• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.909-917
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• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.955-963
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• 2017

Nowadays, fintech becomes the key technology of the mobile banking and payments. Financial market is moved to fintech-based non-face-to-face trade/payment from traditional face-to-face process in Korea. Core of this transition is the smartphones, which have several sensitive sensors for personal identifications such as fingerprint and iris recognition sensors. But it has some originated security risks by data path attacks, for instance, hacking and pharming. Multi-level certification and security systems are applied to avoid these threats effectively, while these protections can be cause of some inconvenience for non-face-to-face certifications and financing processes. In this paper, I confirmed that it have sensible differences correspond with the data connection paths such as WiFi networks and mobile communication networks of the smartphones, and I propose a gradual certification method which alleviates the inconvenience by risk-level definitions of the data-paths.

• The Journal of Bigdata
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• v.7 no.2
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• pp.205-215
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• 2022

The current development of digital platform-based online retail business leads to the rapid growth of freight demand and service innovation. With the demand for converged logistics technologies, our government supports R&D projects to innovate the logistics service. The digital platforms are developed based on their own standard process and data formats. It may cause interoperability and connectivity-related problems. In this research, the standard data flow to connect the data among systems is defined based on the standard process. Especially, data for connectivity is categorized into three groups, common data, connected data, and management data. It may be possible to enhance the applicability to the practical logistics business.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.32-41
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• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.543-550
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• 2009

The traditional simple extrapolation type short term quantitative rainfall forecast can not realize the evolution of rainfall generating weather system. To overcome the drawback of the linear extrapolation type rainfall forecasting model, the history of a weather system from sequential weather radar information and a polynomial regression technique were used to generate forecast fileds of x-directional, y-directional velocities and radar reflectivity which considered the nonlinear behavior related to the evolution of weather systems. Results demonstrated that test statistics of forecasts using the developed model is better than that of 2-CAPPI forecast. However there is still a large room to improve the forecast of spatial and temporal evolution of local storms since the model is not based on a fully physical approach but a statistical approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.311-316
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• 2006

Despite geospatial information systems are widely used in many different fields as a powerful tool for spatial analysis and decision-making, their capabilities to handle realistic 3-D urban environment are very limited. The objective of this work is to integrate the recent developments in 3-D modeling and visualization into GIS to enhance its 3-D capabilities. To achieve a photorealistic view, building models are collected from a pair of aerial stereo images. Roof and wall textures are respectively obtained from ortho-rectified aerial image and ground photography. This study is implemented by using ArcGIS as the work platform and ArcObjects and Visual Basic as development tools. Presented in this paper are 3-D geometric modeling and its data structure, texture creation and its association with the geometric model. As the results, photorealistic views of Purdue University campus are created and rendered with ArcScene.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.497-504
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• 2010

In this paper, the author presents a reliability estimation technique to analyze the effects of traffic loads on pavement mean life based on the national highway database of Suwon and Uijeongbu region from 1999 to 2008. The estimation of the mean life, its standard deviation and reliability for pavement sections are calculated by using an appropriate distribution, Lognormal distribution, based on reliability theory. Furthermore, the probability paper method and Maximum likelihood estimation are both used to estimate parameters. The author found that mean life of newly constructed sections and over-layed sections is about 6.5 to 7.9 years and 7.3 to 9.1 years, respectively. The author also ascertained that the results of cumulative failure probability for pavement life between the proposed methods and observed data are similar. Such an assessment methodology and measures based on reliability theory can provide useful information for maintenance plans in pavement management systems as long as additional life data on pavement sections are accumulated.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• Journal of The Geomorphological Association of Korea
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• v.26 no.4
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• pp.21-31
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• 2019

Timing of terrace formation is a key information for understanding the evolution of fluvial systems. In particular, dating strath terrace (i.e. timing of terrace abandonment) is more difficult than depositional terrace that is conventionally constrained by radiocarbon, OSL and other dating methods targeting samples within terrace deposit. Surface exposure dating utilizing cosmogenic ¹⁰Be provides more reliability because it can be applied directly to the surface of a fluvial terrace. Thus, this method has been increasingly used for alluvial deposits. As well as other geomorphic surfaces over the last decades. Some inherent conditions, however, such as post-depositional ¹⁰Be concentration (i.e. inheritance), surface erosion rate, and density change challenge the application of cosmogenic ¹⁰Be to depositional terrace surface against simple bedrock surface. Here we present the first application of ¹⁰Be depth profile dating to a thin-gravel covered strath terrace in Korea. Monte Carlo simulation (MCS) helped us in better constraining the timing of abandonment of the strath terrace, since which its surface stochastically denuded with time, causing unexpected change of ¹⁰Be production with depth. The age of the strath terrace estimated by MCS was 109 ka, ~4% older than the one (104 ka) calculated by simple depth profile dating, which yielded the best-fit surface erosion rate of 2.1 mm/ka. Our study demonstrates that the application of ¹⁰Be depth profile dating of strath terrace using MCS is more robust and reliable because it considers post-depositional change of initial conditions such as erosion rate.

• Fashion & Textile Research Journal
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• v.25 no.6
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• pp.673-689
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• 2023

To realize the traceability of sustainable textile products, this study presents a low-carbon process through energy savings in the textile material manufacturing process. Traceability is becoming an important element of Life Cycle Assessment (LCA), which confirms the eco-friendliness of textile products as well as supply chain information. Textile products with complex manufacturing processes require traceability of each step of the process to calculate carbon emissions and power usage. Additionally, an understanding of the characteristics of the product planning-manufacturing-distribution process and an overall understanding of carbon emissions sources are required. Energy use in the textile material manufacturing stage produces the largest amount of carbon dioxide, and the amount of carbon emitted from processes such as dyeing, weaving and knitting can be calculated. Energy saving methods include efficiency improvement and energy recycling, and carbon dioxide emissions can be reduced through waste heat recovery, sensor-based smart systems, and replacement of old facilities. In the dyeing process, which uses a considerable amount of heat energy, LNG, steam can be saved by using "heat exchangers," "condensate management traps," and "tenter exhaust fan controllers." In weaving and knitting processes, which use a considerable amount of electrical energy, about 10- 20% of energy can be saved by using old compressors and motors.