Ammar Almomani^1,2,*, Mohammed Alweshah³, Waleed Alomoush⁴, Mohammad Alauthman⁵, Aseel Jabai², Anwar Abbass², Ghufran Hamad², Meral Abdalla², Brij B. Gupta^1,6,7

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3045-3062, 2023, DOI:10.32604/cmc.2023.030567

Abstract Voice classification is important in creating more intelligent systems that help with student exams, identifying criminals, and security systems. The main aim of the research is to develop a system able to predicate and classify gender, age, and accent. So, a new system called Classifying Voice Gender, Age, and Accent (CVGAA) is proposed. Backpropagation and bagging algorithms are designed to improve voice recognition systems that incorporate sensory voice features such as rhythm-based features used to train the device to distinguish between the two gender categories. It has high precision compared to other algorithms used in this problem, as the adaptive… More >

Xuhui Zhu^1,3, Pingfan Xia^1,3, Qizhi He^2,4,*, Zhiwei Ni^1,3, Liping Ni^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 653-671, 2023, DOI:10.32604/cmes.2022.022985

Abstract Multiple classifier system exhibits strong classification capacity compared with single classifiers, but they require significant computational resources. Selective ensemble system aims to attain equivalent or better classification accuracy with fewer classifiers. However, current methods fail to identify precise solutions for constructing an ensemble classifier. In this study, we propose an ensemble classifier design technique based on the perturbation binary salp swarm algorithm (ECDPB). Considering that extreme learning machines (ELMs) have rapid learning rates and good generalization ability, they can serve as the basic classifier for creating multiple candidates while using fewer computational resources. Meanwhile, we introduce a combined diversity measure… More >

Saif Saad Hameed, Ismail Taha Ahmed^*, Omar Munthir Al Okashi

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 327-340, 2023, DOI:10.32604/cmc.2023.031622

Abstract Biometric recognition refers to the identification of individuals through their unique behavioral features (e.g., fingerprint, face, and iris). We need distinguishing characteristics to identify people, such as fingerprints, which are world-renowned as the most reliable method to identify people. The recognition of fingerprints has become a standard procedure in forensics, and different techniques are available for this purpose. Most current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification models. Therefore, we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints… More >

M. Valavan, S. Rita^*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 231-245, 2023, DOI:10.32604/csse.2023.026508

Abstract Fraud detection for credit/debit card, loan defaulters and similar types is achievable with the assistance of Machine Learning (ML) algorithms as they are well capable of learning from previous fraud trends or historical data and spot them in current or future transactions. Fraudulent cases are scant in the comparison of non-fraudulent observations, almost in all the datasets. In such cases detecting fraudulent transaction are quite difficult. The most effective way to prevent loan default is to identify non-performing loans as soon as possible. Machine learning algorithms are coming into sight as adept at handling such data with enough computing influence.… More >

V. Joseph Raymond^1,2,*, R. Jeberson Retna Raj¹

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2147-2163, 2023, DOI:10.32604/csse.2023.028227

Abstract Android devices are popularly available in the commercial market at different price levels for various levels of customers. The Android stack is more vulnerable compared to other platforms because of its open-source nature. There are many android malware detection techniques available to exploit the source code and find associated components during execution time. To obtain a better result we create a hybrid technique merging static and dynamic processes. In this paper, in the first part, we have proposed a technique to check for correlation between features and classify using a supervised learning approach to avoid Multicollinearity problem is one of… More >

Sujit S. Pardeshi¹, Abhishek D. Patange¹, R. Jegadeeshwaran^2,*, Mayur R. Bhosale³

Structural Durability & Health Monitoring, Vol.16, No.3, pp. 271-290, 2022, DOI:10.32604/sdhm.2022.010622

Abstract The regulation of tyre pressure is treated as a significant aspect of ‘tyre maintenance’ in the domain of autotronics. The manual supervision of a tyre pressure is typically an ignored task by most of the users. The existing instrumental scheme incorporates stand-alone monitoring with pressure and/or temperature sensors and requires regular manual conduct. Hence these schemes turn to be incompatible for on-board supervision and automated prediction of tyre condition. In this perspective, the Machine Learning (ML) approach acts appropriate as it exhibits comparison of specific performance in the past with present, intended for predicting the same in near future. The… More >

R. Rajkamal^1,*, Anitha Karthi², Xiao-Zhi Gao³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2013-2033, 2022, DOI:10.32604/cmc.2022.027142

Abstract Diabetes is increasing commonly in people’s daily life and represents an extraordinary threat to human well-being. Machine Learning (ML) in the healthcare industry has recently made headlines. Several ML models are developed around different datasets for diabetic prediction. It is essential for ML models to predict diabetes accurately. Highly informative features of the dataset are vital to determine the capability factors of the model in the prediction of diabetes. Feature engineering (FE) is the way of taking forward in yielding highly informative features. Pima Indian Diabetes Dataset (PIDD) is used in this work, and the impact of informative features in… More >

Attia Qammar¹, Ahmad Karim^1,*, Yasser Alharbi², Mohammad Alsaffar², Abdullah Alharbi²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 915-930, 2022, DOI:10.32604/csse.2022.023652

Abstract Smartphone devices particularly Android devices are in use by billions of people everywhere in the world. Similarly, this increasing rate attracts mobile botnet attacks which is a network of interconnected nodes operated through the command and control (C&C) method to expand malicious activities. At present, mobile botnet attacks launched the Distributed denial of services (DDoS) that causes to steal of sensitive data, remote access, and spam generation, etc. Consequently, various approaches are defined in the literature to detect mobile botnet attacks using static or dynamic analysis. In this paper, a novel hybrid model, the combination of static and dynamic methods… More >

Jabeen Sultana^1,*, Anjani Kumar Singha², Shams Tabrez Siddiqui³, Guthikonda Nagalaxmi⁴, Anil Kumar Sriram⁵, Nitish Pathak⁶

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1007-1024, 2022, DOI:10.32604/iasc.2022.021507

Abstract COVID-19 is a novel virus that spreads in multiple chains from one person to the next. When a person is infected with this virus, they experience respiratory problems as well as rise in body temperature. Heavy breathlessness is the most severe sign of this COVID-19, which can lead to serious illness in some people. However, not everyone who has been infected with this virus will experience the same symptoms. Some people develop cold and cough, while others suffer from severe headaches and fatigue. This virus freezes the entire world as each country is fighting against COVID-19 and endures vaccination doses.… More >

S. Poovizhi, T. R. Ganesh Babu, R. Praveena^*

Molecular & Cellular Biomechanics, Vol.18, No.4, pp. 201-219, 2021, DOI:10.32604/mcb.2021.017984

Abstract Skin is the largest organ and outer enclosure of the integumentary system that protects the human body from pathogens. Among various cancers in the world, skin cancer is one of the most commonly diagnosed cancer which can be either melanoma or non-melanoma. Melanoma cancers are very fatal compared with non-melanoma cancers but the chances of survival rate are high when diagnosed and treated earlier. The main aim of this work is to analyze and investigate the performance of Non-Subsampled Bendlet Transform (NSBT) on various classifiers for detecting melanoma from dermoscopic images. NSBT is a multiscale and multidirectional transform based on… More >