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  • Open Access

    ARTICLE

    Effective Denoising Architecture for Handling Multiple Noises

    Na Hyoun Kim, Namgyu Kim*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2667-2682, 2023, DOI:10.32604/csse.2023.029732

    Abstract Object detection, one of the core research topics in computer vision, is extensively used in various industrial activities. Although there have been many studies of daytime images where objects can be easily detected, there is relatively little research on nighttime images. In the case of nighttime, various types of noises, such as darkness, haze, and light blur, deteriorate image quality. Thus, an appropriate process for removing noise must precede to improve object detection performance. Although there are many studies on removing individual noise, only a few studies handle multiple noises simultaneously. In this paper, we propose a convolutional denoising autoencoder… More >

  • Open Access

    ARTICLE

    Deep Learning with Natural Language Processing Enabled Sentimental Analysis on Sarcasm Classification

    Abdul Rahaman Wahab Sait1,*, Mohamad Khairi Ishak2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2553-2567, 2023, DOI:10.32604/csse.2023.029603

    Abstract Sentiment analysis (SA) is the procedure of recognizing the emotions related to the data that exist in social networking. The existence of sarcasm in textual data is a major challenge in the efficiency of the SA. Earlier works on sarcasm detection on text utilize lexical as well as pragmatic cues namely interjection, punctuations, and sentiment shift that are vital indicators of sarcasm. With the advent of deep-learning, recent works, leveraging neural networks in learning lexical and contextual features, removing the need for handcrafted feature. In this aspect, this study designs a deep learning with natural language processing enabled SA (DLNLP-SA)… More >

  • Open Access

    ARTICLE

    Secure e-Prescription Management System: Mitigating Blended Threat in IoBE

    Deukhun Kim1, Heejin Kim2, Jin Kwak3,*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2501-2519, 2023, DOI:10.32604/csse.2023.029356

    Abstract New information and communication technologies (ICT) are being applied in various industries to upgrade the value of the major service items. Moreover, data collection, storage, processing, and security applications have led to the creation of an interrelated ICT environment in which one industry can directly influence the other. This is called the “internet of blended environments” (IoBE), as it is an interrelated data environment based on internet-of-things collection activities. In this environment, security incidents may increase as size and interconnectivity of attackable operations grow. Consequently, preemptive responses to combined security threats are needed to securely utilize IoBE across industries. For… More >

  • Open Access

    ARTICLE

    Hybrid Trust Based Reputation Mechanism for Discovering Malevolent Node in MANET

    S. Neelavathy Pari1,*, K. Sudharson2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2775-2789, 2023, DOI:10.32604/csse.2023.029345

    Abstract A self-contained connection of wireless links that functions without any infrastructure is known as Mobile Ad Hoc Network (MANET). A MANET’s nodes could engage actively and dynamically with one another. However, MANETs, from the other side, are exposed to severe potential threats that are difficult to counter with present security methods. As a result, several safe communication protocols designed to enhance the secure interaction among MANET nodes. In this research, we offer a reputed optimal routing value among network nodes, secure computations, and misbehavior detection predicated on node’s trust levels with a Hybrid Trust based Reputation Mechanism (HTRM). In addition,… More >

  • Open Access

    ARTICLE

    Rotation, Translation and Scale Invariant Sign Word Recognition Using Deep Learning

    Abu Saleh Musa Miah1, Jungpil Shin1,*, Md. Al Mehedi Hasan1, Md Abdur Rahim2, Yuichi Okuyama1

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2521-2536, 2023, DOI:10.32604/csse.2023.029336

    Abstract Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious task. One of the main functions of sign language is to communicate with each other through hand gestures. Recognition of hand gestures has become an important challenge for the recognition of sign language. There are many existing models that can produce a good accuracy, but if the model test with rotated or translated images, they may face some difficulties to make good performance accuracy. To resolve these challenges of hand gesture recognition, we proposed a Rotation, Translation… More >

  • Open Access

    ARTICLE

    The Laplacian Energy of Hesitancy Fuzzy Graphs in Decision-Making Problems

    N. Rajagopal Reddy1, Mohammad Zubair Khan2, S. Sharief Basha3, Abdulrahman Alahmadi2, Ahmed H. Alahmadi2, Chiranji Lal Chowdhary4,*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2637-2653, 2023, DOI:10.32604/csse.2023.029255

    Abstract Decision-making (DM) is a process in which several persons concurrently engage, examine the problems, evaluate potential alternatives, and select an appropriate option to the problem. Technique for determining order preference by similarity to the ideal solution (TOPSIS) is an established DM process. The objective of this report happens to broaden the approach of TOPSIS to solve the DM issues designed with Hesitancy fuzzy data, in which evaluation evidence given by the experts on possible solutions is presents as Hesitancy fuzzy decision matrices, each of which is defined by Hesitancy fuzzy numbers. Findings: we represent analytical results, such as designing a… More >

  • Open Access

    ARTICLE

    SA-MSVM: Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

    C. P. Thamil Selvi1,*, R. PushpaLakshmi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2439-2456, 2023, DOI:10.32604/csse.2023.029254

    Abstract One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics. Bigdata is created from social websites like Facebook, WhatsApp, Twitter, etc. Opinions about products, persons, initiatives, political issues, research achievements, and entertainment are discussed on social websites. The unique data analytics method cannot be applied to various social websites since the data formats are different. Several approaches, techniques, and tools have been used for big data analytics, opinion mining, or sentiment analysis, but the accuracy is yet to be improved. The proposed work is motivated to do sentiment analysis on Twitter data… More >

  • Open Access

    ARTICLE

    Effective Customer Review Analysis Using Combined Capsule Networks with Matrix Factorization Filtering

    K. Selvasheela1,*, A. M. Abirami2, Abdul Khader Askarunisa3

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2537-2552, 2023, DOI:10.32604/csse.2023.029148

    Abstract Nowadays, commercial transactions and customer reviews are part of human life and various business applications. The technologies create a great impact on online user reviews and activities, affecting the business process. Customer reviews and ratings are more helpful to the new customer to purchase the product, but the fake reviews completely affect the business. The traditional systems consume maximum time and create complexity while analyzing a large volume of customer information. Therefore, in this work optimized recommendation system is developed for analyzing customer reviews with minimum complexity. Here, Amazon Product Kaggle dataset information is utilized for investigating the customer review.… More >

  • Open Access

    ARTICLE

    Hybrid Approach for Privacy Enhancement in Data Mining Using Arbitrariness and Perturbation

    B. Murugeshwari1,*, S. Rajalakshmi1, K. Sudharson2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2293-2307, 2023, DOI:10.32604/csse.2023.029074

    Abstract Imagine numerous clients, each with personal data; individual inputs are severely corrupt, and a server only concerns the collective, statistically essential facets of this data. In several data mining methods, privacy has become highly critical. As a result, various privacy-preserving data analysis technologies have emerged. Hence, we use the randomization process to reconstruct composite data attributes accurately. Also, we use privacy measures to estimate how much deception is required to guarantee privacy. There are several viable privacy protections; however, determining which one is the best is still a work in progress. This paper discusses the difficulty of measuring privacy while… More >

  • Open Access

    ARTICLE

    Tracking Pedestrians Under Occlusion in Parking Space

    Zhengshu Zhou1,*, Shunya Yamada2, Yousuke Watanabe2, Hiroaki Takada1,2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2109-2127, 2023, DOI:10.32604/csse.2023.029005

    Abstract Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians’ sudden appearance in the vehicle’s path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision… More >

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