• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.106-107
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• 2010

본 논문에서는 H.264/AVC의 부호화 효율을 향상 시킬 수 있는 방법을 제안하였다. 제안하는 알고리즘은 확장된 매크로 블록에서 향상된 인트라 예측 및 인터 예측 블록 혼합 코딩 방법을 사용한다. 그리고 인터 블록부터 먼저 부호화 및 복호화하여 인트라 예측 시 참조 픽셀로 사용하는 것을 제안한다. 기존의 인트라 예측 방법에서는 현재 블록의 우측 픽셀들과 하단에 위치한 픽셀들을 이용하지 못하기 때문에 예측 정확도가 높지 않았다. 따라서 본 논문에서는 현재 부호화하려는 블록의 상단과 좌측뿐만 아니라 우측 또는 하단의 복호화가 완료된 픽셀을 이용하여, 예측을 수행하는 확장된 인트라 예측 방법을 제안한다. 그리고 실험을 통하여 제안하는 방법이 기존 기술에 비해 효율적인 것을 보인다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.42-47
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• 2015

This paper presents a rank-based formation for multiple agents based on potential functions, where the proposed method uses the relative position of two neighboring agents. The conventional formation scheme of multiple systems requires communication between agents and a central computer to get the positions of all multiple agents. In the study, differently from previous studies, the formation scheme uses the relative position of two neighboring agents in a local coordinate system. In addition, it introduces a singular agent association that considers only the relative position between an agent and its neighboring agents, instead of multiple associations among all information about all agents. Furthermore, the proposed framework explores the benefits of different formation types. Extensive simulation results show that the proposed approach verifies the viability and effectiveness of the proposed formation.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.80-88
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• 2006

In Object-Oriented Paradigm, various cohesion measurements have been studied taking into account reference relation among components - like attributes and methods - that belong to a class. In addition, a number of methods have taken into research utilizing manual analysis, that is performed by developer's intuition and experience, and automatic analysis in refactoring field. The verification of objective criteria is demanded in order to process automatic refactoring. In this paper, we propose a method exploiting logistic regression and neural network for analysis of the relationship between six factors considering reference relation and method location among classes. Experimental results demonstrate that the logistic regression predicts the results up to 97% and the neural network predicts the outcomes up to 90%. Hence, we conclude that the logistic regression based method is more effective to predict the method location. Moreover, more than 90% of experimental results from both methods show that the six factors used in Move Method in refactoring are suitable to be used as an objective criteria.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.27-33
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• 2010

This paper applies Bayesian Markov inferred localization techniques for determining ZigBee mobile device's position. To evaluate its accuracy, we compare it with conventional technique, map-based localization. While the map-based localization technique referring to database of predefined locations and their RSSI data, the Bayesian Markov inferred localization is influenced by changes of time, direction and distance. All determinations are drawn from the estimation of Received Signal Strength (RSS) using ZigBee modules. Our results show the relationship between RSSI and distance in indoor ZigBee environment and higher localization accuracy of Bayesian Markov localization technique. We conclude that map-based localization is not suitable for flexible changes in indoors because of its predefined condition setup and lower accuracy comparing to distance-based Markov Chain inference localization system.

• Journal of the Korean association of regional geographers
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• v.23 no.2
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.88-96
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• 2021

In surface image velocimetry, a wide area of a river is photographed at an angle to measure its velocity, inevitably causing image distortion. Although a distorted image can be corrected into an orthogonal image by using 2D projective coordinate transformation and considering reference points on the same plane as the water surface, this method is limited by the uncertainty of changes in the water level in the event of a flood. Therefore, in this study, we developed a tilt image correction technique that corrects distortions in oblique images without resetting the reference points while coping with changes in the water level using the geometric relationship between the coordinates of the reference points set at a high position the camera, and the vertical distance between the water surface and the camera. Furthermore, we developed a distortion correction method to verify the corrected image, wherein we conducted a full-scale river experiment to verify the reference point transformation equation and measure the surface velocity. Based on the verification results, the proposed tilt image correction method was found to be over 97% accurate, whereas the experiment result of the surface velocity differed by approximately 4% as compared to the results calculated using the proposed method, thereby indicating high accuracy. Application of the proposed method to an image-based fixed automatic discharge measurement system can improve the accuracy of discharge measurement in the event of a flood when the water level changes rapidly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.245-248
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• 2011

현재의 영상 검색 시스템은 일반적으로 카테고리 검색 및 분류 검색으로 구성되어 있다. 일반적인 영상 데이터베이스 구축 및 현재의 검색 방법으로는 영상에 대한 재미요인을 분석하여 사용자에게 제공되지 않는다. 하지만 본 논문에서 제시하는 Q-방법론을 사용하여 영상을 분석하였다. Q-방법론에 의하여 분석된 영상은 영상 서버에 저장되며 영상 위치와 분석된 영상 디스크립션 및 재미요인은 데이터베이스에 구축하였다. 또한, 카테고리 검색 및 분류 검색에 대한 단점을 보강하기 위하여 키워드 검색시 색인 사전을 참조하여 온톨로지 검색에 대한 기능을 강화하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.93-96
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• 2014

본 논문에서는 가상시점 영상을 생성할 때 발생하는 홀 영역을 효율적으로 채우는 방법을 제안한다. 가상시점 영상을 생성하려면 우선 깊이 영상에 대해 3차원 워핑을 수행한 뒤, 이때 발생하는 작은 홀을 미디언 필터를 이용하여 적절히 채워야 한다. 홀이 채워진 깊이 영상을 기반으로 하여 입력받은 참조 컬러 영상에 대해 3차원 워핑을 수행하여 가상 위치에 새로운 시점 영상을 생성하게 된다. 이때 또한 마찬가지로 3차원 워핑을 수행하기 때문에 홀 영역이 발생하게 된다. 텍스쳐 영상을 워핑하여 새로운 좌표계로 옮긴 영상은 주변 컬러 화소들과의 관계들을 가지고 있다. 텍스쳐 영상을 워핑한 결과 영상에서 발생하는 홀 영역을 채우기 위해 방향성을 고려한 홀 채움 방법을 사용한다. 홀 주변 화소 영역의 값들을 홀을 채우게 될 후보 화소 값으로 설정한 뒤, 각각의 화소값에 대해 비용값을 계산한다. 이때 가장 적은 비용값을 갖게 하는 주변 화소 값을 해당 영역의 홀 채움 값으로 사용하게 된다. 좌영상과 우영상을 워핑할 때 발생하는 홀 영역의 위치가 각각 다르게 나타난다. 홀 영역은 배경화소 값을 이용해 채울 경우 자연스러운 결과를 보인다. 배경화소 값을 이용하기 위해 좌영상과 우영상에 따른 새로운 홀 스캔 방향 또한 제안한다. 능동적으로 홀 스캔 방향을 선택하여 홀 주변 화소값들을 스캔해가며 워핑 결과 발생하는 홀 영역을 효율적으로 채우게 된다. 결과적으로 제안한 방법을 통하여 생성된 가상시점 영상의 화질이 좋아지는 결과를 확인할 수 있었다.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.549-557
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• 2016

Consecutive missing values are likely to occur in long climate data due to system error or defective equipment. Furthermore, it is difficult to impute missing values. However, these complicated problems can be overcame by imputing missing values with reference time series. Reference time series must be composed of similar time series to time series that include missing values. We performed a simulation to compare three missing imputation methods (the adjusted normal ratio method, the regression method and the IDW method) to complete the missing values of time series. A comparison of the three missing imputation methods for the daily mean temperatures at 14 climatological stations indicated that the IDW method was better thanx others at south seaside stations. We also found the regression method was better than others at most stations (except south seaside stations).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.