• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.195-201
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• 2017

Urbanization and industrialization have led to a severe deterioration in urban air qualities. As an air pollution is closely associated with human health, citizen has a growing concern about the air quality policy to improve their residential environment. Due to the recently advance in web- and mobile computing technologies, citizens can easily access various air quality information and public authorities utilize the social media service to communicate citizens with air quality issues. Also citizens' participation and role has been increased to improve urban air qualities. Thus, to meet the technical and societal changes, a GIS-based air quality information system is developed based upon the Ubiquitous Public Access (UPA) model in ISO19154. The proposed system employs the context information model to provide air quality information depending on citizens' health conditions and locations. Also, citizens can present their perceptions of an air quality at their current location Public authorities can thus utilize the citizens' perceptions when establishing new air quality policies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.149-160
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• 2008

As individual users have to provide more information than the minimum for using information communication service, the invasion of privacy of Individual users is increasing. That is why client/server based personal information security platform technologies are being developed such as P3P, EPAL and XACML. By the way enterprises and organizations using primarily role based access control can not use these technologies. because those technologies apply access control policies to individual subjects. In this paper, we suggest an expression language for privacy enhancing role-based access control policy. Suggested privacy enhancing role-based access control policy language model is a variation of XACML which uses matching method and condition, and separately contains elements of role, purpose, and obligation. We suggest policy language model for permission assignment in this paper, shows not only privacy policy scenario with policy document instance, but also request context and response context for helping understanding.

• The Korean Journal of Franchise Management
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• v.15 no.3
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• pp.71-85
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• 2024

Purpose: This study aims to investigate the impact of product and service quality on customer surprise and delight, revisit intention, and SNS word-of-mouth (WOM) intention in the context of franchise restaurants in Korea, focusing on Chinese tourists' experiences. This analysis provides strategic insights into improving customer experiences and driving positive behavioral outcomes within the franchise foodservice sector. Research Design and Methodology: Data were collected from 395 Chinese tourists who visited Korean franchise restaurants using a self-administered questionnaire approach and analyzed with SmartPLS 4.0. Reliability, convergent and discriminant validity were assessed using measurement model. Hypotheses were tested using structural equation model. Results: This study verified that customer's service experience affects customer surprise and delight, which in turn is an important factor in increasing revisit intention and SNS WOM and supports the SOR framework that explains these relationships. In other words, this study presented a model that expands the traditional service quality → customer satisfaction → behavioral intention framework by including surprise and delight. The study also revealed that both product quality and service quality positively influence customer delight. Furthermore, customer surprise and delight significantly influence revisit intention and SNS WOM. The findings suggest that enhancing product and service quality can lead to higher levels of customer surprise and delight and greater likelihood of revisits and positive online feedback.

• Journal of Elementary Mathematics Education in Korea
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• v.19 no.3
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• pp.305-321
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• 2015

This study started with wondering whether the nonproportional model used in unit assessment for 2nd graders is appropriate or not for them. This study aims to explore the applicability of the nonproportional model to 2nd graders when they learn about numbers. To achieve this goal, we analyzed elementary mathematics textbooks, applied two kinds of tests to 2nd graders who have learned three-digit numbers by using the proportional model, and investigated their cognitive characteristics by interview. The results show that using the nonproportional model in the initial stages of 2nd grade can cause some didactical problems. Firstly, the nonproportional models were presented only in unit assessment without any learning activity with them in the 2nd grade textbook. Secondly, the size of each nonproportional model wasn't written on itself when it was presented. Thirdly, it was the most difficult type of nonproportional models that was introduced in the initial stages related to the nonproportional models. Fourthly, 2nd graders tend to have a great difficulty understanding the relationship of nonproportional models and to recognize the nonproportional model on the basis of the concept of place value. Finally, the question about the relationship between nonproportional models sticks to the context of multiplication, without considering the context of addition which is familiar to the students.

• Asia pacific journal of information systems
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• v.23 no.1
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• pp.65-86
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• 2013

Understanding success factors in electronic banking is important to helping banks succeed. In this study, we extend DeLone and McLean's IS success model to the electronic banking by adding trust as a success variable. We tested the extended model by comparing internet banking and mobile banking in Indonesia. Using a structural equation modelling approach. We found that system quality had positive impacts on perceived usefulness and end-user satisfaction for both internet banking and mobile banking. The development of e-banking (internet banking and mobile banking) in Indonesia is in its initial stage. Finally, although we tested for the common method bias to relieve concern, further research may use multiple methods when collecting the data. This study investigated the role of each dimension of IS success in the electronic banking environment. While the original IS success model emphasizes individual and organizational impacts, we have argued that trust is an important indicator of IS impact on an individual socially in the banking industry. The contribution of our study is two-fold. Conceptually, the study is the first to extend the IS success model to the e-banking context. We provide an extension of the updated IS success model by adding trust as an outcome variable in the research model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.167-175
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• 2005

Privacy enforcement has been one of the most important problems in IT area. Privacy protection can be achieved by enforcing privacy policies within an organization's online and offline data processing systems. Traditional security models are more or less inappropriate for enforcing basic privacy requirements, such as purpose binding. This paper proposes a new approach in which a privacy control model is derived from integration of an existing security model. To this, we use an extended role-based access control model for existing security mechanism, in which this model provides context-based access control by combining RBAC and domain-type enforcement. For implementation of privacy control model we use GRBAC(Generalized Role-Based Access Control), which is expressive enough to deal with privacy preference. And small hospital model is considered for application of this model.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.48-54
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• 2023

Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.58-66
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• 1998

Purpose : This paper introduces a new three dimensional magnetic Resonance Image classification which is based on Mar kov Random Field-Gibbs Random Field with a line model. Material and Methods : The performance of the Gibbs Classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at the local neighborhood level. This usually involves the construction of a line model for the image. In this paper we construct a line model for multisignature images based on the differential of the image which can provide an a priori estimate of the unobservable line field, which may lie in regions with significantly different statistics. the line model estimated from the original image data can in turn be used to alter the values of the interaction parameters of the Gibbs Classifier. Results : MRF-Gibbs classifier for volumetric MR images is developed under the condition that the domain of the image classification is $E^{3}$ space rather thatn the conventional $E^{2}$ space. Compared to context free classification, MRF-Gibbs classifier performed better in homogeneous and along boundaries since contextual information is used during the classification. Conclusion : We construct a line model for multisignature, multidimensional image and derive the interaction parameter for determining the energy function of MRF-Gibbs classifier.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.65-71
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• 2005

Area type is often used in freight demand analysis and logistics planning models. For example, in freight transportation planning. area type variable is most often commonly used in freight generation (attraction) model. Yet a reliable, forecastable and measurable definition or area type is generally not documented. In fact, there is little literature on the subject of predicting area type in the context of freight planning models. This can be troublesome when applying models to long-range logistics planning where significant changes in population and employment result in changes in the general character of an area. Through the use of Discriminant Model, GIS (Geographic Information System) analysis and Delphi methods, this paper presents the successful exploration for a quantifiable means of determining area type.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.247-260
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• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).