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  • Open Access

    ARTICLE

    Intelligent Computing and Control Framework for Smart Automated System

    R. Manikandan1,*, G. Ranganathan2, V. Bindhu3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 173-189, 2022, DOI:10.32604/iasc.2022.023922 - 05 January 2022

    Abstract This paper presents development and analysis of different control strategies for smart automated system. The dynamic role of an electrical motor and sensor interfacing with wireless module becomes an essential element in a smart agriculture system to monitor various environmental parameters. The various key parameters such as temperature, humidity, air pressure, soil health and solar radiation are widely used to analyze the growth of plants and soil health based on different climate conditions. However, the smart development of an automatic system to measure these vital parameters provides a feasible approach and helps the farmers to… More >

  • Open Access

    ARTICLE

    Political Ideology Detection of News Articles Using Deep Neural Networks

    Khudran M. Alzhrani*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 483-500, 2022, DOI:10.32604/iasc.2022.023914 - 05 January 2022

    Abstract Individuals inadvertently allow emotions to drive their rational thoughts to predetermined conclusions regarding political partiality issues. Being well-informed about the subject in question mitigates emotions’ influence on humans’ cognitive reasoning, but it does not eliminate bias. By nature, humans tend to pick a side based on their beliefs, personal interests, and principles. Hence, journalists’ political leaning is defining factor in the rise of the polarity of political news coverage. Political bias studies usually align subjects or controversial topics of the news coverage to a particular ideology. However, politicians as private citizens or public officials are… More >

  • Open Access

    ARTICLE

    Integrated Renewable Smart Grid System Using Fuzzy Based Intelligent Controller

    V. Vijayal1,*, K. Krishnamoorthi2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 651-667, 2022, DOI:10.32604/iasc.2022.023890 - 05 January 2022

    Abstract In high power medium voltage applications, the utilization of 5-H Bridge Multi-Level Inverter (MLI) has grown vastly in recent years. The 5-H Bridge MLI can effectively control link voltage as well as power factor. However, the inverter imparts harmonics owing to the high switching frequency. Hence Inductance Capacitance Inductance (LCL) filter is implemented at its output to mitigate harmonics in presence of non-linear load. It’s of highly important to choose LCL parameters wisely in order to attain good filtering effect. This work investigates the application of 5-H Bridge MLI with LCL filter at the output… More >

  • Open Access

    ARTICLE

    Android Malware Detection Based on Feature Selection and Weight Measurement

    Huizhong Sun1, Guosheng Xu1,*, Zhimin Wu2, Ruijie Quan3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 585-600, 2022, DOI:10.32604/iasc.2022.023874 - 05 January 2022

    Abstract With the rapid development of Android devices, Android is currently one of the most popular mobile operating systems. However, it is also believed to be an entry point of many attack vectors. The existing Android malware detection method does not fare well when dealing with complex and intelligent malware applications, especially those based on feature detection systems which have become increasingly elusive. Therefore, we propose a novel feature selection algorithm called frequency differential selection (FDS) and weight measurement for Android malware detection. The purpose is to solve the shortcomings of the existing feature selection algorithms… More >

  • Open Access

    ARTICLE

    VANET: Optimal Cluster Head Selection Using Opposition Based Learning

    S. Aravindkumar*, P. Varalakshmi

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 601-617, 2022, DOI:10.32604/iasc.2022.023783 - 05 January 2022

    Abstract

    Traffic related accidents and route congestions remain to dwell significant issues in the globe. To overcome this, VANET was proposed to enhance the traffic management. However, there are several drawbacks in VANET such as collision of vehicles, data transmission in high probability of network fragmentation and data congestion. To overcome these issues, the Enhanced Pigeon Inspired Optimization (EPIO) and the Adaptive Neuro Fuzzy Inference System (ANFIS) based methods have been proposed. The Cluster Head (CH) has been selected optimally using the EPIO approach, and then the ANFIS has been used for updating and validating the

    More >

  • Open Access

    ARTICLE

    Federated Learning for Privacy-Preserved Medical Internet of Things

    Navod Neranjan Thilakarathne1, G. Muneeswari2, V. Parthasarathy3, Fawaz Alassery4, Habib Hamam5, Rakesh Kumar Mahendran6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 157-172, 2022, DOI:10.32604/iasc.2022.023763 - 05 January 2022

    Abstract Healthcare is one of the notable areas where the integration of the Internet of Things (IoT) is highly adopted, also known as the Medical IoT (MIoT). So far, MIoT is revolutionizing healthcare because it provides many advantages for the benefit of patients and healthcare personnel. The use of MIoT is becoming a booming trend, generating a large amount of IoT data, which requires proper analysis to infer meaningful information. This has led to the rise of deploying artificial intelligence (AI) technologies, such as machine learning (ML) and deep learning (DL) algorithms, to learn the meaning… More >

  • Open Access

    ARTICLE

    Face Recognition System Using Deep Belief Network and Particle Swarm Optimization

    K. Babu1,*, C. Kumar2, C. Kannaiyaraju3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756 - 05 January 2022

    Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component… More >

  • Open Access

    ARTICLE

    Requirements Engineering: Conflict Detection Automation Using Machine Learning

    Hatim Elhassan1, Mohammed Abaker1, Abdelzahir Abdelmaboud2, Mohammed Burhanur Rehman1,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 259-273, 2022, DOI:10.32604/iasc.2022.023750 - 05 January 2022

    Abstract The research community has well recognized the importance of requirement elicitation. Recent research has shown the continuous decreasing success rate of IS projects in the last five years due to the complexity of the requirement conflict refinement process. Requirement conflict is at the heart of requirement elicitation. It is also considered the prime reason for deciding the success or failure of the intended Information System (IS) project. This paper introduces the requirements conflict detection automation model based on the Mean shift clustering unsupervised machine learning model. It utilizes the advantages of Artificial Intelligence in detecting… More >

  • Open Access

    ARTICLE

    Kidney Tumor Segmentation Using Two-Stage Bottleneck Block Architecture

    Fuat Turk1,*, Murat Luy2, Necaattin Barışçı3, Fikret Yalçınkaya4

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 349-363, 2022, DOI:10.32604/iasc.2022.023710 - 05 January 2022

    Abstract Cases of kidney cancer have shown a rapid increase in recent years. Advanced technology has allowed bettering the existing treatment methods. Research on the subject is still continuing. Medical segmentation is also of increasing importance. In particular, deep learning-based studies are of great importance for accurate segmentation. Tumor detection is a relatively difficult procedure for soft tissue organs such as kidneys and the prostate. Kidney tumors, specifically, are a type of cancer with a higher incidence in older people. As age progresses, the importance of having diagnostic tests increases. In some cases, patients with kidney More >

  • Open Access

    ARTICLE

    Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

    Thirumoorthy Palanisamy1,*, Daniyal Alghazzawi2, Surbhi Bhatia3, Areej Abbas Malibari2, Pankaj Dadheech4, Sudhakar Sengan5

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 227-244, 2022, DOI:10.32604/iasc.2022.023692 - 05 January 2022

    Abstract Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required… More >

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