• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1863-1872
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• 2010

Researches recently made in advanced countries into entrepreneurship found that various resources and information are mainly provided to ventures through social capital, which is a resource capital based on a network, and through corporate entrepreneurship. This research is an exploratory study on the effects of social capital and corporate entrepreneurship of new ventures upon their corporate performance, conducted from the standpoint of dynamic capability. For that purpose, a questionnaire investigation was made of 171 venture entrepreneurs in Korea, and the following are the results of an empirical analysis of responses to the questionnaire. First, it was found that social capital, which is a resource capital based on a network, had a significant effect on corporate entrepreneurship. Second, social capital also had a significant effect on ventures corporate performance. Third, corporate entrepreneurship had a significant effect on corporate performance. These results imply that social capital and corporate entrepreneurship have a significant effect on the corporate performance of ventures, which have innate disadvantages concerning the supply of resources. On the other hand, ventures, which encounter relatively more intense demands for change and renovation, can be managed in a sustainable manner just when they adequately accumulate their social capital and utilize their external resources and appropriately conduct their corporate entrepreneurship activities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.157-168
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• 2014

From a complex systems perspective, ecohydrological systems in forests may be characterized with (1) large networks of components which give rise to complex collective behaviors, (2) sophisticated information processing, and (3) adaptation through self-organization and learning processes. In order to demonstrate such characteristics, we applied the recently proposed 'process networks' approach to a temperate deciduous forest in Gwangneung National Arboretum in Korea. The process network analysis clearly delineated the forest ecohydrological systems as the hierarchical networks of information flows and feedback loops with various time scales among different variables. Several subsystems were identified such as synoptic subsystem (SS), atmospheric boundary layer subsystem (ABLS), biophysical subsystem (BPS), and biophysicochemical subsystem (BPCS). These subsystems were assembled/disassembled through the couplings/decouplings of feedback loops to form/deform newly aggregated subsystems (e.g., regional subsystem) - an evidence for self-organizing processes of a complex system. Our results imply that, despite natural and human disturbances, ecosystems grow and develop through self-organization while maintaining dynamic equilibrium, thereby continuously adapting to environmental changes. Ecosystem integrity is preserved when the system's self-organizing processes are preserved, something that happens naturally if we maintain the context for self-organization. From this perspective, the process networks approach makes sense.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2009.06a
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• pp.187-187
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• 2009

Opening of fractures induced by shear dilation or normal deformation can be a significant source of fracture permeability change in fractured rock, which is important for the performance assessment of geological repositories for spent nuclear fuel. As the repository generates heat and later cools the fluid-carrying ability of the rocks becomes a dynamic variable during the lifespan of the repository. Heating causes expansion of the rock close to the repository and, at the same time, contraction close to the surface. During the cooling phase of the repository, the opposite takes place. Heating and cooling together with the, virgin stress can induce shear dilation of fractures and deformation zones and change the flow field around the repository. The objectives of this work are to examine the contribution of thermal stress to the shear slip of fracture in mid- and far-field around a KBS-3 type of repository and to investigate the effect of evolution of stress on the rock mass permeability. In the first part of this study, zones of fracture shear slip were examined by conducting a three-dimensional, thermo-mechanical analysis of a spent fuel repository model in the size of 2 km $\times$ 2 km $\times$ 800 m. Stress evolutions of importance for fracture shear slip are: (1) comparatively high horizontal compressive thermal stress at the repository level, (2) generation of vertical tensile thermal stress right above the repository, (3) horizontal tensile stress near the surface, which can induce tensile failure, and generation of shear stresses at the comers of the repository. In the second part of the study, fracture data from Forsmark, Sweden is used to establish fracture network models (DFN). Stress paths obtained from the thermo-mechanical analysis were used as boundary conditions in DFN-DEM (Discrete Element Method) analysis of six DFN models at the repository level. Increases of permeability up to a factor of four were observed during thermal loading history and shear dilation of fractures was not recovered after cooling of the repository. An understanding of the stress path and potential areas of slip induced shear dilation and related permeability changes during the lifetime of a repository for spent nuclear fuel is of utmost importance for analysing long-term safety. The result of this study will assist in identifying critical areas around a repository where fracture shear slip is likely to develop. The presentation also includes a brief introduction to the ongoing site investigation on two candidate sites for geological repository in Sweden.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.847-857
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• 2020

As IoT equipment is commercialized, Bluetooth or wireless networks will be built into general living devices such as IP cameras, door locks, cars and TVs. Security for IoT equipment is becoming more important because IoT equipment shares a lot of information through the network and collects personal information and operates the system. In addition, web-based attacks and application attacks currently account for a significant portion of cyber threats, and security experts are analyzing the vulnerabilities of cyber attacks through manual analysis to secure them. However, since it is virtually impossible to analyze vulnerabilities with only manual analysis, researchers studying system security are currently working on automated vulnerability detection systems, and Firm-AFL, published recently in USENIX, proposed a system by conducting a study on fuzzing processing speed and efficiency using a coverage-based fuzzer. However, the existing tools were focused on the fuzzing processing speed of the firmware, and as a result, they did not find any vulnerability in various paths. In this paper, we propose IoTFirmFuzz, which finds more paths, resolves constraints, and discovers more crashes by strengthening the mutation process to find vulnerabilities in various paths not found in existing tools.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.467-474
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• 2010

Recently, Study of functional clothing for Vital sensing is focused on reducing artifact by human motions, in order to enhance the electrocardiogram(ECG) sensing accuracy. In this study, considering the factors for each element found from the analysis, a 3-lead electrode inside textile embroidered with silver yarn was developed, and draft designs off our types of vital-signal sensing garments, which are 'chest-belt typed' garment, 'cross-typed' garment 'x-typed' garment and 'curved x-typed' garment, were prepared. The draft designs were implemented on a sleeveless male shirt made of an elastic material so that the garment and the electrodes can remain closely attached along the contour of the human body, and the acquired data was sent to the main computer over a wireless network. In order to evaluate the effects caused by body movements and the ECG-sensing capability for each type in static and dynamic states, displacements were measured from one and two dimensional perspectives. ECG measurement evaluation was also performed for Signal-to-noise ratio(SNR) analysis. Applying the experimental results, the draft garment designs were modified and complemented to produce two types of modular approaches 'continuous-attached' and 'insertion-detached' for the ECG-sensing smart clothing.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.502-502
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• 2007

A catenary system should be designed to have an uniform elasticity over a span in order to maintain the lowest possible loss of contact between a pantograph and a contact wire. A elasticity uniformity of a catenary can be regarded as a important design factor used for predicting the current collection performance for a catenary. There are a couple of formulas to calculate the degree of elasticity uniformity of a catenary according to the literature survey. The effectiveness of these formulas is reviewed by performing catenary elasticity and loss of contact analysis for various different configurations of catenary systems using a beam element based FEM program. The results reveals that these formulas are not suitable to predict the current collection performance for a catenary. Therefore, a new formula based on the standard deviation of the elasticity over a span is proposed in this study. The analysis results show that the new formula for an elasticity uniformity of a catenary is very effective in predicting the current collection performance for a catenary.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.45-62
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• 2011

The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.

• Knowledge Management Research
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• v.23 no.4
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• pp.315-338
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• 2022

In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.