• Journal of Institute of Convergence Technology
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• v.2 no.2
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• pp.1-4
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• 2012

Human error analysis has been performed to prevent accidents and reduce human error rate in diverse contexts; manufacturing, aircraft and nuclear power plants. Until now, human error in our everyday lives has not been focused. This paper addressed human error when users go up and down elevator. First of all, human error types of elevator users were categorized by a taxonomy of unsafe acts. It was also investigated which types of human error occurred in the elevator. Finally display design guidelines were suggested to reduce human error in elevator. Auditorial display and visual display can be used to reduce human errors in elevator. Future study should be performed to check if the proposed design guidelines are effective in the real situations.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.259-267
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• 2021

Recently, the market for personal health care and medical devices based on Bluetooth Low Energy(BLE) has grown rapidly. BLE is being used in various medical data communication devices based on low power consumption and universal compatibility. However, since data errors occurring in the transmission of medical data can lead to medical accidents, it is necessary to analyze the causes of errors and study methods to reduce data error. In this paper, the minimum communication speed to be used in medical devices was set to at least 800 byte/sec based on the wireless electrocardiography regulations of the Ministry of Food and Drug Safety. And the data loss rate was tested when data was transmitted at a speed higher than 800 byte/sec. The factors that cause communication data error were classified, and the relationship between each factor and the data error rate was analyzed through experiments. When there were two or more activated peripherals connected to the central, data error occurred due to channel hopping and bottleneck, and the data error rate increased in proportion to the communication distance and the number of activated peripherals. Through this experiment, when the BLE is used in a medical device that intermittently transmits biosignal data, the risk of a medical accident is predicted to be low if the number of peripherals is 3 or less. But, it was determined that BLE would not be suitable for the development of a biosignal measuring device that must be continuously transmitted in real time, such as an electrocardiogram.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.173-178
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• 2012

In the generated model for the recognition vocabulary, tri-phones which is not make preparations are produced. Therefore this model does not generate an initial estimate of parameter words, and the system can not configure the model appear as disadvantages. As a result, the sophistication of the Gaussian model is fall will degrade recognition. In this system, we propose the error correction system using out-of vocabulary rejection algorithm. When the systems are creating a vocabulary recognition model, recognition rates are improved to refuse the vocabulary which is not registered. In addition, this system is seized the lexical analysis and meaning using probability distributions, and this system deactivates the string before phoneme change was applied. System analysis determine the rate of error correction using phoneme similarity rate and reliability, system performance comparison as a result of error correction rate improve represent 2.8% by method using error patterns, fault patterns, meaning patterns.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.236-244
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• 2024

A representative problem in domestic chestnut industry is the high loss of flesh due to excessive knife peeling in order to increase the peeling rate, resulting in a decrease in production efficiency. In this study, a prediction model for weight loss rate of chestnut by stage of knife peeling process was developed as undergarment study to optimize conditions of the machine. 51 control conditions of the two-stage blade peeler used in the experiment were derived and repeated three times to obtain a total of 153 data. Machine learning(ML) models including artificial neural network (ANN) and random forest (RF) were implemented to predict the weight loss rate by chestnut peel stage (after 1st peeling, 2nd peeling, and after final discharge). The performance of the models were evaluated by calculating the values of coefficient of determination (R), normalized root mean square error (nRMSE), and mean absolute error (MAE). After all peeling stages, RF model have better prediction accuracy with higher R values and low prediction error with lower nRMSE and MAE values, compared to ANN model. The final selected RF prediction model showed excellent performance with insignificant error between the experimental and predicted values. As a result, the proposed model can be useful to set optimum condition of knife peeling for the purpose of minimizing the weight loss of domestic chestnut flesh with maximizing peeling rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12A
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• pp.941-949
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• 2011

In a cooperative communication system with a source node and multiple relays equipping single antenna and a destination node equipping multiple antennas, the selective cooperative spatial multiplexing scheme can obtain spatial multiplexing gain and additional selection diversity gain. But it can degrade a bit error rate performance because some received symbols forwarded from particular relays may be lost by attenuation due to path-loss. We propose a relay and transmission mode selection scheme which selects minimum number of multiple relays having the channel capacity larger than a given data rate and transmission mode which switches spatial multiplexing and spatial diversity mode in cooperation phase to enhance the bit error rate performance. The proposed scheme achieves 1.5~2dB gain at the low SNR range compared with the conventional scheme by obtaining additional spatial diversity gain.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.119-125
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• 1999

The distribution of fatigue crack growth rate is subjected to the measuring interval and calculated method of growth rate. In this paper, in order to establish the method of determining the distribution of fatigue crack growth rate, which ignores those influences, a series of fatigue crack growth experiments and measuring intervals of crack length calculated reasonable are presented. The main conclusions obtained are summarized as follows: 1) As a result of the ΔP constant test and ΔK constant test, it is thought that an approximate measuring interval of 0.3~0.7mm is reasonable, which allows for few errors and is little subjected to the calculated method of crack growth rate. 2) After generally comparing the error estimation by using the experimental data of CCT specimen with the error rating of the CT specimens, it is possible that the fatigue test has few errors within the measuring interval, ξ(Δa/W)=0.0067~0.017, regardless of the dimension of specimen geometry.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.849-853
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• 2014

In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1505-1514
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• 1997

In this paper, a temporally adaptive layered image sequence coding technique employing H.261 is proposed. In the proposed technique, the frame rate of the base layer is adjusted according to the temporal activity measure based on the rate-distortion function. The base layer is encoded using the H.261. Then, the full frame-rate error image is formed by comparing the original image and the interpolated version of the reconstructed base layer image. The enhancement layer is algo encoded using H.261 but with leaky prdiction to provide robust error resilience. The simulation results show that the proposed technique provides better performance than the twin-H.261 with leaky prediction in both the fixed-rate and variable-rate systems.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.99-104
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• 2006

Accurate flow rate distribution has been become a very important part for controling of air change rate since the introduction of house ventilation system. An inappropriate selection of fan due to Incorrect prediction of friction loss makes waste energy. The purpose of this study is to recognize applicability of T-Method at house ventilation system by comparing experiment with T-method, The result of this study is as follows Flow rate is small amount in a house, so duct size must be accurate. And duct design with Equal Friction Loss Method presented large error range. Equal friction loss method is not fit to applicate small amount air flow rate. T-Method predicts accurate flow rate comparatively in a house ventilation system. Error range was 3.5%.