• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.155-162
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• 2023

This study analyzed the impact of negative information on co-branding, targeting co-branding consisting of a symbolic brand and a functional brand with similar brand assets. Through attribution theory, when consumers are exposed to negative information, they will infer the cause of the negative information. As a result, it was confirmed that when co-branding with a symmetrical symbolic brand and a functional brand, negative information has different effects on co-branding depending on the type. Negative information about the quality of co-branded products had a more negative impact on consumer attitudes than negative information about the iconic brand. It was confirmed that negative information about functional brands has a smaller impact than negative information about co-branding, but has a greater impact than negative information about symbolic brands. In addition, it was confirmed that negative information about the symbolic brand had a smaller negative impact on co-branding than negative information about the quality or functionality of the co-branded product.

• Spatial Information Research
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• v.19 no.3
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• pp.53-62
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• 2011

Spatial information services in indoor space are an im portant application area of GIS as in outdoor space. Unlike in outdoor space, a position in indoor space is specified by a symbolic code such as room number, rather than coordinate. Therefore tracking in indoor space is no longer a prediction of coordinates but a symbolic estimation on the current position of a moving object. In this paper, we propose a framework for tracking moving objects in indoor symbolic space with RFID sensors. First, we introduce the concepts of indoor symbolic space and tracking in indoor symbolic space, and define the accessibility graph for trackable indoor symbolic space. Second, we propose a deployment method of RFID readers and a construction algorithm of accessibility graph for trackable indoor symbolic space. Third, a tracking method is proposed for moving objects in symbolic indoor space with RFID sensors. Finally, we present an implementation exmaple and the result of experiment with real data to validate the proposed method.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.225-234
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• 2014

We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of large and complex data has attracted significant interest. Symbolic Data Analysis (SDA) was proposed by Diday in 1980's, which provides a new framework for statistical analysis. In SDA, we analyze an object with internal variation, including an interval, a histogram and a distribution, called a symbolic object. In the study, we focus on a cluster analysis for distribution valued dissimilarities, one of the symbolic objects. A hierarchical clustering has two steps in general: find out step and update step. In the find out step, we find the nearest pair of clusters. We extend it for distribution valued dissimilarities, introducing a measure on their order relations. In the update step, dissimilarities between clusters are redefined by mixture of distributions with a mixing ratio. We show an actual example of the proposed method and a simulation study.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.1
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• pp.48-59
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• 1992

This paper presents the design of a layout processing system that performs circuit and symbolic extraction from hierarchical designs containing arbitrarily shaped layout. The system is flexible enough to deal with various technologies, MOS or bipolar, by providing extraction rules in the form of technology files. In this paper, new efficient algorithms for trapezoidal decomposition of polygon and symbolic path extraction using trapezoidal template are proposed for symbolic extraction. Circuit and symbolic extractor is developed as an integrated design environment of SOLID system.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.134-141
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• 1998

Sometimes we need to acquire symbolic quantity of information instead of physical quantity for the output of any system. For instance we can not control traffic signal accurately through only the number of vehicles. At that case we can produce better output using symbolic quantity of road length and width and vehicle type. But it is very difficult to aggregate symbolic information from the unrelated and mutually conflicted input after calculating linear and related expression. Moreover that will take much time to produce symbolic output by the physical quantity only. In this paper we implemented the ultimate traffic control information by using fuzzy sensor algorithm and compared our results with the conventional traffic controller after studying the necessity of symbolic information in the traffic control.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.975-986
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• 2022

Deep learning is attracting great attention, showing excellent performance in image processing, but is vulnerable to adversarial attacks that cause the model to misclassify through perturbation on input data. Adversarial examples generated by adversarial attacks are minimally perturbated where it is difficult to identify, so visual features of the images are not generally changed. Unlikely deep learning models, people are not fooled by adversarial examples, because they classify the images based on such visual features of images. This paper proposes adversarial attack detection method using Symbolic Representation, which is a visual and symbolic features such as color, shape of the image. We detect a adversarial examples by comparing the converted Symbolic Representation from the classification results for the input image and Symbolic Representation extracted from the input images. As a result of measuring performance on adversarial examples by various attack method, detection rates differed depending on attack targets and methods, but was up to 99.02% for specific target attack.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1080-1086
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• 1987

SLAGEN, a system for symbolic cell layout based on artificial intelligence approach, takes as input a transistor connection description of CMOS standard cells and environment information, and outputs a symbolic layout description. SLAGEN performas transistor grouping by a heuristic search method, in order to minimize the number of separations, and then performs group reordering and transistor reordering with an eye toward minimizing routing. Next, SLAGEN creates a rough initial routing in order to guarantee functionality and correctness, and then improve the initial routing by a rule-based approach.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.54-59
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• 2010

Special-purpose microcontrollers PLCs have been widely used in the area of industrial automation. For the research of analysis and verification for PLC programs, first of all we have to specify formal sematics of PLC programming languages. This paper defines formally the operational semantics of LD language. After we transform the graphical language LD into its textual representation Symbolic LD, we give semantics of Symbolic LD since LD language is a graphical language. This paper defines the natural sematics of Symbolic LD and formalizes it in Coq proof assistant.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.811-820
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• 2017

Software automatic technology research recently focuses not only on generating a single path test-case, but also on finding an optimized path to reach the vulnerability through various test-cases. Although Dynamic Symbolic Execution (DSE) technology is popular among these automatic technologies, most DSE technology researches apply only to Linux binaries or specific modules themselves. However, most software are vulnerable based on input files. Therefore, this paper proposes an input file based dynamic symbolic execution method for software vulnerability verification. As a result of applying it to three kinds of actual binary software, it was possible to create a test-case effectively reaching the corresponding point through the proposed method. This demonstrates that DSE technology can be used to automate the analysis of actual software.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.11
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• pp.1410-1420
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• 2005

The purpose of this study was to analyze characteristics of effective expression on T-shirts pattern by peirce's semiotic theory. The methods of this study was to analyze 721 T-shirts patterns in designer's collection from 2000 to 2004. The results of this study were as follows: First of all, iconic expression showed high frequency after 2000. Characteristics of effective expression were as follows: In geometric expression, repetition was presented as a symbolic sign by regular proportion and rule of dot, line, plane, irregularity, mixture of irregular dot, line, plane. Mixed expression was presented as a iconic and symbolic sign by collage, mixture of dot, line, plane, icon and letter. In iconic expression, simplification of iconic sigrl was presented as a iconic sign by simplification of form, color, texture, realistic expression using digital as a iconic sign, and symbolic face, body as a symbolic sign. Pop art's expression was presented as a iconic sign by a cartoon and commercial character and illusion was presented as a iconic sign. In letter's expression, brand logo was presented as a symbolic sign by transformation of letter's design, a symbolic sign of numeral by transformation of size, thickness, form, color. Symbolic message phrase was presented by slogan, fashion trend, brand image, descriptive indication message as a index sign by using icon or singleness. In conclusion, characteristics of effective expression on T-shirts pattern will present not only the theoretical foundation to raise the value added, but also the information about beauty sense of times, political and social value.