• Journal of IKEEE
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• v.22 no.1
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• pp.46-52
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• 2018

The problem of traffic light detection and recognition has recently become one of the most important topics in various researches on autonomous driving. Most algorithms are based on colors to detect and recognize traffic light signals. These methods have disadvantage in that the recognition rate is lowered due to the change of the color of the traffic light, the influence of the angle, distance, and surrounding illumination environment of the image. In this paper, we propose machine learning based detection and recognition algorithm using shape information to solve these problems. Unlike the existing algorithms, the proposed algorithm detects and recognizes the traffic signals based on the morphological characteristics of the traffic lights, which is advantageous in that it is robust against the influence from the surrounding environments. Experimental results show that the recognition rate of the signal is higher than those of other color-based algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1295-1303
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• 2010

In this paper, an effective method has been proposed for selection of white Gaussian noise(WGN) band for radio background noise measurement system under broad band noise environment. MMN which comes from industrial devices and equipment mostly happens in the shape of broad band noise mostly like impulsive noise and this is the main reason for increasing level in the present radio noise measurements. The existing method based on singular value decomposition has weak point that it cannot give good performance for the broad band signal because it uses signal's white property. The proposed method overcomes such a weakness of singular value decomposition based method by using signal's Gaussian property based method in parallel. Moreover, this proposed method hires a modelling based method which uses parameter estimation algorithm like maximum likelihood estimation(MLE) and gives more accurate result than the method using amplitude probability distribution(APD) graph. Experiment results under the natural environment has done to verify feasibility of the proposed method.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.210.2-210.2
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• 2013

현재 국내의 상용화된 디지털 방식 X-선 영상장치에서 간접변환방식은 대부분 CsI를 사용하고 있으며, X-선 흡수에 의해 전기적 신호를 발생시키는 직접변환방식은 Amorphous Selenium(a-Se)을 사용한다. a-Se은 진공 중에 녹는점이 낮아 증착시 substrate의 온도에 따라 민감한 변화를 보인다. 본 연구에서는 간접변환방식에 비해 높은 영상의 질을 획득할 수 있는 직접변환방식의 a-Se기반 X-선 검출기 제작 시 substrate에 인가된 온도에 따른 특성을 연구하여 최적화 된 substrate의 온도를 알고자 한다. 본 실험에서는 glass에 투명한 전극물질인 Indium Tin Oxide (ITO)가 electrode로 형성된 substrate를 사용하였으며 그 상단에 a-Se을 Physical Vapor Deposition (PVD)방식을 거쳐 X-선 검출기 샘플을 제작하였다. PVD 공정 시 네 개의 보트에 a-Se 시료를 각각 100g씩 총 400g을 넣고, $5{\times}10-5Torr$까지 진공도를 낮추었다. 보트의 온도는 $270^{\circ}C$에서 40분 $290^{\circ}C$에서 90분으로 온도를 인가하여 a-Se을 기화시켜 증착하였다. 증착 시 substrate 온도를 각각 $20^{\circ}C$, $40^{\circ}C$, $60^{\circ}C$, $70^{\circ}C$ 네 종류로 나누어 실험을 진행하였다. 끝으로 증착된 a-Se 상단에 Au를 PVD방식으로 electrode를 형성시켜 a-Se기반의 X-선 검출기 샘플 제작을 완료하였다. 제작된 a-Se기반의 X-선 검출기 샘플의 두께는 80에서 $85{\mu}m$로 온도에 따른 차이가 없었다. 이후에 전기적 특성을 평가하기위해 electrometer와 oscilloscope를 이용하여 Dark current와 Sensitivity를 측정하여 Signal to Noise Ratio(SNR)로 도출하였으며 Scanning Electron Microscope(SEM) 표면 uniformity를 관찰하였다. 또한 제작된 a-Se기반 X-선 검출기 샘플의 hole collection 성능을 확인하고자 mobility를 측정하였다. 측정결과 a-Se의 work function을 고려한 $10V/{\mu}m$기준에서 70kV, 100mA, 0.03sec의 조건의 X-선을 조사 하였을 때 Sensitivity는 세 종류의 검출기 샘플이 15nC/mR-cm2에서 18nC/mR-cm2으로 비슷한 양상을 나타내었지만, substrate온도가 $70^{\circ}C$때의 샘플은 10nC/mR-cm2이하로 저감됨을 알 수 있었다. 그리고 substrate온도 $60^{\circ}C$에서 제작된 검출기 샘플의 전기적 특성이 SNR로 환산 시, 15.812로 가장 우수한 전기적 특성을 나타내어 최적화 된 온도임을 알 수 있었다. SEM촬영 시 온도상승에 따라 표면 uniformity가 우수하였으며, Mobility lifetime에서는 $60^{\circ}C$에서 제작된 검출기 샘플이 deep trap 수치가 높아 hole이 $0.04584cm2/V{\cdot}sec$로 $0.00174cm2/V{\cdot}sec$의 electron보다 26.34배가량 빠른 것을 확인하였다. 본 연구를 통해 a-Se증착 시, substrate에 인가된 온도는 균일한 박막의 형성 및 표면구조에 영향을 미치며 온도가 증가할수록 안정적인 전기적 특성을 나타내지만 $70^{\circ}C$이상일 시, a-Se층의 결정화가 생겨 deep trap을 발생시켜 전기적 특성이 저하됨을 확인 할 수 있었다. 따라서 증착 시의 substrate의 온도 최적화는 a-Se기반 X-선 검출기의 안전성 및 성능향상을 위해 불가피한 요소가 된다고 사료된다.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.85-92
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• 2008

Meshes are the most appropriate data structures for representing 3D geometries. Surface meshes have been frequently used for representing 3D geometries, which only samples data on the surfaces of the given 3D geometries. Thanks to the improvements of computing powers, it is required to develop more complicated contents which utilize the volumetric information of 3D geometries. In this paper, we introduce a novel volumetric mesh libraries based on the half-face data structure, called OpenVolMesh, and describe its designs and implementations. The OpenVolMesh extends the OpenMesh, which is one of the most famous mesh libraries, by supporting volumetric meshes. The OpenVolMesh provides the generic programming, dynamic allocations of primitive properties, efficient array-based data structures, and source-level compatibility with OpenMesh. We show the usefulness of the OpenVolMesh in the developments of 3D volumetric contents with prototypic implementations such as volumetric mesh smoothing and CW-cell decompositions.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• Journal of the Korean School Mathematics Society
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• v.11 no.3
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• pp.439-466
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• 2008

In this paper, we aim to draw up an alternative instruction scheme by designing a web based instruction model on mathematics. Some learning materials are developed according to the scheme, and its educational effects are examined when it is committed to through regular curriculum. The study is composed of three major parts; setting of the theoretical foundation on cultivating Web based educational materials, design and composition of Web based teaching-learning model, and its experiments in the regular class. First of all, we are concerned with the core principles on WBI including the learning theories, developing learner oriented instruction model, design as well as build-up process for education materials, and strategy in instruction. Next, we propose an alternative instruction model for mathematics, in which programs to embody mathematics education and instruction on the Web are constructed, on the while, the study is proceeded through the Web Site. Finally, we design and produce a WBI instruction model on the subject of the plane quadratic curves. This model is examined in the regular class to estimate its educational effects compared with traditional teaching standpoints. Concomitantly, we explore essential elements and the direction of future growth associated with the Web oriented education.

• Convergence Security Journal
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• v.19 no.1
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• pp.67-78
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• 2019

Most existing facial expression recognition methods use a uniform grid method that divides the entire facial image into uniform blocks when describing facial features. The problem of this method may include non-face backgrounds, which interferes with discrimination of facial expressions, and the feature of a face included in each block may vary depending on the position, size, and orientation of the face in the input image. In this paper, we propose a variable-size block method which determines the size and position of a block that best represents meaningful facial expression change. As a part of the effort, we propose the way to determine the optimal number, position and size of each block based on the facial feature points. For the evaluation of the proposed method, we generate the facial feature vectors using LDTP and construct a facial expression recognition system based on SVM. Experimental results show that the proposed method is superior to conventional uniform grid based method. Especially, it shows that the proposed method can adapt to the change of the input environment more effectively by showing relatively better performance than exiting methods in the images with large shape and orientation changes.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.578-589
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• 2014

Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

• Proceedings of the Population Association of Korea Conference
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• 2006.12a
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• pp.113-128
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• 2006

The main theme of this paper was to investigate the role of education as a source of economic growth in Korea. In this study, first, the objective mode was built by extending neoclassical Solow growth theory. Second, the capital deepening typical of an endogenous economic per-capita growth model was developed empirically for seven East-Asian economies as for the medium term, during $1975{\sim}2004$. And then we found the meaning of coefficients of growth factors, direct relative contribution of each input to per-capita growth in seven East-Asian countries, relative indirect contribution of education to per-capita growth in Korea, accounting for difference due to accumulation in Korea. The indirect relative contributions of secondary and higher education and R&D to per-capita growth change the results somewhat. Secondary education is still the largest single contributor 83.6 percent of predicted growth is due to secondary school enrollment in Korea. Primary education comes second with 37.5 percent and followed by higher education at -52.9 percent. Physical investment gives 62.3 percent and unimproved raw labor contributes only -1.4 percent.