• Journal of Digital Convergence
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• v.20 no.3
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• pp.349-357
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• 2022

Drum Set are representative instruments that use grips in modern popular music. Depending on how and how clearly you hold the basic grip, it also affects your performance ability. The purpose of this study is to analyze the characteristics, strengths, and weaknesses of each grip, derive the resulting complex effects, and present practical application plans to the drummers. The research method is largely divided into traditional and matched grips, and in detail, German, American, French, and hybrid styles are included to analyze the performance method utilized. It also refers to the grip method of all drummers from the 1930s to the present, which was registered in Drummer World, an overseas drum site. This study proposed several application plans by classifying and analyzing the most basic grip methods in drum set in detail. I was able to see that the performance impact was different depending on the grip, and I think it will be more helpful for future performances if I understand both the positive and adverse functions of each grip and play it.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.153-153
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• 2022

Large-scale and accurate observations at fine spatial resolution through a means of remote sensing offer an effective tool for capturing rainfall variability over the traditional rain gauges and weather radars. Although satellite rainfall products (SRPs) derived using two major estimation approaches were evaluated worldwide, their practical applications suffered from limitations. In particular, the traditional top-down SRPs (e.g., IMERG), which are based on direct estimation of rain rate from microwave satellite observations, are mainly restricted with their coarse spatial resolution, while applications of the bottom-up approach, which allows backward estimation of rainfall from soil moisture signals, to novel high spatial resolution soil moisture satellite sensors over South Korea are not introduced. Thus, this study aims to evaluate the performances of a state-of-the-art bottom-up SRP (the self-calibrated SM2RAIN model) applied to the C-band SAR Sentinel-1, a statistically downscaled version of the conventional top-down IMERG SRP, and their integration for a targeted high spatial resolution of 0.01° (~ 1-km) over central South Korea, where the differences in climate zones (coastal region vs. mainland region) and vegetation covers (croplands vs. mixed forests) are highlighted. The results indicated that each single SRP can provide plus points in distinct climatic and vegetated conditions, while their drawbacks have existed. Superior performance was obtained by merging these individual SRPs, providing preliminary results on a complementary high spatial resolution SRP over central South Korea. This study results shed light on the further development of integration framework and a complementary high spatial resolution rainfall product from multi-satellite sensors as well as multi-observing systems (integrated gauge-radar-satellite) extending for entire South Korea, toward the demands for urban hydrology and microscale agriculture.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of the Korean Society of Costume
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• v.58 no.10
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• pp.1-20
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• 2008

The purpose of this study is to analyze the formative characteristic of modern Tap dance costume according to its origin and kinds. For this purpose, the study explored the review of literature focusing on the historical back ground of Tap dance and investigated into the kinds of modern tap dance and the formative feature of the tap dance costume. Costumes of leading tap dancers in representative performances and movies are analyzed. The results are summarized as follows: The kinds of current tap dance could be categorized as three types of Jazz Tap Dance, Rhythm & Funk Tap Dance, Irish tap Dance as their development origin. The Tap dance widely distributed through the U.S. Hollywood movie, The Jazz Tap Dance costume was composed of magnificent and luxurious design applying the high fashion of the 1930s and 1950s in the male and female costumes. The U.S. Blacks' tap dance, Rhythm & Funk Tap costume had a close relation with resistant blacks' culture, and showing the type of free dressing not bound by previous tap dance dress. The Irish Tap Dance originated from Irish folk dance displayed the tap dance embroidered costume using the Irish traditional pattern. This study systemized the characteristic of the tap dance costume by kind, and explored the dress revealed at the tap dance as a symbolic system to the cultural zone where the dance is made.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.5
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• pp.18-24
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• 2010

This paper propose a dual-layer beam-forming technique for MIMO-OFDM systems. Dual-layer beam-forming is a capacity enhancing technique to transmit two streams of source data with more than two transmit and receive antennas. Beamforming is a technique to enhance the link-level performances gain using antenna array with the small inter element distance. The proposed scheme can obtain both high capacity of spatial multiplexing and antenna array gain of beamforming for MIMO-OFDM systems. Therefore, it provides better BER performance than the traditional spatial multiplexing and beamforming techniques under the same simulation environment.

• Journal of Advanced Navigation Technology
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• v.1 no.1
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• pp.70-80
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• 1997

In this paper, the performances of two noncoherent code tracking loops, i. e., traditional code tracking loop(TCTL) and modified code tracking loop(MCTL) are analyzed and compared in a CDMA mobile environment. Closed-form formulas for steady-state jitter variance are derived analytically for the two schemes as a function of the pulse shaping filter, timing offset, signal-to-interference ratio, and loop bandwidth. The design issues of the loop filter are also addressed with emphasis on the second-order tracking loop. Finally, the degradation of BER performance due to timing errors is examined in a CDMA reverse link for IMT-2000 designed by ETRI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.855-870
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• 2020

Windows are key components of building facades. Detecting windows, crucial to 3D semantic reconstruction and scene parsing, is a challenging task in computer vision. Early methods try to solve window detection by using hand-crafted features and traditional classifiers. However, these methods are unable to handle the diversity of window instances in real scenes and suffer from heavy computational costs. Recently, convolutional neural networks based object detection algorithms attract much attention due to their good performances. Unfortunately, directly training them for challenging window detection cannot achieve satisfying results. In this paper, we propose an approach for window detection. It involves an improved Faster R-CNN architecture for window detection, featuring in a window region proposal network, an RoI feature fusion and a context enhancement module. Besides, a post optimization process is designed by the regular distribution of windows to refine detection results obtained by the improved deep architecture. Furthermore, we present a newly collected dataset which is the largest one for window detection in real street scenes to date. Experimental results on both existing datasets and the new dataset show that the proposed method has outstanding performance.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.337-343
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• 2016

The core decisions of bulk shipping businesses can be summarized as the timing and the choice of period for which carrying capacity is traded. In particular, frequent decisions to trade freight either with repeated spot transactions or with a one-off long-term deal critically impact business performance. Even though a variety of freight trading strategies can be employed to facilitate the decisions, chartering practitioners have not been active in utilizing these strategies, and academic research has rarely proposed applicable solutions. The specific properties of freight as a tradable commodity are not properly reflected in existing studies, and limitations have been reported in their application to the real world. This research focused on the establishment of applicable freight trading strategies by taking into account two properties of freight: time perishability and term-dependant pricing. In addition to traditional trading strategies, artificial neural networks were applied for the first time to the test of freight trading strategies. The performances of the trading strategies were measured and compared to produce a remarkable outperformance of the ANN. This research is expected to make a significant contribution to chartering practices by enhancing the quality of chartering decisions and eventually enabling the effective management of freight rate risk. In addition to methodological expansion, the result will propose a way to approach the controversial issue of freight market efficiency.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.367-378
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• 2016

Thrust Vectoring is a dynamic feature that offers many benefits in terms of maneuverability and control effectiveness. Thrust vectoring capabilities make the satisfaction of take-off and landing requirements easier. Moreover, it can be a valuable control effector at low dynamic pressures, where traditional aerodynamic controls are less effective. A numerical investigation of Fluidic Thrust Vectoring (FTV) is completed to evaluate the use of fluidic injection to manipulate flow separation and cause thrust vectoring of the primary jet thrust. The methodology presented is general and can be used to study different techniques of fluidic thrust vectoring like shock-vector control, sonic-plane skewing and counterflow methods. For validation purposes the method will focus on the dual-throat nozzle concept. Internal nozzle performances and thrust vector angles were computed for several range of nozzle pressure ratios and fluidic injection flow rate. The numerical results obtained are compared with the analogues experimental data reported in the scientific literature. The model is integrated using a finite volume discretization of the compressible URANS equations coupled with a Spalart-Allmaras turbulence model. Second order accuracy in space and time is achieved using an ENO scheme.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.1-12
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• 2017

Recently, the Go game has been performed between the 'AlphaGo' of the DeepMind and Lee Sedol, a famous professional Go-player of Korea, which leads to arise a lot of interests in the AI (Artificial Intelligence) research area. Based on the Fuzzy logic of the AI, we have also developed another game's AI, .i.e., the Yutnori game, one of Korean traditional board games. However, it is not easy and simple to consider all the cases of the Yutnori game since it is a non-perfect information game in terms of the AI. Thus, we have developed the Fuzzy-logic-based AI which tries to simulate humans' selections, meaning that the suggested AI has focused on the humans' choices depending on diverse situations in the Yutnori. With our extensive simulations using the suggested Yutnori AI, we have analyzed its performances with respect to 10 Yutnori situations among various scenarios. In conclusion, our suggested AI have demonstrated that 6 out of 10 situations are exactly same with the humans' choices and the rest 4 cases are also similar to that of human's, which reveals that our Fuzz-logic-based Yutnori AI can effectively simulate human's choices.