• The Mathematical Education
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• v.62 no.4
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• pp.457-471
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• 2023

Measurement is an imperative content area of early elementary mathematics, but it is reported that students' understanding of units in measurement situations is insufficient despite its importance. Therefore, this study examined lower-grade elementary students' quantitative reasoning of units in length measurement by identifying the levels of reasoning of units. For this purpose, we collected and analyzed the responses of second-grade elementary school students who engaged in a set of length measurement tasks using an open number line in terms of unitizing, iterating, and partitioning. As a result of the study, we categorized students' quantitative reasoning of unit levels into four levels: Iterating unit one, Iterating a given unit, Relating units, and Transforming units. The most prevalent level was Relating units, which is the level of recognizing relationships between units to measure length. Each level was illustrated with distinct features and examples of unit reasoning. Based on the results of this study, a personalized plan to the level of unit reasoning of students is required, and the need for additional guidance or the use of customized interventions for students with incomplete unit reasoning skills is necessary.

• The Journal of the Acoustical Society of Korea
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• v.29 no.5
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• pp.325-331
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• 2010

Categorical perception has been noted as characteristic properties of linguistic stimuli. In this study, Korean monosyllabic minimal pairs (consonant-vowel-consonant, CVC) were analyzed to understand perception boundaries between clinically confusing words. An efficient scheme has been developed to systematically synthesize temporal transition waveforms (11 steps) from one word to the target word for the pairs of /gom/-/gong/, /non/-/noon/, and /don/-/non/. The corresponding slopes, widths, and non-dominant factors of perception boundaries were analyzed for the total of 40 young normal subjects (20 males and 20 females). Results showed that there were relative pattern differences among confusing monosyllabic minimal pairs under categorical perception. For instance, the vowel difference within CVC pairs led to the lowest boundary performance in this experiment set. Data also indicated the potential application of the overall procedure for evaluating auditory functions and assisting rehabilitation programs.

• The Korean Journal of Pharmacology
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• v.30 no.1
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• pp.67-73
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• 1994

Na-Ca exchange transports calcium ion either into (reverse mode Na-Ca exchange) or out of the cell (forward mode Na-Ca exchange) according to the direction of driving force produced by the changes in ratio of intra- and extra-cellular Na concentrations. Thus, Na-Ca exchange is regarded as the regulator of myocardial contraction. However, the existence of reverse mode Na-Ca exchange and its role in myocardial contraction is still questioned. Present study was performed to identify the presence of reverse mode Na-Ca exchange and its possible involvement in the regulation of myocardial contraction in rat heart. Using the left atria of rat, contraction was induced by electrical field stimulation (EFS, 0.5 msec duration and supramaximal voltage). Changing of the stimulation frequencies from resting 4 Hz to 0.4, 1 or 8 Hz caused typical negative staircase effect in twitch tension, but $^{45}Ca$ uptake showed bimodal increase. When the stimulation frequency was abruptly changed from 4 Hz to 0.4 Hz the atrial twitch tension showed three phased-enhancement, that is, the initial rapid increase (the first phase) followed by rapid decrease (the second phase) and stabilization (the third phase). $^{45}Ca$ uptake was equivalent to tension, i.e. initial significant increase in first 30 second and then decrease. Benzamil treatment abolished the first phase of increase in a dose dependent manner from $10^{-5}\;to\;3{\times}10^{-4}M.$ Bay k 8644 $(3{\times}10^{-5}M)$ treatment enhanced the inotropy induced by frequency reduction and abolished the second and third phase decreases. Benzamil treatment also suppressed the contraction stimulated by Bay K 8644. Although the contraction at 4 Hz stimulation was completely abolished by verapamil $3{\times}10^{-5}\;M$ pretreatment, the contraction reappeared as soon as the stimulation frequency was changed into 0.4 or 1 Hz and interstingly,$^{45}Ca$ uptake were significantly higher than no treatment. From these results, it is concluded that reduction of stimulation frequency causes calcium influx by the reverse mode Na-Ca exchange, resulting in initial rapid increase of twitch tension. then it turns into forward mode exchange to efflux the calcium, resulting in decrease of the twitch tension in left atria of rat.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• Korean Journal of Remote Sensing
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• v.12 no.2
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• pp.139-154
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• 1996

In order to evaluate the sensor`s look direction bias in the Landsat TM image and to estimate trends of primary geological lineaments, we have attempted to systematically compare lineaments in TM image, relief shadowed DEM's, and actual lineaments of geologic and topographic map through the Hough transform technique. Hough transform is known to be very effective to estimate the trend of geological lineaments, and help us to obtain the true trends of lineaments. It is often necessary to compensate the preferential enhancements of terrain lineaments in a TM image occurred by to look direction bias, and that can be achieved by utilizing an auxiliary data. In this study, we have successfully adopted the relief shadowed DEM in which the illuminating azimuth angle is perpendicular to look direction of a TM image for assessing true trends of geological lineaments. The results also show that the sum of four relief shadowed DEM's directional components can possibly be used as an alternative. In Euiseong-gun area where Sindong Group and Mayans Group are mainly distributed, geological lineaments trending $N5^{\circ}$~$10^{\circ}$W are dominant, while those of $N55^{\circ}$~$65^{\circ}$ W are major trends in Cheongsong-gun area where Hayang Group, Yucheon Group and Bulguksa Granite are distributed. Using relief shadowed DEM as an auxiliary data, we found the $N55^{\circ}$~$65^{\circ}$ W lineaments which are not cleanly observed in TM image over Euiseong-gun area. Compared with the trend of Gumchon and Gaum strike-slip faults, these lineaments are considered to be an extension of the faults. Therefore these strike-slip faults possibly extend up to Sindong Group in the northwest parts in the study area.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.948-956
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• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.137-145
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• 2016

A novel tracking method is proposed to find coronary artery using high-order curve model in coronary CTA(Computed Tomography Angiography). The proposed method quickly generates numerous artificial trajectories represented by high-order curves, and each trajectory has its own cost. The only high-ranked trajectories, located in the target structure, are selected depending on their costs, and then an optimal curve as the centerline will be found. After tracking, each optimal curve segment is connected, where optimal curve segments share the same point, to a single curve and it is a piecewise smooth curve. We demonstrated the high-order curve is a proper model for classification of coronary artery. The experimental results on public data set sho that the proposed method is comparable at both accuracy and running time to the state-of-the-art methods.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.341-348
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• 2011

ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches' results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.6
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• pp.11-25
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• 2009

A method of instrumentally estimating the seismic intensity (MMI) based on Fourier Acceleration Spectrum, which is the so-called 'FAS MMI method' of Sokolov and Wald (2002), was considered for its applicability to Korea. In order to implement the FAS MMI method, the empirical models of mean (m) and standard deviation (${\sigma}$) for Korea were derived for MMI ${\leq}$ IV according to individual seismic intensity by using the site-consistent horizontal FAS of 580 records from 65 isoseismal maps prepared based on the reported MMI of Korea Meteorological Administration. The site-consistent FAS at a site were obtained by correcting the observed FAS for the difference of the site amplification function relative to that of the target site of Class D station (Yun and Suh, 2007) which was evaluated to be a representative site for the generic soil profile of Korea. The FAS m model for MMI ${\leq}$ IV follows the overall linear relation in log space according to seismic intensities, featuring the FAS mean model for MMI = IV similar to that of the global model of Sokolov and Wald (2002). The ${\sigma}$-values of the FAS model are found to be greater than those of the global model for MMI ${\geq}$ V, while significantly lower than those of the global model for MMI = IV.