• Advances in nano research
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• 제15권2호
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• pp.155-163
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• 2023

Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 추계학술대회
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• pp.180-181
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• 2019

This paper proposes a rate control algorithm for intra coding frame in HEVC encoder using a deep learning approach. The proposed algorithm is designed for CTU level bit allocation in intra frame by considering visual features spatially and temporally. Our features are generated using visual geometry group (VGG-16) with deep convolutional layers, then it is used for bit allocation per each CTU within an intra frame. According to our experiments, the proposed algorithm can achieve -2.04% Luma component BD-rate gain with minimal bit accuracy loss against the HM-16.20 rate control model.

• 한국군사과학기술학회지
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• 제11권1호
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• pp.93-101
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• 2008

It is difficult for a MWR(Missile Warning Radar) to perform a threat decision accurately since there is no tracking part which gives more accurate threat information to the MWR. In this paper, the threat decision algorithm is proposed using an azimuth angular rate to improve the accuracy. The azimuth angular rate is dependent upon the direction of an approaching target. The target is classified into a threat or non-threat using a boundary condition of the azimuth angular rate. The boundary condition is determined using the Monte-Carlo simulation. The performance of the proposed algorithm is evaluated using this condition at field tests of MWR. The efficiency of the proposed method for the threat decision is proved by comparing the results of field tests with the simulation results.

• 한국자동차공학회논문집
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• 제7권7호
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• pp.1-14
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• 1999

In the present study, the flame factor which primarily influence the simulation accuracy of the combustion process in a gasoline engine was modeled as a nonlinear function of turbulent intensity to laminar flame speed ratio. Multi-length-scale production rate model for turbulent kinetic energy equation was introduced to consider the different length scales of the swirling and tumbling motions in cylinder on the production rte of turbulent kinetic energy. By7 introducing the multi-length-scale production rate model for the turbulent kinetic energy equation, the predictions of turbulent burning velocity , cylinder pressure, mass burning rate and engine performance of a gasoline engine can much be improved.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4060-4066
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• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.

• 산업경영시스템학회지
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• 제42권2호
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• pp.28-35
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• 2019

Since guided missiles with the characteristics of the one-shot system remain stored throughout their entire life cycle, it is important to maintain their storage reliability until the launch. As part of maintaining storage reliability, period of preventive test is set up to perform preventive periodic test, in this case failure detection rate has a great effect on setting up period of preventive test to maintain storage reliability. The proposed method utilizes failure rate predicted by the software on the basis of MIL-HDBK-217F and failure mode analyzed through FMEA (Failure Mode and Effect Analysis) using data generated from the actual field. The failure detection rate of using the proposed method is applied to set periodic test of the actual guided missile. The proposed method in this paper has advantages in accuracy and objectivity because it utilizes a large amount of data generated in the actual field.

• 품질경영학회지
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• 제14권1호
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• pp.61-66
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• 1986

Many papers have suggested various models how to decide an optimal time for replacing equipment. In this study, Dynamic Programming is applied to establish a model of replacing equipment and a new algorithm is developed for computerization to meet the increased number of variables. It is possible to predict the real situation with higher accuracy by employing the proposed model including more variables such as planning horizon, original cost, salvage value, decreasing rate, operating and maintenance costs, increasing rate, and so on.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2002년도 제35회 춘계학술대회
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• pp.80-87
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• 2002

We predict the unknown cannon tube erosion rate by using observed values of the standard cannon, 155mm Howitzer Ml85. We know the standard cannon's ten erosion observation values each 400 rounds. An approximate formula fitting the erosion values of the standard cannon has been derived. Numerical simulation applying this formula to the Rauf Imam's erosion equations is presented.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2001년도 가을 학술발표회 논문집
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• pp.1041-1044
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• 2001

This study was performed to evaluate the effect of non-uniform corrosion distribution on the analysis of concrete cover failure. A series of experiments have been undertaken to measure the corrosion rate of reinforcement according to the concentration of chloride ion so as to suggest a relationship between the reinforcement corrosion rate and chloride ion density. The corrosion induced pressure depending on the density of chloride ion has been derived. And nonlinear analysis assuming nonlinear corrosion distribution for cover cracking was achieved and compared with other experimental results to verify the accuracy of the model. Analysis was also performed for various parameters to compare their effects.

• 한국기계가공학회지
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• 제11권3호
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• pp.68-72
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• 2012

Al2017 is typical Duralumin of self-hardening aluminum alloy. It is lightweight, formability and machinability so throughout the industries have widely used automobile, electronics, semiconductor and aircraft as material. A variety of CNC machine tool processing technology, scientific principles and experience have been studied in order to increase accuracy and productivity. Using a machining center is to constant amount of side step and cutting characteristics studied changing depth of cut, revolution per minute and feed rate.