• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.15-21
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• 2017

In the active SONAR system, various studies have been carried out to enhance the resolution of a received signal. In order to obtain higher resolution for detecting a bottoming cylindrical object, the design of a planar array for SONAR is investigated in this paper. It is necessary to employ planar structures for SONAR array to obtain narrower beam pattern which gives high resolution. In this study, the transmit frequency of each acoustic transducer, which consists of an array is 13 kHz. For efficient detection of a target of an asymmetric size, the concept of areal angle is applied, which considers resolution according to both azimuth and elevation angles in array design. In the design, the areal angle is first investigated to satisfy the resolution requirements, and then based on the value of areal angles, the azimuth angle and the elevation angle are calculated respectively to design an array.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1276-1285
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• 2007

Since the TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) system is based on TDD (Time Division Duplexing), the uplink and downlink can be allocated asymmetrically according to the traffic e.g. Web browsing. Although this asymmetric allocation can increase the frequency utilization, it may cause time slot opposing, which implies the time slot is assigned in opposing direction between cells. The time slot opposing can generate significant interference between cells, which results in severe performance degradation. In the paper, a novel dynamic channel allocation (DCA) is proposed in the TD-SCDMA system, to mitigate the impact of time slot opposing considering smart antenna. When the smart antenna is applied in the system, the inter-cell interference is largely affected by beam pattern and beam direction between neighboring cells. Therefore, the time slot opposing and smart antenna should be considered together in the DCA. The intensive simulations show that the proposed scheme can improve the system capacity compared to the conventional DCA schemes.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Korea and Global Affairs
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• v.1 no.1
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• pp.115-152
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• 2017

This paper is to analyse the changes in the future war patterns and ROK's response. To this end the paper is composed of 5 chapters titled instruction; concept, characteristics, types, and evolution of war; changes in the war patterns of the future; Korea's response strategies for the future war. Truth can be immutable, but everything else changes. War has begun with human history, and today there are still wars in places all over the world. As ages change from agricultural society to industrial society to knowledge and information society, aspects(patterns) of war have also changed. Future warfare includes the 5th dimensional war(in the ground, the sea, the air, the universe, the cyber), the network-centric, the precision strike, the rapid maneuver, the non-gunpowder, the non-lethal, the unmanned robot, the informational & cyber, the asymmetric, the non-linear, and the parallel etc. In response to these changes in the pattern of wars, the ROK military should seek (1)to build a future-oriented military force, (2)to continuously develop military innovation and preparedness, and (3)to develop and establish a paradigm for acquiring the power of technology. A Roman strategist, Vegetius said, "If you wish peace, prepare for war." This is a universally accepted maxim in international society today. We must never forget that peace we desire is given when we have the will and ability to keep.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.145-155
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• 2020

The purpose of this study investigates the relationship between business strategy and cost behavior according to the corporate life cycle. To do so, I first examine the relationship between cost behavior and business strategy. And then, I analyze the effect of the business strategy on cost behavior conditional upon corporate life cycle based on listed Korean firms from 2000 to 2019. Specifically, the business strategy index is calculated by using the six continuous financial factors and the Prospector and Defender was defined on the score. Also, the corporate life cycle is distinguished based on the cash flow pattern. I find the evidence that the Prospector firms are likely to strengthen the asymmetry of cost behavior (cost stickiness), and examined that such a relationship was most strongly represented in the Introduction. This study is meaningful in that this is a more comprehensive analysis by examining business strategy and cost strategy according to the corporate life cycle and expand the application of financial information by using financial indicators to distinguish business strategies.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.179-184
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• 2006

An intuitive understanding of the dynamic pattern generation in asymmetric networks may be considered an essential component in developing models for the dynamic information processing. It has been reported that the neural network with cyclic connections generates multiple limit cycles. The dynamics of discrete time network with cyclic connections has been investigated intensively. However, the dynamics of a cyclic connection neural network in continuous-time has not been well-known due to the considerable complexity involved in its calculation. In this paper, the dynamic behavior of a continuous-time cyclic connection neural network, in which each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$, has been investigated. Furthermore, the dynamics and stability of the network have been analyzed using a piece-wise linear approximation.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.339-350
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• 2004

A broadcast method in mobile computing environments which have very large client populations solves the problem of low bandwidth. But most of previous proposed concurrency control protocols are restricted to read-only transactions from mobile client. In this paper, we propose the UTSM-ARM method which uses caching and broadcast method, and allows update transactions in mobile client. The UTSM-ARM decides the validation of cache data consistency with the dynamic update pattern ratio of accessed cached data. Also, the timestamps of accessed cached data and transaction in mobile client guarantee the serializable execution of mobile transactions. As a result, UTSM-ARM makes efficiently use of the asymmetric bandwidth of broadcast environment and can Increase the transaction throughput.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.25-33
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• 2019

This paper presents a novel evolutionary framework for optimizing a bio-inspired fully dynamic neurocontroller for the maneuverable flapping flight of a simulated bird-sized ornithopter robot which takes advantage of the morphological computation and mechansensory feedback to improve flight stability. In order to cope with the difficulty of generating robust flapping flight and its maneuver, the wing of robot is modelled as a series of sub-plates joined by passive torsional springs, which implements the simplified version of feathers attached to the forearm skeleton. The neural controller is designed to have a bilaterally symmetric structure which consists of two fully connected neural network modules receiving mirrored sensory inputs from a series of flight navigation sensors as well as feather mechanosensors to let them participate in pattern generation. The synergy of wing compliance and its sensory reflexes gives a possibility that the robot can feel and exploit aerodynamic forces on its wings to potentially contribute to the agility and stability during flight. The evolved robot exhibited target-following flight maneuver using asymmetric wing movements as well as its tail, showing robustness to external aerodynamic disturbances.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.835-845
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• 2013

Association rule of data mining techniques is the method to quantify the relevance between a set of items in a big database, andhas been applied in various fields like manufacturing industry, shopping mall, healthcare, insurance, and education. Philosophers of science have proposed interestingness measures for various kinds of patterns, analyzed their theoretical properties, evaluated them empirically, and suggested strategies to select appropriate measures for particular domains and requirements. Such interestingness measures are divided into objective, subjective, and semantic measures. Objective measures are based on data used in the discovery process and are typically motivated by statistical considerations. Subjective measures take into account not only the data but also the knowledge and interests of users who examine the pattern, while semantic measures additionally take into account utility and actionability. In a very different context, researchers have devoted a lot of attention to measures of confirmation or evidential support. The focus in this paper was on asymmetric confirmation measures, and we compared confirmation measures with basic association thresholds using some simulation data. As the result, we could distinguish the direction of association rule by confirmation measures, and interpret degree of association operationally by them. Futhermore, the result showed that the measure by Rips and that by Kemeny and Oppenheim were better than other confirmation measures.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.1-11
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• 2015

This study uses the contingent valuation method to estimate the switching cost for adopting the MVNO service. The findings are as follows.: First, Willingness To Switch(WTS) increases as users' using pattern and perceived degree of MVNO service, but satisfaction with current service provider does not play a significant role in predicting Switching Cost. This means that as amount of money users can save exceeds a certain level, users decide to willingly change their service provider to MVNO regardless of their level of satisfaction with current service provider. Second, there are differences in WTS among service subscribers in SKT, KT and LGU+. It means that there will be a difference in the tendency to switch to MVNO among subscribers of service providers. This study suggest the following mangerial perspective to effectively promote the MVNO and boost the MVNO market for activation of mobile data services.: First, MVNOs are better off applying differentiated pricing scheme at attractive rates than using a differentiation of service product and quality. Second, regulators should consider how to implement an MVNO regulatory policy when there is an asymmetric customer loyalty among MNOs. This research will be used to set the MVNO's pricing strategy and to build up a successful regulatory policies.