• Journal of Broadcast Engineering
• /
• v.14 no.2
• /
• pp.144-153
• /
• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

• The Journal of the Korea Contents Association
• /
• v.18 no.9
• /
• pp.125-140
• /
• 2018

Due to rapid development of semiconductor technology, embedded systems have been developed from single-functional system to the multi-functional system. The system composed of software that has different criticality level is called Mixed-Criticality System. Currently, the project related to the Mixed-Criticality System is accelerating the efforts to seek the development direction and take technical initiatives led by EU and USA where the related industry has developed, but the movement in Korea is yet insignificant. Therefore, it is urgent to perform the research and project of various basic technologies to occupy the initiative for the related technology and market. In this paper, we analyze the trends of major project researches and developments related to the MCS. First, after defining the definition of the MCS and system model, we analyze the underlying technology constituting the MCS. In addition, we analyze the project trends of each country researching MCS and discuss the future research areas. Through this study, it is possible to grasp the research trends of the world in order to establish the research direction of the MCS and to lay the foundation for the integration into the military system.

• The Journal of the Korea Contents Association
• /
• v.20 no.10
• /
• pp.615-629
• /
• 2020

Conducting Focus Group Interview (FGI), this study examined the roles and discourses of cryptocurrency's online communities and media (legacy media and YouTube), and based on this, the study proposed the direction of cryptocurrency policy. By reviewing previous literature, this study analyzed the characteristics of investors, the online community, and YouTube, which is an investment environment factor. The study figured out the purpose of use and role of the community via interviews with cryptocurrency professional investors and online community members and analyzed main discussion themes of the five top-ranked YouTube channels related to cryptocurrency with the highest number of subscribers. The results suggested that cryptocurrency's investment was led by those who are in their 20s and 30s, the investors preferred and trusted information on new media than legacy media. The online community played the role of emotional homogeneity and empathy, and YouTube mainly performed the informational role. As a result of discourse analysis and interviews, this study argued that the legal stability of cryptocurrency's policy and protection of individual investors are needed. This study's significance indicates that it used various research methods such as literature research, interviews, content analysis of community/YouTube to analyze the informational role and emotional aspects of new media and suggested policy direction of the digital new deal blockchain technology and the fairness of financial industry.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.1
• /
• pp.75-84
• /
• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.5
• /
• pp.191-205
• /
• 2020

This study examined the possibility of utilizing next-generation technology, such as Virtual Reality or AI robots, in the long-term care facilities for the elderly. For the study, the Focus Group Interview was conducted in three different groups of 14 participants (care workers, social workers, and directors of long-term care facilities for the elderly). The analysis revealed a total of three topics, eight categories, and 26 sub-categories. The main results of the study showed that the use of next-generation technology could assist the psychological and emotional stability, provide curiosity and interest, and relieve the desire for physical activity for the elderly. In addition, for long-term care services staff, it could provide useful services for the elderly with physical constraints, facilitate effective management of the elderly roaming around, and enhance emotional support services. Finally, it could also help directors of long-term care facilities promote their services, educate staff, and keep up with current trends. Participants expressed concerns about the introduction of new technologies, but they generally expected that the application of next-generation technology would be positive for the elderly as well as for care workers and directors of long-term care facilities. Therefore, the use of next-generation technology in long-term care facilities for the elderly will also help develop gerontechnology.

• Journal of Korea Multimedia Society
• /
• v.5 no.6
• /
• pp.712-729
• /
• 2002

In this study, we evaluated degree of importance of e-marketplace solution selection factors. Factor analysis was conducted to find out relationships among various variables which come from literature survey. The result shows that 16(sixteen) -selection variables regarding solution characteristics could be grouped into four areas 'flexibility', 'ease of use', 'security', and 'economy'. And 11(eleven) selection variables regarding to vendor characteristics could be grouped into three areas, 'vendor's support', vendor's general situation', and 'vendor's business accomplishment`. Through various analysis, we found important factors for 3 types of operational companies, buyer-biased, seller biased and neutral. 'Security for data item' was showed as the most important factor for all kind of B2B operational companies. For buyer-biased companies, additional supporting manpower, solution education, and educational cost are shown to be more important factors than others. Place of education, education hours and education level are important for 'Neutral' companies. And the factor 'market share of vendor' are important for 'seller biased' companies.

• Journal of Korea Multimedia Society
• /
• v.10 no.4
• /
• pp.527-536
• /
• 2007

This paper proposes a 3D fashion design system that generates a 3D clothes model by using 2D patterns of clothes and drapes the 3D clothes model on a 3D human model. In the proposed system, 2D patterns of clothes are designed by selecting comer points of 2D mesh. After designing 2D patterns, a 3D clothes model is designed by describing the control points to be connected between 2D patterns. The proposed system reads a 3D human body model file and the designed 3D clothes model and creates a 3D human model putting on the clothes by using the mass-spring model based physical simulation. It calculates collision and reaction between the triangles of human body model and those of clothes for realistic simulation. Because the number of triangles is very large, the collision and reaction processing need a lot of time. To solve this problem, the proposed system decreases the number of collision and reaction processing by using the Octree space subdivision technique. It took a few seconds for generating a 3D human model putting on the designed 3D clothes.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.9
• /
• pp.514-526
• /
• 2004

Microarray is a new technique for gene expression experiment, which has gained biologist's attention for recent years. This technology enables us to obtain hundreds and thousands of expression of gene or genotype at once using microarray Since it requires manual work to analyze patterns of gene expression, we want to develop an effective and automated tools to analyze microarray image. However it is difficult to analyze DNA chip images automatically due to several problems such as the variation of spot position, the irregularity of spot shape and size, and sample contamination. Especially, one of the most difficult problems in microarray analysis is the block and spot addressing, which is performed by manual or semi automated work in all the commercial tools. In this paper we propose a new algorithm to address the position of spot and block using a new concept of regular structure grid searching. In our algorithm, first we construct maximal I-regular sequences from the set of input points. Secondly we calculate the rotational angle and unit distance. Finally, we construct I-regularity graph by allowing pseudo points and then we compute the spot/block address using this graph. Experiment results showed that our algorithm is highly robust and reliable. Supplement information is available on http://jade.cs.pusan.ac.kr/~autogrid.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.318-326
• /
• 2011

The purpose of this study is to investigate whether standardized patient(SP) can be used as a reliable examiner in Objective Structured Clinical Examination(OSCE). 4 SPs and 4 faculties who have more than 2 years experience of OSCE scoring were selected. For 1 assignment 2 members of faculty and 2 SPs were designated as raters. SPs were educated for assessing 2 technical skills, male Foley catheter insertion and wound dressing, for 8 hours (4 hours / day, each topic). The definition, method, cautions and complications for each of procedural skills were covered in the education. Theoretical lectures, video learning, faculty demonstration and practical training on mannequins were employed. The 8 raters were standardized for an hour with simulated OSCE scoring using previous videos on the day before the OSCE. Each assessment was composed of 14 checklists and 1 global rate. The allotted time for each assignment was 5minutes and for evaluation time 2 minutes per student. The evaluation from the faculty and SPs were compared and analyzed with the GENOVA program. The overall generalizability coefficient (G coefficient) was 0.839 from two cases of OASTS. The reliability of the raters was high, 0.946. The inter-rater agreement between faculty group and SP group was 0.949 for checklist and 0.908 for global rating. Therefore SPs can play a role of raters in OSCE for procedural skills, if they are given the appropriate training.

• KIISE Transactions on Computing Practices
• /
• v.21 no.12
• /
• pp.774-779
• /
• 2015

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner using Apache Spark, an in-memory high speed cluster computing environment, which is effective for sequencing and iterating component reasoning jobs. The proposed reasoner can not only check the integrity of a large-scale spatial knowledge base representing topological and directional relationships between spatial objects, but also expand the given knowledge base by deriving new facts in highly efficient ways. In general, qualitative reasoning on topological and directional relationships between spatial objects includes a number of composition operations on every possible pair of disjunctive relations. The proposed reasoner enhances computational efficiency by determining the minimal set of disjunctive relations for spatial reasoning and then reducing the size of the composition table to include only that set. Additionally, in order to improve performance, the proposed reasoner is designed to minimize disk I/Os during distributed reasoning jobs, which are performed on a Hadoop cluster system. In experiments with both artificial and real spatial knowledge bases, the proposed Spark-based spatial reasoner showed higher performance than the existing MapReduce-based one.