• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1603-1618
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• 2024

Emergency operation plans are indispensable elements for effective process safety management especially when unanticipated events occur under extreme situations. In the paper, a synthesis framework is proposed for the integration success path planning and performance analysis. Within the synthesis framework, success path planning is implemented through flow-directed signal tracing, renaming and reconstruction from a complete collection of Minimal Path Sets (MPSs) that are obtained using graph traversal search on GO-FLOW model diagram. The performance of success paths is then evaluated and prioritized according to the task complexity and probability calculation of MPSs for optimum action plans identification. Finally, an Auxiliary Feed Water System of Pressurized Water Reactor (PWR-AFWS) is taken as an example system to demonstrate the flow-directed MPSs search method for success path planning and performance analysis. It is concluded that the synthesis framework is capable of providing procedural guidance for emergency response and safety management with optimal success path planning under extreme situations.

• KIEE International Transactions on Power Engineering
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• v.4A no.2
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• pp.73-78
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• 2004

This paper proposes a framework for determining the minimum load shedding for restoring solvability. The framework includes a continuation power flow (CPF) and an optimal power flow (OPF). The CPF parameterizes a specified outage from a set of multiple contingencies causing unsolvable cases, and it traces the path of solutions with respect to the parameter variation. At the nose point of the path, sensitivity analysis is performed in order to achieve the most effective control location for load shedding. Using the control location information, the OPF for locating the minimum load shedding is executed in order to restore power flow solvability. It is highlighted that the framework systematically determines control locations and the proper amount of load shedding. In a numerical simulation, an illustrative example of the proposed framework is shown by applying it to the New England 39 bus system.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.51-59
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• 2011

In domestic, the binary code analysis technology is insufficient. In general, an executable file that is installed on your computer without the source code into an executable binary files is given only the most dangerous, or because it is unknown if the action is to occur. In this paper, static program analysis at the binary level to perform the design and implementation framework. In this paper, we create a control flow graph. We use the graph of the function call and determine whether dangerous. Through Framework, analysis of binary files is easy.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.70-81
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• 2017

Various components of an engine nozzle are modeled as flexible multi-body components that are operated under high temperature and pressure. In this paper, in order to predict complex behavior of an engine nozzle, thermo-fluid-flexible multi-body dynamics coupled analysis framework was developed. Temperature and pressure on the nozzle wall were obtained by the steady-state flow analysis for a two-dimensional nozzle. The pressure and temperature-dependent material properties were delivered to the flexible multi-body dynamics analysis. Then the deflection and strain distribution for a nozzle configuration was obtained. Heat conduction and thermal analyses were done using MSC.NASTRAN. The present framework was validated for a simple nozzle configuration by using a one-way coupled analysis. A two-way coupled analysis was also performed for the simple nozzle with an arbitrary joint clearance, and an asymmetric flow was observed. Finally, the total strain result for a realistic nozzle configuration was obtained using the one-way and two-way coupled analyses.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Convergence Security Journal
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• v.22 no.4
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• pp.129-133
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• 2022

Deep learning frameworks are still evolving, and there are various frameworks. Typical deep learning frameworks include TensorFlow, PyTorch, and Keras. The Deepram framework utilizes optimization models in image classification through image learning. In this paper, we use the TensorFlow and PyTorch frameworks, which are most widely used in the deep learning image recognition field, to proceed with image learning, and compare and analyze the results derived in this process to know the optimized framework. was made.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.160-169
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• 2006

This paper describes the data structure for program analysis and optimization of bytecode level. First we create an extended CFG(Control Flow Graph). Because of the special properties of bytecode, we must adaptively extend the existing control flow analysis techniques. We build basic blocks to create the CFG and create various data that can be used for optimization. The created CFG can be tested for comprehension and maintenance of Java bytecode, and can also be used for other analyses such as data flow analysis. This paper implements CTOC's CTOC-BR(CTOC-Bytecode tRanslator) for control flow analysis of bytecode level. CTOC(Classes To Optimized Classes) is a Java bytecode framework for optimization and analysis. This paper covers the first part of the CTOC framework. CTOC-BR is a tool that converts the bytecode into tree form for easy optimization and analysis of bytecode in CTOC.

• Knowledge Management Research
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• v.7 no.2
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• pp.53-68
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• 2006

Knowledge has become an important resource for organization. The manufacturing industry is usually operated on the basis of business processes, and most workers are familiar with their own processes. The process-based approach, therefore, can provide an efficient way to capture and navigate knowledge. In this study, we focus on knowledge which may be missed during knowledge transfer among workers. For this, we propose a method for analyzing knowledge flow, which is passed among business processes. We propose a process-based knowledge management framework for analyzing knowledge flow, which employs a two-phase analysis: process analysis and knowledge flow analysis. A knowledge flow model, represented by Knowledge Flow Diagram, is proposed as a tool for representing knowledge. We formulate several semantics for knowledge flow modeling. We build the three-level schema: conceptual, logical, and physical in order to automate the knowledge model adaptive to knowledge management systems. The proposed approach is verified and illustrated through a case study on the manufacturing process of A Company.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.107-112
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• 2020

We analyze the flow aggregate (FA) based network delay guarantee framework, with generalized minimal interleaved regulator (IR) initially suggested by IEEE 802.1 time sensitive network (TSN) task group (TG). The framework has multiple networks with minimal IRs attached at their output ports for suppressing the burst cascades, with FAs within a network for alleviating the scheduling complexity. We analyze the framework with various topology and parameter sets with the conclusion that the FA-based framework with low complexity can yield better performance than the integrated services (IntServ) system with high complexity, especially with large network size and large FA size.