• Journal of Oriental Neuropsychiatry
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• v.26 no.3
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• pp.283-292
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• 2015

Objectives: The study aimed to test the validity and reliability of the questionnaire for cold-heat & deficiency-excess pattern identification of dementia and establish a new version of the questionnaire. Methods: Mean, standard deviation, skewness, internal consistency, correlation and t-test of the 26 items derived from previous study was analyzed in 20 dementia patients. The items with Cronbach-${\alpha}$ coefficient below 0.7 were modified. Thus, we established a new version of the questionnaire consisting of 20 items. Results: Cronbach-${\alpha}$ of each cold, heat, deficiency and excess questionnaire was 0.662, -0.229, 0.722 and 0.778, respectively. The correlation coefficient between cold, heat, deficiency and excess was less than 0.4 and correlation coefficient between dementia and cold, deficiency was 0.518. On t-test, the t-value of cold, deficiency and dementia was -2.196. Conclusions: The results indicated that cold-heat, deficiency-excess questionnaires showed satisfactory discriminant validity. In addition, there was correlation between dementia and cold, deficiency. Finally, we established a new version of the questionnaire for cold-heat, deficiency-excess pattern identification that consisted of 20 items.

• Journal of Korean Medical classics
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• v.28 no.3
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• pp.107-124
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• 2015

Objectives : The purpose of this study is to identify Yangsaeng level and pattern identification of subfertility in childbearing aged women according to the pregnancy experience. Methods : Data was collected by structured questionnaire distributed to 217 women(125 women experienced pregnancy, 92 subfertile women) in I city from Nov. to Dec. 2014. For data analysis, Chi-square test, Fisher's exact test, t-test and Pearson's correlation coefficients were performed using SPSS version 19.0. Results : Drinking rate and stress level of subfertile group were higher than pregnancy experience group. Subfertile women group have more disease related to reproductive system, irregularities of the menstrual cycle and dysmenorrhea than pregnancy experience group. Subfertile women showed lower scores for Yangsaeng level but higher scores for all types of pattern identification of subfertility more than those in the women experiencing pregnancy. Conclusions : The results of this study indicate that reproductive health program for the childbearing aged women is necessary before serviced by western or oriental medical treatment for subinfertile(infertile) women. These results can be used for a program based on oriental medicine in order to improve women's health.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.201-208
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• 2008

An active RFID system has the advantages of a long identification distance and a good identification rate as well as overcoming the passive RFID's drawback such as the lowering of identification rate on metal materials. So, the development of an active RFID system has been gradually increasing in harbor logistics and the national defense area. On the other hand, some identification failures between products developed under the same standards have been reported, and there are difficulties in evaluating the interoperability between developed Products and standard conformance test because an accurate evaluation method and equipment has not been established at the international level. Motivated by these, this study presents a realization of the hardware and software of emulator to evaluate the standard conformance of an active RFID system, Performance of the designed system are then analyzed by means of simulations of Matlab/Simulink, and the applicability of the emulator is verified by evaluating the standard conformance of a real active RFID tag.

• Environmental Analysis Health and Toxicology
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• v.25 no.3
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• pp.207-214
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• 2010

Toxicity identification and quantification are important factors to evaluate the effect of industrial effluent on the aquatic environment. In order to measure the potential and real toxicity of mixed chemicals in the effluents, the biological method (i.e., WET test) should be used as well as chemical analysis method. In this study, we conducted WET test for various kinds of industrial effluents using aquatic organisms such as water flea (Daphnia magna), algae (Pseudokirchneriella subcapitata), fish (Oryzias latipes, Danio rerio), and microorganism (Vibrio fisheri). In addition, we carried out chemical analysis and TIE (Toxicity Identification Evaluation) for effluents in order to identify the substances causing toxicity. Among the 30 kinds of wastewater, S13 showed the highest eco-toxicity and $Ca^{2+}$ and $Cl^-$ ion were suspected as major compounds causing toxicity for aquatic organisms. In order to confirm these suspected compounds, various confirmation procedures need to be carried out.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.694-701
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• 2016

The smart phone application to provide auto identification and answer explanation of multiple choice answer for each OMR answer item in the test paper different from ordinary OMR test by using smart phone is very useful in terms of a self learning and a smart learning. In this paper, smart phone application of OMR mark identification for each question item in test paper is proposed. QR code for each OMR answer is provided for the encrypted correct answer and the reference location of multiple choice answer rectangle location. The OMR answer region is extracted and the marked answer is identified in each question of test paper, in order to compare between the marking answer and the correct answer. Experimental result of smart phone application of the proposed algorithm for the OMR answer images with various size and direction shows excellent recognition performance.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.204-212
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• 2021

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of ²²Na, ⁶⁰Co, and ¹³⁷Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM > ANN > CNN, while the training time followed the order SVM > ANN > CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.

• Journal of the Korean Institute of Telematics and Electronics
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• v.9 no.1
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• pp.17-24
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• 1972

A method utilizing vector representation is investigated for determining a faulty elenlent in passive and active networks by simple external measurements. A large system may be considered as an interconnection of a number of subnetlvorks. By utilizing the relationships between the magintudes of a transfer function at various frequencies and the deviations of a circuit element, the fault simulation curves can be drawn. The fault identification regions are defined from the fault simulation curves. A fault identlfication matrix is constructed corresponding the defined fault identification regions. The fault identification matrix, when premultiplied by a vector whose components are measured from a network, yieldg another vector whose components identify a network element which is faulty. A test procedure for the fault identification method is presented and verified by experiments.

• Computers and Concrete
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• v.20 no.5
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• pp.617-625
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• 2017

Prestress force identification (PFI) is crucial to maintain the safety of prestressed concrete bridges. A synergic identification method has been proposed recently by the authors that can determine the prestress force (PF) and the excitation force simultaneously in prestressed concrete beams with good accuracy. In this paper, the ability of this method in the application with prestressed concrete box-girder bridges is demonstrated. A reasonable assumption is made to capture the similarity of the dynamic behavior of the prestressed concrete box-girder bridge and a beam under a certain loading scenario, and the feasibility of this method for application in a prestressed box-girder bridge is affirmed. A comprehensive laboratory test program is conducted, and the effects of PF, excitation, measuring time and uncertainties are studied. Results show that the proposed method can predict the PF and the excitation force in a prestressed concrete box-girder accurately and has a great robustness against uncertainties.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.893-913
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• 2017

The handwriting based person identification systems use their designer's perceived structural properties of handwriting as features. In this paper, we present a system that uses those structural properties as features that graphologists and expert handwriting analyzers use for determining the writer's personality traits and for making other assessments. The advantage of these features is that their definition is based on sound historical knowledge (i.e., the knowledge discovered by graphologists, psychiatrists, forensic experts, and experts of other domains in analyzing the relationships between handwritten stroke characteristics and the phenomena that imbeds individuality in stroke). Hence, each stroke characteristic reflects a personality trait. We have measured the effectiveness of these features on a subset of handwritten Devnagari and Latin script datasets from the Center for Pattern Analysis and Recognition (CPAR-2012), which were written by 100 people where each person wrote three samples of the Devnagari and Latin text that we have designed for our experiments. The experiment yielded 100% correct identification on the training set. However, we observed an 88% and 89% correct identification rate when we experimented with 200 training samples and 100 test samples on handwritten Devnagari and Latin text. By introducing the majority voting based rejection criteria, the identification accuracy increased to 97% on both script sets.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.447-456
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• 2000

In this paper, we considered three methods for outlier identification sample surveys. First, we studied method of handling and adjusting outliers in normal population. Second, we studied existing methods using mean, maximum and minimum and proposed a test using of median which well reflects characteristic of data regardless of sampling distribution. Finally, we showed our test using median works better than Dixon and mean test through simulation.