• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.51-60
• /
• 2021

In this study, Based on the analysis of the correlation between internal control quality and earnings management, this article discusses the correlation between internal control quality and real activity earnings management and accrued earnings management. For this study, by introducing the concept, classification, measurement method and model of internal control and earnings management, the research hypothesis of this article was proposed. In this analysis, Use the relevant measurement model to calculate the actual activity earnings management level and accrued earnings management level of the enterprise, as the explained variable, establish a model for regression and were analyzed. Also, this study could find the final results draws a conclusion through empirical research: there is a significant negative correlation between the internal control quality of listed companies, real activity earnings management, and accrued earnings management. On the basis of this conclusion, the analysis of possible causes provides a basis for the development of internal control theory and the supervision and control of earnings management behavior in the future.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1153-1160
• /
• 2021

This paper proposes a routing algorithm that determines the optimal path using deep reinforcement learning in software-defined networks. The deep reinforcement learning model for learning is based on DQN, the inputs are the current network state, source, and destination nodes, and the output returns a list of routes from source to destination. The routing task is defined as a discrete control problem, and the quality of service parameters for routing consider delay, bandwidth, and loss rate. The routing agent classifies the appropriate service class according to the user's quality of service profile, and converts the service class that can be provided for each link from the current network state collected from the SDN. Based on this converted information, it learns to select a route that satisfies the required service level from the source to the destination. The simulation results indicated that if the proposed algorithm proceeds with a certain episode, the correct path is selected and the learning is successfully performed.

• The KIPS Transactions:PartD
• /
• v.12D no.4 s.100
• /
• pp.657-662
• /
• 2005

The Non-Sampling Error can happen any time by means of the intended or unintended error by the interviewer or respondent, but it is very difficult to find the error in survey database because it can hardly be computed mathematically and systematically. Until now, we have found it accidentally through the simple relation between the items or through the inspection from the random field. Therefore we introduced an heuristic methodology that can detect the interviewer's error by statistical decision-making or data mining techniques with a case study. It will be helpful so as to improve the statistical duality and provide efficient field management for the supervisor.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.79-86
• /
• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• The KIPS Transactions:PartD
• /
• v.16D no.3
• /
• pp.433-440
• /
• 2009

As information technology of constructional area develops recently, web-based on-line system is rapidly increasing to provide information on diverse constructional materials so as to enhance productivity of constructional business and to reduce cost. Since the constructional materials information provided by these systems, i.e., quality, specification, etc are not standardized, however, the staffs on the constructional site suffer considerable difficulties in using materials information when acquiring information on specific materials, e.g., using diverse information systems or repeating similar jobs. Thus, this research typified information items of constructional materials on the basis of GDAS and designed multi system model to control integrated information on constructional materials. This system can efficiently control and utilize materials information by supporting automatic classification of constructional materials to which OmniClass Part-22 and UNSPSC are applied, conditional complex retrieval of materials information, real-time automatic embodiment of electronic catalog and retrieving/controlling RFID.

• Journal of Korea Multimedia Society
• /
• v.3 no.2
• /
• pp.112-120
• /
• 2000

In this paper, we implement a real-time textile dimension inspection system. It can detect various types of real defects which determine the quality of fabric product, defect positions of textile, classify the distortion angel of moving textile and the density. In the implemented system, we measure the density of textile using zone-crossing method with optical lens to solve the noise and real-time problems. And we compensate distortion angel of textile with the classification of distortion types using gaussian gradient and mean gradient features. And also, it detecs real defects of textile and its positions using gray level co-occurrence matrix features. The implemented texile demension inspection systemcan inspect textile dimensions such as density, distortion angle, defect of textile and defect position at real-time. In the implemented proposed texitile dimension inspection system, It is possible to calculate density and detect default of textile at real-time dimension inspection system, it is possible to calculate density and detect default of textile at textile states throughout at all the significant working process such as dyeing, manufacturing, and other texitle processing.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.133-133
• /
• 2019

하천의 하상재료는 전반적인 하천 계획 및 정비 등의 기초자료이다. 특히 하천의 하상재료 조사는 하천의 조도계수 산정, 하천의 유사이송 특성 분석 및 하천 서식처 등의 하천환경 조사를 위하여 수행한다. 지금까지의 하천 하상재료 조사는 사람이 직접 하상토를 채취하거나 사진을 이용하여 대략적인 스케치를 통해 진행하다보니 자료의 품질에 대한 신뢰도가 떨어지고, 사람이 직접조사를 해야 하기 때문에 비용이 많이 필요하여 몇 개 지점을 대상으로 하상재료 조사를 수행해야 하는 등의 한계를 가지고 있다. 따라서 하천 환경 평가를 위한 하상재료 조사를 위해서는 좀 더 체계적이고 과학적인 기술 개발이 요구된다. 특히 물속의 하천 하상재료를 조사하는 것은 육안 또는 카메라를 이용한 조사로는 어려움이 많기 때문에 하천 전체의 공간적인 하상재료 조사를 위해서는 새로운 기술이 필요하다. 이에 본 연구에서는 보다 정확한 조도계수 산정을 위해 초분광 영상을 이용하여 하상재료를 분류하고, 이를 이용하여 하천 환경 평가를 할 수 있는 하상재료 분포도를 만들기 위한 하상재료의 분광특성 분석 연구를 수행하였다. 초분광 영상의 분광특성은 수백개의 밴드가 연속적으로 구성된 정보를 말하며, 영상 내 모든 화소의 파장정보를 포함하는 데이터 큐브형식으로 구성된다. 물체의 파장정보는 분광기나 초분광 영상 촬영 장치를 통해 수집할 수 있으며 파장정보는 파장과 이에 해당하는 영역의 반사도를 측정하여 하상재료의 분광반사특성으로 확인할 수 있다. 따라서 본 연구에서는 하천의 다양한 하상재료들만의 고유 분광반사특성을 분석하여 하상재료별 분광 라이브러리를 구축하고자 한다. 또한 이와 같이 하상재료별 분광 라이브러리를 구축한 결과를 활용하여 무인기 기반의 초분광 영상을 활용한 하천 하상재료 분류 기술을 개발하고자 한다. 이를 위해 본 연구에서는 하상재료별 분광라이브러리를 구축하였고, 실제 하천에서 무인기 초분광 영상에 활용한 결과 수체가 존재하는 영역에서도 초분광 영상을 활용하여 하상재료의 분류가 가능한 것을 확인하였다.

• Journal of Korean Society of Archives and Records Management
• /
• v.23 no.1
• /
• pp.101-126
• /
• 2023

Photographic archives of universities are one of the most valuable types of records that establish the university's identity and provide historical evidence. Unlike text records, however, they are weak in conveying meanings. Therefore, it is difficult to support users' search and utilization unless the information of photo records is comprehensively described. In this study, for the university photo archives, we tried to structure the classification system of photo archives and develop a metadata set that reflects the category characteristics in the classification. To this end, the photo archives classification system and metadata elements of domestic and American university archives were analyzed and based on this, the model of information structure was proposed. The information structure model presented in this study can help university archives improve the data quality of their photo archives and support users with the abundant discovery of photo archives.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.423-423
• /
• 2023

습지 생태계는 탄소저장고, 대기 온·습도 조절 등의 기능을 수행하는 만큼 면밀한 관리가 요구된다. 습지의 규모와 생태계는 밀접한 연관성을 가지므로 그 규모를 우선적으로 파악할 필요가 있으며, 이를 위해 지표면의 상태를 산지, 습지, 수역 등의 항목으로 구분한 토지피복지도가 고려될 수 있다. 현재, 환경부에서 운영 중인 환경공간정보서비스(https://egis.me.go.kr/)에서는 각각 30 m, 5 m, 1 m의 공간 해상도와 7, 22, 41가지 분류 항목을 갖는 대분류, 중분류, 세분류로 구분된 토지피복지도를 제공하며 이러한 자료들은 모두 1년 이상의 시간 해상도를 갖는다. 습지의 경우, 계절에 따른 환경 변화로 인한 규모의 변동성이 크게 나타날 수 있기 때문에 1년 이하의 시간 해상도를 갖는 고품질 토지피복 분류 정보가 요구된다. 따라서 본 연구에서는 기존 자료의 낮은 시간 해상도 보완을 목표로, 1개월과 30 m의 시·공간 해상도를 갖는 토지피복지도를 구축하기 위한 방법론을 제안하고자 한다. 이를 위해 Landsat-8 등과 같은 다양한 인공위성 자료를 수집하고, Support Vector Machine 등과 같은 머신러닝 기법을 적용하였다. 최종적으로 습지보전법에서 지정한 습지보호지역 중 내륙습지 26개소를 대상으로, 본 연구로부터 산출된 토지피복지도를 기존 환경공간정보서비스 내 대분류 토지피복지도와 비교·평가하였다.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.7
• /
• pp.285-294
• /
• 2023

As software grows continuously in scale and complexity, the role of software architecture has become increasingly important across various industries. Although software architects often rely on their experience and intuition when designing such architecture, there is a variety of methodologies being researched for architecture design. However, these methodologies do not address the specific effects of applying multiple architectural patterns to a system or the sequence in which they should be applied. In this study, we explain the variation in architectural design results depending on the order in which the same set of architectural patterns is applied to a single system. Based on this phenomenon, we identify requirements for applying architectural patterns and propose a method of classifying the patterns to be applied. We also propose a prioritization process for requirements to efficiently apply the classified patterns in a specific order. Finally, we show a case study that prioritizing requirements based on architectural pattern types is beneficial for efficient software architecture design in terms of quality attributes.