• Genomics & Informatics
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• v.11 no.4
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• pp.277-281
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• 2013

RNA analysis has become a reliable method of body fluid identification for forensic use. Previously, we developed a combination of four multiplex quantitative PCR (qRT-PCR) probes to discriminate four different body fluids (blood, semen, saliva, and vaginal secretion). While those makers successfully identified most body fluid samples, there were some cases of false positive and negative identification. To improve the accuracy of the identification further, we tried to use multiple markers per body fluid and adopted the NanoString nCounter system instead of a multiplex qRT-PCR system. After measuring tens of RNA markers, we evaluated the accuracy of each marker for body fluid identification. For body fluids, such as blood and semen, each body fluid-specific marker was accurate enough for perfect identification. However, for saliva and vaginal secretion, no single marker was perfect. Thus, we designed a logistic regression model with multiple markers for saliva and vaginal secretion and achieved almost perfect identification. In conclusion, the NanoString nCounter is an efficient platform for measuring multiple RNA markers per body fluid and will be useful for forensic RNA analysis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.857-860
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• 1993

In this paper, we apply the self generating neuro fuzzy model (SGNFM) to the dimension analysis of the chaotic time series. Firstly, we formulate a nonlinear time series identification problem with nonlinear autoregressive (NARMAX) model. Secondly, we propose an identification algorithm using SGNFM. We apply this method to the estimation of embedding dimension for chaotic time series, since the embedding dimension plays an essential role for the identification and the prediction of chaotic time series. In this estimation method, identification problems with gradually increasing embedding dimension are solved, and the identified result is used for computing correlation coefficients between the predicted time series and the observed one. We apply this method to the dimension estimation of a chaotic pulsation in a finger's capillary vessels.

• The Journal of Korean Medicine
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• v.42 no.1
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• pp.1-11
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• 2021

Objectives: This pilot study aimed to evaluate the agreement between traditional face-to-face Korean medicine (KM) pattern identification and non-face-to-face KM pattern identification using the data from related questionnaires, tongue image, and pulse features in patients with cancer. Methods: From January to June 2020, 16 participants with a cancer diagnosis were recruited at the one Korean medicine hospital. Three experienced Korean medicine doctors independently diagnosed the participants whether they belong to the cold pattern or not, heat pattern or not, deficiency pattern or not, and excess pattern or not. Another researcher collected KM pattern related data using questionnaires including Cold-Heat Pattern Identification (CHPI), tongue image analysis system, and pulse analyzer. Collected KM pattern related data without participants' identifier was provided for the three Korean medicine doctors in random order, and non-face-to-face KM pattern identification was carried out. The kappa value between face-to-face and non-face-to-face pattern identification was calculated. Results: From the face-to-face pattern identification, there were 13/3 cold/non-cold pattern, 4/12 heat/non-heat pattern, 14/2 deficiency/non-deficiency pattern, and 0/16 excess/non-excess pattern participants. In cold/non-cold pattern, kappa value was 0.455 (sensitivity: 0.85, specificity: 0.67, accuracy: 0.81). In heat/non-heat pattern, the kappa value was 0.429 (sensitivity: 0.75, specificity: 0.72, accuracy: 0.75). The kappa value of deficiency/non-deficiency and excess/non-excess pattern was not calculated because of the few participants of non-deficiency, and excess pattern. Conclusions: The agreement between traditional face-to-face pattern identification and non-face-to-face pattern identification seems to be moderate. The non-face-to-face pattern identification using questionnaires, tongue, and pulse features may feasible for the large clinical study.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.1
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• pp.15-21
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• 2010

Previously standardization study for identifying 5 types of pattern identification of stroke patients has been performed and the Korean standard of pattern identification (II) was developed. In the present study we investigated the interactions between total indices designated by the Korean standard of pattern identification(KSPI II) and indices for PI of Cold-Heat and Deficiency-Excess. Indicators for Cold-Heat and Deficiency-Excess are isolated from 58 indices through the survey of oriental medicine doctors and their relationship with KSPI-II indices was analyzed by corresponding analysis method using data of 1581 stroke patients. Means and standard deviations indicated that 2 Cold indices, 14 Heat indices, 12 Deficiency indices, and 5 Excess indices were included for Cold-Heat and Deficiency-Excess pattern identification. The results of corresponding analysis shows the relationship of 57 indices and 4 types of pattern identification (excluding 1 index and 1 pattern among 58 indices and 5 patterns) using the cross-tabulation which was obtained from the clinical data. Most of Cold and Heat index were divided to dimension 1(inertia 51.9%) obtained from the result of corresponding analysis. Deficiency and Excess index were partially associated with dimension 2(inertia 31.7%). These data suggest that pattern identification of Cold-Heat plays an role in the standardization of pattern identification in stroke, although further studies are required by various trials such as analysis of surveys and clinical data.

• Journal of the Korean Wood Science and Technology
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• v.45 no.6
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.

• Korean Journal of Microbiology
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• v.30 no.4
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• pp.278-285
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• 1992

Chemotaxonomic and numerical identification were carried out for a isolate of Streptomyces strain SMF301 producing spores in submerged culture. Fifty taxonomic unit characters were tested and the data were analyzed numerically using the TAXON program. The isolate SMF301 was identified to cluster 1A of Streptomyces and best matched to Streptomyces limosus which is a synonym of Streptomyces albidoflavus. Therefore, it was concluded that the isolate was identified to be a member of Streptomyces alidoflavus.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.15-18
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• 2007

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.762-766
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• 2005

This study was conducted to establish an individual identification system comprising of 19 microsatellite markers located on different bovine autosomes. The markers were typed on 257 animals from five cattle breeds. In total, 112 alleles were detected from the genotyping of 19 microsatellite markers. The average heterozygosities ranged from 0.292 to 0.824 and the polymorphic information content (PIC) ranged from 0.274 to 0.817 in Hanwoo. We found that there were differences in allele frequencies in Hanwoo when compared with other cattle breeds. The calculated cumulative power of discrimination (CPD) was 99.999% when nine microsatellite loci were used for analysis in the individual identification system. Also the matching probability, the probability that two unrelated animals would show the same genotypes, was estimated to be $0.44{\times}10^{-9}$. Therefore, the nine markers used in this study will be used for individual identification in two million Hanwoo individuals.

• The Journal of the Society of Stroke on Korean Medicine
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• v.13 no.1
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• pp.24-32
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• 2012

Object : The purpose of this study is to observe the correlation between change in pattern identification symptoms and scandinavian stroke scale in ischemic stroke patient who had receive traditional Korean medical treatment and conservative treatment. Methods : 43 subjects were recruited from patients with ischemic stroke within 30 days of onset. We chose the subjects who had at least one follow up session and had checked the score between last follow up session and first session in pattern identification and scandinavian stroke scale. We also assessed the correlation between pattern identification and scandinavian stroke scale. Results : There were significant negative correlation between pattern identification and scandinavian stroke scale in Fire-heat pattern and positive correlation in Dampness-phlegm pattern. Conclusions : This study provides evidence that collaborative treatment maybe effective in improving neurologic symptoms in ischemic stroke patients diagnosed as Fire-heat pattern. Further studies with larger scale and longer observation period, more neurologicscales scales, control group would be required.

• Proceedings of the Korean Biophysical Society Conference
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• 1999.06a
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• pp.17-17
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• 1999

Almost half of the entire set of predicted genomic products from M ethanococcus jannaschii are classified as functionally unknown hypothetical proteins. We present a structure-based identification of the biochemical function of a protein with hitherto-unknown function from a M. jannaschii gene, Mj0226.(omitted)