• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Korean Journal of Cognitive Science
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• v.34 no.2
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• pp.85-110
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• 2023

The gaze cueing effect appears as detecting a target rapidly and accurately when the direction of others' gaze corresponds with the location of the visual target. The gaze cue can be affected by the orientation of the face. The gaze cueing effect is strong when the face is presented upright, but the effect has only been observed in some studies when the face is presented inverted(e.g., Tipples, 2005). This study aimed to examine whether the gaze can operate as a cue to guide attention with upright faces, and to add variables that can affect the gaze cue, such as the orientation of the face, the orientation of the background, and a time interval between the gaze cue and the target(SOA). Furthermore, it systematically manipulated these variables to explore whether the gaze cueing effect can be observed under the various conditions. The results showed a significant gaze cueing effect even on the inverted face, contrasting with previous studies. These findings were consistently observed when the background stimulus was absent(Experiment 1) and present(Experiments 2 and 3). However, there was no significant interaction in the orientations between the face and the background. Moreover, in the short SOA(150 ms), we found a significant gaze cueing effect in conditions of every face and background orientation, whereas there was no significant gaze cueing effect in the long SOA(1000 ms). By presenting a consistent observation of the gaze cueing effect under the short SOA(150ms) even in the inverted faces, the results of this study pose questions about the reliability and repeatability of previous studies that did not report significant results of gaze cueing effects in that faces. Furthermore, our results are meaningful in providing additional evidence that attention can be guided toward the direction of the gaze even in various directions of the face and background.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1225-1234
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• 2023

The intensity of crop water stress caused by moisture deficit is affected by growth and heat conditions. For more accurate detection of crop water stress state using remote sensing techniques, it is necessary to select vegetation indices sensitive to crop response and to understand their changes considering not only soil moisture deficit but also heat conditions. In this study, we measured the MERIS terrestrial chlorophyll index (MTCI) and chlorophyll/carotenoid index (CCI) under drought and heat wave conditions. The MTCI, sensitive to chlorophyll concentration, sensitively decreased on non-irrigation conditions and the degree was larger with heat waves. On the other hand, the CCI, correlated with photosynthesis efficiency, showed less sensitivity to water deficit but had decreased significantly with heat waves. After re-irrigation, the MTCI was increased than before damage and CCI became more sensitive to heat stress. These results are expected to contribute to evaluating the intensity of crop water stress through remote sensing techniques.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1085-1095
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• 2023

Time-series data generated from satellite data are crucial resources for change detection and monitoring across various fields. Existing research in time-series data generation primarily relies on single-image analysis to maintain data uniformity, with ongoing efforts to enhance spatial and temporal resolutions by utilizing diverse image sources. Despite the emphasized significance of time-series data, there is a notable absence of automated data collection and preprocessing for research purposes. In this paper, to address this limitation, we propose a system that automates the collection of satellite information in user-specified areas to generate time-series data. This research aims to collect data from various satellite sources in a specific region and convert them into time-series data, developing an automatic satellite image collection system for this purpose. By utilizing this system, users can collect and extract data for their specific regions of interest, making the data immediately usable. Experimental results have shown the feasibility of automatically acquiring freely available Landsat and Sentinel images from the web and incorporating manually inputted high-resolution satellite images. Comparisons between automatically collected and edited images based on high-resolution satellite data demonstrated minimal discrepancies, with no significant errors in the generated output.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Smart Media Journal
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• v.13 no.6
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• pp.9-15
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• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.509-523
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• 2023

The high-level nuclear waste (HLW) repository is exposed to complex environmental conditions consisting of high temperature, high humidity, and radiation, resulting in structural deterioration. Therefore, structural health monitoring is essential, and piezo sensors are used to detect cracks and estimate strength. However, since the monitoring sensors installed in the disposal tunnel and disposal container cannot be replaced or removed, the quantitative life of the monitoring sensor and its suitability must be assessed. In this study, the life of a piezo sensor for monitoring was assessed using an accelerated life test (ALT). The failure mode and mechanism of the piezo sensor under high temperature conditions were determined, and temperature stress's influence on the piezo sensor's life was analyzed. ALT was conducted on temperature stress and the relationship between temperature stress and piezo sensor life was suggested. The life of the piezo sensor was assessed using the Weibull probability distribution and the Arrhenius acceleration model. The suggested relationship can be used in multiple stress ALT designs for more precise life assessment.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.29-38
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• 2024

The Matched Field Processing (MFP) is an estimation method for a source range and depth based on the prediction of sound propagation. However, as the frequency increases, the prediction inaccuracy of sound propagation increases, making it difficult to estimate the source position. Recently proposed, the Frequency-Difference Matched Field Processing (FD-MFP) is known to be robust even if there is a mismatch by applying a frequency-difference autoproduct extracted from the auto-correlation of a high frequency signal. In this paper, in order to evaluate the performance of the FD-MFP using a horizontal line array, simulations were conducted in the environment of the East Sea of Korea. In the area of Bottom Bounce (BB) and Convergence Zone (CZ) where detection of a sound source is possible at a long range, and the results of localization were analyzed. According to the the FD-MFP simulations of horizontal line array, the accuracy of localization is similar or degraded compared to the conventional MFP due to diffracted field and mismatch of sound speed. There was no clear result from the simulations conforming that the FD-MFP was more robust to mismatch than the conventional MFP.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• Economic and Environmental Geology
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• v.30 no.2
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• pp.137-142
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• 1997

At the tailings dam of the disused Brukunga pyrite mine in South Australia, reaction of groundwater with the tailings causes the formation and discharge of sulphuric acid. There is a need to improve remediation efforts by decreasing groundwater flow through the tailings dam. Geophysical methods have been investigated to determine whether they can be used to characterise variations in depth to watertable and map preferred groundwater flow paths. Three methods were used: transient electromagnetic (TEM) soundings, direct current (DC) soundings and profiling, and self potential (SP) profiling. The profiling methods were used to map the areal extent of a given response, while soundings was used to determine the variation in response with depth. The results of the geophysical surveys show that the voltages measured with SP profiling are small and it is hard to determine any preferred channels of groundwater flow from SP data alone. Results obtained from TEM and DC soundings, show that the DC method is useful for determining layer boundaries at shallow depths (less than about 10 m), while the TEM method can resolve deeper structures. Joint use of TEM and DC data gives a more complete and accurate geoelectric section. The TEM and DC measurements have enabled accurate determination of depth to groundwater. For soundings centred at piezometers, this depth is consistent with the measured watertable level in the corresponding piezometer. A map of the watertable level produced from all the TEM and DC soundings at the site shows that the shallowest level is at a depth of about 1 m, and occurs at the southeast of the site, while the deepest watertable level (about 17 m) occurs at the northwest part of the site. The results indicate that a possible source of groundwater occurs at the southeast area of the dam, and the aquifer thickness varies between 6 and 13 m. A map of the variation of resistivity of the aquifer has also been produced from the TEM and DC data. This map shows that the least resistive (i.e., most conductive) section of the aquifer occurs in the northeast of the site, while the most resistive part of the aquifer occurs in the southeast. These results are interpreted to indicate a source of fresh (resistive) groundwater in the southeast of the site, with a possible further source of conductive groundwater in the northeast.