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  • Open Access

    ARTICLE

    Multi-Domain Deep Convolutional Neural Network for Ancient Urdu Text Recognition System

    K. O. Mohammed Aarif1,*, P. Sivakumar2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 275-289, 2022, DOI:10.32604/iasc.2022.022805

    Abstract Deep learning has achieved magnificent success in the field of pattern recognition. In recent years Urdu character recognition system has significantly benefited from the effectiveness of the deep convolutional neural network. Majority of the research on Urdu text recognition are concentrated on formal handwritten and printed Urdu text document. In this paper, we experimented the Challenging issue of text recognition in Urdu ancient literature documents. Due to its cursiveness, complex word formation (ligatures), and context-sensitivity, and inadequate benchmark dataset, recognition of Urdu text from the literature document is very difficult to process compared to the formal Urdu text document. In… More >

  • Open Access

    ARTICLE

    Social Networks Fake Account and Fake News Identification with Reliable Deep Learning

    N. Kanagavalli1,*, S. Baghavathi Priya2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 191-205, 2022, DOI:10.32604/iasc.2022.022720

    Abstract Recent developments of the World Wide Web (WWW) and social networking (Twitter, Instagram, etc.) paves way for data sharing which has never been observed in the human history before. A major security issue in this network is the creation of fake accounts. In addition, the automatic classification of the text article as true or fake is also a crucial process. The ineffectiveness of humans in distinguishing the true and false information exposes the fake news as a risk to credibility, democracy, logical truth, and journalism in government sectors. Besides, the automatic fake news or rumors from the social networking sites… More >

  • Open Access

    ARTICLE

    Multi-Model CNN-RNN-LSTM Based Fruit Recognition and Classification

    Harmandeep Singh Gill1,*, Osamah Ibrahim Khalaf2, Youseef Alotaibi3, Saleh Alghamdi4, Fawaz Alassery5

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 637-650, 2022, DOI:10.32604/iasc.2022.022589

    Abstract Contemporary vision and pattern recognition issues such as image, face, fingerprint identification, and recognition, DNA sequencing, often have a large number of properties and classes. To handle such types of complex problems, one type of feature descriptor is not enough. To overcome these issues, this paper proposed a multi-model recognition and classification strategy using multi-feature fusion approaches. One of the growing topics in computer and machine vision is fruit and vegetable identification and categorization. A fruit identification system may be employed to assist customers and purchasers in identifying the species and quality of fruit. Using Convolution Neural Network (CNN), Recurrent… More >

  • Open Access

    ARTICLE

    Error Rate Analysis of Intelligent Reflecting Surfaces Aided Non-Orthogonal Multiple Access System

    A. Vasuki1, Vijayakumar Ponnusamy2,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 71-86, 2022, DOI:10.32604/iasc.2022.022586

    Abstract A good wireless device in a system needs high spectral efficiency. Non-Orthogonal Multiple Access (NOMA) is a technique used to enhance spectral efficiency, thereby allowing users to share information at the same time and same frequency. The information of the user is super-positioned either in the power or code domain. However, interference cancellation in NOMA aided system is challenging as it determines the reliability of the system in terms of Bit Error Rate (BER). BER is an essential performance parameter for any wireless network. Intelligent Reflecting Surfaces (IRS) enhances the BER of the users by controlling the electromagnetic wave propagation… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Learning-Based Long Short-Term Memory for Satellite IoT Channel Allocation

    S. Lakshmi Durga1, Ch. Rajeshwari1, Khalid Hamed Allehaibi2, Nishu Gupta3,*, Nasser Nammas Albaqami4, Isha Bharti5, Ahmad Hoirul Basori6

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 1-19, 2022, DOI:10.32604/iasc.2022.022536

    Abstract In recent years, the demand for smart wireless communication technology has increased tremendously, and it urges to extend internet services globally with high reliability, less cost and minimal delay. In this connection, low earth orbit (LEO) satellites have played prominent role by reducing the terrestrial infrastructure facilities and providing global coverage all over the earth with the help of satellite internet of things (SIoT). LEO satellites provide wide coverage area to dynamically accessing network with limited resources. Presently, most resource allocation schemes are designed only for geostationary earth orbit (GEO) satellites. For LEO satellites, resource allocation is challenging due to… More >

  • Open Access

    ARTICLE

    A Novel Method of User Identity Recognition Based on Finger Trajectory

    Xia Zhou1, Zijian Wang2, Tianyu Wang2, Jin Han2,*, Zhiling Wang2, Yannan Qian3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 473-481, 2022, DOI:10.32604/iasc.2022.022493

    Abstract User identity recognition is the key shield to protect users’ privacy data from disclosure and embezzlement. The user identity of mobile devices such as mobile phones mainly includes fingerprint recognition, nine-grid password, face recognition, digital password, etc. Due to the requirements of computing resources and convenience of mobile devices, these verification methods have their own shortcomings. In this paper, a user identity recognition technology based on finger trajectory is proposed. Based on the analysis of the users’ finger trajectory data, the feature of the user's finger movement trajectory is extracted to realize the identification of the user. Also, in this… More >

  • Open Access

    ARTICLE

    Adaptive XGBOOST Hyper Tuned Meta Classifier for Prediction of Churn Customers

    B. Srikanth1,*, Swarajya Lakshmi V. Papineni2, Gutta Sridevi3, D. N. V. S. L. S. Indira4, K. S. R. Radhika5, Khasim Syed6

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 21-34, 2022, DOI:10.32604/iasc.2022.022423

    Abstract In India, the banks have a formidable edge in maintaining their customer retention ratio for past few decades. Downfall makes the private banks to reduce their operations and the nationalised banks merge with other banks. The researchers have used the traditional and ensemble algorithms with relevant feature engineering techniques to better classify the customers. The proposed algorithm uses a Meta classifier instead of an ensemble algorithm with an adaptive genetic algorithm for feature selection. Churn prediction is the number of customers who wants to terminate their services in the banking sector. The model considers twelve attributes like credit score, geography,… More >

  • Open Access

    ARTICLE

    Three to Six Phase Power Converter with Partial Resonant AC Link

    V. Ravikumar1,*, S. Muralidharan2, C. Vidhya1

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 207-225, 2022, DOI:10.32604/iasc.2022.022370

    Abstract A six phase system is a balanced multiphase system that can be replace, in certain applications, the three phase system and the application becomes much fault tolerant. In the six phase system a phase angle of 60 degrees is maintained between the phases. Handling power with more number of phases reduces the maximum current in each of the phase in the system. In this work a six phase balanced AC output is derived from a three phase AC source. The proposed system uses a resonant single phase AC link driven by a three phase bidirectional converter unit AC link is… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Deep Learning Framework for Intrusion Detection Systems in WSN-IoT Networks

    M. Maheswari1,2,*, R. A. Karthika1

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 365-382, 2022, DOI:10.32604/iasc.2022.022259

    Abstract With the advent of wireless communication and digital technology, low power, Internet-enabled, and reconfigurable wireless devices have been developed, which revolutionized day-to-day human life and the economy across the globe. These devices are realized by leveraging the features of sensing, processing the data and nodes communications. The scale of Internet-enabled wireless devices has increased daily, and these devices are exposed to various cyber-attacks. Since the complexity and dynamics of the attacks on the devices are computationally high, intelligent, scalable and high-speed intrusion detection systems (IDS) are required. Moreover, the wireless devices are battery-driven; implementing them would consume more energy, weakening… More >

  • Open Access

    ARTICLE

    Deep Embedded Fuzzy Clustering Model for Collaborative Filtering Recommender System

    Adel Binbusayyis*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 501-513, 2022, DOI:10.32604/iasc.2022.022239

    Abstract The increasing user of Internet has witnessed a continued exploration in applications and services that can bring more convenience in people's life than ever before. At the same time, with the exploration of online services, the people face unprecedented difficulty in selecting the most relevant service on the fly. In this context, the need for recommendation system is of paramount importance especially in helping the users to improve their experience with best value-added service. But, most of the traditional techniques including collaborative filtering (CF) which is one of the most successful recommendation technique suffer from two inherent issues namely, rating… More >

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