• Journal of Korean Society of Transportation
• /
• v.22 no.2 s.73
• /
• pp.121-130
• /
• 2004

In these days, multiple-path generation method is highly demanded in practice and research areas, which can represents realistically travelers behavior in choosing possible alternative paths. The multiple-path generation algorithm is one of the key components for policy analysis related to ATIS, DRGS and ATMS in ITS. This study suggested a method to generate multiple Possible paths from an origin to a destination. The approach of the suggested method is different from an other existing methods(K-shortest path algorithm) such as link elimination approach, link penalty approach and simulation approach. The result of the multi-label vine-building shortest path algorithm(MVA) by Kim (1998) and Kim(2001) was used to generate multiple reasonable possible paths with the concept of the rational upper boundary. Because the MVA algorithm records the cost, back-node and back-back node of the minimum path from the origin to the concerned node(intersection) for each direction to the node, many potential possible paths can be generated by tracing back. Among such large number of the potential possible paths, the algorithm distinguishes reasonable alternative paths from the unrealistic potential possible paths by using the concept of the rational upper boundary. The study also shows the very simple network examples to help the concept of the suggested path generation algorithm.

• Cartoon and Animation Studies
• /
• s.40
• /
• pp.337-365
• /
• 2015

The objective of this study proposes the new user's addiction model in 'Social Network Games' (SNGs). Research model is derived from the separation of two characteristics. First one is logical characteristics that includes 'Functional' (F), 'Keystroke' (K), and 'Goal' (G). Second one is feeling characteristics that consists a few factors such as 'Emotion' (E), 'Social' (S), and 'Affection' (A). For the pre-test, a total of 30 participants responded to survey in order to inspect the fitness of research questionnaire, roughly validity of the proposed model, and the direction of this reseach. After that for the main test, a total 300 users participated in this research. The final number of effective participants were 261 because 39 were insincere respondents and without playing SNGs who were excluded. Then we examined the measurement model by performing 'Partial Least Squares - Structural Equation Modeling' (PLS-SEM) analysis to test the research hypothesis empirically. The results of the measurement and structural model test lend support to the proposed research model by providing a good fit to the construct data. Interestingly, the model showed the significant effects of the interaction between eleven hypothesis(H1,H2,H3,H4,H5,H6,H7,H8,H9,H10, H12). Only one hypothesis decision t-value not supported that is involved the relationship between SNGs Addiction and Keystroke, H11(1.193). This research expect to contributes to an exploratory SNGs research to clarify the base of addition and will aids understanding of users' behavior associated with SNGs development.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.7
• /
• pp.499-509
• /
• 2016

The number of female government employees is increasing steadily; therefore, the importance of their effective management is also increasing. Recently, female government employees have organized and exploited their social networks to achieve career success. To obtain a better understanding of the consequences of social networking and its impact on female government employees, 262 female employees were asked to provide details about their experiences and attitudes regarding networking behavior (internal and external networking) and how they influenced affective commitment and individual adaptation performance. The results confirmed that social networking significantly increases emotional sharing, and leads to high levels of affective commitment and individual adaptation performance. The moderating roles that positive psychological capital play in the relationships between social networking (internal and external) and emotional sharing were also investigated. The results confirmed that positive psychological capital enhances the impact internal social networking has on affective commitment and individual adaptation performance. Managerial implications for developing effective female employee management strategies were provided for government managers. Based on these results, the theoretical and practical implications of the research findings are discussed, and recommendations for future research are provided.

• Journal of Korean Society of Transportation
• /
• v.23 no.5 s.83
• /
• pp.157-167
• /
• 2005

Seoul metropolitan public transport reform results in the introduction of the semi-public operation and distance-based fare policies. With implementation of these policies, public transport revenue allocation has been (will be) evolved very complicated because the existing revenue allocation issues have not only been clearly solved, which is generated by the combined relationship among Korea Railroad Corporation (KRC). Seoul Metropolitan Subway Corporation (SMSC). Seoul Metropolitan Rapid Transit Corporation (SMRTC), and Incheon Rapid Transit Corporation (IRTC), but also the revenue allocation problem between bus and urban railroad-related organizations need to be considered in this combined framework. On top of that. based on the future plans such as the private sector's railroad construction plan(s), the light rail transit construction plans of several local governments and the join of remained bus lines of Seoul metropolitan areas, it is understood that the revenue allocation among public transport operating organization will become one of main issues of operation organization as well as local and central governments. As a basic approach for revenue allocation of public transport operation organizations, the purpose of this paper is to propose an integrated model applicable to estimate degree of service contribution in passenger carriage in the combined public transport network. With a hypothesis that the complete electronic card system is deployed, this paper supposes every passenger's loading and alighting stations is recordable. Thereby, this paper limits research scope as to Seoul metropolitan railroad area since used route(s) between origin and destination stations can not be traceded because transfer stations each passenger path through is not recorded. Each model proposed in the paper is as follows: 1. a generalized cost reflecting passenger's transfer behavior; 2.a K path model for determining similar routes between O-D; 3.an assignment model for loading O-D trips onto the detected similar routes using Logit Model.

• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.133-143
• /
• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.33 no.4
• /
• pp.271-277
• /
• 2020

There are increasing cases of monitoring the structural response of structures using multiple sensors. However, owing to cost and management problems, limited sensors are installed in the structure. Thus, few structural responses are collected, which hinders analyzing the behavior of the structure. Therefore, a technique to predict responses at a location where sensors are not installed to a reliable level using limited sensors is necessary. In this study, a numerical study is conducted to predict the seismic response of low-rise buildings using limited information. It is assumed that the available response information is only the acceleration responses of the first and top floors. Using both information, the first natural frequency of the structure can be obtained. The acceleration information on the first floor is used as the ground motion information. To minimize the error on the acceleration history response of the top floor and the first natural frequency error of the target structure, the method for predicting the mass and stiffness information of a structure using the genetic algorithm is presented. However, the constraints are not considered. To determine the range of design variables that mean the search space, the parameter prediction method based on artificial neural networks is proposed. To verify the proposed method, a five-story structure is used as an example.

• Journal of the Korea Convergence Society
• /
• v.6 no.6
• /
• pp.17-26
• /
• 2015

Firms that have adopted internet technology have been confused by distorted market signals. It is natural to look at marketplace outcomes for guidance, when confronted with a new business phenomenon. However, market signals can be unreliable in the early states of any important new information technology. New technologies trigger rampant experimentation, and the experimentation is often unsustainable. As a result, market behavior is distorted and must be interpreted cautiously. In Chapter 1, we review a concept of business model and roles of strategies in a business model. In Chapter 2, we discuss a strategic auditing method for analyzing market/channel positioning, product/service positioning, value chain/value network positioning and external environmental factors. In chapter 3, we introduces major frameworks for understanding factors forming strategies. The strategic grid model categorizes four quadrants depending on the level of impacts of information technology on operation and strategy. The strategic alignment model presents a new method of assessing an alignment of information technology and business throughout all elements of a business model. In this research, we review the concept of a business model. This research introduces factors that shape strategies and new frameworks for understanding these factors. The research objective of this manuscript is to present a guidance for firms how to use information technology for attaining sustainable competitive advantages.

• Journal of Korean Society of Transportation
• /
• v.22 no.3 s.74
• /
• pp.109-125
• /
• 2004

In recent decades, microscopic simulation models have become powerful tools to analyze traffic flow on highways and to assist the investigation of level of service. The existing microscopic simulation models simulate an individual vehicle's speed based on a constant free-flow speed dominantly specified by users and driver's behavior models reflecting vehicle interactions, such as car following and lane changing. They set a single free-flow speed for a single vehicle on a given link and neglect to consider the effects of highway design elements to it in their internal simulation. Due to this, the existing models are limitted to provide with identical simulation results on both curved and tangent sections of highways. This paper presents a model developed to estimate the change of free-flow speeds based on highway design elements. Nine neural network models were trained based on the field data collected from seven different freeway curve sections and three different locations at each section to capture the percent changes of free-flow speeds: 100 m upstream of the point of curve (PC) and the middle of the curve. The model employing seven highway design elements as its input variables was selected as the best : radius of curve, length of curve, superelevation, the number of lanes, grade variations, and the approaching free-flow speed on 100 m upstream of PC. Tests showed that the free-flow speeds estimated by the proposed model were statistically identical to the ones from the field at 95% confidence level at each three different locations described above. The root mean square errors at the starting and the middle of curve section were 6.68 and 10.06, and the R-squares at these points were 0.77 and 0.65, respectively. It was concluded from the study that the proposed model would be one of the potential tools introducing the effects of highway design elements to free-flow speeds in simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.48 no.10
• /
• pp.773-782
• /
• 2020

The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.2
• /
• pp.610-619
• /
• 2016

Digital manufacturing (DM) technology helps engineers design products promptly and reliably at low production cost by simulating a manufacturing process and the material behavior of a product in use, based on three-dimensional digital modeling. The computing infrastructure for digital manufacturing, however, is usually expensive and, at present, the number of professional design engineers who can take advantage of this technology to a product design accurately is insufficient, particularly in small and medium manufacturing companies. Considering this, the Korea Institute of Science and Technology Information (KISTI) and H University is operating a DM track in the form of Industry-University-Research Institute collaboration to train high-performance-computing-based DM professionals. In this paper, a series of courses to train students to work directly into DM practice in industry after graduation is reported. The operating cases of the DM track for two years since 2013 are presented by focusing on the progress in establishment, lecture and practice contents, evaluation of students, and course quality improvement. Overall, the track management, curriculum management, learning achievement of students have been successful. By expediting more active participation of the students in the track and providing more internship and job offers in the participating companies in addition to collaborative capstone design projects, the track can be expanded by fostering a nationwide training network.