• Journal of Technology Innovation
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• v.13 no.3
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• pp.225-255
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• 2005

The similar point of the 19 regional industrial clusters of Japan is that all of the clusters are not limited to an administrational district but rather covers a larger area. When a cluster covers a larger area, there is problem of acquiring responsible businesses and interactive planing. In order to overcome such a problem, private coordinating organizations have been installed and operated to connect and manage inter-activities of industries, universities, and research institutes. TAMA, a private coordinating organization, differs from other associations in a way that it does not deal with one specific field or business. TAMA rather dealswith various product-developing small to middle size companies by offering strategic support for the development of new technologies and expansion of new businesses. Product-developing small to middle size companies comparatively have their own abilities for technological development and marketing which is quite different from other subcontract companies and their relations to large corporations. In such aspect, product-developing companies are actually similar to large corporations with competitiveness in the world market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• Journal of Technology Innovation
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• v.19 no.2
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• pp.153-184
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• 2011

This paper investigates what kind of technological partner firms want to cooperate with in terms of partner location. Two geographical factors are considered. One is geographical proximity, given the tradeoff between the effectiveness of knowledge spillovers in proximity and diverse knowledge absorption from geographically distant partners. The other is how many other firms are co-located with potential partners because it is known that clustering regions can create more technological outputs. Analysis on 2008 Korea Innovation Survey data finds that partner proximity is the single most important factor in choosing a cooperation partner. While firms that are located in a region crowded with related industries prefer proximate partners, others that are surrounded by unrelated industries are more likely to cooperate with distant partners. The findings suggest that geographical proximity matters in partner selection because it not only stimulates knowledge spillovers but also reduces costs involving R&D cooperation such as monitoring costs and information costs. Moreover, firms take into consideration both the benefits and risks of clustering regions. If there are so many unrelated firms that they create agglomeration diseconomies such as congestion costs and unintentional knowledge leakages, firms are more likely to try to find their cooperation partners in other regions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7A
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• pp.717-723
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• 2007

There are many weaknesses in sensor networks due to hardware limitation of sensor nodes besides the vulnerabilities of a wireless channel. In order to provide sensor networks with security, we should find out the approaches different from ones in existing wireless networks; the security mechanism in sensor network should be light-weighted and not degrade network performance. Sowe proposed a novel data origin authentication satisfying both of being light-weighted and maintaining network performance by using Unique Random Sequence Code. This scheme uses a challenge-response authentication consisting of a query code and a response code. In this paper, we show how to make a Unique Random Sequence Code and how to use it for data origin authentication.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.402-408
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• 2007

There are many weaknesses in sensor networks due to hardware limitation of sensor nodes besides the vulnerabilities of a wireless channel. In order to provide sensor networks with security, we should find out the approaches different from ones in existing wireless networks; the security mechanism in sensor network should be light-weighted and not degrade network performance. Sowe proposed a novel data origin authentication satisfying both of being light-weighted and maintaining network performance by using Unique Random Sequence Code. This scheme uses a challenge-response authentication consisting of a query code and a response code. In this paper, we show how to make a Unique Random Sequence Code and how to use it for data origin authentication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.71-73
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• 2017

본 논문에서는 4 방향 윤곽선 추적 기법과 히스토그램 분석 기법을 기반으로 한 개선된 FCM 알고리즘을 적용하여 색조 도플러 초음파 영상에서 상완 동맥의 혈류를 추출하고 분석하는 방법을 제안한다. 제안된 방법에서는 상완 동맥의 혈류를 정확히 추출하기 위해 전처리 과정으로 색조 도플러 초음파 영상 이외의 환자 정보가 있는 영역을 제거한 후, ROI 영역을 추출한다. 추출된 ROI 영역에서 영상의 최대 명암도를 임계치로 설정한 이진화 기법을 적용하여 ROI 영역을 이진화한다. 이진화된 ROI 영역에서 4 방향 윤곽선 추적 기법을 적용하여 상완 동맥이 존재하는 사다리꼴 형태의 영역을 추출한다. 색 정보를 분석한 히스토그램을 이용하여 특징점의 개수를 계산하고 계산된 특징점의 개수를 FCM 알고리즘의 초기 클러스터의 개수로 설정한 후, 추출된 사다리꼴 형태의 영역에 적용하여 양자화 한다. 양자화된 영역 중에서 빨간색으로 분류된 영역을 고혈압 영역으로 추출한다. 제안된 추출 방법을 20개의 색조 도플러 초음파 영상을 대상으로 실험한 결과, 20개의 색조 도플러 초음파 영상에서 18개의 색조 도플러 초음파 영상이 정확히 추출되었다.

• Convergence Security Journal
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• v.7 no.2
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• pp.107-118
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• 2007

Distributed wireless sensor network in various environment have characteristic that is surveillance of environment-element and offering usefully military information but there is shortcoming that have some secure risks. Therefore secure service must be required for this sensor network safety. More safe and effective techniques of node administration are required for safe communication between each node. This paper proposes effective cluster-header and clustering techniques in suitable administration techniques of group-key on sensor network. In this paper, first each node transmit residual electric power and authentication message to BS (Base-Station). BS reflects "Validity Authentication Rate" and residual electric power. And it selects node that is more than these regularity values by cluster header. After BS broadcasts information about cluster header in safety and it transmits making a list of information about cluster member node to cluster header. Also, Every rounds it reflects and accumulates "Validity Authentication Rate" of former round. Finally, BS can select more secure cluster header.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.755-762
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• 2022

This paper propose a clustered algorithm that possible more efficient COVID-19 disease learning prediction within clustering using context-aware attribute information. In typically, clustering of COVID-19 diseases provides to classify interrelationships within disease cluster information in the clustering process. The clustering data will be as a degrade factor if new or newly processing information during treated as contaminated factors in comparative interrelationships information. In this paper, we have shown the solving the problems and developed a clustering algorithm that can extracting disease correlation information in using K-means algorithm. According to their attributes from disease clusters using accumulated information and interrelationships clustering, the proposed algorithm analyzes the disease correlation clustering possible and centering points. The proposed algorithm showed improved adaptability to prediction accuracy of the classification management system in terms of learning as a group of multiple disease attribute information of COVID-19 through the applied simulation results.

• The Korean Journal of Mycology
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• v.46 no.2
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• pp.193-199
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• 2018

The fungus, Podosphaera pannosa, was identified in 1991 as the cause of powdery mildew symptoms on peach (Prunus persica var. persica) fruit from Korea based on the morphological characteristics of the conidial state. Recently, however, in Serbia and France, the cause of 'rusty spot' found on peach fruit was identified as P. leucotricha, and the cause of 'powdery mildew' on nectarine (Prunus persica var. nucipersica) fruit was identified as P. pannosa. To confirm the identity of the Korean pathogen, we collected four samples of powdery mildew from Korean peach fruit: three with the 'powdery mildew' symptom and one with the 'rusty spot' symptom. Morphological examination of the four samples confirmed P. pannosa as the pathogen. Internal transcribed spacer sequences of rDNA were analyzed for molecular characterization. A phylogenetic tree showed that the Korean isolates were clustered into a clade containing P. pannosa from Rosa species, with high sequence similarities of more than 99%. Thus, we showed that the powdery mildew and rusty spot symptoms on peach fruits from Korea are associated with P. pannosa.