• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.177-181
• /
• 2009

Developing u-Public facilities for application u-City is to combine both the state-of-the art of the construction and ubiquitous computing and must be flexibly comprised of the facilities for the basic service of the building such as air conditioning, heating, lighting and electric equipments to materialize a new format of spatial planning and the public facilities inside or outside. Accordingly, in this paper we suggested the time pattern system for predicting the most basic power system loads for the basic service. To application the tim e pattern we applied SOM algorithm and k-means method and then clustered the data each weekday and each time respectively. The performance evaluation results of suggestion system showed that the forecasting system better the ARIMA model than the exponential smoothing method. It has been assumed that the plan for power supply depending on demand and system operation could be performed efficiently by means of using such power load forecasting.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.12
• /
• pp.473-484
• /
• 2017

This study analyzed collaborative R&D projects funded by the Korean government from 2013-2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader's organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.

• Ecology and Resilient Infrastructure
• /
• v.10 no.4
• /
• pp.237-249
• /
• 2023

This study was carried to establish a new landscape-oriented gardening model based on climate, vegetation, and forest landscape characteristics. In addition, innovative forest garden models were suggested through an integrated approach to the ecological characteristics of forest vegetation communities and existing garden planting types. For the study, the key landscape elements that make up the main forest vegetation community were identified. And the vertical layers and horizontal distribution patterns of the community structure were typified by diagnostic species and their growth forms & habits such as dominant species, character species, and differential species, and degree of dominance-sociability. Based on this, a standardized vegetation structure and formation was developed by stratifying the landscape into main features, minor features, and detailed features according to visual dominant elements. Also, the applicability of the forest garden model was examined by applying the concept of borrowing landscape to representative deciduous broadleaf forests in the temperate northern region of Korea. Additionally, an integrated forest garden models based on the conceptual definition and typology of forest gardens, and a strategic approach to forest vegetation were proposed

• The Korean Journal of Applied Statistics
• /
• v.21 no.6
• /
• pp.923-932
• /
• 2008

We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.

• Journal of Intelligence and Information Systems
• /
• v.14 no.2
• /
• pp.121-136
• /
• 2008

Although domestic research funding organizations require patented technologies as an outcome of financial aids, they have much difficulty in evaluating qualitative value of the patented technology due to lack of systematic methods. Especially, because citation data is not essential to patent application in Korea, it is very difficult to evaluate a patent using the incomplete citation data. This study proposes a method for evaluating technology importance of a patent when there is no or insufficient citation data in patents. The technology importance of a patent can be evaluated objectively and quantitatively by the proposed method which consists of 5 steps such as selection of a target patent, collection of related patents, preparation of key word vector, clustering patents, and technological importance assessment. The method was applied to a patent on 'user identification method for payment using mobile terminal' in order to evaluate technology importance and demonstrate how the method works.

• Journal of forensic and investigative science
• /
• v.1 no.2
• /
• pp.5-19
• /
• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.33-40
• /
• 2021

Currently, the shipping and port industries are implementing strategies to improve port processing capabilities through the expansion and efficient operation of port logistics resources to survive fierce competition with rapidly changing trends. The calculation of the port's processing capacity is determined by the loading and unloading equipment installed at the dock, and the port's processing capacity can be improved through various methods, such as additional deployment of logistics resources or efficient operation of resources in use. However, it is difficult to expect an improvement effect in a short period of time because the additional deployment of logistics resources is clearly limited in time is clear. Therefore, it is a feasible way to find an efficient operation method for resources being used to improve processing capacity. Domestic ports are also actively promoting informatization and digitalization with the development of the 4th industrial revolution technology. However, the calculation of the number of Y/T (Yard Tractor) assignments in the current unloading process depends on expert experience, and related previous studies also focus on the allocations of Y/T or Calculation of the total number of Y/T required. Therefore, this study analyzed the factors affecting the number of Y/T allocations using the loading and unloading information of incoming ships, and based on this, cluster analysis, regression analysis, and deep neural network(DNN) model were used.

• Journal of Korea Technology Innovation Society
• /
• v.10 no.1
• /
• pp.73-97
• /
• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Korean Business Review
• /
• v.17
• /
• pp.137-151
• /
• 2004

Wrap accounts are customized financial services for which investment companies and stock brokers manage investors assets based on their preferences. The success of wrap accounts depend upon the accurate understanding of investment risk propensity and the proper designing of financial portfolio. To this end investment companies should accurately measure investors investment risk propensity with calibrated measures. There, unfortunately, exist few highly calibrated measures of investment risk propensity. Therefore the practices of marketing strategies and customer management often turn out to be less effective and fragile to competition. The purposes of this present study aim to understand the investment risk propensity of wrap accounts customers, to help classify the customers based on the degree of the investment risk propensity, and to implement relevant marketing strategies for different groups of customers. Based on previous studies, two hypotheses were delineated and verified. The findings of the study should help differentiate prospective customers into unique and accessible segments for further targeting and positioning wrap account markets.

• The Korean Journal of Applied Statistics
• /
• v.29 no.6
• /
• pp.1077-1094
• /
• 2016

Apache Spark is a fast and general-purpose cluster computing package. It provides a new abstraction named resilient distributed dataset, which is capable of support for fault tolerance while keeping data in memory. This type of abstraction results in a significant speedup compared to legacy large-scale data framework, MapReduce. In particular, Spark framework is suitable for iterative machine learning applications such as logistic regression and K-means clustering, and interactive data querying. Spark also supports high level libraries for various applications such as machine learning, streaming data processing, database querying and graph data mining thanks to its versatility. In this work, we introduce the concept and programming model of Spark as well as show some implementations of simple statistical computing applications. We also review the machine learning package MLlib, and the R language interface SparkR.