• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.101-109
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• 2009

Generally, depth cache and pixel cache of 3D graphics are designed by using write-back scheme for efficient use of memory bandwidth. Also, there are write after read operations of same address or only write operations are occurred frequently in 3D graphics cache. If a cache miss is detected, an access to the external memory for write back operation and another access to the memory for handling the cache miss are operated simultaneously. So on frequent cache miss situations, as the memory access bandwidth limited, the access time of the external memory will be increased due to memory bottleneck problem. As a result, the total performance of the processor or the IP will be decreased, also the problem will increase peak power consumption. So in this paper, we proposed a novel early write back cache architecture so as to solve the problems issued above. The proposed architecture controls the point when to access the external memory as to copy the valid data block. And this architecture can improve the cache performance with same hit ratio and same capacity cache. As a result, the proposed architecture can solve the memory bottleneck problem by preventing intensive memory accesses. We have evaluated the new proposed architecture on 3D graphics z cache and pixel cache on a SoC environment where ARM11, 3D graphic accelerator and various IPs are embedded. The simulation results indicated that there were maximum 75% of performance increase when using various simulation vectors.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.211-234
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• 2007

In e-business, XML is a major format of data and it is essential to efficiently process queries against XML data. XML query caching has received much attention for query performance improvement. In employing XML query caching, some efficient technique of cache replacement is required. The previous techniques considered as a replacement unit either the whole query result or the path in the query result. The former is simple to employ but it is not efficient whereas the latter is more efficient and yet the size difference among the potential victims is large, and thus, efficiency of caching would be limited. In this paper, we propose a new technique where the element in the query result is are placement unit to overcome the limitations of the previous techniques. The proposed technique could enhance the cache efficiency to a great extent because it would not pick a victim whose size is too large to store a new cached item, the variance in the size of victims would be small, and the unused space of the cache storage would be small. A technique of XML semantic cache replacement is presented which is based on the replacement function that takes into account cache hit ratio, last access time, fetch time, size of XML semantic region, size of element in XML semantic region, etc. We implemented a prototype XML semantic cache system that employs the proposed technique, and conducted a detailed set of experiments over a LAN environment. The experimental results showed that our proposed technique outperformed the previous ones.

• The Journal of Information Systems
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• v.27 no.1
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.630-636
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• 2016

The main purpose of this study was to verify if irrational belief of gambling, impulsiveness, and smartphone addiction could discriminate adolescents' gambling addiction (addiction risk group, non-addicted group). To this end, a survey was performed targeting 1,420 middle and high school students living in Jeju. In order to examine the differences between irrational belief of gambling, impulsiveness, and smartphone addiction according to gambling addiction, independent sample t-test was conducted, and to determine if irrational belief of gambling, impulsiveness, and smartphone addiction could discriminate gambling addiction, discriminant analysis was conducted. As a result, first, there were significant differences between irrational belief of gambling, impulsiveness, and smartphone addiction according to adolescents' gambling addiction, and all the variables were significantly higher in the addiction risk group than in the non-addicted group. Second, irrational belief of gambling, impulsiveness, and smartphone addiction were important explanatory variables to discriminate between the addiction risk group and the non-addicted group. In addition, as a result of examining the relative importance of the variables, irrational belief of gambling was the most important, followed by impulsiveness and smartphone addiction. Third, a discriminant function consisting of irrational belief of gambling, impulsiveness, and smartphone addiction showed a 62.5% hit ratio. This study specified the determinant factors of gambling addiction, and has presented meaningful basic data for developing programs to prevent adolescents' gambling addiction in the future.

• Journal of KIISE:Databases
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• v.27 no.1
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• pp.53-63
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• 2000

The mobile computing service market is increasing rapidly due to the development of low-cost wireless network technology and the high-performance mobile computing devices. In recent years, several methods have been proposed to effectively deal with restrictions of the mobile computing environment such as limited bandwidth, frequent disconnection and short-lived batteries. Amongst those methods, much study is being done on the caching method - among the data transmitted from a mobile support station, it selects those that are likely to be accessed in the near future and stores them in the local cache of a mobile host. Existing cache replacement methods have some limitations in efficiency because they do not take into consideration the characteristics of user mobility and spatial attributes of geographical data. In this paper, we show that the value and the semantic of the data, which are stored in the cache of a mobile host, changes according to the movement of the mobile host. We argue it is because data that are geographically near are better suited to provide an answer to a users query in the mobile environment. Also, we define spatial location of geographical data has effect on, using the spatial attributes of data. Finally, we propose two new cache replacement methods that efficiently support user mobility and spatial attributes of data. One is based on the location of data and the other on the meaningful region of data. From the comparative analysis of the previous methods and that they improve the cache hit ratio. Also we show that performance varies according to data density using this, we argue different cache replacement methods are required for regions with varying density of data.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.53-60
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• 2008

Streaming media has contributed to a significant amount of today's Internet Traffic. Like traditional web objects, rich media objects can benefit from proxy caching, but caching streaming media is more of challenging than caching simple web objects, because the streaming media have features such as huge size and high bandwidth. And to support various bandwidth requirements for the heterogeneous ubiquitous devices, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we define the 9-events of transcoding proxy using 4-atomic events. According to these events, the transcoding proxy can define the next actions. Then, we also propose the segment-based caching policy for the transcoding proxy system. The performance results show that the proposing policy have a low delayed start time, high byte-hit ratio and less transcoding data.

• Korean Journal of Psychosomatic Medicine
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• v.11 no.2
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• pp.205-213
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• 2003

Objectives: The authors intended to evaluate long-term outcome of group cognitive behavioral therapy(GCBT) for panic disorder and examined the variables to predict high end-state functioning in 12 months follow-up. Methods: 236 patients meeting DSM-IV criteria for panic disorder were assessed by STAI, ASI, BDI, BSQ, PBQ, ACQ at pre & post treatment, and were asked about the frequency of panic attacks during recent one month. We executed stepwise discriminant analysis on the clinical variables at pre treatment assessment to find the variables for discriminating between high end-state function(HES) and low end-state function(LES). Results: After GCBT, 82.6% of panic patients maintained high end-state functioning at 12 months follow-up. The results of discriminant analysis showed that BDI and BSQ at pre treatment assessment were significant variables to predict end-state functioning at 12 months follow-up. The hit ratio of discriminant analysis was 69.2%. Conclusion: These results suggest that the therapeutic effect of GCBT can be maintained through 12 months. Especially, it is likely that patients who were less depressed and who had less experienced the fear of physical symptoms at pre-treatment can maintain HES.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.664-688
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• 2011

This study aims to explore the variables which determine performance of inter-firm R&D cooperation. As the dependent variable is categorical - whether the new product developed by the inter-firm cooperation were sold or not-and the independent variables were interval, discriminant analysis was used. The independent variables were composed of degree of inter-firm cooperation, experience of cooperation, market attractiveness, R&D intensity, resources and competences of enterprise and efficiency of government support. A total of 144 responses were obtained. The results indicate that the degree or inter-firm cooperation is the best predictor of the performance, followed by market attractiveness, R&D intensity and resources/competences of enterprises. Whereas, the experience of cooperation and efficiency of government support program were not statistically significant predictors. The hit ratio or the percentage of cases correctly classified was 66.2%. We derived several implications of these findings in an effort to guide subsequent inquiry.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.44-57
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• 2002

Multiple spatial queries are defined as two or more spatial range queries to be executed at the same time. The primary processing of internet-based map services is to simultaneously execute multiple spatial queries. To improve the throughput of multiple queries, the time of disk I/O in processing spatial queries significantly should be reduced. The declustering scheme of a spatial dataset of the MIMD architecture cannot decrease the disk I/O time because of random seeks for processing multiple queries. This thesis presents query scheduling strategies to ease the problem of inter-query random seeks. Query scheduling is achieved by dynamically re-ordering the priority of the queued spatial queries. The re-ordering of multiple queries is based on the inter-query spatial relationship and the latency of query processing. The performance test shows that the time of multiple query processing with query scheduling can be significantly reduced by easing inter-query random seeks as a consequence of enhanced hit ratio of disk cache.

• Spatial Information Research
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• v.23 no.2
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• pp.69-81
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• 2015

If one can infer the residential area of SNS users by analyzing the SNS big data, it can be an alternative by replacing the spatial big data researches which result from the location sparsity and ecological error. In this study, we developed the way of utilizing the daily life activity pattern, which can be found from timeline data of tweet users, to infer the residential areas of tweet users. We recognized the daily life activity pattern of tweet users from user's movement pattern and the regional cognition words that users text in tweet. The models based on user's movement and text are named as the daily movement pattern model and the daily activity field model, respectively. And then we selected the variables which are going to be utilized in each model. We defined the dependent variables as 0, if the residential areas that users tweet mainly are their home location(HL) and as 1, vice versa. According to our results, performed by the discriminant analysis, the hit ratio of the two models was 67.5%, 57.5% respectively. We tested both models by using the timeline data of the stress-related tweets. As a result, we inferred the residential areas of 5,301 users out of 48,235 users and could obtain 9,606 stress-related tweets with residential area. The results shows about 44 times increase by comparing to the geo-tagged tweets counts. We think that the methodology we have used in this study can be used not only to secure more location data in the study of SNS big data, but also to link the SNS big data with regional statistics in order to analyze the regional phenomenon.