• Journal of Physiology & Pathology in Korean Medicine
• /
• v.32 no.6
• /
• pp.370-374
• /
• 2018

Oriental Diagnosis System(ODS) is an artificial intelligence program that utilize entered diagnosis knowledge, determine patient's disease and decide right medicine. The purpose of this study is to find a correlation between pattern Identification in Korean medicine and each sasang types(Tae-Eum and So-Yang) by analyzing ODS diagnosis result. Eventually our study secure availability of using ODS program at clinical training or developing diagnosis program. Subject of this study is 50 patients who was performed Sasang constitution diagnosis (28 patients were Tae-Eum and 22 patients were So-Yang). We analyize patient's diagnosis records by using ODS program and obtained result about pattern Identification. We used SPSS statistics 23 in analyzing the differences of the scores of Eight Principle Pattern Identification, Qi-Blood Pattern Identification, and Bing-xie Pattern Identification in each Sasang types (Tae-Eum, So-Yang). The Heat and Heat-moisture scores were significantly different(p<0.05) and Qi-Blood Pattern Identification scores were not different in each Sasang types(p>0.05). And Weight was significantly different in each Sasang types(p<0.05). It is hard to generalize the result because subject of this study was not enough and had sample speciality(tinnitus patients). However, we explained correlation between pattern Identification in korean medicine and each sasang types based on quantifiable and objective evidence system. it can be used at education of korean medicine and evidence of practice diagnosis. Futhermore, there have been no studies about anaylizing correlation between pattern Identification in Korean medicine and each sasang types using ODS program. So it is worthy of being utilized at clinical evidence data of ODS program.

• Structural Engineering and Mechanics
• /
• v.11 no.3
• /
• pp.237-258
• /
• 2001

Structural identification via modal analysis in structural mechanics is gaining popularity in recent years, despite conceptual difficulties connected with its use. This paper is devoted to illustrate both the capabilities and the indeterminacy characterizing structural identification problems even in quite simple instances, as well as the cautions that should be accordingly adopted. In particular, we discuss an application of an identification technique of variational type, based on the measurement of eigenfrequencies and mode shapes, to a steel frame with friction joints under various assembling conditions. Experience has suggested, so as to restrict the indeterminacy frequently affecting identification issues, having resort to all the a priori acknowledged information on the system, to the symmetry and presence of structural elements with equal stiffness, to mention one example, and mindfully selecting the parameters to be identified. In addition, considering that the identification techniques have a local character and correspond to the updating of a preliminary model of the structure, it is important that the analytical model on the first attempt should be adequately accurate. Secondly, it has proved determinant to cross the results of the dynamic identification with tests of other typology, for instance, static tests, so as to fully understand the structural behavior and avoid the indeterminacy due to the nonuniqueness of the inverse problem.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.3
• /
• pp.419-426
• /
• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of Distribution Science
• /
• v.17 no.10
• /
• pp.49-59
• /
• 2019

Purpose - This study aims to verify the effect of sports sponsorship recognition on corporate image and the relationship between image and identification, corporate image and purchasing intention, brand identification and purchasing intention Research design, data, and methodology - To carry out the purpose of this study, a set of data was collected from 320 surveys and 305 of them were used. Statistic programs, SPSS 18.0 and AMOS 20.0, were used to analyze the data. Results - It was found that emotional sports sponsorship recognition and social sponsorship sports sponsorship recognition had positive effects on corporate image and brand identification. Corporate image also had a positive effect on brand identification. Besides, it was analyzed that corporate image and brand identification had positive effects on purchasing intention. Conclusions - The results show that sports sponsorship recognition can influence brand identification and purchasing intention, and contribute to the enhancement of corporate image. Since brand personality that matches the self-image of the targeted customer will have a more positive effect on the relationship with the consumer, marketing activities should be carried out so that the brand image can be identified with the company image of sports sponsorship activities.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.2 s.344
• /
• pp.39-43
• /
• 2006

This paper deals with the AR Identification of unknown system using cumulant, which is the 3rd order statistics of output signal in the presence of the noise signal. The algorithms for identification of unknown system we applies to the AR identification method using the cumulant which is possible to the guarantees of global convergence and the representation of amplitude and phase information of system among with the method of parametric modeling. In the process of identification, we considered unknown system to the one of AR system. After the generation of input signal, it was being passed through the system then We use the its output signal that the noise is added. As a result of identification of AR system by changing the signal to noise ratio, we get the fairly good results compared to original system output values and confirmed that the pole was located in the unit circle of z transform.

• Journal of Microbiology
• /
• v.33 no.2
• /
• pp.95-102
• /
• 1995

A probability identification matrix of acidophilic Streptomyces was constructed. The phenetic data of the strains were derived from numerical classification described by Seong et al. The minimum number of diagnostic characters was determined using computer programs for calculation of different separation indices. The resulting matrix consisted of 25 clusters versus 53 characters. Theoretical evaluation of this matrix was achieved by estimating the chuster overlap and the identification scores for the Hypothetical Median Organisms (HMO) and for the representatives of each cluster. Cluster overlap was found to be relatively small. Identification scores for the HMO and the randomly selected representatives of each cluster were satisfactory. The matrix was assessed practically by applying the matrix to the identification of unknown isolates. Of the unknown isolates, 71.9% were clearly identified to one of eight clusters. The numerical classification data was also used to design a selective isolation medium for antibiotic-producing organisms. Four chemical substances including 2 antibiotics were determined by the DLACHAR program as diagnostic for the isolation of target organisms which have antimicrobial activity against Micrococcus luteus. It was possible to detect the increased rate of selective isolation on the synthesized medium. Theresults show that the numerical phenetic data can be applied to a variety of purposes, such as construction of identification matrix and selective isolation medium for acidophilic antinomycetes.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.7
• /
• pp.51-61
• /
• 2017

Purpose - Present study investigates character identification and emotional response to character that may affect consumers' intention to purchase the character-attached products. And this study explores whether symbolic relevance and object relevance affect the character identification, and whether character attractiveness and character salience affect the emotional response to characters. Research design, data, and methodology - SNS characters, animated characters, game characters, and traditional characters were used as experimental characters. And stationery as experimental product was used. 250 college students participated in the empirical study, and structural equation model was used to verify hypotheses. Results - First, the character identification and emotional response to characters affected the intention to purchase the products positively, and the emotional response to characters also positively affected character identification; second, symbolic relevance had no positive impact upon character identification, while object relevance had positive influence on character identification; and third, character attractiveness and salience had a positive effect on the emotional response. Conclusions - Present study contributes to the progress of character theories. Marketers should find ways to increase consumers' object relevance to characters and the level of characters' attractiveness and salience in order to promote the intent to purchase the products.

• Journal of KIISE
• /
• v.42 no.2
• /
• pp.220-226
• /
• 2015

Semantic role labeling (SRL) systems determine the semantic role labels of the arguments of predicates in natural language text. An SRL system usually needs to perform four tasks in sequence: Predicate Identification (PI), Predicate Classification (PC), Argument Identification (AI), and Argument Classification (AC). In this paper, we use the Korean Propbank to develop our Korean semantic role labeling system. We describe our Korean semantic role labeling system that uses sequence labeling with structured Support Vector Machine (SVM). The results of our experiments on the Korean Propbank dataset reveal that our method obtains a 97.13% F1 score on Predicate Identification and Classification (PIC), and a 76.96% F1 score on Argument Identification and Classification (AIC).

• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.2
• /
• pp.283-295
• /
• 2010

Although some large units, upper than division, have a identification system, most of them depend on US military. Especially, the company unit can not but execute GOP(General OutPost) guidance and battles inefficiently because they apply the method of conventional identification system. urrently, North Korea causes the high tension of peninsular by experimenting nuclear weapons and launching ICBM(Intercontinental Ballistic Missile). In addition, ROK military will reduce the number of personnel and division through reorganizing the structure into NCW (Network Centric Warfare) until 2020. These unstable situation and future tendency require the high technical identification system based on USN(Ubiquitous Sensor Network) in company unit level. his study suggests the method that the company unit apply the identification system based on USN which distinguish between friend and foe in the warfare. The identification system concludes the results through experiment of military analysis model (AWAM; Army Weapon effectiveness Analysis Model). After analyzing the experiment results, it indicates the budget requirement and operational operability of identification system. This will be able to improves battle efficiency and to prevent damages of friendly forces.

• Structural Engineering and Mechanics
• /
• v.30 no.2
• /
• pp.191-209
• /
• 2008

A structural monitoring system based on cheap and wireless monitoring system is investigated in this paper. Due to low-cost and low power consumption, micro-electro-mechanical system (MEMS) is suitable for wireless monitoring and the use of MEMS and wireless communication can reduce system cost and simplify the installation for structural health monitoring. For system identification using wireless MEMS, a finite element (FE) model updating method through correlation with the initial analytical model of the structure to the measured one is used. The system identification using wireless MEMS is evaluated experimentally using a three storey frame model. Identification results are compared to ones using data measured from traditional accelerometers and results indicate that the system identification using wireless MEMS estimates system parameters with reasonable accuracy. Another smart sensor considered in this paper for structural health monitoring is Lead Zirconate Titanate (PZT) which is a type of piezoelectric material. PZT patches have been applied for the health monitoring of structures owing to their simultaneous sensing/actuating capability. In this paper, the system identification for building structures by using PZT patches functioning as sensor only is presented. The FE model updating method is applied with the experimental data obtained using PZT patches, and the results are compared to ones obtained using wireless MEMS system. Results indicate that sensing by PZT patches yields reliable system identification results even though limited information is available.