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We explore the feasibility of measuring learner engagement and classifying the engagement level based on machine learning applied on data from 2D/3D camera sensors and eye trackers in a 1:1 learning setting. Our results are based on nine pilot sessions held in a local high school where we recorded features related to student engagement while consuming educational content. We label the collected data...
In recent years, the work on expressive styles of speech has increased rather than focusing on basic emotions. The present paper shows the comparison of expressive speech and neutral speech on the basis of pitch and intensity where neutral speech can be further modify to produce expressive style with emotion which is suitable for story telling application. Our approach is to perform an analysis of...
In this study, a system is proposed to help physicians perform processing on images taken with a magnifying endoscopy with narrow band imaging. In our proposed system, the transition from lesion to normal zone is quantitatively analyzed and presented by texture analysis. Eleven feature values are calculated, i.e., six from a co-occurrence matrix and five from a run length matrix with a scanning window...
Clustering Web services into functionally similar clusters is a very efficient approach to service discovery. A principal issue for clustering is computing the semantic similarity between services. Current approaches use similarity-distance measurement methods such as keyword, information-retrieval or ontology based methods. These approaches have problems that include discovering semantic characteristics,...
The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalities and draw correct diagnosis is vital. We experimented with wavelet and Local Energy based Shape Histogram (LESH) features combined with Echo State Network classifier. The suggested...
In order to utilize identification to the best extent, we need robust and fast algorithms and systems to process the data. Having palmprint as a reliable and unique characteristic of every person, we extract and use its features based on its geometry, lines and angles. There are countless ways to define measures for the recognition task. To analyze a new point of view, we extracted textural features...
In this study an approach that uses social networking data for developing sentiment analysis system is proposed. With the help of developed software, it is tried to find out whether there is any relation between universities' academic success and sentiment of the public about them in social media. After collecting enough text based data from Twitter, preprocessing of data is carried out and final...
Many governments and institutions have guidelines for health-enhancing physical activity. Additionally, according to recent studies, the amount of time spent on sitting is a highly important determinant of health and wellbeing. In fact, sedentary lifestyle can lead to many diseases and, what is more, it is even found to be associated with increased mortality.
Tibetan-Chinese named entity extraction can effectively improve the performance of Tibetan-Chinese cross language question answering system, information retrieval, machine translation and other researches. In the condition of no practical Tibetan named entity recognition system and Tibetan-Chinese translation model, this paper proposes a method to extract Tibetan-Chinese entities based on comparable...
As one tool for structuring a massive volume of archived news videos based on their semantic contents, this paper proposes a method to detect scene duplicates from news videos. A scene duplicate is a pair of video segments taken at the same event from different viewpoints. Referring to the audio channel is effective to detect scene duplicates regardless of viewpoints, but it cannot be relied on when...
People take regular medical examinations mostly not for discovering diseases but for having a peace of mind regarding their health status. Therefore, it is important to give them an overall feedback with respect to all the health indicators that have been ranked against the whole population. In this paper, we propose a framework of mining Personal Health Index (PHI) from a large and comprehensive...
This paper proposes a method for extractive multi-document summarization based on the combined features of n-grams co-occurrences and dependency word pairs co-occurrences. Unigram is the basic text unit, Big ram and skip-big ram reflect the word sequential relationships in the sentences, Dependency word pairs describe the syntactic relationships between words. The co-occurrences of each feature reflect...
Refactoring is the process of changing the internal structure of software without changing its external behavior. So far, numerous tools have been proposed on that refactoring support. However, it is difficult for existing refactoring support tools to support consecutively co-occurred refactorings. To alleviate this problem, a tool which supports consecutively co-occurred refactorings is required...
This paper presents a new automatically quantitative facial features classification system for TCM spirit diagnosis based on facial features. Facial diagnosis is an important diagnostic method in TCM (Traditional Chinese Medicine) and has been used for a long time. However, this traditional diagnostic method is mainly based on observation by TCM doctors and their personal experience. To develop quantification...
The Texture Feature Extraction (TFE) plays an important role in satellite image processing application. This paper proposes a novel method for Satellite Imagery Classification. Our proposed method is a combination of Local Binary Pattern (LBP) and Fuzzy c-means classification algorithm. Local Binary Pattern is calculated by thresholding a 3 × 3 neighborhood of each pixel by the center pixel value...
Attention is amongst the high level cognitive task which is associated with complex process in the brain. But in almost all researches, this process is associated with a secondary task, (like numeration). Some believe that the link between these two cognitive activities (i.e. attention and numeration) in human brain is very close and intricate. However, the goal of this research is to evaluate the...
Nowadays, pathologist« grade breast cancer histopathology slides by microscopes based on Nottingham as an international standard. The mitotic counting is one of the three scoring criteria in Nottingham standard for breast cancer grading based on histopathology slide image studies. Large number of non-mitosis organs, which exists in histopathology slide tissue, is one of the most important challenges...
Epilepsy is a common neurological disorder characterized by abnormal excessive or synchronous neural activity in brain. In this study, we develop an unsupervised learning for seizure prediction. Extracting wavelet features of brain electroencephalogram (EEG), we propose a Hidden Markov Model (HMM) with a mixture of Gaussian observation model as an unsupervised learning setting for seizure prediction,...
Heterogeneous social networks present a great challenge for link mining tasks and especially for link prediction. Recent work insists on the importance of information heterogeneity intelligent exploitation in order to achieve best results. That will be more possible only with the development of new techniques that may represent heterogeneous network in an effective way making it possible to simplify...
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