Jianping Yu^1,2,3, Zhuqing Qiao¹, Wensheng Tang^1,2,3,*, Danni Wang¹, Xiaojun Cao⁴

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 713-728, 2021, DOI:10.32604/iasc.2021.017154 - 01 July 2021

Abstract In a distributed system such as Internet of things, the data volume from each node may be limited. Such limited data volume may constrain the performance of the machine learning classification model. How to effectively improve the performance of the classification in a distributed system has been a challenging problem in the field of data mining. Sharing data in the distributed network can enlarge the training data volume and improve the machine learning classification model’s accuracy. In this work, we take data sharing and the quality of shared data into consideration and propose an efficient… More >

Shabib Aftab^1,2, Saad Alanazi³, Munir Ahmad¹, Muhammad Adnan Khan^4,*, Areej Fatima⁵, Nouh Sabri Elmitwally^3,6

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1341-1357, 2021, DOI:10.32604/cmc.2021.016814 - 22 March 2021

Abstract Diabetes mellitus, generally known as diabetes, is one of the most common diseases worldwide. It is a metabolic disease characterized by insulin deficiency, or glucose (blood sugar) levels that exceed 200 mg/dL (11.1 ml/L) for prolonged periods, and may lead to death if left uncontrolled by medication or insulin injections. Diabetes is categorized into two main types—type 1 and type 2—both of which feature glucose levels above “normal,” defined as 140 mg/dL. Diabetes is triggered by malfunction of the pancreas, which releases insulin, a natural hormone responsible for controlling glucose levels in blood cells. Diagnosis… More >

Hanan Abdullah Mengash^1,*, Hanan A. Hosni Mahmoud^1,2

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1013-1032, 2021, DOI:10.32604/cmc.2021.014942 - 12 January 2021

Abstract Strabismus is a medical condition that is defined as the lack of coordination between the eyes. When Strabismus is detected at an early age, the chances of curing it are higher. The methods used to detect strabismus and measure its degree of deviation are complex and time-consuming, and they always require the presence of a physician. In this paper, we present a method of detecting strabismus and measuring its degree of deviation using videos of the patient’s eye region under a cover test. Our method involves extracting features from a set of training videos (training… More >

Yulan Zheng^∗

Computer Systems Science and Engineering, Vol.35, No.4, pp. 293-298, 2020, DOI:10.32604/csse.2020.35.293

Abstract With the development of e-commerce, more and more enterprises attach importance to precision marketing for network channels. This study adopted the decision tree algorithm in data mining to achieve precision marketing. Firstly, precision marketing and C4.5 decision tree algorithm were briefly introduced. Then e-commerce enterprise A was taken as an example. The data from January to June 2018 were collected. Four attributes including age, income, occupation and educational background were selected for calculation and decision tree was established to extract classification rules.The results showed that the consumers of the products of the company were high-income More >

Shuo He^1,∗, Jianbin Zheng^1,†, Jiale Lin^2,‡, Tao Tang^1,§, Jintao Zhao^1,¶, Hongbao Liu^1,ll

Computer Systems Science and Engineering, Vol.35, No.3, pp. 141-149, 2020, DOI:10.32604/csse.2020.35.141

Abstract Nowadays, many payment service providers use the discounts and other marketing strategies to promote their products. This also raises the issue of people who deliberately take advantage of such promotions to reap financial benefits. These people are known as ‘scalper parties’ or ‘econnoisseurs’ which can constitute an underground industry. In this paper, we show how to use machine learning to assist in identifying abnormal scalper transactions. Moreover, we introduce the basic methods of Decision Tree and Boosting Tree, and show how these classification methods can be applied in the detection of abnormal transactions. In addition,… More >

Bing Xu^1,∗, Darong Huang^2,†, Bo Mi^3,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 113-121, 2020, DOI:10.32604/csse.2020.35.113

Abstract In this paper, according to the information classification algorithm in data mining, data in the network payment system of e-commerce is mined, forming an effective evaluation of the security of the network payment system. Firstly, the method of network security risk prediction is discussed. Secondly, according to the characteristics of network payment system, the system security index system is analyzed in detail, and the specific application process of the C4.5 Classification Algorithm in security evaluation is discussed. Finally, the data mining process is designed in detail and the corresponding code established. In this paper, data More >

Lei Yang¹, Li Feng^{1, *}, Liwei Tian¹, Hongning Dai¹

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1825-1836, 2020, DOI:10.32604/cmc.2020.010011 - 20 August 2020

Abstract The registration rate of freshmen has been a great concern at many colleges and universities, particularly private institutions. Traditionally, there are two inquiry methods: telephone and tuition-payment-status. Unfortunately, the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices secret. On the other hand, the latter is not always feasible because only few students are willing to pay their university tuition fees in advance. It is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of subjectivity.… More >

Uma K.V^1,*, Appavu alias Balamurugan S²

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 61-70, 2020, DOI:10.31209/2019.100000153

Abstract Real world data consists of lot of impurities. Entropy measure will help to handle impurities in a better way. Here, data selection is done by using Naïve Bayes’ theorem. The sample which has posterior probability value greater than that of the threshold value is selected. C5.0 decision tree classifier is taken as base and modified the Gain calculation function using Tsallis entropy and Association function. The proposed classifier model provides more accuracy and smaller tree for general and Medical dataset. Precision value obtained for Medical dataset is more than that of existing method. More >

Suhas S. Aralikatti¹, K. N. Ravikumar¹, Hemantha Kumar^1,*, H. Shivananda Nayaka¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.14, No.2, pp. 127-145, 2020, DOI:10.32604/sdhm.2020.07595 - 23 June 2020

Abstract The state of cutting tool determines the quality of surface produced on the machined parts. A faulty tool produces poor surface, inaccurate geometry and non-economic production. Thus, it is necessary to monitor tool condition for a machining process to have superior quality and economic production. In the present study, fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique. Cutting force and vibration signals were acquired to monitor tool condition during machining. A set of four tooling conditions namely healthy, worn flank, broken insert and extended… More >

Zhichun Jia^{1, 2}, Qiuyang Han¹, Yanyan Li¹, Yuqiang Yang¹, Xing Xing^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722 - 30 April 2020

Abstract With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values.… More >