• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.1-10
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.834-838
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• 1992

Tracking performance depends on the quantity of the measurement data. In the Kalman-Bucy filter and other trackers, this dependence is well understood in terms of the measurement noise covariance matrix, which specifies the uncertainty in the value of measurement inputs. In this paper, we derived approximated error covariance matrix to evaluate the dependence of target detection probability and false alarm probability in the presence of uncertainty of measurement origin.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.391-395
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• 2023

Helicopter accidents due to spatial disorientation in low visibility conditions continue to persist as a major issue. These incidents often stem from human error, typically induced by stress, and frequently result in fatal outcomes. This study employs machine learning to analyze flight data and evaluate the efficacy of a flight illusion detection algorithm, laying groundwork for further research. This study collected flight data from approximately 20 pilots using a simulated flight training device to construct a range of flight scenarios. These scenarios included three stages of flight: ascending, level, and descent, and were further categorized into good visibility conditions and 0-mile visibility conditions. The aim was to investigate the occurrence of flight illusions under these conditions. From the extracted data, we obtained a total of 54,000 time-series data points, sampled five times per second. These were then analyzed using a machine learning approach.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.476-481
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• 2019

Early detection of fire is an important measure for minimizing the loss of life and property damage. However, fire and smoke need to be simultaneously detected. In this context, numerous studies have been conducted on image-based fire detection. Conventional fire detection methods are compute-intensive and comprise several algorithms for extracting the flame and smoke characteristics. Hence, deep learning algorithms and convolution neural networks can be alternatively employed for fire detection. In this study, recorded image data of fire in a ship engine room were analyzed. The flame and smoke characteristics were extracted from the outer box, and the YOLO (You Only Look Once) convolutional neural network algorithm was subsequently employed for learning and testing. Experimental results were evaluated with respect to three attributes, namely detection rate, error rate, and accuracy. The respective values of detection rate, error rate, and accuracy are found to be 0.994, 0.011, and 0.998 for the flame, 0.978, 0.021, and 0.978 for the smoke, and the calculation time is found to be 0.009 s.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.61-68
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• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.57-64
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• 2017

CCSDS Standard is widely used in the international space telecommunication area. But standard recommendation of CCSDS is not restrictive, so, we can select an appropriate encryption protocol among the layer. For synchronization, encryption sync is attached in the beginning of the encrypted data. In the exceptional environmental condition, although the receiver can not decrypt the normal data, the sender have no conception of that situation. In this paper, we propose a two-stage SES alarmed link encryption synchronization method having optimized threshold value necessary to decide whether the receiver has a correct decryption or not. first, through the experiment of mutual relations between error rate and encryption synchronization detection error, we can predict worst communication environment for the selected encryption synchronization pattern. second, through the experiment for finding what number of consecutive frame synchronization error is an appropriate reference value and analysis of that experiment, we suggest an optimized threshold value for resynchronization request. lastly, through the output images we can predict the probability error that should be guaranteed by channel coder.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.176-181
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• 2002

In this paper, we consider the optimal control of detection threshold to minimize the conditional expectation of mean-square state estimation error for a probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the suboptimal detection threshold in a closed-form. This results are very useful for real- time implementation.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.145-149
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• 2016

For obtaining high speed data rate, underwater acoustic communication has several problems by the different environmental problem. To achieve high speed data rate, a method of multiple antennas have been researched. V-BLAST Algorithm is a detection method applied to terrestrial wireless communications. In this paper, BER performance of VBLAST detection for MIMO system is analyzed in the paper.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.542-544
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• 2005

This paper describes the detection of spatio-temporal parameter using an accelerometer and footswitches to evaluate a symmetry and balance of hemiplegic patients. We detected gait data using a 3-axis accelerometer that mounted between L3 and IA intervertebral area and footswitches made by FSR-Sensor attached insole. To minimize the error of the gait parameters to be detected incorrectly in case of using only accelerometer, we enhancement the performance of detection by measuring an accelerometer and foots witches data at the same time. So, it was possible to detect more accurate gait parameters. As a result, we can confirm the symmetry and balance of hemiplegic patients. In the future. these results could be used to evaluate the walking ability in hemiplegic patients in clinical pratice.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.113-114
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• 2008

In this paper, binary pulse-position modulation (2PPM) time-hoping (TH) ultra-wideband (UWB) system is applied to multiple input multiple output (MIMO) system using vertical bell lab layered space-time (V-BLAST) structure to achieve high-data-rate communications. This UWB-MIMO system and its receivers are analyzed, and its BER performances are evaluated. In the receiver, various MIMO detection algorithms such as zero-forcing (ZF), ZF-ordered successive interference cancellation (OSIC), minimum-mean-square-error (MMSE), MMSE-OSIC and maximum likelihood (ML) are comparatively studied.