• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3835-3850
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• 2024

The high-temperature gas-cooled reactor (HTGR) with spherical fuel elements contains complex pebble flow. The flow behavior of pebbles is influenced by various factors, such as pebble density, friction coefficient, wall structure, and discharge port size. Using a GPU-DEM numerical model, the effects of the friction coefficient on the cyclic loading and unloading of pebbles in the full-scale HTR-PM are studied. Numerical simulations with up to 420,000 spherical pebbles are conducted. Four sets of friction coefficient values are determined for comparative analysis based on experimental measurements. Discharging speed, residence time, stress, porosity, and velocity distribution are quantitatively analyzed. In addition, a comparison with the CT-PFD experiment is carried out to validate the numerical model. The results show that near-wall retention phenomena are observed in the reactor core only when using large friction coefficients. However, using friction coefficient values closer to the measured experimental values, the pebble bed in HTR-PM exhibited good flow characteristics. Furthermore, the friction coefficient also influences the porosity and velocity distribution of the pebble bed, with lower friction coefficients resulting in lower overall stress in the bed. The discharge outlet's influence varies with different friction coefficient values. In summary, this study demonstrates that the value of the friction coefficient has a complex influence on the pebble flow in HTR-PM, which provides important insights for future numerical and experimental studies in this field.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.12-21
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• 2017

From 1960, the government decided to build apartment houses on a large scale in order to resolve the rising housing problems. However, the maintenance issues that have arisen from the deterioration of housing has not received adequate attention. The policy focuses only on the supply of housing. By passing new laws, the durable period during which buildings allowed reconstruction was increased, and long term maintenance plans were treated as important issues. The government was then obligated to establish certain long term maintenance plans and costs by legislating a Housing Act and requiring it be adjusted every three years. However, when planning long-term repair costs, doing so without considering the time value of money would become a problem. In addition, if differences between the planned repair costs and actual costs occur, it becomes necessary to adjust the long-term repair costs but, as of yet, the criteria to adjust such things does not exist. For these reasons, if there is lack of money to execute large-scale repair work, a building is unlikely to respond to deterioration of housing; on the other hand, an unnecessary reserve or pool of money can lead to conflict among residents. Therefore, this paper will propose estimation and adjustment models considering the time value of money for long term maintenance costs of apartment houses.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.13-27
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• 2019

This study shows the changes in the space created by the planning and leisure activities of Hangang River Park, focusing on the Yeouido portion of the Hangang River Park, which has the most users and the greatest degree of planning. The relationship between planning, behavior, and space changes are explained based on Giddens's Structural Theory. As research material, Hangang River Park plans and satellite photos were interpreted and newspaper articles were used to identifying the space changes and their causes, and a model of the space changes was derived through the application of the theory. The flow of space change in the Yeouido portion of the Hangang River Park due to planning and leisure activities is as follows. In the 1970s, the first sports spaces are made due to need from residents near the riverside, but huge plans for the utilization of the entire space were not realized. In the 1980s, leisure spaces were planned and developed through a comprehensive plan. Various sports spaces were built, but the environment of the spaces became a slum. In the 1990s, various leisure activities were revitalized due to the revision of the legal system, regulations on the usage of space, and space maintenance, and from the late 1990s, ecological issues arose along the Hangang River. In the 2000s, there was an overall space improvement project directed by two comprehensive plans, and cultural and ecological issues appeared in the Hangang River Park plans. However, actual leisure spaces were developed along with the promotion of large-scale activities. Regarding the structuration theory, elements of interaction, modality, and structure are the aspects of space changes in the Yeouido portion Hangang River Park. As the flow of the space change, the proportions of the comprehensive plan and the individual plans were similar. The comprehensive plan was influenced by the change of public businesses and the proliferation of large-scale activities. Individual plans were influenced by the user's activities and opinions. However, both plans were influenced by the users and suppliers. The leisure space of the Hangang River Park can be viewed as a social space, in terms of the structuring as a theory due to the user repeatedly changing the use of the space. The purpos of this study is to investigate the changes in the Hangang River Park space through planning and leisure activities. Through this study, we can understand the characteristics of the Hangang River Park in planning the leisure activity space.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.43-62
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• 2004

Conventionally the estimation method of the origin-destination Matrix has been developed by implementing the expansion of sampled data obtained from roadside interview and household travel survey. In the survey process, the bigger the sample size is, the higher the level of limitation, due to taking time for an error test for a cost and a time. Estimating the O-D matrix from observed traffic count data has been applied as methods of over-coming this limitation, and a gradient model is known as one of the most popular techniques. However, in case of the gradient model, although it may be capable of minimizing the error between the observed and estimated traffic volumes, a prior O-D matrix structure cannot maintained exactly. That is to say, unwanted changes may be occurred. For this reason, this study adopts a conjugate gradient algorithm to take into account two factors: estimation of the O-D matrix from the conjugate gradient algorithm while reflecting the prior O-D matrix structure maintained. This development of the O-D matrix estimation model is to minimize the error between observed and estimated traffic volumes. This study validates the model using the simple network, and then applies it to a large scale network. There are several findings through the tests. First, as the consequence of consistency, it is apparent that the upper level of this model plays a key role by the internal relationship with lower level. Secondly, as the respect of estimation precision, the estimation error is lied within the tolerance interval. Furthermore, the structure of the estimated O-D matrix has not changed too much, and even still has conserved some attributes.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.53-77
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• 2008

In recent years, although numbers of corporations are bringing in PMO, they seem to be indifferent to PMO performance measurement. This demonstrates that there are also other reasons beside performance measurement of information systems (IS) project being ambiguous by introducing PMO; the lack of acknowledging the concrete function of PMO, and the scarcity of empirical study about the effect of PMO on the project members and project performance. In this sense, this study is aimed at proposing a new research model in which project success factors (i.e., standardization, management advocacy, and staff expertise) affect PMO capability (i.e., knowledge management, resources management, and problem solving competency) positively, leading to project performance (i.e., task outcomes, psychological outcomes, and organizational outcomes) eventually. To empirically test the research model, data are surveyed from PMO department and IS department. To prove the validity of the proposed research model, PLS analysis is applied with valid 132 questionnaires. By employing PLS technique, the measurement reliability and validity of research variables are tested and the path analysis is conducted to do the hypothesis testing. The path analysis results can be organized into 7 ways in large scale. First, standardization of project success factors has a positive association with knowledge management, resources management, and problem solving competency of PMO capabilities. The findings of this result indicate that the multiple or single project management should satisfy standardization in order to operate an effective PMO. Second, management advocacy of project success factors has a positive association with knowledge management, resources management, and problem solving competency. Management advocacy refers to the willingness of management to provide the required resources and authority for project success. There is agreement among researchers regarding the importance of management advocacy for favorable PMO capability. Third, staff expertise of project success factors has a positive association with knowledge management, resources management, and problem solving competency. The findings of this result indicate that the formation of an exceptional consultant or members with a proficient knowledge for staff expertise of project member is the key factor to elevate the PMO capability. Past research suggests that experience and knowledge and the resultant familiarity with the problem faced can be an important determinant of PMO capability. A capable project with appropriate staff expertise means that it enjoys a diversity of abilities and experiences. Fourth, knowledge management competency of PMO capabilities has a positive impact on psychological outcomes but has no direct effect on task outcomes and organizational outcomes. In domestic case of S. Korea, PMO was finally introduced to many other corporations in 2005 though it started bringing in 2000. Therefore, it had neither a significant impact on the task outcomes nor organizational outcomes by lacking the contents and the infrastructure of the knowledge management because the knowledge consolidation and management period of PMO is comparatively shorter by terms than other foreign nations. Fifth, resources management competency of PMO capabilities has a positive association with task outcomes, psychological outcomes, and organizational outcomes. In addition, problem solving competency of PMO capabilities has a positive association with task outcomes, psychological outcomes, and organizational outcomes. Therefore, the findings of this results stress that PMO capabilities has a positive impact on project performance. Sixth, according to the path analysis of the hypothesis, which suggested in this research, problem solving competency is the PMO capability which is the key success factor for task, psychological, and organizational outcomes as an integrated performance model. Further, the analysis reveals that problem solving competency is an important factor for integrated performance model. The finding is in line with past IS research, which affirms that the work of IS projects is essentially a problem solving endeavor. Seventh, in the path analysis of the hypothesis in this research, the path of the management advocacy $\rightarrow$ problem solving competency $\rightarrow$ organizational outcomes appears to be the most important and strongest path. In brief, the finding of this study suggests that project success factors influence PMO capability positively, and project performance as well. From the results, it can be concluded that PMO helped great improve the project success rate and project performance. This study advances research on PMO capability in three important aspects. First, the findings of our study have implications for IS theory and future research. Our study contributes to IS theory by synthesizing concepts from PMO research and project management research with those in IS research. We proposed and tested PMO capability of IS projects and the findings of our investigation provided some preliminary answers to some of the questions raised. Secondly, this thesis does not only help depicting the concept of IT governance but also approaches empirically. It makes a gradual approach to the main content, step by step, in contrary of simple standard, scholastic way of thinking. Finally, we argued that this task-oriented(technical) view is not sufficient to adequately conceptualize IS project performance. Hence, we applied that the research on organization teams, which provides a flip viewpoint to that of project management research in that it gives more weight for psychological outcomes of organizational work groups, can be very helpful in reconceptualizing the IS project performance construct. The limitations of this study are also discussed to provide research directions for future research.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.435-445
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• 2023

A delta is a depositional landform that is formed when sediment transported by a river is deposited in a relatively low-energy environment, such as a lake, sea, or a main channel. Among these, a delta formed at the confluence of rivers has a great importance in river management and research because it has a significant impact on the hydraulic and sedimentological characteristics of the river. Recently, the equilibrium state of the confluence area has been disrupted by large-scale dredging and construction of levees in the Nakdong River. However, due to the natural recovery of the river, the confluence area is returning to its pre-dredging natural state through ongoing sedimentation. The time-series data show that the confluence delta has been steadily growing since the dredging, but once it reaches a certain size, it repeats growth and retreat, and the overall size does not change significantly. In this study, we developed a model to explain the sedimentation-erosion processes in the confluence area based on the assumption that the confluence delta reaches a dynamic equilibrium. The model is based on two fundamental principles: sedimentation due to supply from the tributary and erosion due to the main channel. The erosion coefficient that represents the Nakdong River confluence areas, was obtained using data from the tributaries of the Nakdong River. Sensitivity analyses were conducted using the developed model to understand how the confluence delta responds to changes in the sediment and water discharges of the tributary and the main channel, respectively. We then used annual average discharge of the Nakdong River's tributaries to predict the dynamic equilibrium positions of the confluence deltas. Finally, we conducted a simulation experiment on the development of the Gamcheon-Nakdong River delta using recorded daily discharge. The results showed that even though it is a simple model, it accurately predicted the dynamic equilibrium positions of the confluence deltas in the Nakdong River, including the areas where the delta had not formed, and those where the delta had already formed and predicted the trend of the response of the Gamcheon-Nakdong River delta. However, the actual retreat in the Gamcheon-Nakdong River delta was not captured fully due to errors and limitations in the simplification process. The insights through this study provide basic information on the sediment supply of the Nakdong River through the confluence areas, which can be implemented as a basic model for river maintenance and management.

• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.65-77
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• 2017

Recently, many Korean major construction companies are suffering from profit loss mainly due to a direct impact from delays in their overseas projects. In general, changes are inevitable in a large-scale project, and most of changes are directly linked to construction delay. Therefore, in the event that an extension of time is necessary due to a change, the contractor must manage the delay based on the condition of the contract to effectively manage risks from delay to the completion date. Thus it is important to understand delay protocol defined in the condition of the contract early in the project, but there have been few or no study to propose methodology or tool to support this effort. This paper presents a review on the project planning and controling practices of major Korean construction companies along with the issues on delay claims and disputes in mega-international projects and suggests a tool to assess delay risk in the condition of the contract. To propose a delay risk assessment model for international construction projects, major standard conditions of contract have been reviewed including FIDIC Red Book(1999), PSSCOC(2014) and SIA 9th Edition(2010). To reflect recent trend of major international owners, standard conditions which they are utilizing for their projects also have been reviewed including those of ARAMCO and QP. The model provides a categories of risks to be reviewed on the condition of the contract along with standard level of the risk which is common in the international standard form of the contracts. This study also performed a case study on an actual international project to confirm the effectiveness of proposed model to identify and respond to a delay risk of a project.