From Honeymoon to Divorce: Fragmenting Relations between China and South Korea in Politics,Economics – and Sport

This is an analysis of two East Asian Nations, South Korea and China, and a descent from growing friendship to growing friction in economics, politics and sport – with sport as an analogue of fragmentation and the Guangzhou Asian Games as an analogous illustration of crescive tension between the two nations in economics, politics and sport in the twenty-first century.     

XMage: An image retrieval method based on partial similarity

XMage is introduced in this paper as a method for partial similarity searching in image databases. Region-based image retrieval is a method of retrieving partially similar images. It has been proposed as a way to accurately process queries in an image database. In region-based image retrieval, region matching is indispensable for computing the partial similarity between two images because the query processing is based upon regions instead of the entire image. A naive method of region matching is a sequential comparison between regions, which causes severe overhead and deteriorates the performance of query processing. In this paper, a new image contents representation, called Condensed eXtended Histogram (CXHistogram), is presented in conjunction with a well-defined distance function CXSim() on the CX-Histogram. The CXSim() is a new image-to-image similarity measure to compute the partial similarity between two images. It achieves the effect of comparing regions of two images by simply comparing the two images. The CXSim() reduces query space by pruning irrelevant images, and it is used as a filtering function before sequential scanning. Extensive experiments were performed on real image data to evaluate XMage. It provides a significant pruning of irrelevant images with no false dismissals. As a consequence, it achieves up to 5.9-fold speed-up in search over the R*-tree search followed by sequential scanning.     

Extrovert and Lonely Individuals’ Social TV Viewing Experiences: A Mediating and Moderating Role of Social Presence

Social TV viewing is generally understood as a simultaneous act of watching TV and engaging in communication about the TV program with other TV viewers connected online. In response to the increasing popularity of this new TV viewing practice, the current study examined how individuals’ extrovert personality and loneliness influence social TV viewing experiences through the theoretical notion of social presence. An online survey was completed by 330 individuals. Results demonstrated that extrovert personality positively influenced social TV viewing experiences; it is important to note that this relationship was mediated by social presence. Loneliness itself was negatively related to social TV viewing experiences; however, this relationship was moderated by social presence. Specifically, when lonely people felt strong social presence, they enjoyed social TV viewing experiences. The findings provide theoretical implications for social TV research, the dynamic role of social presence, social enhancement model, and social compensation model.     

Antimelanogenic effects of <Emphasis Type="Italic">Inula britannica</Emphasis> flower petal extract fermented by <Emphasis Type="Italic">Lactobacillus plantarum</Emphasis> KCCM 11613P

The inhibitory effects of Lactobacillus plantarum-fermented and non-fermented Inula britannica extracts on the tyrosinase activity were comparatively investigated to examine whether and how they improve the whitening activity, and the contents of total flavonoids and polyphenolics as bioactive compounds were determined. The skin whitening activity using in vitro or ex vivo tyrosinase and L-3,4-dihydroxyphenylalanine (L-DOPA) staining was examined. The total flavonoid content (TFC) was increased by 13.4% after 72 h-fermentation. The viabilities of the B16F10 cells treated with the fermented and non-fermented control extracts were 100.26% and 92.15% at 500 μg/ml, respectively. In addition, the inhibition of tyrosinase activity was increased by the fermented samples from 29.33% to 41.74% following fermentation for up to 72 h. The tyrosinase activity of the untreated control group was increased to 145.69% in B16F10 cells. The results showed that I. britannica fermented by L. plantarum dose-dependently inhibited tyrosinase activity, which was stimulated by α-melanocyte stimulating hormone. These results suggest that lactic fermented I. britannica extracts can be used as effective skin-whitening materials.     

Out of the book and into the classroom: The experiences of Korean social studies pre-service teachers in an international teaching practicum in the United States

Despite the growing interest and importance of pre-service teachers’ cross-cultural experiences, a review of the literature shows that few studies have discussed the international teaching practicum experiences of pre-service teachers from Asian countries. Bridging this gap, this qualitative case study examined the perceptions and experiences of 15 Korean social studies pre-service teachers who participated in an international teaching practicum in the United States. The findings of the study demonstrated that although participants encountered difficulties in speaking a foreign language and adjusting to a different culture, they also gained confidence and self-efficacy by negotiating and actively participating in the teaching and learning process. This international teaching practicum also helped participants promote their own understanding of multiculturalism and their different perspectives of the teachers’ roles, teaching pedagogies, and local education systems. This study offers implications for future multicultural professional development in teacher education and contributes to developing a body of research and scholarship on international teaching practicums from Asian contexts that have, to date, been largely underexplored.     

Improving document clustering in a learned concept space

Most document clustering algorithms operate in a high dimensional bag-of-words space. The inherent presence of noise in such representation obviously degrades the performance of most of these approaches. In this paper we investigate an unsupervised dimensionality reduction technique for document clustering. This technique is based upon the assumption that terms co-occurring in the same context with the same frequencies are semantically related. On the basis of this assumption we first find term clusters using a classification version of the EM algorithm. Documents are then represented in the space of these term clusters and a multinomial mixture model (MM) is used to build document clusters. We empirically show on four document collections, Reuters-21578, Reuters RCV2-French, 20Newsgroups and WebKB, that this new text representation noticeably increases the performance of the MM model. By relating the proposed approach to the Probabilistic Latent Semantic Analysis (PLSA) model we further propose an extension of the latter in which an extra latent variable allows the model to co-cluster documents and terms simultaneously. We show on these four datasets that the proposed extended version of the PLSA model produces statistically significant improvements with respect to two clustering measures over all variants of the original PLSA and the MM models.     

Mentoring Undergraduate Interdisciplinary Mathematics Research Students: Junior Faculty Experiences

Abstract

To be successful, junior faculty must properly manage their time in the face of expanding responsibilities. One such responsibility is supervising undergraduate research projects. Student research projects (either single or multi-student) can be undertaken as a full-time summer experience, or as a part-time academic year commitment. With many potential undergraduate research formats, and with different types of students, junior faculty may find challenges in forming their research group, establishing a structure that promotes student productivity, picking an appropriate project, or in effectively mentoring their students. This article draws from the authors’ experiences to help junior faculty navigate these complexities so that all parties reap the benefits of undergraduate research in interdisciplinary mathematical disciplines.     

Construction of query concepts based on feature clustering of documents

In Information Retrieval, since it is hard to identify users’ information needs, many approaches have been tried to solve this problem by expanding initial queries and reweighting the terms in the expanded queries using users’ relevance judgments. Although relevance feedback is most effective when relevance information about retrieved documents is provided by users, it is not always available. Another solution is to use correlated terms for query expansion. The main problem with this approach is how to construct the term-term correlations that can be used effectively to improve retrieval performance. In this study, we try to construct query concepts that denote users’ information needs from a document space, rather than to reformulate initial queries using the term correlations and/or users’ relevance feedback. To form query concepts, we extract features from each document, and then cluster the features into primitive concepts that are then used to form query concepts. Experiments are performed on the Associated Press (AP) dataset taken from the TREC collection. The experimental evaluation shows that our proposed framework called QCM (Query Concept Method) outperforms baseline probabilistic retrieval model on TREC retrieval.