• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.208-216
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• 2003

ISO 14649 (data model for STEP-NC) is a new interface scheme or language for CAD-CAM-CNC chain under established by ISO TC184 SCI. Up to this point, the new language is mainly made for milling and turning, and other processes such as EDM will be completed in the future. Upon completion, it will be used as the international standard language for e-manufacturing paradigm by replacing the old machine-level language, so called M&G code used since 1950's. With the rich information contents included in the new language, various intelligent functions can be made by the CNC as the CNC knows what-to-make and how-to-make. In particular, On-Machine Inspection required for quality assurance in the machine level, can be done based on the information of feature­based tolerance graph. Previously, On-Machine inspection has been investigated mainly for milling operation, and only a few researches were made for turning operation without addressing the data model. In this thesis, we present a feature-based on-machine inspection process by the 4 Tasks: 1) proposing a new schema for STEP-NC data model, 2) converting the conventional tolerance scheme into that of STEP-NC, 3) modifying the tolerance graph such that the tolerance can be effectively measured by the touch probe on the machine, and 4) generating collision-free tool path for actual measurement. Task 1 is required for the incorporation of the presented method in the ISO 14649, whose current version does not much include the detailed schema for tolerance. Based on the presented schema, the tolerance represented in the conventional drafting can be changed to that of STEP-NC (Task 2). A special emphasis was given to Task 3 to make the represented tolerance accurately measurable by the touch probe on the machine even if the part setup is changed. Finally, Task 4 is converting the result of Task into the motion of touch probe. The developed schema and algorithms were illustrated by several examples including that of ISO 14649 Part 12.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1909-1928
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• 2020

Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.23-32
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• 2008

This paper presents a task planning system for a steward robot, which has been developed as an interactive intermediate agent between an end-user and a complex smart home environment called the ISH (Intelligent Sweet Home) at KAIST (Korea Advanced Institute of Science and Technology). The ISH is a large-scale robotic environment with various assistive robots and home appliances for independent living of the elderly and the people with disabilities. In particular, as an approach for achieving human-friendly human-robot interaction, we aim at 'simplification of task commands' by the user. In this sense, a task planning system has been proposed to generate a sequence of actions effectively for coordinating subtasks of the target subsystems from the given high-level task command. Basically, the task planning is performed under the framework of STRIPS (Stanford Research Institute Problem Solver) representation and the split planning method. In addition, we applied a state-partitioning technique to the backward split planning method to reduce computational time. By analyzing the obtained graph, the planning system decomposes an original planning problem into several independent sub-problems, and then, the planning system generates a proper sequence of actions. To show the effectiveness of the proposed system, we deal with a scenario of a planning problem in the ISH.

• Journal of the Korean Society of Combustion
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• v.16 no.2
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• pp.16-22
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• 2011

It is a challenging task to apply large detailed chemical mechanisms of fuel oxidation in simulation of complex combustion phenomena. There exist a few systematic methodologies to reduce detailed chemical mechanisms to smaller sizes involving less computational load. This research work concerns generation of a skeletal chemical mechanism by a directed relation graph with specified accuracy requirement. Two sequential stages for mechanism reduction are followed in a perfectly stirred reactor(PSR) for high temperature chemistry and to consider the autoignition delay time for low and high temperature chemistry. Reduction was performed for the detailed chemical mechanism of n-heptane consisting of 561 species and 2539 elementary reaction steps. Validation results show acceptable agreement for the autoignition delay time and the PSR calculation in wide parametric ranges of pressure, temperature and equivalence ratio.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.145-150
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• 2009

The awareness of boundaries in wireless sensor networks has many benefits. The identification of boundaries is especially challenging since typical wireless sensor networks consist of low-capability nodes that are unaware of their geographic location. In this paper, we propose a simple, efficient algorithm to detect nodes that are near the boundary of the sensor field as well as near the boundaries of holes. Our algorithm relies purely on the connectivity information of the underlying communication graph and does not require any information on the location of nodes. We introduce the 2-neighbor graph concept, and then make use of it to identify nodes near boundaries. The results of our experiment show that our algorithm carries out the task of topological boundary detection correctly and efficiently.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.256-268
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• 2000

Multi-way spatial join is a nested expression of two or more spatial joins. It costs much to process multi-way spatial join, but there have not still reported the scheme of parallel processing of multi-way spatial join. In this paper, parallel processing of multi-way spatial join consists of parallel multi-way spatial filter and parallel spatial refinement. Parallel spatial refinement is executed by the following two steps. The first is the generation of a graph used for reducing duplication of both spatial objects and spatial operations from pairs candidate object table that are the results of multi-way spatial filter. The second is the parallel spatial refinement using that graph. Refinement using the graph is proved to be more efficient than the others. In task creation for parallel refinement, minimum duplication partitioning of the Spatial_Obicct_On_Node graph shows best performance.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.269-277
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• 1998

In most of the distributed deadlock detection algorithms using messages called probes, only a portion of the generated messages are effectively used, and hence the wasted probes cause heavy communication traffic. In this paper, a distributed deadlock detection algorithm is proposed which can efficiently detect deadlocks making use of those residue probes. Our algorithm is complete in the sense that they detect not only those deadlocks in which the initiator is involved as most other algorithms do, but all the other deadlocks that are present anywhere in a connected wait-for-graph. To detect all the deadlocks, the algorithms known to be most efficient require O(ne) messages, where e and n are the number of edges and nodes in the graph, respectively. The single execution of the presented algorithm can accomplish the same task with O(e) messages.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.262-269
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• 2007

Hierarchical Planning based on Abstraction of World Elements and Operators(HiPAWO) is proposed for mobile robots task planning, where abstraction of world elements is used for hierarchical planning and abstraction of operators is used for hierarchical decomposition of abstracted actions. Especially, a hierarchical domain theory based on JAH(Joint of Action Hierarchy)-graph is proposed to improve efficiency of planning, where a number of same actions are included in both adjacent hierarchical levels of domain theories to provide relationships between adjacent hierarchical levels. To show the validities of our proposed HiPAWO, experimental results are illustrated and will be compared with two other classical planning methods.