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  • Open Access

    ARTICLE

    Early Detection of Autism in Children Using Transfer Learning

    Taher M. Ghazal1,2, Sundus Munir3,4, Sagheer Abbas3, Atifa Athar5, Hamza Alrababah1, Muhammad Adnan Khan6,*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 11-22, 2023, DOI:10.32604/iasc.2023.030125

    Abstract Autism spectrum disorder (ASD) is a challenging and complex neuro-development syndrome that affects the child’s language, speech, social skills, communication skills, and logical thinking ability. The early detection of ASD is essential for delivering effective, timely interventions. Various facial features such as a lack of eye contact, showing uncommon hand or body movements, babbling or talking in an unusual tone, and not using common gestures could be used to detect and classify ASD at an early stage. Our study aimed to develop a deep transfer learning model to facilitate the early detection of ASD based on facial features. A dataset… More >

  • Open Access

    ARTICLE

    Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

    Elumalaivasan Poongavanam1,*, Padmanathan Kasinathan2, Kulothungan Kanagasabai3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 249-265, 2023, DOI:10.32604/iasc.2023.030101

    Abstract The nation deserves to learn what India’s future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is… More >

  • Open Access

    ARTICLE

    An Intelligent Cardiovascular Diseases Prediction System Focused on Privacy

    Manjur Kolhar*, Mohammed Misfer

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 529-542, 2023, DOI:10.32604/iasc.2023.030098

    Abstract Machine learning (ML) and cloud computing have now evolved to the point where they are able to be used effectively. Further improvement, however, is required when both of these technologies are combined to reap maximum benefits. A way of improving the system is by enabling healthcare workers to select appropriate machine learning algorithms for prediction and, secondly, by preserving the privacy of patient data so that it cannot be misused. The purpose of this paper is to combine these promising technologies to maintain the privacy of patient data during the disease prediction process. Treatment of heart failure may be improved… More >

  • Open Access

    ARTICLE

    A Cross-Domain Trust Model of Smart City IoT Based on Self-Certification

    Yao Wang1, Yubo Wang1, Zhenhu Ning1,*, Sadaqat ur Rehman2, Muhammad Waqas1,3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 981-996, 2023, DOI:10.32604/iasc.2023.030091

    Abstract Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced… More >

  • Open Access

    ARTICLE

    Temperature Control Design with Differential Evolution Based Improved Adaptive-Fuzzy-PID Techniques

    Prabhu Kaliappan1,*, Aravindaguru Ilangovan2, Sivachitra Muthusamy3, Banumathi Sembanan4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 781-801, 2023, DOI:10.32604/iasc.2023.030047

    Abstract This paper presents the design and performance analysis of Differential Evolution (DE) algorithm based Proportional-Integral-Derivative (PID) controller for temperature control of Continuous Stirred Tank Reactor (CSTR) plant in chemical industries. The proposed work deals about the design of Differential Evolution (DE) algorithm in order to improve the performance of CSTR. In this, the process is controlled by controlling the temperature of the liquid through manipulation of the coolant flow rate with the help of modified Model Reference Adaptive Controller (MRAC). The transient response of temperature process is improved by using PID Controller, Differential Evolution Algorithm based PID and fuzzy based… More >

  • Open Access

    ARTICLE

    Precise Multi-Class Classification of Brain Tumor via Optimization Based Relevance Vector Machine

    S. Keerthi1,*, P. Santhi2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1173-1188, 2023, DOI:10.32604/iasc.2023.029959

    Abstract The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain tumors. The brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or malignant. Most tumors are misdiagnosed due to the variability and complexity of lesions, which reduces the survival rate in patients. Diagnosis of brain tumors via computer vision algorithms is a challenging task. Segmentation and classification of brain tumors are currently one of the most essential surgical and pharmaceutical procedures. Traditional brain tumor identification techniques require manual segmentation or handcrafted… More >

  • Open Access

    ARTICLE

    Multimodal Machine Learning Based Crop Recommendation and Yield Prediction Model

    P. S. S. Gopi*, M. Karthikeyan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 313-326, 2023, DOI:10.32604/iasc.2023.029756

    Abstract Agriculture plays a vital role in the Indian economy. Crop recommendation for a specific region is a tedious process as it can be affected by various variables such as soil type and climatic parameters. At the same time, crop yield prediction was based on several features like area, irrigation type, temperature, etc. The recent advancements of artificial intelligence (AI) and machine learning (ML) models pave the way to design effective crop recommendation and crop prediction models. In this view, this paper presents a novel Multimodal Machine Learning Based Crop Recommendation and Yield Prediction (MMML-CRYP) technique. The proposed MMML-CRYP model mainly… More >

  • Open Access

    ARTICLE

    Grey Wolf Optimizer Based Deep Learning for Pancreatic Nodule Detection

    T. Thanya1,*, S. Wilfred Franklin2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 97-112, 2023, DOI:10.32604/iasc.2023.029675

    Abstract At an early point, the diagnosis of pancreatic cancer is mediocre, since the radiologist is skill deficient. Serious threats have been posed due to the above reasons, hence became mandatory for the need of skilled technicians. However, it also became a time-consuming process. Hence the need for automated diagnosis became mandatory. In order to identify the tumor accurately, this research proposes a novel Convolution Neural Network (CNN) based superior image classification technique. The proposed deep learning classification strategy has a precision of 97.7%, allowing for more effective usage of the automatically executed feature extraction technique to diagnose cancer cells. Comparative… More >

  • Open Access

    ARTICLE

    Modelling Mobile-X Architecture for Offloading in Mobile Edge Computing

    G. Pandiyan*, E. Sasikala

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 617-632, 2023, DOI:10.32604/iasc.2023.029337

    Abstract Mobile Edge Computing (MEC) assists clouds to handle enormous tasks from mobile devices in close proximity. The edge servers are not allocated efficiently according to the dynamic nature of the network. It leads to processing delay, and the tasks are dropped due to time limitations. The researchers find it difficult and complex to determine the offloading decision because of uncertain load dynamic condition over the edge nodes. The challenge relies on the offloading decision on selection of edge nodes for offloading in a centralized manner. This study focuses on minimizing task-processing time while simultaneously increasing the success rate of service… More >

  • Open Access

    ARTICLE

    Design of Optical Filter Using Bald Eagle Search Optimization Algorithm

    L. Jegan Antony Marcilin*, N. M. Nandhitha

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1215-1226, 2023, DOI:10.32604/iasc.2023.028764

    Abstract Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber. Better working conditions of such machines can be monitored by analyzing its radiations. Various wavelengths such as 656.3, 486.1, 464.7 nm are quite significant which are used for health monitoring of thermonuclear machines. The optical thin film filters which work on constructive and destructive interference are the ideal choices. These filters are multilayered with a pair of high and low refractive index dielectric materials. Significantly high transmission index at the desired wavelength and relatively low transmission at the other wavelengths are desired. With this as the objective, it… More >

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