사용자가 제기한 부당해고 재심판정취소소송중에 원직이 소멸한 경우의 법원의 처리

정진경(鄭鎭京) 서울대학교 노동법연구회 2013 노동법연구 Vol.0 No.35

행정처분의 취소소송에 있어서 판단의 기준시에 관하여는 처분시설과 구두변론종결시설이 대립하고 있는바 우리나라의 통설과 판례는 처분시설을 따르고 있다. 그런데 노동위원회의 명령이나 결정에 대한 취소소송에 있어서는 그 위법판단의 기준시점의 문제는 구제의 필요성과 관련된 것이다. 처분시설을 취한다고해도 구제명령의 발령 후에 구두변론종결시까지 명령의 이행이나 집행을 불능케하는 사정이 발생한 경우에는 취소소송의 판단에 있어 이를 고려할 필요가 있다. 이러한 경우 우리 법원은 사실심 변론종결 당시를 기준으로 하여 원칙적으로 원고인 사용자에게 명령의 취소를 구할 법률상의 이익을 결여하여 소의 이익이 없다고 판단하고 있다. 하지만, 원직복직 등을 명한 재심판정과 관련하여 사용자가 항소한 경우 원직의 소멸로 원직복직 명령이 이행 불가능하게 되었을 때 그 취소를 구할 소의 이익이 없다고 하는 판단은 이행강제금 제도 등이 신설된 현재에 있어서는 부적절하다. 소를 각하하는 경우 원직이 소멸하였음에도 원직복직을 명하는 재심판정은 그대로 남아 있어 원고는 이행강제금 부과 등의 불이익을 당할 위험이 계속하여 존속하기 때문이다. 결국 부당해고 구제신청과 관련한 노동위원회의 결정은 그것이 순수한 행정처분이라기보다는 사용자와 근로자 사이의 부당해고와 관련한 분쟁에 있어서의 준사법적 판단이라는 점을 고려하여, 재심판정이 존속함으로써 사용자와 근로자사이의 분쟁이 종결될 수 없는 특별한 경우에는 위법성의 판단시점을 구두변론 종결시점으로 하는 방법을 검토할 필요가 있다. About the base point of judgment in respect to revocation litigation of administrative disposition, conflict exists between the ‘disposition point theory’ and the ‘closing oral argument point theory’. Commonly accepted theory and judicial precedents of Korea are in line with the ‘disposition point theory’. In case of revocation litigation against orders and decisions of labor committee, the base point of illegality decision is associated with the necessity for relief. Even if the ‘disposition point theory’ is taken, there is a need to consider the circumstances that make compliance and execution of order impossible up to the closing oral argument point after the issuance of relief order. In this case, our courts have decided that employers, plaintiffs, are lack of right protection interest because they have no legal interest to obtain the revocation of order, in principle, considering the time of closing oral argument as a base point. If employers appeal adjudications related to reinstatement order, however, the judgment that there is no interest of right protection to obtain the revocation is inadequate when the execution of reinstatement order become unenforceable because of disappearance of original job at this time charge for compelling the performance has been newly established. The rejection of lawsuit might cause danger of disadvantage like the charge for compelling the performance to plaintiff because of the existence of retrial adjudication ordering the reinstatement even after the original job has been disappeared. Labor committee decisions related to relief application of unfair dismissal are quasi-judicial adjudications in the dispute of unfair dismissal between employer and employee, rather than pure administrative dispositions. Therefore, it is needed to consider some method to make closing oral argument point as a base point for illegality decisions in some special cases that existence of retrial judgment prevents the end of dispute between employer and employee.

수퍼포인트-고해상도신경망; HRNet을 이용한 관심점 검출방법

김동성(Dongsung Kim) Korean Institute of Information Scientists and Eng 2021 정보과학회논문지 Vol.48 No.2

Interest point detector is a fundamental method in computer vision for image matching and image recognition. SIFT, ORB, etc. have been used in many computer vision applications. As acquiring ground truth of interest points is difficult, SuperPoint has been devised to make pseudo ground truth using synthetic corners in training the model. The SuperPoint produced competitive performance to leading conventional computer vision interest point detectors. This paper proposes SuperPoint-High Resolution Network (HRN) to improve repeatability that is one of the most important features in an interest point detector by substituting HRN exchanging information among different resolution activation maps for the shared encoder implemented with a convolutional neural network and by modifying the detector head to accommodate high-resolution activation maps. The proposed method demonstrated immense improvements in HPatches data over the SuperPoint in terms of repeatability and localization errors of interest points.

Tracking Humans Based on Interest Point over Span-Space in Multifarious Situations

Mohammad Alamgir Hossain,Goutam Sanyal 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.9

Tracking humans in complex surroundings is a very vital, exciting and red-hot topic since last few decades. There are lots of opinions and approaches proposed and developed by different researchers to prove that their methodology is comparatively superior to others. Human activity can be tracked based on the appropriate motion of human being. This motion is segregated into two categories as global motion and limb motion. We assumed that human may carry something with him or her. However, to apply our method everything is considered as object in our proposed model. The objects are being tracked, segmented and subsequently are being classified. The global-parts of this human motion approach (HMA) are being tracked by using ellipsoid shape of human models. However, based on the tracked object we tried to establish the performance of matching and recognition of human object methods (HOM). Here we have considered interest-points as a tracking parameter of the associated image descriptor. The interest-points measured in scale based on the shape of span-space of tracked-image-object (TIO) and they should fall into one of the category (global motion or limb motion). In this paper we propose the way to detect and identify interest-points by using generalized detectors. Subsequently we shall build sparse-matrix set of interest-points to compute image descriptors for human-image-matching (HIM). To detect the scale of interest-points based on span-space; however, we have used sophisticated statistical and mathematical approaches so that we can get more accurate experimental results. Our experimental results show that it is successfully applied in case of small number of people moving together accompanied by occlusion and shadow or reflection effect. However we have also tried to implement the different modes of human activity (e.g., standing, playing, talking, walking, running, etc.). There are some constraints for model of camera and the assumptions required for geometric shape of ground plane. Robust results show the superiority of our applied methodology.

Image Retrieval Method Based on IPDSH and SRIP

( Xu Zhang ),( Baolong Guo ),( Yunyi Yan ),( Wei Sun ),( Meng Yi ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5

At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users` interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points` neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

A Matching Strategy to Recognize Occluded Number

최형일(Hyung-Il Choi),김계영(Gye-Young Kim),Thi Thuong Pham 한국컴퓨터정보학회 2011 한국컴퓨터정보학회 학술발표논문집 Vol.19 No.1

This paper proposes a method of occluded number recognition by matching interest points. Interest points of input pattern are found via SURF features extracting and matched to interest points of clusters in database following three steps: SURF matching, coordinate matching and SURF matching on coordinate matched points. Then the satisfied interest points are counted to compute matching rate of each cluster. The input pattern will be assigned to cluster having highest matching rate. We have experimented our method to different numerical fonts and got encouraging results.

Shade Interest Points for Dynamic Stream Object Categorization

S. Suresh Babu,Venkata Naresh Mandhala,Siva Koteswara Rao Chinnam,Tai-hoon Kim 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.4

Discovery of investment focuses for ensuing handling is one of the fundamental parts of machine vision. Object order of pictures vigorously depends on investment point identification from which nearby picture descriptors are registered for picture matching. Since investment focuses are focused around luminance, past methodologies generally overlooked the color viewpoint. Later an approach that uses saliency-based peculiarity determination improved by a primary part dissection based scale choice strategy is created. It is utilized to lessen the affectability to changing imaging conditions, and hence it is a light-invariant investment point's location framework. Utilization of color expands the uniqueness of investment focuses. In the setting of item distinguishment, the human observation framework is regularly pulled in by contrasts between parts of pictures and by movement or moving articles. In this manner, in the feature indexing system, investment focuses give more helpful data when contrasted with static pictures. So we propose to amplify the above methodology for element feature streams utilizing Space-Time Interest Points (Stips) that uses a calculation for scale adaption of spatio-worldly investment focuses. STIP distinguishes moving questions in features and describes some particular changes in the development of these articles. A handy execution of the proposed framework accepts our case to help element streams and further it could be utilized as a part of uses, for example, Motion Tracking, Entity Detection and Naming applications.

일반논문 : 의료정책 변화 과정에서의 이익집단과 제도의 역할 분석 : 영국과 미국의 비교

최종호 ( Jong Ho Choi ) 한국민족연구원 2015 민족연구 Vol.0 No.63

이 논문은 영국과 미국의 의료정책의 변화과정을 통해 이익집단이 이 과정에 어떻게 영향을 주었는지, 이익집단의 정치가 제도적 촉진과 제약과 맞물려 어떠한 결과를 나타냈는지 탐색한다. 이 논문은 이익집단을 주요 행위자로 간주하고 정부와 갈등 또는 협력관계를 통해 의료개혁의 방향과 속도를 결정한다고 본다. 그러나 ``이익집단 정치``는 국가의 제도적 특성과 맞물려 개혁 속도와 개혁 달성 여부에 영향을 준다고 가정한다. 이를 1980년대 이후 미국과 영국의 의료정책 개혁 사례에 적용한다. 자유주의 복지국가로 구분되는 미국의 레이건 시기와 영국의 대처 시기에는 양국 모두 축소지향적 정부와 반복지적인 이익집단이 유인동기를 공유하면서 의료체계의 축소 개혁을 시도하였으나 두 국가의 독특한 제도적 특성과 맞물리면서 상이한 개혁결과를 도출하였다. 1990년대 중반 이후 블레어 정부와 클린턴 정부 시기에는 두 국가 모두 확대지향적 정부와 친복지적 이익집단이 유인동기를 공유하면서 의료개혁을 추진하였으나 이 결과 역시 상이하였다. 2010년대 캐머런 정부와 오바마 정부 시기의 의료개혁은 상이한 정부의 성향, 이익집단과의 유인동기 공유의 다양성, 그리고 독특한 제도적 특성이 맞물려 좀 더 복잡하게 전개되고 있다. This paper aims to investigate ‘health-care politics of interest groups’ in the U.K. and the U.S. This paper argues that the interest group is a primary actor who leads the health-care reform by sharing incentive with government. However, different ‘interest group politics’ of both countries is affected by a country-specific institutional context. In the era of retrenchment(post-1980s period), the health-care reform of both countries under the conservative government(Thatcher and Reagan) with retrenchment-oriented characteristics have been successfully implemented. however, health-care reform exhibit different outcomes since their ‘interest group politics’ interacted with country-specific institutional veto points. In the era of permanent austerity(after the mid 1990s period), expansionoriented reform under the Blair administration was implemented and succeeded, while that of Clinton administration failed due to the strong influence of anti-welfare interest groups and institutional veto points. After the 2010s, health-care reforms under the Cameron and Obama administration dramatically changed and diverged because of different government partisanship, diverse patterns of incentive sharing of interest groups and institutional characteristics.

이익집단 반복지정치(anti-welfare politics)의 경험적 분석

최종호(Choi, Jong Ho) 한국정치학회 2012 한국정치학회보 Vol.46 No.2

복지국가의 변화에 있어서 정부와 이익집단 사이에서 일어나는 반복지정치(anti-welfare politics)는 중요한가? 또한 정치제도는 복지개혁을 유인하거나 제약하는가? 이 논문은 서구 선진민주주의 국가에서 우파정당과 반복지적 성격을 띠는 이익 집단들이 생성하는‘이익집단 반복지정치’를 측정하고, 이 요인이 복지국가의 변화에 어떠한 영향을 미치는지 경험적으로 검증하고자 하는 시도이다. 이와 함께‘이익집단 반복지정치’가 국가 내에 존재하는 제도적 맥락과 어떻게 맞물리는지에 대한 상호작용 효과(interactive effect)도 함께 검증한다. 경험적 분석 결과, ‘이익집단 반복지정치’는 선진민주주의 국가의 사회지출 비율과 탈상품화의 수준을 낮추거나 좀 더 선별적(targeted)인 특성의 복지개혁으로 이끌고 있다는 것이 검증되었다. 그러나 국가 내에 존재하는 비토포인트의 수가 많을수록‘이익집단 반복지정치’의 영향이 미치지 못할 가능성이 높다는 것도 함께 검증되었다. Does ‘anti-welfare politics’between the government and interest groups matter in changes of the welfare state? Also, do political institutions induce or constrain welfare reform? This article measures the‘ anti-welfare politics of interest groups’led by right-wing parties and anti-welfare interest groups in advanced democracies, and empirically examines how this factor affects changes of welfare state. Moreover, this article explores the interactive effect between the ‘anti-welfare politics of interest groups’and institutional veto points. Based on the results of empirical analysis, I find that the‘ antiwelfare politics of interest groups’either reduces the country’s welfare expenditure or leads to a tendency toward more targeted welfare provision. The results also suggest that the influence of ‘antiwelfare politics of interest groups’can vary due to differences in veto points in advanced democracies.

A Novel Action Recognition Method Based on Improved Spatio-Temporal Features and AdaBoost-SVM Classifiers

Xiaofei Ji,Lu Zhou,Qianqian Wu 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.5

Most of existed action recognition methods based on spatio-temporal descriptors have ignored their spatial distribution information. However the spatial distribution information usually is very useful to improve the discriminative ability of the motion representation. An improved spatio-temporal is proposed in this paper by combining local spatio-temporal feature and global positional distribution information (FEA) of interest points. Furthermore, in order to improve the classifier’s performance, an Adaboost-SVM method is utilized to recognize the human actions by using the proposed motion descriptor. The proposed recognition method is tested on the public dataset of KTH. The test results verified the proposed representation and recognition method can more accurately describe and recognize the human motion.

DeepPIM: A deep neural point-of-interest imputation model

Chang, Buru,Park, Yonggyu,Kim, Seongsoon,Kang, Jaewoo Elsevier science 2018 Information sciences Vol.465 No.-

<P><B>Abstract</B></P> <P>A point-of-interest (POI) is a specific location in which someone is interested. In social network services such as Instagram, users share their experiences with text and photos, and link POIs to their posts. POIs can be utilized to understand user preferences and behavior. However, not all posts have POI information. In our study, we found more than half of the posts do not have POI information. The current state-of-the-art POI imputation model adds missing POI information. However, it relies on a conventional machine learning method that requires a substantial amount of laborious feature engineering. To address this problem, we propose DeepPIM, a deep neural POI imputation model that does not require feature engineering. DeepPIM automatically generates textual, visual, user, and temporal features from text, photo, user, and posting time information, respectively. For evaluating DeepPIM, we construct a new large-scale POI dataset. We show that DeepPIM significantly outperforms the current state-of-the-art model on the dataset. Our newly created large-scale POI dataset and the source code of DeepPIM are available at http://github.com/qnfnwkd/DeepPIM.</P>