• Journal of Digital Convergence
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• v.17 no.8
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• pp.123-130
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• 2019

The advent of the full-fledged Internet of Things era will bring together various types of information through Internet of Things devices, and the vast amount of information collected will be generated as new information by the analysis process. To effectively store this generated information, a flexible and scalable cloud computing system is advantageous. Therefore, the main determinants for effective client system acceptance are viewed as motivator factor (economics, efficiency, etc.) and hindrance factor (transitional costs, security issues, etc.) and the purpose of this study is to determine which detailed factors play a major role in making new system acceptance decisions around harm. The factors required to determine the major priorities are defined as the system acceptance determinants from the technical point of view obtained through the literature review, and the questionnaire is prepared based on the factors derived, and the survey is conducted on the experts concerned. In addition, the AHP analysis aims to achieve a final priority by performing a bifurcation between components for measuring a decision unit. Furthermore, the results of this study will serve as an important basis for making decisions based on acceptance (enabling) of technology.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.47-54
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• 2006

Shear wave velocity of uncemented soil can be expressed as the function of effective stresses when capillary phenomena are negligible. However, the terms of effective stresses are divided into the direction of wave propagation and polarization because stress states are generally anisotropy. The shear wave velocities are affected by ${\alpha}$ parameters and ${\beta}$ exponents that are experimentally determined. The ${\beta}$ exponents are controlled by contact effects of particulate materials (sizes, shapes, and structures of particles) and the ${\alpha}$ parameters are changed by contact behaviors among particles, material properties of particles, and type of packing (i.e., void ratio and coordination number). In this study, consolidation tests are performed by using clay, mica and sand specimens. Shear wave velocities are measured during consolidation tests to investigate the stress-induced and inherent anisotropies by using bender elements. Results show the shear wave velocity depends on the stress-induced anisotropy for round particles. Furthermore, the shear wave velocity is dependent on particle alignment under the constant evvective stress. This study suggests that the shear wave velocity and the shear modulus should be carefully estimated and used for the design and construction of geotechnical structures.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.853-862
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• 2002

Face Detection can be defined as follows : Given a digitalized arbitrary or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition facial expression, head gesture and so on, and is one of important qualify factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidily. For this. face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector sire of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to us more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.147-153
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• 2002

Due to the growth of population and industrial development at the coastal cities, there has been much increase in necessity to effective control of the wastes into the coastal water and river. The amount of disposal at those waters has been increased rapidly and it is necessary for us to track of it in order to keep the water clean. The investigation and research related to the water quality in this region have been conducted continuously but the systematic survey of the disposed wastes at the bottom was neglected and/or minor. In this study we surveyed the status of disposed waste distribution at the bottom coastal water and river from the scanned images. The intensity of sound received by the side scan sonar tow vehicle from the sea floor provides information as to the general distribution and characteristics of the superficial wastes. The port and starboard side scanned images produced from a transducer borne on a tow fish connected by tow cable to a tug boat have the area with width of 22m∼112m, and band of 44m∼224m. All data are displayed in real-time on a high-resolution color display (1280 ${\times}$ 1024 pixels) together with position information by DGPS. From the field measurement and analysis of the recorded images, we could draw the location and distribution of bottom disposals. Furthermore, we made a database system which might be fundamental for planning the waste reception and process control system.

• Journal of radiological science and technology
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• v.33 no.1
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• pp.51-59
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• 2010

We developed an analysis software that automatically detects incoming isotopes for multi-purpose gamma-ray detectors. The software is divided into three major parts; Network Interface Module (NIM), Spectrum Analysis Module (SAM), and Graphic User Interface Module (GUIM). The main part is SAM that extracts peak information of energy spectrum from the collected data through network and identifies the isotopes by comparing the peaks with pre-calibrated libraries. The proposed peak detection algorithm was utilized to construct libraries of standard isotopes with two peaks and to identify the unknown isotope with the constructed libraries. We tested the software by using GammaPro1410 detector developed by NuCare Medical Systems. The results showed that NIM performed 200K counts per seconds and the most isotopes tested were correctly recognized within 1% error range when only a single unknown isotope was used for detection test. The software is expected to be used for radiation monitoring in various applications such as hospitals, power plants, and research facilities etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.863-870
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• 2015

A Compensation Algorithm for The Position of the User Hands based on the Moving Mean-Shift ($CAPUH_{MMS}$) in Human Robot Interface (HRI) System running the Kinect sensor is proposed in order to improve the performance of the gesture recognition is proposed in this paper. The average error improvement ratio of the trajectories ($AEIR_{TJ}$) in left-right movements of hands for the $CAPUH_{MMS}$ is compared with other compensation algorithms such as the Compensation Algorithm based on the Compensation Algorithm based on the Kalman Filter ($CA_{KF}$) and the Compensation Algorithm based on Least-Squares Method ($CA_{LSM}$) by the developed realtime performance simulator. As a result, the $AEIR_{TJ}$ in up-down movements of hands of the $CAPUH_{MMS}$ is measured as 19.35%, it is higher value compared with that of the $CA_{KF}$ and the $CA_{LSM}$ as 13.88% and 16.68%, respectively.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.190-197
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• 2005

본 논문에서는 출입국자 관리의 효율성과 체계적인 출입국 관리를 위하여 여권 코드를 자동으로 인식하고 위조 여권을 판별할 수 있는 여권 인식 및 얼굴 인증 방법을 제안한다. 여권 이미지는 기울어진 상태로 스캔되어 획득되어질 수도 있으므로 기울기 보정은 문자 분할 및 인식, 얼굴 인증에 있어 매우 중요하다. 따라서 본 논문에서는 여권 영상을 스미어링한 후, 추출된 문자열 중에서 가장 긴 문자열을 선택하고 이 문자열의 좌측과 우측 부분의 두께 중심을 연결하는 직선과 수평선과의 기울기를 이용하여 여권 여상에 대한 각도 보정을 수행한다. 여권 코드 추출은 소벨 연산자와 수평 스미어링, 8방향 윤곽선 추적 알고리즘을 적용하여 여권 코드의 문자열 영역을 추출하고, 추출된 여권 코드 문자열 영역에 대해 반복 이지화 방법을 적용하여 코드의 문자열 영역을 이진화한다. 이진화된 문자열 영역에 대해 CDM 마스크를 적용하여 문자열의 코드들을 복원하고 8방향 윤곽선 추적 알고리즘을 적용하여 개별 코드를 추출한다. 추출된 개별 코드는 ART2 알고리즘을 적용하여 인식한다. 얼굴 인증을 위해 템플릿 매칭 알고리즘을 이용하여 얼굴 템플릿 데이터베이스를 구축하고 여권에서 추출된 얼굴 영역과의 유사도 측정을 통하여 여권 얼굴 영역의 위조 여부를 판별한다. 얼굴 인증을 위해서 Hue, YIQ-I, YCbCr-Cb 특징들의 유사도를 종합적으로 분석하여 얼굴 인증에 적용한다. 제안된 여권 인식 및 얼굴 인증 방법의 성능을 평가를 위하여 원본 여권에 얼굴 부분을 위조한 여권과 노이즈, 대비 증가 및 감소, 밝기 증가 및 감소 및 여권 영상을 흐리게 하여 실험한 결과, 제안된 방법이 여권 코드 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.권 영상에서 획득되어진 얼굴 영상의 특징벡터와 데이터베이스에 있는 얼굴 영상의 특징벡터와의 거리 값을 계산하여 사진 위조 여부를 판별한다. 제안된 여권 인식 및 얼굴 인증 방법의 성능을 평가를 위하여 원본 여권에서 얼굴 부분을 위조한 여권과 기울어진 여권 영상을 대상으로 실험한 결과, 제안된 방법이 여권의 코드 인식 및 얼굴 인증에 있어서 우수한 성능이 있음을 확인하였다.진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료 제공 사이트에 대한 메타 자료를 데이터베이스화했으며 이를 통해 학생들이 원하는 실시간 자료를 검색하여 찾을 수 있고 홈페이지를 방분했을 때 이해하기 어려운 그래프나 각 홈페이지가 제공하는 자료들에 대한 처리 방법을 도움말로 제공받을 수 있게 했다. 실

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.114-122
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• 2018

This study presents the emergency assessment method about seismic safety of cable-supported bridges using seismic acceleration sensors installed on the primary structural elements of them. The structural models of bridges are updated iteratively to make their dynamic characteristics to be similar to those of real bridges based on the comparison of their natural frequencies with those of real bridges estimated from acceleration data measured at ordinary times by the seismic acceleration sensor. The displacement at the location of each seismic acceleration sensor is derived by seismic analysis using design earthquake, and the peak value of them is determined as the disaster management criteria in advance. The displacement time history is calculated by the double integration of the acceleration time history which is recorded at each seismic acceleration sensor and filtered by high cut(low pass) and low cut(high pass) filters. Finally, the seismic safety is evaluated by the comparison of the peak value in calculated displacement time history with the disaster management criteria determined in advance. The applicability of proposed methodology is verified by performing the seismic safety assessment of 12 cable-supported bridges using the acceleration data recorded during Gyeongju earthquake.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.16-23
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• 2019

Fine particulate matter known as PM 2.5 refers to the atmospheric particulate matter that has a diameter less than 2.5 micrometer identified as dangerous element for human health and its concentration can provide us a clear picture about air dust concentration. Humans stay indoor almost 90% of their life time and also there is no official indoor dust concentration data, so our study is focused on measuring the indoor air quality. Indoor dust data monitoring is very important in hospital environments beside that other places can also be considered for monitoring like classrooms, cements factories, computer server rooms, petrochemical storage etc. In this paper, visible light communication system is proposed by Manchester encoding technique for electromagnetic interference (EMI)-free indoor dust monitoring. Important indoor environment information like dust concentration is transferred by visible light channel in wide range. An average voltage-tracking technique is utilized for robust light detection to eliminate ambient light and low-frequency noise. The incoming light is recognized by a photo diode and are simultaneously processed by a receiver micro-controller. We can monitor indoor air quality in real-time and can take necessary action according to the result.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.