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An Analysis on the Relationship among Mingli-variable, Self-efficacy and Depression in Middle-aged Women with Discontinued Career (경력단절 중년여성의 명리변수와 자기효능감 및 우울감 관계 분석)

  • Sun-Ok Shin
    • Industry Promotion Research
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    • v.8 no.3
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    • pp.95-109
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    • 2023
  • The purpose of this paper is to empirically grasp the influence on self-efficacy and depression and the relationship between variables, focusing on middle-aged women in their 40s and 50s who are psychologically and socially vulnerable. Through this, it was intended to explore the psychological problems of highly educated careerinterrupted women from a personal perspective and further derive implications for the development of policies and services for socially highly educated career-interrupted women. The relationship between variables was analyzed through a survey based on measurement tools structured by variables of Saju factors, self-efficacy, and depression, and the effect of the sub-dimensional characteristics of Saju structure on self-efficacy, and the resulting level of depression were verified through structural equation model analysis. Bigeop, Jaeseong, and Kwanseong have been found to have a positive and direct effect on self-efficacy and negative direct effect on depression, eventually increasing self-efficacy and lowering depression. It was found that Siksang had a positive (+) relationship with depression and a negative (-) relationship with self-efficacy, but Inseong did not directly affect self-efficacy and depression. In addition, the indirect effects between variables and the effects between self-efficacy and depression were identified.

Efficient Poisoning Attack Defense Techniques Based on Data Augmentation (데이터 증강 기반의 효율적인 포이즈닝 공격 방어 기법)

  • So-Eun Jeon;Ji-Won Ock;Min-Jeong Kim;Sa-Ra Hong;Sae-Rom Park;Il-Gu Lee
    • Convergence Security Journal
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    • v.22 no.3
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    • pp.25-32
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    • 2022
  • Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

Big data analysis on NAVER Smart Store and Proposal for Sustainable Growth Plan for Small Business Online Shopping Mall (네이버 스마트스토어에 대한 빅데이터 분석 및 소상공인 온라인쇼핑몰 지속성장 방안 제안)

  • Hyeon-Moon Chang;Seon-Ju Kim;Chae-Woon Kim;Ji-Il Seo;Kyung-Ho Lee
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.153-172
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    • 2022
  • Online shopping has transformed and rapidly grown the entire market at the forefront of wholesale and retail services as an effective solution to issues such as digital transformation and social distancing policy (COVID-19 pandemic). Small business owners, who form the majority at the center of the online shopping industry, are constantly collecting policy changes and market trend information to overcome these problems and use them for marketing and other sales activities in order to overcome these problems and continue to grow. Objective and refined information that is more closely related to the business is also needed. Therefore, in this paper, through the collection and analysis of big data information, which is the core technology of digital transformation, key variables are set in product classification, sales trends, consumer preferences, and review information of online shopping malls, and a method of using them for competitor comparison analysis and business sustainability evaluation has been prepared and we would like to propose it as a service. If small and medium-sized businesses can benchmark competitors or excellent businesses based on big data and identify market trends and consumer tendencies, they will clearly recognize their level and position in business and voluntarily strive to secure higher competitiveness. In addition, if the sustainable growth of the online shopping mall operator can be confirmed as an indicator, more efficient policy establishment and risk management can be expected because it has an improved measurement method.

Real-time Steel Surface Defects Detection Appliocation based on Yolov4 Model and Transfer Learning (Yolov4와 전이학습을 기반으로한 실시간 철강 표면 결함 검출 연구)

  • Bok-Kyeong Kim;Jun-Hee Bae;NGUYEN VIET HOAN;Yong-Eun Lee;Young Seok Ock
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.31-41
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    • 2022
  • Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

Class Classification and Validation of a Musculoskeletal Risk Factor Dataset for Manufacturing Workers (제조업 노동자 근골격계 부담요인 데이터셋 클래스 분류와 유효성 검증)

  • Young-Jin Kang;;;Jeong, Seok Chan
    • The Journal of Bigdata
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    • v.8 no.1
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    • pp.49-59
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    • 2023
  • There are various items in the safety and health standards of the manufacturing industry, but they can be divided into work-related diseases and musculoskeletal diseases according to the standards for sickness and accident victims. Musculoskeletal diseases occur frequently in manufacturing and can lead to a decrease in labor productivity and a weakening of competitiveness in manufacturing. In this paper, to detect the musculoskeletal harmful factors of manufacturing workers, we defined the musculoskeletal load work factor analysis, harmful load working postures, and key points matching, and constructed data for Artificial Intelligence(AI) learning. To check the effectiveness of the suggested dataset, AI algorithms such as YOLO, Lite-HRNet, and EfficientNet were used to train and verify. Our experimental results the human detection accuracy is 99%, the key points matching accuracy of the detected person is @AP0.5 88%, and the accuracy of working postures evaluation by integrating the inferred matching positions is LEGS 72.2%, NECT 85.7%, TRUNK 81.9%, UPPERARM 79.8%, and LOWERARM 92.7%, and considered the necessity for research that can prevent deep learning-based musculoskeletal diseases.

A Study on Method of Framework Data Update and Computing Land Change Ratio using UFID (UFID를 이용한 기본지리정보 갱신 및 지형변화율 산출 방안 연구)

  • Kim, Ju Han;Kim, Byung Guk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.157-167
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    • 2006
  • During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

Career map and course map recommendation system for employment (취업준비를 위한 career map and course map 추천 시스템)

  • Kwon, Wonhyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.276-279
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    • 2022
  • The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning

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A Study on the effect of SCM Integration and Green SCM practices to Environmental Performance (공급체인 통합과 친환경 활동이 환경성과에 미치는 영향에 관한 연구)

  • Kim, Changbong;Jung, Sunnam
    • International Area Studies Review
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    • v.15 no.1
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    • pp.447-466
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    • 2011
  • This paper examined the supply chain management Integration factors and environmental performance in Korean industry. Focusing on SCM Integration, GreenSCM practice, and environmental performance factors, purpose of this study is finding linkage between SCM Integration factors with new environmental practice factors and environmental performance. Based on the analysis of eighty-eight cases, the following results were found. First, We found External environmental collaboration factors and Internal environmental monitoring factors within Green Supply Chain Practices. Second, SCM Integration have a positively significant influence on environmental performance. Third, Internal environmental monitoring factors have a positively significant influence on Environmental performance but External environmental collaboration factors doesn't. This study suggests that only with high level of Integration firms may have good result on entire supply chain environmental performance. Finally, our empirical evidence shows that company should be prepared for new environmental trade regulation with Green Supply chain management integration.

The Role of Culture in Regional Innovation System : Focusing on the Cases of Yufuin and Yubari (지역혁신체계에서 문화의 역할 : 유후인과 유바리의 사례를 중심으로)

  • Chung, Jong-Eun;Han, Seola
    • 지역과문화
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    • v.6 no.4
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    • pp.47-72
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    • 2019
  • The purpose of this paper is to explore what roles can and should regional culture play in establishing a regional innovation system, which has been recently described as an essential factor for balanced regional development and specialized regional development. In doing so, we first investigated key concepts and discourses regarding regional innovation system and examined the success factors of a regional innovation system. We also explored how the Korean policy makers have developed the nation's regional innovation policy and regional cultural policy in order to understand the policy context and its limitations. After examining the theoretical background, we reviewed the representative cases of regional innovation in Japan, Yufuin and Yubari, to grasp the way in which 'culture' plays its roles in the formation of the regional innovation system. Since culture has a role as a unique sector, such as art and content industry, as well as a community's style of life, this study tried to explore the aspects and ways of how culture can contribute to the establishment of regional innovation systems considering these distinctive levels. In drawing the implications of the case study, we found that special attention is required for the 'process of formation' of regional innovation systems. We also confirmed that the success of the core activities at each stage heavily relies on the culture of the region; in order to fully understand the relations, it is necessary to re-establish the existing concept of culture and cultural policy with a more holistic perspective.

Exploratory Study on the Efficient Operation of Parcel Delivery Network with the Growth of Online Shopping Industries (온라인 쇼핑의 성장에 따른 택배물류 네트워크의 효율적 운영에 관한 탐색적 연구)

  • Lim, Hyunwoo;Lim, Jong Won;Yi, Hansuk
    • Asia Marketing Journal
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    • v.9 no.2
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    • pp.97-129
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    • 2007
  • The critical link between consumer-based internet ordering and the delivery of the product to the consumer is a key success factor in online shopping. Market areas of online shopping company implies the range of space where products ordered from online shopping can be physically delivered to customers distributed over space with reasonable shipping cost and lead time through the physical distribution network. The average rate of growth in online shopping is 36% per year in Korea for the last 5 years. But there are no maps available that describe sales/delivery density of online shopping, few researches are focused on the short-term/long-term adaptation to demand increase by online shopping. In this paper (1) Maps of trade area are described indicating the sales/delivery density around the nation. (2) Empirical researches suggested that short-term adaptation to demand increase resulted in price reduction and service in enhancement of service quality in local transportation. But the long-term adaptation on the parts of parcel delivery industry are to be investigated in future researches.

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