• SUVANNABHUMI
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• v.8 no.1
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• pp.121-146
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• 2016

Defining key characteristics of Southeast Asia requires historical interpretation. Southeast Asia is a diverse and complicated region, but some of modern history's "grand narratives" serve to unify its historical experience. At a minimum, the modern history of the region involves decisive encounters with universal religions, the rise of Western colonialism, the experience of world wars, decolonization, and the end of the "cycle of violence". The ability of the region's peoples to adapt to these many challenges and successfully build new nations is a defining feature of Southeast Asia's place in the global stage. This paper will begin with a question: is it possible to develop a hermeneutic of "expedience" as a way to interpret the region's history? That is, rather than regard the region from a purely Western, nationalist, "internalist" point of view, it would be useful to identify a new series of interpretative contexts from which to begin scholarly analysis. In order to contextualize this discussion, the paper will draw upon the writings of figures who explored the region before knowledge about it was shaped by purely colonist or nationalist enterprises. To this end, particular attention will be devoted to exploring some of John Furnivall's ways of conceptualizing Southeast Asia. Investigating Furnivall, a critic of colonialism, will be done in relation to his historical situation. Because Furnivall's ideas have played a pivotal role in the interpretation of Southeast Asia, the paper will highlight the intellectual history of the region in order to ascertain the value of these concepts for subsequent historical interpretation. Ultimately, the task of interpreting the region's history requires a framework which will move beyond the essentializing orientalist categories produced by colonial scholarship and the reactionary nation-building narratives which followed. Instead, by beginning with a mode of historical interpretation that focuses on the many realities of expedience which have been necessary for the region's peoples, it may be possible to write a history which highlights the extraordinarily adaptive quality of Southeast Asia's populations, cultures, and nations. To tell this story, which would at once highlight key characteristics of the region while showing how they developed through historical encounters, would go a long way to capturing Southeast Asia's contribution's to global development.

• Korea Trade Review
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• v.48 no.4
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• pp.169-188
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• 2023

The increase in assertive and unilateral measures represents a key feature of the recent global trade environment. Against this backdrop, the EU is pushing to introduce the so-called "anti-coercion instrument(the instrument)," which aims to allow unilateral countermeasures in the event of economic coercion or threats from third countries. This paper examines the recent assertive trade environment and the legislative background of the instrument. It evaluated the necessity of and concerns arising from the instrument by comparing the existing EU trade policy, i.e., Trade Barrier Regulation (TBR). In addition, the paper aims to analyze the permissibility of the instrument under the WTO system, especially in the context of the principle of "strengthening of the multilateral system." Finally, the paper draws implications of the instrument in terms of our domestic policies that can effectively address economic threats or trade friction in the growing geopolitical crisis.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.2
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• pp.139-148
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• 2020

The most important factor affecting the berthing energy generated when a ship berths is the berthing velocity. Thus, an accident may occur if the berthing velocity is extremely high. Several ship features influence the determination of the berthing velocity. However, previous studies have mostly focused on the size of the vessel. Therefore, the aim of this study is to analyze various features that influence berthing velocity and determine their respective importance. The data used in the analysis was based on the berthing velocity of a ship on a jetty in Korea. Using the collected data, machine learning classification algorithms were compared and analyzed, such as decision tree, random forest, logistic regression, and perceptron. As an algorithm evaluation method, indexes according to the confusion matrix were used. Consequently, perceptron demonstrated the best performance, and the feature importance was in the following order: DWT, jetty number, and state. Hence, when berthing a ship, the berthing velocity should be determined in consideration of various features, such as the size of the ship, position of the jetty, and loading condition of the cargo.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.544-551
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• 2023

Speech enhancement used to improve the perceptual quality and intelligibility of noise speech has been studied as a method using a complex-valued spectrum that can improve both magnitude and phase in a method using a magnitude spectrum. In this paper, a study was conducted on how to apply attention mechanism to complex-valued spectrum-based speech enhancement systems to further improve the intelligibility and quality of noise speech. The attention is performed based on additive attention and allows the attention weight to be calculated in consideration of the complex-valued spectrum. In addition, the global average pooling was used to consider the importance of the feature map. Complex-valued spectrum-based speech enhancement was performed based on the Deep Complex U-Net (DCUNET) model, and additive attention was conducted based on the proposed method in the Attention U-Net model. The results of the experiments on noise speech in a living room environment showed that the proposed method is improved performance over the baseline model according to evaluation metrics such as Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short Time Object Intelligence (STOI), and consistently improved performance across various background noise environments and low Signal-to-Noise Ratio (SNR) conditions. Through this, the proposed speech enhancement system demonstrated its effectiveness in improving the intelligibility and quality of noisy speech.

• Journal of Arbitration Studies
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• v.20 no.3
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• pp.71-91
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• 2010

ADR is alternative dispute resolution that includes mediation, adjudication, arbitration, conciliation and ombudsman schemes. ADR may be an alternative to going to court or to a tribunal. The main types of ADR are conciliation, arbitration or mediation and ADR is divided into national leading ADR and private lading ADR and national leading ADR includes court-annexed ADR and administrative ADR. Court-annexed ADR has become a well established feature of the judicial systems on a global basis. The bulk of court-annexed ADR in Glove is by way of mediation. Thus each nation takes part in ADR by court involvement and Enactment of ADR-related Laws. And the involvement of nations have both the regulative character and promotive character in ADR. In addition to the national leading ADR, the private leading ADR also must be activated as United Kingdom. Thus this paper deals with national leading ADR and private leading ADR and the purpose of this paper is to contribute to the activation of ADR by studying the promotion and limited the involvement of nation in ADR and private leading ADR in United Kingdom.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1102-1105
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• 2004

In this paper, the problem of a viewer's head tracking in a desktop-based interactive stereoscopic display system is considered. A fast and low-cost approach to the problem is important for such a computing environment. The system under consideration utilizes a shuttle glass for stereoscopic display. The proposed method makes use of an image taken from a single low-cost video camera. By using a simple feature extraction algorithm, the obtained points corresponding to the image of the user-worn shuttle glass are used to estimate the glass center, its local 'yaw' angle, as measured with respect to the glass center, and its global 'yaw' angle as measured with respect to the camera location. With these estimations, the stereoscopic image synthetic program utilizes those values to interactively adjust the two-view stereoscopic image pair as displayed on a computer screen. The adjustment is carried out such that the so-obtained stereoscopic picture, when viewed from a current user position, provides a close-to-real perspective and depth perception. However, because the algorithm and device used are designed for fast computation, the estimation is typically not precise enough to provide a flicker-free interactive viewing. An error concealment method is thus proposed to alleviate the problem. This concealment method should be sufficient for applications that do not require a high degree of visual realism and interaction.

• Journal of Power Electronics
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• v.17 no.2
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• pp.411-421
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• 2017

An approach based on a 2D lumped model is presented to quantify the voltage transfer gain (VTG) in power converter low power planes. The advantage of the modeling approach is the ease with which typical noise reduction devices such as decoupling capacitors or ferrite beads can be integrated into the model. This feature is enforced by a new modular approach based on effective matrix partitioning, which is presented in the paper. This partitioning is used to decouple power plane equations from external device impedance, which avoids the need for rewriting of a whole set of equation at every change. The model is quickly solved in the frequency domain, which is well suited for an automated layout optimization algorithm. Using frequency domain modeling also allows the integration of frequency-dependent devices such inductors and capacitors, which are required for realistic computation results. In order to check the precision of the modeling approach, VTGs for several layout configurations are computed and compared with experimental measurements based on scattering parameters.