cost sensors in order to improve maturity in space technology, mostly the system of attitude determination and control. The development of this knowledge turns out to be very interesting in order to achieve a space mission which leads to the progression of the spatial technology readiness level (TRL) defined by the international measurement More >

  • Open Access

    ARTICLE

    Speak-Correct: A Computerized Interface for the Analysis of Mispronounced Errors

    Kamal Jambi1,*, Hassanin Al-Barhamtoshy1, Wajdi Al-Jedaibi1, Mohsen Rashwan2, Sherif Abdou3

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1155-1173, 2022, DOI:10.32604/csse.2022.024967 - 09 May 2022

    Abstract Any natural language may have dozens of accents. Even though the equivalent phonemic formation of the word, if it is properly called in different accents, humans do have audio signals that are distinct from one another. Among the most common issues with speech, the processing is discrepancies in pronunciation, accent, and enunciation. This research study examines the issues of detecting, fixing, and summarising accent defects of average Arabic individuals in English-speaking speech. The article then discusses the key approaches and structure that will be utilized to address both accent flaws and pronunciation issues. The proposed… More >

  • Open Access

    ARTICLE

    Advanced Authentication Mechanisms for Identity and Access Management in Cloud Computing

    Amjad Alsirhani, Mohamed Ezz, Ayman Mohamed Mostafa*

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 967-984, 2022, DOI:10.32604/csse.2022.024854 - 09 May 2022

    Abstract Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security… More >

  • Open Access

    ARTICLE

    Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

    Shital Joshi1, S. Manimurugan2,3, Ahamed Aljuhani2,*, Umar Albalawi2, Amer Aljaedi2

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1111-1130, 2022, DOI:10.32604/csse.2022.024802 - 09 May 2022

    Abstract The Internet of Things (IoT) represents a radical shifting paradigm for technological innovations as it can play critical roles in cyberspace applications in various sectors, such as security, monitoring, medical, and environmental sectors, and also in control and industrial applications. The IoT in E-medicine unleashed the design space for new technologies to give instant treatment to patients while also monitoring and tracking health conditions. This research presents a system-level architecture approach for IoT energy efficiency and security. The proposed architecture includes functional components that provide privacy management and system security. Components in the security function… More >

  • Open Access

    ARTICLE

    Automatic Liver Tumor Segmentation in CT Modalities Using MAT-ACM

    S. Priyadarsini1,*, Carlos Andrés Tavera Romero2, Abolfazl Mehbodniya3, P. Vidya Sagar4, Sudhakar Sengan5

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1057-1068, 2022, DOI:10.32604/csse.2022.024788 - 09 May 2022

    Abstract In the recent days, the segmentation of Liver Tumor (LT) has been demanding and challenging. The process of segmenting the liver and accurately spotting the tumor is demanding due to the diversity of shape, texture, and intensity of the liver image. The intensity similarities of the neighboring organs of the liver create difficulties during liver segmentation. The manual segmentation does not provide an accurate segmentation because the results provided by different medical experts can vary. Also, this manual technique requires a large number of image slices and time for segmentation. To solve these issues, the… More >

  • Open Access

    ARTICLE

    Analysis of Cognitive Radio for LTE and 5G Waveforms

    Ramesh Ramamoorthy1, Himanshu Sharma2, A. Akilandeswari3, Nidhi Gour2, Arun Kumar4,*, Mehedi Masud5

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1207-1217, 2022, DOI:10.32604/csse.2022.024749 - 09 May 2022

    Abstract Spectrum sensing is one of the major concerns in reaching an efficient Quality of service (QOS) in the advanced mobile communication system. The advanced engineering sciences such as 5G, device 2 device communications (D2D), Internet of things (IoT), MIMO require a large spectrum for better service. Orthogonal frequency division multiplexing (OFDM) is not a choice in advanced radio due to the Cyclic Prefix (CP), wastage of the spectrum, and so on. Hence, it is important to explore the spectral efficient advanced waveform techniques and combine a cognitive radio (CR) with the 5G waveform to sense… More >

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