• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.644-652
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• 2020

The objective of this study was carried out to examine the academic self-efficacy mediating effect in the relationships of AIS educaton and contextual performance. For this study, data collected from 282 students were analyzed using the SPSS 23.0 and AMOS 23.0 programs. Results of this study are as follows. First, it was found that AIS education had a positive (+) impact on contextual performance. Second, it was found that academic self efficacy had an effect on contextual performance. Third, it was found that academic self efficacy had a mediating effect on the relationship of AIS education and contextual performance. The Sobel test was performed to identify the mediating effect. AIS education had a direct impact on contextual performance as well as an indirect impact through academic self-efficacy. These results provide that AIS education improves academic self-efficacy and thereby be effective for contextual performance. Follow-on research needs to expand of sample and using diverse variables.

• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.316-334
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• 2006

In the traditional computing paradigm, developers design software to run in a fixed and well-defined environment. The real environment, however, is too complicated to analyze all situations perfectly. Consequently, traditional software, which is implemented only for what is wanted as input, often fails badly in real environment. As a new approach, self-adaptive software can avoid runtime failures adapting to unpredictable situations. Self-adaptive software must firstly evaluate the contextual situation to determine the need for adaptation. Existing researches do not support the abstraction mechanism for identifying contextual problem. Consequently, they can have troubles with identifying the contextual problem as the execution environment is getting complex. In addition, they cannot support the expandability for contextual problems, which software can evaluate. This paper suggests the goal-based evaluation method of contextual situation for coping with the limitations of existing researches.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.85-91
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• 2014

The objective of the research is to automatically recognize railway objects from MLS data in which 9 key objects including terrain, track, bed, vegetation, platform, barrier, posts, attachments, powerlines are targeted. The proposed method can be divided into two main sub-steps. First, multi-scale contextual features are extracted to take the advantage of characterizing objects of interest from different geometric levels such as point, line, volumetric and vertical profile. Second, by considering contextual interactions amongst object labels, a contextual classifier is utilized to make a prediction with local coherence. In here, the Conditional Random Field (CRF) is used to incorporate the object context. By maximizing the object label agreement in the local neighborhood, CRF model could compensate the local inconsistency prediction resulting from other local classifiers. The performance of proposed method was evaluated based on the analysis of commission and omission error and shows promising results for the practical use.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.116-121
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• 2010

New teaching and studying methods using educational contents are gradually widespread with the advancement of information and communication technology. As educational contents, in this paper, we design and implement linguistic contents for studying essential expressions applied to various situations of real life. In detail, the linguistic contents are run on web environments, and have suitable animations for learning essential expressions based on several foreign languages in contextual dialogues. Also, useful functions are included in contents to reinforce what users have learned.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2267-2270
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• 2003

This paper has been studied to implement MQ encoder in JPEG2000 on FPGA. In the JPEG2000 architecture, Each of coding passes collects contextual information about the bit-plane data. An MQ coder uses contextual information and its internal state to decode a compressed bit-stream. This paper draws up JPEG2000 Standard Part 1: FCD 15444-1 It is simulated with Modelsim and tested with JBIG2 data.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.151-158
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• 2000

This dissertation measures transitory items using earnings change scaled by beginning-of-period price(FreemanㆍTse 1992) and the earnings-to-price ratio(AliㆍZarowin 1992). Contextual regression model results confirm the incremental explanatory power for predominantly permanent earnings, and suggest that cash flows also have incremental explanatory power in the presence of predominantly permanent earnings. But contextual regression results represent that while earnings are consistent with a smaller marginal impact from extreme (transitory) earnings on abnormal returns, cash flows have no greater impact on abnormal returns in the presence of large transitory components in earnings.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.59-76
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• 2014

The purpose of this study is to investigate the effect of individual cultural disposition on the perception of contextual information and attitude toward contextual material, and to provide the effective ways of delivering information. To investigate individual cultural disposition, this study employed Triandis(1988)'s cultural scale that classified people into four categories using individualism/collectivism and vertical/horizontal dimensions. The results revealed that Korean college students had higher horizontal collectivism than other cultural dispositions, but only a few Korean college students had vertical individualism. The results using regression analysis revealed that Korean college students with vertical collectivism significantly perceived more contextual information than other groups.

• ETRI Journal
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• v.34 no.2
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• pp.292-295
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• 2012

Beyond the simple keyword matching methods in contextual advertising, we propose a rich contextual matching (CM) model adopting a classification method for topic targeting and a query expansion method for semantic ad matching. This letter reports on an investigation into the empirical effects of the CM model by comparing the click-through rates (CTRs) of two practical online news advertising systems. Based on the evaluation results from over 100 million impressions, we prove that the average CTR of our proposed model outperforms that of a traditional model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.67-77
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• 2004

The recent research has been focused on fusion of audio and visual features for reliable speech recognition in noisy environments. In this paper, we propose a neural network based model of robust speech recognition by integrating audio, visual, and contextual information. Bimodal Neural Network(BMNN) is a multi-layer perception of 4 layers, each of which performs a certain level of abstraction of input features. In BMNN the third layer combines audio md visual features of speech to compensate loss of audio information caused by noise. In order to improve the accuracy of speech recognition in noisy environments, we also propose a post-processing based on contextual information which are sequential patterns of words spoken by a user. Our experimental results show that our model outperforms any single mode models. Particularly, when we use the contextual information, we can obtain over 90% recognition accuracy even in noisy environments, which is a significant improvement compared with the state of art in speech recognition. Our research demonstrates that diverse sources of information need to be integrated to improve the accuracy of speech recognition particularly in noisy environments.

• Journal of the Korean Society of Food Culture
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• v.28 no.5
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• pp.463-472
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• 2013

Beverages can vary in their appropriateness depending on the context of their different uses; therefore, an intention to consume a beverage is likely dependent on the context of its use. This study associated the consumer acceptability of commercial beverage products examined in a previous study (Kim and others, 2013) with its appropriateness under different use contexts. Consumers (n=360) were divided into two conditions: blind and brand. Consumers rated appropriateness for 13 use contexts for each beverage product. The results indicated that the contextual appropriateness were significantly different among the beverage samples and seemed to be positively influenced by the acceptability of beverages. The beverages with higher liking scores were more appropriate in a greater number of contexts, including "when tired", "refreshing", and "rest". However, there were inappropriate contexts (e.g., "while weight watching", "after exercise", "with a meal", and "health care") regardless of degree of acceptability. In the brand condition, some differences in contextual appropriateness were observed when comparing results from the blind condition (e.g., "with a meal", "health care").