[ 제2부 2주제 ] 최근 지입차주 겸 운전기사 판결의 비교를 통한 근로자 개념의 재검토

구건서 노동법이론실무학회 2013 정기학술대회 Vol.2013 No.10

지입차주 겸 운전기사 판결 비교를 통한 근로자 개념의 재검토 - 야구장모형 시론 -

구건서 노동법이론실무학회 2014 노동법포럼 Vol.- No.12

The drivers of owner-operators which owned by themselves have the double status of the owner-operator and the driver. They seem self-employee or employed worker depending on the concrete actual relation. Regarding these driver of owneroperators who have the double status, there exist wide variety of views from interpretation of the laws to legislative policy to consider them as employee workers would be protected by labor law admit to employee concept, or as own business operators would be applied general civil law. Some of drivers of owner-operators may stand in the equal or prominent position in relation to business transactions, but most of them might be in the weak position, possess one car purchased by installments or debt and sell their own labor for living. Therefore, in terms of social fairness, it is advisable to interpret positively whether driver of owner-operators is recognized as employee or not. Since there exist various forms of owner-operators, it is difficult to solve legal disputes by simple interpretation of the employee concept. As a result, need of separate legislation is raised for special types of employee workers as well as drivers of owner-operators. Current law in force regarding the employee concept have issues both in legislation or interpretation. From the point of legislation, Merkmale presented by definition of employee concept provision in the current positive laws (The Labor Standards Act Article 2-1, The Labor Union Act Article 2-1) is not consistent with the results considering the relevance of legal effect and meaning so that it is hard to be utilized for the judgement criteria of employee concept. In the view of interpretation, precedents of employee concept judged by tangible approach and listed the factual evidences parallel to check the relationship of employer-employee only, order relation or dominance relation can't be determined, with the results that legal stability is profoundly violated because of absence of predictability and high risk of court's intervention. Also, based on the judgement of the Supreme Court ruling "use dependency" strictly, criteria's meet more than 51% of employee and less than 49% of self-employment could be protected as employee worker, however, extremely relevant to criteria's meet 49% of employee and more than 51% of selfemployment has no protection. Supreme Court's interpretation by comprehensive judgement focused on "use dependency" excludes special type of employee workers stated in the middle of gray zone from the protection of the labor laws who are practically workers but formed in workers in special types of employment. Considering the given environment expanding diversity of means of working and type of utilizing labors, rather than dichotomous way of logic such as 'employee or employer' or 'all or nothing', solution should be found how to protect self-employee or self labor provider who looks like owner operator but actually provides own labor for compensation. Among them, many of underprivileged are living by selling their own labors. While labour supply in a variety of forms to determine by single frame named use dependency is difficult and using all of the approaches including the ontological approach, teleological approach and the positive law approach, to clarify the employee concept is probably impossible? Because technology and society are evolving rapidly, creating new forms of labor supply, and the increase of remote working and flexible working and of course with the help of smart devices instruction is not directed at their own processes autonomously, the type of smart work supply is widely spread. Even so, since the labor law is a last safety valve in capitalist society ensuring human life for people who take the lives by providing their labor, the employee concept to protect workers is somehow bound to define. Since employee concept is the entrance and exit of the labor law, interpretation and legislation should be faithfully di...

비디오 영상 정보 검색을 위한 문자 추출 및 인식

구건서 한국컴퓨터산업학회 2002 컴퓨터産業敎育學會論文誌 Vol.3 No.7

본 논문에서는 비디오에서 입력된 영상으로부터 내용기반 검색을 위해 자동으로 자막을 추출하여 특징 추출을 기반의 단층 연결 신경망 인식기(FE-MCBP)에 의해 자막 문자를 인식하여 영상 자막의 내용을 검출하는 방법을 제시하였다. 비디오에서 자막 추출은 먼저, 비디오에서 일정한 시간 간격으로 획득한 프레임 중에서 히스토그램 분석을 통하여 키 프레임을 찾는 과정을 수행하며, 그 다음에 각각의 키 프레임에 대하여 칼라 세그먼테이션 후 라인 검사 방법 통하여 자막 영역을 추출하도록 하였다. 마지막으로 추출된 자막영역에서 개별문자를 분리하였다. 본 연구에서는 칼라 히스토그램을 분석 후 지역 최대값을 이용하여 세그먼테이션 후 라인 검사를 수행함으로써 처리 속도와 자막영역 검출의 정확도를 개선하였다. 비디오에서 자막 추출은 비디오 정보를 멀티미디어 데이터베이스화하는 초기 단계로 추출된 자막은 바로 문자 인식기의 입력이 된다. 또한 인식된 자막정보는 데이터베이스로 구축되며 내용기반 검색 기법에 의해 검색되도록 하였다. In this paper, We propose an efficient automatic caption detection and location method, caption recognition using FE-MCBP(Feature Extraction based Multichained BackPropagation) neural network for content based retrieval of video. Frames are selected at fixed time interval from video and key frames are selected by gray scale histogram method. for each key frames, segmentation is performed and caption lines are detected using line scan method. lastly each characters are separated. This research improves speed and efficiency by color segmentation using local maximum analysis method before line scanning. Caption detection is a first stage of multimedia database organization and detected captions are used as input of text recognition system. Recognized captions can be searched by content based retrieval method.

저성과자 해고에 대한 정당성 판단 - 실적 부진자·근무태도 불량자·조직 부적응자를 중심으로 -

구건서 노동법이론실무학회 2011 정기학술대회 Vol.2011 No.2

타이어 코드 신경망 인식

구건서,오해석 한국지능시스템학회 1996 한국지능시스템학회 학술발표 논문집 Vol.6 No.1

기울어진 신규차량번호판 인식을 위한 FE-MCBP

구건서(Gun-Sea Koo) 한국컴퓨터정보학회 2007 韓國컴퓨터情報學會論文誌 Vol.12 No.5

본 논문은 문자의 특징을 추출하여 다중연결 인식기를 통해 신규 자동차 번호판을 인식하는 방법을 제안한다. 이를 위해 영상 전처리과정과 번호판 영역 추출을 위한 과정과 개별문자 추출 과정을 통해 얻어진 개별문자를 인식을 위해 FE-MCBP를 제안하였다. FE-MCBP는 차량 번호판처럼 한글과 숫자가 흔용된 문자열을 인식할 때는 문자의 특징을 기반으로 하는 인식기로서 기존 역전파 인식기에 비해 인식률 면에서 9.7%가 향상되었다. 아울러 기울어진 번호판 영상을 정규화하기 위하여 직선 성분 검출 및 영역 좌표 생성기술을 이용하였다. 시스템 운용 면에서 볼 때 신규차량번호판 인식 시스템은 번호판 영역이 기울진 영상도 인식이 가능하기 때문에 비스듬하게 획득된 번호판 영상이나, 훼손된 번호판의 경우도 인식이 가능한 것으로 연구결과 나타났다. This paper presents how to recognize the new-type vehicle license plate using multi-link recognizer after extract the features from characters. In order to assist this task, this paper proposed FE-MCBP to recognize each character that got through image preprocess, extract range of vehicle license plate and extract process of each character. FE-MCBP is the recognizer based on the features of the character. The recognizer is employed to identify the new-type vehicle licence plates which have both the hangul and the arabic numeral characters. And its recognition rate is improved 9.7 percent than the back propagation recognizer before. Also it makes use of extract of linear component and region coordinate generation technology to normalize a image of the tilted vehicle license plate. The recognition system of the new-type vehicle license plate make possible recognize a image of the tilted vehicle license plate when using this system. Also. this system can recognize the tilted or imperfect vehicle licence plates.

자동차 스키드마크 인식을 위한 FE-SM/SONN

구건서(Gun-Seo Koo) 한국컴퓨터정보학회 2012 韓國컴퓨터情報學會論文誌 Vol.17 No.1

본 논문은 차량이 급제동으로 인해 도로 위에 생성된 스키드마크와 같이 형태가 모호하게 나타난 영상을 인식하기 위해 FE-SM/SONN을 제안하였다. FE-SM/SONN은 타이어 트레드 패턴이 뭉개져서 나타나는 스키드마크 경우, 그 패턴이 모호한 영상으로 취득된다. 이를 인식하기 위해 퍼지 이론과 트레드 패턴의 특징을 이용한 자기 조직 신경망 인식기를 통해 스키드마크를 인식하는 방법이다. 이러한 실험을 위해 48개 타이어모델과 144개 스키드마크가 사용되었고, 전체 인식율은 89%이며, 비교 분석을 위해서는 기존 역전파 인식기에 비해 인식률 면에서 13.51%가 향상되었고, FE-MCBP에 비해 8.78% 향상을 보였다. 이 논문의 기대효과로는 모호한 영상의 특징을 추출하여 인식이 가능하였고, 트레드 패턴 영상이 그레이 영상으로 나타날 경우도 퍼지 이론에 의해 인식이 가능한 것으로 연구결과 나타났다. In this paper, We proposes FE-SM/SONN for recognizing blurred and smeared skid mark image caused by sudden braking of a vehicle. In a blurred and smeared skid marks, tread pattern image is ambiguous. To improve recognition of such image, FE-SM/SONN reads skid marks utilizing Fuzzy Logic and distinguishing tread pattern SONN(Self Organization Neural Networks) recognizer. In order to substantiate this finding, 48 tire models and 144 skid marks were compared and overall recognition ratio was 89%. This study showed 13.51% improved recognition compared to existing back propagation recognizer, and 8.78% improvement than FE-MCBP. The expected effect of this research is achieving recognition of ambiguous images by extracting distinguishing features, and the finding concludes that even when tread pattern image is in grey scale, Fuzzy Logic enables the tread pattern recognizable.

IPTV에서 컷 검색을 위한 색 분포정보를 이용한 FE-CBIRS

구건서(Gun-Seo Koo) 한국컴퓨터정보학회 2009 韓國컴퓨터情報學會論文誌 Vol.14 No.1

본 논문은 IPTV에서 방영되는 디지털 콘텐츠에서 검색하고자 하는 컷의 위치 정보를 검색하는데, 이때 색 분포에 관한 특징 정보를 이용한 FE-CBIRS을 제안한다. 기존 CBIRS에서는 색상과 모양에 대한 정보를 추출하여 이미지를 구분하는 특징정보로써 활용하며, 이미지를 세그멘테이션 처리하여 얻은 부분영역 특징정보를 전체 이미지의 특징정보와 함께 사용하여 검색하는 방법을 제시하였다. 또한 적용되는 색상 특징 정보의 경우 색상, 채도, 명도의 각각에 대한 평균, 표준편차, 왜도를 사용하며 부분영역을 특징정보로 적용하는 경우 대표색상만을 사용한다. 아울러 모양특징정보의 경우 추출된 부분영역들에 대한 불변 모멘트가 주요하게 사용된다. 이로 인한 처리시간의 문제, 정확성의 문제가 제기되어 왔다. 그러나 본 논문에서 제시하는 방법에서는 추출된 색상 특징정보들을 클래스별로 구분하여 인덱싱 하고 검색 시 비교대상 이미지를 해당 컷에 한정하여 적용하므로서 검색속도를 향상시키도록 하였다. This paper proposes novel FE-CBIRS that finds best position of a cut to be retrieved based on color feature distribution in digital contents of IPTV. Conventional CBIRS have used a method that utilizes both color and shape information together to classify images, as well as a method that utilizes both feature information of the entire region and feature information of a partial region that is extracted by segmentation for searching. Also, in the algorithm, average, standard deviation and skewness values are used in case of color features for each hue, saturation and intensity values respectively. Furthermore, in case of using partial regions, only a few major colors are used and in case of shape features, the invariant moment is mainly used on the extracted partial regions. Due to these reasons, some problems have been issued in CBIRS in processing time and accuracy so far. Therefore, in order to tackle these problems, this paper proposes the FE-CBIRS that makes searching speed faster by classifying and indexing the extracted color information by each class and by using several cuts that are restricted in range as comparative images.

빅데이터를 활용한 맞춤형 취업 전략에 관한 연구

구건서(Gun-Seo Koo) 한국컴퓨터정보학회 2015 韓國컴퓨터情報學會論文誌 Vol.20 No.1

본 논문은 취업하고자하는 학생의 빅데이터를 분석하여 최적의 취업 성공률을 높이기 위한 취업 전략 구축 방법을 제안한다. 특히 취업 방향을 잘 결정하지 못하여 취업률이 낮은 2년제 여자전문대학생을 대상으로 실험을 했으며, 기존 취업 전략의 중대한 문제점은 구직업체의 요구에 의해 학생들의 학교 성적 정보, 외모, 성격 등 단순한 정보만으로 구직에 참여하게 된다. 이로 인해 취업하려는 학생들의 만족도가 떨어지고, 취업 후 부적응 사례로 중도 직장을 포기하는 사태가 발생한다. 이런 문제를 해결하기 위해서 빅데이터 분석을 이용하여 취업 전략을 구축하고자 하는 것이다. 이를 증명하기 위해 전년 대비, 2014년 취업 통계 데이터로 증명했으며, 취업의뢰건도 전년 대비 21.3%가 상승했고, 기업과 학생간 취업 매칭률도 전년대비 81.4%증가 했다. 가장 중요한 최종 취업성공률도 전년 대비 63.1%가 증가한 것으로 나타났다. In this paper, we propose a analyses the big data of students who are willing to find employment and thus presents strategy for their higher success rate of employment. The experiment covered in this paper is based on female two-year community college students who are yet unsure about their future employment. The primary flaw of pervious employment strategy was job opportunity was only based on simple factors such as student"s grade, appearance, and personality due to employers and firms"s demand. Therefore, students were less satisfied and often resign. In order to prevent these failures, this paper plans a strategy by analyzing the big data. Furthermore, this is proven by the comparison between 2014 employment statistics and those of previous years, and employment request has been 21.3 percent increased along with 81.4 percent increase in match rate between firms and graduating students. Most importantly, the final success rate of employment presented 63.1 percent increase compared to the previous year.

MCBP망을 이용한 타이어 DOT 코드인식

구건서,오해석,강염임 崇實大學校 生産技術硏究所 1996 論文集 Vol.26 No.1

In this paper, the topic is the automatio of car's tire automatic classificatio through the recongnizing DOT code of the tire information code. For that, after it accepted car's tire stamp character through the imae processing, neural networks recognized this character data. In this paper, the case in large pattern come down learning time, to solve that problem, we have image optimum processing that after accept stamp cahracter through image processing device, process binary image to 7 x 8. This image recognize throgh MCBP networks that construct backpropagation networks. In here, instead of learining to 36 units of numeric '1∼9', alphabet 'A∼Z' units, we are learned them after divided three parts of numeric 10 units, alphabet 'A∼M', 'N∼Z'. Such being the case, it excels, it excels in recognize speed rather then do that. At this time, the data is that projects a stamp character on camera accepated easily and the first among image processing procedures. It solves naturally problem that the similarity problem like numeric '1', and alphabet 'I', or '2' and 'Z', and what is more has a good recognition rate.