• Journal of Distribution Science
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• 제13권12호
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• pp.95-103
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• 2015

Purpose - The Visegrád Group cooperation of the past 14 years and that of V4 for the past 20 years has very important significance in the 21st century that must be maintained. This cooperation is valuable because of the trade routes that connect northern Poland to the Balkans in southern Croatia, which forman important basis for the resuscitation of Central European development. Currently, because of the European manufacturing base and industrial development, an energy supply and stable energy distribution networks have been introduced to secure cooperation and not competition within the Visegrád Group. This paper's research emphasizes the supply chain hub in neighboring countries. Although Central and Eastern European countries are small, they can provide a competitive response to Western Europe if they collaborate with the V4 group and other countries. Research design, data, and methodology - The subjects of this study in the Visegrád Group area are related to the development of Marketing and Distribution Sciences in the integrated European Union. In relation to the existing energy infrastructure, construction companies and financial institutions benefit from large-scale construction projects. Existing or new infrastructure facilities among the V4 must comply with the preconditions of regional energy markets. The network of emerging markets is changing into a European-logistics hub of new markets. This hub is closely associated with the economic development of European self-sustainment given that energy for distribution and consumption is imported from Russia. Therefore, this paper indirectly provides data on the regional distribution of energy as alternative bases in Europe for market expansion to Asia. Results - As a result, it appeared unlikely that V4 failed to implement homogeneity following the standards of Western Europe, as proposed by the EU. Throughout European history, individuals have gathered in Central Europe as an innovation hub. Currently, the region is being established independently for energy industrial development and not for tourism development, and is expected to play a central role in innovation and distribution consumption. Therefore, similar to Western and Northern Europe, V4 only appears to engage in distribution consumption on the basis of the identity that it formed for itself. This area is expected to either create a regional platform or a voice over a single economic policy. Conclusions - To this end, regarding the distribution of consumer groups within and outside the region, the V4 group is expected to be established for various policy areas and as a Eurasian outpost of trade and distribution logistics. In addition, given its purpose of engaging in the distribution of energy cooperation and trade clusters, the Visegrád Group will be in charge of the center axis of the bridge for distribution logistics trading partners from the Western Balkans to Caucasus and Eastern Europe. Thus, the Visegrád Group is entering this region as a platform for market share by enabling all or any investor can gain greater industrial benefits.

• Journal of the Korean Geographical Society
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• 제51권6호
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• pp.853-871
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• 2016

The interest in the prevention of sex crimes and social secure is growing as the number of cases by sexual offences becomes higher. Although various punishable ways have been introduced so far, increasing sex crime is still going on. Thus, effectiveness of legal systems for preventing crimes is questionable. More recently, the approach for environmental criminology has been paid attention for reducing criminal opportunities through environmental design and management of crimes. This study attempts to look over the spatial distribution of sexual crimes in the context of environmental criminology, and examine the correlation between regional environmental factors and the occurrence of sexual crimes empirically. To do this, we visualized the map for sex crimes at the macro-scale and explored the spatial distribution of sexual crimes and spatial clusters based on various spatial statistics using sex crime data published online by the ministry of gender equality and family. Also, we derived the environmental characteristics of sexual crimes by multivariate regression analysis on a large number of explanatory variables of regional environment. Our results will help to understand the current situation and spatial aspects of sex crimes in the nation more realistically. Further, it is respected that our results might be useful basic information for establishing regional policies and plans for the prevention of the sexual crime and enhanced public policing.

• Survey Research
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• 제8권2호
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• pp.67-89
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• 2007

The Korea National Health and Nutrition Examination Survey(KNHANES) consists of Health Interview Survey, Health Behaviour Survey, Nutrition Survey, and Health Examination, and is designed to produce a broad range of descriptive health and nutritional statistics for sex and age subdomains of the population. These data can be used to measure and monitor the health and nutritional status of the population of Korea. The survey has been conducted three times from 1998. The Korea Centers for Disease Control and Prevention(KCDC) is preparing for the 4th survey which is to be conducted from 2007 through 2009. This study is to design a sample for the 4th survey. The main new feature of the sampling design is using a rolling sampling design method. Since KCDC has imposed some operational requirements, e,g., the needs of producing the annual national statistics and of year-round data collection by some regular staffs, a rolling sampling design method is introduced. This is the first time in history of applying a rolling sampling design for a national-wide large scale survey in Korea. Bringing in the rolling sampling, measurement variation due to different data collectors may be minimized.

• Journal of The Korean Astronomical Society
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• 제36권3호
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• pp.89-95
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• 2003

Observations of dark matter dominated dwarf and low surface brightness disk galaxies favor density profiles with a flat-density core, while cold dark matter (CDM) N-body simulations form halos with central cusps, instead. This apparent discrepancy has motivated a re-examination of the microscopic nature of the dark matter in order to explain the observed halo profiles, including the suggestion that CDM has a non-gravitational self-interaction. We study the formation and evolution of self-interacting dark matter (SIDM) halos. We find analytical, fully cosmological similarity solutions for their dynamics, which take proper account of the collisional interaction of SIDM particles, based on a fluid approximation derived from the Boltzmann equation. The SIDM particles scatter each other elastically, which results in an effective thermal conductivity that heats the halo core and flattens its density profile. These similarity solutions are relevant to galactic and cluster halo formation in the CDM model. We assume that the local density maximum which serves as the progenitor of the halo has an initial mass profile ${\delta}M / M {\propto} M^{-{\epsilon}$, as in the familiar secondary infall model. If $\epsilon$ = 1/6, SIDM halos will evolve self-similarly, with a cold, supersonic infall which is terminated by a strong accretion shock. Different solutions arise for different values of the dimensionless collisionality parameter, $Q {\equiv}{\sigma}p_br_s$, where $\sigma$ is the SIDM particle scattering cross section per unit mass, $p_b$ is the cosmic mean density, and $r_s$ is the shock radius. For all these solutions, a flat-density, isothermal core is present which grows in size as a fixed fraction of $r_s$. We find two different regimes for these solutions: 1) for $Q < Q_{th}({\simeq} 7.35{\times} 10^{-4}$), the core density decreases and core size increases as Q increases; 2) for $Q > Q_{th}$, the core density increases and core size decreases as Q increases. Our similarity solutions are in good agreement with previous results of N-body simulation of SIDM halos, which correspond to the low-Q regime, for which SIDM halo profiles match the observed galactic rotation curves if $Q {\~} [8.4 {\times}10^{-4} - 4.9 {\times} 10^{-2}]Q_{th}$, or ${\sigma}{\~} [0.56 - 5.6] cm^2g{-1}$. These similarity solutions also show that, as $Q {\to}{\infty}$, the central density acquires a singular profile, in agreement with some earlier simulation results which approximated the effects of SIDM collisionality by considering an ordinary fluid without conductivity, i.e. the limit of mean free path ${\lambda}_{mfp}{\to} 0$. The intermediate regime where $Q {\~} [18.6 - 231]Q_{th}$ or ${\sigma}{\~} [1.2{\times}10^4 - 2.7{\times}10^4] cm^2g{-1}$, for which we find flat-density cores comparable to those of the low-Q solutions preferred to make SIDM halos match halo observations, has not previously been identified. Further study of this regime is warranted.

• Journal of the Korean Association of Geographic Information Studies
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• 제12권3호
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• pp.152-163
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• 2009

This study identified characteristics of households in Seo Geumsa based on factors related to how well each household understood and agreed or disagreed with the Newtown project and the resettlement process that is required to establish the renewal promotion plan. To this end, the authors applied the unit of spatial analysis developed by Tong, segmented the land intended for large-scale development, and then developed a method for analyzing and comparing the segmented lands by certain characteristics. The results of the survey were analyzed in three stages: the characteristics of districts; the relationships between agreement and disagreement factors and differences among segmented districts. And, to assess districts with features that differed from the overall features of households in renewal districts, the authors developed a two-way stage division plan and conducted a cluster analysis. The authors analyzed districts with individual characteristics based on the household features developed by Tong, and then analyzed the features of household distribution in these districts along with spatial location.

• Journal of the Korea Society of Computer and Information
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• 제27권2호
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• pp.171-177
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• 2022

In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.

• Particle and aerosol research
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• 제19권4호
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• Journal of Internet Computing and Services
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• 제25권4호
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Journal of Intelligence and Information Systems
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• 제17권4호
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Journal of Intelligence and Information Systems
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• 제25권1호
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.