• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.127-136
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• 2007

It is easy to install and maintain a mobile multi-hop wireless network due to its self-organizing characteristics. However it has security weakness of the authentication of mobile multi-hop relay stations. Specially, the mobile multi-hop relay network in the IEEE 802.16j has the additional security weakness caused by the requirement of backward compatibility for mobile stations of the conventional IEEE 802.16 system. In this paper, we propose a novel mutual authentication scheme applicable to IEEE 802.16j-based mobile multi-hop relay network architecture. The scheme is able to resolve the initial trust gain problem of a multi-hop node at its entry to the network, the problem of rogue mobile multi-hop node and the problem of hop-by-hop authentication between multi-hop nodes. Effectively, the scheme is a hybrid scheme of the distributed authentication method and the centralized authentication method which have been considered to be deployed in the wireless ad-hoc network and the wireless network connected to wired authentication servers, respectively. Also, we analyze the effectiveness of the proposed hybrid authentication method.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.525-532
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• 2021

In the ocean, it is difficult to separate the effects of one cause due to the multiple causes, but the self-organizing map can be analyzed by adding other factors to the cluster result. Therefore, in this study, the results of the clustering of sea level data were applied to sea surface temperature. Sea level data was clustered into a total of 6 nodes. The difference between sea surface temperature and sea level height has a one-month delay, which applied sea surface temperature data a month ago to the clustered results. As a result of comparing the mean of sea surface temperature of 140 to 150°E, where the sea surface temperature was variously distributed, in the case of nodes 1, 3, and 5, it was possible to find a meandering sea surface temperature distribution that is clearly distinguished from the sea level data. While nodes 2, 4 and 6, the sea surface temperature distribution was smooth. In this study, sea surface temperature data were applied to the clustered results of sea level data, but later it is necessary to apply wind or geostrophic velocity data to compare.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.1
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• pp.19-40
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• 2021

This study aims to explore alternative strategies for the archival professional training system in response to changing records management environments. It found implications in the training and qualification system for overseas archival professionals and compared and analyzed the qualification system for Korean archival professionals. In addition, by analyzing the archival graduate schools' general status and the instructors' research performance, the study confirmed that many instructors have low academic interest in archival studies and the gap between schools was significant. Based on this, interviews with professors and experts were conducted to gather opinions on improving the archival professional training system. In conclusion, the study presents prerequisite tasks of organizing an archival community governance system and securing self-regulatory power. Moreover, it proposes innovative measures for the archival professional training system with three major tasks: creating graduate education guidelines, establishing a continuing and deepening education system, and transforming educational institutions.

• Journal of KIISE:Information Networking
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• v.34 no.2
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• pp.88-99
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• 2007

P2P systems are distributed data sharing systems, and each node in them plays the role of client as well as server. There are several studies using Distributed Hash Table, such as Chord, CAN, Tapestry, Pastry, but these systems don't consider the physical latency, therefore they have a weakness of difficulty to guarantee stable performance. To improve this problem, we present the TP2P system. This system is a self-organizing hierarchical overlay system and it uses Chord routing mechanism for lookup data. This system is organized by several subnets, each subnet is organized by physically close nodes, and global network organized by all nodes. In each subnet, one node finds a data, it saves in a node in the subnet, therefore it has higher probability to reduce physical lookup latency than Chord system. And each node has global information of some nodes in its subnet, and it is used to lookup data, therefore the number of hops decrease about 25% as well as the physical lookup latecy are reduced.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.58-65
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• 2003

This paper studies a steering control method using a neural network algorithm for an intelligent autonomous driving robot. Previous horizontal steering control methods were made by various possible situation on the road. However, it isn't possible to make out algorithms that consider all sudden variances on the road. In this paper, an intelligent steering control algorithm for an autonomous driving robot system is presented. The algorithm is based on Self Organizing Maps(SOM) and the feature points on the road are used as training datum. In a simulation test, it is available to handle a steering control using SOM for an autonomous steering control. The algorithm is evaluated on an autonomous driving robot. The algorithm is available to control a steering for an autonomous driving robot with better performance at the experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.51-57
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• 2009

Ubiquitous sensor network is the communication environment where sensor nodes move freely and construct network to get the services from the system. So, it does not need fixed infrastructure and can easily be placed in unaccessible regions like war or calamity area. Wireless sensor network protocol has self-organizing capability, need to adapt topology change flexibly and also has technique that sensor nodes work cooperatively, because network disconnection is frequently occurred due to the active mobility of sensor nodes. In this paper, we design a cluster based fault-tolerant routing protocol for the efficient topology construction and to guarantee stable data transmission in USN. The performance of the proposed protocol is evaluated by an analytic model.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.515-522
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• 2004

In this study, we tried to investigate that the advantages of SOM(Self Organizing Map) algorithm such as data accumulation ability and the degradation trend trace ability would be adaptable to the analysis of partial discharge pattern recognition. For the purpose, we analyzed partial discharge data obtained from the typical artificial defects in GIS and XLPE power cable system through SOM algorithm. As a result, partial discharge pattern recognition could be well carried out with an acceptable error by use of Kohonen map in SOM algorithm. Also, it was clarified that the additional data could be accumulated during the operation of the algorithm. Especially, we found out that the data accumulation ability of Kohonen map could make it possible to suggest new patterns, which is impossible through the conventional BP(Back Propagation) algorithm. In addition, it is confirmed that the degradation trend could be easily traced in accordance with the degradation process. Therefore, it is expected to improve on-site applicability and to trace real-time degradation trends using SOM algorithm in the partial discharge pattern recognition

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1265-1271
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• 2009

본 연구에서는 강우의 시 공간적 분포의 불규칙한 변동성을 고려한 강우-유출예측모형을 위해 인공신경망(Artificial Neural Networks: ANNs)의 기법의 일종인 자기조직화(Self Organizing Map: SOM) 이론과 역전파 학습 알고리즘(Back Propagation Algorithm: BPA) 이론을 복합적으로 이용하였다. 기존의 인공신경망 연구에서 야기된 저 갈수기의 유출량에 대한 과대평가, 홍수기의 유출량에 대한 과소평가, 예측값이 연속적으로 선행 유출량을 나타내는 Persistence 현상을 해결하기 위하여 패턴분류 성능을 지닌 SOM 이론을 예측모형의 전처리 과정으로 이용하였다. 먼저, 본 연구에서 제안한 방법은 SOM에 의해 강우-유출 관계를 분류하고, SOM에 의한 분류에 따라 각각의 모형을 구성한다. 개별적으로 구축된 모형은 유출량의 예측을 위해 각각의 양상에 따라 분류된 자료를 이용한다. 결과적으로 본 연구에서 제안한 방법은 과거의 인공신경망의 일반적인 적용에 의한 결과보다 더 나은 예측능력을 보여주었으며, 더불어 유출량의 과소 및 과대추정과 Persistence 현상과 같은 문제점이 나타나지 않았다. 또한 강우량 및 유출량의 범위에 제한을 받지 않는 강우-유출예측 모형의 개발 및 홍수기로부터 갈수기까지의 보다 넓은 범위의 유출량의 예측에 기여할 것으로 기대된다.

• Research in Community and Public Health Nursing
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• v.18 no.2
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• pp.266-275
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• 2007

Purpose: The purpose of this study was to evaluate achievements of a community health center for vulnerable population in urban areas and to find out its strength and weakness. Method: This evaluative study employed system theories and analytic techniques. Results: The purpose of improving vulnerable population's health-related self-care abilities adequately met the operation of programs. This center maintained close connection to a nursing college as a information resource. The subjects' satisfaction was high because team members who visited them were faithful and there were face-to-face contact, sufficient time set, closeness and resourcefulness. There were needs for regular meetings to discuss overall matters in organizing the program and to improve management skills. The mean score of health promotion lifestyle was 2.23 on a 4 point scale. This score indicates what in higher than vulnerable people in other communities. Conclusions: Community-based nursing centers for vulnerable population in urban areas should be developed as support organizations and community network.