Ye Tian¹, Liguo Zhang^1,2, Linshan Shen^1,*, Guisheng Yin¹, Lei Chen³

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 195-211, 2021, DOI:10.32604/iasc.2021.016314 - 17 March 2021

Abstract Skin cancer is one of the most common types of cancer in the world, melanoma is considered to be the deadliest type among other skin cancers. Quite recently, automated skin lesion classification in dermoscopy images has become a hot and challenging research topic due to its essential way to improve diagnostic performance, thus reducing melanoma deaths. Convolution Neural Networks (CNNs) are at the heart of this promising performance among a variety of supervised classification techniques. However, these successes rely heavily on large amounts of class-balanced clearly labeled samples, which are expensive to obtain for skin… More >

Chunhua Zhou^*, Jianjing Shen, Xiaofeng Guo, Zhenyu Zhou

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 127-141, 2021, DOI:10.32604/iasc.2021.012532 - 07 January 2021

Abstract In the process of interaction between users and battlefield situation information, combat tasks are the key factors that affect users’ information selection. In order to solve the problems of battlefield situation information recommendation (BSIR) for combat tasks, we propose a task-oriented battlefield situation information hybrid recommendation model (TBSI-HRM) based on tensor factorization and deep learning. In the model, in order to achieve high-precision personalized recommendations, we use Tensor Factorization (TF) to extract correlation relations and features from historical interaction data, and use Deep Neural Network (DNN) to learn hidden feature vectors of users, battlefield situation More >

Zhengbo Luo¹, Hamïd Parvïn^2,3,4,*, Harish Garg⁵, Sultan Noman Qasem^6,7, Kim-Hung Pho⁸, Zulkefli Mansor⁹

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2691-2708, 2021, DOI:10.32604/cmc.2021.012547 - 28 December 2020

Abstract These days, imbalanced datasets, denoted throughout the paper by ID, (a dataset that contains some (usually two) classes where one contains considerably smaller number of samples than the other(s)) emerge in many real world problems (like health care systems or disease diagnosis systems, anomaly detection, fraud detection, stream based malware detection systems, and so on) and these datasets cause some problems (like under-training of minority class(es) and over-training of majority class(es), bias towards majority class(es), and so on) in classification process and application. Therefore, these datasets take the focus of many researchers in any science… More >

Eunmok Yang¹, Gyanendra Prasad Joshi², Changho Seo^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1647-1663, 2021, DOI:10.32604/cmc.2020.013210 - 26 November 2020

Abstract In network-based intrusion detection practices, there are more regular instances than intrusion instances. Because there is always a statistical imbalance in the instances, it is difficult to train the intrusion detection system effectively. In this work, we compare intrusion detection performance by increasing the rarely appearing instances rather than by eliminating the frequently appearing duplicate instances. Our technique mitigates the statistical imbalance in these instances. We also carried out an experiment on the training model by increasing the instances, thereby increasing the attack instances step by step up to 13 levels. The experiments included not… More >

Yan Zhang^1,2, Jin Han^1,2,*, Chengsheng Yuan^1,2, Shuo Yang³, Chuanlong Li^1,2, Xingming Sun^1,2

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 563-574, 2021, DOI:10.32604/cmc.2020.012502 - 30 October 2020

Abstract Over the past 10 years, lightning disaster has caused a large number of casualties and considerable economic loss worldwide. Lightning poses a huge threat to various industries. In an attempt to reduce the risk of lightning-caused disaster, many scholars have carried out in-depth research on lightning. However, these studies focus primarily on the lightning itself and other meteorological elements are ignored. In addition, the methods for assessing the risk of lightning disaster fail to give detailed attention to regional features (lightning disaster risk). This paper proposes a grid-based risk assessment method based on data from… More >

Chung Le Van¹, Vikram Puri¹, Nguyen Thanh Thao², Dac-Nhuong Le^3,4,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 17-33, 2021, DOI:10.32604/cmc.2020.013125 - 30 October 2020

Abstract With the rapid growth of the autonomous system, deep learning has become integral parts to enumerate applications especially in the case of healthcare systems. Human body vertebrae are the longest and complex parts of the human body. There are numerous kinds of conditions such as scoliosis, vertebra degeneration, and vertebrate disc spacing that are related to the human body vertebrae or spine or backbone. Early detection of these problems is very important otherwise patients will suffer from a disease for a lifetime. In this proposed system, we developed an autonomous system that detects lumbar implants More >

Rashmi Rai¹, Ambarish Kumar Rai^2,*

International Journal of Mental Health Promotion, Vol.22, No.4, pp. 291-302, 2020, DOI:10.32604/IJMHP.2020.012153 - 22 December 2020

Abstract The intimate partner violence (IPV) against women has been identified as a violation of human rights and a serious public health concern. There is not only the immediate consequence of partner violence, such as injury or death but also the other long-term health consequences. IPV can be associated with psychological effects such as depressive disorder, posttraumatic stress disorder, and substance abuse. The study aims to explore the nature and causes of IPV on women’s life and their personal experiences to deal with. This is an NGO-based study. For better understanding of the issues, Purposive sampling… More >

Yang Yang^1,*, Qian Zhao¹, Linna Ruan², Zhipeng Gao¹, Yonghua Huo³, Xuesong Qiu¹

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1139-1155, 2020, DOI:10.32604/iasc.2020.011705

Abstract In network anomaly detection, network traffic data are often imbalanced, that is, certain classes of network traffic data have a large sample data volume while other classes have few, resulting in reduced overall network traffic anomaly detection on a minority class of samples. For imbalanced data, researchers have proposed the use of oversampling techniques to balance data sets; in particular, an oversampling method called the SMOTE provides a simple and effective solution for balancing data sets. However, current oversampling methods suffer from the generation of noisy samples and poor information quality. Hence, this study proposes More >

Yuqing Yang^{1, 3}, Peng Fu^{2, *}, Xiaojiang Yang^{1, 4}, Hong Hong⁵, Dequn Zhou¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2413-2423, 2020, DOI:10.32604/cmc.2020.011881 - 16 September 2020

Abstract Massive Open Online Course (MOOC) has become a popular way of online learning used across the world by millions of people. Meanwhile, a vast amount of information has been collected from the MOOC learners and institutions. Based on the educational data, a lot of researches have been investigated for the prediction of the MOOC learner’s final grade. However, there are still two problems in this research field. The first problem is how to select the most proper features to improve the prediction accuracy, and the second problem is how to use or modify the data… More >

Baili Zhang^{1, 2, 3, *}, Shan Zhou¹, Le Yang¹, Jianhua Lv^{1, 2}, Mingjun Zhong⁴

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1975-1986, 2020, DOI:10.32604/cmc.2020.010914 - 16 September 2020

Abstract The Internet of Medical Things (IoMT) will come to be of great importance in the mediation of medical disputes, as it is emerging as the core of intelligent medical treatment. First, IoMT can track the entire medical treatment process in order to provide detailed trace data in medical dispute resolution. Second, IoMT can infiltrate the ongoing treatment and provide timely intelligent decision support to medical staff. This information includes recommendation of similar historical cases, guidance for medical treatment, alerting of hired dispute profiteers etc. The multi-label classification of medical dispute documents (MDDs) plays an important… More >