• Journal of the Korean Society of Safety
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• v.29 no.3
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• pp.129-135
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• 2014

The number of abnormal operation procedures (AOPs) for mitigating a plant abnormal status amounts to about one hundreds for the most of 1000MWe optimized power plant (OPR1000) and it is expected that the number of AOPs would be increased to cope with an abnormal status occurred newly. However, it is not well organized for operators to select a proper AOP from alarms occurred in main control room (MCR) during a plant abnormal status. It may be a burden to operators since the selection of AOP to respond an abnormal status is authorized by operators. When multiple alarms occur in MCR, it would take more time to respond them than a single alarm. To reduce the efforts, various MCR operation support systems have been developed. The purpose of this study was to develop a multi-alarm pattern card to select an appropriate AOP effectively when multiple alarms occurs in a single upper layout (UL) of MCR. It can be applied for an operation support tool as well as an education tool.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1392-1405
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• 2019

The cathode voltage of aluminum electrolytic cell is relatively stable under normal conditions and fluctuates greatly when it has an anomaly. In order to detect the abnormal range of cathode voltage, an anomaly detection algorithm based on sliding window was proposed. The algorithm combines the time series segmentation linear representation method and the k-nearest neighbor local anomaly detection algorithm, which is more efficient than the direct detection of the original sequence. The algorithm first segments the cathode voltage time series, then calculates the length, the slope, and the mean of each line segment pattern, and maps them into a set of spatial objects. And then the local anomaly detection algorithm is used to detect abnormal patterns according to the local anomaly factor and the pattern length. The experimental results showed that the algorithm can effectively detect the abnormal range of cathode voltage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1531-1539
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• 2014

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. In other words, the design of algorithm that exactly detects abnormal signal and classifies PVC by analyzing the persons's physical condition and/or environment and variable QRS pattern is needed. Thus, PVC classification by personalized abnormal signal detection and QRS pattern variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and subtractive operation method and selected abnormal signal sets. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of abnormal beat detection and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 98.33% in abnormal beat classification error and 94.46% in PVC classification.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.59-72
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• 2010

WIM(Weigh-In-Motion) is the system measuring the weight of the vehicle with a high-speed. In the existing WIM system, vehicle weight is measured based on the constant speed and the error ratio has 10%. However, because of measuring the driving pattern, that is abnormal driving pattern which is like the acceleration and down-shift of the drivers, it has the error ratio which is bigger than the real. In order to it reduces the error ratio of WIM system, the improved WIM system needs to find the abnormal driving pattern. In order to reducing the error ratio of these WIM systems, the improved WIM system can find abnormal driving patterns. In this paper, the improved WIM system which analyzes the abnormality driving pattern influencing on the error ratio of WIM system of an existing and minimizes the error span is designed. The improved WIM system has the multi step loop structure of adding the loop sensor to an existing system. In addition, the measure function defined as an intrinsic is improved and the weight measured by the abnormal driving pattern is amended. The analysis of experiment result improved WIM system can know the fact that the error span reduces by 8% less than in the existing the maximum average sampling error 22.98%.

• International Journal of Contents
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• v.13 no.2
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• pp.21-28
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• 2017

Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• Journal of the Korean Home Economics Association
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• v.20 no.3
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• pp.1-8
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• 1982

In this study, we attempted to make an original pattern of clothing for an abnormal type of figure, especially for the type of kyphosis. We measured the curvature of the spine of a woman with kyphosis with a Martin measuring instrument and a silhouetter in the following ways. First, we counted the rate of shrinkage of the standard lines drawn on the surface of the body according as the body moved. Secondly, placing the front and back darts, the front and back shoulder darts and the side darts according to“Munhwa”pattern, we made cubic cuttings of four moving postures as well as the standing one. Thirdly, we superposed the developed patterns of the standing and the moving postures, measuring the position change and the amount to the change of the darts, and compared them. The results are as follows: 1) In the developed pattern of a cubic cutting of the basic pattern and the standing posture, the neckhole became larger than that of the basic pattern, and the waist line was lowered than that of the basic pattern because the center back line was shortened due to the curved backbone.

• Journal of Korean Physical Therapy Science
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• v.9 no.1
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• pp.123-128
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• 2002

Objectives: The objective of this study was to investigate factor analysis of low back pain patients. Methods: The data were collected from hospital located in Daegu. Observation was made on 40 low back pain patients and factor analysis study was also performed in terms of their abnormal physical findings. Results: The low back pain patients occupied 20% of all clinical patients in male group and 20% in female group. The occurrence of acute low back pain in the first factor tended to be higher among in male group than among in female group. While it was significantly higher muscle weakness of the back in female group. The most prevailing abnormal finding among low back pain patients in the first factor were tender point on the back, While it was significantly lower Decreased tendon reflex in both sexes Conclusions: The factor pattern of abnormal physical findings in low back pain patients was much different between male and female patients, suggesting the different pattern of etiology. Although low back pain is one of the most common symptoms causing limitation activity, as yet there is no known specific effective treatment.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.332-333
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• 2018

This paper presents an advanced abnormal over-current protection with $SuperFET^{(R)}$ 800V MOSFET in Flyback converter. In advanced abnormal over-current protection, digital pattern generator is proposed to detect a steep di/dt current condition when secondary rectifier diode or the transformer is shorted. If current sensing signal is larger than current limit during consecutive switching cycle, Gate signal will be stopped for 7 internal switching periods. If the abnormal over-current maintains pattern, the controller goes into protection mode. The Advanced over-current protection has been implemented in a 0.35um BCDMOS process (ON Semiconductor process).

• Journal of the Korean Home Economics Association
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• v.20 no.3
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• pp.9-18
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• 1982

In this study, we attempted to make an original pattern of clothing for an abnormal type of figure, especially for the type of kyphosis. We measured the curvature of the spine of a woman with kyphosis with a Martin measuring instrument and a silhouetter in the following ways. First, we counted the rate of shrinkage of the standard lines drawn on the surface of the body according as the body moved. Secondly, placing the front and back darts, the front and back shoulder darts and the side darts according to“Munhwa”pattern, we made cubic cuttings of four moving postures as well as the standing one. Thirdly, we superposed the developed patterns of the standing and the moving postures, measuring the position change and the amount of the chaange of the darts, and compared them. The results are as follows: 1) In the developed pattern of a cubic cutting of the basic pattern and the standing posture, the neckhole became larger than that of the basic pattern, and the waist line was lowered than that of the basic pattern because the center back line was shortened due to the curved backbone. 2) As for the change of the standard line according to the movement, we found that the waist line, the center front line, the center back line, the bust width line, the upper back width line and the back width line became longer. Special consideration must be given to the function of the clothing for an abnormal type of figure. 3) The difference of the measurements between the cubic cutting and the body measurement regardless of the body movement is due to a gap by an acute angle at the jutted place between the developed pattern and the body surface. We found that the body measurement of the upper back width line, the back width line and the bust line became larger. Consequently, in making an original clothing pattern, it is desirable that we must not place the front and the back waist darts at the jutted place on the back from the functional and the aesthetic viewpoint of clothing. It is also desirable that we must widen the neckhole because the shoulder angle is close to a straight line due to a jut of the upper back width line.