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the division of the test paper can reflect the quality of examination paper, but it is difficult to find some decisive courses in dozens of courses. In order to find out the curriculum that decides the role of different levels of students, the concept of course discrimination is proposed, which focuses on the value of course discrimination, the classification method and the proportion of special courses...
Virtual learning community is an important organizational form for collaborative learning. And the learning emotion, interaction degree, knowledge test are important characteristics of learning. However, the existing constructing strategy is unable to accurately determine the matching degree between the learner and the community. The lower matching degree will weaken the learning performance of learners...
This paper presents a computer-aided system for automatic diagnosis of cirrhosis based on ultrasound images. We first propose a dynamic programming algorithm to automatically extract the liver capsule, and then the continuity and smoothness of capsule serve as an important guideline for image classification. Via the decomposition of the ultrasound image in spatial and gray scales, the density and...
The task of classifying EEG signals for self-paced Brain Computer Interface (BCI) applications is extremely challenging. This difficulty in classification of self-paced data stems from the fact that the system has no clue about the start time of a control task and the data contains a large number of periods during which the user has no intention to control the BCI. Therefore, to improve the performance...
Polarity detection is a research topic of major interest, with many applications including detecting the polarity of product reviews. However, in some cases, the polarity of the product reviews might not be available while the polarity of the product itself might be, prohibiting the use of any form of fully supervised learning technique. This scenario, while different, is close to that of multiple...
Online monitoring of tool wear condition is of great significance to manufacturing system. In order to adaptively adjust the length of sliding time window, dynamically update the prediction model, and ultimately improve the monitoring accuracy under limited number of available training samples, an adaptive dynamic non-bias least squares support vector machine (ADNLSSVM) is adopted to build tool condition...
Previous work on fire detection has focused on hand-designed features or carefully designed detectors. However, there are no universal hand-designed features or detectors that work well for various classification tasks or even for various fire detection scenarios. In this paper we propose a new method of video-based fire detection by learning multi-layer ICA spatiotemporal features. This method can...
Tuberculosis (TB) these days is considered as a major health threat in most of the countries of the world. Bacillus, also referred to as Mycobacterium tuberculosis, is the main cause of mortality due to TB. It is reported that mortality rates of patients with tuberculosis are higher when it is not diagnosed at an early stage. At present the approaches used to diagnose TB are based on the incorrect...
Intrusion behavior and detection analysis particularly rely upon the type of data. Most of the datasets used in intrusion analysis are heterogeneous and imbalanced data sets. In these data sets, the features vary with a huge difference in between and within the feature values. This is very effective while taking decision, especially in the supervised learning. To analyze the intrusion problem, support...
For traditional data mining tasks, algorithms are commonly selected by manual effort. However, it is a challenge for any practitioner to select the most appropriate algorithm from hundreds of candidates. To address this issue, we have proposed a novel model for supporting automatic selection on data mining algorithms. The model incorporates the extracted characteristics of data sets and the dynamically...
Cyber bullying is a new phenomenon resulting from the advance of new communication technologies including the Internet, cell phones and Personal Digital Assistants. It is a challenging bullying problem occurring in a new territory. Online bullying can be particularly damaging and upsetting because it's usually anonymous or hard to trace. In this paper, the proposed method is utilizing a dataset of...
Drowsiness is one of the main causes of severe traffic accidents occurring in our daily life. In order to reduce the number of drowsiness-induced accidents, various researches have been conducted with the aim of finding practical and non-invasive drowsiness detection systems by using behavioral measuring techniques. Many of the previous works on behavioral measuring techniques have mainly focused...
The importance of automatic person identification using non-intrusive biometric modality has created enormous interest in computer vision society over the last few years. For this, gait based person recognition is receiving much more attention in different applications like visual surveillance, security control, people counting. In this paper, we have presented a gait based person identification system...
In this paper, we demonstrate a new way to perform continuous authentication using Mouse Dynamics as the behavioural biometric modality. In the proposed scheme, the user will be authenticated per mouse event performed on his/her system. We have used a publicly available mouse dynamics dataset and extracted per event features suitable for the proposed scheme. In this research, we have used the mouse...
According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text. First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine...
Ship detection is one of the most important applications of target recognition based on optical remote sensing images. In this paper, we propose an uncertain ship target extraction algorithm based on dynamic fusion model of multi-feature and variance feature of optical remote sensing image. We choose several geometrical features, such as length, wide, rectangular ratio, tightness ratio and so on,...
We investigate feature selection methods, which have been applied to automatic kinds of compressed audio classification systems. It is based on attribute dependency for feature optimization and modified SVM (Support Vector Machine) for classifier. In this paper, we present a new method for feature selection based on priori knowledge by removing both irrelevant and redundant features, and it still...
Road detection is an important problem with application to driver assistance systems and autonomous, self-guided vehicles. The focus of this paper is on the problem of feature extraction and classification for front-view road detection. Specifically, we propose using Support Vector Machines (SVM) for road detection and effective approach for self-supervised online learning. The proposed road detection...
Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as object detection, recognition, and tracking. We propose a new method for detecting object boundaries using planar laser scanners (LIDARs) and, optionally, co-registered imagery. We formulate boundary detection as a classification...
Existing cover song detection systems require prior knowledge of the number of cover songs in a test set in order to identify cover(s) to a reference song. We describe a system that does not require such prior knowledge. The input to the system is a reference track and test track, and the output is a binary classification of whether the inputs are either a reference and a cover or a reference and...
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