• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.1
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• pp.29-38
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• 2010

It is highly requested that the more complicated embedded software is used for high performance and multiple functions of the systems. This is inevitably increasing the errors. Therefore the embedded software testing is getting important recently. There are not general testing methods which are able to be applied for any embedded systems, but via this research, we introduce a testing method which is based on TTCN-3, a testing standard, for embedded systems. A testing environment for network-based embedded software is implemented with considering the features of TTCN-3 testing which is based on message exchange. The testing environment has two additional parts with TTCN-3 test system, the network analyzer to access the network-based systems and the communication interface which is suggested for embedded systems in previous work, and we have implemented the whole testing environment with interacting these two parts. In addition to the normal testing domain, called single node testing as a unit testing of V-model, we suggest another concept to test multiple nodes in network. It could be achieved by adding keywords such as supervisor and object which are describing the feature of TTCN-3 testing component and generating the TTCN-3 Executable code which contains new keywords. The testing has done for embedded software which is based on CAN network and the demonstration of the testing environment has been shown in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.275-284
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• 2008

In this paper we design and implement a management framework base on JMX to control and manage ubiquitous home networks. To do this, we organize the ubiquitous home network test-bed that consists of information electronics and sensor devices. In the test-bed network, we implement the management framework which can control and manage various applications and devices in home network environment. In addition, it can also define and add new services easily. Moreover, it is possible to provide various management interfaces with multi-protocols. The framework is formed to integrate legacy management systems readily.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1796-1803
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• 2015

Unlike commercial LTE network, LTE-R railway network is arranged along a railroad track and the base stations of the network (RUs) are also installed on the waysides. For urban railway systems that are composed of underground tunnels, the leakage coaxial cables are widely used due to the radio propagation characteristics in tunnels. In theory, the tunnel sections are interpreted as the waveguide with blank spaces and for this reason, the tunnel sections are expected to be better than open ground sections in terms of the radio propagation characteristics. In this paper, we analyze the radio propagation characteristics based on this theory by replacing the leakage coaxial cables in the network with Yagi antennas. The test has been carried out in the 2.2km tunnel in the Daebul test track of KORAIL with 2.6GHz LTE-R Network. The LTE-R applicability in urban railways has been tested through the analysis on the radio propagation characteristics with the unmanned train operation system in Daebul tunnel.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.67-73
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• 2021

The need for precise location data is growing across numerous markets, and so is the number of affordable high-precision GPS receivers. In this paper, we validated the performance of RTAP2U, a low-cost high-precision RTK receiver that was recently released. Two positioning modes were tested: static and driving. The static test conducted Zero-Baseline Single-RTK and Network-RTK survey for 57 hours and 51 hours, respectively. For the driving test, Network-RTK survey was conducted using VRS services provided by NGII based on Trimble PIVOT and Geo++ GNSMART. The static test showed about 1 cm horizontal and vertical accuracies, which is very stable considering the test duration longer than 50 hours. The integer ambiguity FIX rate marked a solid 100%. The driving test result also reached a 100% FIX rate. Horizontal and vertical accuracies were better than 2 cm and 3 cm, respectively. Researchers can refer to this paper when considering affordable high-precision GPS receivers as an option.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.12
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• pp.1-9
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• 1993

In this paper, to realize the network management function in automated manufacturing network Mini-MAP, the network management requirements are analyzed and the network management system is implemented on the basis of this analysis. The implemented management system which has both local management and remote management mechanism is considered as a single domain on the Mini-MAP network. Here, the remote management functions consist of network status, monitoring and remote operations and the local management functions have parameter display and network self testing. The MAP network controller is designed according to the MAP version 3.0 specifications and IEEE 802 standards. the operations of network management system are certified througth the test environments which consists of the implemented network adaptor and softwares for Mini-MAP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.737-745
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• 2008

Recent developments of process and measurement technology bring much interest to the online monitoring of process operations such as milling, grinding, broaching, etc. The objective of online monitoring systems is to detect process changes as early as possible. This is helpful in protecting facilities against unexpected failures and then preventing unnecessary loss. This paper investigates, when the process monitoring data are obtained as a profile, the monitoring performances of a statistical $T^2$-statistic and a feedforward neural network by using a wavelet transform. Numerical experiments using cutting force data presented by Axinte show that the proposed wavelet based $T^2$-test has an acceptable power in detecting profile changes. However, its operating characteristic is very sensitive to autocorrelation. On the contrary, compared with $T^2$-test, the neural network has more stable performance in the presence of autocorrelation. This indicates that an adaptive feature to analyze noises should be incorporated into the wavelet based $T^2$-test.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.175-183
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• 2022

The collision between a ship and bridge across a waterway may result in extremely serious consequences that may endanger the safety of life and property. Therefore, factors affecting ship bridge collision must be investigated, and the impact force should be discussed based on various collision conditions. In this study, a finite element model of ship bridge collision is established, and the peak impact force of a ship bridge collision based on 50 operating conditions combined with three input parameters, i.e., ship loading condition, ship speed, and ship bridge collision angle, is calculated via numerical simulation. Using neural network models trained with the numerical simulation results, the prediction model of the peak impact force of ship bridge collision involving an extremely short calculation time on the order of milliseconds is established. The neural network models used in this study are the basic backpropagation neural network model and Elman neural network model, which can manage temporal information. The accuracy of the neural network models is verified using 10 test samples based on the operating conditions. Results of a verification test show that the Elman neural network model performs better than the backpropagation neural network model, with a mean relative error of 4.566% and relative errors of less than 5% in 8 among 10 test cases. The trained neural network can yield a reliable ship bridge collision force instantaneously only when the required parameters are specified and a nonlinear finite element solution process is not required. The proposed model can be used to predict whether a catastrophic collision will occur during ship navigation, and thus hence the safety of crew operating the ship.

• The Korean Journal of Community Living Science
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• v.25 no.4
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• pp.511-531
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• 2014

This study explores supportive and conflictual network structures of elderly single and couple households and analyzes the effects of supportive and conflictual networks on suicidal thoughts by gender and family type. The analysis considered a sample of 522 individuals over the age of 60 who did not live with their adult children. The statistical methods used to analyze data were descriptive statistics, a t-test, a chi-square test and a regression analysis using SPSS WIN 20.0. The results are as follows. First, men and elderly single households had support networks that were smaller than those of women and elderly couple households. The conflictual network of elderly couples households was larger than that of elderly single households. In addition, the larger the network, the more the conflictual was. Second, elderly single households thought about suicide more often than elderly couple households. Third, economic status, the number of adult children, the size of conflictual network and subjective health had considerable influence on suicidal thoughts of elderly single and couple households. The size of the conflictual network had a greater effect on suicidal thoughts of elderly individuals than that of the supportive network. These results have important policy implications for elderly single and couple households.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1384-1386
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• 2005

This paper focuses on development of load test simulator of a steam turbine-generator in a nuclear power plant. When load is taken off from electrical power network, it is very difficult to effectively control the steam flow to turbine of the nuclear turbine-generator, because of disturbances, such as electrical load and network unbalance on electrical network. Up to the present time, the conventional control system has been used for the load control on nuclear steam generator, owing to the easy control algorithms and the advantage which have been proven on the nuclear power plant. However, since there are problems with stability control during low power and start-up, only a highly experienced operator can operate during those procedures. Also, a great deal of time and an expensive simulator is needed for the training of an operator. The KEPRI is developed simulator for 600MW nuclear power plant to take a test of generator load rejection, throttle valve, and turbine load control. Total load test is implemented before start up.