• Convergence Security Journal
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• v.7 no.1
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• pp.83-89
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• 2007

This paper is to suggest the method of embedding a signature to pictures secretly under the orthogonal wavelet transform which represents pictures as multi-resolution representations. As it is focused upon the differential output under the multi-resolution representation of pictures, this method can embed bit series to pictures. In doing so, it can compound approximately 6K byte of information with gray-level image $256{\times}256$. The method can include not only the database which designates copyright of pictures but also the author and usage of pictures, and the information of the picture itself. Therefore, this method can easily discriminate the inspection of picture database.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.207-215
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• 2020

Studies on aesthetic experience in games mostly focus on engineering approach centered on structural determination of specific target within the game as well as humanistic·social approach in forms of artistic conversation on game play experience. This paper have established a theoretic guideline regarding the progress of aesthetic experience which allows analysis from the perspective of player experience acquired during game play. Based on such guideline, the study classifies cognitive data (Eye-Tracking, Playing Action, Facial Expression) on aesthetic experience and suggests the methods to measure such data. By deducing errors and points to be considered related to measuring methods through pilot tests, this study will contribute to the execution of empirical study focused on player perspective.

• Journal of KIISE
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• v.44 no.11
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• pp.1209-1218
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• 2017

A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.

• The Journal of Bigdata
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• v.5 no.2
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• pp.29-42
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• 2020

In Korea, micro-enterprises are in charge of an important part of the common people's economy, but face difficulties such as excessive competition, deteriorating profitability, and concentration of life-oriented industries. In order to solve this problem, the government is providing commercial district analysis services for micro-enterprises. However, the data provided by various organizations is not standardized, and there is a limit to the composition of the service with limited data. In this paper, we propose a method of solving the data consistency problem and linking and analyzing between questionnaire information and commercial district information to expand the data analysis service. The proposed linking methods are three methods: linking the commercial area information and questionnaire information in the same area based on the type of business and area, linking the survey information centered on individual micro-enterprise, and linking a small area of questionnaire information with a large area of commercial district information. The linked commercial district information and questionnaire information can be used in various ways or expanded analysis services. This proposed a method to overcome the limitations of existing commercial district analysis services with questionnaire information and lay the foundation for expanding the commercial district analysis services necessary for micro-enterprises.

• Journal of KIISE:Databases
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• v.28 no.2
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• pp.153-167
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• 2001

다차원 온라인 분석처리(Multidimensional On-Line Analytical Processing: MOLAP)에서 집계 연산은 중요한 기본 연산이다. 기존의 MOLAP 집계 연산은 다차원 배열 구조를 기반으로 한 파일 구조에 대해서 연구되어 왔다. 이러한 파일 구조는 편중된 분포를 갖는 데이터에서는 잘 동작하지 못한다는 단점이 있다. 본 논문에서는 편중된 분포에도 잘 동작하는 다차원 파일구조를 사용한 집계 알고리즘을 제안한다. 먼저, 새로운 분리-포함 분할이라는 개념을 사용한 집계 연산 처리 모델을 제안한다. 집계 연산 처리에서 분리-포함 분할 개념을 사용하면 페이지들의 액세스 순서를 미리 알아 낼 수 있다는 특징을 가진다. 그리고, 제안한 모델에 기반하여 원-패스 버퍼 크기(one-pass buffer size)를 사용하여 집계 연산을 처리하는 원-패스 집계 알고리즘을 제안한다. 원-패스 버퍼 크기란 페이지 당 한 번의 디스크 액세스를 보장하기 위해 필요한 최소 버퍼 크기이다. 또한, 제안한 집계 연산 처리 모델 하에서 제안된 알고리즘이 최소의 원-패스 버퍼 크기를 갖는다는 것을 증명한다. 마지막으로, 많은 실험을 통하여 이론적으로 구한 원-패스 버퍼 크기가 실제 환경에서 정확히 동작함을 실험적으로 확인하였다. 리 알고리즘은 미리 알려진 페이지 액세스 순서를 이용하는 버퍼 교체 정책을 사용함으로써 최적의 원-패스 버퍼 크기를 달성한다. 제안하는 알고리즘을 여 러 집계 질의가 동시에 요청되는 다사용자 환경에서 특히 유용하다. 이는 이 알고리즘이 정규화 된 디스크 액세스 횟수를 1.0으로 유지하기 위해 반드시 필요한 크기의 버퍼만을 사용하기 때문이다.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.15-23
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• 2010

The 4-DAT is a tool for analyzing general development process such as XP and Scrum. In this paper, we suggest a new evaluation method based on 3-DAT for mobile game. Since the 4-DAT has inappropriate evaluation items and unnecessary elements for mobile game development, a revised evaluation method which was optimized using three dimension. The 3-D based evaluation method have development context variables of 5 items and 20 detailed criteria. They were defined based on the theory of P.Abrahammsson, B. Boehm and R. Turner. For the experiment, We applied to five mobile game developments which were earned out for 4 months. It analyzed the three factors of the development teams dependence, inequity and flexibility. This study found that short-term mobile game developments can be completed with low risk when dependence is low, inequity is high and flexibility is high.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.355-371
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• 2009

The purpose of this study is to investigate the spatial structure of the production of technological knowledge in the Korean photonics industry. Patent data were used as a proxy of knowledge production. The data were gathered by keywords among the registered patents which were applied from 1996 to 2007. The photonics industry patents registered at United States Patent Trademark Office(USPTO) show that Korea and Taiwan, as a latecomer, have rapidly increased. The photonics industry patents registered at Korean Intellectual Property Office(KIPO) were analyzed by type of application: single-applicant and co-applicant patents. The analysis of single-applicant patents shows that technological knowledge in the Korean photonics industry has been produced mainly in Seoul, Suwon, and Daejeon. The degree of spatial bias, however, has been slightly decreased during the study period. Above-mentioned regions are also main centers in the analysis of co-applicant patents, but the forms of inter-regional cluster and network are different over time. It is because agents participating in co-applicant patents are diverse and increased. Furthermore, it seems that policies, such as the improvement of the infrastructure of ICT, the promotion of the photonics industry and the industry-university-institute collaboration, are very influential.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.331-340
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• 2018

This study used data from '2016 Chungnam Citizens' Lifelong Education Needs Survey'. This analyzed the basic situation of Citizen Participation Education. It also typifies the interest and participation intention of lifelong education by region, and compared the interest and participation intention of Citizen Participation Education. Through this, we intend to provide concrete basic data for activating the Citizen Participation Education in Chungnam. We analyzed data of 4,108 people in 2016 lifelong education needs survey. This was named enjoy learning type, bias earning type, and elderly learning type. Second, the enjoy learning type group is a group that enjoys participating throughout lifelong education area. bias earning type group is a group that perceives that lifelong education is limited to vocational ability education, culture art education, and liberal arts education. These are groups that are interested and participating only in three areas. The elderly learning type group is a group that shows typical characteristics of the elderly learners and is a group that is concentrated on participation in culture arts education. Third, enjoy learning type group is the second most experienced participant. They are the group with the highest participation interest and participation intention. bias earning type group is the group with the highest participation experience. They are also the second highest group of participating interests and willingness to participate. elderly learning type group is the group with lowest participation experience, participation interest, and participation intention. Finally, we suggest the ways to revitalize Citizen Participation Education in lifelong education.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.596-608
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• 2004

A lot of work has been done to reduce disk access time in I/O intensive systems, which store and handle massive amount of data, by distributing data across multiple disks and accessing them in parallel. Most of the previous work has focused on an efficient mapping from a grid cell to a disk number on the assumption that data space is regular grid-like partitioned. Although we can achieve good performance for low-dimensional data by grid-like partitioning, its performance becomes degenerate as grows the dimension of data even with a good disk allocation scheme. This comes from the fact that they partition entire data space equally regardless of distribution ratio of data objects. Most of the data in high-dimensional space exist around the surface of space. For that reason, we propose a new declustering algorithm based on the partitioning scheme which partition data space from the surface. With an unbalanced partitioning scheme, several experimental results show that we can remarkably reduce the number of data blocks touched by a query as grows the dimension of data and a query size. In this paper, we propose disk allocation schemes based on the layout of the resultant data blocks after partitioning. To show the performance of the proposed algorithm, we have performed several experiments with different dimensional data and for a wide range of number of disks. Our proposed disk allocation method gives a performance within 10 additive disk accesses compared with strictly optimal allocation scheme. We compared our algorithm with Kronecker sequence based declustering algorithm, which is reported to be the best among the grid partition and mapping function based declustering algorithms. We can improve declustering performance up to 14 times as grows dimension of data.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.238-241
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• 2023

Recently deep learning models are widely used for various tasks such as facial recognition and face editing. Their training process often involves a dataset with imbalanced age distribution. It is because some age groups (teenagers and middle age) are more socially active and tends to have more data compared to the less socially active age groups (children and elderly). This imbalanced age distribution may negatively impact the deep learning training process or the model performance when tested against those age groups with less data. To this end, we propose an age-controllable face synthesis technique using a feature decomposition to classify age from facial images which can be utilized to synthesize novel data to balance out the age distribution. We perform extensive qualitative and quantitative evaluation on our proposed technique using the FFHQ dataset and we show that our method has better performance than existing method.