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  • Open Access

    ARTICLE

    Enhanced Neuro-Fuzzy-Based Crop Ontology for Effective Information Retrieval

    K. Ezhilarasi1,*, G. Maria Kalavathy2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 569-582, 2022, DOI:10.32604/csse.2022.020280

    Abstract Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers. Familiarizing ontology as information retrieval (IR) aids in augmenting the searching effects of user-required relevant information. The crux of conventional keyword matching-related IR utilizes advanced algorithms for recovering facts from the Internet, mapping the connection between keywords and information, and categorizing the retrieval outcomes. The prevailing procedures for IR consume considerable time, and they could not recover information proficiently. In this study, through applying a modified neuro-fuzzy algorithm (MNFA), the IR time is mitigated, and the retrieval accuracy is enhanced for trouncing the… More >

  • Open Access

    ARTICLE

    Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network

    Baili Zhang1, Keke Ling1,*, Pei Zhang2,3, Zhao Zhang2,3, Mingjun Zhong4

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 699-715, 2022, DOI:10.32604/csse.2022.020193

    Abstract Calculating the most reliable maximum flow (MRMF) from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network (CDN). However, SDBA, as the current state-of-the-art MRMF algorithm, is too complex to meet real-time computing needs. This paper proposes a set of MRMF algorithms: NWCD (Negative Weight Community Deletion), SCPDAT (Single-Cycle Preference Deletion Approximation algorithm with Time constraint) and SCPDAP (Single-Cycle Preference Deletion Approximation algorithm with Probability constraint). NWCD draws on the “flow-shifting” algorithm of minimum cost and maximum flow, and further defines the concept of… More >

  • Open Access

    ARTICLE

    A New Method of Image Restoration Technology Based on WGAN

    Wei Fang1,2,*, Enming Gu1, Weinan Yi1, Weiqing Wang1, Victor S. Sheng3

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 689-698, 2022, DOI:10.32604/csse.2022.020176

    Abstract With the development of image restoration technology based on deep learning, more complex problems are being solved, especially in image semantic inpainting based on context. Nowadays, image semantic inpainting techniques are becoming more mature. However, due to the limitations of memory, the instability of training, and the lack of sample diversity, the results of image restoration are still encountering difficult problems, such as repairing the content of glitches which cannot be well integrated with the original image. Therefore, we propose an image inpainting network based on Wasserstein generative adversarial network (WGAN) distance. With the corresponding technology having been adjusted and… More >

  • Open Access

    ARTICLE

    Healthcare Device Security Assessment through Computational Methodology

    Masood Ahmad1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Sabita Khatri2, Adil Hussain Seh1, Mohd Nadeem1, Alka Agrawal1,*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 811-828, 2022, DOI:10.32604/csse.2022.020097

    Abstract The current study discusses the different methods used to secure healthcare devices and proposes a quantitative framework to list them in order of significances. The study uses the Hesitant Fuzzy (HF), Analytic Hierarchy Process (AHP) integrated with Fuzzy Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to classify the best alternatives to security techniques for healthcare devices to securing the devices. The technique is enlisted to rate the alternatives based on the degree of satisfaction of their weights. The ranks of the alternatives consequently decide the order of priority for the techniques. A1 was the most probable alternative… More >

  • Open Access

    ARTICLE

    A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

    Adriano G. Passos, Tiago Cousseau, Marco A. Luersen*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020

    Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small… More >

  • Open Access

    ARTICLE

    On Mixed Model for Improvement in Stock Price Forecasting

    Qunhui Zhang1, Mengzhe Lu3,4, Liang Dai2,*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 795-809, 2022, DOI:10.32604/csse.2022.019987

    Abstract Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. But the fact is that forecasting stock prices by using various models has been suffering from low accuracy, slow convergence, and complex parameters. This study aims to employ a mixed model to improve the accuracy of stock price prediction. We present how to use a random walk based on jump-diffusion, to obtain stock predictions with a good-fitting degree by adjusting different parameters. Aimed at getting better parameters and then using the time series model to predict the data, we employed the time… More >

  • Open Access

    ARTICLE

    Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing

    A. S. Anakath1,*, R. Kannadasan2, Niju P. Joseph3, P. Boominathan4, G. R. Sreekanth5

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 479-492, 2022, DOI:10.32604/csse.2022.019940

    Abstract Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider in the network, they will… More >

  • Open Access

    ARTICLE

    FACT: An Air-Ground Communication Framework for Seeding Quality Control of Aircraft

    Dequan Li1,2, Jiming Li1,2, Xu Zhou1,2, JinRong Hu3, Xin Wang4, Jing Duan1,2,*

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 539-555, 2022, DOI:10.32604/csse.2022.019551

    Abstract A new type of air-ground communication application framework named FACT (framework for air-ground communication technology with weather-modification aircraft) is presented to track and command weather-modification aircraft to perform ideal cloud seeding. FACT provides a set of solutions from three perspectives, namely, onboard, onground and air-to-ground, with the core purpose of solving the problems of the rapid exchange of information, contract analysis and identifying potential seeding areas when flight plans and meteorological conditions change. On board, the observed data are processed centrally and transmitted downward through air-to-ground communication. The real-time application and sharing of aircraft detection data are strengthened on the… More >

  • Open Access

    ARTICLE

    Optimal Data Placement and Replication Approach for SIoT with Edge

    B. Prabhu Shankar1,*, S. Chitra2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 661-676, 2022, DOI:10.32604/csse.2022.019507

    Abstract Social networks (SNs) are sources with extreme number of users around the world who are all sharing data like images, audio, and video to their friends using IoT devices. This concept is the so-called Social Internet of Things (SIot). The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources, and this task demands an efficient storage procedure. For this kind of large volume of data storage, the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low latency. The major issue is… More >

  • Open Access

    ARTICLE

    Semantic Based Greedy Levy Gradient Boosting Algorithm for Phishing Detection

    R. Sakunthala Jenni*, S. Shankar

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 525-538, 2022, DOI:10.32604/csse.2022.019300

    Abstract The detection of phishing and legitimate websites is considered a great challenge for web service providers because the users of such websites are indistinguishable. Phishing websites also create traffic in the entire network. Another phishing issue is the broadening malware of the entire network, thus highlighting the demand for their detection while massive datasets (i.e., big data) are processed. Despite the application of boosting mechanisms in phishing detection, these methods are prone to significant errors in their output, specifically due to the combination of all website features in the training state. The upcoming big data system requires MapReduce, a popular… More >

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