• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1029-1040
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• 2011

In this paper we propose an intelligent navigation algorithm for real world problem which can build a map without localization. Proposed algorithm operates online and furthermore does not require many memories for applying real world problem. After applying proposed algorithm to toy and huge data set, it does not require to calculate a whole eigenspace and need less memory compared to existing algorithm. Thus we can obtain that proposed algorithm is suitable for real world mobile navigation algorithm.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3164-3170
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• 2000

The use of the A' for the path search of the agent in the game map give the overhead of computing time in real time game processing. The other heuristic search algorithms do not guarantee the optical path. The route table of which the row is defined by current position, goal position, visiting position is presented in this paper. This route table is made in the game development phase and tilized in game playing. The visiting position which is contatined in the optimal path to the goal position from the current position can guarantee the optical path, and this mothod has no overhead on computing time. But the memory space is requred too much. This problem can also be solved using the data compression by skipping the duplicated route table.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.340-342
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• 2003

Location based services based on positions of moving objects are expanding the business area gradually. The location is included all estimate position of the future as well as the position of the present and the past. Location based routing service is active business application in which the position information of moving objects is applied efficiently. This service includes the trajectory of past positions, the real-time tracing of present position of special moving objects, and the shortest and optimized paths combined with map information. In this paper, we describes the location based routing services is extend in distributed web GIS environment. Web GIS service systems provide the various GIS services of analyzing and displaying the spatial data with friendly user - interface. That is, we propose the efficient architecture and technologies for servicing the location based routing services in distributed web GIS environment. The position of moving objects is acquired by GPS (Global Positioning System) and converted the coordinate of real world by map matching with geometric information. We suppose the swapping method between main memory and storages to access the quite a number of moving objects. And, the result of location based routing services is wrapped the web-styled data format. We design the schema based on the GML. We design these services as components were developed in object-oriented computing environment, and provide the interoperability, language-independent, easy developing environment as well as re - usability.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.11
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• pp.109-116
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• 2019

Seongbuk Village and Ungcheon Village are Town Wall Villages that reflect social and historical backgrounds. villagers have formed villages based on community life. The streets and places of the villages are accumulated as images in the memory of the inhabitants. Based on their imagination-concept, 30 sketch maps, reflecting residents' cognitive perception were collected. Analysis of 30 sketch maps shows that other forming of Collective maps. In the past, Villages historical facilities had changed roles, but the relationship between the place and the place has been continuous, and according to the development process of the villages, the relationship between streets and places has been formed. Following this, the analysis methodology of social spaces and sketch will be examined in depth.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of KIISE:Information Networking
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• v.28 no.2
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• pp.262-276
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• 2001

Recently much research for developing forwarding table that support fast router without employing both special hardware and new protocols. This article introduces a new forwarding data structure based on the software to enable forwarding lookup to be penormed at giga-bit speed. The forwarding table is known as a bottleneck of the routers penormance due to its high complexity proportional to the forwarding table size. The recent research that based on the software uses a Patricia trie and its variants. and also uses a hash function with prefix length key and others. The proposed forwarding table structure construct a forwarding table by the bit stream array in which it constructs trie from routing table prefix entries and it represents each pointer pointing the child node and the associated forwarding table entry with one bit The trie structure and routing prefix pointer need a large memory when representing those by linked-list or array. but in the proposed data structure, the needed memory size is small enough since it represents information with one bit. Additionally, by use a lookup method that start searching at desired middle level we can shorten the search path. The introduced data structure. called bit-map trie shows that we can implement a fast forwarding engine on the conventional Pentium processor by reducing the backbone routing table fits into Level 2 cache of Pentium II processor and shortens the searching path. Our experiments to evaluate the performance of proposed method show that this bit-map trie accomplishes 5.7 million lookups per second.

• Journal of IKEEE
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• v.23 no.1
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• pp.134-142
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• 2019

As the development of internet of energy (IoE) technologies and spread of various electronic devices have diversified patterns of energy consumption, the reliability of demand prediction has decreased, causing problems in optimization of power generation and stabilization of power supply. In this study, we propose a deep learning method, 1-Dimention-Convolution and Bidirectional Long Short-Term Memory (1D-ConvBLSTM), that combines a convolution neural network (CNN) and a Bidirectional Long Short-Term Memory(BLSTM) for highly reliable demand forecasting by effectively extracting the energy consumption pattern. In experimental results, the demand is predicted with the proposed deep learning method for various number of learning iterations and feature maps, and it is verified that the test data is predicted with a small number of iterations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.17-28
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• 2017

Recently, a study on data has been actively conducted because the value of the data has become more useful. Web crawler that is program of data collection recently spotlighted because it can take advantage of the various fields. Web crawler can be defined as a tool to analyze the web pages and collects the URL by traversing the web server in an automated manner. For the treatment of Big-data, distributed Web crawler is widely used which is based on the Hadoop MapReduce. But, it is difficult to use and has constraints on the performance. Apache spark that is the In-memory computing platform is an alternative to MapReduce. The search engine which is one of the main purposes of web crawler displays the information you search by keyword gathered by web crawler. If search engines implement a spark-based web crawler instead of traditional MapReduce-based web crawler, it would be a more rapid data collection.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.49-56
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• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.162-167
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• 2015

This paper describes the reason and the problem solving for the double-layer pattern of a Daejeon correlator operated in Korea-Japan Correlation Center. When the electric power of an input signal in the correlator is charged small enough to be buried in the noise, it is hard to see a signal with a specific pattern in the input signal, but when the electric power is large, a specific one is reported to be seen. By comparing data from observation with one from software correlator, it was confirmed from the analysis using the AIPS software that the amplitude gain of a source signal was affected about 3%. Therefore, in order to solve the problem of double-layer patterns, we found that a problem in the memory management module responsible for both the data input and the data serialization of the correlator is a cause for the double-layer pattern detected periodically. In other words, while data is serialized and read repeatedly in the memory area assigned to serialize the data from the serialization module, redundant last data is generated and an overlap for the memory allocation is occurred. Therefore, by modifying the program of the FPGA memory sections on serialization module to correct the problem, we confirmed that double-layer pattern is disappeared and correlation results are normally acquired.