• Journal of Practical Engineering Education
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• v.6 no.2
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• pp.135-139
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• 2014

In this study, the new model of presentation remote controller in which has improved the conventional function and deteceted the level of human's tension on a real time basis is suggested and tested. Existing presentation remote controller was just used turning the pages. But new model controls presentation and check tension level on real time using the smart phone's bluetooth interface. The proposed system is comprised with the PPG (Photo-Plethysmo-Graphy) sensor, Bluetooth and Wi-Fi modules. The configured system is to process (within 150 ms) the pulse signals of the presenter and stored the data. As a result, it can check and make up for the week presentation part and used as sources for improving self-confidence. This is the result obtained from the process of capstone design irregular course for 20 weeks of a graduate-to-be in four-year college.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.107-114
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• 2022

In this paper, we have enhanced the risk prediction of hypertension using the feature selection method in the Korean National Health and Nutrition Examination Survey (KNHANES) database of the Korea Centers for Disease Control and Prevention. The study identified various risk factors correlated with chronic hypertension. The paper is divided into three parts. Initially, the data preprocessing step of removes missing values, and performed z-transformation. The following is the feature selection (FS) step that used a factor analysis (FA) based on the feature selection method in the dataset, and feature importance (FI) and multicollinearity analysis (MC) were compared based on FS. Finally, in the predictive analysis stage, it was applied to detect and predict the risk of hypertension. In this study, we compare the accuracy, f-score, area under the ROC curve (AUC), and mean standard error (MSE) for each model of classification. As a result of the test, the proposed MC-FA-RF model achieved the highest accuracy of 80.12%, MSE of 0.106, f-score of 83.49%, and AUC of 85.96%, respectively. These results demonstrate that the proposed MC-FA-RF method for hypertension risk predictions is outperformed other methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.1-10
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• 2024

The radio propagation characteristics of the 6, 10, and 17 GHz frequency bands in multiple paths in an indoor lobby environment were analyzed. The line-of-sight (LOS) and non-LOS (NLOS) paths were measured from a distance of 2-16 m (0.5 m intervals) from the transmitting to the receiving antenna positions. For basic transmission losses, three parameters were compared using the floating intercept path loss model corresponding to the path. For a root mean square delay spread, the measurement results were compared for cumulative probabilities of 10, 50, and 90%. Propagation loss and propagation delay occurred in all measured frequencies owing to the existence of pillars and an unusual lobby structure. Thus, a measurement scenario for an indoor lobby environment and the provision of standard measurement data was proposed. The results may facilitate research on the radio propagation characteristics of 5G and millimeter-wave bands in indoor lobby environments with various structures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8879-8888
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• 2015

When the disaster like earthquake in urban area occur, due to the collapse accidents for subway, tunnel space with buildings or underground area, enormous property and human damage are happened. Specially, since it is difficult to identify survived status of humans within collapsed debris and accurately buried locations of the humans, inputs of considerable time and manpower for rescuing them are required. Besides, secondary damage can be occurred by additional collapses. The aim of this study is to propose a stochastic location positioning method that enables to provide aid information by determining locations of mobile devices for buried persons in 2-D plane using wireless communication technologies. This study selected a detection method for buried persons based on Wi-Fi signal, and identified characteristics of signal strengths by distance unit. Using these methods, a stochastic location detection model in 2-D plane was built. It is expected that this technology will be utilized as a core technology that can protects safety and human life of the public by providing data for rescuing quickly buried persons in cases of national disasters for future.

• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.592-599
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• 2019

This study aimed to develop an equation for estimating stem volume for Larix kaempferiin South Korea using independent variables, diameter at breast height (DBH), and height as being closely associated with stem volume. Analysis was conducted on the growth performance of 2,840 Larix kaempferi samples across South Korea after felling them and gleaning diameter data according to both stem height and stem analyses. In order to test the fitness of six different stem taper equations, empirical assessment was conducted for fitness index (FI), bias, mean, and absolute deviation (MAD), and coefficient variation (%CV). The two selectedmodels found to be optimal were the following: model one (V=a+bDBH²), established by employing DBH only; and model four (V=a+bDBH²H), established by utilizing DBH and height, respectively. The findings of non-linear regression indicated statistical significance (p < 0.05) in a and b, which were the coefficients for the intercepts and slopes of the models. The FI of the models ranged between 94% and 99%, and the bias was close to zero, while MAD ranged from 0.01 to 0.05, and %CV from 5.97 to 14.43, indicating a high level of fitness. Thus, using the suggested models, the basic information necessary for forest management was obtained, and an estimation of the stem volume was effected without delay soon after effecting DBH and height measurements.

• ETRI Journal
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• v.25 no.2
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• pp.89-100
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• 2003

The notion of pseudorandomness is the theoretical foundation on which to consider the soundness of a basic structure used in some block ciphers. We examine the pseudorandomness of the block cipher KASUMI, which will be used in the next-generation cellular phones. First, we prove that the four-round unbalanced MISTY-type transformation is pseudorandom in order to illustrate the pseudorandomness of the inside round function FI of KASUMI under an adaptive distinguisher model. Second, we show that the three-round KASUMI-like structure is not pseudorandom but the four-round KASUMI-like structure is pseudorandom under a non-adaptive distinguisher model.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.79-82
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• 2017

IoT devices are interconnected in global network with different functionalities and manage the data transfer in cloud computing. IoT devices can be used anytime, anywhere with any device with different applications and protocols. Same devices but different applications according to end user requirements such as sensors and Wi-Fi devices, reusability of these applications can enhance the development process. However, large number of variations in cloud computing make it difficult the features selection in application because of compatibility issues of devices. In this paper we have proposed multi-Software Product Lines (multi-SPLs) approach to manage the variabilities and commonalities of IoT applications and protocols. Feature modeling is used to manage the commonalities and variabilities of SPL. We proposed that multi-SPLs feature model is more appropriate for modeling of IoT applications and protocols.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1996.04b
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• pp.145-152
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• 1996

This paper deals with an experimental study on the f~iction torque characteristics of magnctic fluid seals for various oil temperatures, rotating speeds, and vacuum pressures. The friction torque of MFS was measured by high response torque meter. The experimental results show that, as the rotating speed increases, the fi'iction torque of MFS increases and as the oil temperature increases, the friction torque of MFS decreases. Also, the experimental results show that the friction torque of Model II is 1.73 ~ 2.56, 2.0 ~ 2.89, 2.0 - 3.25 times larger than those of Model I under the atmospheric pressure, vacuum pressure(10$^{-4}$ and 10$^{-6}$ torr), respectively.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.21-30
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• 2024

As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wireless charging system, stability issues are being raised because it requires a large amount of power compared with conventional wired charging. SAE J2954 is a standard for building autonomous vehicle wireless charging infrastructure, and the standard defines a communication method between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, and UWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and the charging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robust communication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wireless power transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technology is used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actual autonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance information was collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Model that apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.