• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.43-51
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• 2011

The recent development of the technology for wireless mobile computing and applied technology for location-based services has made it possible to support query processing faster than that in the past. However, some technological limitations on hardware and software still exist. The most critical aspects of query processing are accuracy and speed. For improving the accuracy, it is required that detailed information on the data involved in query processing be saved. In this case, the amount of information on the data increases, which decreases the speed. On the other hand, for increasing the speed, it is necessary to reduce the broadcast cycle, which enables rapid data acquisition as desired. In this case, because of insufficient index information, the listen time for the client increases, which may cause unnecessary energy consumption. Therefore, a trade-off occurs between the accuracy and speed. This paper proposes a hierarchical bitmap-based spatial index (HBI) as a solution for the aforementioned problems. HBI describes an object with 0 and 1 on the Hilbert curve map. It reduces the broadcast cycle by decreasing the index size on the basis of bit information and tree structure. Therefore, it is able to shorten the listen time and query processing time. In addition, HBI enables the detection of the locations of all the objects so that it is possible selectively listen to a broadcast. A performance evaluation of the proposed technique demonstrates that it is excellent.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.2
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• pp.55-60
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• 2009

By applying NDVI(Normalized Difference Vegetation Index) and TCT(Tasseled-Cap Transformation) image algorithm on the basis of KOMSAP-2 MSC(Multi Spectral Camera) image(Jun. 12, 2007) for Naenam-myeon, Gyeongju city in this study, DN distribution map was drawn up. Discrimination analysis of image algorithm for the accuracy improvement of forest type classification was conducted through the comparative analysis between the distribution maps of NDVI and TCT DN, and forest field surveying data, and finally, the accuracy of the forest type classification was verified through the overlay analysis with the forest field surveying data. Through this study, it is thought that low cost and high efficiency will be able to be expected in the process of the examination for the automation practicality of the forest type classification and of the production of the accurate forest type classification map by using KOMPSAT-2 MSC image.

• The Journal of Korean Academy of Prosthodontics
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• v.39 no.3
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• pp.282-296
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• 2001

The accuracy of master cast reproduction by a polyvinylsiloxane impression material using two visible-light curing resin and autopolymerizing polymethyl methacrylate resin custom tray material was investigated. Custom trays were fabricated from a master cast that had three index points marked on both inner and outer vestibules and then poured in yellow stone. The distance between the reproduced index points were measured to be ${\pm}0.001mm$ with a measuring microscope and the algebraic norms calculated for each tray material. No differences were found in the algebraic norms of inner and outer dimensions for upper tray impressions by ANOVA(p>0.05). However, T-test revealed that there were differences between upper and lower impressions and Tukey's hsd test revealed that in lower tray impressions, the Palatray in inner, the Lightplast in outer dimensions respectively were different from other materials. The index points reproduced on the casts compared with the master cast, were closer together for upper tray impressions. All four tray materials produced acceptable casts, 1. Algebraic norms of inner and outer dimensions of the test casts for upper trays were not statistically different irrespective of materials.(P>0.05) 2. T-test showed that there were differences between means with upper and lower trays especially in outer dimension.(P>0.05) 3. But, algebraic norms of inner and outer dimensions of the test casts for lower trays were statistically different between materials. 4. Palatray XL in inner, Lightplast-platten in outer dimensions respectively for lower trays were different from other materials, but, the nearest to the original model.

• The Journal of Korean Physical Therapy
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• v.30 no.6
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• pp.234-238
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• 2018

Purpose: Aim of this study was to investigate whether there are ipsilateral motor deficits for visuospatial accuracy and fine movements by making a comparison between stroke patients and healthy subjects. We examined whether ipsilateral motor deficits are influenced by the level of functional movements and muscle strength of the upper and lower extremities of the affected side. Methods: Thirty post-stroke subjects and 20 normal aged matched subjects were recruited. Outcome measures for less-affected side were the tracking task and nine-hole pegboard test. Fugl-Meyer test and motricity index were applied for the measurement of functional movements and muscle strength of affected side. Results: Tracking task and nine-hole pegboard test was significantly different between control and experimental group. In terms of accuracy index according to tracking, the experimental group showed a lower accuracy index in the MCP joint than the control group. However, there were no significant difference relation between the level of motor function of the affected side and the motor deficit level of ipsilateral side. Conclusion: Ipsilateral motor deficits may have significant clinical implications. It needs to be noted that although many patients, families, and medical staff are focused only on motor deficits of the affected side, motor deficits of the sound side can cause difficulties in daily living movements requiring delicate movements. In addition, there was no significant correlation between the level of motor function of the affected side and motor deficits of the sound side.

• Journal of Korea Trade
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• v.25 no.4
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• pp.17-36
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• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.856-874
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• 2019

The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.

• The Korean Journal of Nuclear Medicine
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• v.28 no.3
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• pp.357-363
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• 1994

We evaluated the diagnostic accuracy of $^{99m}Tc$-DISIDA scintigrauhy as a mean of differentiating biliary atresia from neonatal hepatitis. $^{99m}Tc$-DISIDA scintigraphy was visually interpreted by assessing the presence or absence of radioactivity in the intestine or gall bladder. In patients without intestinal radioactivity, we measured the hepatic retention index and the hepatic uptake index. The hepatic retention Index was expressed as the amount of change of liver activity from 5 minutes to 30 minutes postinjection. The hepatic uptake Index was graded visually with 5 minute images using the following scoring scheme : grade 0(normal hepatic uptake), grade 1(decreased hepatic uptake), grade 2(hepatic uptake equal to cardiac uptake), and grade 3(hepatic uptake less than cardiac uptake). Age, total bilirubin, and hepatic uptake index were compared between the biliary atresia and the neonatal hepatitis group, between neonatal hepatitis patients with and without intestinal radioactivity, and between the biliary atresia and neonatal hepatitis patients with absent intestinal radioactivity. The results were as follows ; 1) None of the 30 biliary atresia patients showed intestinal radioactivity, while 31/40 neonatal hepatitis patients showed intestinal radioactivity. The sensitivity, specificity, and accuracy of the presence of intestinal radioactivity ?or the diagnosis of biliary atresia was 100%, 78%, and 87%, respectively. 2) In patients with absent intestinal radioactivity the mean hepatic retention index was $1.5{\pm}0.6$ in the 16 biliary atresia patients, and $1.1{\pm}0.2$ in the 7 neonatal hepatitis patients(p<0.01). All 7 patients with hepatic retention index over 1.5 had biliary atresia. But there were 9 patients with biliary atresia below 1.5. 3) No significant differences were found in age, total bilirubin, or hepatic uptake Index between biliary atresia and neonatal hepatitis patients. However there were differences in age, total bilirubin, and hepatic uptake index between neonatal hepatitis patients with and without intestinal radioactivity. The hepatic uptake index was significantly lower, age was old, and total bilirubin was low in the group with intestinal radioactivity compared the group without intestinal radioactivity(p<0.05). Relation between total bilirubin and the hepatic uptake index was that total bilirubin was relatively low at normal hepatic uptake index in biliary atresia and neonatal hepatitis patients. 4) When hepatic uptake index and hepatic retention index were high it suggest that biliary atresia is more likely, considered relation between hepatic uptake Index and the hepatic retention index. Thus, we conclude that $^{99m}Tc$-DISIDA scintigraphy is accurate in the differential diagnosis of biliary atresia and neonatal hepatitis. In patients without intestinal radioactivity, the hepatic retention index and hepatic uptake index, along with the patient's age and total bilirubin level may supplement diagnosis and improve diagnostic accuracy.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1721-1726
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• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.

• Journal of Forest and Environmental Science
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• v.34 no.2
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• pp.142-144
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• 2018

This paper discusses the development of semi-automatic search program for crown delineation in stand level. The crown of an individual tree was delineated by applying the Watershed (WS) and Valley Following (VF) algorithms. Unmanned Aerial Vehicle (UAV) images were used in the semi-automatic search program to delineate the crown area. The overall accuracy and Khat were used in accuracy assessment. WS algorithm's model showed the overall accuracy and Khat index of 0.80 and 0.59, respectively, in Plot 1. However, the overall accuracy and Khat of VF algorithm's model were 0.78 and 0.51, respectively, in Plot 2.