• Journal of the Korea Society of Computer and Information
• /
• v.18 no.9
• /
• pp.111-120
• /
• 2013

Uncertainty in Context-aware computing is mainly a consequence of the complexity of context acquisition mechanisms and context processing. The presence of uncertainty may harm the users' confidence in the application, rendering it useless. This paper describes a three-phase strategy to manage uncertainty by identifying its possible sources, representing uncertain information, and determining how to proceed, once uncertain context is detected. The level of effort that is necessary to eliminate the uncertainty of context information affects the reliability of the system, because Sensor network system have no intervention of humans. In this paper, We applied proposed method to the development for the sensor network system, Uncertainty management can be applied a part of the system development life-cycle. It confirmed that result of testing show that detection performance is stable.

• Journal of the Korean Society for information Management
• /
• v.23 no.2
• /
• pp.287-309
• /
• 2006

While numerous studies have suggested the significance of uncertainty during the process of information-seeking, less research has investigated user uncertainty in the actual search process using a real system. This study investigated user perceptions of uncertainty in the process of the selection of Web search terms in the real information-seeking process. The subjects at the doctoral or post-doctoral level were limited to the discipline of science in order to understand user perceptions in this field. The findings revealed various dimensions, types, and incidents of uncertainty. The typology of uncertainty facilitated an understanding of the subjects' information-seeking context by identifying various aspects of the context that constituted the subjects' uncertainty The identification of two principal origins of uncertainty based on the different types of uncertainty generated implications to improve information systems and services.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.3
• /
• pp.105-117
• /
• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.4
• /
• pp.254-259
• /
• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• International Journal of Contents
• /
• v.5 no.3
• /
• pp.40-49
• /
• 2009

While numerous studies have suggested the significance of uncertainty during the process of information-seeking, less research has investigated user uncertainty in the actual search process using a real system. This study investigated user perceptions of uncertainty in the process of the selection of information retrieval system in the real information-seeking process. Considering the role of commercial Web search engines as supplementary tools for traditional bibliographic databases in academic research environments, this study analyzed the selection behavior of scholarly researchers, who use such search tools for their academic study. The researchers were limited to the discipline of science in order to understand user perceptions in this field. The findings revealed various dimensions, types, and incidents of uncertainty. Variations appeared in different incidents of uncertainty relating to the unique characteristics of the subjects' information-seeking context. The identification of three principal origins of uncertainty based on the different types of uncertainty generated implications to improve information systems and services.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.3
• /
• pp.239-248
• /
• 2006

Current context-aware applications In ubiquitous computing environments make the assumption that the context they are dealing with is correct. However, in reality, both sensed and interpreted context informations are often uncertain or imperfect. In this paper, we propose a probability extension model to ontology-based model for rep resenting uncertain contexts and use Bayesian networks to resolve about uncertainty of context informations. The proposed model can support the development and operation of various context-aware services, which are required in the ubiquitous computing environment.

• Annual Conference of KIPS
• /
• 2021.05a
• /
• pp.373-376
• /
• 2021

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavior of deep learning. The deep ensemble provides increased accuracy and estimated uncertainty; however, linearly increasing the size makes the deep ensemble unfeasible for memory-intensive tasks. To address this problem, we used model pruning and quantization with a deep ensemble and analyzed the effect in the context of uncertainty metrics. We empirically showed that the ensemble members' disagreement increases with pruning, making models sparser by zeroing irrelevant parameters. Increased disagreement implies increased uncertainty, which helps in making more robust predictions. Accordingly, an energy-efficient compressed deep ensemble is appropriate for memory-intensive and uncertainty-aware tasks.

• Journal of Digital Convergence
• /
• v.19 no.10
• /
• pp.119-132
• /
• 2021

This study focused on examining the impact of the social context that causes gender differences in entrepreneurship, not the phenomenon itself. Specifically, this study verified the moderating effect of the social context on the relationship between gender and entrepreneurship using data from 20 countries in the Global Entrepreneurship Trend Report (GETR). In order to test hypotheses involving social context implications, Hofstede's cultural dimension factors such as power distance, individualism, masculinity, and uncertainty avoidance variables, and institutional factors such as gender equality and social security are used as specific variables reflecting the social context. Empirical analysis through GLM found that gender did not independently influence entrepreneurship, and gender had a significant effect by interacting with power distance, individualism, uncertainty avoidance, gender equality, and social security variables, respectively. Such empirical results show that the gender difference in entrepreneurship is not due to the unique characteristics inherent in each gender but on the level of the country's social context to which the individual belongs.

• Journal of The Korean Association For Science Education
• /
• v.40 no.1
• /
• pp.1-12
• /
• 2020

In scientific argumentation, students can use rebuttals to escape uncertainty, which, in this case, can be defined as a vague and fuzzy feeling about other students' explanations. As rebuttals can play a critical role in the sophistication of arguments and the alleviation of uncertainty, this study aims to understand the dynamics of uncertainty and rebuttals by exploring the context of the uncertainty experienced by elementary school students in the argumentation of "Why did the kidney beans not germinate?" and to get insights based on the research results. Twenty fourth-grade students and their homeroom teacher in Kyong-Ki province, South Korea, took part in the research. Students engaged in argumentation in five small groups of four students. The researcher collected qualitative data through video transcriptions, student interviews, and field notes. In the data analysis, the researcher employed the constant comparative method to explore in what context students experienced uncertainty and how they used rebuttals. The results of this study were as follows: First, students tried to reduce their uncertainty through argumentation on why the kidney beans did not germinate. Second, students used elaboration-oriented rebuttals, personal opinion-oriented rebuttals, and blame-oriented rebuttals to reduce this uncertainty. However, when they used blame-oriented rebuttals, their uncertainty and negative emotions increased. Third, intervention by the teacher led students to stop using blame-oriented rebuttals. Instead, they employed elaboration-oriented rebuttals to explore why the kidney beans would not sprout, and finally, they escaped uncertainty by discovering an appropriate explanation. Based on the findings of this study, the researcher discussed how the interaction between uncertainty and elaboration-oriented rebuttals could shape and facilitate argument development in elementary school students.

• Journal of Distribution Science
• /
• v.16 no.6
• /
• pp.25-35
• /
• 2018

Purpose - Although marketing networks are crucial competitive advantage in terms of firm's new information and resource acquisition ability, their impact on new product development performance remains vague, especially under environmental uncertainty. The principal objective of this research is to provide a better understanding of effects of technological uncertainty and volume uncertainty on first tier supplier's perceived performance of new product development under conditions reflecting varying levels of structural holes. Specifically, this research examines the moderating effect of structural holes on the relationship between environmental uncertainty and new product development performance. Research design, data, and methodology - To test the hypotheses, a questionnaire survey was conducted with a Korean engineering firm's major first-tier suppliers in the context of internal network entities, manufacturer-supplier-subsupplier relationships, and to verify the proposed hypotheses, structural equation modeling was established. Construct measures were based on existing measures and previous research. Results - The survey results indicate that technological uncertainty and volume uncertainty differentially affect NPD performance under conditions of high and low structural holes. Conclusions - This study offer some theoretical and practical implications among distribution channel members, especially, this study suggests that interfirm networks have critical competitive advantage in uncertain environments. The distinctiveness of engineering industry might limit the generalizability of the results. Thus, future research should consider a wider range of industries.