• Korean Journal of Optics and Photonics
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• v.26 no.4
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• pp.187-194
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• 2015

A system of infrared camera optics with wide field of view and anamorphic lenses is proposed, and its validity verified through manufacture. The infrared camera produced provides a wide field of view of over 100 degrees in the horizontal direction, and an even greater magnification in the vertical direction. As a result, the system can have a wider surveillance range and improved detection ability at the same time. In addition, a new optomechanical automatic athermalization mechanism is proposed and applied to the infrared camera. Its performance and utility is proved through testing.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.307-317
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• 2008

Relaxed static stability(RSS) concept has been applied to improve aerodynamic performance of modem version supersonic jet fighter aircraft. Therefore, flight control system are necessary to stabilize an unstable aircraft and provides adequate handling qualities. Also, flight control systems of modem version aircraft employ a safety system to support emergency situations such as a pilot unknown attitude flight conditions of an aircraft in night flight-testing. This situation is dangerous because the aircraft can lose if the pilot not take recognizance of situation. Therefore, automatic recovery system is necessary. The system called the "Pilot Activated Recovery System" or PARS, provided a pilot initiated automatic maneuver capable of an aircraft recoveries in situations of unusual attitudes. This paper addresses the concept of PARS and designed using nonlinear control law design process based on model of supersonic jet trainer. And, this control law is verified by nonlinear analysis and real-time pilot evaluation using in-house software. The result of evaluation reveals that the PARS support recovery of an aircraft unusual attitude and improve a safety of an aircraft.

• Journal of Mechanical Science and Technology
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• v.15 no.11
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• pp.1472-1481
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• 2001

In this paper, an advanced shift controller that supervises the shift transients with adaptive compensation is presented. Modern shift control systems for vehicle automatic transmission are designe d to provide smooth transients for passengers' comfort and better component durability. In the conventional methods, lots of testing and calibration works have been done to tune gains of the controller, but it does not assure optimum shift quality at all times owing to system variations often caused by uncertainties in shifting hydraulic systems and external disturbances. In the proposed control scheme, an adaptive compensation controller with intelligent supervisor is implemented to achieve improved shift quality over the system variations. The control input pattern which generates clutch pressure commands in hydraulic actuating systems, is updated through a learning process to adjust for each subsequent shift based on continuous monitoring of shifting performance and environmental changes. The proposed algorithm is implemented and evaluated on the experimental test setup. Results from the experimental studies for several operation modes show both improved performance and adaptability of the proposed shift controller to uncertain changes of the shifting environment in vehicle power transmission systems.

• Journal of Korean Academy of Nursing
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• v.51 no.3
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• pp.347-362
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• 2021

Purpose: This study developed a cognitive behavioral therapy program aimed at altering the physical condition, emotions, and behaviors of fibromyalgia patients, and confirmed the program's clinical applicability. The program was developed by analyzing previous studies conducting in-depth interviews with fibromyalgia patients, drawing on cognitive behavior theory to establish the program contents, recruiting experts to test its validity, and conducting a preliminary survey. Methods: To confirm the program's effect, this study used a randomized controlled trial design. The participants were outpatients diagnosed with fibromyalgia in Dong-A University Hospital, Busan. The 30 patients in the experimental group took part in the program, which comprised 8 sessions (90 to 120 minutes) based on cognitive behavior theory, delivered over 8 weeks. Hypothesis testing was carried out using the repeated measures ANOVA. Results: The analysis revealed significant differences between the experimental and control groups in positive automatic thoughts, pain, fatigue, depression, and interpersonal relationships. However, there was no significant difference between the groups in terms of sleep disorders and negative automatic thoughts. Conclusion: This program is a positive effect on physical condition, emotions, and behaviors. It is thus expected to be used to help fibromyalgia patients improve their disease conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.132-132
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• 2021

Access to accurate spatial precipitation in many hydrological studies is necessary. Existence of many mountains with diverse topography in South Korea causes different spatial distribution of precipitation. Rain gauge stations show accurate precipitation information in points, but due to the limited use of rain gauge stations and the difficulty of accessing them, there is not enough accurate information in the whole area. Weather radars can provide an integrated precipitation information spatially. Despite this, weather radar data have some errors that can not provide accurate data, especially in heavy rainfall. In this study, some location-based variable like aspect, elevation, plan curvature, profile curvature, slope and distance from the sea which has most effect on rainfall was considered. Then Automatic Weather Station data was used for spatial training of variables in each event. According to this, K-fold cross-validation method was combined with Adaptive Neuro-Fuzzy Inference System. Based on this, 80% of Automatic Weather Station data was used for training and validation of model and 20% was used for testing and evaluation of model. Finally, spatial distribution of precipitation for 1×1 km resolution in Gwangdeoksan radar station was estimates. The results showed a significant decrease in RMSE and an increase in correlation with the observed amount of precipitation.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.19-30
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• 2015

Smart TV manufacturers have constructed automatic Smart TV execution environment for reducing cost of Smart TV testing. However, the conventional test methods still require high cost because of manual test script written by testers. Test scripts manully written have less reusability, and then less reusable scripts cannot be used for new TV models. In this paper, we propose constructing reusable test models for Smart TV and present a model-based Smart TV test script generation method using the modes. And we apply the method to NetCast Smart TV to confirm the effectiveness of enhancing reusability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.747-754
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• 2013

This paper describes SCTE(System and Control unit Test Equipment) as an integrated test equipment for airborne SAR system and control unit. SCTE enhances reusability of test equipment by modular design for required functions and strengthens automatic testing and test convenience by providing functions such as script-based testing function and report generation function. Also, it includes a navigation data simulator which can simulate various flight conditions. In this paper, we details SCTE requirements, H/W and S/W design, implementation, and test results with control unit and SAR system.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.209-216
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• 2019

Over the past decade, researchers were able to solve complex medical problems as well as acquire deeper understanding of entire issue due to the availability of machine learning techniques, particularly predictive algorithms and automatic recognition of patterns in medical imaging. In this study, a technique called transfer learning has been utilized to classify Magnetic Resonance (MR) images by a pre-trained Convolutional Neural Network (CNN). Rather than training an entire model from scratch, transfer learning approach uses the CNN model by fine-tuning them, to classify MR images into Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal control (NC). The performance of this method has been evaluated over Alzheimer's Disease Neuroimaging (ADNI) dataset by changing the learning rate of the model. Moreover, in this study, in order to demonstrate the transfer learning approach we utilize different pre-trained deep learning models such as GoogLeNet, VGG-16, AlexNet and ResNet-18, and compare their efficiency to classify AD. The overall classification accuracy resulted by GoogLeNet for training and testing was 99.84% and 98.25% respectively, which was exceptionally more than other models training and testing accuracies.

• International Journal of Air-Conditioning and Refrigeration
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• v.12 no.4
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• pp.184-191
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• 2004

In order to improve the performance of a 2 room heat pump with a constant speed compressor, the optimum refrigeration circuit of the heat pump with different cooling and heating capacities is developed by applying capillary tubes. The refrigeration circuit is composed of four parts; a heating circuit, a cooling circuit, a by-pass circuit and a balance circuit. The performance of the 2 room heat pump are investigated from a rating experiment and a reliability experiment, using the calorimeter. Results of the rating experiment show that the capacity of heat pump is about $93\%$ of the design value. In particular, the capacity of the cooling single operation is about $13\%$ higher than the design value, and the capacity of the heating multi operation is about $5\%$ higher than the design value. From the reliability experi-ment, it is found that the lowest driving voltage of the compressor is about $75\%$ of the rating voltage. Also the compressor is reoperated normally under the flood back and the over load.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.329-338
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• 2019

Today's embedded software (SW) developments are mostly preceded by composing Software Requirement Specification (SRS). In particular, in the domain of weapon systems, it is essential to have a systematic method for the verification of the SW functionality. To be more specific, it is crucial to check if the SW functionality is implemented as described in SRS, so-called SW suitability verification. Unfortunately, existing static or dynamic SW testing methods are not sufficient to evaluate suitability with SRS since those testings only verify the robustness of the SW codes. In this paper, we propose an automatic embedded SW suitability verification framework which is based on a structured SRS. The major challenge in the automation of this verification framework is how to get rid of ambiguities in SRS. In order to overcome this challenge, we propose a structured SRS description framework and the supporting toolchain for that. We show how the proposed framework is applied to an actual SRS of a weapon system.