• Journal of Korea Game Society
• /
• v.14 no.2
• /
• pp.77-84
• /
• 2014

Presence of soft shadow effects from an area light makes virtual scenes look more realistic. However, since computation of soft shadow effects takes a long time, acceleration methods are required to apply it to real-time 3D applications. Many researches assumed that area lights are white rectangles. We suggest a new method which renders soft shadows under the area light source having arbitrary shape and color. In order to approximate visibility test, we use a shadow mapping result near a pixel. Complexity of shadow near a pixel is used to determine degree of precision of our visibility estimation. Finally, our method can present more realistic soft shadows for the area light that have more general shape and color in real-time.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.1
• /
• pp.82-88
• /
• 2017

Recently recommendation methods need personalization and diversity as well as accuracy whereas the traditional researches have been mainly focused on the accuracy of recommendation in terms of quality. The diversity of recommendation is also important to people in terms of quantity in addition to quality since people's desire for content consumption have been stronger rapidly than past. In this paper, we pay attention to similarity of data gathered simultaneously among different types of contents. With this motivation, we propose an enhanced recommendation method using correlation analysis with considering data similarity between two types of contents which are movie and music. Specifically, we regard folksonomy tags for music as correlated data of genres for movie even though they are different attributes depend on their contents. That is, we make result of new recommendation movie items through mapping music folksonomy tags to movie genres in addition to the recommendation items from the typical collaborative filtering. We evaluate effectiveness of our method by experiments with real data set. As the result of experimentation, we found that the diversity of recommendation could be extended by considering data similarity between music contents and movie contents.

• Journal of the Korean Geosynthetics Society
• /
• v.5 no.2
• /
• pp.9-15
• /
• 2006

The numerical analysis program using artificial displacement method is developed to analyze the deformation behavior of excavated behind ground of retention wall. The elasto-plastic model suggested by Drucker-Prager was used to represent soil behavior and the model's solution was obtained from the return mapping method. To validate of the program, the predicted results by the numerical analysis and the measured results by a field test are compared. The results of numerical analysis showed good agreement with the measured results in field and theoretical values.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2042-2059
• /
• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4443-4462
• /
• 2020

This paper proposes a new framework of reversible data hiding scheme for absolute moment truncation coding (AMBTC) compressed images. AMBTC-based RDH can be applied to optical remote sensing (ORS) image transmission, which achieves target region preservation and image compression simultaneously. Existing methods can be concluded as two types. In type I schemes, stego codes mimic the original AMBTC format where no file bloat occurs, yet the carried secret data is limited. Type II schemes utilize predication errors to recode quantity levels of AMBTC codes which achieves significant increase in embedding capacity. However, such recoding causes bloat inside stego format, which is not appropriate in mentioned ORS transmission. The proposed method is a novel type I RDH method which prevents bloat inside AMBTC stego codes with significant improvement in embedding capacity. The AMBTC compressed trios are grouped into two categories according to a given threshold. In smooth trio, the modified low quantity level is constructed by concatenating Huffman codes and secret bits. The reversible contrast mapping (RCM) is performed to complex trios for data embedment. Experiments show that the proposed scheme provides highest payload compared with existing type I methods. Meanwhile, no expansion inside stego codes is caused.

• Wind and Structures
• /
• v.38 no.4
• /
• pp.231-244
• /
• 2024

As wind farms expand into low wind speed areas, an increasing number are being established in mountainous regions. To fully utilize wind energy resources, it is essential to understand the details of mountain flow fields. Reconstructing the wind speed field in complex terrain is crucial for planning, designing, operation of wind farms, which impacts the wind farm's profits throughout its life cycle. Currently, wind speed reconstruction is primarily achieved through physical and machine learning methods. However, physical methods often require significant computational costs. Therefore, we propose a Full Convolutional Neural Network (FCNN)-based reconstruction method for mountain wind velocity fields to evaluate wind resources more accurately and efficiently. This method establishes the mapping relation between terrain, wind angle, height, and corresponding velocity fields of three velocity components within a specific terrain range. Guided by this mapping relation, wind velocity fields of three components at different terrains, wind angles, and heights can be generated. The effectiveness of this method was demonstrated by reconstructing the wind speed field of complex terrain in Beijing.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.16 no.12
• /
• pp.2226-2240
• /
• 1992

This paper studies the applicability of the method of caustics into anisotropic materials under mode I and mixed static loading conditions and introduces the procedure to obtain stress intensity factors(S.I.F.) in anisotropic materials by the method of caustics. The mapping equations for initial and caustic curves in anisotropic materials were introduced and their computer graphical images were compared to the experimental ones to check the validity of the mapping equations proposed in this paper. The agreement between them was found to satisfactory. Two kinds of method to determine S.I.F. in anisotropic materials by the method of caustics were proposed in this paper and applied into the orthotropic materials under various loading conditions. In the case of mode I loading condition, the S.I.F.'s obtained by this paper's methods were found to be quite similar to the results by other method, boundary element method(B.E.M) and in the case of mixed loading condtion, the S.I.F's by this paper and B.E.M. showed a little differences(2.2-24.4%) with respect to the slanted angle of crack.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.16 no.11 s.102
• /
• pp.1123-1130
• /
• 2005

In this paper, we propose an improved side information processing scheme which is important in the sub-block phase weighting(SPW) method for the peak-to-average power ratio(PAPR) reduction. SPW method is to divide the input OFDM subchannels into several subblocks and to multiply phase weighting with each subblocks, properly for the reduction of the peak power. SPW method is similar to the conventional PTS method when the number of sub-carriers, signal modulation format and the number of subblocks are the same. However, unlike the conventional PTS(Partial Transmit Sequence) and SLM(Selected Mapping) method using many stages of IFFT(Inverse Fast Fourier Transform), SPW method only needs one IFFT. Although PAPR can be reduced by SPW method, complex computation burden still remains. In this paper the flipping algorithm and the full iteration algorithm are used f3r the phase control method. Through the computer simulation, we analyze and discuss the properties and the performance of the suggested method.

• Journal of the Korean Society of Safety
• /
• v.32 no.5
• /
• pp.168-178
• /
• 2017

In order to prevent major and chemical accidents, some of the plants which would like to install and operate hazard chemicals handling facilities must submit Off-site Consequence Analysis due to recent arisen leak accidents since 2015. A lot of chemical industrials choose gas detectors as mitigation equipment to early detect gas vapor. The way of placement of gas detectors has two methods; Code-based Design(CBD) and Performance-based Design. The CBD has principles for gas detectors to be installed with consideration for the place that is expected to accumulate gas, and the leak locations according to legal standards and technical guidelines, and has a possibility to be unable to detect by these rules to locate gas detectors by vapor density information. The PBD has two methods; a Geographic Method and Scenario based Method. The Scenario-based Method has been suggested to make up for the Geographic Coverage Method. This Scenario-based Method draw the best optimum placement of gas detectors by considering leak locations, leak speed information, leak directions and etc. However, the domestic placement guidelines just refers to the CBD. Therefore, this study is to compare existing placement location of gas detectors by the domestic CBD with placement locations, coverages and the number of gas detectors in accordance with the Scenario-based Method. Also this study has measures for early detecting interest of Vapor Cloud and suitable placement of gas detectors to prevent chemical accidents. The Phast software was selected to simulate vapor cloud dispersion to predict the consequence. There are two cases; an accident hole size of leak(8 mm) from API which is the highst accident hole size less than 24.5 mm, and a normal leak hole size from KOSHA Guide (1.8 mm). Detect3D was also selected to locate gas detectors efficiently and compare CBD results and PBD results. Currently, domestic methods of gas detectors do not consider any risk, but just depend on domestic code methods which lead to placement of gas detectors not to make personnels recognize tolerable or intolerable risks. The results of the Scenario-based Method, however, analyze the leak estimated range by simulating leak dispersion, and then it is able to tell tolerable risks. Thus it is considered that individuals will be able to place gas detectors reasonably by making objectives and roles flexibly according to situations in a specific plant.

• Journal of the Korean association of regional geographers
• /
• v.22 no.1
• /
• pp.251-266
• /
• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.