• Korean Journal Plant Pathology
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• v.11 no.4
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• pp.374-379
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• 1995

The cDNA of tobacco mosaic virus-pepper strain (TMV-P) coat protein (CP) genes were introduced into tobacco plants (Nicotiana tabacum cv. Samsun nn) using a binary Ti plasmid vector of Agrobacterium tumefaciens. these cDNAs introduced into tobacco plants were detected by polymerase chain reaction. Symptom development was distinctly suppressed in the transgenic plant introduced buy sense CP cDNA when the plant was inoculated with TMV-P, while in transgenic tobacco plants of antisense CP gene, symptom development was not suppressed as in non-transgenic plants. TMV-P concentration in the sense CP transgenic tobacco plant was decreased to 1/14 of the concentration in non-transgenic plants. Expression of the kanamycin resistance gene of these transgenic plants could be detected in the progeny.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.433-444
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• 2016

When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.561-574
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• 2010

We studied the performance of 8 data mining algorithms including decision trees, logistic regression, LDA, QDA, Neral network, and SVM and their combinations of 2 ensemble techniques, bagging and boosting. In this study, we utilized 13 data sets with binary responses. Sensitivity, Specificity and missclassificate error were used as criteria for comparison.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.212-217
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• 2007

As a preliminary study for the development of electrical stimulation strategy of artificial retina, we set up a method fur the reconstruction of input intensity variation from retinal ganglion cell(RGC) responses. In order to estimate light intensity variation, we used an optimal linear filter trained from given stimulus intensity variation and multiple single unit spike trains from RGCs. By applying ON/OFF stimulation(ON duration: 2 sec, OFF duration: 5 sec) repetitively, we identified three functional types of ganglion cells according to when they respond to the ON/OFF stimulus actively: ON cell, OFF cell, and ON-OFF cell. Experiments were also performed using a Gaussian random stimulus and a binary random stimulus. The input intensity was updated once every 90 msec(i. e. 11 Hz) to present the stimulus. The result of reconstructing 11 Hz Gaussian and binary random stimulus was not satisfactory and showed low correlation between the original and reconstructed stimulus. In the case of ON/OFF stimulus in which temporal variation is slow, successful reconstruction was achieved and the correlation coefficient was as high as 0.8.

• Molecules and Cells
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• v.43 no.11
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• pp.909-920
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• 2020

Cytosolic Ca²⁺ levels ([Ca²⁺]_c) change dynamically in response to inducers, repressors, and physiological conditions, and aberrant [Ca²⁺]_c concentration regulation is associated with cancer, heart failure, and diabetes. Therefore, [Ca²⁺]_c is considered as a good indicator of physiological and pathological cellular responses, and is a crucial biomarker for drug discovery. A genetically encoded calcium indicator (GECI) was recently developed to measure [Ca²⁺]_c in single cells and animal models. GECI have some advantages over chemically synthesized indicators, although they also have some drawbacks such as poor signal-to-noise ratio (SNR), low positive signal, delayed response, artifactual responses due to protein overexpression, and expensive detection equipment. Here, we developed an indicator based on interactions between Ca²⁺-loaded calmodulin and target proteins, and generated an innovative GECI sensor using split nano-luciferase (Nluc) fragments to detect changes in [Ca²⁺]_c. Stimulation-dependent luciferase activities were optimized by combining large and small subunits of Nluc binary technology (NanoBiT, LgBiT:SmBiT) fusion proteins and regulating the receptor expression levels. We constructed the binary [Ca²⁺]_c sensors using a multicistronic expression system in a single vector linked via the internal ribosome entry site (IRES), and examined the detection efficiencies. Promoter optimization studies indicated that promoter-dependent protein expression levels were crucial to optimize SNR and sensitivity. This novel [Ca²⁺]_c assay has high SNR and sensitivity, is easy to use, suitable for high-throughput assays, and may be useful to detect [Ca²⁺]_c in single cells and animal models.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.61-70
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• 2008

The study proposed a new type of bus information, Real-time Bus Crowdedness (RBC) information, to meet various demands of users and improve the convenience level of using public transportation, while existing bus information provided by bus information systems(BIS) were limited to bus operating information such as predicted bus arrival time. To analyze the impacts of providing the proposed RBC information, stated preference(SP) survey was performed and a methodology of disaggregate analysis (e.g., binary logit) was applied to develop passenger choice models. Additionally, passenger choice models incorporating the heterogeneity of different user groups(i.e., by age or trip purposes) were developed to evaluate the different responses on RBC information. The results showed that providing RBC information was significantly related to users' bus choices and the responses of user groups were significantly different, especially the age group of more then 60 was most affected by the RBC information on their bus choices. Also trip purposes were significantly related to users' bus choices, for instance the impacts of providing RBC information was bigger for non-business trips(leisure/meet friend/personal business, shopping, hospital) compared to business trip.

• The Journal of Korean Obstetrics and Gynecology
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• v.26 no.1
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• pp.82-91
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• 2013

Objectives: The purpose of this study is to find out the patterns of teenage girls who is easy to suffer from Menstrual Disorders. Methods: The data from the 1681 participants were collected using a structured menstrual history questionnaire. Based on the survey responses, we had 97 adolescents with menstrual disorder as the test group and 97 adolescents without menstrual disorder as the control group. The clinical trials subjects were asked to respond to another questionnaire for identifying Blood Pressure Pulse Analyzer tests. We identified significant variables for dysmenorrhea from comparison between the test and control group; a binary response variable from the test group's responses for ever experiencing dysmenorrhea and explanatory variables from Blood Pressure Pulse Analyzer. Results: The reselts of Blood Pressure Pulse Analyzer test showed that the score of Energ_R, EIX_R were lower in dysmenorrhea group than the control group. The reselts of Blood Pressure Pulse Analyzer test showed that the score of Energ_R, EIX_R were lower, and T4_R were higher in hypomenorrhea group than the control group. The reselts of Blood Pressure Pulse Analyzer test showed that the score of Energ_R, EIX_R were lower in Irregular Menstruation group than the control group. Conclusions: Blood Pressure Pulse Analyzer test showed that the score of Energ_R, EIX_R were lower in the test group than the control group.

• KSBB Journal
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• v.16 no.5
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• pp.480-485
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• 2001

Genetic transformation in dandelion(Taraxacum mongolicum Hand). was studied. We used for transformation by Agrobacterium tumefaciens strian LBA4404 harboring a binary vector pBI121 carrying the CaMV 35S promoter-GUS gene fusion used as a reporter gene and NOS promoter-NPTII gene as a positive selection marker. To obtain transformed plants, leaf explants of dandelion were cocultured with Agrobacterium tumefaciens LBA4404 for 10 mins, then transferred to MS medium containing 1 $\mu$M IAA, 1$\mu$M BA, 100$\mu$g/ML carbenicillin and 50 $\mu$g/ML kanarmycin sulfate. After two weeks of subculture of the explants, Kanamycin-resistant shoots were formed on explants survived. When subjected to GUS histochemical assay, all of the regenerants showed the GUS-positive responses. Plantlets were be be transformed to soil for further growth.

• ETRI Journal
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• v.32 no.5
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.