• Korean Journal of Remote Sensing
• /
• v.30 no.6
• /
• pp.817-827
• /
• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.5
• /
• pp.29-37
• /
• 2018

Biodiversity refers to the diversity of organisms originating from all sources, including terrestrial ecosystems, aquatic ecosystems, and complex ecosystems and it is considered to be the standard of the area to be preserved and protected. So The Importance of environmental assessment for biodiversity conservation is increasing and International efforts to quantify biodiversity and to develop indices have been made, but there are insufficient researches on the use of biomass databases and their quantification in Korea. In this study, the biodiversity map was constructed using the 3rd National Ecosystem Survey Mammal Data with three spatial units(Administrative Area, 1:5,000 index map, hexagonal lattice). and the difference of map constructed by spatial unit was suggested to help research on quantification and evaluation of biodiversity in the future. As a result of the study, biodiversity index for the same area varied according to the spatial unit and overall average and standard deviation were different too. Therefore it is necessary to utilize appropriate spatial unit considering the suitability and purpose of quantification rather than using specific unit. It also showed the necessity of establishing a standard for biodiversity index as a result of comparative analysis with ecosystem and nature map. Based on this research, comprehensive efforts should be made for the sustainable development of the country through further research and institutional improvement for quantification and evaluation of biodiversity, set standards.

• Science of Emotion and Sensibility
• /
• v.12 no.1
• /
• pp.137-144
• /
• 2009

This study aims to develop a 3D map which allows users to better understand the overall topography and to memorize the general concepts of the current location for tourists. The Map also utilizes different forms and color codes of the block units in the panoramic view. First, in preparation for making the road block unit, 28 types of roads presented in common map were defined. Based on the definitions, 12 dominant groups were formed. In designing each form, visual correlation was considered. Second, 42 types of terrain features presented in normal maps were defined for making the panoramic block unit. Then, 2 dominant groups, each contains 5 subgroups, were made according to the assemble pattern and the size of area. On the basis of the grouped units, the panoramic block units were produced with 3D pole line graphics maintaining integration. Lastly, each panoramic block units were categorized by color classes such as blue, green, gray and brown class. The overall color combination of the work was evaluated as well harmonized since the Moon&Spencer's Aesthetic measure value exceeds 0.5.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.4
• /
• pp.56-64
• /
• 2009

As the Internet has been improved to Web 2.0, it introduces new approaches including Rich Internet Application (RIA) technology such as Flash, AJAX, Silverlight, etc. The RIA which is platform independent technology allows applications to provide rich client-side interfaces, and allows the browser to interact with users without communication to server. In this paper, we propose a method of spatial data service based on RIA technology. Internet map service using spatial data generally requires rich client-side interfaces and various interactions. These features can be provided by the RIA. The proposed method uses Flash developed by Macromedia as RIA technology. It can be applicable on any platform including mobile environment. The spatial data server makes Flash file known as SWF (Shock Wave File) with manipulation code for map and spatial data that is requested by user, and send it to the web browser. Once the web browser receives a SWF, client SWF manipulates user interactions, such as zooming and panning, without communication with server. Experiments that execute the application on various web browsers including mobile web browser and measure time of map interaction are carried out to compare with traditional bitmap based WMS (Web Map Service). As a result of experiments, we have confirmed improvement of interactivity and performance with RIA approach.

• Journal of KIISE
• /
• v.43 no.1
• /
• pp.40-46
• /
• 2016

Digital road map generation is primarily based on artificial satellite photographing or in-site manual survey work. Therefore, these map generation procedures require a lot of time and a large budget to create and update road maps. Consequently, people have tried to develop automated map generation systems using GPS trajectory data sets obtained by public vehicles. A fundamental problem in this road generation procedure involves the extraction of representative trajectory such as main roads. Extracting a representative trajectory requires the base data set of piecewise line segments(GPS-trajectories), which have close starting and ending points. So, geometrically similar trajectories are selected for clustering before extracting one representative trajectory from among them. This paper proposes a new divide- and-conquer approach by partitioning the whole map region into regular grid sub-spaces. We then try to find similar trajectories by sweeping. Also, we applied the $Fr{\acute{e}}chet$ distance measure to compute the similarity between a pair of trajectories. We conducted experiments using a set of real GPS data with more than 500 vehicle trajectories obtained from Gangnam-gu, Seoul. The experiment shows that our grid partitioning approach is fast and stable and can be used in real applications for vehicle trajectory clustering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.479-482
• /
• 2014

Nowadays open-source hadoop systems have been using widely to efficiently manage a fast-growing big data. Hadoop systems consist of distributed file processing system called HDFS (Hadoop Distributed File System) and distributed parallel processing system called MapReduce. The MapReduce reads and processes big data from HDFS and then processed results are written in HDFS again by the MapReduce. Such a processing method has different system structure respectively according to hadoop version. Therefore, this paper shows analysis results for performance of hadoop systems. For this, we devise a way which monitors hadoop systems and measure occurrence frequency of processes, threads, and variables generated in hadoop system itself using the devised way. So, by using the measured results as analysis indicator, we help the indicator predict inner performance of hadoop systems.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.20 no.5
• /
• pp.502-509
• /
• 2010

A test facility which can simultaneously measure turbocharger operating condition variables and vibro-acoustic emission in the situations that are quite similar to real internal combustion engine operating conditions has been introduced. Using this facility, a new method sweeping from full open throttle to deep surge region along constant speed curves can be utilized instead of the stationary method that has been traditionally used to obtain turbocharger compressor maps. Data covering an extensive range of the compressor performance map have been collected and analyzed. An experimental study is performed to define a noise diagram that correlates vibro-acoustic measurements to aerothermodynamic operating conditions. An instrumentation set in the facility allows the automatic definition of the operating point on the turbine and compressor map of the turbocharger. Also, radiated sound pressure and casing vibration data corresponding to the point are obtained by a microphone in the vicinity of the compressor casing and an accelerometer on the casing. The major source(s) of noise at specific operating point on the map can be easily identified with these maps. Also, acoustic characteristics of a given turbocharger at the vicinity of the surge as well as in the surge are also defined. Finally, the possibility to define mild surge region of a turbocharger using vibro-acoustic measurements is studied.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.1
• /
• pp.95-100
• /
• 2011

The test was done on cars travelling at speeds of 20km/h, 60km/h and 100km/h, the performance testing mode for chassis dynamometer. In this test, the secondary waveform were measured, including those using faulty MAP sensors, oxygen sensors and spark plugs. The results from these measurements and their analysis of secondary waveform can be summarized as follows: 1) The secondary waveform measured from the faulty oxygen sensor showed a lot of noise around peak voltage and in the rising and falling sections during spark line which means that the air fuel mixture was non-homogeneous. 2) The secondary waveform from the faulty MAP sensor showed the worst shape compared to other sensors, including variation of spark line, state of air-fuel mixture and velocity of flame front. 3) The spark line time of secondary waveform using a faulty spark plug displayed the shortest and smallest energy spark line, which means that a misfire occurred.

• Korean Journal of Oriental Medicine
• /
• v.12 no.2 s.17
• /
• pp.85-92
• /
• 2006

Pulse is one of the basic diagnostic information of TKM(Traditional Korean Medicine). To quantify and standardize pulse diagnosis, we had collected an amount of clinical data from May 2005 by using newly developed pulse analyzer. But there were many noises in pulse wave according to measuring method, environment, operator and condition of patient. So some data can’t be included for analyzing diagnosis. To reduce noises from measuring pulse and to collect reliable pulse wave data, we made the process map of measuring method and applied six sigma project. With this we can improved the method of measuring pulse wave in collecting clinical data. The project follows a disciplined process of five macro phases: define, measure, analyze, improve and control (DMAIC). A process map and C-E diagram are used to identify process input and output variables. The major input variables are selected by using C&E matrix, and process map is developed by analyzing input variables. And the optimum process conditions are going to be controled to avoid in increasing loss of collecting pulse wave data.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.1886-1908
• /
• 2020

With the technical advances, the amount of big data is increasing day-by-day such that the traditional software tools face a burden in handling them. Additionally, the presence of the imbalance data in big data is a massive concern to the research industry. In order to assure the effective management of big data and to deal with the imbalanced data, this paper proposes a new indexing algorithm for retrieving big data in the MapReduce framework. In mappers, the data clustering is done based on the Sparse Fuzzy-c-means (Sparse FCM) algorithm. The reducer combines the clusters generated by the mapper and again performs data clustering with the Sparse FCM algorithm. The two-level query matching is performed for determining the requested data. The first level query matching is performed for determining the cluster, and the second level query matching is done for accessing the requested data. The ranking of data is performed using the proposed Monarch chaotic whale optimization algorithm (M-CWOA), which is designed by combining Monarch butterfly optimization (MBO) [22] and chaotic whale optimization algorithm (CWOA) [21]. Here, the Parametric Enabled-Similarity Measure (PESM) is adapted for matching the similarities between two datasets. The proposed M-CWOA outperformed other methods with maximal precision of 0.9237, recall of 0.9371, F1-score of 0.9223, respectively.