• Composites Research
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• v.19 no.1
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• pp.29-35
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• 2006

The avoidance of enemy's radar detection is very important issue in the modem electronic weapon system. Researchers have studied to minimize reflected signals of radar. In this research, two types of radar absorbing structure (RAS), 'C'-type shell and 'U'-type shell, were fabricated using fiber-reinforced composite materials and their radar cross section (RCS) were evaluated. The absorption layer was composed of glass fiber reinforced epoxy and nano size carbon-black, and the reflection layer was fabricated with carbon fiber reinforced epoxy. During their manufacturing process, undesired thermal deformation (so called spring-back) was observed. In order to reduce spring-back, the bending angle of mold was controlled by a series of experiments. The spring-back of parts fabricated by using compensated mold was predicted by finite element analysis (ANSYS). The RCS of RAS shells were measured by compact range and predicted by physical optics method. The measured RCS data was well matched with the predicted data.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.401-408
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• 2017

GNSS(Global Navigation Satellite System) is positioning and navigation system using satellites. Accurate positioning is possible in all regions of the world using satellite signals. In Korea, GPS was introduced in the late 1980s. GPS is used in research and work in various fields such as navigation, surveying, and GIS. Since 1995, NGII(National Geographic Information Institute) has installed and operated CORS(Continuously Operating Reference Station) for the practical use of GNSS surveying, RINEX download and VRS(Virtual Reference Station) service was provided for precise positioning. Demand for these services is explosively increasing in the field of surveying. Therefore, there is a need for research to provide good service. In this study, status of national surveying infra structure was researched focused on CORS and its services. As a results, current status of CORS and service were presented. Users of VRS service has increased greatly. In order to provide stable service and advanced surveying, it is necessary to continuously upgrade services such as providing services for various GNSS satellites and securing stability through server redundancy in the data center.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.45-52
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• 2022

Recently, interest in and demand for sensors that recognize physical activity and their products are increasing. In particular, the development of wearable materials that are flexible, stretchable, and able to detect the user's biological signals is drawing attention. In this study, an experiment was conducted to improve the dip-coating efficiency of a single-walled carbon nanotube dispersion solution after fine holes were made in a hydrophobic material with a micro needle. In this study, dip-coating was performed with a material that was not penetrated, and comparative analysis was performed. The electrical conductivity of the sensor was measured when the sensor was stretched using a strain universal testing machine (Dacell Co. Ltd., Seoul, Korea) and a multimeter (Keysight Technologies, Santa Rosa, CA, USA) was used to measure resistance. It was found that the electrical conductivity of a sensor that was subjected to needling was at least 16 times better than that of a sensor that was not. In addition, the gauge factor was excellent, relative to the initial resistance of the sensor, so good performance as a sensor could be confirmed. Here, the dip-coating efficiency of hydrophobic materials, which have superior physical properties to hydrophilic materials but are not suitable due to their high surface tension, can be adopted to more effectively detect body movements and manufacture sensors with excellent durability and usability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.155-163
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• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2C
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• pp.109-120
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• 2006

SPT-Uphole test is a seismic field test using receivers on ground surface and a SPT (Standard penetration test) source in depth. Even though this method is simple and economic, it makes hesitate to apply in real field that it is difficult to obtain reliable travel time information of shear wave because of the characteristics of SPT impact source. To overcome this shortcoming, in this paper, modified SPT-Uphole method using two component surface geophones was suggested. Numerical analysis was performed using finite element method for understanding the characteristics of surface motion induced by in-depth vertical source, and comparison study of the various methods which determine the travel time information in SPT-Uphole method was performed. In result, it is thought that the most reasonable method is using the first local maximum point of the root mean square value signals of vertical and horizontal component in time domain. Finally, modified SPT-Uphole method using two component surface geophones was performed at the site, and the applicability in field was verified by comparing wave velocity profiles determined by the SPT-Uphole method with the profiles determined by SASW method and SPT-N values.

• Atmosphere
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• v.34 no.1
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.406-412
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• 2023

In this paper, we studied the effect of noise caused by ambient light on a reflective PPG measurement device using infrared light. Noise caused by ambient light was examined by dividing it into general situations and special situations. In the general situation, noise due to changes in time and ambient light sources was randomly observed, and in the special situation, a halogen lamp was used to observe the effect of noise variations. In the experiment, PPG signals were measured and data acquired in real-time depending on each situation, and the measured data was analyzed in the time domain and frequency domain. First, through a general situation experiments, it was visually observed that noise increases with the brightness of ambient light, and through frequency analysis, it was observed that the noise sources were white noise, power line noise, and internal noise of the circuit. Futhermore, using a halogen lamp, we experimented with the change in noise depending on the change in distance from the ambient light and calculated the SNR. As a result of the experiment, an SNR of 3.2 dB was shown at a distance of 50 cm with an irradiance of 278.3 W/m². It was observed that normal measurement was difficult at SNRs below that, and an irradiance of 27.7 W/m² was obtained. It showed a value of 18.2 dB at a distance of 2 m, and it was observed that normal PPG measurement was possible through a filter at values above that.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.740-754
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• 2009

Sound in the ocean is scattered by inhomogeneities of many different kinds, such as the sea surface, the sea bottom, or the randomly distributed bubble layer and school of fish. The total sum of the scattered signals from these scatterers is called reverberation. In order to simulate the reverberation signal precisely, combination of a propagation model with proper scattering models, corresponding to each scattering mechanism, is required. In this article, we develop a reverberation model based on the ray theory easily combined with the existing scattering models. Developed reverberation model uses (1) Chapman-Harris empirical formula and APL-UW model/SSA model for the sea surface scattering. For the sea bottom scattering, it uses (2) Lambert's law and APL-UW model/SSA model. To verify our developed reverberation model, we compare our results with those in Ellis' article and 2006 reverberation workshop. This verified reverberation model SNURM is used to simulate reverberation signal for the neighboring seas of South Korea at mid frequency and the results from model are compared with experimental data in time domain. Through comparison between experiment data and model results, the features of reverberation signal dependent on environment of each sea is investigated and this analysis leads us to select an appropriate scattering function for each area of interest.