• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.194-200
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• 2022

Traditionally, postal services that produce and deliver paper-based notices have been the mainstream. The reason is that it has the function of distribution and proof of delivery in the postal delivery system as well as the advantage of information delivery through postal delivery. After all, for the purpose of distribution and proof of delivery, many organizations use paper-based postal notices. However, in recent years, it has been in the spotlight to produce a paper-based postal notice as an electronic notice and deliver information to a mobile device through the Internet. In this paper, we propose a safe interworking method for user identification information required for private institutions to transmit mobile electronic notices. In order for a private institution to accurately deliver an electronic notice to a mobile service subscriber, a means to confirm whether the private institution and the mobile device subscriber are the same person is required. In the mobile electronic notification service, the connecting information provided by the personal identity proofing agency is used as a means of user identification. Connecting information is called a resident registration number on the Internet and is one-way hash information that can only be created by the personal identity proofing agency designated by the government. In order to transmit a mobile electronic notice, it is necessary to share connecting information for the same user identification between the institution that requests the sending of the electronic notice and the institution that processes the sending of the electronic notice. Connecting information is personal information that can uniquely identify a user, and if it is disclosed, damage such as personal information infringement may occur. As such, it is necessary to prevent problems that may arise from misuse and abuse of connecting information as well as increase in the benefits of sending the mobile electronic notice. In this paper, a safe and effective mobile electronic notification service can be performed by suggesting a method for safe interworking of information related to the mobile electronic notification service.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.277-283
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• 2014

Fuzzy modeling is generally using the given data and the fuzzy rules are established by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is presented by selection of the input variables, the number of space division and membership functions and in this paper the consequent part of the fuzzy rule is identified by polynomial functions in the form of linear inference and modified quadratic. Parameter identification in the premise part devides input space Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. In this paper, membership function of the premise part is dividing input space by using trapezoid-type membership function and by using gas furnace process which is widely used in nonlinear process we evaluate the performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.491-499
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• 2001

In this paper, the scheme of an efficient fuzzy rule generation and fuzzy system construction using GA(genetic algorithm) and FCM(fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. In the structure identification, input data is transformed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, a set fuzzy rules are generated for a given criterion by FCM clustering algorithm . In the parameter identification premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this one can systematically obtain the valid number of fuzzy rules which shows satisfying performance for the given problem. Finally, we applied the proposed method to the Box-Jenkins data and rice taste data modeling problems and obtained a better performance than previous works.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Korean Journal of Oriental Medicine
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• v.13 no.2 s.20
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• pp.59-63
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• 2007

The purpose of this study was to diagnosis that what patterns identification using the statistical method. Discriminant analysis using the medical specialist and resident pattern identification agree case in stroke patients within 1 month of onset. The agreement rate of dificiency of Gi(75%), heat-transformation(74%), dampphlegm syndrome(69%), deficiency of Eum(51%) and syndrome of blood stagnation(43%) are respectively 0.75, 0.74, 0.69, 0.51 and 0.43 in medical specialist and using linear discriminant function pattern identification are same. The study of inspection, pulse feeling and palpitation will be continued to evaluate concordance rate. Discrimination model will be make to get higher Accuracy and prediction, it means becomes the help in pattern identification diagnosis objectivity and scientific.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.87-93
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• 2014

TIn analysis as the first step of S/W development, security requirements of identification and authentication, ID and password management, authentication process, authentication method, ete. should be defined. Identification is to uniquely identify certain users and applications running on a certain system. Authentication means the function to determine true or false users and applications in some cases. This paper is to suggest the security requirements for identification and authentication in analysis step. Firstly, individual ID should be uniquely identified. The second element is to apply the length limitations, combination and periodic changes of passwords. The third should require the more reinforced authentication methods besides ID and passwords and satisfy the defined security elements on authentication process. In this paper, the security requirements for the step of identification and authentication have been explained through several practical implementation methods.

• Korean journal of food and cookery science
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• v.27 no.1
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• pp.33-42
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• 2011

The purposes of this study were to understand the influence of brand personality-self image congruence in quick service restaurants on customer satisfaction and to empirically analyze whether or not customers' brand identification plays a moderating role between brand personality-self image congruence and customer satisfaction. Based on a total of 478 samples obtained from empirical research from June 10 to June 16, 2010, self-administered questionnaires were completed by patrons in a metropolitan area, and data were analyzed based on frequency, exploratory factor analysis, reliability analysis, correlation analysis, and hierarchical regression analysis. Results of the study were as follows: From the factor analysis of brand personality and self-image, 5 factors, i.e. sophistication (5 items), competence (5 items), likability (5 items), trendiness (5 items), and ruggedness (5 items) were extracted. The results show that trendiness (${\beta}$=-0.151) among brand personality-self image congruence had a significant positive effect on customer satisfaction. Further, customers' brand identification (${\beta}$=0.645) had a significant positive effect on customer satisfaction. In addition, the effect of brand personality-self image congruence (only, likability ${\times}$ brand identification; ${\beta}$=0.245) in quick service restaurants on customer satisfaction was found to be partially moderated by customers' brand identification. In other words, the findings show that customers wanted to identify with a specific brand because it provides a means to continue transactions with the brand if it corresponds with their self-image or if the overall image of the brand is favorable. Limitations and future research directions are also discussed.

• Smart Structures and Systems
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• v.17 no.6
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• pp.917-933
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• 2016

In a prestressed concrete bridge, the magnitude of the prestress force (PF) decreases with time. This unexpected loss can cause failure of a bridge which makes prestress force identification (PFI) critical to evaluate bridge safety. However, it has been difficult to identify the PF non-destructively. Although some research has shown the feasibility of vibration based methods in PFI, the requirement of having a determinate exciting force in these methods hinders applications onto in-service bridges. Ideally, it will be efficient if the normal traffic could be treated as an excitation, but the load caused by vehicles is difficult to measure. Hence it prompts the need to investigate whether PF and moving load could be identified together. This paper presents a synergic identification method to determine PF and moving load applied on a simply supported prestressed concrete beam via the dynamic responses caused by this unknown moving load. This method consists of three parts: (i) the PF is transformed into an external pseudo-load localized in each beam element via virtual distortion method (VDM); (ii) then these pseudo-loads are identified simultaneously with the moving load via Duhamel Integral; (iii) the time consuming problem during the inversion of Duhamel Integral is overcome by the load-shape function (LSF). The method is examined against different cases of PFs, vehicle speeds and noise levels by means of simulations. Results show that this method attains a good degree of accuracy and efficiency, as well as robustness to noise.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.75-79
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• 2007

We propose an effective voice-based gender identification method using a support vector machine(SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model(GMM) using the mel frequency cepstral coefficients(MFCC). A novel means of incorporating a features fusion scheme based on a combination of the MFCC and pitch is proposed with the aim of improving the performance of gender identification using the SVM. Experiment results indicate that the gender identification performance using the SVM is significantly better than that of the GMM. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

• Journal of Korean Society of Rural Planning
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• v.25 no.1
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• pp.67-74
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• 2019

This study is to identify the heat vulnerability area as represented by heat risk factors which could be attributable to heat-related deaths. The heat risk factors were temperature, Older Adults(OA), Economic Disadvantage(ED), Accessibility of Medical Services(AMS), The population Single Person Households(SPH). The factors are follow as; the temperature means to the number of days for decades average daily maximum temperature above $31^{\circ}C$, the Older Adults means to population ages 65 and above, furthermore, the Economic Disadvantage means to the population of Basic Livelihood Security Recipients(BLSR), the Accessibility of Medical Services(AMS) means to 5 minutes away from emergency medical services. The results of the analysis are showed that the top-level of temperature vulnerability areas is Dong, the top-level of vulnerability OA areas is Eup, the top-level of AMS vulnerability is Eup. Moreover, the top-level of vulnerability ED area appears in the Eup and Dong. The result of analysing relative importance to each element, most of the Eup were vulnerable to heat. Since, there are many vulnerable groups such as Economic Disadvantage, Older Adults in the Eup. We can be figured out estimated the number of heat-related deaths was high in the Eup and Dong by the data of emergency activation in the Chungcheongnam-do Fire Department. Therefore, the result of this study could be reasonable.