• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.3
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• pp.58-66
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• 2003

The cut tree approach of Montreuil and Ratliff [16] and eigenvector approach [10] are used to automatically draw a feasible facility layout with aisle structure. The department arrangement can minimize an aisle distance criterion considering door locations and dimension constraints. The aisle distance is measured by the door to door distance between departments. An eigenvector and cut tree approaches [1] are implemented based on the branch and bound technique in Kim et al. [2] in order to obtain feasible layouts. Then, the algorithm to fix the door location of each department is developed. After the door locations are determined, the factory layout is evaluated in terms of aisle distance. The aisle structure is obtained by expanding the original layout. The solution is kept until we will find better factory layout. The proposed approach based on the branch and bound technique, in theory, will provide the optimal solution. If the runs are time and/or node limited, the proposed method is a strong heuristic. The technique is made further practical by the fact that the solution is constrained such that the rectangular shape dimensions length(l) and width(w) are fixed and a perfect fit is generated if a fit is possible.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Journal of Engineering Education Research
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• v.17 no.3
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• pp.34-41
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• 2014

In distance education, use of proper software tools can greatly enhance student's attention and learning efficiency. In such software tools, offering diverse multimedia information is one of the most critical factors. However, integration and synchronization of the various media types has been relatively difficult parts of implementation. This paper proposes a prototype system that uses a metafile and event handling mechanism for the uniform treatment of various media types. This event-level integration and synchronization of multimedia makes the implementation relatively simple. With this approach, instructor's behaviors are automatically recorded, and the instructors can freely choose and show any type of multimedia contents while lecturing. Current commercial or non-commercial lecture management systems could incorporate this approach, so that the distance education market could be expanded with richer multimedia contents.

• International Journal of CAD/CAM
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• v.8 no.1
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• pp.45-53
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• 2009

As the point sampling technology evolves rapidly, there has been increasing need in generating tool path from dense point set without creating intermediate models such as triangular meshes or surfaces. In this paper, we present a new tool path generation method from point set using Euclidean distance fields based on Algebraic Point Set Surfaces (APSS). Once an Euclidean distance field from the target shape is obtained, it is fairly easy to generate tool paths. In order to compute the distance from a point in the 3D space to the point set, we locally fit an algebraic sphere using moving least square method (MLS) for accurate and simple calculation. This process is repeated until it converges. The main advantages of our approach are : (1) tool paths are computed directly from point set without making triangular mesh or surfaces and their offsets, and (2) we do not have to worry about no local interference at concave region compared to the other methods using triangular mesh or surface model. Experimental results show that our approach can generate accurate enough tool paths from a point set in a robust manner and efficiently.

• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.379-390
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• 2024

This study proposes a fuzzy inventory model for managing large-scale production, incorporating cost considerations. The model accounts for two types of expenditure scenarios-parametric and exponential. Uncertainty surrounds holding costs, setup costs, and demand rates. The approach considers a supply chain system with a complex manufacturing process, factoring in transportation costs based on the quantity of goods and distance between the supplier and retailer. The initial crisp model is then transformed into a fuzzy simulation, incorporating specific fuzzy variables affecting inventory costs. The proposed method significantly reduces overall inventory costs for the entire supply chain. Retailer demand is linked to inventory levels, and vendor/distributor storage deteriorates over time. The fuzzy condition assumes hexagonal variables for all associated factors. The study employs the signed distance method for defuzzification to determine the optimal order quantity with hexagonal fuzzy numbers. Mathematical examples are provided to illustrate the practicality of the proposed approach.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.643-646
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• 1999

In this paper, we propose a feature extraction method based on Bhattacharyya distance for multiclass problems. The Bhattacharyya distance provides a valuable information in determining the effectiveness of a feature set and has been used as separability measure for feature selection. Recently, a feature extraction algorithm hat been proposed for two normally distributed classes based on Bhattacharyya distance. In this paper, we propose to expand the previous approach to multiclass cases. Experiment results show that the proposed method compares favorably with the conventional methods.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.379-383
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• 2015

This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

• Journal of radiological science and technology
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• v.37 no.4
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• pp.323-330
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• 2014

Image reconstruction is one of the most important processes in CT (Computed tomography) technology. For fast scanning and low dose to the objects, iterative reconstruction is becoming more and more important. In the implementation of iterative reconstruction, projection and backprojection processes are considered to be indispensable parts. However, many approaches for projection and backprojection may result severe image artifacts due to their discrete characteristics and affects the reconstructed image quality. Thus, new approaches for projection and backprojection are highly demanded these days. In this paper, distance-driven approach was evaluated and compared with other conventional methods. The numerical simulator was developed to make the phantoms, and projection and backprojection images were compared using these approaches. As a result, it turned out that there are less artifacts during projection and backprojection in parallel and fan beam geometry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.932-951
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• 2021

The effectiveness of testing in Model-based Testing (MBT) for Software Product Line (SPL) can be achieved by considering fault detection in test case. The lack of fault consideration caused test case in test suite to be listed randomly. Test Case Prioritization (TCP) is one of regression techniques that is adaptively capable to detect faults as early as possible by reordering test cases based on fault detection rate. However, there is a lack of studies that measured faults in MBT for SPL. This paper proposes a Test Case Prioritization (TCP) approach based on dissimilarity and string based distance called Last Minimal for Local Maximal Distance (LM-LMD) with Dice-Jaro-Winkler Dissimilarity. LM-LMD with Dice-Jaro-Winkler Dissimilarity adopts Local Maximum Distance as the prioritization algorithm and Dice-Jaro-Winkler similarity measure to evaluate distance among test cases. This work is based on the test case generated from statechart in Software Product Line (SPL) domain context. Our results are promising as LM-LMD with Dice-Jaro-Winkler Dissimilarity outperformed the original Local Maximum Distance, Global Maximum Distance and Enhanced All-yes Configuration algorithm in terms of Average Fault Detection Rate (APFD) and average prioritization time.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.154.2-154
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• 2001

This paper presented a adaptation approach based on maximum model distance (MMD) method. This method shares the same framework as they are used for training speech recognizers with abundant training data. The MMD method could adapt to all the models with or without adaptation data. If large amount of adaptation data is available, these methods could gradually approximate the speaker-dependent ones. The approach is evaluated through the phoneme recognition task on the TIMIT corpus. On the speaker adaptation experiments, up to 65.55% phoneme error reduction is achieved. The MMD could reduce phoneme error by 16.91% even when ...