• International Journal of Fluid Machinery and Systems
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• v.8 no.4
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• pp.264-273
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• 2015

This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and two Francis model test turbines all at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that two to three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.79-85
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• 2017

It is critical that passengers should be given timely and correct escape or evacuation guidance from captain and crews when there are hazardous situations in a ship. Otherwise the consequences could be disastrous as "SEWOL Ferry" the South Korean passenger ship which sank in southern coastal area on 16th April 2014. Due to the captain's delayed evacuation decision and lack of sufficient number of crews to guide passengers' evacuation, the accident recorded many casualties, most of whom were high school students (302 passengers sank down with the ship while 172 rescued). Building a passenger ship with well-designed physical escape routes is one thing and guiding passengers to those escape routes in real disaster situation is another. Passengers get panic and move to a wrong direction, bottleneck makes situation worse, and even crews get panic also - passive static escape route signage and small number of trained crews might not be enough to take care of them. SESS (Smart Escape Support System) is being developed sponsored by South Korea Ministry of Ocean and Fisheries starting from 2016 with 4 years of roadmap. SESS comprises multiple active dynamic signage devices which communicate with real-time escape routing server software via LoRa (Long Range) proprietary wireless network.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.69-81
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• 2014

While much in the field of public management has emphasized the importance of nonprofit advocacy activities in policy and decision-making procedures, few have considered the relevance and impact of leading actors on structuring diverse patterns of information sharing and communication through social media. Building nonprofit advocacy is a complicated process for a single organization to undertake, but social media applications such as Facebook and Twitter have facilitated nonprofit organizations and stakeholders to effectively share information and communicate with each other for identifying their mission as it relates to environmental issues. By analyzing the Australian Marine Conservation Society's (AMCS) Twitter network data from the period 1 April to 20 April, 2013, this research discovered diverse patterns in nonprofit advocacy by leading actors in building advocacy. Based on the webometrics approach, analysis results show that nonprofit advocacy through social media is structured by dynamic information flows and intercommunications among participants and followers of the AMCS. Also, the findings indicate that the news media and international and domestic nonprofit organizations have a leading role in building nonprofit advocacy by clustering with their followers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.11-13
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• 2013

무선 센서 네트워크는 개방된 환경에서 무작위로 배치되어 악의적인 공격자들에게 쉽게 노출된다. 센서 노드는 한정된 에너지 자원과 손쉽게 훼손된다는 단점을 통해 허위 보고서와 투표 삽입 공격이 발생한다. Li와 Wu는 두 공격을 대응하기 위해 확률적 투표기반 여과기법을 제안하였다. 확률적 투표기반 여과기법은 고정적인 검증 경로를 결정하기 때문에 특정 노드의 에너지 자원고갈 위험이 있다. 본 논문에서는 센서 네트워크에서 보고서 여과 확률 향상을 위하여 퍼지 시스템을 기반으로 다음 노드 선택을 약 6% 효율적인 경로 선택 방법을 제안한다. 제안 기법은 전달 경로 상의 노드 중 상태정보가 높은 노드를 검증 노드로 선택하고, 선택된 검증 노드는 허용 범위 경계 값을 기준으로 공격 유형을 판별하고 여과한다. 실험결과를 통해 제안기법은 기존기법과 비교하였을 때 에너지 효율이 향상되었다.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.124-129
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• 1992

The goal of the proposed Intelligent Assisting System - IAS is to assist human operators in an intelligent way, while leaving decision and goal planning instances for the human. To realize the IAS the very important issue of manipulation skill identification and analysis has to be solved, which then is stored in a Skill Data Base. Using this data base the IAS is able to perform complex manipulations on the motion control level and to assist the human operator flexibly. We propose a model for manipulation skill based on the dynamics of the grip transformation matrix, which describes the dynamic transformation between object space and finger joint space. Interaction with a virtual world simulator allows the calculation and feedback of appropriate forces through controlled actuators of the sensor glove with 10 degrees-of-freedom. To solve the sensor glove calibration problem, we learn the nonlinear calibration mapping by an artificial neural network(ANN). In this paper we also describe the experimental system setup of the skill acquisition and transfer system as a first approach to the IAS. Some simple manipulation examples and simulation results show the feasibility of the proposed manipulation skill model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.123-145
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• 2017

Due to the increasing demand for spectrum resources, cognitive radio networks and dynamic spectrum access draw a lot of research into efficiently utilizing limited spectrum resources. To set up cluster-based CR ad-hoc common channels, conventional methods require a relatively long time to successfully exchange the initialization messages. In this paper, we propose a fast and reliable common channel initialization protocol for CR ad-hoc networks. In the proposed method, the cluster head sequentially broadcasts a system activation signal through its available channels with a predetermined correlation pattern. To detect the cluster head's broadcasting channels and to join the cluster, each member node implements fast Fourier transform (FFT) and computes autocorrelation of an FFT bin sequence for each available channel of the member node. This is compared to the predetermined reference pattern. The join request and channel decision procedures are also presented in this paper. In a simulation study, the performance of the proposed method is evaluated.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.372-381
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• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.313-316
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• 2002

이동 물체의 이동 거리 추적이나 대상 물체의 인식과 판별 물체의 특징 추출과 같은 응용분야에서 컴퓨터(Computer)와 비젼시스템(vision system)을 이용한 영상 데이터 처리 분야에 대한 이용률이 증가하면서, 그에 따른 연구가 활발히 진행되고 있다. 따라서 CCD 카메라(Charge-Couple Device Camera)로부터 입력된 그레이 레벨(Gray Level)의 영상을 입력받아 처리과정을 거쳐 위치정보를 전송하는 과정에서 정확한 정보를 얻기 위한 전처리 과정 방법을 제안하고, 실제 시스템에 적용한 결과를 제시한다. 여기서 영상의 전처리 과정 중 입력 영상에서 불필요한 부분을 제거하거나, 배경과 대상물의 분리, 내포된 잡음을 없애기 위하여 흔히 이진화 방법을 많이 사용한다 특히 이진화 과정에서 그레이 레벨의 입력영상에서 히스토그램(histogram) 정보를 이용하여 영상의 이진화시의 임계값을 찾는 것은 아주 중요한 요인이다 따라서 본 논문에서는 신경회로망을 이용하여 실시간으로 CCD 카메라를 통하여 입력되는 그레이 레벨의 입력 영상에 대하여 동적으로 적당한 임계값을 .찾는 방법을 제안하고자한다. 또한 제안한 신경회로망을 이용한 임계값 추출 알고리즘(algorithms)을 구현한 시스템(system)에 적용하여 일반적인 방법과 비교 검토하고 응용 가능성을 확인한다.

• Journal of Communications and Networks
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• v.11 no.3
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• pp.297-305
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• 2009

Multiprotocol label switching (MPLS) networks require dynamic flow admission control to guarantee end-to-end quality of service (QoS) for each Internet protocol (IP) traffic flow. In this paper, we propose to tackle the joint routing and admission control problem for the IP traffic flows in MPLS networks without rerouting already admitted flows. We propose two mathematical programming models for this problem. The first model includes end-to-end delay constraints and the second one, end-to-end packet loss constraints. These end-to-end QoS constraints are imposed not only for the new traffic flow, but also for all already admitted flows in the network. The objective function of both models is to minimize the end-to-end delay for the new flow. Numerical results show that considering end-to-end delay (or packet loss) constraints for all flows has a small impact on the flow blocking rate. Moreover, we reduces significantly the mean end-to-end delay (or the mean packet loss rate) and the proposed approach is able to make its decision within 250 msec.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.80-88
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• 2017

Although hazard identification is one of the most important steps of safety management process, numerous hazards remain unidentified in the construction workplace due to the dynamic environment of the construction site and the lack of available resource for visual inspection. To this end, our previous study proposed the collective sensing approach for safety hazard identification and showed the feasibility of identifying hazards by capturing collective abnormalities in workers' walking patterns. However, workers generally performed different activities during the construction task in the workplace. Thereby, an additional process that can identify the worker's walking activity is necessary to utilize the proposed hazard identification approach in real world settings. In this context, this study investigated the feasibility of identifying walking activities during construction task using Wearable Inertial Measurement Units (WIMU) attached to the worker's ankle. This study simulated the indoor masonry work for data collection and investigated the classification performance with three different machine learning algorithms (i.e., Decision Tree, Neural Network, and Support Vector Machine). The analysis results showed the feasibility of identifying worker's activities including walking activity using an ankle-attached WIMU. Moreover, the finding of this study will help to enhance the performance of activity recognition and hazard identification in construction.