• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Clinics in Shoulder and Elbow
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• v.26 no.3
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• pp.245-251
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• 2023

Background: For anatomic total arthroscopic repair, cementless humeral fixation has recently gained popularity. However, few studies have compared clinical, radiographic, and patient-reported outcomes between cemented and press-fit humeral fixation, and none have performed follow-up for longer than 5 years. In this study, we compared long-term postoperative outcomes in patients receiving a cemented versus press-fit humeral stem anatomic arthroscopic repair. Methods: This study retrospectively analyzed 169 shoulders that required primary anatomic total shoulder arthroplasty (aTSA). Shoulders were stratified by humeral stem fixation technique: cementation or press-fit. Data were collected pre- and postoperatively. Primary outcome measures included range of motion, patient reported outcomes, and radiographic measures. Results: One hundred thirty-eight cemented humeral stems and 31 press-fit stems were included. Significant improvements in range of motion were seen in all aTSA patients with no significant differences between final cemented and press-fit stems (forward elevation: P=0.12, external rotation: P=0.60, and internal rotation: P=0.77). Patient reported outcome metrics also exhibited sustained improvement through final follow-up. However, at final follow-up, the press-fit stem cohort had significantly better overall scores when compared to the cemented cohort (visual analog score: P=0.04, American Shoulder and Elbow Surgeon Score: P<0.01, Simple Shoulder Test score: P=0.03). Humeral radiolucency was noted in two cemented implants and one press-fit implant. No significant differences in implant survival were observed between the two cohorts (P=0.75). Conclusions: In this series, we found that irrespective of humeral fixation technique, aTSA significantly improves shoulder function. However, within this cohort, press-fit stems provided significantly better outcomes than cemented stems in terms of patient reported outcome scores. Level of evidence: III.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1525-1536
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• 2021

Objective: To investigate the feasibility of cine three-dimensional (3D) balanced steady-state free precession (b-SSFP) imaging combined with a non-local means (NLM) algorithm for image denoising in evaluating cardiac function in children with repaired tetralogy of Fallot (rTOF). Materials and Methods: Thirty-five patients with rTOF (mean age, 12 years; range, 7-18 years) were enrolled to undergo cardiac cine image acquisition, including two-dimensional (2D) b-SSFP, 3D b-SSFP, and 3D b-SSFP combined with NLM. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and ejection fraction (EF) of the two ventricles were measured and indexed by body surface index. Acquisition time and image quality were recorded and compared among the three imaging sequences. Results: 3D b-SSFP with denoising vs. 2D b-SSFP had high correlation coefficients for EDV, ESV, SV, and EF of the left (0.959-0.991; p < 0.001) as well as right (0.755-0.965; p < 0.001) ventricular metrics. The image acquisition time ± standard deviation (SD) was 25.1 ± 2.4 seconds for 3D b-SSFP compared with 277.6 ± 0.7 seconds for 2D b-SSFP, indicating a significantly shorter time with the 3D than the 2D sequence (p < 0.001). Image quality score was better with 3D b-SSFP combined with denoising than with 3D b-SSFP (mean ± SD, 3.8 ± 0.6 vs. 3.5 ± 0.6; p = 0.005). Signal-to-noise ratios for blood and myocardium as well as contrast between blood and myocardium were higher for 3D b-SSFP combined with denoising than for 3D b-SSFP (p < 0.05 for all but septal myocardium). Conclusion: The 3D b-SSFP sequence can significantly reduce acquisition time compared to the 2D b-SSFP sequence for cine imaging in the evaluation of ventricular function in children with rTOF, and its quality can be further improved by combining it with an NLM denoising method.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.8-16
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• 2024

This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• Journal of Applied Biological Chemistry
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• v.57 no.3
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• pp.235-242
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• 2014

The purpose of this study is the establishment of scientific processes for making food safety policies. Thus, we investigated pesticide residue level of the agricultural commodities from market, and performed risk assessment. Fifteen agricultural items are chosen based on the frequency of Korean consumption. The samples were collected from 9 cities where populations are more than one million. Total 283 active ingredients were monitoring ( total sample number =232). Single-analysis of target pesticides was for three kinds of possible growth regulators and the multicomponent analysis was for 280 kinds of pesticides, a total of 283 species were selected to perform the pesticide residues. Before monitoring the analytes, the improvements of the analytical methods were done by method validations under the CODEX analytical method development guidelines and can produce metrics that represent the international standards applied in accordance with the guidelines. In addition to residual pesticides detected during monitoring we compare the ADI to EDI values using detected result and dietary consumption data which is extracted from annual market basket survey. The 163 samples were non-detected in the total 232 samples so it means that every agricultural commodity will residual pesticides-free in 70.3%. The detected residual pesticides showed for a total of 69 cases (29.7%). Two of samples violate Korean MRL (0.9%). The ratio of EDI compared to ADI resulted in only from 0.00087 to 0.902%. In result, we can assume that all detected residual pesticides are very safe level and current policies of Korean pesticides control may be working.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.77-85
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• 2014

A goal of Bizcool entrepreneurship education targeting on the youth falls on letting understand the process of starts-up, enhance entrepreneurship will and their business creativities rather than training trivial starts-up skills such as writing business plan for successful starts-up. The effects of education enable Bizcoo students to recognize rightly the concept of starts-up training and lead to spread out demand for entrepreneurship education. The feedback check-up for how entrepreneurship education affects students getting through of it is necessary and possible to bring its' improvement alternatives. Despite of such highlight, not many measuring tools and indexes of evaluating an effectiveness of entrepreneurship education are developed and studied up until. This research suggests for the optimal indexes for them. In specific, this research 49 the first question sets of evaluating an effectiveness of entrepreneurship education classified 3 large categories and 11 following sub categories each of them such as entrepreneurship orientation, creativity, entrepreneurship preparing activities etc,. representing embedding education effects though entrepreneurship education. This research carry out the empirical survey research utilizing driven question sets against 5 different Bizcools sampling 287 students. The survey research delivers the final 3 large categories and 8 following sub categories(Innovativeness, risk-taking, problem-solving potent, cooperative decision-making potent, efficient behavior capacity, data collecting potent, career search, starts-up search and preparation), and 38 measuring indexes by search and confirming factor analysis. This research never drop the confidence test over each indexes and obtain the proper figures. Last but not least, this research confirm the gap between starts-up club members and non members as to an effectiveness of entrepreneurship education and 9 different indexes.

• Korean Journal of Ecology and Environment
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• v.39 no.3 s.117
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• pp.320-330
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• 2006

An integrated health of a lotic ecosystem, Cho River, was evaluated by various approaches such as conventional water quality analysis, physical assessments of Qualitative Habitat Evaluation Index (QHEI), and the bioassay of Index of Biological Integrity (IBI) durin August${\sim}$September 2005. The IBI model used in the study was based on original multivariate metric model and then modified the metric attributes of the model for the regional application. Physical habitat health, based on the QHEI, was estimated using eleven metrics. During the study, values of IBI model averaged 36, which was judged as 'fair' to 'good' conditions. Spatial variations in the model values were evident: the headwater site (S1) was estimated as 48, indicating an 'excellent' condition, and the other sites were estimated 32${\sim}$38, 'good' condition. Values of the QHEI in the all sites averaged 148, which is judged as a good condition. The QHEI values varied from 120 (fair condition) to 199 (excellent condition) depending on the location of the stream. Site 5 (S5) was estimated as 'fair${\sim}$good' condition, while Site 7 (S7) was estimated as 'excellent' condition. The biological health, based on the IBI, reflected the habitat health. However, chemical conditions in terms of pH, turbidity, electric conductivity, dissolved oxygen (DO) did not make a difference in the biological health because of minor chemical differences among the locations.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.