• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.343-352
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• 2007

The present study aims to investigate the design standard for acoustic criteria of Korean traditional music which could be used for the design of Korean traditional music halls. In order to do this, subjective listening tests were undertaken to musicians using auralized sounds which were convolved with the impulse response of traditional instruments recorded in an anechoic chamber. 94 pairs of sound were made which have different value of acoustic parameters including RT, BR, Brilliance, G, C80, ITDG, IACC. A paired comparison method(PCM) was used to analyze the results from the subjective listening tests. The results show that the preference of acoustic criteria for the Korean traditional music is far different from those of western music. As a result, specific range of acoustic criteria were suggested for the appropriate acoustic conditions of Korean traditional music. Also, a guideline of the acoustic design of halls for performing the Korean traditional music was suggested which could be used as a basic reference in the future works.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.149-160
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• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.57-65
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• 2013

We developed a computer program (CDFlow v. 1.0) to design countermeasures against debris flows in natural terrain. The program can predict the probability of landslides occurring in natural terrain and can estimate the zone of damage caused by a debris flow. It can also be used to design the location and size of countermeasures against the debris flow. The program is run using the ArcGIS Engine, which is one of the most well-known Geographic Information System (GIS) tools for developers. The quasi-dynamic wetness index and the infinite slope stability equation were applied to predict landslide probability as a type of slope safety factor. The calculated safety factor was compared with the required safety factor, and areas of high probable potential for landslides were then selected and represented on the digital map. The volume of debris flow was estimated using these areas of high probable potential for landslides and soil depth. The accumulated volume of debris flow can be calculated along the flow channel. To assess the accuracy of the program, it was applied to a real landslide site at Deoksan-ri, Inje-gun, Kangwon-Province, where four debris barriers have been installed in the watershed of the site. The results of soil tests and a field survey indicate that the program has great potential for estimating probable landslide areas and the trajectory of debris flows. Calculation of the capacity volume of existing debris barriers revealed that they had insufficient capacity to store the calculated amount of debris flow. Therefore, this program enables a rational estimation of the optimal location and size of debris barriers.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.88-95
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• 2011

An embedded mobile device mostly has lower computation power than a general purpose computer because of its relatively lower system specifications. Consequently, conventional face tracking and face detection methods, requiring complex algorithms for higher recognition rates, are unsuitable in a mobile environment aiming for real time detection. On the other hand, by applying a real-time tracking and detecting algorithm, we would be able to provide a two-way interactive multimedia service between an user and a mobile device thus providing a far better quality of service in comparison to a one-way service. Therefore it is necessary to develop a real-time face and eye tracking technique optimized to a mobile environment. For this reason, in this paper, we proposes a method of tracking horizontal face position of a user on a T-DMB device for enhancing the quality of 3D DMB content. The proposed method uses the orientation of edges to estimate the left and right boundary of the face, and by the color edge information, the horizontal position and size of face is determined finally to decide the horizontal face. The sobel gradient vector is projected vertically and candidates of face boundaries are selected, and we proposed a smoothing method and a peak-detection method for the precise decision. Because general face detection algorithms use multi-scale feature vectors, the detection time is too long on a mobile environment. However the proposed algorithm which uses the single-scale detection method can detect the face more faster than conventional face detection methods.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.140-152
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• 2015

HCI(Human Computer Interaction) enables the interaction between people and computers by using a human-familiar interface called as Modality. Recently, to provide an optimal interface according to various devices and service environment, an advanced HCI method using multiple modalities is intensively studied. However, the multimodal interface has difficulties that modalities have different data formats and are hard to be cooperated efficiently. To solve this problem, a multimodal communicator is introduced, which is based on EMMA(Extensible Multimodal Annotation Markup language) and MMI(Multimodal Interaction Framework) of W3C(World Wide Web Consortium) standards. This standard based framework consisting of modality component, interaction manager, and presentation component makes multiple modalities interoperable and provides a wide expansion capability for other modalities. Experimental results show that the multimodal communicator is facilitated by using multiple modalities of eye tracking and gesture recognition for a map browsing scenario.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.188-200
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• 2002

The WRR scheduling algorithm is widely used in ATM networks due to its simplicity and the low cost of hardware implementation. It guarantees minimum cell rate according to the weight of each queue. The fairness is a important factor for ABR service. That is, scheduling algorithm allocates network resources fairly to each VC. However, WRR algorithm shows worse performance on bursty traffic. Because it schedules input traffics according to predetermined weight, it can not satisfies fairness criteria, MCR plus equal share and Maximum of MCR or Max-Min share, defined by ATM Forum TM 4.1 specification. The Nabeshima et al algorithm is not adapt to network status rapidly because it is not compensate the weights of unused bandwidth to VCs and assign the unused bandwidth to VCs by RR method. In this paper, we propose a scheduling algorithm for satisfying the two fairness criteria, MCR plus equal share and Maximum of MCR or Max-Min share, among the six criteria defined by ATM Forum TM 4.1 specification. The WRR, Nabeshima et al, and the proposed scheduling algorithms are compared with respect to fairness and convergence time throughout experimental simulation. According to the simulation results, the proposed algorithm shows higher fairness and more rapid convergence than other algorithms.

• The Journal of Engineering Geology
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• v.7 no.2
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• pp.101-112
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• 1997

Gravity and electrical resistivity surveys were carried out across the Kwangju fault in the downstream area of the Jangsung Lake, to investigate the location and geometrical feature of the fault. In the resistivity survey, dipole - dipole array method was adopted for 3 survey lines of which length and electrode spacing are 500m and 25m, respectively. Resistivity data are interpreted with aid of computer program "RESIS" which is widely used in resistivity data analysis and two dimensional resistivity profiles are obtained for 3 survey lines. Two large fracture zones relevant to the Kwangju fault are identified in the resistivity profiles. The total of 80 gravity data are observed with the mean spacing of 40 m and the exact leveling is accompanied to obtain more precise gravity anomalies. The subterranean density discontinuities calculated from the inverse method are appeared at the depths of 650rn and 120m. It is considered that the deep discontinuity indicates boundary between Jurassic granites and oveflying Cretaceous tuff formation. while, the shallow discontinuity is interpreted to be a boundary between alluvial deposits and basements. The subsurface geological structure to satisfy the observed Bouguer anomaly is determined from the iterative forward method in which results from existing surface geological informations, the inverse method, and from the resistivity interpretations are employed as an iuitial model. In conclusion, Kwangju fault is appeared to be a high angle normal fault mainly formed in tension stress filed.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.99-106
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• 2018

In the process of acquiring information through the cyber ISR (Intelligence Surveillance Reconnaissance) and research into the agent to help decision-making, periodic communication between the C&C (Command and Control) server and the agent may not be possible. In this case, we have studied how to effectively surveillance and reconnaissance. Due to the network configuration, agents planted on infiltrated computers can not communicate seamlessly with C&C servers. In this case, the agent continues to collect data continuously, and in order to analyze the collected data within a short time in When communication is possible with the C&C server, it can utilize limited resources and time to continue its mission without being discovered. This research shows the superiority of incremental learning method over batch method through experiments. At an experiment with the restricted memory of 500 mega bytes, incremental learning method shows 10 times decrease in learning time. But at an experiment with the reuse of incorrectly classified data, the required time for relearn takes twice more.