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The primary failure mechanism in brittle materials such as ceramics, granite and some metal alloys is through the presence of defects which result in crack formation and propagation under the application of load. We are interested in studying this process of crack propagation, interaction and coalescence, which degrades the strength of the specimen. Traditionally, engineering applications that study...
Stories can have tremendous power – not only useful for entertainment, they can activate our interests and mobilize our actions. The degree to which a story resonates with its audience may be in part reflected in the emotional journey it takes the audience upon. In this paper, we use machine learning methods to construct emotional arcs in movies, calculate families of arcs, and demonstrate the ability...
We propose an action parsing algorithm to parse a video sequence containing an unknown number of actions into its action segments. We argue that context information, particularly the temporal information about other actions in the video sequence, is valuable for action segmentation. The proposed parsing algorithm temporally segments the video sequence into action segments. The optimal temporal segmentation...
The world is witnessing a remarkable increase in the usage of video surveillance systems. Besides fulfilling an imperative security and safety purpose, it also contributes towards operations monitoring, hazard detection and facility management in industry/smart factory settings. Most existing surveillance techniques use hand-crafted features analyzed using standard machine learning pipelines for action...
The full behavior of software-intensive systems of systems (SoS) emerges during operation only. Runtime monitoring approaches have thus been proposed to detect deviations from the expected behavior. They commonly rely on temporal logic or domain-specific languages to formally define requirements, which are then checked by analyzing the stream of monitored events and event data. Some approaches also...
This article provides a comparison of two feature selection algorithms, Information Gain Thresholding and Koller and Sahami's algorithm in the context of text document classification on the Reuters Corpus Volume 1 dataset. The algorithms were evaluated by testing the performance of classifiers trained on the features they select from a given dataset. Results show that Koller and Sahami's algorithm...
With the development of science and technology, computer technology is increasingly updated, and multimedia search technology has been widely used. For music retrieval, textbased retrieval technology can't meet the diversified retrieval needs. Humming retrieval is through matching the input audio and the audio in the database to match the audio. It's a more convenient way to retrieve music. In this...
Identifying families of malware is today considered a fundamental problem in the context of computer security. The correct mapping of a malicious sample to a known family simplifies its analysis and allows experts to focus their efforts only on those samples presenting unknown characteristics or behaviours, thus improving the efficiency of the malware analysis process. Grouping malware in families...
Mobility impaired individuals need the wheelchair to support their independent life, so monitor activities performed on the wheelchair can provide significant insights on their general health status. Activity recognition related to healthy people is a well established research area; however, only few works addressed this problem for wheelchair users. This paper proposes a novel approach based on dynamic...
Moving objects' detection in dynamic scenes is a very important task in video processing. In the applications of image processing (for example, video-surveillance), more attention is paid to whether there is an interested object in the scene rather than where the object is located. As a matter of fact, similar to static backgrounds, the statistical histograms of the most dynamic backgrounds have favorable...
The traditional target detection and identification algorithm is difficult to adapt to the massive data. And the expression of the method it relies on is designed by means of manual, which is not only very time-consuming, but also very dependence for professional knowledge and data itself. Aiming at the problem of pedestrian detection in complex environment, a pedestrian detection algorithm based...
Grey Wolf Optimizer (GWO) is a new meta-heuristic optimization. It is inspired by the unique predator strategy and organization system of grey wolves. Since the GWO algorithm is easy to fall into local optimum especially when it is used in the high-dimensional data, an improved GWO algorithm combined with Cuckoo Search (CS) is proposed in this paper. By introducing the global-search ability of CS...
Gender classification has multiple applications including, but not limited to, face perception, age, ethnicity and identity analysis, video surveillance and smart human computer interaction. The majority of computer based gender classification algorithms analyse the appearance of facial features predominantly based on the texture of the static image of the face. In this paper, we propose a novel algorithm...
Gesture recognition has multiple applications in medical and engineering fields. The problem of hand gesture recognition consists of identifying, at any moment, a given gesture performed by the hand. In this work, we propose a new model for hand gesture recognition in real time. The input of this model is the surface electromyography measured by the commercial sensor the Myo armband placed on the...
Automatic malware categorization plays an important role in combating the current large volume of malware and aiding the corresponding forensics. Generally, there are lot of sample information could be extracted with the static tools and dynamic sandbox for malware analysis. Combine these obtained features effectively for further analysis would provides us a better understanding. On the other hand,...
Autism spectrum disorders (ASD) is a disorder that affects communication, social skills or behaviours of some people. Children or adults with ASD often have some common repetitive behaviours or self-stimulatory behaviours. These behaviours usually refer to specific behaviours such as flapping, rocking, spinning, etc. This work investigates these behaviours and provides a benchmark dataset for researchers...
Feature selection is to select certain quantity of important features from large number of original features. In this paper, a new feature selection algorithm based on features unit (FU) is presented. The algorithm uses entropy of information to determine whether a feature should integrate with other features on the basis of its relevance to the class. As for the features which fit to integrate with...
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...
Protein sequence classification is increasingly crucial in the current “biological information sciences” epoch, where researchers hammer at functional genomics and proteomics technologies for predicting the function of large-scale new proteins. This has sparked interest in the methods which do not rely on traditional sequence alignment, but prefer machine learning approaches. In this paper, we present...
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