• The Journal of Korean Association of Computer Education
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• v.18 no.6
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• pp.71-79
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• 2015

In a new era of Cloud and Big data, how to search the useful data from dynamic huge data pool in a right time and right way is most important at the stage where the information is getting more important. Above all, in the era of s Big Data it is required to design the advanced efficient intelligent Knowledge system which can process the dynamic variable big data. Accordingly in this paper we propose Dynamic personal Knowledge Network as one of the advanced Intelligent system approach. Adopting the human brain function and its neuro dynamics, an Intelligent system which has a structural flexibility was designed. For Structure-Function association, a personal Knowledge Network is made to be structured and to have reorganizing function as connecting the common nodes. We also design this system to have a reasoning process in the extracted optimal paths from the Knowledge Network.

• The Journal of Bigdata
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• v.2 no.2
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• pp.33-46
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• 2017

Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.1-11
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• 2016

Currently Korean government is rushing the new electronic government system introduced as 'platform e-government' with big data and cloud computing technologies and systems, ultimately intending to provide the public institution services customized from the integrated counter or window for the heterogeneous resident services. In this regard, this study suggested how to design the new metadata information system in which mutual integration of information systems can take place, where heterogeneous services can be shared efficiently at the application and data unit, as a separate application that can provide a single one- stop service for residents' petition at the integrated level in the back-office based on the public data in possession of each of government ministries and related organizations. If this proposed system is implemented, the achievement of customized public service can be advanced one step forward in processing the petitions of the residents by organically connected link between 'Demand Chain' and 'Supply Chain' in the integrated window. In other words, it could be made possible through the unification of both the 'Supply Chain' performed in the office space of the officials at the back-office level and the 'Demand Chain' performed in the living space of the residents at the front-office level.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.87-94
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• 2019

In this paper, the method of analyzing the unformatted data of consumers accumulated on social networks in the era of the Fourth Industrial Revolution by utilizing data from the service design and social psychology aspects was proposed. First, the fandom phenomenon, which shows subjective and collective behavior in a space on a social network rather than physical space, was defined from a data service perspective. The fandom model has been transformed into a collective level of customer Persona that has been analyzed at a personal level in traditional service design, and social network analysis that analyzes consumers' big data has been presented as an efficient way to pattern and visually analyze it. Consumer data collected through social leasing were pre-processed by column based on correlation, stability, missing, and ID-ness. Based on the above data, the company's brand strategy was divided into active and passive interventions and the effect of this strategic attitude on the growth direction of the consumer's fandom community was analyzed. To this end, the fandom model of consumers was proposed by dividing it into four strategies that the brand strategy had: stand-alone, decentralized, integrated and centralized, and the fandom shape of consumers was proposed as a growth model analysis technique that analyzes changes over time.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.499-512
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• 2020

The development of the economy and network environment has a great impact on physical stores, and physical bookstores are gradually upgrading and transforming with the pace of the times. This study takes the modern bookstore under the concept of the third space as the research object. The purpose of it is to understand the needs of consumers for the space of the modern bookstores, explore the characteristics and development direction of them, which provides theoretical guidance for the follow-up development of the modern bookstore. Based on the concept of the third space and the theory of lifestyle shops and reorganizing theoretical investigation and prior research, the researcher extracts the characteristic elements of modern bookstores in line with the concept of the third space. Moreover, the research analyzes five bookstores opened in large-scale commercial facilities after 2010 as research cases. Through the analysis of the results, it shows that the modern bookstore is a multi-functional and compounded space which is gradually transformed from a single bookseller to a seller of selling lifestyle proposal. And through the analysis of big data to predict the changes in market consumption, we can find out the different needs of consumers, so as to carry out the targeted design of bookstore space and then improve the value of it. In the context of the co-development of economy and culture, the transformation of modern bookstores actually conforms to the change of consumer demand and realizes a virtuous circle.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.188-199
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• 2023

CCTV is widely used as a crime prevention method globally; however, there is insufficient evidence regarding its effectiveness. This study assesses the suitability of CCTV locations and their impact on crime prevention. First, to analyze the appropriateness of the location of CCTVs, we overlaid the locations of crimes and CCTV, and found that there are many cases where CCTV were placed where crime rarely occurred. Using various cases, we verified CCTV's crime prevention effectiveness. The WDQ was applied to comprehensively analyze the impact of CCTV surveillance area and surrounding areas to determine the crime prevention effect. As a result of the analysis, CCTV was found to be effective in preventing crime. In 53.09% of the cases, there was a diffusion effect of crime control benefits in the surrounding area, which was four times more than the cases with a transfer effect. Thus, strategically installing CCTV in appropriate locations enhances crime prevention effectiveness based on spatial analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.8
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• pp.181-188
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• 2016

Recently, as the amount of spatial information increases, an interest in the study of spatial information processing has been increased. Spatial database systems extended from the traditional relational database systems are difficult to handle large data sets because of the scalability. SpatialHadoop extended from Hadoop system has a low performance, because spatial computations in SpationHadoop require a lot of write operations of intermediate results to the disk, resulting in the performance degradation. In this paper, Spatial Computation Spark(SC-Spark) is proposed, which is an in-memory based distributed processing framework. SC-Spark is extended from Spark in order to efficiently perform the spatial operation for large-scale data. In addition, SC-Spark based on the GPGPU is developed to improve the performance of the SC-Spark. SC-Spark uses the advantage of the Spark holding intermediate results in the memory. And GPGPU-based SC-Spark can perform spatial operations in parallel using a plurality of processing elements of an GPU. To verify the proposed work, experiments on a single AMD system were performed using SC-Spark and GPGPU-based SC-Spark for Point-in-Polygon and spatial join operation. The experimental results showed that the performance of SC-Spark and GPGPU-based SC-Spark were up-to 8 times faster than SpatialHadoop.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.225-231
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• 2022

Transcendence of space and time, virtual reality, augmented reality, etc. are being realized through the latest technologies in the era of the 4th industrial revolution. In a situation where they are currently experiencing artificial intelligence, augmented reality, big data, etc., the degree of interest in the latest technologies of the 4th industrial revolution for radiology students, the necessary competencies in the 4th industrial revolution era, and the prospect of the radiation field employment environment in the 4th industrial revolution era The purpose of this study was to find out the level of awareness of From February 7th to February 18th, 2022, surveys on awareness were analyzed using questionnaires for 2nd and 3rd year students in the Department of Radiology at S University in Daegu. As a result of the study, the level of interest in 3D modeling was shown to be the highest with an average of 3.34 ± 1.09 points, and interest in big data and artificial intelligence was also shown with an average of 3.27 ± 1.17 and 3.33 ± 1.07 points. In addition, the correlation between the awareness of the necessary competencies in the 4th industrial revolution era and the awareness of the prospects for employment in the radiation field in the 4th industrial revolution era was the highest (r=0.778, p<0.01), and the interest in the latest technologies in the 4th industrial revolution and the 4th industrial revolution It was found that there was also a correlation between the perceptions of the necessary capabilities of the times (r=0.694, p<0.01). In the era of the 4th industrial revolution, it is judged that it is necessary to strengthen professional education that can handle the latest technologies such as 3D printing, artificial intelligence, and big data, and to strengthen employment capabilities related to the latest technologies in the field of radiation medical technology.