• Information Systems Review
• /
• v.18 no.1
• /
• pp.141-155
• /
• 2016

This study identified terminologies related to the proximity and frequency of disaster by social network analysis (SNA) and text mining, and then expressed the outcome into a mind map. The termdocument matrix of text mining was utilized for the terminology proximity analysis, and the SNA closeness centrality was calculated to organically express the relationship of the terminologies through a mind map. By analyzing terminology proximity and selecting disaster response-related terminologies, this study identified the closest field among all the disaster response fields to disaster response and the core terms in each disaster response field. This disaster response terminology analysis could be utilized in future core term-based terminology standardization, disaster-related knowledge accumulation and research, and application of various response scenario compositions, among others.

• Journal of Digital Contents Society
• /
• v.15 no.2
• /
• pp.251-261
• /
• 2014

In the typical P2P VOD system, it is very important to develop the fast and efficient peer searching scheme since the peers frequently join and leave to/from P2P system. This paper proposes a new peer searching scheme for P2P VOD system based on DHT network environment. The proposed scheme constructs DHT network by managing the peers having close playback starting times and close network locations into a peer all together. The peer information is mapped onto DHT nodes by hashing the key values each of which consists of the starting time and network location of the peer. From the simulation results, the number of messages required to search the partner peers are decreased, and the number of buffer maps exchanging among the peers are also decreased. The proposed scheme can reduce the average network distances among the partner peers. As a result, the proposed scheme makes routing more efficient and it saves the network resources by decreasing communication traffic overhead.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.4
• /
• pp.523-531
• /
• 2011

Many of the wells which were constructed to use ground water resource are abandoned and not managed efficiently after its use. And a variety of heavy metals and organic compounds are released from the abandoned wells and this can cause ground water pollution. Therefore in this paper implemented to monitor locational information drill holes and underground water sensing information on real time basis using u-GIS environment to combined ubiquitous sensor node and GIS technology to improve these problems. In addition, this system suggests using system by UML 2.0 by analyzing variety requirement of user and between system internal modules interaction and data flow. It provides graphical user interfaces (GUI) to system users to monitor water-well related property information and its managements for each water-well at remote site by variety platform by GIS map and web environment and mobile device based on smart phone.

• Journal of Advanced Navigation Technology
• /
• v.18 no.5
• /
• pp.468-475
• /
• 2014

The recommend system is getting more difficult real time recommend by lager preference data set, computing power and recommend algorithm. For this reason, recommend system is proceeding actively one's studies toward distribute processing method of large preference data set. This paper studied distribute processing method of large preference data set using hadoop distribute processing platform and mahout machine learning library. The recommend algorithm is used Co-occurrence Matrix similar to item Collaborative Filtering. The Co-occurrence Matrix can do distribute processing by many node of hadoop cluster, and it needs many computation scale but can reduce computation scale by distribute processing. This paper has simplified distribute processing of co-occurrence matrix by changes over from four stage to three stage. As a result, this paper can reduce mapreduce job and can generate recommend file. And it has a fast processing speed, and reduce map output data.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.10
• /
• pp.11-17
• /
• 2010

Mobile device, one of typical devices in ubiquitous environment, is received attention owing to portability. In these days, technical researches on a kind of the device are focusing on applications of smart phone. For example, the techniques using geographical position and applied instances such as augmented reality techniques are gradually increasing. That makes data processing important. Mobile application services for users also require various application techniques based on moving objects. In addition, they require the techniques that processed data are needed to be shown in visualization. However, this is reality that it lacks of showing visualization works to improve the understanding of thing what it is. To reduce or solve the problems, in this paper we show the results to implement the R tree based 3 dimension index architecture in visualization. Further, we implemented and present creating objects, showing in 3D for the objects, catching spatial position on a node map through mini map function and improving the understanding of R tree by visualizing.

• Journal of KIISE:Databases
• /
• v.27 no.1
• /
• pp.13-21
• /
• 2000

Online analytical processing (OLAP) systems are introduced to support decision support systems. Many researches focussed on efficient processing of aggregate functions that usually occur in OLAP queries. However, most previous researches in the literature are deal with the situation in which aggregate functions arc applied to all the values in a given range. Since those approaches utilize characteristic of aggregate functions applied to a range, they are difficult to be applied to a muitipoint query that is a query considering only some points in a given range. In this paper, we propose the Ranking Index and the flanking Decision Tree (RDT) for efficient evaluation of multipoints MAX/MIN queries. The ranking of possible MAX/MIN values are computed with RDT Then MAX/MIN values can be acquired from the Ranking Index. We show through experiments that our method provides high performance in most situations. In other words, the proposed method is robust as well as efficient. A single common set of precomputed results for both MAX and MIN values is another advantage of the proposed method.

• KIISE Transactions on Computing Practices
• /
• v.22 no.1
• /
• pp.20-25
• /
• 2016

With the advent of the era of digital big data, the Hadoop platform has become widely used in various fields. However, the Hadoop MapReduce framework suffers from problems related to the increase of the name node's main memory and map tasks for the processing of large number of small files. In addition, a method for running C++-based tasks in the MapReduce framework is required in order to conjugate GPUs supporting hardware-based data parallelism in the MapReduce framework. Therefore, in this paper, we present a face detection system that generates a sequence file for images to process big data for images in the Hadoop platform. The system also deals with tasks for GPU-based face detection in the MapReduce framework using Hadoop Pipes. We demonstrate a performance increase of around 6.8-fold as compared to a single CPU process.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.6
• /
• pp.599-607
• /
• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• Journal of the Korea Computer Graphics Society
• /
• v.6 no.4
• /
• pp.1-7
• /
• 2000

Traditionally, three dimension model s have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity. it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined. traversed, and rendered together. In fact, as suggested by Shade et al. [1]. these different representations can be used as different LOD's for a given object. For in stance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range. and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform : designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection. handling their transition s. implementing appropriate interaction schemes. and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit. to accommodate new node types for environment maps. billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also. during interaction, regardless of the viewing distance. a 3D representation would be used, if it exists. Finally. we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

• Journal of KIISE:Information Networking
• /
• v.30 no.2
• /
• pp.282-292
• /
• 2003

This paper proposes an efficient data structure for forwarding IPv4 and IPv6 packets at the gigabit speed in backbone routers. The LPM(Longest Prefix Matching) search becomes a bottleneck of routers' performance since the LPM complexity grows in proportion to the forwarding table size and the address length. To speed up the forwarding process, this paper introduces a data structure named BMT(Bit-Map Tie) to minimize the frequent main memory accesses. All the necessary search computations in BMT are done over a small index table stored at cache. To build the small index table from the tie representation of the forwarding table, BMT represents a link pointer to the child node and a node pointer to the corresponding entry in the forwarding table with one bit respectively. To improve the poor performance of the conventional tries when their height becomes higher due to the increase of the address length, BMT adopts a binary search algorithm for determining the appropriate level of tries to start. The simulation experiments show that BMT compacts the IPv4 backbone routers' forwarding table into a small one less than 512-kbyte and achieves the average speed of 250ns/packet on Pentium II processors, which is almost the same performance as the fastest conventional lookup algorithms.