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  • Open Access


    Twitter Media Sentiment Analysis to Convert Non-Informative to Informative Using QER

    C. P. Thamil Selvi1,*, P. Muneeshwari2, K. Selvasheela3, D. Prasanna4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3545-3555, 2023, DOI:10.32604/iasc.2023.031097

    Abstract The term sentiment analysis deals with sentiment classification based on the review made by the user in a social network. The sentiment classification accuracy is evaluated using various selection methods, especially those that deal with algorithm selection. In this work, every sentiment received through user expressions is ranked in order to categorise sentiments as informative and non-informative. In order to do so, the work focus on Query Expansion Ranking (QER) algorithm that takes user text as input and process for sentiment analysis and finally produces the results as informative or non-informative. The challenge is to convert non-informative into informative using… More >

  • Open Access


    Eye Strain Detection During Online Learning

    Le Quang Thao1,2,*, Duong Duc Cuong2, Vu Manh Hung3, Le Thanh Vinh3, Doan Trong Nghia4, Dinh Ha Hai3, Nguyen Nhan Nhi3

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3517-3530, 2023, DOI:10.32604/iasc.2023.031026

    Abstract The recent outbreak of the coronavirus disease of 2019 (Covid-19) has been causing many disruptions among the education systems worldwide, most of them due to the abrupt transition to online learning. The sudden upsurge in digital electronic devices usage, namely personal computers, laptops, tablets and smartphones is unprecedented, which leads to a new wave of both mental and physical health problems among students, for example eye-related illnesses. The overexposure to electronic devices, extended screen time usage and lack of outdoor sunlight have put a consequential strain on the student’s ophthalmic health because of their young age and a relative lack… More >

  • Open Access


    Enhanced Cuckoo Search Optimization Technique for Skin Cancer Diagnosis Application

    S. Ayshwarya Lakshmi1,*, K. Anandavelu2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3403-3413, 2023, DOI:10.32604/iasc.2023.030970

    Abstract Skin cancer segmentation is a critical task in a clinical decision support system for skin cancer detection. The suggested enhanced cuckoo search based optimization model will be used to evaluate several metrics in the skin cancer picture segmentation process. Because time and resources are always limited, the proposed enhanced cuckoo search optimization algorithm is one of the most effective strategies for dealing with global optimization difficulties. One of the most significant requirements is to design optimal solutions to optimize their use. There is no particular technique that can answer all optimization issues. The proposed enhanced cuckoo search optimization method indicates… More >

  • Open Access


    DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

    E. Gokulakannan*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3415-3427, 2023, DOI:10.32604/iasc.2023.030965

    Abstract Deep learning is the subset of artificial intelligence and it is used for effective decision making. Wireless Sensor based automated irrigation system is proposed to monitor and cultivate crop. Our system consists of Distributed wireless sensor environment to handle the moisture of the soil and temperature levels. It is automated process and useful for minimizing the usage of resources such as water level, quality of the soil, fertilizer values and controlling the whole system. The mobile app based smart control system is designed using deep belief network. This system has multiple sensors placed in agricultural field and collect the data.… More >

  • Open Access


    Design of Fuzzy Logic Control Framework for QoS Routing in MANET

    M. Vargheese1,*, S. Vanithamani2, D. Stalin David3, Ganga Rama Koteswara Rao4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3479-3499, 2023, DOI:10.32604/iasc.2023.030948

    Abstract Wireless networks with no infrastructure arise as a result of multiple wireless devices working together. The Mobile Ad hoc Network (MANET) is a system for connecting independently located Mobile Nodes (MNs) via wireless links. A MANET is self-configuring in telecommunications, while MN produces non-infrastructure networks that are entirely decentralized. Both the MAC and routing layers of MANETs take into account issues related to Quality of Service (QoS). When culling a line of optical discernment communication, MANET can be an effective and cost-saving route cull option. To maintain QoS, however, more or fewer challenges must be overcome. This paper proposes a… More >

  • Open Access


    Intention Estimation of Adversarial Spatial Target Based on Fuzzy Inference

    Wenjia Xiang1, Xiaoyu Li1,*, Zirui He1, Chenjing Su1, Wangchi Cheng2, Chao Lu3, Shan Yang4

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3627-3639, 2023, DOI:10.32604/iasc.2023.030904

    Abstract Estimating the intention of space objects plays an important role in aircraft design, aviation safety, military and other fields, and is an important reference basis for air situation analysis and command decision-making. This paper studies an intention estimation method based on fuzzy theory, combining probability to calculate the intention between two objects. This method takes a space object as the origin of coordinates, observes the target’s distance, speed, relative heading angle, altitude difference, steering trend and etc., then introduces the specific calculation methods of these parameters. Through calculation, values are input into the fuzzy inference model, and finally the action… More >

  • Open Access


    Encephalitis Detection from EEG Fuzzy Density-Based Clustering Model with Multiple Centroid

    Hanan Abdullah Mengash1, Alaaeldin M. Hafez2, Hanan A. Hosni Mahmoud3,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3129-3140, 2023, DOI:10.32604/iasc.2023.030836

    Abstract Encephalitis is a brain inflammation disease. Encephalitis can yield to seizures, motor disability, or some loss of vision or hearing. Sometimes, encephalitis can be a life-threatening and proper diagnosis in an early stage is very crucial. Therefore, in this paper, we are proposing a deep learning model for computerized detection of Encephalitis from the electroencephalogram data (EEG). Also, we propose a Density-Based Clustering model to classify the distinctive waves of Encephalitis. Customary clustering models usually employ a computed single centroid virtual point to define the cluster configuration, but this single point does not contain adequate information. To precisely extract accurate… More >

  • Open Access


    Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security

    Amal H. Alharbi1, S. Karthick2, K. Venkatachalam3, Mohamed Abouhawwash4,5, Doaa Sami Khafaga1,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2773-2787, 2023, DOI:10.32604/iasc.2023.030763

    Abstract Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security techniques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of… More >

  • Open Access


    Automatic Clustering of User Behaviour Profiles for Web Recommendation System

    S. Sadesh1,*, Osamah Ibrahim Khalaf2, Mohammad Shorfuzzaman3, Abdulmajeed Alsufyani3, K. Sangeetha4, Mueen Uddin5

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3365-3384, 2023, DOI:10.32604/iasc.2023.030751

    Abstract Web usage mining, content mining, and structure mining comprise the web mining process. Web-Page Recommendation (WPR) development by incorporating Data Mining Techniques (DMT) did not include end-users with improved performance in the obtained filtering results. The cluster user profile-based clustering process is delayed when it has a low precision rate. Markov Chain Monte Carlo-Dynamic Clustering (MC2-DC) is based on the User Behavior Profile (UBP) model group’s similar user behavior on a dynamic update of UBP. The Reversible-Jump Concept (RJC) reviews the history with updated UBP and moves to appropriate clusters. Hamilton’s Filtering Framework (HFF) is designed to filter user data… More >

  • Open Access


    Enhanced Feature Fusion Segmentation for Tumor Detection Using Intelligent Techniques

    R. Radha1,*, R. Gopalakrishnan2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3113-3127, 2023, DOI:10.32604/iasc.2023.030667

    Abstract In the field of diagnosis of medical images the challenge lies in tracking and identifying the defective cells and the extent of the defective region within the complex structure of a brain cavity. Locating the defective cells precisely during the diagnosis phase helps to fight the greatest exterminator of mankind. Early detection of these defective cells requires an accurate computer-aided diagnostic system (CAD) that supports early treatment and promotes survival rates of patients. An earlier version of CAD systems relies greatly on the expertise of radiologist and it consumed more time to identify the defective region. The manuscript takes the… More >

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