• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.167-176
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• 2011

This study's purpose is to analyse factors of determination about detouring for makinga standard model in regard of unfavorableness and uncertainty when unspecified individual recipients make a decision at the time of course detour. In order to achieve this, we surveyed SP investigation whether making a detour or not for drivers as a target who take a high way and National highway. Based on this result, we analysed detour determination factors of drivers, establishing a combination model of Decision Tree and Neural Network model. The result demonstrates the effected factors on drivers' detour determination are in ordering of the recognition of alternative routevs, reliable and frequency of using traffic information, frequency of transition routes and age. Moreover, from the outcome in comparison with an existing model and prediction through undistributed data, the rate of combination model 8.7% illustrates the most predictable way in contrast with logit model 12.8%, and Individual Model of Decision Tree 13.8% which are existed. This reveals that the analysis of drivers' detour determination factors is valid to apply. Hence, overall study considers as a practical foundation to make effective detour strategies for increasing the utility of route networking and dispersion in the volume of traffic from now on.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.151-152
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• 2012

This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.178-188
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• 2010

This paper addresses the problem of determining if two surfaces intersect tangentially or transversally in a mathematically consistent manner and approximating an intersection curve. When floating point arithmetic is used in the computation, due to the limited precision, it often happens that the decision for tangential and transversal intersection is not clear cut. To handle this problem, in this paper, interval arithmetic is proposed to use, which provides a mathematically consistent way for such decision. After the decision, the intersection is traced using the validated ODE solver, which runs in interval arithmetic. Then an iterative method is used for computing the accurate intersection point at a given arc-length of the intersection curve. The computed intersection points are then approximated by using a B-spline curve, which is provided as one instance of intersection curve for further geometric processing. Examples are provided to demonstrate the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.122-127
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• 1998

This paper suggests an integrated method for discovering knowledge from a large database. Our approach applies an attribute-oriented concept hierarchy ascension technique to extract generalized data from actural data in databases, induction of decision trees to measure the value of information, and knowledge reduction of rough set theory to remove dispensable attributes and attribute values. The integrated algorithm first reduce the size of database for the concept generalization, reduces the number of attributes by way of elimination condition attributes which have little influence on decision attribute, and finally induces simplified decision rules removing the dispensable attribute values by analyzing the dependency relationships among the attributes.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.310-320
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• 1999

A mixed model assembly line (MMAL) is a special type of production line where a variety of product models similar in product characteristics are assembled. Determining the model sequence is an important problem for the efficient use of MMALs. This paper considers interactive multiobjective decision making problems for MMAL sequencing. Evolution program is employed as an underlying framework. In this study, a way of approximating the linear utility function is first studied. To improve its search efficiency to the solution space preferred by a decision maker, some modifications of a standard evolution program are made: operating several subpopulations instead of a single population and merging two or more subpopulations to a single subpopulation, and using a Pareto pool. Extensive computational experiments are carried out to verify the performance of the proposed approach. The computational results show that our approach is promising in solution quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1199-1203
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• 2012

This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.103-111
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• 2012

PURPOSES : Effective speed management is necessary for preventing traffic crashes on the road. Speed hump is known as an effective tool for managing speed. Unlike existing studies which are mainly focused on humps for vehicles, this study proposed a novel method to determine design parameters for bicycle speed humps based on a multi-criteria decision making process. METHODS : Three objectives including the effectiveness of speed reduction, bicycle safety, and user's comfortability were incorporated into the proposed evaluation framework for determining design parameters. A multi-criteria value function was also derived and utilized as a part of the proposed method. RESULTS : Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS : It is expected that the outcomes of this study can be a valuable precursor for developing design guidelines for bicycle road and facility.

• IE interfaces
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• v.25 no.3
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• pp.338-346
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• 2012

Regarding the green environment, it is important to boost the spread of environmentally friendly vending machines and to operate the vehicles for their inventory replenishments while minimizing emissions of greenhouse gases. In general, the vending machine management company lacks capability to operate the supply chain effectively in an integrated way under the dynamic, complex, and stochastic environment. This paper presents a decision support system, termed DSSVM, for the operations of the general and smart vending machine supply chains with stock-out-based, one stage item substitution in a green logistics environment. The DSSVM supports the estimation of item demand and substitution probabilities, determination of operation parameters, supply chain analysis, what-if analysis, and $CO_2$ analysis for which various analytical models are employed.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.31-40
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support the managers in their decision making. That is the reason many companies are tend to have Business Intelligence Systems. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studied more to help managers make right decisions for the DSS implementation.