• Nano
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• v.13 no.10
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• pp.1850122.1-1850122.6
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• 2018

Vertically aligned $WO_3$-CuO core-shell nanorod arrays for $NH_3$ sensing are prepared. The sensor is fabricated by preparing $WO_3$-CuO nanorod arrays directly on silicon wafer with interdigital Pt electrodes. The $WO_3$-CuO nanorod arrays are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). The sensor based on the vertically aligned $WO_3$-CuO nanorod arrays exhibits ultrasensitive $NH_3$ detection, indicating p-type behavior. The optimum sensing temperature is found to be about $150^{\circ}C$. Both response and recovery time to $NH_3$ ranging from 50 ppm to 500 ppm are around 10-15 s. A possible $NH_3$ sensing mechanism of the vertically aligned hybrid nanorod arrays is proposed.

• Architectural research
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• v.20 no.4
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• pp.109-120
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• 2018

In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.

• Journal of Industrial and Engineering Chemistry
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• v.67
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• pp.417-428
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• 2018

In this study, we fabricated hierarchically self-assembled thin films composed of graphene oxide (GO) sheets and gold nanoparticles (Au NPs) using the Langmuir-Blodgett (LB) and Langmuir-Schaefer (LS) techniques and investigated their gas-sensing performance. First, a thermally oxidized silicon wafer ($Si/SiO_2$) was hydrophobized by depositing the LB films of cadmium arachidate. Thin films of ligand-capped Au NPs and GO sheets of the appropriate size were then sequentially transferred onto the hydrophobic silicon wafer using the LB and the LS techniques, respectively. Several different films were prepared by varying the ligand type, film composition, and surface pressure of the spread monolayer at the air/water interface. Their structures were observed by scanning electron microscopy (SEM) and atomic force microscopy (AFM), and their gas-sensing performance for $NH_3$ and $CO_2$ was assessed. The thin films of dodecanethiol-capped Au NPs and medium-sized GO sheets had a better hierarchical structure with higher uniformity and exhibited better gas-sensing performance.

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.14-18
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• 2020

This study investigates the nitrogen dioxide (NO₂) sensing characteristics of an Si MOSFET gas sensor with a tungsten trioxide (WO₃) sensing layer deposited using the sputtering method. The Si MOSFET gas sensor consists of a horizontal floating gate (FG) interdigitated with a control gate (CG). The WO₃ sensing layer is deposited on the interdigitated CG-FG of a field effect transistor(FET)-type gas sensor platform. The sensing layer is deposited with different thicknesses of the film ranging from 100 nm to 1 ㎛ by changing the deposition times during the sputtering process. The sensing characteristics of the fabricated gas sensor are measured at different NO₂ concentrations and operating temperatures. The response of the gas sensor increases as the NO₂ concentration and operating temperature increase. However, the gas sensor has an optimal performance at 180℃ considering both response and recovery speed. The response of the gas sensor increases significantly from 24% to 138% as the thickness of the sensing layer increases from 100 nm to 1 ㎛. The sputtered WO₃ film consists of a dense part and a porous part. As reported in previous work, the area of the porous part of the film increases as the thickness of the film increases. This increased porous part promotes the reaction of the sensing layer with the NO₂ gas. Consequently, the response of the gas sensor increases as the thickness of the sputtered WO₃ film increases.

• Atmosphere
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• v.17 no.2
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• pp.125-133
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• 2007

Cloud amount calculation algorithm was developed using MTSAT-1R satellite data. The cloud amount is retrieved at 5 km ${\times}$ 5 km over the Korean Peninsula and adjacent sea area. The algorithm consists of three steps that are cloud detection, cloud type classification, and cloud amount calculation. At the first step, dynamic thresholds method was applied for detecting cloud pixels. For using objective thresholds in the algorithm, sensitivity test was performed for TBB and Albedo variation with temporal and spatial change. Detected cloud cover was classified into 3 cloud types (low-level cloud, cirrus or uncertain cloud, and cumulonimbus type high-level cloud) in second step. Finally, cloud amount was calculated by the integration method of the steradian angle of each cloud pixel over $3^{\circ}$ elevation. Calculated cloud amount was compared with measured cloud amount with eye at surface observatory for the validation. Bias, RMSE, and correlation coefficient were 0.4, 1.8, and 0.8, respectively. Validation results indicated that calculated cloud amount was a little higher than measured cloud amount but correlation was considerably high. Since calculated cloud amount has 5km ${\times}$ 5km resolution over Korean Peninsula and adjacent sea area, the satellite-driven cloud amount could show the possibility which overcomes the temporal and spatial limitation of measured cloud amount with eye at surface observatory.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1239-1249
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• 2018

Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.694-706
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• 2022

This study focusses on the development of a motion-sensing smart leggings prototype with the help of a module that monitors motion using a fiber-type stretch sensor. Additionally, it acquires data on Electrocardiogram (ECG), respiration, and body temperature signals, for the development of smart clothing used in online exercise coaching and customized healthcare systems. The research process was conducted in the following order: 1) Fabrication of a fiber-type elastic strain sensor for motion monitoring, 2) Positioning and attaching the sensor, 3) Pattern development and three-dimensional (3D) design, 4) Prototyping 5) Wearability test, and 6) Expert evaluation. The 3D design method was used to develop an aesthetic design, and for sensing accurate signal acquisition functions, wearability tests, and expert evaluation. As a result, first, the selection or manufacturing of an appropriate sensor for the function is of utmost importance. Second, the selection and attachment method of a location that can maximize the function of the sensor without interfering with any activity should be studied. Third, the signal line selection and connection method should be considered, and fourth, the aesthetic design should be reflected along with functional verification. In addition, the selection of an appropriate material is important, and tests for washability and durability must be made. This study presented a manufacturing method to improve the functionality and design of smart clothing, through the process of developing a prototype of motion-sensing smart leggings.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.617-620
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• 2017

The periodic monitoring of crop conditions and timely estimation of crop yield are of great importance for supporting agricultural decision-makings, as well as for effectively coping with food security issues. Remote sensing has been regarded as one of effective tools for crop condition monitoring and crop type classification. Since 2010, RDA (Rural Development Administration) has been developing technology for monitoring on crop condition using remote sensing and model. These special papers address recent state-of-the-art of remote sensing and geospatial technologies for providing operational agricultural information, such as, crop yield estimation methods using remote sensing data and process-oriented model, crop classification algorithm, monitoring and prediction of weather and climate based on remote sensing data,system design and architecture of crop monitoring system, history on rice yield forecasting method.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.3
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• pp.66-78
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• 1995

In this paper, we address vehicle modeling and dynamic analysis of four wheel steering systems (4WS). 4WS is one of the devices used for the improvement of vehicle maneuverability and stability. All research done here is based on a production vehicle from a manufacturer. To study actual system response, a three dimensional, full vehicle model was created. In past research of this type, simple, two dimensional, bicycle vehicle models were typically used. First, we modelled and performed a dynamic analysis on a conventional two wheel steering(2WS) vehicle. The modeling and analysis for this model and subsequent 4WS vehicles were performed using ADAMS(Automatic Dynamic Analysis of Mechanical Systems) software. After the original vehicle model was verified with actual experiment results, the rear steering mechanism for the 4WS vehicle was modelled and the rear suspension was changed to McPherson-type forming a four wheel independent suspension system. Three different 4WS systems were analyzed. The first system applied a mechanical linkage between the front and rear steering mechanisms. The second and third systems used, simple control logic based on the speed and yaw rate of the vehicle. 4WS vehicle proved dynamic results through double lane change test.

• Proceedings of the KSRS Conference
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• v.2
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• pp.930-933
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• 2006

A new algorithm for satellite microwave rainfall retrievals over the land of Taiwan using TMI (TRMM Microwave Imager) data on board TRMM (Tropical Rainfall Measuring Mission) satellite is described in this study. The scattering index method (Grody, 1991) was accepted to develop a rainfall estimation algorithm and the measurements from Automatic Rainfall and Meteorological Telemetry System (ARMTS) were employed to evaluate the satellite rainfall retrievals. Based on the standard products of 2A25 derived from TRMM/PR data, the rainfall areas over Taiwan were divided into convective rainfall area and stratiform rainfall areas with/without bright band. The results of rainfall estimation from the division of rain type are compared with those without the division of rain type. It is shown that the mean rainfall difference for the convective rain type is reduced from -6.2mm/hr to 1.7mm/hr and for the stratiform rain type with bright band is decreased from 10.7 mm/hr to 2.1mm/hr. But it seems not significant improvement for the stratiform rain type without bright band.