• Journal of IKEEE
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• v.24 no.1
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• pp.200-207
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• 2020

In this paper, an area-efficient feature extractor was proposed for security surveillance radar systems and FPGA-based implementation results were presented. In order to reduce the memory requirements, features extracted from Doppler profile for FFT window-size are used, while those extracted from total spectrogram for frame-size are excluded. The proposed feature extractor was design using Verilog-HDL and implemented with Xilinx Zynq-7000 FPGA device. Implementation results show that the proposed design can reduce the logic slice and memory requirements by 58.3% and 98.3%, respectively, compared with the existing research. In addition, security surveillance radar system with the proposed feature extractor was implemented and experiments to classify car, bicycle, human and kickboard were performed. It is confirmed from these experiments that the accuracy of classification is 93.4%.

• Ocean Systems Engineering
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• v.5 no.1
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• pp.1-19
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• 2015

The water jetting system for a jack-up spudcan requires the suitable design considering the platform/spudcan particulars, environments, and soil conditions, either the surficial clay or surficial sand. The usage of water jetting depends critically on soil conditions. The water jetting is usually used for the smooth and fast extraction of the spudcan in the surficial clay condition. It is also required for inserting spudcan up to the required depth in the surficial sand condition, which is investigated in this paper. Especially, it should be very careful to use the water jetting during an installation of spudcan in the surficial sand condition, because there is a risk of overturning accident related to the punch-through. Therefore, in this study, the effect of water jetting flow rate and time on the change of soil properties and penetration resistance is analyzed to better understand their interactions and correlations when inserting the spudcan with water jetting in surficial sand condition. For the investigation, a wind turbine installation jack-up rig (WTIJ) is selected as the target platform and the multi layered soil (surficial sand overlaying clays) is considered as the soil condition. The environmental loading and soil-structure interaction (SSI) analysis are performed by using CHARM3D and ANSYS. This kind of investigation and simulation is needed to decide the proper water jetting flow rate and time of spudcan for the given design condition.

• YAKHAK HOEJI
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• v.52 no.6
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• pp.480-487
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• 2008

We described an estimation of measurement uncertainty in quantitative analysis of 11-nor-9-carboxy-${\Delta}^9$-tetrahydrocannabinol (THCCOOH), the major metabolite of ${\Delta}^9$-tetrahydrocannabinol, in urine sample by solid-phase extraction (SPE) and GC/MS detection. The analytical results were compared and the different contributions to the uncertainty were evaluated. Inter-day and inter-person validation were performed using statistical analysis of several indicative factors. Measurement uncertainty associated with target analyte in real forensic samples was estimated using quality control (QC) data. Traceability of measurement was established through traceable standards, calibrated volumetric glassware and volume measuring device. The major factors of contribution to combined standard uncertainty, were calibration linearity, inter-day repeatability and inter-person reproducibility, while those associated with preparation of analytical standards and sampling volume were not so important considering the degree of contribution. Relative combined standard uncertainties associated with the described method was 12.05% for THCCOOH.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.12
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• pp.99-107
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• 1998

A stereo vision system such as the structure of human's eyes has two cameras at separated positions from which we can obtain two input images and then put them together to create 3-D image. It can show more virtual effect than the conventional 2-D image system. But, the stereo image system has to control the convergence angle so that the stereo disparity could always be zero because observers can be fatigued and unconscious of stereo image in conditions that the stereo disparity is not zero for a long work. Therefore, in the paper, optical JTC system which can process adaptive tracking of a specific moving object is proposed as a new approach to keep the stereo disparity to be zero. In this method, optical JTC system obtains the values of the relative locations of a moving objects in left and right images and then these values are used for maintaining the stereo disparity to be zero. Through some optical experiments the proposed stereo vision system is proved to be insensitive to background noises and operate in real-time.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.153-158
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• 2013

Target learning model is not recognized in this category or not classified clearly failed to determine if the vocabulary recognition is reduced. Form of classification learning model is changed or a new learning model is added to the recognition decision tree structure of the model should be changed to a structural problem. In order to solve these problems, a decision tree learning model for classification learning algorithm is proposed. Phonological phenomenon reflected sound enough to configure the database to ensure learning a decision tree learning model for classifying method was used. In this study, the indoor environment-dependent recognition and vocabulary words for the experimental results independent recognition vocabulary of the indoor environment-dependent recognition performance of 98.3% in the experiment showed, vocabulary independent recognition performance of 98.4% in the experiment shown.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.29-38
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• 2015

The coastline influenced naturally and artificially changes dynamically. While the long-term change is influenced by the rise in the surface of the sea and the changes in water level of the rivers, the short-term change is influenced by the tide, earthquake and storm. Also, man-made thoughtless development such as construction of embankment and reclaimed land not considering erosion and deformation of coast has been causes for breaking functions of coast and damages on natural environment. In order to manage coastal environment and resources effectively, In this study is intended to analyze and predict erosion in coastal environment and changes in sedimentation quantitatively by detecting changes in coastal line from data collection for satellite images and aerial LiDAR data. The coastal line in 2007 and 2012 was extracted by manufacturing Digital Surface Model (DSM) with Aviation LiDAR materials. For the coastal line in 2009 and 2010, Normalized Difference Vegetation Index (NDVI) method was used to extract the KOMPSAT-2 image selected after considering tide level and wave height. The change rate of the coastal line is varied in line with the forms of the observation target but most of topography shows a tendency of being eroded as time goes by. Compared to the relatively monotonous beach of Taean, the gravel and rock has very complex form. Therefore, there are more errors in extraction of coastlines and the combination of transect and shoreline, which affect overall changes. Thus, we think the correction of the anomalies caused by these properties is required in the future research.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.761-766
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• 2011

A hedge is a linguistic device to express uncertainties. Hedges are used in a sentence when the writer is uncertain or has doubt about the contents of the sentence. Due to this uncertainty, sentences with hedges are considered to be non-factual. There are many applications which need to determine whether a sentence is factual or not. Detecting hedges has the advantage in information retrieval, and information extraction, and QnA systems, which make use of non-hedge sentences as target to get more accurate results. In this paper, we constructed Korean hedge corpus, and extracted generalized hedge cue-word patterns from the corpus, and then used them in detecting hedges. In our experiments, we achieved 78.6% in F1-measure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.224-229
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• 1999

In the field of speech recognition, the research area can be classified into the following two categories: one which is concerned with the development of phoneme-level recognition system, the other with the efficiency of word-level recognition system. The resonable phoneme-level recognition system should detect the phonemic boundaries appropriately and have the improved recognition abilities all the more. The traditional LPC methods detect the phoneme boundaries using Itakura-Saito method which measures the distance between LPC of the standard phoneme data and that of the target speech frame. The MFCC methods which treat spectral transitions as the phonemic boundaries show the lack of adaptability. In this paper, we present new speech recognition system which uses auto-correlation method in the phonemic boundary detection process and the multi-layered Feed-Forward neural network in the recognition process respectively. The proposed system outperforms the traditional methods in the sense of adaptability and another advantage of the proposed system is that feature-extraction part is independent of the recognition process. The results show that frame-unit phonemic recognition system should be possibly implemented.

• Smart Media Journal
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• v.5 no.1
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• pp.38-43
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• 2016

As smart environment is spread out in our living environments, the needs of an approach related to Human Computer Interaction(HCI) is increases. One of them is head pose estimation. it related to gaze direction estimation, since head has a close relationship to eyes by the body structure. It's a key factor in identifying person's intention or the target of interest, hence it is an essential research in HCI. In this paper, we propose an approach for head pose estimation with pre-defined several directions by random forest classifier. We use canny edge detector to extract feature of the different facial image which is obtained between input image and averaged frontal facial image for extraction of rotation information of input image. From that, we obtain the binary edge image, and make two accumulated histograms which are obtained by counting the number of pixel which has non-zero value along each of the axes. This two accumulated histograms are used to feature of the facial image. We use CAS-PEAL-R1 Dataset for training and testing to random forest classifier, and obtained 80.6% accuracy.