• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.695-702
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• 2010

This paper presents an image alignment algorithm for application of AOI (Automatic Optical Inspection) based on SIFT. Since the correspondences result using SIFT descriptor have many wrong points for aligning, this paper modified and classified those points by five measures called the CCFMR (Cascade Classifier for False Matching Reduction) After reduced the false matching, rotation and translation are estimated by point selection method. Experimental results show that the proposed method has fewer fail matching in comparison to commercial software MIL 8.0, and specially, less than twice with the well-controlled environment’s data sets (such as AOI system). The rotation and translation accuracy is robust than MIL in the noise data sets, but the errors are higher than in a rotation variation data sets although that also meaningful result in the practical system. In addition to, the computational time consumed by the proposed method is four times shorter than that by MIL which increases linearly according to noise.

• Journal of Environmental Health Sciences
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• v.28 no.1
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• pp.31-39
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• 2002

Generally, inaccurate reports on environmental issues occur due to various factors. The purpose of this study was to find out a way to enhance accuracy of environmental reporting. So the reporters' career and college major had been compared to the accuracy of their articles. The by-lined environmental articles in nine dailies published in 1991 were checked. Results of this study were as follows. (I) Inaccuracy rate in environmental articles was 54.2%. Inaccuracies appeared 1.7 times per an article, while the average frequency of inaccuracies in overall articles was 0.9 time. (2) Errors in the articles consist of 65.8% of subjective inaccuracies and 34.2% of subjective inaccuracies. They derive from the false usage of terminology(15.8% ),misquotation(14.5%), incorrect statistics(13%), exaggeration(13%), inaccurate title(7.9%), and false comparison(5%). (3) Inaccuracy rate by the type of articles was 66.7% in columns, 60% in feature stories, 54.5% in-depth stories, 40.9% in straight news, respectively. (4) Inaccuracy rate by the specific field was shown 71.4% in environmental impacts assessment, 52.5% in water pollution, 37.5% in waste management, and 35.7% in air pollution. (5) According to the result of chi-square test analysis, there were no statistically significant differences of inaccuracy rate and of subjective, and objective inaccuracies relevant to the period of reporters' career covering environmental reporting and the nature of articles, and college major.

• The Mathematical Education
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• v.49 no.2
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• pp.161-174
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• 2010

The purpose of the study is to analyze various types of errors appeared in true-false proof problems of matrix and to find out correction method. In order to achieve this purpose, error test was conducted to the subject of 87 second grade students who were chosen from D high schoool. It was shown from this test that the most frequent error type was caused by the lack of understanding about concepts and essential facts of matrix(35.3%), and then caused by the invalid logically reasoning (27.4%), and then caused by the misusing conditions(18.7%). Through three hours of correction lessons with 5 students, the following correction teaching method was proposed. First, it is stressed that the operation rules and properties satisfied in real number system can not be applied in matrix. Second, it is taught that the analytical proof method and the reductio ad absurdum method are useful in the proof problem of matrix. Third, it is explained that the counter example of E=$\begin{pmatrix}1\;0\\0\;1 \end{pmatrix}$, -E should be found in proof of the false statement. Fourth, it is taught that the determinant condition should be checked for the existence of the inverse matrix.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.260-267
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• 2021

In this paper, we intend to use a new mixed model of YoloV5 and DeepSort. For fire detection, we want to increase the accuracy by automatically extracting the characteristics of the flame in the image from the training data and using it. In addition, the high false alarm rate, which is a problem of fire detection, is to be solved by using this new mixed model. To confirm the results of this paper, we tested indoors and outdoors, respectively. Looking at the indoor test results, the accuracy of YoloV5 was 75% at 253Frame and 77% at 527Frame, and the YoloV5+DeepSort model showed the same accuracy at 75% at 253 frames and 77% at 527 frames. However, it was confirmed that the smoke and fire detection errors that appeared in YoloV5 disappeared. In addition, as a result of outdoor testing, the YoloV5 model had an accuracy of 75% in detecting fire, but an error in detecting a human face as smoke appeared. However, as a result of applying the YoloV5+DeepSort model, it appeared the same as YoloV5 with an accuracy of 75%, but it was confirmed that the false positive phenomenon disappeared.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.87-94
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• 2023

This study analyzed and identified various causes of caustic alarms of 163 fire detectors that occurred from January 2019 to December 2021 at domestic semiconductor manufacturing plants equipped with about 30,000 fire detectors, and proposed a new non-fire prevention cause investigation plan by applying the NFPA 921 scientific methodology. The results of the study are as follows. First, in terms of necessary recognition and problem definition, an analog detector and an integrated monitoring system were proposed to quickly determine the location and installation space information of the fire detector. Second, in order to prevent speculative causes and errors in various analyses in terms of data analysis and hypothesis establishment, non-fire reports were classified into five by factor and defined, and the causes of occurrence by factor were classified and proposed. Finally, in terms of hypothesis verification and final hypothesis selection, a non-fire prevention improvement termination process and a final hypothesis verification sheet were proposed to prevent the cause from causing re-error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11B
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• pp.730-735
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• 2005

While the E-mail is a important way of fast communication in these days. it is real that the E-mail is often misused as a commercial advertisement method and creates many social problems. Even though various filtering techniques for blocking spam mails have been developed, reliability of mail systems is decreased by misreading normal mails as spam mails, i.e. false-positive errors. In this paper, the SMBC(Spam Mail Blocking Center) platform employing spam mail recovery method based on privacy information is proposed and designed. The SMBC is designed in frame layer based on spam blocking system of proxy sewer and can be physically implemented in various topology so that flexible development with layered module is possible. Using privacy information makes the proposed SMBC platform minimize processing load and false-positive error rates so that it can improve mail system reliabilities.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.357-365
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• 2005

We present a B-spline fitting method based on genetic algorithm for the extraction of object contours from the complex image sequence, where objects with similar shape and intensity are adjacent each other. The proposed algorithm solves common malfitting problem of the existing B-spline fitting methods including snakes. Classical snake algorithms have not been successful in such an image sequence due to the difficulty in initialization and existence of multiple extrema. We propose a B-spline fitting method using a genetic algorithm with a new initial population generation and fitting function, that are designed to take advantage of the contour of the previous slice. The test results show that the proposed method extracts contour of individual object successfully from the complex image sequence. We validate the algorithm by false-positive/negative errors and relative amounts of agreements.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1043-1057
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• 2015

In order to recognize intelligent threats quickly and detect and respond to them actively, major public bodies and private institutions operate and administer an Intrusion Detection Systems (IDS), which plays a very important role in finding and detecting attacks. However, most IDS alerts have a problem that they generate false positives. In addition, in order to detect unknown malicious codes and recognize and respond to their threats in advance, APT response solutions or actions based systems are introduced and operated. These execute malicious codes directly using virtual technology and detect abnormal activities in virtual environments or unknown attacks with other methods. However, these, too, have weaknesses such as the avoidance of the virtual environments, the problem of performance about total inspection of traffic and errors in policy. Accordingly, for the effective detection of intrusion, it is very important to enhance security monitoring, consequentially. This study discusses a plan for the reduction of false positives as a plan for the enhancement of security monitoring. As a result of an experiment based on the empirical data of G, rules were drawn in three types and 11 kinds. As a result of a test following these rules, it was verified that the overall detection rate decreased by 30% to 50%, and the performance was improved by over 30%.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.686-692
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• 2016

A Crimp Force Monitor (CFM) is equipment for detecting crimp errors by analyzing crimp signals obtained from force and strain sensors. The analysis is commonly performed by aligning a measured crimp signal with a reference signal and comparing their difference. Current analysis methods often suffer from wrong alignments that result in false negative detections. This paper presents a new crimp signal analysis method in CFM. First, a falling edge alignment is proposed that matches falling edges of the measured and the reference signals by minimizing the absolute difference summation. Second, a signal parameter error is introduced to evaluate the crimp quality difference between the measured signal and the reference. For calculating the signal parameter error, part of a signal is identified and divided into several regions to maximize the signal parameter errors. Experiments showed that the proposed method can improve the signal alignment and accurately detect bad crimps especially with the strain sensor.