• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.169-175
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• 2016

Geofence is a virtual perimeter for a real-world geographical area, which could be statically or dynamically established the specified area if necessary. Many geofencing applications incorporate 2D(two-dimensional) map such as the Google map, allowing administrators to define boundaries on top of a satellite view of a specific geographical area. But these applications do not provide 3D(three-dimensional) spatial information as well as 2D location information no matter where indoor or outdoor. Therefore we propose a mechanism to identify indoor or outdoor location for 3D geofence, and implement 3D geofence using smartphone. The proposed mechanism identifies the position information on 3D geofence regardless of indoor or outdoor, inter-floor with only GPS and WiFi. In the near future, 3D geofence as well as LBS are promising applications that become possible when IoT can become organized and connected by location.

• Journal of KIISE
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• v.44 no.7
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• pp.674-679
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• 2017

In big-data environments wherein large amounts of text documents are produced daily, titles are very important clues that enable a prompt catching of the key ideas in documents; however, titles are absent for numerous document types such as blog articles and social-media messages. In this paper, a title-generation model for which sequence-to-sequence RNNs with attention and copying mechanisms are employed is proposed. For the proposed model, input sentences are encoded based on bi-directional GRU (gated recurrent unit) networks, and the title words are generated through a decoding of the encoded sentences with keywords that are automatically selected from the input sentences. Regarding the experiments with 93631 training-data documents and 500 test-data documents, the attention-mechanism performances are more effective (ROUGE-1: 0.1935, ROUGE-2: 0.0364, ROUGE-L: 0.1555) than those of the copying mechanism; in addition, the qualitative-evaluation radiative performance of the former is higher.

• Journal of KIISE
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• v.44 no.7
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• pp.703-709
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• 2017

Outsourcing databases is to offload storage and computationally intensive tasks to the third party server. Therefore, data owners can manage big data, and handle queries from clients, without building a costly infrastructure. However, because of the insecurity of network systems, the third-party server may be untrusted, thus the query results from the server may be tampered with. This problem has motivated significant research efforts on authenticating various queries such as range query, kNN query, function query, etc. Although aggregation queries play a key role in analyzing big data, authenticating aggregation queries has not been extensively studied, and the previous works are not efficient for data with high dimension or a large number of distinct values. In this paper, we propose the AMR-tree that is a data structure, applied to authenticate aggregation queries. We also propose an efficient proof construction method and a verification method with the AMR-tree. Furthermore, we validate the performance of the proposed algorithm by conducting various experiments through changing parameters such as the number of distinct values, the number of records, and the dimension of data.

• Journal of KIISE
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• v.45 no.1
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• pp.61-68
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• 2018

The identification of genes that contribute to the prediction of prognosis in patients with cancer is one of the challenges in providing appropriate therapies. To find the prognostic genes, several classification models using gene expression data have been proposed. However, the prediction accuracy of cancer prognosis is limited due to the heterogeneity of cancer. In this paper, we integrate microarray data with biological network data using a modified PageRank algorithm to identify prognostic genes. We also predict the prognosis of patients with 6 cancer types (including breast carcinoma) using the K-Nearest Neighbor algorithm. Before we apply the modified PageRank, we separate samples by K-Means clustering to address the heterogeneity of cancer. The proposed algorithm showed better performance than traditional algorithms for prognosis. We were also able to identify cluster-specific biological processes using GO enrichment analysis.

• Journal of Information Management
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• v.29 no.1
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• pp.1-19
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• 1998

With development in computing and networking technologies, national supports and attention for building digital library, which is to overcome the limits of time and location in using information resources, is increasing. To accomplish the main goal of digital library that is to freely share and transfer information on network, the importance of standardization in developing electronic document is increasing. Now several tools to develop electronic document, which will be used in digital library, are developed for electronic document used on WWW. But none of them has absolute advantages to other formats. Those tools, that is, have comparative advantages and disadvantages for making electronic documents. Through reviewing features and analyzing comparative advantage and disadvantage of SGML, HTML, and PDF, which will be used to develop electronic documents in digital libraries, this study focuses on their comparative advantages and disadvantages. With doing it, this study propose relevant type of electronic document formats to the types of information resources.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.175-180
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• 2013

In this paper, we proposed that the functionality of teenage school girl cosmetics to improve the performance of the new product development and efficient production of information, analysis and policy analysis system for the SNS. The proposed system functional cosmetics of high school girls on the SNS efficient algorithms to analyze the content and methodology proposed to maximize the throughput of the system, to minimize the execution time of each task. In addition, functional cosmetics of high school girls in the state by identifying the symbols, the analytical results in the development and production of products to reflect propose a visual methodology. Therefore, the proposed system only in cosmetics, as well as an analysis similar to rapidly changing consumer preferences in the manufacturing sector can be applied in various ways.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.273-281
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• 2016

The issue about the safety management of gas related work has been studied toward a direction to utilize IoT system recently. For this purpose, the matters of user's demand has been deduced through the literature survey, field survey, and professional consultation, by studying the characteristics of worker, work, and work site. In summary, these are the demands for mobile App, 1)a clear arrangement of contents, 2)a design with high readability, 3)a design with low death, 4) securing of user's accessibility, 5)an effective information transmission plan in the work section where it is impossible to operate the mobile device, 6)an activation of alarm function at the section of high working error, 7)a fast two-way transmission and receipt of safety inspection matter needed at work, 8)a selection of images and contents that can guide the situation to the worker in case of accident, 9)an alarm function for the degree of danger in an area of worker's location. Based on these, a basic design of safety application for gas related work has been proposed, that can secure the user accessibility.

• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.10
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• pp.979-988
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• 2012

The 3D structure of GDL for fuel cells was measured using high-resolution X-ray tomography in order to study material transport in the GDL. A computational algorithm has been developed to remove noise in the 3D image and construct 3D elements representing carbon fibers of GDL, which were used for both structural and fluid analyses. Changes in the pore structure of GDL under various compression levels were calculated, and the corresponding volume meshes were generated to evaluate the anisotropic permeability of gas within GDL as a function of compression. Furthermore, the transfer of liquid water and reactant gases was simulated by using the volume of fluid (VOF) and pore-network model (PNM) techniques. In addition, the simulation results of liquid water transport in GDL were validated by analogous experiments to visualize the diffusion of fluid in porous media. Through this research, a procedure for simulating the material transport in deformed GDL has been developed; this will help in optimizing the clamping force of fuel cell stacks as well as in determining the design parameters of GDL, such as thickness and porosity.

• Journal of KIISE
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• v.45 no.1
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• pp.53-60
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• 2018

This study describes a spatial web object retrieval system using Spark, an in - memory based distributed processing system. Development of social networks has created massive amounts of spatial web objects, and retrieval and analysis of data is difficult by using exist spatial web object retrieval systems. Recently, development of distributed processing systems supports the ability to analyze and retrieve large amounts of data quickly. Therefore, a method is promoted to search a large-capacity spatial web object by using the distributed processing system. Data is processed in block units, and one of these blocks is converted to RDD and processed in Spark. Regarding the discussed method, we propose a system in which each RDD consists of spatial web object index for the included data, dividing the entire spatial region into non-overlapping spatial regions, and allocating one divided region to one RDD. We propose a system that can efficiently use the distributed processing system by dividing space and increasing efficiency of searching the divided space. Additionally by comparing QP-tree with R-tree, we confirm that the proposed system is better for searching the spatial web objects; QP-tree builds index with both spatial and words information while R-tree build index only with spatial information.