• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1101-1113
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• 2016

This study was conducted to analyze the effects of parenting programs for children with disabilities through meta-regression analysis of experimental studies published in Korea. Twenty-two studies with a randomized or non-randomized control group prepost test design were included in the analysis. Parenting programs had a significant effect on parenting stress (ES= -1.08, p <.001, $I^2=67.4%$), parenting ecacy (ES=0.72, p <.001, $I^2=58.0%$) and self-esteem (ES=0.58, p =.016, $I^2=0$). The meta-regression analysis showed that research designs and therapy providers had different effects on dependent variables. Results support that parenting programs are helpful for parents of children with disabilities in reducing parenting stress and improving parenting efficacy, and self-esteem.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.854-860
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• 2009

Ubiquitous is a new computing environment with IT technology and information communication, and appling various equipments likes PDA and application parts. Recently, user's using environment is changing to smart phone and is expanded learning tools to learner without educational environment. Thus, in this paper, we designed SCORM based meta-data to use smart phone. For this purpose, we made U-learning server and smart phone process server that is to handling with existence LMS and SCORM. To apply smart phones characteristics that have different ones each other, meta-data was able to have some resource information as like CPU, screen size and memory. The meta-data adapter could be process the characteristics.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.424-427
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• 2015

근래 들어 모바일 기기의 시스템을 장악하여 사용자의 기밀 정보를 빼내는 악성 행위의 한 방법으로 Code Reuse Attack (CRA)이 널리 사용되고 있다. 이와 같은 CRA를 막기 위하여 call-return이 일어날 때마다 이들 address를 비교해 보는 shadow stack과 branch에 대한 몇 가지 규칙을 두어 CRA 를 탐지하는 branch regulation과 같은 방식이 연구되었다. 우리는 shadow stack과 branch regulation을 종합하여 여러 종류의 CRA를 적은 성능 오버헤드로 탐지할 수 있는 CRA Detection System을 만들고자 한다. 이를 위하여 반드시 선행 되어야 할 연구인 바이너리 파일 분석과 meta-data 생성 및 압축 기술을 제안한다. 실험 결과 생성된 meta-data는 압축 기술을 적용하기 전보다 1/2에서 1/3 가량으로 그 크기가 줄어들었으며 CRA Detection System의 탐지가 정상적으로 동작하는 것 또한 확인할 수 있었다.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.2
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• pp.1-16
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• 2018

Purpose : This meta-analysis was aimed at guiding future research in stroke treatment and to provide real-world data relating to the effects of aquatic exercise therapy on balance in patients with chronic stroke. Methods : We performed a meta-analysis comprising 22 studies involving aquatic exercise therapy performed between 2006 and 2017. A meta-analysis software program was used to calculate the mean effect size, effect size by intervention, and effect size by outcome. We also performed a meta-regression analysis and an analysis of publishing bias. Results : The mean effect size was 0.563. The effect size by outcome was observed to be the largest for the functional reach test, followed by the Berg balance scale, balance equipment, the Timed Up and Go test and one leg standing. Meta-regression analysis showed that effect size increased with an increase in the duration, number, length of exercise session. Conclusion : Aquatic exercise therapy appears to show a moderate effect on balance in patients with chronic stroke. A meta-analysis is warranted for further research to determine the effects of aquatic exercise on walking, muscle strength, and range of motion.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1429-1440
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• 2008

In a meta-analysis combining the results from different clinical trials, it is important to consider the possible heterogeneity in outcomes between trials. Such variations can be regarded as random effects. Thus, random-effect models such as HGLMs (hierarchical generalized linear models) are very useful. In this paper, we propose a HGLM framework for analyzing the binominal response data which may have variations in the odds-ratios between clinical trials. We also present the prediction intervals for random effects which are in practice useful to investigate the heterogeneity of the trial effects. The proposed method is illustrated with a real-data set on 22 trials about respiratory tract infections. We further demonstrate that an appropriate HGLM can be confirmed via model-selection criteria.

• Journal of Korean Library and Information Science Society
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• v.36 no.1
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• pp.415-440
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• 2005

This paper analyses meta-data systems for serials in order to provide the fundamental infrastructure for serials-sharing systems based on semantic interoperability. According to the primitive features of serials information, meta-data for serials are classified into 3 main subsystems: serial identification Information, serial bibliographic information and serial holding information. The serial identification information that play the important role of the primary key in library management systems should be refined to accommodate serials with digital formats. Although MARC formats have been commonly used for the description of serial bibliographic information, a new meta-data format for serial bibliographic information that harmonize with the abundance of meta-data elements in MARC and the simplicity of DCMI. For serial holding information, the newly proposed standards such as ANSI/NSIO Z39.50 are adequate to grasp the varieties of serial holding patterns. It should be able to differentiate the level of description by means of the types of serial information services. As the current computing technology generally uses XML for the representation and Process of information, the meta-data system for serials should be based on XML.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.134-137
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• 2016

Big data analysis refers the ability to store, manage and analyze collected data from an existing database management tool. In addition, extract value from large amounts of structured or unstructured data set and means the technology to analyze the results. Meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. Meta-analysis is sometimes expressed as an analysis of another analysis. Commonly, factors of metabolic syndrome can be defined as abdominal obesity, high triglycerides, low high density lipoprotein cholesterol, elevated blood pressure, and elevated fasting glucose. This study will find meaningful mediator variables for criterion variables that affect before and after the metabolic syndrome studies, on the basis of the results of a meta-analysis. We reviewed a total of 5 studies related to metabolic syndrome published in Korea between 2000 and 2016, where a cause and effect relationship is established between variables that are specified in the conceptual model of this study.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.403-414
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• 2011

Recently, smart phones based on Android platform have been widely used, and lots of applications have been developed. Data generated from an application are frequently transferred to other applications. Therefore, a method that can easily transfer or share meta-data among applications is required. Generally meta-data created by android applications are java objects. The android platform uses clipboard, intent and content provider in order to transfer data among the applications. However, those ways are designed to transfer data as a record. So these methods have to marshall the object to a record and unmarshall the record to an object. In this paper, we designed and implemented the MetaService which can transfer any type of object made by applications. When the MetaService is used, we can reduce complex implementations such as clipboards and content providers and we can reduce many bugs. Therefore, we can make the applications simple and increase productivity.

• Journal of Pharmacopuncture
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• v.24 no.3
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• pp.107-121
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• 2021

Objectives: The purpose of this study is to analyze the efficacy of traditional Chinese medicine (TCM) injections specified in the clinical guideline for COVID-19 by conducting a meta-analysis of viral pneumonia data. Methods: TCM injections data on viral pneumonia were collected until July 31, 2021. CNKI, PubMed, EMBASE, and the Cochrane electronic database were used to collect the clinical data. "COVID-19," "Viral pneumonia," "Tanreqing," "Xiyanping," "Reduning," "Xingnaojing," "Xuebijing," "Shenmai," "Shengmai," and "Shenfu" were used as keywords. All data collected were mainly about TCM injections and viral pneumonia. Furthermore, studies that included results such as the total effective rate, cough disappearance time, antipyretic time, lung rhomboid disappearance time, and adverse drug reaction were collected for the meta-analysis to identify the efficacy of TCM injections. However, data unrelated to TCM injections specified in the clinical guidelines for COVID-19 or viral pneumonia were excluded. The quality of included RCTs was assessed by the Cochrane Risk of Bias Tool, and Review Manager 5.3 software was used to conduct the meta-analysis. Results: A total of 18 studies with 1540 patients were included in this study. The results of the meta-analysis showed that the total effective rate OR = 4.61 (95% CI 2.92, 7.25, p = 1.00/ I² = 0%); the cough disappearance time: SMD -1.23 (-1.37, -1.09, p < 0.00001/ I² = 94%); the antipyretic time: SMD -1.26 (-1.40, -1.11, p < 0.00001/ I²=94%); lung rhomboid disappearance time: SMD -1.17 (-1.33, -1.02, p < 0.00001/ I² = 89%); and adverse drug reaction was OR 0.36 (95% CI 0.20, 0.64, p = 0.21/ I² = 30%). From the results, the treatment group (TCM injection) showed better efficacy than the control group (Western medication). Conclusion: Xiyanping, Reduning, and Tanreqing injections may yield benefits as COVID-19 treatments. However, clinical trials on TCM injections for the treatment of COVID-19 are still lacking. More high-quality clinical trials are still required.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.163-172
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• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.