• Journal of Forest and Environmental Science
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• v.29 no.4
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• pp.307-313
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• 2013

Forest Survey consists of road survey, topographic survey, tree mapping survey, stream survey and also ridge survey. Information from forest survey is important and become essential in preparing base map to be used for forest harvesting planning and control. With the current technologies technique of data processing and mapping from traditionally hand drawn method had shifted to a computer system particularly the use of Computer Aided Design (CAD). This gives great advantages to the forest managers and logging operators. However data processing and mapping duration could be further reduced by integrating CAD with other established software such as Microsoft Excel. This time study to show that there is significance difference in term of duration for data processing and efficiency using AutoCAD in combination with Microsoft Excel program as compare to the use of AutoCAD program alone. From the study, it shows that the integration of AutoCAD and Microsoft Excel is able to reduce 70% of duration for data processing and mapping as compared to the use of AutoCAD program alone.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.137-142
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• 1999

The purpose of this study is to develope a CAD-based tool for rasterization of polygonal vector map in AutoCAD. To identity the layer property of polygonal entity with user-defined coordinates as topology, algorithm in processing entity data of selection set that intersected with scan line was used, and the layers were extracted sequentially by sorted intersecting points in data-list. In addition to the functions for querying and modifying topology, two options for mapping were set up to construct plan projection type and to change meshes' properties in existing DTM data. In case of plan projection type, user-defined cell size of 3DFACE mesh is available for more detailed edge, and topological draping on landform can be executed in case of referring DTM data as an AutoCAD's drawing. The concept of algorithm was simple and clear, but some unexpectable errors were found in detecting intersected coordinates that were AutoCAD's error, not the utility's. Also, the routines to check these errors were included in algorithmic processing. Developed utility named MESHMAP was written in entity data control functions of AutoLISP language and dialog control language(DCL) for the purpose of user-oriented interactive usage. MESHMAP was proved to be more effective in data handling and time comparing with GRIDMAP module in LANDCADD which has similar function.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.8-13
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• 2019

Visual place recognition is widely researched area in robotics, as it is one of the elemental requirements for autonomous navigation, simultaneous localization and mapping for mobile robots. However, place recognition in changing environment is a challenging problem since a same place look different according to the time, weather, and seasons. This paper presents a feature extraction method using a deep convolutional auto-encoder to recognize places under severe appearance changes. Given database and query image sequences from different environments, the convolutional auto-encoder is trained to predict the images of the desired environment. The training process is performed by minimizing the loss function between the predicted image and the desired image. After finishing the training process, the encoding part of the structure transforms an input image to a low dimensional latent representation, and it can be used as a condition-invariant feature for recognizing places in changing environment. Experiments were conducted to prove the effective of the proposed method, and the results showed that our method outperformed than existing methods.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.939-946
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• 2018

In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2067-2075
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• 2017

Lately big data processing is considered as an emerging issue. As a huge amount of data is generated, data processing capability is getting important. In processing big data, both Hadoop distributed file system and unstructured date processing-based NoSQL data store are getting a lot of attention. However, there still exists problems and inconvenience to use NoSQL. In case of low volume data, MapReduce of NoSQL normally consumes unnecessary processing time and requires relatively much more data retrieval time than RDBMS. In order to address the NoSQL problem, in this paper, an interworking scheme between NoSQL and the conventional RDBMS is proposed. The developed auto-mapping scheme enables to choose an appropriate database (NoSQL or RDBMS) depending on the amount of data, which results in fast search time. The experimental results for a specific data set shows that the database interworking scheme reduces data searching time by 35% at the maximum.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.229-231
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• 2006

NLPCA(Nonlinear Principal Component Analysis) is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA operates by a feedforward neural network called AANN(Auto Associative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA is presented. To verify its applicability, simulation study on the data supplied from sensor network is executed.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.295-300
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• 2006

The integral imaging system is an auto-stereoscopic display that allows users to see 3D images without wearing special glasses. In the integral imaging system, the 3D object information is taken from several view points and stored as elemental images. Then, users can see a 3D reconstructed image by the elemental images displayed through a lens array. The elemental images can be created by computer graphics, which is referred to the computer-generated integral imaging. The process of creating the elemental images is called image mapping. There are some image mapping methods proposed in the past, such as PRR(Point Retracing Rendering), MVR(Multi-Viewpoint Rendering) and PGR(Parallel Group Rendering). However, they have problems with heavy rendering computations or performance barrier as the number of elemental lenses in the lens array increases. Thus, it is difficult to use them in real-time graphics applications, such as virtual reality or real-time, interactive games. In this paper, we propose a new image mapping method named VVR(Viewpoint Vector Rendering) that improves real-time rendering performance. This paper describes the concept of VVR first and the performance comparison of image mapping process with previous methods. Then, it discusses possible directions for the future improvements.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.38.2-38.2
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• 2016

The mapping of dark matter clustering from real to redshift spaces introduces the anisotropic property to the measured density power spectrum in redshift space, known as the Redshift Space Distortion (hereafter RSD) effect. The mapping formula is intrinsically non-linear, which is complicated by the higher order polynomials due to the indefinite cross correlations between the density and velocity fields, and the Finger-of-God (hereafter FoG) effect due to the randomness of the peculiar velocity field. Furthermore, the rigorous test of this mapping formula is contaminated by the unknown non-linearity of the density and velocity fields, including their auto- and cross-correlations, for calculating which our theoretical calculation breaks down beyond some scales. Whilst the full higher order polynomials remains unknown, the other systematics can be controlled consistently within the same order truncation in the expansion of the mapping formula, as shown in this paper. The systematic due to the unknown non-linear density and velocity fields is removed by separately measuring all terms in the expansion using simulations. The uncertainty caused by the velocity randomness is controlled by splitting the FoG term into two pieces, 1) the non-local FoG term being independent of the separation vector between two different points, and 2) the local FoG term appearing as an indefinite polynomials which is expanded in the same order as all other perturbative polynomials. Using 100 realizations of simulations, we find that the best fitted non-local FoG function is Gaussian, with only one scale-independent free parameter, and that our new mapping formulation accurately reproduces the observed power spectrum in redshift space at the smallest scales by far, up to k ~ 0.3 h/Mpc, considering the resolution of future experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1004-1007
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• 1996

Various auto-tuning methods using relay feedback are presented recently. They are composed of the consecutive procedures identifying Nyquist critical point using relay feedback and designing PID controller by one point of Nyquist plot mapping. This paper suggests a strategy to get the knowledges of Nyquist critical point and the neighborhood point of it using relay feedback. The parameters of PID controller are established by dominant pole approximation based on these knowledges. Designers can make use of the damping ratio as a time domain specification. So design flexibilities are taken in view of stability and performance of the system response considering practical system condition.