• Structural Engineering and Mechanics
• /
• v.43 no.2
• /
• pp.163-177
• /
• 2012

This paper presents a LMI(linear matrix inequality)-based fuzzy approach of modeling and active vibration control of geometrically nonlinear flexible plates with piezoelectric materials as actuators and sensors. The large-amplitude vibration characteristics and dynamic partial differential equation of a piezoelectric flexible rectangular thin plate structure are obtained by using generalized Fourier series and numerical integral. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the nonlinear structural system, which combines the fuzzy inference rule with the local linear state space model. A robust fuzzy dynamic output feedback control law based on the T-S fuzzy model is designed by the parallel distributed compensation (PDC) technique, and stability analysis and disturbance rejection problems are guaranteed by LMI method. The simulation result shows that the fuzzy dynamic output feedback controller based on a two-rule T-S fuzzy model performs well, and the vibration of plate structure with geometrical nonlinearity is suppressed, which is less complex in computation and can be practically implemented.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.1
• /
• pp.94-101
• /
• 1992

The multilayer perceptron, trained by the error back-propagation learning rule, has been known as a mapping network which can represent arbitrary functions. However depending on the complexity of a function and the initial weights of the multilayer perceptron, the error back-propagation learning may fall into a local minimum or a flat area which may require a long learning time or lead to unsuccessful learning. To solve such difficulties in training the multilayer perceptron by standard error back-propagation learning rule, the paper proposes a learning method which progressively enlarges the learning domain from a small area to the entire region. The proposed method is devised from the investigation on the roles of hidden nodes and connection weights in the multilayer perceptron which approximates a function of one variable. The validity of the proposed method was illustrated through simulations for a function of one variable and a function of two variable with many extremal points.

• Journal of the Korean Society for Railway
• /
• v.16 no.4
• /
• pp.348-351
• /
• 2013

The aim of this research is to analyze and periodize the relationship between railroad and river transportation as one aspect of the transformation of the land transportation system in Korea. As a result, three phases can be observed: a first phase of equality and interdependence (1910s); a second phase, subordinating rivers to feeder lines under railroad's dominance; and a third phase when trucks and buses became a major means for local transportation in place of traditional shipping routes. River ports were among the main planned destinations during the first and second phases, but such plans were changed or withdrawn after the third phase. This relationship between river and rail illustrates one geopolitical factor relating to the development of Korea's rail transportation network.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1087-1089
• /
• 2003

The aim of this study is to evaluate the Pi-SAR data for land cover discrimination using a standard method. For this purpose, the original polarization and Pauli components of the Pi-SAR X-band and L-band data are used and the results are compared. As a method for the land cover discrimination, the traditional method of statistical maximum likelihood decision rule is selected. To increase the accuracy of the classification result, different spatial thresholds based on local knowledge are determined and used for the actual classification process. Moreover, to reduce the speckle noise and increase the spatial homogeneity of different classes of objects, a speckle suppression filter is applied to the original Pi-SAR data before applying the classification decision rule. Overall, the research indicated that the original Pi-SAR polarization components can be successfully used for separation of different land cover types without taking taking special polarization transformations.

• Journal of Korea Port Economic Association
• /
• v.18 no.2
• /
• pp.135-151
• /
• 2002

This study focuses on analysing the period of carrier's responsibility. The Hague Rules apply only while the cargo is in carriage. This period of carrier's responsibility begins when the ship' tackle is hooked on the goods for loading and continues until they are unhooked from the lifting gear after discharge. The Hague Rules are consequently said to apply from tackle to tackle. Also The Hamburg Rules lays down the basic principle that the carrier will be responsible for the goods during the time he is in charge of them at the port of loading, during the carriage and at the port of discharge. These period of carrier's responsibility should be determinated according to custom of the port of loading and discharge because of the importance of local custom in the loading and discharge of goods.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.4 no.2
• /
• pp.80-89
• /
• 1996

Fatigue life of a notched shaft was evaluated in order to estimate the durability and integrity of the notched shaft in design stage. Cumulative fatigue dama- ge analysis was performed using local strain approach based on the assumption that the fatigue life of a notched component is approximately same as that of a smooth specimen is subjected to the same strain at the notched component. In this paper, shafts with different notch root radius of 1, 2㎜ resulting in different values of stress concentration factors were tested under||rotating bending fatigue loading condition. Theoretical stress concentration factor for each notch type was calculated using finite element method. Fatigue life prediction program, FALIPS, written in C language was developed using the strain-life curve, and the local strain approach integrating Neuber's rule, cyclic stress-strain, and hysteresis loop equations. The fatigue life evaluated using the fatigue notch factor obtained from the experimentally determined fatigue strength showed very large scattering with nonconservatism, but the fatigue notch factors derived from the stress concentration factors and Peterson's equation reduced the considerablely accurate fatigue life evaluation within a factor of three.

• Journal of environmental and Sanitary engineering
• /
• v.19 no.1
• /
• pp.24-36
• /
• 2004

This study is to investigate the present condition of waste disposal establishment and to analysis problems which could be produced at location selection formalities of waste disposal establishment. It proposed building methods of waste disposal establishment to lead spontaneous participation of local resident according to case analysis of waste disposal establishment. There are research results; i) Opposition of inhabitants was the majority of reason at the business abandonment or delay of waste disposal establishment. Therefore agreement formation course with local inhabitants is most important position. ii) Many estimate have been needed for waste disposal establishment, but support estimate of government was 30-50% that is really low compare with other environmental establishment. So that it need to increase of government estimate. iii) Location collection is carried out based on law and final collected location must be executed without delay of relation business as soon as possible. iv) Standard of location collection has to divide into small, middle and large size and to apply with same rule according to divided location. v) It must be change public subscription before and location selection after and maintain continuance of information offer to local inhabitants and offered information. vi) after building of waste disposal establishment for solving distrust of waste disposal establishment. It must be planed and carried on useful support countermeasure to local inhabitants in actuality.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.58-73
• /
• 2014

As is well known, cooperative sensing can significantly improve the sensing accuracy as compared to local sensing in cognitive radio networks (CRNs). However, a large number of cooperative secondary users (SUs) reporting their local detection results to the fusion center (FC) would cause much overhead, such as sensing delay and energy consumption. In this paper, we propose a fast cooperative sensing scheme, called double threshold fusion (DTF), to reduce the sensing overhead while satisfying a given sensing accuracy requirement. In DTF, FC respectively compares the number of successfully received local decisions and that of failed receptions with two different thresholds to make a final decision in each reporting sub-slot during a sensing process, where cooperative SUs sequentially report their local decisions in a selective fashion to reduce the reporting overhead. By jointly considering sequential detection and selective reporting techniques in DTF, the overhead of cooperative sensing can be significantly reduced. Besides, we study the performance optimization problems with different objectives for DTF and develop three optimum fusion rules accordingly. Simulation results reveal that DTF shows evident performance gains over an existing scheme.

• Information Systems Review
• /
• v.24 no.1
• /
• pp.105-123
• /
• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.6
• /
• pp.619-627
• /
• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.