The Spitzer c2d Survey Of Nearby Dense Cores. VII. Chemistry And Dynamics In L43

We present results from the Spitzer Space Telescope and molecular line observations of nine species toward the dark cloud L43. The Spitzer images and molecular line maps suggest that it has a starless core and a Class I protostar evolving in the same environment. CO depletion is seen in both sources, and DCO(+) lines are stronger toward the starless core. With a goal of testing the chemical characteristics from pre- to protostellar stages, we adopt an evolutionary chemical model to calculate the molecular abundances and compare with our observations. Among the different model parameters we tested, the best-fit model suggests a longer total timescale at the pre-protostellar stage, but with faster evolution at the later steps with higher densities.NSF AST-0307250, AST0607793NASA NNX07AJ72GNational Research Foundation of Korea (NRF) government (MEST) 2009-0062865KOSEF R012007- 000-20336-0Astronom

A discriminative HMM/N-gram-based retrieval approach for Mandarin spoken documents

In recent years, statistical modeling approaches have steadily gained in popularity in the field of information retrieval. This article presents an HMM/N-gram-based retrieval approach for Mandarin spoken documents. The underlying characteristics and the various structures of this approach were extensively investigated and analyzed. The retrieval capabilities were verified by tests with word- and syllable-level indexing features and comparisons to the conventional vector-space model approach. To further improve the discrimination capabilities of the HMMs, both the expectation-maximization (EM) and minimum classification error (MCE) training algorithms were introduced in training. Fusion of information via indexing word- and syllable-level features was also investigated. The spoken document retrieval experiments were performed on the Topic Detection and Tracking Corpora (TDT-2 and TDT-3). Very encouraging retrieval performance was obtained

A Temporal Frequent Itemset-Based Clustering Approach For Discovering Event Episodes From News Sequence

When performing environmental scanning, organizations typically deal with a numerous of events and topics about their core business, relevant technique standards, competitors, and market, where each event or topic to monitor or track generally is associated with many news documents. To reduce information overload and information fatigues when monitoring or tracking such events, it is essential to develop an effective event episode discovery mechanism for organizing all news documents pertaining to an event of interest. In this study, we propose the time-adjoining frequent itemset-based event-episode discovery (TAFIED) technique. Based on the frequent itemset-based hierarchical clustering (FIHC) approach, our proposed TAFIED further considers the temporal characteristic of news articles, including the burst, novelty, and temporal proximity of features in an event episode, when discovering event episodes from the sequence of news articles pertaining to a specific event. Using the traditional feature-based HAC, HAC with a time-decaying function (HAC+TD), and FIHC techniques as performance benchmarks, our empirical evaluation results suggest that the proposed TAFIED technique outperforms all evaluation benchmarks in cluster recall and cluster precision

Using Technology-Supported Enrichment Activities to Extend Student Learning in a Chinese as a Foreign Language Classroom

The purpose of this study was to investigate whether exposing middle school students to content above their ability level produced significant differences in students’ confidence in their Chinese as a foreign language competence in each of the following four areas: reading, listening, speaking, and learning vocabulary. Participants (N = 30) were sixth and seventh graders. Results of paired t-test analyses indicated that there was no significant difference in student confidence in Chinese reading competence, t(30) = 0.78, p = 0.22; in Chinese speaking competence, t(30) = -0.50, p = 0.31; or to learn Chinese vocabulary, t(30) = -0.80, p = 0.21. However, there was a significant difference in student confidence in ability to learn Chinese listening, t(30) = -1.78, p \u3c 0.05. It is suggested that exposing students to content well above their ability level can increase their confidence in ability to learn Chinese listening