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  • Open Access

    ARTICLE

    Robust ACO-Based Landmark Matching and Maxillofacial Anomalies Classification

    Dalel Ben Ismail1, Hela Elmannai2,*, Souham Meshoul2, Mohamed Saber Naceur1

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2219-2236, 2023, DOI:10.32604/iasc.2023.028944

    Abstract Imagery assessment is an efficient method for detecting craniofacial anomalies. A cephalometric landmark matching approach may help in orthodontic diagnosis, craniofacial growth assessment and treatment planning. Automatic landmark matching and anomalies detection helps face the manual labelling limitations and optimize preoperative planning of maxillofacial surgery. The aim of this study was to develop an accurate Cephalometric Landmark Matching method as well as an automatic system for anatomical anomalies classification. First, the Active Appearance Model (AAM) was used for the matching process. This process was achieved by the Ant Colony Optimization (ACO) algorithm enriched with proximity information. Then, the maxillofacial anomalies… More >

  • Open Access

    ARTICLE

    THD Reduction for Permanent Magnet Synchronous Motor Using Simulated Annealing

    R. Senthil Rama1, C. R. Edwin Selva Rex2, N. Herald Anantha Rufus3,*, J. Annrose4

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2325-2336, 2023, DOI:10.32604/iasc.2023.028930

    Abstract Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion (THD) technique. Reduced THD achieves lower peak current, higher efficiency and longer equipment life span. Simulated annealing (SA) is applied due to the effectiveness of locating solutions that are close to ideal and to challenge large-scale combinatorial optimization for Permanent Magnet Synchronous Machine (PMSM). The parameters of direct torque controllers (DTC) for the drive are automatically adjusted by the optimization algorithm. Advantages of the PI-Fuzzy-SA algorithm are retained when used together. It also improves the rate of system convergence. Speed response improvement and harmonic… More >

  • Open Access

    ARTICLE

    A Novel Outlier Detection with Feature Selection Enabled Streaming Data Classification

    R. Rajakumar1,*, S. Sathiya Devi2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2101-2116, 2023, DOI:10.32604/iasc.2023.028889

    Abstract Due to the advancements in information technologies, massive quantity of data is being produced by social media, smartphones, and sensor devices. The investigation of data stream by the use of machine learning (ML) approaches to address regression, prediction, and classification problems have received considerable interest. At the same time, the detection of anomalies or outliers and feature selection (FS) processes becomes important. This study develops an outlier detection with feature selection technique for streaming data classification, named ODFST-SDC technique. Initially, streaming data is pre-processed in two ways namely categorical encoding and null value removal. In addition, Local Correlation Integral (LOCI)… More >

  • Open Access

    ARTICLE

    Wireless Network Security Using Load Balanced Mobile Sink Technique

    Reem Alkanhel1, Mohamed Abouhawwash2,3, S. N. Sangeethaa4, K. Venkatachalam5, Doaa Sami Khafaga6,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2135-2149, 2023, DOI:10.32604/iasc.2023.028852

    Abstract Real-time applications based on Wireless Sensor Network (WSN) technologies are quickly increasing due to intelligent surroundings. Among the most significant resources in the WSN are battery power and security. Clustering strategies improve the power factor and secure the WSN environment. It takes more electricity to forward data in a WSN. Though numerous clustering methods have been developed to provide energy consumption, there is indeed a risk of unequal load balancing, resulting in a decrease in the network’s lifetime due to network inequalities and less security. These possibilities arise due to the cluster head’s limited life span. These cluster heads (CH)… More >

  • Open Access

    ARTICLE

    Secured Cyber Security Algorithm for Healthcare System Using Blockchain Technology

    D. Doreen Hephzibah Miriam1, Deepak Dahiya2, Nitin3, C. R. Rene Robin4,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1889-1906, 2023, DOI:10.32604/iasc.2023.028850

    Abstract Blockchain technology is critical in cyber security. The most recent cryptographic strategies may be hacked as efforts are made to build massive electronic circuits. Because of the ethical and legal implications of a patient’s medical data, cyber security is a critical and challenging problem in healthcare. The image secrecy is highly vulnerable to various types of attacks. As a result, designing a cyber security model for healthcare applications necessitates extra caution in terms of data protection. To resolve this issue, this paper proposes a Lionized Golden Eagle based Homomorphic Elapid Security (LGE-HES) algorithm for the cybersecurity of blockchain in healthcare… More >

  • Open Access

    ARTICLE

    Implementation of FPGA Based MPPT Techniques for Grid-Connected PV System

    Thamatapu Eswara Rao*, S. Elango

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1783-1798, 2023, DOI:10.32604/iasc.2023.028835

    Abstract Global energy demand is growing rapidly owing to industrial growth and urbanization. Alternative energy sources are driven by limited reserves and rapid depletion of conventional energy sources (e.g., fossil fuels).Solar photovoltaic (PV), as a source of electricity, has grown in popularity over the last few decades because of their clean, noise-free, low-maintenance, and abundant availability of solar energy. There are two types of maximum power point tracking (MPPT) techniques: classical and evolutionary algorithm-based techniques. Precise and less complex perturb and observe (P&O) and incremental conductance (INC) approaches are extensively employed among classical techniques. This study used a field-programmable gate array… More >

  • Open Access

    ARTICLE

    Defending Adversarial Examples by a Clipped Residual U-Net Model

    Kazim Ali1,*, Adnan N. Qureshi1, Muhammad Shahid Bhatti2, Abid Sohail2, Mohammad Hijji3

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2237-2256, 2023, DOI:10.32604/iasc.2023.028810

    Abstract Deep learning-based systems have succeeded in many computer vision tasks. However, it is found that the latest study indicates that these systems are in danger in the presence of adversarial attacks. These attacks can quickly spoil deep learning models, e.g., different convolutional neural networks (CNNs), used in various computer vision tasks from image classification to object detection. The adversarial examples are carefully designed by injecting a slight perturbation into the clean images. The proposed CRU-Net defense model is inspired by state-of-the-art defense mechanisms such as MagNet defense, Generative Adversarial Network Defense, Deep Regret Analytic Generative Adversarial Networks Defense, Deep Denoising… More >

  • Open Access

    ARTICLE

    Networking Controller Based Real Time Traffic Prediction in Clustered Vehicular Adhoc Networks

    T. S. Balaji1,2, S. Srinivasan3,*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2189-2203, 2023, DOI:10.32604/iasc.2023.028785

    Abstract The vehicular ad hoc network (VANET) is an emerging network technology that has gained popularity because to its low cost, flexibility, and seamless services. Software defined networking (SDN) technology plays a critical role in network administration in the future generation of VANET with fifth generation (5G) networks. Regardless of the benefits of VANET, energy economy and traffic control are significant architectural challenges. Accurate and real-time traffic flow prediction (TFP) becomes critical for managing traffic effectively in the VANET. SDN controllers are a critical issue in VANET, which has garnered much interest in recent years. With this objective, this study develops… More >

  • Open Access

    ARTICLE

    Adaptive Sub-Threshold Voltage Level Control for Voltage Deviate-Domino Circuits

    C. Arun Prasath1,*, C. Gowri Shankar2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1767-1781, 2023, DOI:10.32604/iasc.2023.028758

    Abstract Leakage power and propagation delay are two significant issues found in sub-micron technology-based Complementary Metal-Oxide-Semiconductor (CMOS)-based Very Large-Scale Integration (VLSI) circuit designs. Positive Channel Metal Oxide Semiconductor (PMOS) has been replaced by Negative Channel Metal Oxide Semiconductor (NMOS) in recent years, with low dimension-switching changes in order to shape the mirror of voltage comparator. NMOS is used to reduce stacking leakage as well as total exchange. Domino Logic Circuit is a powerful and versatile digital programmer that gained popularity in recent years. In this study regarding Adaptive Sub Threshold Voltage Level Control Problem, the researchers intend to solve the contention… More >

  • Open Access

    ARTICLE

    Harnessing LSTM Classifier to Suggest Nutrition Diet for Cancer Patients

    S. Raguvaran1,*, S. Anandamurugan2, A. M. J. Md. Zubair Rahman3

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2171-2187, 2023, DOI:10.32604/iasc.2023.028605

    Abstract A customized nutrition-rich diet plan is of utmost importance for cancer patients to intake healthy and nutritious foods that help them to be strong enough to maintain their body weight and body tissues. Consuming nutrition-rich diet foods will prevent them from the side effects caused before and after treatment thereby minimizing it. This work is proposed here to provide them with an effective diet assessment plan using deep learning-based automated medical diet system. Hence, an Enhanced Long-Short Term Memory (E-LSTM) has been proposed in this paper, especially for cancer patients. This proposed method will be very useful for cancer patients… More >

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