• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.153-166
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• 2008

This paper suggests the use of wavelet multiresolution analysis (WMRA) and neural network for generation of artificial earthquake accelerograms from target spectrum. This procedure uses the learning capabilities of radial basis function (RBF) neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, WMRA is used to decompose earthquake accelerograms to several levels that each level covers a special range of frequencies, and then for every level a RBF neural network is trained to learn to relate the response spectrum to wavelet coefficients. Finally the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the method.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.58-66
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• 2008

In this paper, we have proposed a method and procedure which can find out the unknown network protocol. Although it seems to be difficult to identify the protocol, we can find out the rule in the packet according to the method we have proposed. We have to recognize functions of the system and make the list of events first. Then we capture the network packet whenever the event are occurred. The captured packets are examined by means of the method that is finding repeated parts, changed parts according to the input value, fixed parts and changed parts according to regular rules. Finally we make the test program to verify the protocol. We applied this method and procedure to upgrade Electronic Warfare Test System which is operated by ADD. We have briefly described the redesign of control and analysis software for Electronic Warfare Test System

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.832-854
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• 2019

Action recognition has been studied in computer vision field for years. We present an effective approach to recognize actions using a dimension reduction method, which is applied as a crucial step to reduce the dimensionality of feature descriptors after extracting features. We propose to use sparse matrix and randomized kd-tree to modify it and then propose modified Local Fisher Discriminant Analysis (mLFDA) method which greatly reduces the required memory and accelerate the standard Local Fisher Discriminant Analysis. For feature encoding, we propose a useful encoding method called mix encoding which combines Fisher vector encoding and locality-constrained linear coding to get the final video representations. In order to add more meaningful features to the process of action recognition, the convolutional neural network is utilized and combined with mix encoding to produce the deep network feature. Experimental results show that our algorithm is a competitive method on KTH dataset, HMDB51 dataset and UCF101 dataset when combining all these methods.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.249-257
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• 2024

This study analyzes the current status and prospects of Iran's air defense network, focusing on the Russian-made S-300 system, and derives implications for the development of South Korea's air defense network. Iran's air defense network exhibits strengths such as long-range detection and interception capabilities, multi-target processing, high-altitude interception, and electronic warfare response. However, it also reveals weaknesses, including lack of mobility, difficulty in detecting low-altitude targets, obsolescence, training level of operating personnel, and vulnerability to electronic warfare. Real-world cases confirm these weaknesses, making the system susceptible to enemy evasion tactics, swarm drone attacks, and electronic warfare. Drawing from Iran's case, South Korea should establish a multi-layered defense system, strengthen low-altitude air defense and electronic warfare capabilities, foster the domestic defense industry for technological self-reliance, and enhance international cooperation. By addressing these aspects, South Korea can establish a robust air defense network and firmly protect its national security. Future research should aim to secure and analyze materials from the Iranian perspective for a more objective evaluation of Iran's air defense network and continuously track Iran's efforts to improve its air defense network and the trend of strengthening drone forces to predict changes in the Middle East security situation.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• Journal of Korea Technology Innovation Society
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• v.4 no.2
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• pp.157-171
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• 2001

This paper discusses the economics of local loop architecture focusing on existing technologies, ADSL, HFC, and new one, PLC, and suggests a new modeling approach of access network system and the numerical equations. To modelize access network system and drive the numerical equations, we consider the double star and the tree & branch architecture and made block diagram of each access system. In addition, we introduce the density of subscriber as a variable and the equation of seeking the optimal number of cell in a service area. The economics of local loop architecture is analyzed in two ways, i.e. with and without consideration of the cost of cable and infrastructure. From the numerical analysis, we find that in case of not including the cost of cable and infrastructure, there is no much difference in the cost per one subscriber, while, in case of including it, there is remarkable difference among technologies. Therefore we conclude that the economics of local loop architecture is depend on the density of subscriber and existing network infrastructures.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.246-251
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• 2022

As the number of data and devices explodes, centralized data processing and AI analysis have limitations due to the load on the network and cloud. On-device AI technology can provide intelligent services without overloading the network and cloud because the device itself performs AI models. Accordingly, the need for on-device AI technology is emerging. Many smartphones are equipped with On-Device AI technology to support the use of related functions. In this paper, we compare software tools that implement On-Device AI.

• Asia pacific journal of information systems
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• v.26 no.2
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• pp.299-321
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• 2016

Previous studies on strategic alliance formation have largely overlooked the effects that organizations' routine development can have on the relationship between organizations' network position and their alliance ambidexterity strategy. This study extends ambidexterity research by adding internal and network perspectives and examining their cumulative effects on alliance ambidexterity. We first acknowledge the interplay between organizations' internal knowledge exploration/exploitation strategies and organizations' alliance ambidexterity and determine that organizations with a high level of internal knowledge breadth are more likely to make focused alliance decisions. Second, our analysis of 145 US-based information technology organizations with an active alliance behavior reveals that having well-formed routines as a result of previous collaborations strengthens the tendency of brokerage organizations to follow alliances that focus on either exploration or exploitation. Although most alliance studies have commonly argued in favor of an ambidextrous approach, this study provides critical evidence that both internal knowledge exploration/exploitation strategies and development of routines constrain organizations' alliance formation decisions, guiding them towards a more focused approach.

• Smart Structures and Systems
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• v.15 no.1
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Journal of Applied Reliability
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• v.5 no.4
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• pp.465-486
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• 2005

A unreliable network system results in unsatisfied performance. A performance criterion of a network is throughput and availability. One of the most compelling technological advances of this decade has been the advent of deploying wireless networks of heterogeneous smart sensor nodes for complex information gathering tasks, The advancement and popularization of wireless communication technologies make more efficiency to network devices with wireless technology than with wired technology. Recently, the research of wireless sensor network has been drawing much attentions. In this paper, We evaluate throughput and availability of wireless sensor network, which have hierarchical structure based on clustering and estimate the maximum hroughput, average throughput and availability of the network considering several link failure patterns likely to happen at a cluster consisted of sensor nodes. Also increasing a number of sensor nodes in a cluster, We analysis the average throughput and availability of the network.