• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.45-51
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• 2019

The use of the Internet of things plays a major role in the Fourth Industrial Revolution, and a series of tasks of accumulating, converging, analyzing and reusing various data and services becomes very important. Because the pace and scope if the paradigm shift in Fourth Industrial Revolution is so rapid and unpredictable, the development and utilization of a system to fulfill this role for IOT are urgently required. In this paper, we introduce the Web-based IOT management system, which connects the IOT with OKMindmap, which is a domestic open source software and service, and the Node-RED service. This system combines the advantages of OKMindmap with the advantages of Node-RED, which is capable of visual component based programming, so that it can easily and flexibly connect the IOT based on Web browsers, and various data and services can be integrated and linked. We developed a camera module, a temperature and humidity sensor module, and the motor control module in Raspberry PI basically, and tested the operation successfully. We plan to extend the IOT component gradually by using Arduino and System On Chip.

• Journal of KIISE
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• v.44 no.4
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• pp.383-391
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• 2017

As we enter a new era of Big Data, the amount of semantic data has rapidly increased. In order to derive meaningful information from this large semantic data, studies that utilize the SWRL(Semantic Web Rule Language) are being actively conducted. SWRL rules are based on data extracted from a user's empirical knowledge. However, conventional reasoning systems developed on single machines cannot process large scale data. Similarly, multi-node based reasoning systems have performance degradation problems due to network shuffling. Therefore, this paper overcomes the limitations of existing systems and proposes more efficient distributed inference methods. It also introduces data partitioning strategies to minimize network shuffling. In addition, it describes a method for optimizing the incremental reasoning process through data selection and determining the rule order. In order to evaluate the proposed methods, the experiments were conducted using WiseKB consisting of 200 million triples with 83 user defined rules and the overall reasoning task was completed in 32.7 minutes. Also, the experiment results using LUBM bench datasets showed that our approach could perform reasoning twice as fast as MapReduce based reasoning systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.165-173
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• 2008

In this paper, we propose a new reliable broadcast protocol referred to as timer-based reliable broadcast (TRB) for wireless sensor networks (WSNs). The proposed TRB scheme exploits (1) bitmap based explicit ACK to effectively reduce the unnecessary error control messages and (2) randomized timer for ACK transmission to substantially reduce the possibility of contentions. Although it has been argued that 100% reliability is not necessary in WSNs, there should be messages (such as mission-critical message, task assignment, software updates, etc.) that need to be reliably delivered to the entire sensor field. We propose to use the TRB algorithm for such cases. Performance evaluation shows that the TRB scheme achieves 100 % reliability significantly better than other schemes with expense of slightly increased energy consumption.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.85-91
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• 1989

In this paper, we propose a neural net system for speech recognition, which is composed of two neural networks. Firstly the self-supervised BP(Back Propagation) network generates the distributed concept corresponding to the activity pattern in the hidden units. And then the self-organizing neural network forms a concept map which directly displays the similarity relations between concepts. By doing the above, the difficulty in learning the conventional BP network is solved and the weak side of BP falling into a pattern matcher is gone, while the strong point of generating the various internal representations is used. And we have obtained the concept map which is more orderly than the Kohonen's SOFM. The proposed neural net system needs not any special preprocessing and has a self-learning ability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.12
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• pp.874-880
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• 2019

This paper introduces a method which can be effectively used for the path planning of UAV in a realistic map which has mountainous terrains, air defense networks and radars based on the Visibility Graph. Existing studies of Visibility Graph have been studied mainly for simple shape obstacles in 2-dimensional environment such as self-driving cars which avoid buildings. However, for UAV, Visibility Graph must be used in 3-dimensional environment for the variance of altitude. This occurs significant elapsed time increase because of the increase of the amount of the visibility of node sets. To solve this problem, this paper decrease the number of nodes which consists the complex terrain environments using convex hull based on Layered Visibility Graph. With convex hull method, this paper confirmed that the elapsed time is decreased about 99.5% compared to the case which has no decrease of the number of nodes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.74-84
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• 2010

In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.183-192
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• 2012

Although underground water resource has relatively less pollution rate compared with surface water, its recovery faces many difficulties due to poor management. Our country monitors underground water to manage it effectively through auxiliary observation network for underground water. In this paper, we suggest water-well auto measure system based on Geosensor for business efficiency increase of water-well management and realtime monitering. In this system is consist of user GUI(Graphic User Interface) composed with water-well information and movement sub-observation network prototype system composed with GPS(Global Positioning System) and wireless sensor node such as water temperature, water level, electrical conductivity. In this system is using the light of the sun for self-power, variety water-well information collected wireless sensor node was a wireless transmitting/receiving a using CDMA(Code Division Multiple Access) module. Also, for promote with user ease, user GUI express that water-well collected in GIS(Geographic Information System) map. For performance evaluation of the proposed system, we perform experiment using sensing information through designed sub-observation network. And we was proved superiority of the proposed system through qualitative evaluation with other paper.