• Korean Journal of Optics and Photonics
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• v.29 no.3
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• pp.110-118
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• 2018

We have designed a mid-infrared optical system for an airborne electro-optical targeting system. The mid-IR optical system is a dual-field-of-view (FOV) optics for an airborne electro-optical targeting system. The optics consists of a beam-reducer, a zoom lens group, a relay lens group, a cold stop conjugation optics, and an IR detector. The IR detector is an f/5.3 cooled detector with a resolution of $1280{\times}1024$ square pixels, with a pixel size of $15{\times}15{\mu}m$. The optics provides two stepwise FOVs ($1.50^{\circ}{\times}1.20^{\circ}$ and $5.40^{\circ}{\times}4.23^{\circ}$) by the insertion of two lenses into the zoom lens group. The IR optical system was designed in such a way that the working f-number (f/5.3) of the cold stop internally provided by the IR detector is maintained over the entire FOV when changing the zoom. We performed two analyses to investigate thermal effects on the image quality: athermalization analysis and Narcissus analysis. Athermalization analysis investigated the image focus shift and residual high-order wavefront aberrations as the working temperature changes from $-55^{\circ}C$ to $50^{\circ}C$. We first identified the best compensator for the thermal focus drift, using the Zernike polynomial decomposition method. With the selected compensator, the optics was shown to maintain the on-axis MTF at the Nyquist frequency of the detector over 10%, throughout the temperature range. Narcissus analysis investigated the existence of the thermal ghost images of the cold detector formed by the optics itself, which is quantified by the Narcissus Induced Temperature Difference (NITD). The reported design was shown to have an NITD of less than $1.5^{\circ}C$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.557-564
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• 2017

The purpose of the thermal imaging observation device mounted on the K's tank in the Republic of Korea military is to convert infrared rays into visual information to provide information about the environment under conditions of restricted visibility. Among the various performance indicators of thermal observation devices, such as the view, magnification, resolution, MTF, NETD, and Minimum Resolvable Temperature Difference (MRTD), the MRTD is the most important, because it can indicate both the spatial frequency and temperature resolvable. However, the standard method of measuring the MRTD in NATO contains many subjective factors. As the measurement result can vary depending on subjective factors such as the human eye, metal condition and measurement conditions, the MRTD obtained is not stable. In this study, these qualitative MRTD measurement systems are converted into quantitative indicators based on a gray scale using imaging processing. By converting the average of the gray scale differences of the black and white images into the MRTD, the mean values can be used to determine whether the performance requirements required by the defense specification are met. The (mean) value can also be used to discriminate between detection, recognition and identification and the detectable distance of the thermal equipment can be analyzed under various environmental conditions, such as altostratus, heavy rain and fog.

• Journal of the Korean Society of Radiology
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• v.11 no.1
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• pp.49-54
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• 2017

As the Radiofrequency(RF) increases with the magnetic field strength, the wavelength of the RF excitation field becomes smaller, which leads to more the thermal effect in the human-body placed in the electric field. MRI scanner used was GE signa 1.5T, HDx 3.0T and Philips 3.0T with same routine clinical sequence protocol. Therefore temperature was measured before and after each scan. Taken the temperatures in the ear with ear infra-red type thermometer(Braun co). 3.0T were temperature increases more than $0.15^{\circ}C$ and GE 3.0T MRI equipment about $0.14^{\circ}C$ higher than the Philips 3.0T MRI(p<0.012). Psychogenic status was investigated by the survey respondents about their status can not just answer therefore, a little different from the expected. In our study of Thermal effect of clinical MRI with clinical protocol sequence, we found that the 3.0T in the body-temperature rise was greater than the 1.5T. Therefore, in clinical 3.0T examine the dangerous situation caused by the temperature rise occurred (burns, impaired thermoregulatory mechanism in patients with high-temperature damage, exhaustion occurs due to excessive sweating), not to appear the more watched the patient's condition with procedure.

• Journal of the Korean Chemical Society
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• v.37 no.6
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• pp.570-576
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• 1993

1-, 3-, 9-, and 21-Monolayer Langmuir-Blodgett(LB) films of stearic acid were deposited on silver-coated glass slides at the surface pressure of 30 mN/m. Fourier transform infrared(FTIR) reflection-absorption spectra (RAS) of these LB films were recorded at various temperatures from 31 to $72^{\circ}C.$ The spectra at $31^{\circ}C$ exhibited characteristic features of highly perpendicular orientation of the hydrocarbon chain. In the 1-monolayer LB film, the C=O stretching band was not observed, presumably due to the image dipole effect on the silver surface. In the 1-and 3-monolayer LB films, the trans isomer of stearic acid was prominent, but the cis isomer was dominant in the 21-monolayer LB film. FTIR-RAS measurements at an elevated temperature indicated that the chain melting temperature increases and approached to the bulk melting point with increasing the number of monolayer, except for the 1-monolayer LB film which has a higher melting temperature than the 3-monolayer film due to the strong interaction with the silver substrate.

• Journal of Navigation and Port Research
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• v.40 no.3
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• pp.159-164
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• 2016

The goal of this study is to implement a communication system that can monitor the status of the nacelle using the power cable itself, without the dedicated communication lines such as an UTP cable and optical fiber for the offshore wind turbine. An inductive coupling powerline communication system for a MW class offshore wind turbine was proposed and its communication performance was demonstrated. The inductive couplers was designed for operation at up to 500 A using a ferrite composite materials. Field test was carried out on the wind farms of Jeju island. Using the iperf communication test program, we have obtained more than 15 Mbps data transmission rate through the 100 m power cable that was installed between the nacelle and the bottom of the power converter. In the data transmission stability test for a week, there was no failure ever. The minimum transmission rate was 15 Mbps and the average data rate was about 20 Mbps. Next, we have installed an infrared camera inside the nacelle in order to measure the temperature distribution and variation of the nacelle. The real-time thermal image taken by the camera was successfully sent to the monitoring system without error.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.55-61
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• 2021

In this paper, we proposed a DeepLabv3+ based encoder-decoder model utilizing an attention mechanism for precise semantic segmentation. The DeepLabv3+ is a semantic segmentation method based on deep learning and is mainly used in applications such as autonomous vehicles, and infrared image analysis. In the conventional DeepLabv3+, there is little use of the encoder's intermediate feature map in the decoder part, resulting in loss in restoration process. Such restoration loss causes a problem of reducing segmentation accuracy. Therefore, the proposed method firstly minimized the restoration loss by additionally using one intermediate feature map. Furthermore, we fused hierarchically from small feature map in order to effectively utilize this. Finally, we applied an attention mechanism to the decoder to maximize the decoder's ability to converge intermediate feature maps. We evaluated the proposed method on the Cityscapes dataset, which is commonly used for street scene image segmentation research. Experiment results showed that our proposed method improved segmentation results compared to the conventional DeepLabv3+. The proposed method can be used in applications that require high accuracy.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.