• Korean Journal of Remote Sensing
• /
• v.36 no.2_2
• /
• pp.379-399
• /
• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Science of Emotion and Sensibility
• /
• v.22 no.4
• /
• pp.97-106
• /
• 2019

The purpose of this study was to investigate the effect of the type and measurement location of a fabric strain gauge sensor on the detection performance for respiratory signals. We implemented two types of sensors to measure the respiratory signal and attached them to a band to detect the respiratory signal. Eight healthy males in their 20s were the subject of this study. They were asked to wear two respiratory bands in turns. While the subjects were measured for 30 seconds standing comfortably, the respiratory was given at 15 breaths per minute were synchronized, and then a 10-second break; subsequently, the entire measurement was repeated. Measurement locations were at the chest and abdomen. In addition, to verify the performance of respiratory measurement in the movement state, the subjects were asked to walk in place at a speed of 80 strides per minute(SPM), and the respiratory was measured using the same method mentioned earlier. Meanwhile, to acquire a reference signal, the SS5LB of BIOPAC Systems, Inc., was worn by the subjects simultaneously with the experimental sensor. The Kruskal-Wallis test and Bonferroni post hoc tests were performed using SPSS 24.0 to verify the difference in measurement performances among the group of eight combinations of sensor types, measurement locations, and movement states. In addition, the Wilcoxon test was conducted to examine whether there are differences according to sensor type, measurement location, and movement state. The results showed that the respiratory signal detection performance was the best when the respiratory was measured in the chest using the CNT-coated fabric sensor regardless of the movement state. Based on the results of this study, we will develop a chest belt-type wearable platform that can monitor the various vital signal in real time without disturbing the movements in an outdoor environment or in daily activities.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.4
• /
• pp.3-14
• /
• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• Journal of Platform Technology
• /
• v.11 no.2
• /
• pp.26-38
• /
• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• Journal of Korean Society for Atmospheric Environment
• /
• v.34 no.3
• /
• pp.393-405
• /
• 2018

Volatile organic compounds (VOCs) are representative air pollutants due to their detrimental effects on human health and their role in formation of secondary organic aerosols. Assessments and monitoring programs of VOCs using periodic grab sampling like Tedlar bags, canisters, and sorbent traps provide limited information, often with delay times of days or weeks. Selected ion flow tube mass spectrometry (SIFT-MS) is an emerging analytical technique for the real-time quantification of VOCs in air. It relies on chemical ionization of the VOCs molecules in air introduced into helium carrier gas using $H_3O^+$, $NO^+$, and $O_2{^+}$ precursor ions. Real-time monitoring method of 60 VOCs in the ambient air was developed using TO-15 standard gas mixture. Calibration curves, method detection limit, and quantitation reproducibility of the target compounds were tested. Dynamic dilution system was used to dilute standard gas from 0.174 ppbv to 100 ppbv, where calibration curves showed good linearity with $r^2$> 0.95 in all target analytes. Limit of detection (LOD) all compounds were sub ppbv, and some halogenated compounds showed pptv levels. Seven consecutive analyses of target compounds showed good repeatability with relative standard deviation of less than 10%. One day monitoring of VOCs in ambient air was conducted in Geoje. Average concentration of target VOCs in Geoje were relatively lower than other regions, among which formaldehyde showed the highest concentration ($15.4{\pm}5.78ppbv$). SIFT-MS provided good temporal resolution data (1 data per 3.2 minute), which can be used for identifying ephemeral short-term event. It is expected that SIFT-MS will be a versatile monitoring platform for VOCs in ambient air.

• Convergence Security Journal
• /
• v.6 no.3
• /
• pp.1-12
• /
• 2006

Malicious codes have been widely documented and detected in information security breach occurrences of Microsoft Windows platform. Legacy information security systems are particularly vulnerable to breaches, due to Window kernel-based malicious codes, that penetrate existing protection and remain undetected. To date there has not been enough quality study into and information sharing about Windows kernel and inner code mechanisms, and this is the core reason for the success of these codes into entering systems and remaining undetected. This paper focus on classification and formalization of type target and mechanism of various Windows kernel-based attacks, and will present suggestions for effective response methodologies in the categories of, "Kernel memory protection", "Process & driver protection" and "File system & registry protection". An effective Windows kernel protection system will be presented through the collection and analysis of Windows kernel and inside mechanisms, and through suggestions for the implementation methodologies of unreleased and new Windows kernel protection skill. Results presented in this paper will explain that the suggested system be highly effective and has more accurate for intrusion detection ratios, then the current legacy security systems (i.e., virus vaccines and Windows IPS, etc) intrusion detection ratios. So, It is expected that the suggested system provides a good solution to prevent IT infrastructure from complicated and intelligent Windows kernel attacks.

• Korean Journal of Remote Sensing
• /
• v.36 no.2_2
• /
• pp.337-349
• /
• 2020

In this study, Helikite, Low Altitude Remote Sensing (LARS) platform, was used to acquire coastal images. In the obtained image, the land and water masses were divided using four types of region clustering algorithms, and then waterline was extracted using edge detection. Quantitative comparisons were not possible due to the lack of in-situ waterline data. But, based on the image of the infrared band where water masses and land are relatively clear, the waterlines extracted by each algorithm were compared. As a result, it was found that each algorithm differed significantly in the part where the distinction between water masses and land was ambiguous. This is considered to be a difference in the process of selecting the threshold value of the digital number that each algorithm uses to distinguish the regions. The extraction of waterlines through various algorithms is expected to be used in conjunction with a Low Altitude Remote Sensing system that can be continuously monitored in the future to explain the rapid changes in coastal shape through several years of long-term data from fixed areas.

• Journal of Service Research and Studies
• /
• v.5 no.2
• /
• pp.111-118
• /
• 2015

Although the development of mobile devices are made us a free life, they were displayed the subject of this financial crime and attacking forces in the other side. Among finance-related crime is become a serious crime that are targeting smartphones by SMS phishing, phishing, pharming, voice phishing etc. In particular, SMS phishing is increased according to phenomenon using the nature of a text message in the mobile. SMS phishing is become new crime due to the burden to the smartphone user. Their crime is also the advanced way from the existing fraud, such as making the malicious apps. Especially it generates loopholes in the law by a method such as using a foreign server. For safe from SMS phishing attacks, proactive pre-diagnosis is even more important rather than post responses. It is necessary to deploy blocking programs for detecting SMS phishing attacks in advance to do this. In this paper we are investigating the process of block types and block apps that are currently deployed and presenting the evaluation of the application of the detection block setting app.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.191-201
• /
• 2018

Recently, the frequency of heavy rainfall is increasing due to the effects of climate change, and heavy rainfall in urban areas has an unexpected and local characteristic. Floods caused by localized heavy rains in urban areas occur rapidly and frequently, so that life and property damage is also increasing. It is crucial how fast and precise observations can be made on successful flood management in urban areas. Local heavy rainfall is predominant in low-level storms, and the present large-scale radars are vulnerable to low-level rainfall detection and observations. Therefore, it is necessary to introduce a new urban flood forecasting system to minimize urban flood damage by upgrading the urban flood response system and improving observation and forecasting accuracy by quickly observing and predicting the local storm in urban areas. Currently, the WHAP (Water Hazard Information Platform) Project is promoting the goal of securing new concept water disaster response technology by linking high resolution hydrological information with rainfall prediction and urban flood model. In the WHAP Project, local rainfall detection and prediction, urban flood prediction and operation technology are being developed based on high-resolution small radar for observing the local rainfall. This study is expected to provide more accurate and detailed urban flood warning system by enabling high-resolution observation of urban areas.

• Korean Journal of Remote Sensing
• /
• v.39 no.3
• /
• pp.311-323
• /
• 2023

Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.