Abhishek Singhal^*, Devendra Kumar Sharma

Computer Systems Science and Engineering, Vol.48, No.3, pp. 609-625, 2024, DOI:10.32604/csse.2023.046730 - 20 May 2024

Abstract This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions, employing a deep learning classification algorithm for speech signal analysis. In this study, speech samples are categorized for both training and testing purposes based on their geographical origin. Category 1 comprises speech samples from speakers outside of India, whereas Category 2 comprises live-recorded speech samples from Indian speakers. Testing speech samples are likewise classified into four distinct sets, taking into consideration both geographical origin and the language spoken by the speakers. Significantly, the results indicate a noticeable difference… More >

Zimeng Yang, Qiulan Wu, Feng Zhang^*, Xuefei Chen, Weiqiang Wang, Xueshen Zhang

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 491-506, 2023, DOI:10.32604/iasc.2023.037558 - 29 April 2023

Abstract Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation. With the continuous development of artificial intelligence technology, the use of deep learning methods for interpreting remote-sensing images has matured. Existing neural networks disregard the spatial relationship between two targets in remote sensing images. Semantic segmentation models that combine convolutional neural networks (CNNs) and graph convolutional neural networks (GCNs) cause a lack of feature boundaries, which leads to the unsatisfactory segmentation of various target feature boundaries. In this paper, we propose a new semantic segmentation model for remote… More >

Ivan Izonin^1,*, Roman Tkachenko¹, Michal Gregus², Zoia Duriagina^1,3, Nataliya Shakhovska¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5933-5947, 2022, DOI:10.32604/cmc.2022.022582 - 14 January 2022

Abstract The advent of additive technologies has provided a significant breakthrough in the production of medical implants. It has reduced costs, increased productivity and accuracy of the implant manufacturing process. However, there are problems associated with assessing defects in the microstructure, mechanical and technological properties of alloys, both during their production by powder metallurgy and in the process of 3D printing. Thus traditional research methods of alloys properties demand considerable human, material, and time resources. At the same time, artificial intelligence tools create opportunities for intelligent evaluation of the conformity for the microstructure, phase composition, and… More >

Iqra Afzal¹, Fiaz Majeed¹, Muhammad Usman Ali², Shahzada Khurram³, Akber Abid Gardezi⁴, Shafiq Ahmad⁵, Saad Aladyan⁵, Almetwally M. Mostafa⁶, Muhammad Shafiq^7,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.022711 - 07 December 2021

Abstract In this era of electronic health, healthcare data is very important because it contains information about human survival. In addition, the Internet of Things (IoT) revolution has redefined modern healthcare systems and management by providing continuous monitoring. In this case, the data related to the heart is more important and requires proper analysis. For the analysis of heart data, Electrocardiogram (ECG) is used. In this work, machine learning techniques, such as adaptive boosting (AdaBoost) is used for detecting normal sinus rhythm, atrial fibrillation (AF), and noise in ECG signals to improve the classification accuracy. The… More >

R. Sujatha¹, Jyotir Moy Chatterjee², NZ Jhanjhi³, Thamer A. Tabbakh⁴, Zahrah A. Almusaylim^5,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 115-129, 2022, DOI:10.32604/iasc.2022.019133 - 26 October 2021

Abstract Heart failure (HF) is an intercontinental pandemic influencing in any event 26 million individuals globally and is expanding in commonness. HF healthiness consumptions are extensive and will increment significantly with a maturing populace. As per the World Health Organization (WHO), Cardiovascular diseases (CVDs) are the major reason for all-inclusive death, taking an expected 17.9 million lives per year. CVDs are a class of issues of the heart, blood vessels and include coronary heart sickness, cerebrovascular illness, rheumatic heart malady, and various other conditions. In the medical care industry, a lot of information is as often… More >

P. S. Anoop¹, Pranav Nair², V. Sugumaran^1,*

Structural Durability & Health Monitoring, Vol.15, No.3, pp. 261-279, 2021, DOI:10.32604/sdhm.2021.06656 - 07 September 2021

Abstract Tyre Pressure Monitoring Systems (TPMS) are installed in automobiles to monitor the pressure of the tyres. Tyre pressure is an important parameter for the comfort of the travelers and the safety of the passengers. Many methods have been researched and reported for TPMS. Amongst them, vibration-based indirect TPMS using machine learning techniques are the recent ones. The literature reported the results for a perfectly balanced wheel. However, if there is a small unbalance, which is very common in automobile wheels, ‘What will be the effect on the classification accuracy?’ is the question on hand. This More >

Muhammad Azam¹, Tanvir Ahmed¹, Rehan Ahmad², Ateeq Ur Rehman³, Fahad Sabah¹, Rao Muhammad Asif^4,*

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 853-867, 2021, DOI:10.32604/iasc.2021.019101 - 20 August 2021

Abstract Sentiment analysis is a method for assessing an individual’s thought, opinion, feeling, mentality, and conviction about a specific subject on indicated theme, idea, or product. The point could be a business association, a news article, a research paper, or an online item, etc. Opinions are generally divided into three groups of positive, negative, and unbiased. The way toward investigating different opinions and gathering them in every one of these categories is known as Sentiment Analysis. The enormously growing sentiment data on the web especially social media can be a big source of information. The processing… More >

PCD Kalaivaani^1,*, Dr. R Thangarajan²

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 71-79, 2020, DOI:10.31209/2019.100000152

Abstract Web mining is the process of integrating the information from web by traditional data mining methodologies and techniques. Opinion mining is an application of natural language processing to extract subjective information from web. Online reviews require efficient classification algorithms for analysing the sentiments, which does not perform an in–depth analysis in current methods. Sentiment classification is done at document level in combination with topics and sentiments. It is based on weakly supervised Joint Sentiment-Topic mode which extends the topic model Maximum Entropy Discrimination Latent Dirichlet Allocation by constructing an additional sentiment layer. It is assumed More >

Mohamed EL Boujnouni¹, Mohamed Jedra²

Computer Systems Science and Engineering, Vol.33, No.6, pp. 409-420, 2018, DOI:10.32604/csse.2018.33.409

Abstract Support Vector Domain Description (SVDD) is an effective kernel-based method used for data description. It was motivated by the success of Support Vector Machine (SVM) and thus has inherited many of its attractive properties. It has been extensively used for novelty detection and has been applied successfully to a variety of classification problems. This classifier aims to find a sphere with minimal volume including the majority of examples that belong to the class of interest (positive) and excluding the most of examples that are either outliers or belong to other classes (negatives). In this paper More >