• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.75-84
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• 2017

The prolonged economic slowdown has forced many youths to opt for starting a business instead of seeking employment. Universities have shown their interest in startup training by opening startup courses and encouraging relevant student communities, while at the same time helping their students land a job. Along with this, the government has been implementing various policies through creative economy and youth startup initiatives, but the resulting quantitative growth has not been supported by a commensurate level of qualitative growth and this has created problems on the supplier side, such as by producing redundant functions and roles in multiple projects and inefficient investment. This study, which aims at proposing a direction towards more active support and thus helping the government achieve qualitative accomplishments that can match its effort in terms of quantitative growth, analyzes the current status of startup support of universities in Korea by examining the data regarding training programs and projects, and highlights the issues stemming from startup organizations in colleges. It also suggests solutions for improving in-college startup training and establishing an interlinked system among the relevant bodies in and out of college, with the hope that the results and alternatives proposed in this study will be utilized as the basis for more active student startup support activities.

• Journal of architectural history
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• v.12 no.1 s.33
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• pp.25-41
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• 2003

This paper is a study of Le Corbusier's trace regulateur of the 1920s, particularly its role in the design of the Villas La Roche-Jeanneret and Stein-de Monzie. It proceeds on the basis of the following three themes: first, the relation between the regulating line and the dom-ino frame; second, its status as a proportional device based not on a module system but one that defines relations; third, its function as an essential practical device in the design process. In the Villa La Roche-Jeanneret, the embedded horizontal planes of the dom-ino frame were constant, but the vortical lines of the columns were altered according to the changes in plan. Initially, a left-hand bay window formed a symmetry with the right-hand bay window, the only constant in the design process. With subsequent changes, mullion sections of the horizontal window and roof elements came to provide the reference points for the regulating line. Eventually, a regulating line different from the one that controlled the bay window and the elongated volume came to control the entrance hall of Villa La Roche, resulting in three different kinds of regulating lines in the final version. In contrast to the Villa La Roche-Jeanneret, a singular and consistent regulation line was anticipated in the earliest design stages of the Villa Stein-de Monzie. The repetition of its A:B grid and the standard $2.5m{\times}1.0m$ sliding window determined the proportions of both its plan and elevation, and thus the regulating line became 'automatic,' losing its viability as a practical tool. Though the regulating titles of the La Roche-Jeanneret look as if they were an afterthought, drawn after the design was complete, they were most active, requiring tenacity and discipline in their application. On the other hand, the seemingly 'redundant' regulating line of the Villa Stein-de Monzie gains its raison d'etre from the dom-ino frame. Its cantilevers and uninterrupted horizontal window could be used in decisive fashion because of the guarantee that the correct proportion would always be maintained. Thus we discover that Le Corbusier's discipline of the 1920s had a certain spectrum of flexibility. His 'parti' ranged from the extremely loose and malleable grid of the Villa La Roche-Jeanneret to the fixed grid of the Villa Stein-de Monzie. In different ways, these projects retain the tension between the dom-ino frame and the regulating line. For Le Corbusier, as much as the grid was an object with fixed attributes, it was also an active medium manipulated by the will of the architect.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.4
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• pp.31-37
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• 2008

Conventional cooperative communications can attain gain of spatial diversity and path loss reduction because destination node independently received same signal from source node and relay node located between source node and destination node. However, these techniques bring about decreased spectral efficiency with relay node and increased complexity of receiver by using maximal ratio combining (MRC). This paper has proposed cooperative ARQ protocol that can improve the above problems and can get the better performance. This method can increase the spectral efficiency than conventional cooperative communication because if the received signal from source node is satisfied by the destination preferentially, the destination transmits ACK message to both relay node and source node and then recovers the received signal. In addition, if ARQ message indicates NACK relay node operates selective retransmission and we can increase reliability of system compared with that of general ARQ protocol in which source node retransmits data. In the proposed protocol, the selective retransmission and ARQ message are to be determined by comparing log-likelihood ratio (LLR) computation of received signal from source node with predetermined threshold values. Therefore, this protocol don't waste redundant bandwidth with CRC code and can reduce complexity of receiver without MRC. We verified spectral efficiency and BER performance for the proposed protocol through Monte-Carlo simulation over Rayleigh fading plus AWGN.

• Journal of Energy Engineering
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• v.23 no.2
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• pp.49-56
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• 2014

It is important to keep stable effluent water quality and minimize operation cost in biological wastewater treatment plant. However, the optimal operation is difficult because of the change of influent flow rate and concentrations, the nonlinear dynamics of microbiology growth rate and other environmental factors. Therefore, many wastewater treatment plants are operated for much more redundant oxygen or chemical dosing than the necessary. In this study, the optimal control scheme for dissolved oxygen (DO) is suggested to prevent over-aeration and the reduction of the electric cost in plant operation while maintaining the dissolved oxygen (DO) concentration for the metabolism of microorganisms in oxic reactor. For optimal control, The oxygen uptake rate (OUR) is realtime measured for the identification of influent characterization and the identification of microorganisms' oxygen requirement in oxic reactor. Optimal DO seT-Point needed for the microorganism is suggested based on real time measurement of oxygen uptake of microorganism and the control of air blower. Therefore, both stable effluent quality and minimization of electric cost are satisfied with a suggested optimal setpoint decision system by providing the necessary oxygen supply requirement to the microorganisms coping with the variations of influent loading.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.417-429
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• 2008

This paper presents an experimental result to evaluate the redundancy in continuous span two plate-girder bridges which are generally classified as a non-redundant load path structure. The experiments were performed when one of the two girders is seriously cracked. To estimate the effects of bottom lateral bracing on the redundancy, the experiment variable was considered as the bottom lateral bracing, and two 1/5-scaled bridge specimens with and without lateral bracing system were fabricated. The ultimate loading tests were conducted on the damaged specimens with an induced crack at a girder in the side span. The test results showed that the load carrying capacity of damaged specimen with bracing was about 1.2 times higher than that without bracing. To evaluate the redundancy in each specimen, numerical analysis was performed to calibrate the difference of dead load between the actual bridge and the test specimens. When the dead load calibration is considered, the results showed that a continuous span two-girder bridges have a reasonable redundancy even without lateral bracing. Especially, the level of redundancy is increased by about 1.8 times when the lateral bracing is provided.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.2
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• pp.47-61
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• 2009

The purpose of this study was to understand the laws related to the safety management of children's play facilities(LRSMCPF) including the "Safety Supervision Law of Children's Play Facilities(SSLCPF)" and the "Quality Management and Industrial Products Safety Management Law(QMIPSAL)", in order to analyze the problems by 4 phases-development of products, landscape design, landscape construction and maintenance considering landscape project procedure-and to propose a revision of the laws. The results are as follows: 1. The various LRSMCPF, SSLCPF and QMIPSAL, as basic laws for the safety management of children's play facilities, were insufficient regarding the features of children's play facilities and play spaces, which are both comparatively varied and complex. 2. In development of products, the one-year duration of safety certification based on QMIPSAL was too short and the procedure for safety certification were redundant in both products and plants inspection, and export and import product inspection. 3. The field inspection of construction sites based on SSLCPF was repeated with quality control and a consultation of rules based on "Construction Technology Management Law". 4. There are not enough safety inspection organizations regarding children's play facilities to meet the demand of safety certification, safety inspection, and safety education in the near future. 5. For children's play safety, the establishment of a general safety management system for children's play connected with the phases is needed to ensure safe play equipment, to construct safe playgrounds, and to manage play facilities. The criteria, regulations, and procedure regarding safety certification and safety inspection of play facilities must be revised efficiently and standardized to a global level as well. To improve the system and contents of safety certification and inspection, authorization of safety inspection organizations based on landscape architecture is needed. Further study will be required to concretely analyze in detail the laws, enforcement decrees and rules, and ordinances that consider the practical experience of professional landscape architects, inspectors, and lawyers.

• Korean Journal of Culture and Arts Education Studies
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• v.5 no.1
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• pp.97-147
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• 2010

Under the recent trend of globalization, a new proposal on education has not been able to avoid the request for multi-cultural trend. Furthermore, education has been exposed to circumstances which are far different from the previous situations in which global cooperation and intercultural understanding have been more emphasized. 'Educational Nomadism'is a metaphor of creating new value and significance of education. In fact, transnational education which could be a crisis and opportunity at the same time has recently been the mainstream throughout the world. In terms of education, Korea has encountered base hollowing-out in which excessive dependence on the US education and autonomous education coexist. In fact, the world has spent a lot of time and money to have better educational background on a resume through redundant expense by the government and parents. Under this critical situation, it's urgent to change Korea's modern education into a creative educational system in connection with an advanced foreign educational system and further develop the advantage of Korea's education. A parent's investment in his/her child is a support to create new culture as well as an assistance for hope and better future of Korean education. A new direction of parents' education fever that has opened a door to global communitas can stir up infinite potential through which the flow of education fever can be changed to the resources of new civilization. The global cooperation and efforts for communitas means the communication with this world. Through this communication, the culture in which people are forced to zero-sum competition can leap into the education for change of civilization which creates pleasure of self sufficiency and donation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.