• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.64-72
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• 2013

This paper proposes a dynamic gesture recognition algorithm using SVM(Support Vector Machine) which is suitable for multi-dimension classification. First of all, the proposed algorithm locates the beginning and end of the gestures on the video frames at the Kinect camera, spots meaningful gesture frames, and normalizes the number of frames. Then, for gesture recognition, the algorithm extracts gesture features using body parts' positions and relations among the parts based on the human model from the normalized frames. C-SVM for each dynamic gesture is trained using training data which consists of positive data and negative data. The final gesture is chosen with the largest value of C-SVM values. The proposed gesture recognition algorithm can be applied to the interactive storybook as gesture interface.

• Elastomers and Composites
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• v.39 no.1
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• pp.23-35
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• 2004

In this work, effects of hyper-elastic rubber material properties on the indentation load-deflection curve and subindenter deformation are first examined via finite element (FE) analyses. An optimal data acquisition spot is selected, which features maximum strain energy density and negligible frictional effect. We then contrive two normalized functions, which map an indentation load vs. deflection curve into a strain energy density vs. first invariant curve. From the strain energy density vs. first invariant curve, we can extract the rubber material properties. This new spherical indentation approach produces the rubber material properties in a manner more effective than the common uniaxial tensile/compression tests. The indentation approach successfully measures the rubber material properties and the corresponding nominal stress-strain curve.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.43-50
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• 2010

English vowels can be divided into monophthongs and diphthongs depending on the number of vocal tract shapes. Diphthongs are usually produced with more than one shape. This study attempts to collect acoustical data of English diphthongs published by Hillenbrand et al.(1995) online and to examine acoustic features of the diphthongs for phoneticians and English teachers. Sixty three American males and females were chosen after excluding those subjects with different target vowels or ambiguous formant tracks. The author used Praat to obtain the acoustical data systematically at eleven equidistant timepoints over the diphthongal segment. Obvious errors were corrected based on the spectrographic display of each diphthong. Results show that the formant trajectories of the diphthongs produced by the American males and females appeared quite similar. When the female formant values were uniformly normalized to those of the males, almost a perfect collapse occurred. Secondly, the diphthongal movements on the vowel space appeared not linear due to the coarticulatory gesture for the following consonant. Thirdly, the average duration of the diphthongs produced by the females was 1.156 times longer than that of the males while the pitch ratio between the two groups turned out to be 1.746 with a similar contour over measurement points. The author concludes that English diphthongs produced by various groups can be compared systematically when the acoustical values are obtained at proportional timepoints. Further studies will be desirable on the comparison of English diphthongs produced by native and nonnative speakers.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1366-1377
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• 2005

Experimental study was carried out in an atmospheric pressure, laboratory-scale dump combustor showing features of combustion instabilities. Flame structure and heat release rates were obtained from OH emission spectroscopy. Qualitative comparisons were made between line-integrated OH chemiluminescence image and Abel-transformed one. Local Rayleigh index distributions were also examined. Mean temperature, normalized standard deviation and temperature fluctuations were measured by coherent anti-Stokes Raman spectroscopy (CARS). To see the periodic behavior of oscillating flames, phase-resolved measurements were performed with respect to the pressure wave in the combustor. Results on system damping and driving characteristics were provided as a function of equivalence ratio. It also could be observed that phase resolved temperatures have been changed in a well-defined manner, while its difference between maximum and minimum reached up to 280K. These results would be expected to play an important role in better understanding of driving mechanisms and thermo-acoustic interactions.

• Korean Journal of Remote Sensing
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• v.7 no.2
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• pp.131-147
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• 1991

Feature enhancement combined with some pattern recognition techiques were applied to the Remote Sensing Data for geological mapping with particular emphasis on non-me-tallic ore deposits and their related geologies. The area chosen is north of Ulsan, the size of which is about 400km$^2$. The geology of the area consists mainly of volcanics, volcanic sediments and clastic sediments of Miocene age, underlain by the Kyungsang sediments of Cretaceous age. The mineralization occurs in tuffs or along the bedding plane of tuffaceous sediments, the main products of which are Kaolinite and Bentonite. The outcrops or mine dumps in the study area were most effectively extracted on the histrogram normalized image of TM Band 1 and 2, due to their high reflectivity. These may be confused with some artificial features, like slate roof complex of the poultry farm or cement ground, which should be classified by field checking. Detailed examination of enhancment image combined with pattern recognition techniques made enable to classify different rocks and thereby extract volcanic products which are mainly related to non-metallic ore deposits in the study area.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1266-1276
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• 2021

The mask parameters of a coded aperture are critical design features when optimizing the performance of a gamma-ray camera. In this paper, experiments and Monte Carlo simulations were performed to derive the minimum detectable activity (MDA) when one seeks a real-time imaging capability. First, the impact of the thickness of the modified uniformly redundant array (MURA) mask on the image quality is quantified, and the imaging of point, line, and surface radiation sources is demonstrated using both cross-correlation (CC) and maximum likelihood expectation maximization (MLEM) methods. Second, the minimum detectable activity is also derived for real-time imaging by altering the factors used in the image quality assessment, consisting of the peak-to-noise ratio (PSNR), the normalized mean square error (NMSE), the spatial resolution (full width at half maximum; FWHM), and the structural similarity (SSIM), all evaluated as a function of energy and mask thickness. Sufficiently sharp images were reconstructed when the mask thickness was approximately 2 cm for a source energy between 30 keV and 1.5 MeV and the minimum detectable activity for real-time imaging was 23.7 MBq at 1 m distance for a 1 s collection time.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.316-321
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• 2022

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly, infecting millions of people worldwide. On March 11, 2020, the World Health Organization declared coronavirus disease (COVID-19) a pandemic owing to the worldwide spread of SARS-CoV-2, which created an unprecedented burden on the global healthcare system. In this context, there are increasing concerns regarding co-infections with other respiratory viruses, such as the influenza virus. In this study, clinical data of patients infected with SARS-CoV-2 and other respiratory viruses were compared with patients infected with SARS-CoV-2 alone. The hematology and blood biochemistry results of 178 patients infected with SARS-CoV-2 , who were tested on admission, were retrospectively reviewed. In patients with SARS-CoV-2 and adenovirus co-infection, C-reactive protein levels were elevated on admission, whereas lactate dehydrogenase (LDH), prothrombin time, international normalized ratio, activated partial thromboplastin clotting time, and bilirubin values were all within the normal range. Moreover, patients with SARS-CoV-2 and human bocavirus co-infection had low LDH and high bilirubin levels on admission. These findings reveal the clinical features of respiratory virus and SARS-CoV-2 co-infections and support the development of appropriate approaches for treating patients with SARS-CoV-2 and other respiratory virus co-infections.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.715-721
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• 2000

In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

• The Korean Journal of Quaternary Research
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• v.18 no.2 s.23
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• pp.105-106
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• 2004

The NDVI(normalized difference vegetation index) dataset is unique or main tool to assess the global, multi seasonal, multi annual, and multi spectral changes over the World. These features are useful for environmental studies in particular, for the vegetation coverage monitoring of the country as Mongolia, where are large pastureland and pastoral animal husbandry, which dependent on natural conditions. Pasture vegetation cover is changing accordingly with both of global climate change and anthropogenic effect or human impacts. Using past 20 years (1982-2001) NDVI derived from NOAA satellite, its dynamical trend has been decreased in all natural zones differently. Also applied the method named "Two Years Differences" which could calculate the number of years with increased or decreased NDVI values at the same place. From May to September have occurred the 9 years maximum decreases of NDVI over Mongolia, but it obtained differently in spatial and temporal scale. In 24.4 ? 32.7% of all territory occurred one year decrease of NDVI and in 18% occurred more than 3 years frequent decrease of NDVI. According to the linear trend of NDVI and in 18% occurred more than 3 years frequent decrease of NDVI dynamics over 69% of whole territory of Mongolia NDVI values had been decreased due to both natural and human induced impacts to the pasture condition. In this paper also included some results of the integrated analyses of NOAA/NDVI and ground truth data over Monglia separately by natural zones.