• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.103-108
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• 2004

This paper will describe integrated system design process and its application. Integrated design process is performed activities concurrently and sequentially for product development. For a group of activities to be truly integrated, the flow of deliverables among them must be well defined, and committed to. For this purpose, the study will suggest procedure that is executed context analysis of standard process, interface definition from activity decomposition, integration of related activities, and definition of concurrency & sequential activities flow, This procedure and method will contribute to minimize time loss that is emerged from activities iteration by not definitely definition of activities interface.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.141-149
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• 2011

The substantial effort is required to make a virtual character smoothly move like a human being in the virtual environment. Since a virtual character acts on the basis of the actions, it is the most critical to define actions for smooth flow of action. It has been actively studied the programming by demonstration which defines series of actions to be performed by a virtual character based on the actions operated by a person. However, such approaches can't easily draw many sequential actions because they create sequential actions in the same length all the time or restrict the actions used to create such actions. For smooth flow of action, it is required to derive sequential actions as much as possible from the actions of a virtual character and to select the representative set of actions. Accordingly, it is necessary to study how to create sequential actions as reducing diverse limits. This study suggests the approach to select sequential actions suitable for a virtual character by collecting the actions of a character manipulated by a person and deriving a set of actions to be performed by a virtual character. The experiment describes the process to create the actions by applying the approach suggested in this study to the driving game. In accordance with the analysis results, it was found that a set of actions performed by a person was generated without being restricted by a length or a part to divide. Finally, we confirmed that the suggested method selects the best sequential actions, appropriate to virtual character, among more generated actions.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.106-106
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• 1999

When we design real-time software target system is analyzed and then we structure sequential executive modules into concurrent tasks. As a result of the analysis, control flow and dataflow diagram based on the RTSA notation is produced. This diagram is structured into concurrenttasks under the condition that performance problem is not serious. The criteria structuring concurrenttasks are introduced as Concurrent Design Approach for Real-Time System(CODARTS) by Gomaa.But structuring concurrent tasks using the criteria of CODARTS is somewhat difficult because thecriteria are dependent on designer's experience. CODARTS is an wide-range and abstractmethodology. As a result, the design can be inconsistent and peoples can understand it differently Inthis paper, we restructure the CODARTS methodology, propose a revised CODARTS structure andrepresent the task structuring steps for this new framework to overcome the understanding andinconsistency problems. The revised CODARTS framework and task structuring steps can be used toautomate the design of real time concurrent software systems. Finally, we show an example of taskstructuring in revised CODARTS framework.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.487-492
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• 2008

Facial expression recognition is an intensive research area for designing Human Computer Interfaces. In this work, we present a new facial expression recognition system utilizing Enhanced Independent Component Analysis (EICA) for feature extraction and discrete Hidden Markov Model (HMM) for recognition. Our proposed approach for the first time deals with sequential images of emotion-specific facial data analyzed with EICA and recognized with HMM. Performance of our proposed system has been compared to the conventional approaches where Principal and Independent Component Analysis are utilized for feature extraction. Our preliminary results show that our proposed algorithm produces improved recognition rates in comparison to previous works.

• International Journal of Concrete Structures and Materials
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• v.6 no.4
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• pp.209-220
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• 2012

Post-earthquake fire (PEF) can lead to a rapid collapse of buildings that have been partially damaged as a result of a prior earthquake. Almost all standards and codes for the design of structures against earthquake ignore the risk of PEF, and thus buildings designed using those codes could be too weak when subjected to a fire after an earthquake. An investigation based on sequential analysis inspired by FEMA356 is performed here on the immediate occupancy (IO), life safety (LS) and collapse prevention (CP) performance levels of two portal frames, after they are pushed to arrive at a certain level of displacement corresponding to the mentioned performance level. This investigation is followed by a fire analysis of the damaged frames, examining the time taken for the damaged frames to collapse. As a point of reference, a fire analysis is also performed for undamaged frames and before the occurrence of earthquake. The results indicate that while there is minor difference between the fire resistances of the fire-alone situation and the frames pushed to the IO level of performance, a notable difference is observed between the fire-alone analysis and the frames pushed to arrive at LS and CP levels of performance and exposed to PEF. The results also show that exposing only the beams to fire results in a higher decline of the fire resistance, compared to exposing only the columns to fire. Furthermore, the results show that the frames pushed to arrive at LS and CP levels of performance collapse in a global collapse mode laterally, whereas at the IO level of performance and fire-alone situation, the collapse mechanism is mostly local through the collapse of beams. Whilst the investigation is conducted for a certain class of portal frames, the results confirm the need for the incorporation of PEF into the process of analysis and design, and provide some quantitative measures on the level of associated effects.

• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.621-626
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• 2021

A sequential design of experiments was used to optimize MOF-801 synthesis process. For the initial screening, a general 2^k factorial design was selected followed by the central composition design, one of the response surface methods. A 2³ factorial design based on the molar ratio of fumaric acid, dimethylformamide (DMF), and formic acid was performed to select the more suitable response variable for the design of experimental method among the crystallinity and BET specific surface area of MOF-801. After performing 8 synthesis experiments designed by MINITAB 19 software, the characteristic analysis was performed using XRD analysis and nitrogen adsorption method. The crystallinity with R² = 0.999 was found to be more suitable for the experimental method than that of BET specific surface area. Based on analysis of variance (ANOVA), it was confirmed that the molar ratio of fumaric acid and formic acid was a major factor in determining the crystallinity of MOF-801. Through the response optimization and contour plot of two factors, the optimal molar ratio of ZrOCl₂·8H₂O : fumaric acid : DMF : formic acid was 1 : 1 : 39 : 35. In order to optimize the synthesis process, the central composition design on synthesis time and temperature was performed under the identical molar ratio of precursors. The results derived through the designed 9 synthesis experiments were calculated using the quadratic model equation. Thus, the maximum crystallinity of MOF-801 predicted under the synthesis time and temperature of 7.8 h and 123 ℃, respectively.

• Journal of KIISE
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• v.43 no.10
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• pp.1124-1130
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• 2016

A controlled group is closed compared to other organizations, which hinders collection of data and accurate analysis, so that it is hard to evaluate a controlled group's power structure and predict future changes using usual analytical methods including sociological approach. Analyzing a controlled group using SNA can allow for evaluation of inner power structure by revealing the relationships between members and identifying members with central roles given limited data. In this study, in order to evaluate changes in power structure, time-sequential SNA research was conducted by analyzing eigenvector centrality, which reflects individual influence and reveals the overall power structure. The result showed an improvement in accuracy compared to other centralities that contain individual degree or closeness, and made it possible to presume structural changes such as promotion or purge of a member.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Tunnel and Underground Space
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• v.4 no.2
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• pp.102-118
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• 1994

Thermomechanical analysis is conducted on the radioactive repository in deep rock mass considering the in-situ stress, excavation and thermal loading of a radioactive waste. Thermomechanical properties of a discontinuous rock mass are estimated by a theoretical method so called sequential analysis. Using the estimated properties as input for finite element analysis, the influence on temperature distribution and thermal stress is analyzed within the scope of 2-dimensional steady state and transient heat transfer and coupled thermal elastic plastic behaviour. Granitic rock mass is taken for this analysis. The analysis is done for two different rock mass conditions, i.e. continuous-homogeneous and highly jointed conditions, for the purpose of comparison. In the case of steady state, the extent of disturbed zone around the storage tunnel due to the heat production of the spent-fuel canister varies depending on the thermomechanical properties of the rock mass. In the case of transient analyses, the response of the jointed rock mass to the thermal loading after radioactive waste disposal varies significantly with time, resulting in dramatic changes in the both size and location of disturbed zone.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.467-482
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• 2020

We investigate a monitoring procedure for the early detection of parameter changes in location-scale time series models. We introduce a detector for monitoring procedure based on modified residual cumulative sum (CUSUM). The asymptotic properties of the monitoring procedure are established under the null and alternative hypotheses. Simulation results and data analysis are also provided for illustration.