• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1005-1018
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• 2017

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver's driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle' fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle's fault and noxious gas emitted to the outside.

• Membrane Journal
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• v.13 no.3
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• pp.174-181
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• 2003

In this study the formation of the particle layer near the membrane surface was observed for the crossflow micro filtration module by the high speed video system. The microfiltration membrane of 0.2 {\mu}m$ nominal pore size and the 0.05 wt% solution of the polyacryl-copolymer particle distributed between 100 and 180 {\mu}m$ were used for the experiment. The feed rates were changed to 0.5, 0.75, 1.0, 1.25 and 1.5 cm/sec while the permeate rates were maintained at $20{\pm}3%$ of the feed rates, respectively, It was observed that the particles were accumulated rapidly on the membrane surface as the feed flow rate increased, but the particles were not accumulated at 0.5 cm/sec, Also, it was confirmed that almost all of the particles in the layer already formed during filtration were removed within 30 seconds as the feed flow rate increased to 1.88 cm/sec.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1256-1263
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• 2024

In the realm of Architecture, Engineering, and Construction (AEC) education, various factors play a crucial role in shaping students' acceptance of the learning environments facilitated by visualization technologies, such as virtual reality (VR). Works on leveraging the heterogeneous educational information (i.e., pedagogical data, student performance data, and student survey data) to identify essential factors influencing students' learning experience and performance in virtual environments are still insufficient. This research proposed KnowLearn, an interactive learning assistant system, to integrate an educational knowledge graph (KG) and a locally deployed large language model (LLM) to generate real-time personalized learning recommendations. As the knowledge base of KnowLearn, the educational KG accommodated multi-faceted educational information from twelve perspectives, such as the teaching content, students' academic performance, and their perceived confidence in a specific course from the AEC discipline. A heterogeneous graph attention network (HAN) was utilized to infer the latent information in the KG and, thus, identified the perceived confidence, intention to use, and performance in a relevant quiz as the top three indicators that significantly influenced students' learning outcomes. Based on the information preserved in the KG and learned from the HAN model, the LLM enhanced the personalization of recommendations concerning adopting virtual learning environments while protecting students' privacy. The proposed KnowLearn system is expected to feasibly provide enhanced recommendations on the teaching module design for educators from the AEC domain.

• Spatial Information Research
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• v.22 no.4
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• pp.39-47
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• 2014

The Yeongsan river estuary has a serious water quality problem due to the water stagnation and it is imperative to predict the changes of water quality for mitigating water pollution. EFDC(Environmental Fluid Dynamics Code) model was mainly utilized to predict the changes of water quality for the estuary. The EFDC modeling normally accompanies the large volume of modeling output. For checking the spatial distribution of the modeling results, post-processing for converting of the output is prerequisite and mainly post-processing program is EFDC_Explorer. However, EFDC_Explorer only shows the spatial distribution of the time series and this doesn't support overlay function with other thematic maps. This means the impossible to the connection analysis with a various GIS data and high dimensional analysis. Therefore, this study aims to develop a post-processing system of a EFDC output to use them as GIS layers. For achieving this purpose, a editing module for main input files, and a module for converting binary format into an ASCII format, and a module for converting it into a layer format to use in a GIS based environment, and a module for visualizing the reconfigured model result efficiently were developed. Using the developed system, result file is possible to automatically convert the GIS based layer and it is possible to utilize for water quality management.

• Annual Conference of KIPS
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• 2017.04a
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3435-3440
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• 2010

Unlike the electric method capable of checking only product defect, the real time optical metrology is suggested for measuring and visualizing vibration with respect to position of surface acoustic wave in RF device. The measuring limits and conditions for surface acoustic wave is given, and the interference and diffraction due to RF signal are analyzed by optical interpretation. A single mode laser and a 105MHz-center-frequency repeater filter were employed for experiments and theoretical analysis. In this paper, the optical metrology providing visual energy distribution and real time inspection for surface acoustic wave is proposed for development of high quality multi-service and multi-frequency RF module.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.5
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• pp.165-173
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• 2007

Flow characteristics inside a blower unit of an automotive HVAC module were investigated experimentally using a high-resolution PIV technique. The PIV system consists of a 2-head Nd:YAG laser, a high-resolution CCD camera, optics and a synchronizer. The prototype siroco-fan with forward-curved blades was operated under the same condition of real car. The scroll casing was made transparently for capturing clear flow images. The time-averaged velocity fields were measured in three cross sections. Flow is accelerated with going toward the outer wall of scroll due to centrifugal force and large pressure gradient formed in the region between the fan and the outer casing wall. The presence of the cut-off region and diffusing duct of fan outlet influences largely the flow structure inside the blower unit.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.591-596
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• 2012

Recently, the efficient management system for photovoltaic power plants has been required due to the continuously increasing construction of photovoltaic power plants. In this paper, we propose a cloud-based intelligent management system for many photovoltaic power plants. The proposed system stores the measured data of power plants using Hadoop HBase which is a column-oriented database, and processes the calculations of performance, efficiency, and prediction the amount of power generation by parallel processing based on Map-Reduce model. And, Web-based data visualization module allows the administrator to provide information in various forms.

• 한국가시화정보학회:학술대회논문집
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• 2007.11a
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• pp.105-108
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• 2007

To diagnose the vascular diseases from the viewpoint of hemodynamics, we need detailed quantitative hemodynamic information of related blood flows with a high spatial resolution of tens micrometer and a high temporal resolution in the order of millisecond. For investigating in-vivo hemodynamic phenomena of vascular circulatory diseases, a new diagnosing technique combining a medical radiography and PIV method was newly developed. This technique called 'Angiographic PIV system' consists of a medical X-ray tube, an X-ray CCD camera, a shutter module for generating double pulse-type X-ray, and a synchronizer. Through several preliminary tests, the feasibility of the Angiographic PIV technique was verified. For in-vivo applications to real blood flows, we developed tracer microcapsules, which were optimized to this system, made of a contrast material of iodine and a matrix material of PVA (polyvinylpyrrolidone). In near future, the Angiographic PIV technique will be used for understanding hemodynamic phenomena of vascular diseases and for their early detection.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.11
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• pp.1211-1216
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• 2013

In this study, a dynamic camera actuation system for simultaneous in situ image acquisition is developed to achieve real-time observation of transient liquid flow on a lab-on-a-disk. A disk-type electric circuit, namely circuit-on-a-disk, co-rotated with the lab-on-a-disk improves the dynamic image acquisition ability in terms of a frame rate. The circuit-on-a-disk is comprised of a camera connected with a motor, a microprocessor and a wireless communication module. The camera connected with the motor enables to realize dynamic tracking of a transient flow and real-time image acquisition. The obtained images can be simultaneously transferred by a video/audio transmitter unit to a personal computer. Also, the microprocessor receives signals from the personal computer, and then controls the focusing position of the camera. We are expecting that heaters, sensors, and light sources also can be integrated on the circuit-on-a-disk, and they will enable various functional actuations as well as precise image acquisition.