• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.785-799
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• 2017

One of the most widely used image media in recent years, omni-directional panorama images are attracting much attention. Since this image is ultra-high value-added, the intellectual property of this image must be protected. In this paper, we propose a blind digital watermarking method for this image. In this paper, we assume that the owner of each original image may be different, insert different watermark data into each original image, and extract the watermark from the projected image, which is a form of service of omni- directional panorama image. Therefore, the main target attack in this paper is the image distortion which occurs in the process of the omni- directional panorama image. In this method, SIFT feature points of non-stitched areas are used, and watermark data is inserted into data around each feature point. We propose two methods of using two-dimensional DWT coefficients and spatial domain data as data for inserting watermark. Both methods insert watermark data by QIM method. Through experiments, these two methods show robustness against the distortion generated in the panorama image generation process, and additionally show sufficient robustness against JPEG compression attack.

• Proceedings of the CALSEC Conference
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• 1999.11a
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• pp.529-534
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• 1999

전자상거래는 구매자와 판매자 모두에게 많은 이점을 제공할 수 있어 최근 이에 관한 연구들이 많이 진행되고 있다. 특히 중소제조업체의 경우, 전자상거래라는 경영환경의 변화는 새로운 기회로 다가오고 있어, 상대적으로 기술력이 취약한 중소제조업체의 전자상거래를 지원하기 위한 요소 기술들의 개발 필요성이 점차 부각되고 있다. 이에 본 연구에서는 중소 금형제조업체의 판매과정을 사이버 공간에서 수행할 수 있는 전자상거래 기술을 개발하였다. 일반적으로 변화하는 경영환경에서는 생산과 관련된 계획과 통제가 보다 더 신속하고 정확하게 이루어져야 한다. 즉 전자상거래 환경에서의 제조업체는 구매자가 요구한 제품의 생산과 납기일을 맞추어 줄 수 있는지의 여부를 실시간으로 응답할 수 있어야 한다. 나아가서 인터넷을 통해 접수된 주문들은 해당 제조업체의 생산능력을 초과할 수 있는데 이 때에는 접수된 주문들 중에서 자사의 이익을 극대화할 수 있는 주문집합을 선별하여 접수여부를 결정해야 한다. 이와 같이 전자상거래 환경하에서의 제조업체는 생산과 관련된 정보를 신속하게 전달 받아 주문접수여부에 관한 의사결정을 올바르게 수행하는 것이 중요한데 본 연구에서는 중소 금형제조업체의 일정계획 및 주문처리를 위한 일정계획 기반의 선정 에이전트의 구조와 방법론을 제시하였다. 지금까지 일정계획에 관한 연구들은 대부분 납기일의 만족과 비용의 최소화 측면을 위주로 다루었다. 그러나 본 연구에서의 문제는 비용의 최소화보다는 납기일을 준수하면서 가장 많은 이익을 가져다 줄 수 있는 최적주문집합을 선정하는 문제를 다루고있다.자료를 수집하고, 통계분석 패키지를 이용하여 자료를 분석하였다. 방식을 결합한 하이브리드 형태이다.인터넷으로 주문처리하고, 신속 안전한 배달을 기대한다. 더불어 고객은 현재 자신의 물건이 배달되는 경로를 알고싶어 한다. 웹을 통해 물건을 주문한 고객이 자신이 물건의 배달 상황을 웹에서 모니터링 한다면 기업은 고객으로 공간적인 제약으로 인한 불신을 불식시키는 신뢰감을 주게 된다. 이러한 고객서비스 향상과 물류비용 절감은 사이버 쇼핑몰이 전국 어디서나 우리의 안방에서 자연스럽게 점할 수 있는 상황을 만들 것이다.SP가 도입되어, 설계업무를 지원하기위한 기본적인 시스템 구조를 구상하게 된다. 이와 함께 IT Model을 구성하게 되는데, 객체지향적 접근 방법으로 Model을 생성하고 UML(Unified Modeling Language)을 Tool로 사용한다. 단계 4)는 Software Engineering 관점으로 접근한다. 이는 최종산물이라고 볼 수 있는 설계업무 지원 시스템을 Design하는 과정으로, 시스템에 사용될 데이터를 Design하는 과정과, 데이터를 기반으로 한 기능을 Design하는 과정으로 나눈다. 이를 통해 생성된 Model에 따라 최종적으로 Coding을 통하여 실제 시스템을 구축하게 된다.the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and b

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2003.11a
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• pp.75-78
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• 2003

MPEG-4 표준은 저작자가 정지영상, 텍스트, 2D/3D 그래픽스, 오디오, 심지어 임의형의 비디오 등과 같이 다양한 형태의 객체들을 개별적으로 구성하고 이들을 시/공간자적으로 다루기 용이하게 해 준다. 이와 같은 객체 기반 코딩 특성에 의해서 대화형 방송 콘텐츠를 제작하는데 가장 유용한 방식으로 고려할 수 있다. 피러나, 콘텐츠의 제작, 전송, 소비 관전에서 고려해 달 때, 콘텐츠 제작자 또는 저작권자의 보호 및 관리가 필요하게 되었다. 이에 따라 최근에는 OPIMA (Open Platform Initiative for Multimedia Access), SDMI (Secure Digital Music Initiative) and MPEG(Moving Picture Expert Group) OPIMATfMr(Intellectual Property Management & Protection)와 같은 국제 표준 단체들이 콘텐츠 보호 및 관리에 대한 관심을 가지게 되었다. 특히, MPEG의 경우에 MPEG-4 IPMP를 표준화하여 디지털 콘텐츠와 저작권에 대한 보호를 체계적이고 효과적으로 다루는 연구를 가장 활발히 해오고 있다. 이 논문에서 우리는 MPEG-4 콘텐츠 저작자가 MPEG-4 규격에 맞게 보호화 된 객체 기반 방송용 콘텐츠를 쉽고 편리하게 제작학 수 있도록 하기 위한 MPEG씨 콘텐츠 및 저자권 보호를 위한 MPEG-4 IPMP 저작 도구를 제안하고자 한다. 제안한 MPEG-4 콘텐츠 및 저작권 보호 저작 도구는 저작자에게 친근한 사용자 인터페이스를 제공하여 편집 및 수정이 용이한 텍스트 포맷인 IPMP회된 XMT(extensible Mpeg-4 Textual format) 파일을 생성한다. 또한, 콘텐츠 전송 및 저장의 효율성을 위해 이진 포멧인 IPMP화된 MP4 파일을 생성할 수 있다.으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.우 $23.87\%$($18.00\~30.91\%$), 갑폭 $23.99\%$($17.82\~30.48\%$), 체중 $91.51\%$($58.86\~129.14\%$)이였으며 성장율은 사육 온도구간별 차는 없었다.20 km 까지의 지점들(지점 2에서 지점 6)에서 매우 높은 값을 보이며 이는 조석작용으로 해수와 담수가 강제혼합되면서 표층퇴적물이 재부유하기 때문이라고 판단된다. 영양염류는 월별로 다소의 차이는 있으나, 대체적으로 지점 1과 2에서 가장 낮고, 상류로 갈수록 점차 증가하며 지점 7 상류역이 하류역에 비해 높은 농도이다. 월별로는 7월에 규산염, 용존무기태질소 및 암모니아의 농도가 가장 높은 반면에 용존산소포화도는 가장 낮다. 그러나 지점 14 상류역에서는 5월에 측정한 용존무기태질소, 암모니아, 인산염 및 COD 값이 7월보다 다소 높거나 비슷하다. 한편 영양염류와 COD값은 대체적으로 8월에 가장 낮으나 용존산소포화도는 가장 높다.출조건은 $100^{\circ}C$에서 1분간의 고온단시간 추출이 적합하였다. 증가를 나타내었는데, 저장기간에 따른 물성의 변화는 숭어에 비하여 붕장어가 적었다.양식산은 aspartic acid 및 proline이 많았다. 또한 잉어는 천연산이

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.13-23
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• 2023

Unlike building construction projects, where the activity is repeatedly carried out in a limited area, civil engineering projects such as roads and railroads are carried out in a linear type in a horizontal working space over several tens of kilometers. Each activity is managed with a station number that has a unit of distance from the starting point to the end point. For this reason, since the work location information of the activity is a major management factor, the Gantt chart system that expresses only schedule information may have limitations. In this study, authors propose a method for constructing a linear schedule chart that can simultaneously express schedule information indicating the start and finish dates and location information indicating the start and end positions of each activity, and develop a system for generating a linear schedule chart. In the study, the coordinate axes of the linear schedule chart consisted of distance and date values on the X and Y axes, respectively, and each activity was expressed as a symbol that can infer the type of work to increase the visibility of the linear schedule chart compared to the simple bar chart method. The linear schedule chart generation system was reviewed for practical applicability by utilizing the actual schedule data of bridge structures in a railroad project.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.303-314
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• 2023

Voice conversion, a technology that allows an individual's speech data to be regenerated with the acoustic properties(tone, cadence, gender) of another, has countless applications in education, communication, and entertainment. This paper proposes an approach based on the StarGAN-VC model that generates realistic-sounding speech without requiring parallel utterances. To overcome the constraints of the existing StarGAN-VC model that utilizes one-hot vectors of original and target speaker information, this paper extracts feature vectors of target speakers using a pre-trained version of Rawnet3. This results in a latent space where voice conversion can be performed without direct speaker-to-speaker mappings, enabling an any-to-any structure. In addition to the loss terms used in the original StarGAN-VC model, Wasserstein distance is used as a loss term to ensure that generated voice segments match the acoustic properties of the target voice. Two Time-Scale Update Rule (TTUR) is also used to facilitate stable training. Experimental results show that the proposed method outperforms previous methods, including the StarGAN-VC network on which it was based.

• Journal of Gifted/Talented Education
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• v.21 no.3
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• pp.595-610
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• 2011

It is hard to understand the coexistence of giftedness and disorder in an individual, but the twice-exceptional is widely recognized now. Gifted autistic spectrum disorder is one of its subtypes in which giftedness exists with autistic spectrum disorder (ASD) simultaneously. Like other constructs including giftedness, the nature of gifted ASD has not been understood in a fundamental and wholistic manner. This paper suggests a cognitive mechanism of gifted ASD based on the integrated model of human abilities(Song, 2009; Song & Porath, 2005), which explains how giftedness coexists with ASD and interacts with each other, producing the characteristics of gifted individuals with ASD. According to the suggested mechanism, the excessive growth of mental spaces in the brain may cause ASD. The over-grown mental spaces result in excessively strong short-term sensory memory and better facility of processing, promoting internal cognitive activities on one hand, but relative lack of cognitive activities in the real world space results in ASD symptoms on the other hand. The cognitive structure of gifted ASD students also contributes to the presentation of giftedness in specific domains. This study suggests that gifted individuals with ASD need to be discouraged from fully engaging in domains they are interested in or the most confident of, rather to be encouraged to invest their giftedness to overcome their ASD symptoms. This study also provides new perspectives on theoretical and educational approaches for gifted ASD.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.53-62
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• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.39-51
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• 2021

Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.