• Journal of Korean Medicine Rehabilitation
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• v.33 no.4
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• pp.79-93
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• 2023

Objectives The purpose of this study is to investigate therapeutic exercise and to provide the evidence of daoyin exercise for shoulder pain. Methods Electronic databases including PubMed, EMBASE, China National Knowledge Infrastructure, Science ON, Oriental Medicine Advanced Searching Integrated System were searched up to October 2022. We selected randomized controlled trials. The quality of studies was assessed by Cochrane risk of bias tool. Meta-analysis were perfomed by Review Manager software. Results Eighteen randomized controlled trials were collected in accordance with the selection and exclusion criteria. Among the 18 trials, 7 trials used strengthening exercise, 4 trials used stablilization exercise, 5 trials used both types of intervention, and 2 trials used daoyin exercise. The study characteristics, results and method of intervention were analyzed. Meta-analysis showed that therapeutic exercise appeared to more effective than no treatment group for shoulder pain (standardized mean difference=-1.18, 95% confidence interval=-1.44 to 0.91, Z=8.82, p<0.00001; chi²=2.71, p=0.61; I²=0%). Conclusions All of 18 selected studies reported the effectiveness of therapeutic exercise for shoulder pain. Combining strengthening and stablilization exercise is considered the most efficient way for shoulder pain. Based on this study, well-designed studies should be performed to be evidence of the use of daoyin exercise for shoulder pain.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.77-87
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• 2024

In this paper, we propose a study applying the Delphi technique to domestic blockchain experts to determine urgent and pivotal conditions for NFT proliferation. We examine these conditions from a PEST (Political, Economic, Social, and Technological Analysis of the Macro Environment) perspective, as well as the functions of digital assets (measurement, storage, and exchange). Through two rounds of expert surveys on the seven NFT perspectives, we identify 6 activating factors that can help guide future policy-making for the NFT market. These factors have broad implications for the development of new industries using blockchain technology and tokens. The Delphi method employed in this study is a group discussion technique that gathers opinions from experts anonymously through two rounds and to address drawbacks related to expert selection bias and opinion alignment, additional opinion collection and review of projections were conducted in each round.

• Journal of Periodontal and Implant Science
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• v.54 no.1
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• pp.3-12
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• 2024

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.

• Asia Marketing Journal
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• v.13 no.3
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• pp.25-53
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• 2011

This study probes the effect of loyalty program on the customer retention based on the real transaction data(n=2,892) acquired from education service industry. We try to figure out the outcomes of reward program through more than 1 year-long data gathered and analyzed according to quasi-experimental design(i.e., before and after design). We adopt this kinds of research scheme in regard that previous studies measured the effect of loyalty program by dividing the customers into two group(i.e., members vs. non-members) after the firms or stores had started the program. We believe that it might not avoid the self-selection bias. The research questions of this study could be explained such as: First, most research said that the loyalty programs could increase the customer loyalty and contribute to the sustainable growth of company. But there are little confirmation that this promotional tool could be justified in terms of financial perspective. Thus, we are interested in both the retention rate and financial outcomes caused by the introduction of loyalty programs. Second, reward programs target mainly current customer. Especially CRM(customer relationship management) said that it is more profitable for company to build positive relationship with current customer instead of pursuing new customer. And it claims that reward program is excellent means to achieve this goal. For this purpose, we check in this study whether there is a interaction effect between loyalty program and customer type in retaining customer. Third, it is said that dis-satisfied customers are more likely to leave the company than satisfied customers. While, Bolton, Kannan and Bramlett(2000) claimed that reward program could contribute to minimize the effect of negative service by building emotional link with customer, it is not empirically confirmed. This point of view explained that the loyalty programs might work as exit barrier to current customer. Thus, this study tries to identify whether there is a interaction effect between loyalty program and service experience in keeping customer. To achieve this purpose, this study adopt both Kaplan-Meier survival analysis and Cox proportional hazard model. The research outcomes show that the average retention period is 179 days before introducing loyalty program but it is increased to 227 days after reward is given to the customers. Since this difference is statistically significant, it could be said that H1 is supported. In addition, the contribution margin coming from increased transaction period is bigger than the cost for administering loyalty programs. To address other research questions, we probe the interaction effect between loyalty program and other factors(i.e., customer type and service experience) affecting it. The analysis of Cox proportional hazard model said that the current customer is more likely to engage in building relationship with company compared to new customer. In addition, retention rate of satisfied customer is significantly increased in relation to dis-satisfied customer. Interestingly, the transaction period of dis-satisfied customer is notably increased after introducing loyalty programs. Thus, it could be said that H2, H3, and H4 are also supported. In summary, we found that the loyalty programs have values as a promotional tool in forming positive relationship with customer and building exit barrier.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.351-360
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• 2018

The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.599-610
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• 2016

This paper reports the results of a systematic review (SR) and meta-analysis research to compare the effect of Kangaroo care, targeting mothers and premature infants. A randomized clinical trial study was performed until February 2015. The domestic literature contained the non-randomized clinical trial research without restriction according to the level of the study design. A search of the Ovid-Medline, CINAHL, PubMed and KoreaMed, the National Library of KOREA, the National Assembly Library, NDSL, KISS and RISS. Through the KMbase we searched and combined the main term ((kangaroo OR KC OR skin-to-skin) AND (care OR contact)) AND (infant OR preterm OR Low Birth Weight OR LBW), ((kangaroo OR kangaroo OR kangaroo) AND (care OR nursing care OR management OR skin contact)) was made; these were all combined with a keywords search through the selection process. They were excluded in the final 25 studies (n=3051). A methodology checklist for randomized controlled trials (RCTs) designed by SIGN (Scottish Intercollegiate Guidelines Network) was utilized to assess the risk of bias. The overall risk of bias was regarded as low. In 16 studies that were evaluated as a grade of "++", 9 studies were evaluated as a grade of "+". As a result of meta-analysis, kangaroo care regarding the effects of premature mortality, severe infection/sepsis had an insignificant effect. Hyperthermia incidence, growth and development (height and weight), mother-infant attachment, hypothermia incidence, length of hospital days, breast feeding rate, sleeping, anxiety, confidence, and gratification of mothering role were considered significant. In satisfaction of the role performance, depression and stress presented contradictory research results for individual studies showing overall significant difference. This study has some limitations due to the few RCTs comparing kangaroo care in the country. Therefore, further RCTs comparing kangaroo care should be conducted.

• Journal of Life Science
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• v.20 no.4
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• pp.481-486
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• 2010

The rates of synonymous and nonsynonymous nucleotide substitutions were studied for sequences of nuclear and chloroplast genes in Sorbus aucuparia. Results suggested that DNA evolution in this species had taken place, on average, at a slower rate in the chloroplast genes than in the nuclear genes: a rate variation pattern similar to those observed in eudicot plants. Within the nucleus, the synonymous substitution rates (Ks) (2.45-2.60) were two-fold higher than nonsynonymous substitution rates (Ka) (1.15-1.30). More notably, the values of Ks (1.20-1.26) were about six-fold higher than those of Ka (0.26-0.42) within the chloroplast genome. Ka/Ks ratios for nuclear and chloroplast genes of S. aucuparia had mean values of 0.178 and 0.056, respectively. A Ka/Ks ratio < 1 indicated negative (purifying) selection. The chloroplast genes had a lower effective number of codons (ENC) values (22.4-32.2) than those of nuclear genes (35.8-38.7). The analysis of the G+C content indicated that the chloroplast genes in this investigation had a higher preference for synonymous codons ending with A and T (G+C content range, 28.4-29.1%) where there was a slight bias toward codons ending with G+C (63.2-64.2%) in the nuclear genome.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.89-97
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• 2012

In this paper, we propose a novel approach to noise power estimation for speech enhancement in noisy environments. The method based on IMCRA (improved minima controlled recursive averaging) which is widely used in speech enhancement utilizes a rough VAD (voice activity detection) algorithm which excludes speech components during speech periods in order to improves the performance of the noise power estimation by reducing the speech distortion caused by the conventional algorithm based on the minimum power spectrum derived from the noisy speech. However, since the VAD algorithm is not sufficient to distinguish speech from noise at non-stationary noise and low SNRs (signal-to-noise ratios), the speech distortion resulted from the minimum tracking during speech periods still remained. In the proposed method, minimum power estimate obtained by IMCRA is modified by SMT (spectral minima tracking) to reduce the speech distortion derived from the bias of the estimated minimum power. In addition, in order to effectively estimate minimum power by considering the distribution characteristic of the speech and noise spectrum, the presented method combines the minimum estimates provided by IMCRA and SMT depending on the weighting factor based on the subband. Performance of the proposed algorithm is evaluated by subjective and objective quality tests under various environments and better results compared with the conventional method are obtained.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4689-4695
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• 2014

Background: A great number of studies have shown that cytochrome P450 1A1 (CYP1A1) genetic polymorphisms, CYP1A1 Msp I and CYP1A1 Ile/Val, might be risk factors for digestive tract cancers, including esophageal cancer (EC), gastric cancer (GC), hepatic carcinoma (HC), as well as colorectal cancer (CC), but the results are controversial. In this study, a meta-analysis of this literature aimed to clarify associations of CYP1A1 genetic polymorphisms with digestive tract cancers susceptibility in Chinese populations. Materials and Methods: Eligible case-control studies published until December 2013 were retrieved by systematic literature searches from PubMed, Embase, CBM, CNKI and other Chinese databases by two investigators independently. The associated literature was acquired through deliberate search and selection based on established inclusion criteria. Fixed-effects or random-effects models were used to estimate odds ratios (ORs and 95%CIs). The meta-analysis was conducted using Review Manager 5.2 and Stata 12.0 softwares with stability evaluated by both stratified and sensitivity analyses. Moreover, sensitivity analysis and publication bias diagnostics confirmed the reliability and stability. Results: Eighteen case-control studies with 1,747 cases and 2,923 controls were selected for CYP1A1 MspI polymorphisms, and twenty case-control studies with 3, 790 cases and 4, 907 controls for the CYP1A1 Ile/Val polymorphisms. Correlation associations between CYP1A1 Ile/Val polymorphisms and digestive tract cancers susceptibility were observed in four genetic models in the meta-analysis (GG vs AA:OR= 2.03, 95%CI =1.52- 2.72; AG vs AA: OR=1.26, 95%CI =1.07-1.48; [GG+AG vs AA] :OR =1.42, 95%CI=1.20-1.68, [GG vs AA+AG]:OR=1.80, 95%CI =1.40-2.31). There was no association between CYP1A1 Msp I polymorphisms and digestive tract cancers risk. Subgroup analysis for tumor type showed a significant association of CYP1A1 Ile/Val genetic polymorphisms with EC in China. However, available data collected by the study failed to reveal remarkable associations of GC or HC with CYP1A1 Ile/Val genetic polymorphisms and EC, GC or CC with CYP1A1 MspI genetic polymorphisms. Conclusions: Our results indicated that CYP1A1 Ile/Val genetic polymorphisms, but not CYP1A1 Msp I polymorphisms, are associated with an increased digestive tract cancers risk in Chinese populations. Additional well-designed studies, with larger sample size, focusing on different ethnicities and cancer types are now warranted to validate this finding.