• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.507-512
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• 2001

Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

• Therapeutic Science for Rehabilitation
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• v.10 no.1
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• pp.19-35
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• 2021

Objective : This study aimed to systematically examine studies on the life-space mobility in community-dwelling elderly and analyze and summarize the research trends. Methods : The Embase and PubMed databases were searched for articles on the life-space mobility of community-dwelling elderly published between January 2010 and January 2020. Based on the selection and exclusion criteria of the 335 articles, a total of 27 articles were finally selected and analyzed. Results : As a results, 11 (40.7%) cohort studies had evidence level II. This study showed that the participants in the studies were healthy elderly (81.5%), and the University of Alabama Life-Space Assessment (UAB-LSA) used the most participants (88.9%). Of the foci of the 27 finally selected studies, 8 (29.6%) were physical, 8 (29.6%) were psychosocial, 6 (22.2%) were cognitive, and 2 (7.4%) were social, and 3 (11.1%) were others. The life-space mobility of the elderly needs to be analyzed from a multidimensional point of view, and not based on a single factor such as the physical, cognitive, psychosocial, or social. Conclusion : The results of this study are expected to verify causality through the study of life-space mobility for the elderly staying in various communities and provide future directions for the study on the mobility of the elderly's and the development of community-based intervention programs.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.183-193
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• 2009

Both On-Line Analytical Processing (OLAF) data cubes and Statistical Databases (SDBs) deal with multidimensional data sets. and both are concerned with statistical summarizations over the dimensions of the data sets. However, there is a distinction between the two that can be made. While SDBs are usually derived from other base data, OLAF data cubes often represent directly the base data. In other word, the base data of SDBs are the macro-data, whereas the core cubiod data in OLAF data cubes are the micro-data. The base table in OLAF is used to populate the data cube with values of the measure attribute, and each record in the base tables is used to populate a cell of the core cuboid. The fact that OLAF data cubes mostly represent the micro-data may make some records be absent in the base table. Some cells of the core cuboid remain empty, if corresponding records are absent in the base table. Wang and others proposed a method for securing OLAF data cubes against privacy breaches. They assert that the proposed method does not depend on specific types of aggregation functions. In this paper, however, it is found that their assertion on aggregate functions is wrong whenever any cell of the core cuboid remains empty. The objective of this study is to design an inference control process in OLAF data cubes which rectifying Wang's error.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.55-67
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• 2016

Purpose: The aims of this were to analyse the quantitative research trends and describe the factors influencing health related to quality of life (HRQoL) and instruments used to HRQoL after Intensive care units (ICU) discharge. Methods: This study were included 84 published papers regarding HRQoL after ICU discharge from initial data to December 2015. Results: The majority of papers were performed abroad. Only 4 papers with regard to HRQoL of ICU survivors were performed by nurses. 36 studies (42.8%) were used to measure HRQoL ICU survivors using the SF-36. 29 studies (34.5%) were used to measure HRQoL at 3~6 months after ICU discharge. Older age, longer length of stay at ICU, severity of illness, anxiety and depression were main risk factors to lower HRQoL in ICU patients. Conclusions: This study provides a better understanding of quality of life follwing critical illness. Therefore, further stduy is needed to develop patient centered intervention considered patients'health status and recovery phase. Additionally, large prospective multicenter cohort studies should be required.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• 한국노년학
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• v.36 no.4
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• pp.1003-1024
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• 2016

The human rights of older people have gotten more attention recently in South Korea, a country that is in transition to a super-aged society. This study aimed to systematically review studies on elder abuse and related factors among community-dwelling older adults in South Korea over twenty years (1994-2016). We searched major databases (Riss, DBpia, KISS, KMbase, and PubMed) and identified published studies relevant to the topic. Based on inclusion and exclusion criteria related to study quality, a total of 31 studies were selected for this review. We examined types, measurements, and risk factors of elder abuse as well as study designs in the selected studies, guided by Johannesen's theoretical framework on elder abuse. All of the reviewed studies on elder abuse in Korea were cross-sectional studies, most of which focused on older people living in urban areas, using a non-random sampling method. All of the studies focused on certain types of elder abuse only. Some adopted elder-abuse instruments that were not validated, and others used self-developed instruments without psychometric tests. As for the risk factors of elder abuse in South Korea, the physical and mental health of the victims and aggressors impacted the risk of elder abuse, but general sociodemographic factors such as age, sex, and education were less likely to be related to the risk. In addition, decreasing caregiver burden and building elder-friendly communities are important for the prevention of elder abuse. Needed are further empirical studies on elder abuse with a theoretical framework that gives consideration to the unique sociocultural contexts of Korea. It is also recommended to develop instruments to measure elder abuse reflecting the sociocultural contexts of Korea, and to examine the multi-dimensional risk factors of elder abuse.