• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• Current Optics and Photonics
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• v.5 no.2
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• pp.164-172
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• 2021

In this paper a catadioptric laser-irradiation-precision test system is designed, to achieve a high-precision laser-irradiation-accuracy test. In this system, we adopt the method of imaging the entire target surface at a certain distance to realize the measurement of laser-irradiation precision. The method possesses the advantages of convenient operation, high sensitivity, and good stability. To meet the test accuracy requirement of 100 mm/km (0.01%), the coma, field curvature, and distortion over the entire field of view should be eliminated from the optical system's design. Taking into account the whole length of the tube and the influence of stray light on the structure type, a catadioptric system with a hood added near the primary imaging surface is designed. After optimization using the ZEMAX software, the modulation transfer function (MTF) of the designed optical system is 0.6 at 30 lp/mm, the full-field-of-view distortion is better than 0.18%, and the energy concentration in the 10-㎛-radius surrounding circle reaches about 90%. The illumination-accuracy test results show that the measurement accuracy of the radiation hit rate is better than 50 mm when the test distance is 1 km, which is better than the requirement of 100 mm/km for the laser-irradiation-accuracy test.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.1645-1651
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• 2015

This paper describes the changes of shape accuracy in workpiece materials depending on the turning clearance angle. The experiments started from choosing three workpiece materials, SM45C(machine structural carbon steel), STS303(stainless steel) and SCM415 (chrome-molybdenum steel). The experiments showed specifically how features of selected materials changed when they were processed with diverse machining depths, 0.1 mm, 0.2 mm and 0.3 mm, with various negative angles, $0.0^{\circ}(-6.0^{\circ})$, $0.3^{\circ}(-6.3^{\circ})$ and $0.9^{\circ}(-6.9^{\circ})$, and called cutting edge inclination starting from a fixed rotational speed, 2,500 rpm, focusing on the feed rate, 0.07 mm/rev and 0.10 mm/rev. The results of the accuracy of processing, cylindricity, deviation from coaxiality, etc. were compared using the graph and table. The accuracy of cylindricity in the order of degree $0.0^{\circ}{\rightarrow}0.3^{\circ}{\rightarrow}0.9^{\circ}$ depending on the workpiece materials showed the best cylindricity when it was $0.9^{\circ}$. In conclusion, the accuracy improved in specific degrees irrespective of the quality of the materials when the bite negative angles increased. This means that workability improved in these experiments. In addition, the processing shape changed depending on depth of the cut and feed rate.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.95-106
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• 2013

The study compares accuracies between humans and computer algorithms in the discrimination of spontaneous smiles from posed smiles. For this purpose, subjects performed two tasks, one was judgment with single pictures and the other was judgment with pair comparison. At the task of judgment with single pictures, in which pictures of smiling facial expression were presented one by one, subjects were required to judge whether smiles in the pictures were spontaneous or posed. In the task for judgment with pair comparison, in which two kinds of smiles from one person were presented simultaneously, subjects were to select spontaneous smile. To calculate the discrimination algorithm accuracy, 8 kinds of facial features were used. To calculate the discriminant function, stepwise linear discriminant analysis (SLDA) was performed by using approximately 50 % of pictures, and the rest of pictures were classified by using the calculated discriminant function. In the task of single pictures, the accuracy rate of SLDA was higher than that of humans. In the analysis of accuracy on pair comparison, the accuracy rate of SLDA was also higher than that of humans. Among the 20 subjects, none of them showed the above accuracy rate of SLDA. The facial feature contributed to SLDA effectively was angle of inner eye corner, which was the degree of the openness of the eyes. According to Ekman's FACS system, this feature corresponds to AU 6. The reason why the humans had low accuracy while classifying two kinds of smiles, it appears that they didn't use the information coming from the eyes enough.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.788-791
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• 2006

The perception of English labial consonants was investigated via experiment where 40 Korean EFL learners identified nonwords with the target labial consonants [p, b, f, v] in 4 different prosodic locations. The results showed that there was a strong positional effect since the accuracy rates of the four target consonants differed by position. Specifically, the average accuracy rate for the target consonants was higher in the stressed intervocalic position and initial onset position than in the unstressed intervocalic position and final coda position. Further, the accuracy rate for [f] is was high in all prosodic locations except the unstressed intervocalic position. This is unexpected in markedness theory given that fricatives are assumed to be more difficult to learn than stops.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.489-498
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• 2006

In this paper, we suggested a vehicle classification algorithm using pattern recognition method. At present, Inductive Loop Detector is rarely used for vehicle classification because of its low accuracy. To improve the accuracy, we suggest a new algorithm for Loop Detector using neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and occupancy-time. The output is classified vehicles. The developed algorithm was assessed at test sites and the recognition rate was 91.3percent. The results verified that the proposed algorithm improves the vehicle classification accuracy compared to the conventional method based on Loop Detector.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.39-50
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• 2016

In this paper, we present a comparative study of spatial domain features for writer identification and verification with different ink width conditions. The existing methods give high error rates, when comparing two handwritten images with different pen types. To the best of our knowledge, we are the first to design the feature with different ink width conditions. To address this problem, contour based features were extracted using a chain code method. To improve accuracy at higher levels, we considered histograms of chain code and variance in bins of histogram of chain code as features to discriminate handwriting samples. The system was trained and tested for 1,000 writers with two samples using different writing instruments. The feature performance is tested on our newly created dataset of 4,000 samples. The experimental results show that the histogram of chain code feature is good compared to other methods with false acceptance rate of 11.67%, false rejection rate of 36.70%, average error rates of 24.18%, and average verification accuracy of 75.89% on our new dataset. We also studied the effect of amount of text and dataset size on verification accuracy.

• The Journal of Korean Society for Radiation Therapy
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• v.10 no.1
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• pp.30-44
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• 1998

Accurate delivery of doses using a high dose rate(HDR) brachytherapy, remote afterloading system(RALS) depends on knowing the strength of the radioactive source at the time of treatment, the precision and consistency of the timer, and the ability of the unit to position the source at the proper dwell location along the applicator. Periodic Quality Assurance(QA) on HDR machines is a part of the standard protocol of any user. The safety of the patient & staff, positional accuracy, temporal accuracy, and dose delivery accuracy are periodically(weekly, quarterly, monthly) estimated using HDR source(Ir-192), treatment planning devices, measurement devices, and overall treatment devices with regard to treatment delivery. The overall measurement results are estimated successfully and assessed its clinical significance. As a result, our HDR brachytherapy units has been very accurate until now. The QA program protocol permits routine clinical use and provides a high confidence level in the accurate operation of HDR units. Therefore, regular QA of HDR brachytherapy is essential for successful treatment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2159-2164
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• 2008

Ubiquitous healthcare system is system that monitors and manages user's health information, and most important in the healthcare system is accuracy of the measured health data. But, the accuracy changes remarkably according to user's motion artifacts in real life. To elevate accuracy of health data, we proposed new algorithm to detect maximum point of pulse wave for heart rate extraction. and the proposed algorithm is to detect maximum points detect of pulse wave in photo-plethysmography signal included motion artifacts by fuzzy inference and multi sub-band filters. In results of experiment to evaluate the performance of the proposed algorithm, we could verify the proposed algorithm extracted maximum point of pulse wave in complex motion artifacts.