• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.19 no.3
• /
• pp.103-119
• /
• 2016

This study aims to assess habitat feature on the large-scale spawning ground of the Boreal Digging Frog Kaloula borealis in Daemyung retarding basin of Daegu, and to analyze the relationships between species abundance and meteorological factors for each habitat. Fifty-seven(57) pitfalls were installed to collect species abundance of 4 survey regions, and high-resolution satellite image, soil sampling equipment, digital topographic map, and GPS were used to develop habitat features such as terrain, soil, vegetation, human disturbance. The analysis shows that the frog is most abundant in sloped region with densely herbaceous cover in southern part of the retarding basin. In the breeding season, lowland regions, where Phragmites communis and P. japonica dominant wetlands and temporary ponds distributed, are heavily concentrated by the species for spawning and foraging. Located in between legally protected Dalsung wetands and lowland regions of the retarding basin, riverine natural levee is ecologically important area as core habitat for Kaloula borealis, and high number of individuals were detected both breeding and non-breeding seasons. Temperate- and pressure-related meteorological elements are selected as statistically significant variables in species abundance of non-breeding season in lowland and highland regions. However, in sloped regions, only a few variables are statistically significant during non-breeding season. Moreover, breeding activities in sloped regions are statistically significant with minimum temperature, grass minimum temperature, dew point temperature, and vapor pressure. Significant meteorological factors with habitat features are effectively applied to establish species conservation strategy of the retarding basin and to construct for avoiding massive road-kills on neighboring roads of the study sites, particularly post-breeding movements from spawning to burrowing areas.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.8
• /
• pp.349-356
• /
• 2013

As various features of the smartphone have been used, a lot of information have been stored in the smartphone, including the user's personal information. However, a frequent update of the operating system and applications may cause a loss of data and a risk of missing important personal data. Thus, the importance of data backup is significantly increasing. Many users employ the backup feature to store their data securely. However, in the point of forensic view these backup files are considered as important objects for investigation when issued hiding of smartphone or intentional deletion on data of smartphone. Therefore, in this paper we propose a scheme that analyze structure and restore data for Kies backup files of Samsung smartphone which has the highest share of the smartphone in the world. As the experimental results, the suggested scheme shows that the various types of files are analyzed and extracted from those backup files compared to other tools.

• Korean Journal of Geomatics
• /
• v.2 no.1
• /
• pp.47-55
• /
• 2002

Remote sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation./sup 1)/ EOC (Electro -Optical Camera) sensor loaded on the KOMPSAT-1 (Korea Multi- Purpose Satellite-1) performs the earth remote sensing operation. EOC can get high-resolution images of ground distance 6.6m during photographing; it is possible to get a tilt image by tilting satellite body up to 45 degrees at maximum. Accordingly, the device developed in this study enables to obtain images by photographing one pair of tilt image for the same point from two different planes. KOMPSAT-1 aims to obtain a Korean map with a scale of 1:25,000 with high resolution. The KOMPSAT-1 developed automated feature extraction system based on stereo satellite image. It overcomes the limitations of sensor and difficulties associated with preprocessing quite effectively. In case of using 6, 7 and 9 ground control points, which are evenly spread in image, with 95% of reliability for horizontal and vertical position, 3-dimensional positioning was available with accuracy of 6.0752m and 9.8274m. Therefore, less than l0m of design accuracy in KOMPSAT-1 was achieved. Also the ground position error of ortho-image, with reliability of 95%, is 17.568m. And elevation error showing 36.82m was enhanced. The reason why elevation accuracy was not good compared with the positioning accuracy used stereo image was analyzed as a problem of image matching system. Ortho-image system is advantageous if accurate altitude and production of digital elevation model are desired. The Korean map drawn on a scale of 1: 25,000 by using the new technique of KOMPSAT-1 EOC image adopted in the present study produces accurate result compared to existing mapping techniques involving high costs with less efficiency.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.1
• /
• pp.127-137
• /
• 2019

The growth in smartphone service has given rise to an increase in frequency and importance of authentication. Existing smartphone authentication mechanisms such as passwords, pattern lock and fingerprint recognition require a high level of awareness and authenticate users temporarily with a point-of-entry techniques. To overcome these disadvantages, there have been active researches in behavior-based authentication. However, previous studies focused on enhancing the accuracy of the authentication. Since authentication is directly used by people, it is necessary to reflect actual users' perception. This paper proposes user perception on behavior-based authentication with feature analysis. We conduct user survey to empirically understand user perception regarding behavioral authentication with selected authentication features. Then, we analyze acceptance of the behavioral authentication to provide continuous authentication with minimal awareness while using the device.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.3917-3941
• /
• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• Korean Journal of Applied Biomechanics
• /
• v.29 no.3
• /
• pp.129-135
• /
• 2019

Objective: The purpose of this study is to present the scientific and quantitative data by finding the common points and differences of the side-kick according to the height change through the difference of the side kick motion performance according to the three target height changes and the function of the lower limbs muscle in side kick motion of Taekwondo Poomsae. Method: For this, total 14 players were selected who were registered in Korea Taekwondo Association and skilled group 7 players who had a medal from national competition and 7 players who did not have Taekwondo experience from department of physics. 4 video cameras to the feature on side kick per target height, and the subjects' support foot was located on the ground reactor and the practice was conducted 3 times: waist, chest, and head as the target height. the basic materials were collected by using Kwon 3D XP program and the T-test was conducted to verify the statistic difference between groups (SPSS 24.0). At this time, the statistics significance level was set as .05 and the following conclusion was obtained. Results: The lower the proficiency and the higher the height, the more the joint coordination between the hip and the knee. Conclusion: Summary of the result shows a common point that the change of target's height makes the lower the proficiency and the higher the height, the more the joint coordination between the hip and the knee. Also, the higher the target's height became, the greater angular momentum of thighs, shanks, foot became in common.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.2
• /
• pp.62-69
• /
• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• SUVANNABHUMI
• /
• v.8 no.1
• /
• pp.121-146
• /
• 2016

Defining key characteristics of Southeast Asia requires historical interpretation. Southeast Asia is a diverse and complicated region, but some of modern history's "grand narratives" serve to unify its historical experience. At a minimum, the modern history of the region involves decisive encounters with universal religions, the rise of Western colonialism, the experience of world wars, decolonization, and the end of the "cycle of violence". The ability of the region's peoples to adapt to these many challenges and successfully build new nations is a defining feature of Southeast Asia's place in the global stage. This paper will begin with a question: is it possible to develop a hermeneutic of "expedience" as a way to interpret the region's history? That is, rather than regard the region from a purely Western, nationalist, "internalist" point of view, it would be useful to identify a new series of interpretative contexts from which to begin scholarly analysis. In order to contextualize this discussion, the paper will draw upon the writings of figures who explored the region before knowledge about it was shaped by purely colonist or nationalist enterprises. To this end, particular attention will be devoted to exploring some of John Furnivall's ways of conceptualizing Southeast Asia. Investigating Furnivall, a critic of colonialism, will be done in relation to his historical situation. Because Furnivall's ideas have played a pivotal role in the interpretation of Southeast Asia, the paper will highlight the intellectual history of the region in order to ascertain the value of these concepts for subsequent historical interpretation. Ultimately, the task of interpreting the region's history requires a framework which will move beyond the essentializing orientalist categories produced by colonial scholarship and the reactionary nation-building narratives which followed. Instead, by beginning with a mode of historical interpretation that focuses on the many realities of expedience which have been necessary for the region's peoples, it may be possible to write a history which highlights the extraordinarily adaptive quality of Southeast Asia's populations, cultures, and nations. To tell this story, which would at once highlight key characteristics of the region while showing how they developed through historical encounters, would go a long way to capturing Southeast Asia's contribution's to global development.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.947-960
• /
• 2023

In Korea, traditional paper promissory notes are currently undergoing a transformation, being gradually replaced by electronic notes. This transformation is being steered under the Korea Financial Telecommunications Institute, a trusted authority. However, existing electronic systems have security vulnerabilities, including the risk of hacking and internal errors within the institute. To this end, we have defined a novel anonymous electronic promissory note system based on blockchain. We have constructed a concrete protocol and conducted security analysis of our protocol. Note that, in our protocol, every note information is committed so that the note remains undisclosed until the point of payment. Once the note information becomes public on the blockchain, it enables the detection of illicit activities, such as money laundering and tax evasion. Furthermore, our protocol incorporates a feature of split endorsement, which is a crucial functionality permitted by the Korean electronic note system. Consequently, our proposed protocol is suitable for practical applications in financial transactions.

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