• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1017-1026
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• 2015

Infrared (IR) target detection is one of the key technologies in Automatic Target Detection/Recognition (ATD/R) for military applications. However, IR sensors have limitations due to the weather sensitivity and atmospheric effects. In recent years, sensor information fusion study is an active research topic to overcome these limitations. SAR sensor is adopted to sensor fusion, because SAR is robust to various weather conditions. In this paper, a Boolean Map Visual Theory-Morphology (BMVT-M) method is proposed to detect targets in SAR and IR images. Moreover, we suggest the IR and SAR image registration and decision level fusion algorithm. The experimental results using OKTAL-SE synthetic images validate the feasibility of sensor fusion-based target detection.

• Journal of Korean Academy of Nursing Administration
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• v.17 no.3
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• pp.336-348
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• 2011

Purpose: This methodological study was done to develop a telephone consultation algorithms and practice guidelines for patient discharged with ophthalmic diseases. Methods: The ophthalmic problems of the patients were identified and expert knowledge on managing the problems was acquired. Algorithms and practice guidelines were developed based on the expert knowledge. The content validity of algorithms and practice guidelines was evaluated by the experts. Results: The preliminary algorithms and practice guidelines were developed from 60 detailed signs and symptoms and 45 nursing interventions. The experts agreed that 57 detailed signs and symptoms linked with nursing interventions were valid, with the content validity index over 80%. Meeting with nurse experts and ophthalmologists was convened to review the rest of the 3 detailed signs and symptoms linked with nursing interventions. Finally, 60 detailed signs and symptoms and 46 nursing interventions were confirmed. Conclusion: This study suggests that the algorithms and practice guidelines are effective decision-making tools and utilization of these algorithms and practice guidelines is expected to improve the quality of clinical nursing and patient satisfaction.

• Smart Structures and Systems
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• v.17 no.1
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• pp.135-147
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• 2016

This paper describes a smart structural system, which uses smart materials for real-time monitoring and active control of bolted-joints in steel structures. The goal of this research is to reduce the possibility of failure and the cost of maintenance of steel structures such as bridges, electricity pylons, steel lattice towers and so on. The concept of the smart structural system combines impedance based health monitoring techniques with a shape memory alloy (SMA) washer to restore the tension of the loosened bolt. The impedance-based structural health monitoring (SHM) techniques were used to detect loosened bolts in bolted-joints. By comparing electrical impedance signatures measured from a potentially damage structure with baseline data obtained from the pristine structure, the bolt loosening damage could be detected. An outlier analysis, using generalized extreme value (GEV) distribution, providing optimal decision boundaries, has been carried out for more systematic damage detection. Once the loosening damage was detected in the bolted joint, the external heater, which was bonded to the SMA washer, actuated the washer. Then, the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. Additionally, temperature variation due to the heater was compensated by applying the effective frequency shift (EFS) algorithm to improve the performance of the diagnostic results. An experimental study was conducted by integrating the piezoelectric material based structural health monitoring and the SMA-based active control function on a bolted joint, after which the performance of the smart 'self-monitoring and self-healing bolted joint system' was demonstrated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.85-92
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• 2002

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current methods used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). Generally speaking, the nonlinear profile formulas provide better accuracy than the linear profile formulas. However, all the formulas mentioned have a common drawback to ground profile, such as sharp corners or the grid points of any two straight lines. In this paper, we propose an algorithm of finding a spline surface which interpolates the given data and an appropriate method to calculate the earthwork. We present some computational results showing that our proposed method provides better accuracy than Chen and Lin's method.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.462-466
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• 2005

Dynamic (On-line) signature verification system consists of preprocessing, feature extraction, comparison and decision process for internal processing, and registration and verification windows for the user interface. We describe an implementation and design for an advanced dynamic signature verification system. Also, we suggest the method of feature extraction, matching algorithm, efficient user interface and an objective criteria for evaluating the performance.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.1-24
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• 2016

With the innovation of information technology, non-face-to-face robo advisor with high accessibility and convenience is spreading. The current robot advisor recommends appropriate investment products after understanding the investment propensity based on the structured data entered directly or indirectly by individuals. However, it is an inconvenient and obtrusive way for financial consumers to inquire or input their own subjective propensity to invest. Hence, this study proposes a way to deduce the propensity to invest in unstructured data that customers voluntarily exposed during consultation or online. Since prediction performance based on unstructured document differs according to the characteristics of text, in this study, classification algorithm optimized for the characteristic of text left by financial consumers is selected by performing prediction performance evaluation of various learning discrimination algorithms and proposed an intelligent method that automatically recommends investment products. User tests were given to MBA students. After showing the recommended investment and list of investment products, satisfaction was asked. Financial consumers' satisfaction was measured by dividing them into investment propensity and recommendation goods. The results suggest that the users high satisfaction with investment products recommended by the method proposed in this paper. The results showed that it can be applies to non-face-to-face robo advisor.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.488-497
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• 2004

This paper describes the hybrid document summarization using the indicative summarization and the query-based summarization. The learning models are built from teaming documents in order to extract topic phrases. We use Naive Bayesian, Decision Tree and Supported Vector Machine as the machine learning algorithm. The system extracts topic phrases automatically from new document based on these models and outputs the summary of the document using query-based summarization which considers the extracted topic phrases as queries and calculates the locality-based similarity of each topic phrase. We examine how the topic phrases affect the summarization and how many phrases are proper to summarization. Then, we evaluate the extracted summary by comparing with manual summary, and we also compare our summarization system with summarization mettled from MS-Word.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1465-1466
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• 2006

The monitoring and diagnosing technique for lightning arresters is important to assure the reliability of power supply in GIS-substation. In this paper, we described the implementation of an expert system for GIS arrester facilities. The proposed system consists of a data acquisition module (DAM), a wireless communication module, and a personal computer. The DAM detects system voltages, total leakage currents and its harmonic components, and includes an algorithm to calculate the resistive leakage current by the principle that the magnitudes of resistive leakage current are equal at the same level of the system voltage applied to the arrestor. Also, we designed a surge event detection circuit which can acquire the date, the polarity, and the amplitude of surge events. All the acquired data are transmitted after correction by many algorithms to the remote station through the ZigBee protocol. The expert system is based on the Jave Expert System Shell (JESS) and make more reliable decision by using an exclusive inference process.

• Journal of Sensor Science and Technology
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• v.5 no.3
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• pp.55-64
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• 1996

To control arousal level using physiological index, electrodermal activity signal was detected and separated into skin impedance level and response. Arousal state decision and control algorithm was studied to implement and evaluate real time portable arousal control system. The implemented system can detect and control arousal state from initial drowsy state. This system will be applicable to the evaluation of the effect of warning signal, driver's drowsy detecting system, and sleep study.