• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.2
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• pp.129-140
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• 2006

The existing CBD development methods deal with the analysis phase in a superficial manner. Applying such a superficial analysis to business applications with a number of subsystems makes analysis models be inconsistent with levels and styles, only depending on experiences of the analysts. This inconsistent analysis might cause more serious problems during the subsequent development phases, resulting in the failure of the projects. In this paper, we propose a rule-based analysis pattern that provides an analysis template for business applications. This pattern analyzes the concepts of business applications by using external events and internal rules that process the events. Employing this pattern, a huge business application can be developed by a couple of co-analysts who work together in a consistent and systematic manner. This paper also describes an efficient way to develop business components with the suggested analysis pattern using banking deposit case study through UML Components development process.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.23-51
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• 2003

With the recent expansion of internet shopping mall, the importance of intelligent products recommendation agents has been increasing. for the products recommendation, This paper propose case-based reasoning approach, and developed a case-based bundle products recommendation system which can recommend a set of sea food used in family events. To apply CBR approach to the bundle products recommendation, it requires the following 4R steps : \circled1 Retrieval, \circled2 Reuse, \circled3 Revise, \circled4 Retain. To retrieve similar cases from the case-base efficiently, case representation scheme is most important. This paper used OW(Object Modeling Technique) to represent bundle products recommendation cases, and developed a similarity measure method to search similar cases. To measure similarity, we used weight-sum approach basically. Especially This paper propose the meaning and uses of taxonomies for representing case features.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.17-30
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• 2015

Unlike existing widely used bytecode-centric Android application code obfuscation methodology, our scheme in this paper makes encrypted file i.e. DEX file self-extracted arbitrary Android application. And then suggests a method regarding making the loader app to execute encrypted file's code after saving the file in arbitrary folder. Encrypted DEX file in the loader app includes original code and some of Manifest information to conceal event treatment information. Loader app's Manifest has original app's Manifest information except included information at encrypted DEX. Using our scheme, an attacker can make malicious code including obfuscated code to avoid anti-virus software at first. Secondly, Software developer can make an application with hidden main algorithm to protect copyright using suggestion technology. We implement prototype in Android 4.4.2(Kitkat) and check obfuscation capacity of malicious code at VirusTotal to show effectiveness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.1-8
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• 2019

Recently, consumer distrust has deepened due to blog posts focusing only on public relations due to 'viral marketing'. In addition, marketing projects such as false writing or exaggerated use of the latter phase are one of the most popular programs in 2016 as they are cheaper and more effective than newspaper and TV ads, and the size of advertising costs is set to be a major means of advertising at '3 trillion 394.1 billion won. From this 'viral marketing,' it has become an Internet environment that needs tools to filter information. The fake review filtering application ADDAVICHI presented in this paper extracts, analyzes, and presents blog keywords, total number of searches, reliability and satisfaction when users search for content such as "event" and "taste restaurant." Reliability shows the number of ad posts on a blog, the total number of posts, and satisfaction shows a clean post with confidence divided into positive and negative posts. Finally, the keyword shows a list of the top three words in the review from a positive post. In this way, it helps users interpret information away from advertising.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.343-352
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• 2012

In this paper, we implemented a touchless interface for DID(Digital Information Display) system using gesture recognition technique which includes both hand motion and hand shape recognition. Especially this touchless interface without extra attachments gives user both easier usage and spatial convenience. For hand motion recognition, two hand-motion's parameters such as a slope and a velocity were measured as a direction-based recognition way. And extraction of hand area image utilizing YCbCr color model and several image processing methods were adopted to recognize a hand shape recognition. These recognition methods are combined to generate various commands, such as, next-page, previous-page, screen-up, screen-down and mouse -click in oder to control DID system. Finally, experimental results showed the performance of 93% command recognition rate which is enough to confirm the possible application to commercial products.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.103-111
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• 2012

This paper is a basic study for making a system that can predict the success and failure of entertainment contents at the initial stage of production. It proposes the user's emotion modeling of dynamic narrative on entertainment contents. To make this possible, 1) dynamic narrative emotion model is proposed based on theoretical research of narrative structure and cognitive emotion model. 2) configuring the emotion types and emotion value, proposed model of three emotion parameter(desire, expectation, emotion type) are derived. 3)To measure user's emotion in each story event of dynamic narrative, cognitive behavior and description of user(film, game) is established. The earlier studies on the user research of conceptual, analytic approach is aimed of predicting on review of the media and user's attitude, and consequently these results is delineated purely descriptive. In contrast, this paper is proposed the method of user's emotion modeling on dynamic narrative. It would be able to contributed to the emotional evaluation of entertainment contents using specific information.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.947-958
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• 2006

In order to increase extensibility and reusability of business components, the variable things need to be analyzed from the analysis phase and identified as components. In this paper, we propose a rule-based analysis pattern, which can effectively extract object-based main concepts from a variable business process in the analysis phase and identify a variable business component by applying the pattern to the UML Components development process. It can make analysis artifacts consistent and readable for analysts with different level of knowledge and experience to apply the pattern to analysis of rule-based variable business processes. And also, variable business components can be easily identified by applying the pattern to the UML Components development process. In order to prove the feasibility of the pattern, we have applied the pattern the deposit and import/export subsystem of the banking domain. According to our experience, we can make the same business conceptual models between the deposit and import/export subsystem due to the main concepts suggested by the pattern and effectively identify a variable business components in the UML Components development process.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.406-413
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• 2020

In this paper, to improve the classification accuracy of bird and amphibian acoustic sound, we utilize GLU (Gated Linear Unit) and Self-attention that encourages the network to extract important features from data and discriminate relevant important frames from all the input sequences for further performance improvement. To utilize acoustic data, we convert 1-D acoustic data to a log-Mel spectrogram. Subsequently, undesirable component such as background noise in the log-Mel spectrogram is reduced by GLU. Then, we employ the proposed temporal self-attention to improve classification accuracy. The data consist of 6-species of birds, 8-species of amphibians including endangered species in the natural environment. As a result, our proposed method is shown to achieve an accuracy of 91 % with bird data and 93 % with amphibian data. Overall, an improvement of about 6 % ~ 7 % accuracy in performance is achieved compared to the existing algorithms.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.634-648
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• 2001

Message Sequence Charts(MSC) has been used to describe the interactions of numerous concurrent tasks in telecommunication software. After the MSC specification is verified in requirement analysis phase, it can be used not only to synthesize state-based design models, but also to generate test sequences. Until now, the verification is accomplished by generating global state transition graph using the location information only. In this paper, we extend the condition statement of MSC to describe the activation condition of scenarios and the change of state variables, and propose an approach to construct global finite state machine (GFSM) using this information. The GFSM only includes feasible states and transitions of the system. We can generate the test sequences using the existing FSM-based test sequence generation technology.