• Title/Summary/Keyword: industrial networks

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Characteristics of the Social Innovation Cluster Formation in Seongdong-gu and Eunpyeong-gu, Seoul, Korea (서울 성동구와 은평구의 사회혁신클러스터 형성 특성)

  • Roh, Kyeongran;Choo, Sungjae
    • Journal of the Economic Geographical Society of Korea
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    • v.22 no.2
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    • pp.214-235
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    • 2019
  • This study adopts the concept of social innovation cluster in which social economy organizations as one of the emerging axes of economic systems operate in collaboration with government agencies, investment institutions, intermediate supporting organizations and non-profit organizations, and investigates how the clusters of this kind grow in the context of the Korean socio-economic situation for the cases of Seongdong-gu and Eunpyeong-gu in Seoul, Korea. For this purpose, it has identified the actors of the clusters and their internal relations, and analyzed the process of cluster formation. A social network analysis of the partnerships between the actors has shown that Seongdong-gu has more diversified types of the network participation of universities, global networks and investment institutions than Eunpyeong-gu. It is interpreted that this pattern has resulted from the domination of private organizations in the former area, which is also confirmed by in-depth interviews with persons involved in the clusters. Although the facets of social innovation clusters are manifested in both areas, even in their initial stage, such factors as linkages between industrial actors and convergence with other clusters, which appear in the maturing stage of cluster formation, has yet to be found. It is suggested that the sustainable growth of social innovation clusters should be accompanied by information sharing and cooperation between the two areas on the future orientation of development.

A Study on Similar Trademark Search Model Using Convolutional Neural Networks (합성곱 신경망(Convolutional Neural Network)을 활용한 지능형 유사상표 검색 모형 개발)

  • Yoon, Jae-Woong;Lee, Suk-Jun;Song, Chil-Yong;Kim, Yeon-Sik;Jung, Mi-Young;Jeong, Sang-Il
    • Management & Information Systems Review
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    • v.38 no.3
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    • pp.55-80
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    • 2019
  • Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

Restoration of The Transportation Network between North and South Korea for Mt. Geumgang Tourism (금강산(내금강) 관광을 위한 남북연결 교통망에 관한 연구)

  • HONG, Gil-Jong;BAE, Sun-Hak
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.51-64
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    • 2019
  • Mt. Geumgang has been a scenic spot representing the Korean peninsula since the Joseon Dynasty, and became a symbol of inter-Korean exchanges with the Gaesong Industrial Complex after the division of the South and North. Mt. Geumgang Tour Course is divided into the Inner-Geumgang (Naegeumgang) and the Outer-Geumgang (Oegeumgang). It was common for the Mt. Geumgang tour route during the Joseon Dynasty and the Japanese Imperialization period to enter the Inner-Geumgang, near Seoul, and come to the East Sea through the Outer-Geumgang. However, the tour route starting from Goseong was utilized for the Mt. Geumgang tour course operated by Hyundai. Because North Korea opened only the Outer-Geumgang area. North Korea has only opened some of its tour courses to Hyundai, but if Geumgang tourism is resumed in the future, there is a high possibility that it will be opened further, such as opening some sections of the Inner-Geumgang in 2007. In this case, it is necessary to connect additional transportation networks to access Inner-Geumgang from South Korea. The best alternative was the restoration of the Mt. Geumgang Railway. However, considering the fact that the reconstruction of the Mt. Geumgang Railway can not be completed due to the construction of the Imnam Dam, it is the most realistic alternative to restore Route 31 connecting Yanggu and Geumgang-eup. As a result of the analysis of road connecting Inner-Geumgang, three routes were confirmed. All of which were adjacent to the existing National Route 31. These routes passing through Dutayeon and Mundeung-ri and joining the Route 31 from Inje. Considering road length, topography characteristics, and military facility layout, it seems that the connection of 'Dutaeyun - Mundeung - Geumgang' is a realistic alternative connecting from South Korea to Inner-Geumgang.

Characteristics and Optimization of the Formula of Mashed Potatoes Using Purple-fleshed Potato (Solanum tuberosum L.) by Mixture Design (혼합물 실험계획법을 이용한 유색감자 자영(Solanum tuberosum L.) 매쉬드 포테이토 분말의 혼합비 최적화 및 매쉬드 포테이토의 특성)

  • Jung, Hwabin;Choi, Ji-il;Yoon, Won Byong
    • Food Engineering Progress
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    • v.21 no.2
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    • pp.167-173
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    • 2017
  • Purple-fleshed potato powder (PFPP) was investigated to determine optimal mixing ratio with milk powder and dextrin to produce a ready-to-eat mashed potato powder. The rheological characteristics, color, and anthocyanin contents were studied at a different concentration of ingredients. The power-law model was applied to explain the mechanical spectra of mashed potatoes which represented the change in structure induced by different mixing ratios. Mixture design was used to obtain the experimental points used to establish the empirical models to describe the effects of each ingredient on the characteristic of the mashed potato. The results of mechanical spectra showed that both storage and loss moduli (G' and G'') were significantly influenced by PFPP and milk powder concentration. The power law parameters n' and n'' showed higher values for the mashed potato with a lower concentration of PFPP and a higher concentration of milk powder, which showed that the gel networks involved in the mashed potato were weaker. The optimum mixing ratio with the highest redness and anthocyanin content, while maintaining the rheological properties similar to the commercial mashed potato, was determined as PFPP:milk powder:dextrin = 90.49:4.86:4.65 (w/w). The proportions of PFPP and milk powder in the formulation significantly changed the characteristics of mashed potato, whereas no significant effect of dextrin was observed in this formulation.

A Study on the Operation of Multi-Beam Antenna for Airborne Relay UAV considering the Characteristics of Aircraft (비행체의 특징을 고려한 공중중계 무인기 다중빔 안테나 운용 방안)

  • Park, Sangjun;Lee, Wonwoo;Kim, Yongchul;Kim, Junseob;Jo, Ohyun
    • Journal of Convergence for Information Technology
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    • v.11 no.4
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    • pp.26-34
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    • 2021
  • In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

Deep Learning-based Technology Valuation and Variables Estimation (딥러닝 기반의 기술가치평가와 평가변수 추정)

  • Sung, Tae-Eung;Kim, Min-Seung;Lee, Chan-Ho;Choi, Ji-Hye;Jang, Yong-Ju;Lee, Jeong-Hee
    • The Journal of the Korea Contents Association
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    • v.21 no.10
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    • pp.48-58
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    • 2021
  • For securing technology and business competences of companies that is the engine of domestic industrial growth, government-supported policy programs for the creation of commercialization results in various forms such as 『Technology Transaction Market Vitalization』 and 『Technology Finance-based R&D Commercialization Support』 have been carried out since 2014. So far, various studies on technology valuation theories and evaluation variables have been formalized by experts from various fields, and have been utilized in the field of technology commercialization. However, Their practicality has been questioned due to the existing constraint that valuation results are assessed lower than the expectation in the evaluation sector. Even considering that the evaluation results may differ depending on factors such as the corporate situation and investment environment, it is necessary to establish a reference infrastructure to secure the objectivity and reliability of the technology valuation results. In this study, we investigate the evaluation infrastructure built by each institution and examine whether the latest artificial neural networks and deep learning technologies are applicable for performing predictive simulation of technology values based on principal variables, and predicting sales estimates and qualitative evaluation scores in order to embed onto the technology valuation system.

Crack Detection on Bridge Deck Using Generative Adversarial Networks and Deep Learning (적대적 생성 신경망과 딥러닝을 이용한 교량 상판의 균열 감지)

  • Ji, Bongjun
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.9 no.3
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    • pp.303-310
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    • 2021
  • Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started to be conducted. Deep learning requires sufficient data on the situations to be predicted, but bridge crack data is relatively difficult to obtain. In particular, it is difficult to collect a large amount of crack data in a specific situation because the shape of bridge cracks may vary depending on the bridge's design, location, and construction method. This study developed a crack detection model that generates and trains insufficient crack data through a Generative Adversarial Network. GAN successfully generated data statistically similar to the given crack data, and accordingly, crack detection was possible with about 3% higher accuracy when using the generated image than when the generated image was not used. This approach is expected to effectively improve the performance of the detection model as it is applied when crack detection on bridges is required, though there is not enough data, also when there is relatively little or much data f or one class.

Fandom-Persona Design based on Social Network Analysis (소셜 네트워크 분석을 이용한 팬덤 페르소나 디자인)

  • Sul, Sanghun;Seong, Kihun
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.87-94
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    • 2019
  • In this paper, the method of analyzing the unformatted data of consumers accumulated on social networks in the era of the Fourth Industrial Revolution by utilizing data from the service design and social psychology aspects was proposed. First, the fandom phenomenon, which shows subjective and collective behavior in a space on a social network rather than physical space, was defined from a data service perspective. The fandom model has been transformed into a collective level of customer Persona that has been analyzed at a personal level in traditional service design, and social network analysis that analyzes consumers' big data has been presented as an efficient way to pattern and visually analyze it. Consumer data collected through social leasing were pre-processed by column based on correlation, stability, missing, and ID-ness. Based on the above data, the company's brand strategy was divided into active and passive interventions and the effect of this strategic attitude on the growth direction of the consumer's fandom community was analyzed. To this end, the fandom model of consumers was proposed by dividing it into four strategies that the brand strategy had: stand-alone, decentralized, integrated and centralized, and the fandom shape of consumers was proposed as a growth model analysis technique that analyzes changes over time.

A Study on Model for Drivable Area Segmentation based on Deep Learning (딥러닝 기반의 주행가능 영역 추출 모델에 관한 연구)

  • Jeon, Hyo-jin;Cho, Soo-sun
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.105-111
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    • 2019
  • Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

Associations of Transport Accessibility with Restaurants' Survival in Gwangju Metropolitan Area (광주광역시 음식점 개폐업과 교통접근성의 상관관계 분석)

  • Song, Yena;Jang, Hanwool;Lee, Keumsook
    • Journal of the Economic Geographical Society of Korea
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    • v.23 no.4
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    • pp.425-437
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    • 2020
  • In Korea, the proportion of self-employed and unpaid family workers is relatively higher than other OECD countries and the operation periods of their businesses are generally shorter than others. This indicates frequent startups and closures and thus unstable employment status and income, which inevitably generates huge social costs. Restaurants are a representative business that self-employed workers easily enter and their 5-year survival rate is found to be lower than 20%. This is shorter survival period than other business sectors. This study aims to examine the associations of transport accessibility with restaurants' survival in Gwangju metropolitan area. Convenient location has been known to be a crucial factor for sales improvements and longer operation and such location is closely linked with good transport accessibility. Results from survival analysis on empirical data show that better access to road networks is significantly associated with longer survival of restaurants though subway accessibility is not. This can be explained by low modal share of subway in the study area and at the same time, requires further case studies where more developed and matured subway systems are in operation.