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there is currently a significant amount of technology in hospitals in particular in the Intensive Care Units (ICU). The clinical data daily generated are integrated into Decision Support Systems (DSS), in real time for a better quality of patient care.The hospital environment has many outbreaks of infections, objects or environments in which microorganisms can survive or multiply, such as the facilities,...
Approximate functional dependencies, even with suitable temporal extensions, have been recently proposed as a methodological tool for mining clinical data. It allows healthcare stakeholders to derive new knowledge from overwhelming amount of healthcare and clinical data. Some examples of the kind of knowledge derivable from data through dependencies may be "month by month, patients with the same...
With the development of cyber threats on the Internet, the number of malware, especially unknown malware, is also dramatically increasing. Since all of malware cannot be analyzed by analysts, it is very important to find out new malware that should be analyzed by them. In order to cope with this issue, the existing approaches focused on malware classification using static or dynamic analysis results...
Left ventricular hypertrophy (LVH) is the main manifestation of cardiovascular disease in patients with hypertension, and is an independent risk factor for multiple cardiovascular complications. So the medical researchers attach enough importance to it in aspect of clinical practice. Electrocardiograph (ECG) has the unique advantages of simple operation and low price, which support its widespread...
In recent times, there has been significant interest in the machine recognition of human emotions, due to the suite of applications to which this knowledge can be applied. A number of different modalities, such as speech or facial expression, individually and with eye gaze, have been investigated by the affective computing research community to either classify the emotion (e.g. sad, happy, angry)...
Configuration management tools, CMTs for short, are a set of indispensable software for DevOps (Development and Operations). CMTs automate system deployment and configuration through CMT modules, which are reusable, shareable units of configuration code. Therefore, thousands of CMT modules have been developed for various systems, and are still growing fast. Although CMT repositories usually provide...
Based on the development and application of on-board subsystem test bench for current CTCS-3 system, this paper focuses on the approach of automatically generation of test sequence, takes the existing test sequences of ETCS-2 (European Train Control system level 2) as the train set existing relatively mature test sequence as the training set, to execute association rule mining. The whole data mining...
The traditional silk pattern design process depends largely on designer's knowledge and experience which makes the new creative design very difficult to produce. The research applies expert system to the silk design field and uses association data mining to extract association rules from ancient silk relics, the expert system recommends users with appropriate design through description rules and association...
Cluster analysis aims at classifying data elements into different categories according to their similarity. It is a common task in data mining and useful in various field including pattern recognition, machine learning, information retrieval and so on. As an extensive studied area, many clustering methods are proposed in literature. Among them, some methods are focused on mining clusters with arbitrary...
Identifying the technology trends, key patents to be aware of, the key players active in the field, the product areas that are heavily patented or scarcely addressed, and the focus of a company's competitors represent crucial aspects of developing a successful strategic plan, determining a company's freedom to make and sell their product, and focusing future research & product development efforts...
Data mining can find some interest information from large amounts of data. Data association (association rules) can find associations among data items. Data classification distinguishes every data from a data set or group, and it also can combine data association. Formal concept analysis is a data analyzing theory which discovers concept structure in data sets. It can transform formal context into...
This paper presents some preliminary work on detecting sex offenders who might register in social networks under assumed identities using data mining, string matching, and weight-biased scoring.
Recruitment and selection of new employees rank to the important processes of human potential management and development. Especially the process of employee selection prepares proper conditions for a successful work performance and decides on a future progress-ability of the organizations. In a unique sector of private security, the precise realization of employee selection can solve one of the most...
In the Area of Security, Intrusion Detection System (IDS) form an individual trailing and plays an essential role in information Security. As the usability of the internet among the users in a wide area is increasing day by day so as the importance of security and to keep the system aware of the malicious activities is also increasing. It has the following limitations on low detection rate, high false...
This paper introduces the technological techniques of data cleaning and data extraction. The current state of domestic and international research in these two areas is reviewed and their future development considered. The following concepts are all explained: the basic principle of data cleaning, the framework models, the need for and the objectives of data cleaning, the testing method and the cleaning...
Iris recognition is a biometric authentication system proving vital for ensuring security and has been employed as an important case to test the algorithms developed in pattern recognition. The unique circular shape of the iris and its time invariance makes it a versatile technique that has an accuracy that can be mathematically proven. Here in this work we propose a new segmentation technique and...
The purpose of data mining is to explore, find and hence analyze relevant data from a massive data source using various technical means. This paper introduces the development of data mining to date, its functions, tasks and algorithms, as well as the process of data mining. The application and problems of data mining are also presented and finally the potential future development of data mining technology...
This paper proposes an attack pattern mining algorithm to extract attack pattern in massive security logs. The improved fuzzy clustering algorithm is used to generate sequence set. Then PrefixSpan is used to mine frequent sequence from the sequence set. The experimental results show that this algorithm can effectively mine the attack pattern, improve the accuracy and generate more valuable attack...
There is no previous research that compares the results of k-means, CLOPE clustering and Latent Dirichlet Allocation (LDA) topic modeling algorithms for detecting trending topics on tweets. Since not all tweets contain hashtags, we considered three training data feature sets: hashtags, keywords and keywords + hashtags in this study. Our proposed methodology proved that CLOPE can also be used in a...
Deep Neural Networks (DNNs) have shown to outperform traditional methods in various visual recognition tasks including Facial Expression Recognition (FER). In spite of efforts made to improve the accuracy of FER systems using DNN, existing methods still are not generalizable enough in practical applications. This paper proposes a 3D Convolutional Neural Network method for FER in videos. This new network...
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