Vaibhav Rupapara¹, Furqan Rustam², Abid Ishaq², Ernesto Lee³, Imran Ashraf^4,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1931-1949, 2023, DOI:10.32604/iasc.2023.028257

Abstract Diabetes mellitus is a metabolic disease that is ranked among the top 10 causes of death by the world health organization. During the last few years, an alarming increase is observed worldwide with a 70% rise in the disease since 2000 and an 80% rise in male deaths. If untreated, it results in complications of many vital organs of the human body which may lead to fatality. Early detection of diabetes is a task of significant importance to start timely treatment. This study introduces a methodology for the classification of diabetic and normal people using an ensemble machine learning model… More >

S. Dinesh Kumar^1,*, A. Jagadeeshwaran²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2201-2215, 2023, DOI:10.32604/iasc.2023.027467

Abstract Recent advancements in power electronics technology evolves inverter fed electric motors. Speed signals and rotor position are essential for controlling an electric motor accurately. In this paper, the sensorless speed control of surface-mounted permanent magnet synchronous motor (SPMSM) has been attempted. SPMSM wants a digital inverter for its precise working. Hence, this study incorporates fifteen level inverter to the SPMSM. A sliding mode observer (SMO) based sensorless speed control scheme is projected to determine rotor spot and speed of the multilevel inverter (MLI) fed SPMSM. MLI has been operated using a multi carrier pulse width modulation (MCPWM) strategy for generation… More >

P. Ramya^1,*, B. Karthik²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2379-2391, 2023, DOI:10.32604/iasc.2023.026291

Abstract Word Sense Disambiguation has been a trending topic of research in Natural Language Processing and Machine Learning. Mining core features and performing the text classification still exist as a challenging task. Here the features of the context such as neighboring words like adjective provide the evidence for classification using machine learning approach. This paper presented the text document classification that has wide applications in information retrieval, which uses movie review datasets. Here the document indexing based on controlled vocabulary, adjective, word sense disambiguation, generating hierarchical categorization of web pages, spam detection, topic labeling, web search, document summarization, etc. Here the… More >

S. Soundararajan^1,*, B. R. Tapas Bapu², C. Kotteeswaran¹, S. Venkatasubramanian³, P. J. Sathish Kumar⁴, Ahmed Mudassar Ali²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1227-1240, 2023, DOI:10.32604/iasc.2023.025752

Abstract Recently, Wireless Sensor Network (WSN) becomes most potential technologies for providing improved services to several data gathering and tracking applications. Because of the wireless medium, multi-hop communication, absence of physical protectivity, and accumulated traffic, WSN is highly vulnerable to security concerns. Therefore, this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis. It is challenging to determine if packet loss is caused by a collision in the medium access path, poor channel quality, or a selective forwarding assault. Identifying misbehaving nodes at… More >

S. Poornima^1,*, N. Sripriya¹, Adel Fahad Alrasheedi², S. S. Askar², Mohamed Abouhawwash^3,4

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2393-2409, 2023, DOI:10.32604/iasc.2023.024820

Abstract Plant diseases prediction is the essential technique to prevent the yield loss and gain high production of agricultural products. The monitoring of plant health continuously and detecting the diseases is a significant for sustainable agriculture. Manual system to monitor the diseases in plant is time consuming and report a lot of errors. There is high demand for technology to detect the plant diseases automatically. Recently image processing approach and deep learning approach are highly invited in detection of plant diseases. The diseases like late blight, bacterial spots, spots on Septoria leaf and yellow leaf curved are widely found in plants.… More >

V. Satheesh Kumar^1,*, S. Ramesh²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2191-2200, 2023, DOI:10.32604/iasc.2023.021188

Abstract At 12.8 MHz center frequency, the advanced miniaturized polymer-based planar high quality factor (Q) passive elements embedded bandpass filter works in the L-band. Because most of the demands operate inside the spectrum, the wideband or high-speed operation necessary to enhance must be acquired in microwave frequency ranges. The channel has a quiet, high-performance microfilter with wideband rejection. Capacitors and inductors are used in the high quality factor (Q) passive components, and related networks are incorporated in the filter. Embedded layers are concatenated using Three-Dimensional Integrated Circuit (3D-IC) integration, parasitics are removed, and interconnection losses are negotiated using de-embedding methods. A… More >

M. S. Vivekanandan¹, T. Jesudas^2,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1639-1652, 2023, DOI:10.32604/iasc.2023.032301

Abstract In an urban city, the daily challenges of managing cleanliness are the primary aspect of routine life, which requires a large number of resources, the manual process of labour, and budget. Street cleaning techniques include street sweepers going away to different metropolitan areas, manually verifying if the street required cleaning taking action. This research presents novel street garbage recognizing robotic navigation techniques by detecting the city’s street-level images and multi-level segmentation. For the large volume of the process, the deep learning-based methods can be better to achieve a high level of classification, object detection, and accuracy than other learning algorithms.… More >

J. Aran Glenn^1,*, Srinivasan Alavandar²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1523-1545, 2023, DOI:10.32604/iasc.2023.033545

Abstract Nowadays, researchers are becoming increasingly concerned about developing a highly efficient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change. The introduction of Electric Vehicles (EVs) solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulfilled by the installation and expansion of solar-powered Photovoltaic (PV) systems. Hence, this paper focuses on designing an effective PV based EV charging system that aids in stepping towards the achievement of a pollution free future. For overcoming the inherent intermittency associated with PV, a novel… More >

S. Amutha^*, J. Raja Sekar

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1863-1880, 2023, DOI:10.32604/iasc.2023.028903

Abstract In this digital era, Cardio Vascular Disease (CVD) has become the leading cause of death which has led to the mortality of 17.9 million lives each year. Earlier Diagnosis of the people who are at higher risk of CVDs helps them to receive proper treatment and helps prevent deaths. It becomes inevitable to propose a solution to predict the CVD with high accuracy. A system for predicting Cardio Vascular Disease using Deep Neural Network with Binarized Butterfly Optimization Algorithm (DNN–BBoA) is proposed. The BBoA is incorporated to select the best features. The optimal features are fed to the deep neural… More >

T. Edwin Ponraj^1,*, J. Charles²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1189-1203, 2023, DOI:10.32604/iasc.2023.033383

Abstract The mutation is a critical element in determining the proteins’ stability, becoming a core element in portraying the effects of a drug in the pharmaceutical industry. Doing wet laboratory tests to provide a better perspective on protein mutations is expensive and time-intensive since there are so many potential mutations, computational approaches that can reliably anticipate the consequences of amino acid mutations are critical. This work presents a robust methodology to analyze and identify the effects of mutation on a single protein structure. Initially, the context in a collection of words is determined using a knowledge graph for feature selection purposes.… More >