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The propose of this research was to classify the English as a foreign language (EFL) learners based on their performance on the reading test. Three levels of reading comprehension are customarily defined: (1) Factual level or Reading the lines, (2) Interpretive level or Reading between the lines, and (3) Evaluative level or Reading beyond the lines. Further analyzing and synthesizing factors underlying...
Innovation is widely recognized as one main contributor to a firm's competitiveness. To conduct innovation, an organization must utilize its tangible and intangibles resources. The current study is aimed at examining the effect of intangible resources, namely human, organizational and relational resources on innovation in the context of service firms (i.e., tutoring agencies) in Indonesia. In addition,...
In the context of games for learning, it is argued that taking individual differences among players into consideration during game design can be beneficial for the game and/or learning experience. Researchers have studied a variety of factors that can be used for taking individual differences among players into consideration. Although research work indicates that the intelligence levels according...
Pairs trading is a market-neutral strategy that exploits historical correlation between stocks to achieve statistical arbitrage. Existing pairs-trading algorithms in the literature require rather restrictive assumptions on the underlying stochastic stock-price processes and the so-called spread function. In contrast to existing literature, we consider an algorithm for pairs trading which requires...
Semantic computing is one of the important and indispensable approaches to analyze various kinds of environmental phenomena and its changes in the real world. In this paper, we present “A Seawater-Quality Analysis Semantic-Space in Hawaii-Islands with Multi-Dimensional World Map System” to realize a global and environmental analysis for ocean environment with the multi-dimensional world map system...
Social networks and location based social networks have many active users who provide various kind of data, such as where they have been, who their friends are, which items they like more, when they go to a venue. Location, social network and temporal information provided by them can be used by recommendation systems to give more accurate suggestions. Also, recommendation systems can provide dynamic...
Registration of histopathology volumes to Magnetic Resonance Images(MRI) is a crucial step for finding correlations in Prostate Cancer (PCa) and assessing tumor agressivity. This paper proposes a two-stage framework aimed at registering both modalities. Firstly, Speeded-Up Robust Features (SURF) algorithm and a context-based search is used to automatically determine slice correspondences between MRI...
Objective: To provide references for mental health of IT workers, marriage, well-being and social support were analysed. Methods: 260 randomized married volunteers were sampled to finish marital quality questionnaire, memorial university of new found land scale of happiness and social support rating scale. SPSS 19.0 was applied to input and process experimental datas. Results: (1) IT workers felt...
Trust model has been suggested as an effective security mechanism in distributed network environment. Considerable researches have been done on trust evaluation and trust prediction. Traditional methods take the historical behavior data into consideration to predict the trust value of the network entity. However, the context of the network entity is seldom taken into account. It is obvious that the...
The growth of digital data is tremendous. Any aspect of life and matter is being recorded and stored on cheap disks, either in the cloud, in businesses, or in research labs. We can now afford to explore very complex relationships with many variables playing a part. But for this we need powerful tools that allow us to be creative, to sculpt this intricate insight formulated as models from the raw block...
Quantified Self is a growing community of individuals seeking self-improvement through self-measurement. Initially, personal variables such as diet, exercise, sleep, and productivity are tracked. This data is then explored for correlations, to ultimately either change negative or confirm positive behavioural patterns. Tools and applications that can handle these tasks exist, but they mostly focus...
This study conducted a preliminary investigation on the correlations between learners' EEG-based workload and their self-reported cognitive load in a multimedia learning context. An experiment including two learning tasks was conducted with 15 graduate students. The NeuroSky brainwave headset was used to collect participants' electroencephalography (EEG) data and using the theta/alpha ratio as brain...
In [10] and [16], we proposed tools for simultaneous variable selection and parameter estimation in a functional linear model with a functional outcome and a large number of scalar predictor. We call these techniques Function-on-Scalar Lasso (FSL) and Adaptive Function-on-Scalar Lasso(AFSL). A scalar group lasso was used to fit the FSL and AFSL estimates. While this approach works well, we improve...
Infographic is a type of information visualization that uses graphic design to enhance human ability to identify patterns and trends. It is popularly used to support spread of information. Yet, there are few studies that investigate how infographics affect learning and how individual factors, such as learning styles and enjoyment of the information affect infographics perception. In this sense, this...
People often under or over-estimate their performance on interactive learning experiences with virtual agents, especially when it comes to interpersonal skills such as empathy. To generate more accurate self-assessment of performance, we propose the use of in-action reflective learning opportunities during interactive learning experiences with virtual agents. We conducted a user study in which third-year...
Semantic context is an important and useful cue for scene parsing in complicated natural images with a substantial amount of variations in objects and the environment. This paper proposes Spatially Constrained Location Prior (SCLP) for effective modelling of global and local semantic context in the scene in terms of inter-class spatial relationships. Unlike existing studies focusing on either relative...
This paper tries to do the research of analyzing the relation of the customer trust, the customer satisfaction and purchase intention under the electronic commerce shopping environment. Drawing on the theory of customer trust, customer satisfaction and purchase intention, based on a survey of 102 respondents from the University in China, the United Kingdom, and the United States, the results showed...
Rich contexts enable the provision of context-aware services on mobile smart phones, but they also introduce threats of privacy leakages. It is widely held that the key to privacy preservation is to achieve efficient tradeoffs between the utilization of contexts, the preservation of privacy. Götz et al. present δ privacy that exploits temporal relation to decide the release/suppression, this technique...
Dynamic Music Emotion Prediction is crucial to the emerging applications of music retrieval and recommendation. Considering the influence of temporal context and hierarchical structure on emotion in music, we propose a Deep Bidirectional Long Short-Term Memory (DBLSTM) based multi-scale regression method. In this method, a post-processing component is utilised for individual DBSLTM output to further...
Depth maps are becoming increasingly important in the context of emerging video coding and processing applications. Depth images represent the scene surface and are characterized by areas of smoothly varying grey levels separated by sharp edges at the position of object boundaries. To enable high quality view rendering at the receiver side, preservation of these characteristics is important. Lossless...
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