• Journal of KIISE:Databases
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• v.31 no.1
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• pp.23-29
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• 2004

In this paper, we propose a search method for time sequences which supports the normalized distance as a similarity measure. In many applications where the shape of the time sequence is a major consideration, the normalized distance is a more suitable similarity measure than the simple Lp distance. To support normalized distance queries, most of the previous work has the preprocessing step for vertical shifting which normalizes each sequence by its mean. The proposed method is motivated by the property of sequence for feature extraction. That is, the variation between two adjacent elements of a time sequence is invariant under vertical shifting. The extracted feature is indexed by the spatial access method such as R-tree. The proposed method can match time series of similar shape without vertical shifting and guarantees no false dismissals. The experiments are performed on real data(stock price movement) to verify the performance of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.57-62
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• 2004

We have proposed an efficient method of word separation in a handwritten legal amount on bank check based on the spatial gaps between the connected components. The previous gap measures all suffer from the inherent problem of underestimation or overestimation that causes a deterioration in separation performance. In order to alleviate such burden, we have developed a modified version of each distance measure. Also, 4 class clustering based method of integrating three different types of distance measures has been proposed to compensate effectively the errors in each measure, whereby further improvement in performance of word separation is expected. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over 2 - 3% of the word separation rate than their corresponding original distance measures. In addition, the proposed combining method based on 4-class clustering achieved further improvement by effectively reducing the errors common to two of three distance measures as well as the individual errors.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.319-327
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• 2016

Purpose: Automated guidance systems (AGSs) for mobile farm machinery have several advantages over manual operation in the crop production industry. Many researchers and companies have tried to develop such a system. However, it is not easy to evaluate the performance of an AGS because there is no established device used to evaluate it that complies with the ISO 12188 standard. The objective of this study was to develop a tracking sensor system using five laser distance measurement sensors. Methods: One sensor-for long-range distance measurement-was used to measure travel distance and velocity. The other four sensors-for mid-range distance measurement-were used to measure lateral deviation. Stationary, manual driving, and A-B line tests were conducted, and the results were compared with the real-time kinematic differential global positioning system (RTK-DGPS) signal used by the AGS. Results: For the stationary test, the average error of the tracking sensor system was 1.99 mm, and the average error of the RTK-DGPS was 15.19 mm. For the two types of driving tests, the data trends were similar. A comparison of the changes in lateral deviation showed that the data stability of the developed tracking system was better. Conclusions: Although the tracking system was not capable of measuring long travel distances under strong sunlight illumination because of the long-range sensor's limitations, this dilemma could be overcome using a higher-performance sensor.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.152-159
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• 2019

In general, a Doppler radar can measure only the velocity of a moving target. To measure the distance of a moving target, it is necessary to use a frequency-modulated continuous wave or pulse radar. However, the latter are very complex in terms of both hardware as well as signal processing. Moreover, the requirement of wide bandwidth necessitates the use of millimeter-wave frequency bands of 24 GHz and 77 GHz. Recently, a new kind of Doppler radar using multitone frequency has been studied to sense the distance of moving targets in addition to their speed. In this study, we show that distance sensing of moving targets is possible by adjusting only the frequency of a 2.4 GHz Doppler radar with low cost phase lock loop. In particular, we show that distance can be sensed using only alternating current information without direct current offset information. The proposed technology satisfies the Korean local standard for low power radio equipment for moving target identification in the 2.4 GHz frequency band, and enables multiple long-range sensing and radio-frequency identification applications.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.669-676
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• 2023

In this paper, a multi-purpose golf putting range finder based on an IR razer sensor and an inertial sensor was designed and made. It was designed to measure distance and slope within a 50m outdoor measurement range for the main purpose of golf putting distance measurement, and at the same time, it is designed to measure temperature information that affects putting. In addition, the distance meter supports house maintenance work by providing length and horizontality measurement values within the indoor 80m measurement range, and provides safety from indoor or vehicle fires by providing indoor temperature measurement values to mobile phones through linkage with the web server. In order to evaluate the accuracy of the proposed method and its interworking performance with a smartphone, a prototype was produced and a web server was built, and the usefulness was confirmed by showing an acceptable error rate within 5% in repeated experiments.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.81-90
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• 2004

This paper presents new testability measure based on learning, which can be useful in the deterministic process of test pattern generation algorithms. This testability measure uses the structural information that are obtained by teaming. The proposed testability measure searches for test pattern that can early detect the conflict in case of the hardest decision problems. On the other hand in case of the easiest decision problem, it searches for test pattern that likely results in the least conflict. The proposed testability measure reduces CPU time to generate test pattern that accomplishes the same fault coverage as that of the distance-based measure.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.415-420
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• 1996

The main objective of the present study is to propose a new measure of uncertainty importance based on distributional sensitivity analysis. The new measure is developed to utilize a metric distance obtained from cumulative distribution functions (cdfs). The measure is evaluated for two cases: one is a cdf given by a known analytical distribution and the other given by an empirical distribution generated by a crude Monte Carlo simulation. To study its applicability, the present measure has been applied to two different cases. The results are compared with those of existing three methods. The present approach is a useful measure of uncertainty importance which is based on cdfs. This method is simple and easy to calculate uncertainty importance without any complex process. On the basis of the results obtained in the present work, the present method is recommended to be used as a tool for the analysis of uncertainty importance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.38-47
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• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure. Furthemore, it is recently reported that the Bhattacharyya distance can be used to estimate error of Gaussian ML classifier within 1-2% margin. In this paper, we propose a feature extraction method utilizing the Bhattacharyya distance. In the proposed method, we first predict the classification error with the error estimation equation based on the Bhauacharyya distance. Then we find the feature vector that minimizes the classification error using two search algorithms: sequential search and global search. Experimental reslts show that the proposed method compares favorably with conventional feature extraction methods. In addition, it is possible to determine how man, feature vectors arc needed for achieving the same classification accuracy as in the original space.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.3
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• pp.249-254
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• 2005

In this paper, we analysis the recognition performance of PCA/LDA by distance measures. We are adapt to ORL face database with the fourteen distance measures. In case of PCA, it has high performance for the manhattan distance and the weighted SSE distance to face recognition, In case of PCA/LDA, it has high performance for the angle-based distance and the modified SSE distance. Also, PCA/LDA is better than PCA for reduction of dimension. Therefore, the PCA/LDA method and the angle-based distance have the most performance and a few dimension for face recognition with ORL face database.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.45-49
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• 2012

VDL(VHF Data Link) Mode E uses TDMA(Time Division Multiple Access) based aeronautical communication technologies for airborne environments. In the VDL Mode E, aircraft uses RR(Reservation Requests) slot to request data slot. However, RR needs a long guard time, since aircraft communication spans a considerable distance. The more number of aircrafts causes a larger amount of guard times which can make a throughput decreased. In this paper, we propose an enhanced MAC to reduce the guard time by using the distance information of aircraft. The ground station sends management data including time stamp. And then all aircraft can measure their distance from the ground station.