• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2577-2581
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• 2012

Objective: To conduct a meta-analysis to investigate the value of EBV DNA in diagnosis of nasopharyngeal cancer (NPC) in Asian populations, and provide important evidence for screening. Methods: Prospective or respective case-control or cohort studies regarding the detection role of EBV DNA for NPC were included in our study. We conducted a comprehensive literature search in PubMed, EMBASE, and the Chinese Biomedical Database (CBM database between January 1980 and March 2012. Results: A total of 18 studies with 1492 NPC cases and 2641 health controls were included. Almost of the included studies were conducted in China, and only one other conducted in Thailand. The overall results demonstrated that the pooled sensitivity, specificity, positive likelihood (+LR) and negative likelihood (-LR) were 0.73 (0.71-0.75), 0.89 (0.88-0.90), 8.84 (5.65-13.84) and 0.19(0.11-0.32), respectively. The overall EBV DNA detection showed the largest area of 0.932 under the summary receiver operator curve (SROC). The accuracy of detection by plasma for NPC (0.86) was higher than in serum (0.81), with largest areas under the SROC of 0.97 and 0.91, respectively. Conclusion: Our results demonstrated the EBV DNA detection in plasma or serum has high sensitivity and specificity in diagnosis of NPC, especially in Chinese populations with a high risk of cancer.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.549-556
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• 2008

Web-based Enterprise Intranet System is developed Object-oriented programming language and data management is constructed using RDBMS. Between Object-oriented programming language and RDBMS bring about "Object-Relational Impedance Mismatch" due to heterogeneous paradigm. To solve this kinds of problems commonly use the ORM Framework that it is converting data between incompatible type systems in databases and object-oriented programming languages, uses complex mapping metadata. It causes difficult to develop and maintain because of inflexible in changes. This paper proposed persistence framework that solve the existing complexity of ORM framework and has more flexible in evolution of database table. This persistence framework is unnecessary meta information that connecting with entity of database table and the objects, it offers users convenience of maintenance and it allows far more flexible and affordable systems to be built because of automatically code generation. The result of testing based on the proposed persistence framework with Hibernate, iBATIS, It is similar response time with iBATIS and it has more about three times faster than Hibernate. But iBATIS has problems of mass data processing.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.464-475
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• 2003

few sample objects and compressed histogram information of image databases. The histogram information is used to estimate the selectivity of spherical range queries and a small number of sample objects is used to compensate the selectivity error due to the difference of the similarity measures between meta server and local image databases. An extensive experiment on a large number of image data demonstrates that our proposed method performs well in the distributed heterogeneous environment.

• Animal Bioscience
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• v.34 no.10
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• pp.1623-1631
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• 2021

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW^0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R² = 0.39) than the NRC equation (R² = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.285-293
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• 2023

Background: Irritable bowel syndrome (IBS) is a digestive disorder characterized by abdominal discomfort or pain accompanied by a change in stool condition. Owing to its complicated mechanisms, a standard treatment for IBS has not yet been established. Yukgunja-tang (YGT) is a Korean herbal medicine known in Asia to be effective in the treatment of gastrointestinal symptoms. In this study, we will conduct a systematic review of randomized controlled trials (RCTs) to assess the efficacy and safety of YGT in IBS treatment. Methods and analysis: English databases, such as Embase, Medline (via PubMed), Allied and Complementary Medicine Database, and Cochrane Central Register of Controlled Trials, will be searched for articles published up to April 2023. Additional databases, such as five Korean, one Chinese, and one Japanese database, will be included. RCTs and quasi-RCTs will also be included in the assessment of the efficacy of YGT. The overall efficacy rate will be the primary outcome, and data such as IBS quality-of-life measurements, global symptom scores, and adverse events will be the secondary outcomes. Review Manager Version 5.3 will be used for evaluation, and the risk of bias (RoB) will be evaluated using Cochrane Collaboration's RoB tool. The Grading of Recommendations Assessment, Development, and Evaluation approach will be used to score the quality of evidence. Conclusion: This study will demonstrate the efficacy and safety of YGT for treating patients with IBS.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1244-1248
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• 2010

The previous study of Digital Broadcasting Recommendation system is based on user explicit profiling information. But user profile is always changing and the exact extraction of user profile is very important in recommendation system like Digital TV using many user interactions. This paper is studied of realtime user profiles aggregation through user remote controller input and matching this profiles with contents meta-data like contents genre information, event information, content viewing time. It is not used commercial database system and network communication solution considering embedded system hardware restriction. And it is considered people want different content genre based on watching time. From the results of this paper, there are improvement of user satisfaction of contents recommendation.

• Korean Management Science Review
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• v.28 no.1
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• pp.1-10
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• 2011

One of the fundamental roles of web object navigation is to support what the user wants precisely and efficiently from the enormous web database to the web browser. As long as the web search results are a set of individual lists, it is all right to display each and every web result for the web browser to display a web object one by one. However, in case the search results are a collection of multiple interrelated web objects, then there is a need to represent for a new mechanism for linked web objects at a time. We define a unit of web objects derived from a Steiner tree where the web objects include a set of specific keywords calculated by the weight from which the solutions are extracted. Even if a web object does not include all the keywords, then the related hypertext linked web objects are derived and displayed onto the mobile web browser with meta data in one shot. In this paper, it is applied for the mobile browser that the web contents can dynamically be displayed with Steiner trees until each renewal of the navigation request may be issued. In this paper, a new synchronized mobile browsing method is developed so that the navigating time can drastically be reduced and the web navigating efficiency can be dramatically enhanced without sacrificing memory consumption.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.17 no.1
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• pp.1-5
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• 2014

The diagnosis and treatment of cow's milk protein allergy (CMPA) is still a challenge. A systematic literature search was performed using Embase, Medline, The Cochrane Database of Systematic Reviews and Cochrane Central Register of Controlled Clinical Trials for the diagnosis and treatment of cow's milk allergy (CMA). Since none of the symptoms of CMPA is specific and since there is no sensitive diagnostic test (except a challenge test), the diagnosis of CMPA remains difficult. A "symptom-based score" is useful in children with symptoms involving different organ systems. The recommended dietary treatment is an extensive cow milk based hydrolysate. Amino acid based formula is recommended in the most severe cases. However, soy infant formula and hydrolysates from other protein sources (rice) are gaining popularity, as they taste better and are cheaper than the extensive cow's milk based hydrolysates. Recent meta-analyses confirmed the safety of soy and estimate that not more than 10-15% of CMPA-infants become allergic to soy. An accurate diagnosis of CMA is still difficult. The revival of soy and the development of rice hydrolysates challenge the extensive cow's milk based extensive hydrolysates as first option and amino acid formula.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.