Gürcan Çetin^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4519-4539, 2022, DOI:10.32604/cmc.2022.031734 - 28 July 2022

Abstract Recently, machine learning algorithms have been used in the detection and classification of network attacks. The performance of the algorithms has been evaluated by using benchmark network intrusion datasets such as DARPA98, KDD’99, NSL-KDD, UNSW-NB15, and Caida DDoS. However, these datasets have two major challenges: imbalanced data and high-dimensional data. Obtaining high accuracy for all attack types in the dataset allows for high accuracy in imbalanced datasets. On the other hand, having a large number of features increases the runtime load on the algorithms. A novel model is proposed in this paper to overcome these… More >

Jyoti Arora¹, Meena Tushir², Keshav Sharma¹, Lalit Mohan¹, Aman Singh^3,*, Abdullah Alharbi⁴, Wael Alosaimi⁴

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4801-4817, 2022, DOI:10.32604/cmc.2022.025960 - 28 July 2022

Abstract Datasets with the imbalanced class distribution are difficult to handle with the standard classification algorithms. In supervised learning, dealing with the problem of class imbalance is still considered to be a challenging research problem. Various machine learning techniques are designed to operate on balanced datasets; therefore, the state of the art, different under-sampling, over-sampling and hybrid strategies have been proposed to deal with the problem of imbalanced datasets, but highly skewed datasets still pose the problem of generalization and noise generation during resampling. To over-come these problems, this paper proposes a majority clustering model for… More >

T. Ragupathi^1,*, M. Govindarajan¹, T. Priyaradhikadevi²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1351-1366, 2022, DOI:10.32604/iasc.2022.025756 - 03 May 2022

Abstract The rapid advancements in the field of big data, wearables, Internet of Things (IoT), connected devices, and cloud environment find useful to improve the quality of healthcare services. Medical data classification using the data collected by the wearables and IoT devices can be used to determine the presence or absence of disease. The recently developed deep learning (DL) models can be used for several processes such as classification, natural language processing, etc. This study presents a bacterial foraging optimization (BFO) based convolutional neural network-gated recurrent unit (CNN-GRU) with class imbalance handling (CIH) model, named BFO-CNN-GRU-CIH… More >

Heewon Chung, Jinseok Lee^*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5607-5628, 2022, DOI:10.32604/cmc.2022.028154 - 21 April 2022

Abstract For the classification problem in practice, one of the challenging issues is to obtain enough labeled data for training. Moreover, even if such labeled data has been sufficiently accumulated, most datasets often exhibit long-tailed distribution with heavy class imbalance, which results in a biased model towards a majority class. To alleviate such class imbalance, semi-supervised learning methods using additional unlabeled data have been considered. However, as a matter of course, the accuracy is much lower than that from supervised learning. In this study, under the assumption that additional unlabeled data is available, we propose the More >

M. Sandeep Kumar¹, Mohammad Zubair Khan^2,*, Sukumar Rajendran¹, Ayman Noor³, A. Stephen Dass¹, J. Prabhu¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4397-4409, 2022, DOI:10.32604/cmc.2022.025865 - 21 April 2022

Abstract Diabetics is one of the world’s most common diseases which are caused by continued high levels of blood sugar. The risk of diabetics can be lowered if the diabetic is found at the early stage. In recent days, several machine learning models were developed to predict the diabetic presence at an early stage. In this paper, we propose an embedded-based machine learning model that combines the split-vote method and instance duplication to leverage an imbalanced dataset called PIMA Indian to increase the prediction of diabetics. The proposed method uses both the concept of over-sampling and More >

Soban Arshad¹, Khalid Iqbal^1,*, Sheneela Naz², Sadaf Yasmin¹, Zobia Rehman²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4283-4301, 2022, DOI:10.32604/cmc.2022.025442 - 21 April 2022

Abstract Telecom industry relies on churn prediction models to retain their customers. These prediction models help in precise and right time recognition of future switching by a group of customers to other service providers. Retention not only contributes to the profit of an organization, but it is also important for upholding a position in the competitive market. In the past, numerous churn prediction models have been proposed, but the current models have a number of flaws that prevent them from being used in real-world large-scale telecom datasets. These schemes, fail to incorporate frequently changing requirements. Data… More >

Xianghui Li^*

Molecular & Cellular Biomechanics, Vol.19, No.2, pp. 105-114, 2022, DOI:10.32604/mcb.2022.018736 - 25 March 2022

Abstract Objective: This study aims to analyze the effect of core strength strengthening training on exercise-induced lumbar injuries. Methods: Sixteen athletes suffering from lumbar injuries were randomly divided into two groups, group A and group B. Group A performed core strength strengthening training, while group B only performed normal study and life. Before and after the experiment, the Visual Analogue Scale (VAS) score, lumbar spine mobility, Oswestry Disability Index (ODI) and overall effect evaluation of the two groups were recorded and compared. Results: After the experiment, the VAS score of group A decreased to 2.78 ± 1.89 points,… More >

Ajinkya S. Umbarkar^1,*, Deoram V. Nandanwar¹, Omprakash P. Chimankar²

Sound & Vibration, Vol.56, No.2, pp. 193-203, 2022, DOI:10.32604/sv.2022.015322 - 25 March 2022

Abstract Here we report first ever study on acoustical evaluation of Kanheri Caves located in Sanjay Gandhi National Park, Mumbai (Maharashtra, India). These caves are dated to a period between 2^nd century BCE to 7^th century CE. In this study we used an ambisonic recorder to capture Impulse Response, which carries acoustic signature of the place. Out of total 109 caves 41 were surveyed in available time. Out of those reverberant environment was noted in 12 caves. Measurements were made only in 3 caves (Cave Nos. 1, 3, 11) which are important. In the beginning we carried… More >

Ayman A. Aly¹, Mohamed O. Elhabib², Bassem F. Felemban¹, B. Saleh¹, Dac-Nhuong Le^3,4,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 93-107, 2022, DOI:10.32604/cmc.2022.019681 - 24 February 2022

Abstract The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors More >

Shihao Zhou¹, Ziyuan Xu^3,4, Jin Han^1,*, Xingming Sun^1,2, Yi Cao⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5995-6009, 2022, DOI:10.32604/cmc.2022.023316 - 14 January 2022

Abstract In recent years, academic misconduct has been frequently exposed by the media, with serious impacts on the academic community. Current research on academic misconduct focuses mainly on detecting plagiarism in article content through the application of character-based and non-text element detection techniques over the entirety of a manuscript. For the most part, these techniques can only detect cases of textual plagiarism, which means that potential culprits can easily avoid discovery through clever editing and alterations of text content. In this paper, we propose an academic misconduct detection method based on scholars’ submission behaviors. The model… More >