• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.139-142
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• 2020

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.210-213
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• 2017

The construction industry has witnessed an exponential growth of drones used in the field over the past few years. Likewise, the field of maintenance has paid increasing attention to using drones with a view to improving the efficiency of condition checks in high-rise buildings and major space. Although operators manipulate drones to inspect buildings at present, drones are expected to autonomously move around without operators in a few years. Also, for indoor maintenance, it is important for drones to find accurate locations, which is implemented by real-time locating systems(RTLS). Yet, the accuracy of RTLS varies across the types of systems and indoor settings, which warrants a locating system suitable for indoor space and a location correction system designed to improve the accuracy. Hence, the current study investigated the accuracy of real-time locating systems(RTLS) for the maintenance of indoor space of buildings with drones and delved into the methods of correcting the location information to improve the accuracy of RTLS.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.166-171
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• 2023

This paper presents the synaptic characteristics of IGZO memristors in neuromorphic computing, using MATLAB/Simulink and NeuroSim. In order to investigate the variations in the conductivity of IGZO memristor and the corresponding changes in the hidden layer, simulations are conducted by using the MNIST dataset. It was observed from simulation results that the recognition accuracy could be dependent on various parameters of IGZO memristor, along with the experimental exploration. Moreover, we identified optimal parameters to achieve high accuracy, showing an outstanding accuracy of 96.83% in image classification.

• 대한상한금궤의학회지
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• v.14 no.1
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• pp.41-50
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• 2022

Objective : The purpose of this study is to explore the most suitable machine learning model algorithm for Shanghanlun diagnostic system classification using natural language processing (NLP). Methods : A total of 201 data items were collected from 『Shanghanlun』 and 『Clinical Shanghanlun』, 'Taeyangbyeong-gyeolhyung' and 'Eumyangyeokchahunobokbyeong' were excluded to prevent oversampling or undersampling. Data were pretreated using a twitter Korean tokenizer and trained by logistic regression, ridge regression, lasso regression, naive bayes classifier, decision tree, and random forest algorithms. The accuracy of the models were compared. Results : As a result of machine learning, ridge regression and naive Bayes classifier showed an accuracy of 0.843, logistic regression and random forest showed an accuracy of 0.804, and decision tree showed an accuracy of 0.745, while lasso regression showed an accuracy of 0.608. Conclusions : Ridge regression and naive Bayes classifier are suitable NLP machine learning models for the Shanghanlun diagnostic system classification.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

• Proceedings of the KSME Conference
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• 2001.06e
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• pp.410-415
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• 2001

An analytical and numerical examination of second-order fractional-step methods and boundary condition for the incompressible Navier-Stokes equations is presented. In this study, the compatibility condition for pressure Poisson equation and its boundary conditions, stability, and numerical accuracy of canonical fractional-step methods has been investigated. It has been found that satisfaction of compatibility condition depends on tentative velocity and pressure boundary condition, and that the compatible boundary conditions for type D method and approximately compatible boundary conditions for type P method are proper for divergence-free velocity for type D and approximately divergence-free for type P method. Instability of canonical fractional-step methods is induced by approximation of implicit viscous term with explicit terms, and the stability criteria have been founded with simple model problems and numerical experiments of cavity flow and Taylor vortex flow. The numerical accuracy of canonical fractional-step methods with its consistent boundary conditions shows second-order accuracy except $D_{MM}$ condition, which make approximately first-order accuracy due to weak coupling of boundary conditions.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.26 no.2
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• pp.167-172
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• 1990

A number of studies for the improvement of the accuracy of the Loran C fix were carried out previously. But most studies were preformed when a ship was at anchorage, or in port. To investigate the accuracy of the Loran C fix when a ship was underway and in port, a series of observation was made on the route between Pusan and Cheju from Oct. 1988 to Oct. 1989. The obtained results are summerized as follows: 1. There is little difference in the accuracy of the Loran C fix by daytime and night, and the higher the mountain nearby ship, the greater the error of ship's position. 2. When a ship is at anchorage and underway, and the accuracy of ship's position is almost not affected by course while underway. 3. In order to promote the accuracy of the fixed position, a navigator must correct the propagation velocity and the geodetic system simultaneously, but in this paper the authors find that a most accurate position can be obtained by converting the geodetic system only.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.640-647
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• 2018

This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.8
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• pp.741-746
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• 2007

In this paper, we propose an accuracy analysis method for air-to-ground weapon delivery. The lethality, which is one of the most important factor to evaluate combat effectiveness of a fighter, depends on the capability to improve the accuracy of the conventional weapon delivery. We present error elements which affect the error analysis for air-to-ground weapon delivery from the initial design phase to the final validation phase. And we introduce an accuracy analysis method to reflect the error elements and to evaluate them quantitatively. We assume zero bias-error and consider random error for the weapon delivery accuracy analysis.

• Journal of Power System Engineering
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• v.19 no.2
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• pp.27-32
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• 2015

This paper describes a distance measurement system with high accuracy that utilizes a stereo-based camera and a pan-tilt unit for automatically maintaining the positional relationship between a vessel and a target on the side of a facility at a close range. The measurement system offers an advantage in that it can measure the distance to a target while tracking it. In order to improve the ability to control the position of a vessel between it and a target while maintaining the distance especially at a close range, the accuracy of the measurement system has to be improved. The accuracy of the distance measured by our system is increased with revisions of the conclusively generated data of distance measurement. We verified the accuracy of our system from an experiment, which generated results that had an accuracy of 30 mm for distances in the range between 2-8 m.