• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.1
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• pp.105-114
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• 2006

Ubiquitous Sensor Network consists of a number of sensor nodes with a limited computation power and limited communication capabilities, and a sensor node is able to communicate with each other at anytime and in any place. Due to the rapid research and development in sensor networks, it will rapidly grow into environments where hmm beings can interact in an intuitive way with sensing objects which can be PDAs, sensors, or even clothes in the future. We are aiming at realizing an Unattended Secure Security System to apply it to Ubiquitous Sensor Network. In this paper, the vulnerabilities in the Unattended security system are identified, and a new protocol called OMAC-SNEP is proposed for the Unattended Secure Security System. Because the CBC-MAC in SNEP is not secure unless the message length is fixed, the CBC-MAC in SNEP was replaced with OMAC in SNEP. We have shown that the proposed protocol is secure for my bit length of messages and is almost as efficient as the CBC-MAC with only one key. OMAC-SNEP can be used not only in Unattended Security System, but also any other Sensor Networks.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.103-110
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• 2022

Since satellite images generally include clouds in the atmosphere, it is essential to detect or mask clouds before satellite image processing. Clouds were detected using physical characteristics of clouds in previous research. Cloud detection methods using deep learning techniques such as CNN or the modified U-Net in image segmentation field have been studied recently. Since image segmentation is the process of assigning a label to every pixel in an image, precise pixel-based dataset is required for cloud detection. Obtaining accurate training datasets is more important than a network configuration in image segmentation for cloud detection. Existing deep learning techniques used different training datasets. And test datasets were extracted from intra-dataset which were acquired by same sensor and procedure as training dataset. Different datasets make it difficult to determine which network shows a better overall performance. To verify the effectiveness of the cloud detection network such as Cloud-Net, two types of networks were trained using the cloud dataset from KOMPSAT-3 images provided by the AIHUB site and the L8-Cloud dataset from Landsat8 images which was publicly opened by a Cloud-Net author. Test data from intra-dataset of KOMPSAT-3 cloud dataset were used for validating the network. The simulation results show that the network trained with KOMPSAT-3 cloud dataset shows good performance on the network trained with L8-Cloud dataset. Because Landsat8 and KOMPSAT-3 satellite images have different GSDs, making it difficult to achieve good results from cross-sensor validation. The network could be superior for intra-dataset, but it could be inferior for cross-sensor data. It is necessary to study techniques that show good results in cross-senor validation dataset in the future.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.3-12
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• 2023

Fire accidents in buildings are reported more frequently nowadays. Existing building fire accidents can lead to large-scale accidents as damage to human and physical resources increases over time, so it is necessary to quickly find ways to suppress fires and rescue them. Currently, more attention is being paid to new buildings than the existing buildings. In addition, fire information can not be captured in a real time basis for the buildings. In line with the demands of this technology, this study presents a quick and systematic fire management method to minimize damage caused by fire in buildings. As a way to achieve the purpose of the study, ArduinoTM sensors and ExcelTM and RevitTM-DynamoTM tools have been combined to develop a new fire information management system and develop a real-time 3D visualization model. It is expected to contribute to the real-time smart fire management system by proposing a fire management application as a way to utilize it in the future.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.433-441
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• 2007

The bio-Sensors, which are sensing the vital signs of human bodies, are largely used by the medical equipment. Recently, the sensor network technology, which composes of the sensor interface for small-seize hardware, processor, the wireless communication module and battery in small sized hardware, has been extended to the area of bio-senor network systems due to the advances of the MEMS technology. In this paper we have suggested a design and implementation of a health care information system(called u-EMS) using a bio-sensor network technology that is a combination of the bio-sensor and the sensor network technology. In proposed system, we have used the following vital body sensors such as EKG sensor, the blood pressure sensor, the heart rate sensor, the pulse oximeter sensor and the glucose sensor. We have collected various vital sign data through the sensor network module and processed the data to implement a health care measurement system. Such measured data can be displayed by the wireless terminal(PDA, Cell phone) and the digital-frame display device. Finally, we have conducted a series of tests which considered both patient's vital sign and context-awared information in order to improve the effectiveness of the u-EMS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.421-428
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• 2009

In Korea, the change of river flux due to seasons change is so considerable because of the mountainous terrain with the sharp slope and leaned rainfall. This unfavorable natural condition and the difficulties in precise grasping of the river status made the water resource management difficult so that the necessity of the precise river management has been continuously increased. In this study, a precise river-region DEM using the latest equipments of ALS and MBES is constructed. After acquiring DEM from each senor on the river region, a single DEM was generated by combining them. Also, the field inspection was carried out in the overlapped region of ALS and MBES in order to verify the quality of DEM. The verification of DEM was carried out by comparison between TINs obtained from the combined result of ALS and MBES and the surveying result from total station at more than 10 points in the selected two test areas. As a result, NO.1-area's RMSE of 0.322m and 0.113m are obtained for NO. 1 and NO. 2 areas, respectively. The result of this study shows the feasibility of DEM construction for river region using ALS and MBES as seen in the case of NO. 2 area. At the same time, it was appeared that a better method on the data fusion should be developed as seen in the result of NO. 1 area.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.6
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• pp.63-71
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• 2006

In this paper, we propose a secure solution for user authentication by using fingerprint verification on the sensor-client-server model, even with the client that is not necessarily trusted by the sensor holder or the server. To protect possible attacks launched at the untrusted client, our solution makes the fingerprint sensor validate the result computed by the client for the feature extraction. However, the validation should be simple so that the resource-constrained fingerprint sensor can validate it in real-time. To solve this problem, we separate the feature extraction into binarization and minutiae extraction, and assign the time-consuming binarization to the client. After receiving the result of binarization from the client, the sensor conducts a simple validation to check the result, performs the minutiae extraction with the received binary image from the client, and then sends the extracted minutiae to the server. Based on the experimental results, the proposed solution for fingerprint verification can be performed on the sensor-client-server model securely and in real-time with the aid of an untrusted client.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1489-1503
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• 2022

Drone and sensor technologies are enabling digitalization of agricultural crop's growth information and accelerating the development of the precision agriculture. These technologies could be able to assess damage of crops when natural disaster occurs, and contribute to the scientification of the crop insurance assessment method, which is being conducted through field survey. This study was aimed to calculate lodged damage rate from the vegetation indices extracted by drone based RGB images for soybean. Support Vector Classifier (SVC) models were considered by adding vegetation indices to the Crop Surface Model (CSM) based lodged damage rate. Visible Atmospherically Resistant Index (VARI) and Green Red Vegetation Index (GRVI) based lodged damage rate classification were shown the highest accuracy score as 0.709 and 0.705 each. As a result of this study, it was confirmed that drone based RGB images can be used as a useful tool for estimating the rate of lodged damage. The result acquired from this study can be used to the satellite imagery like Sentinel-2 and RapidEye when the damages from the natural disasters occurred.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.899-910
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• 2023

The majority of research on lifestyle has been conducted based on a variable-centered approach. However, over the last decades, there is a growing body of research on lifestyle in terms of a person-centered approach. Hence, this study identifies senior generations' profiles based on the combination of the five realms of lifestyle. More specifically, this study utilized a Latent profile analysis(LPA) to explore both quantitatively and qualitatively distinct types of senior generation' lifestyle profiles. As a result, the five distinct types of senior lifestyle profiles were identified and these five profiles were then contrasted with traveling attitude and behavioral intention(traveling intention). In addition, this study attempted to identify similarity in the patterns of relations with theoretical antecedent, correlate and outcome variables. Results showed that even though senior generation belonging to profile groups pertaining to the high level of all five types of lifestyle were associated with a high level of attitude and behavior intention, there was no differences among the profiles. This means that regardless of the patterns of senor generation lifestyle profiles, there was no similarity. Nevertheless, it should be considered that senior generation consider a security when making a travel ling decision regardless of the patterns of lifestyle profiles. This results suggest that senior generation' traveling satisfaction is more likely obtained with the experience of safety and convenience during their travel. At last, this study discusses some implication tourism theory related to lifestyle, practices and future research on tourism profiles.

• Tuberculosis and Respiratory Diseases
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• v.50 no.3
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• pp.310-319
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• 2001

Background : The peak flowmeter is very useful in monitoring of out-patients as well as those in emergency departments because of its convenience and simplicity with low cost. There have been many studies aimed at determining the accuracy and reproducibility of the peak flow meter in normal population. However, there is a paucity of reports regarding its accuracy in patients with chronic obstructive pulmonary disease(COPD) or asthma. The accuracy of the peak expiratory flow(PEF) measured with a mini-Wright peak flowmeter was assessed by a comparison with the results of a mass flow sensor. Methods : The PEF measurements were performed in 108 patients aged 19-82 years presenting with either a chronic obstructive lung disease or asthma before and after inhaling salbutamol. The PEF measurements from the mini-Wright flowmeter were compared with those obtained by the calibrated mass flow sensor. Results : The average of the readings taken by the mini-Wright meter were 37-39 l/min higher than those taken by the mass flow sensor. The average percentage error of the mini-Wright meter were higher, ranging less than 300 l/min. The mean of the differences between the values obtained using both instruments (the bias)$\pm$limits of agreement(${\pm}2$ SD) were $37.1{\pm}90\;l/min$ for the PEF(p<0.001). Conclusions : The mini-Wright peak flowmeter overestimated the flows in patients with COPD or asthma. It was also found that the accuracy of the mini-Wright peak flowmeter decreased in its mid to low range. The limits of agreement are wide and the difference between the two instruments is significant. Therefore, the measurements made between the two types of machines in patients with asthma or COPD cannot be used interchangeably.