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  • 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 >

  • Open Access

    ARTICLE

    Enhanced Mesh Network Using Novel Forgotten Polynomial Algorithm for Pharmaceutical Design

    D. Ahila Jeyanthi*, T. M. Selvarajan

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 669-680, 2022, DOI:10.32604/iasc.2022.022187

    Abstract The molecular structures are modelled as graphs which are called the molecular graphs. In these graphs, each vertex represents an atom and each edge denotes covalent bond between atoms. It is shown that the topological indices defined on the molecular graphs can reflect the chemical characteristics of chemical compounds and drugs. A large number of previous drug experiments revealed that there are strong inherent connections between the drug’s molecular structures and the bio-medical and pharmacology characteristics. The forgotten topological index is introduced to be applied into chemical compound and drug molecular structures, which is quite helpful for medical and pharmaceutical… More >

  • Open Access

    ARTICLE

    Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

    R. K. Rojin1,*, M. Mary Linda2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 245-258, 2022, DOI:10.32604/iasc.2022.021834

    Abstract Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate… More >

  • Open Access

    ARTICLE

    Insider Threat Detection Based on NLP Word Embedding and Machine Learning

    Mohd Anul Haq1, Mohd Abdul Rahim Khan1,*, Mohammed Alshehri2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 619-635, 2022, DOI:10.32604/iasc.2022.021430

    Abstract The growth of edge computing, the Internet of Things (IoT), and cloud computing have been accompanied by new security issues evolving in the information security infrastructure. Recent studies suggest that the cost of insider attacks is higher than the external threats, making it an essential aspect of information security for organizations. Efficient insider threat detection requires state-of-the-art Artificial Intelligence models and utility. Although significant have been made to detect insider threats for more than a decade, there are many limitations, including a lack of real data, low accuracy, and a relatively low false alarm, which are major concerns needing further… More >

  • Open Access

    ARTICLE

    Light-Weight Present Block Cipher Model for IoT Security on FPGA

    R. Bharathi*, N. Parvatham

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 35-49, 2022, DOI:10.32604/iasc.2022.020681

    Abstract The Internet of Things (IoT) plays an essential role in connecting a small number of billion devices with people for diverse applications. The security and privacy with authentication are challenging work for IoT devices. A light-weight block cipher is designed and modeled with IoT security for real-time scenarios to overcome the above challenges. The light-weight PRESENT module with the integration of encryption (E)-decryption (D) is modeled and implemented on FPGA. The PRESENT module has 64-bit data input with 80/128/256-bit symmetric keys for IoT security. The PRESENT module performs16/32/64 round operations for state register and key updation. The design mainly uses… More >

  • Open Access

    ARTICLE

    Bidirectional Long Short-Term Memory Network for Taxonomic Classification

    Naglaa. F. Soliman1,*, Samia M. Abd Alhalem2, Walid El-Shafai2, Salah Eldin S. E. Abdulrahman3, N. Ismaiel3, El-Sayed M. El-Rabaie2, Abeer D. Algarni1, Fatimah Algarni4, Fathi E. Abd El-Samie1,2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 103-116, 2022, DOI:10.32604/iasc.2022.017691

    Abstract Identifying and classifying Deoxyribonucleic Acid (DNA) sequences and their functions have been considered as the main challenges in bioinformatics. Advances in machine learning and Deep Learning (DL) techniques are expected to improve DNA sequence classification. Since the DNA sequence classification depends on analyzing textual data, Bidirectional Long Short-Term Memory (BLSTM) algorithms are suitable for tackling this task. Generally, classifiers depend on the patterns to be processed and the pre-processing method. This paper is concerned with a new proposed classification framework based on Frequency Chaos Game Representation (FCGR) followed by Discrete Wavelet Transform (DWT) and BLSTM. Firstly, DNA strings are transformed… More >

  • Open Access

    ARTICLE

    Modelling of the Slope Solute Loss Based on Fuzzy Neural Network Model

    Xiaona Zhang1,*, Jie Feng2, Zhen Hong3, Xiaona Rui4

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 677-688, 2022, DOI:10.32604/csse.2022.023136

    Abstract In regards to soil macropores, the solute loss carried by overland flow is a very complex process. In this study, a fuzzy neural network (FNN) model was used to analyze the solute loss on slopes, taking into account the soil macropores. An artificial rainfall simulation experiment was conducted in indoor experimental tanks, and the verification of the model was based on the results. The characteristic scale of the macropores, the rainfall intensity and duration, the slope and the adsorption coefficient of ions, were chosen as the input variables to the Sugeno FNN model. The cumulative solute loss quantity on the… More >

  • Open Access

    ARTICLE

    Roosters Algorithm: A Novel Nature-Inspired Optimization Algorithm

    Mashar Gencal1,*, Mustafa Oral2

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 727-737, 2022, DOI:10.32604/csse.2022.023018

    Abstract Some species of females, e.g., chicken, bird, fish etc., might mate with more than one males. In the mating of these polygamous creatures, there is competition between males as well as among their offspring. Thus, male reproductive success depends on both male competition and sperm rivalry. Inspired by this type of sexual life of roosters with chickens, a novel nature-inspired optimization algorithm called Roosters Algorithm (RA) is proposed. The algorithm was modelled and implemented based on the sexual behavior of roosters. 13 well-known benchmark optimization functions and 10 IEEE CEC 2018 test functions are utilized to compare the performance of… More >

  • Open Access

    ARTICLE

    CNN Based Automated Weed Detection System Using UAV Imagery

    Mohd Anul Haq*

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 837-849, 2022, DOI:10.32604/csse.2022.023016

    Abstract The problem of weeds in crops is a natural problem for farmers. Machine Learning (ML), Deep Learning (DL), and Unmanned Aerial Vehicles (UAV) are among the advanced technologies that should be used in order to reduce the use of pesticides while also protecting the environment and ensuring the safety of crops. Deep Learning-based crop and weed identification systems have the potential to save money while also reducing environmental stress. The accuracy of ML/DL models has been proven to be restricted in the past due to a variety of factors, including the selection of an efficient wavelength, spatial resolution, and the… More >

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