• Journal of Korean Society for Atmospheric Environment
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• v.30 no.4
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• pp.378-386
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• 2014

The use of bus stop in the center lane has reduced the emissions of exhaust gas on the road due to the improvement of the traffic speed but has caused a health problem for the citizens who are waiting for the bus in the platform, and thus the air pollution control of bus stop in the center lane is emerging as a more important part. This study was conducted to investigate the air pollution degree for the center lane-bus stops in four regions using mobile air measuring vehicle, and to evaluate the characteristics of air pollution by comparing with the data measured at the urban air monitoring site close to the bus stops. In addition, the correlation analysis was performed to analyze the impact to neighboring region by vehicle exhaust gas. The regional mean concentration of nitrogen dioxide in the center lane-bus stops ranged from 0.025 to 0.043 ppm which shows from 2.5 times to 5.3 times higher than the values of urban air monitoring site selected as a control group. The regional mean concentration of ozone in the center lane-bus stops ranged from 0.023 to 0.034 ppm which shows from 3% to 28% lower than the values of urban air monitoring site selected as a control group. The concentrations of nitrogen dioxide and ozone for the sampling regions did not exceed one hour-air quality environmental standard (0.1 ppm). The mean concentration of particulate matter for four center lane-bus stops was $28{\mu}g/m^3$ which shows about 27% higher than the values of urban air monitoring site selected as a control group, and that of particulate matter did not exceed one day-air quality environmental standard ($100{\mu}g/m^3$). In the results of correlation analysis between data from center lane-bus stops and data from urban air monitoring sites, the correlation coefficient (r) of nitrogen dioxide was relatively low as 0.316 to 0.416, and the correlation coefficient was high as the distance was close and vice versa. However, the correlation coefficient of ozone ranged from 0.167 to 0.658 and the correlation coefficient was high as the distance was far and vice versa.

• Journal of the HCI Society of Korea
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• v.12 no.4
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• pp.65-73
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• 2017

While electricity demand is generally increasing, stably controlling supply is becoming a serious challenge because renewable energies are becoming popular and often their productions are dependent on the weather. The 'demand response' programs can be used to complement the problems of renewable energies, and therefore their role is becoming increasingly important. This study provides an analysis of a demand response pilot that was conducted in Korea. The study first focused on questionnaire surveys and in-depth interviews, and the data was used to perform a Technology Acceptance Model (TAM) analysis. The goal of the pilot was to have the residential users reduce their power consumptions when an energy reduction mission is issued during peak load hours. The experimental subjects consisted of two groups with different characteristics. Subjects in group A obtained smart meters as an optional function of IoT platform service provided by a mobile service company, and received a charge deduction as their compensation. Subjects in group B either voluntarily purchased smart meters as individuals or received them by participating in an energy self-sufficient village program that was run by a local government, and were entitled to a donation as their compensation. With the analysis, group A was found to fit the extended technology acceptance model that includes perceived playfulness in addition to perceived ease of use and perceived usefulness. On the contrary, group B failed to fit the model well, but perceived usefulness was found to be relatively more important compared to group A. The results indicate that the residential energy groups' behavior changes are dependent on each group's characteristics, and group-specific DR design should be considered to improve the effectiveness of DR.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.226-245
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• 2019

To understand the dynamics of radial growth of trees and micro-climate at a site of Korean fir (Abies koreana Wilson) forest on high-altitude area of Mt. Hallasan National Park, Jeju Island, Korea, high precision dendrometers were installed on the stems of Korean fir trees, and the sensors for measuring micro-climate of the forest at 10 minutes interval were also installed at the forest. Data from the sensors were sent to nodes, collected to a gateway wireless, and transmitted to a data server using mobile phone communication system. By analyzing the radial growth data for the trees during the growing season in 2016, we can estimate that the radial growth of Korean fir trees initiated in late April to early May and ceased in late August to early September, which indicates that period for the radial growth was about 4 months in 2016. It is interesting to observe that the daily ambient temperature and the daily soil temperature at the depth of 20 cm coincided with the values of about 10 ℃ when the radial growth of the trees initiated in 2016. When the radial growth ceased, the values of the ambient temperature went down below about 15 ℃ and 16 ℃, respectively. While the ambient temperature and the soil temperature are evaluated to be the good indicators for the initiation and the cessation of radial growth, it becomes clear that radii of tree stems showed diurnal growth patterns affected by diurnal change of ambient temperature. In addition, the wetting and drying of the surface of the tree stems affected by precipitation became the additional factors that affect the expansion and shrinkage of the tree stems at the forest site. While it is interesting to note that the interrelationships among the micro-climatic factors at the forest site were well explained through this study, it should be recognized that the precision monitoring made possible with the application of high resolution sensors in the measurement of the radial increment combined with the observation of 10 minutes interval with aids of information and communication technology in the ecosystem observation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1341-1349
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• 2011

This research is focused on an analysis on the structure of RAW image file and the development of a RAW image file viewer for an embedded device. Recently, several RAW image file formats are being used for saving and displaying the images created by various DSLR cameras, and the necessity of handing RAW images in mobile multimedia devices is increasing. For the development of RAW image decoding/encoding library applicable to WinCE-based embedded devices viewer, an analysis of RAW image file formats, such as CRW, CR2, PEF, NEF, MRW, have been performed because their formats are not released in public. By using the library, the analysis software which can extract RAW image data, 2~3 JPEG image files and other informations such as the specification of a camera and various photographic parameters from RAW image files, were developped and a RAW image file viewer which can run in WinCE-based embedded devices. The experimental result has shown that the viewer could encode and decode RAW image files successfully and it took approximately 10secs to load them to the screen in S3C6410 based embedded platform. The outcomes of this research cloud be a good information and solution to multimedia application developers.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.23-31
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• 2020

The need for personalized recommendation is growing due to convenient access and various types of items due to the development of information communication and smartphones. Weather and weather conditions have a great influence on the decision-making of users' places and activities. This weather information can increase users' satisfaction with recommendations. In this paper, we propose a collaborative filtering-based place recommendation system using living index by utilizing living index of users' location information on mobile platform to find users with similar propensity and to recommend places by predicting preferences for places. The proposed system consists of a weather module for analyzing and classifying users' weather, a recommendation module using collaborative filtering for place recommendations, and a management module for user preferences and post-management. Experiments have shown that the proposed system is valid in terms of the convergence of collaborative filtering algorithms and living indices and reflecting individual propensity.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.313-321
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• 2014

In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.63-70
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• 2011

A bicycle is different from vehicles in the structure that a rider is fully exposed to the surrounding environment. Therefore, it needs to make use of prior information about local weather, air quality, trail road condition. Moreover, since it depends on human power for moving, it should acquire route property such as hill slope, winding, and road surface to improve its efficiency in everyday use. Recent mobile applications which are to be used during bicycle riding let us aware of the necessity of development of intelligent bicycles. This study aims to develop a riding state (up-hill, down-hill, accelerating, braking) recognition algorithm using a low-power wrist watch type embedded system which has 3-axis accelerometer and wireless communication capability. The developed algorithm was applied to 19 experimental riding data and showed more than 95% of correct recognition over 83.3% of the total dataset. The altitude and temperature sensor also in the embedded system mounted on the bicycle is being used to improve the accuracy of the algorithm. The developed riding state recognition algorithm is expected to be a platform technology for intelligent bicycle interface system.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7853-7857
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• 2015

Background: Mortality from breast cancer is high in low- and middle-income countries, in part because most patients have advanced stage disease when first diagnosed. Case-finding may be one approach to changing this situation. Materials and Methods: We conducted a pilot study to explore the feasibility of population-based case finding for breast cancer by community health workers (CHWs) using different data collection methods and approaches to management of women found to have breast abnormalities. After training 8 CHWs in breast problem recognition, manual paper data collection and operation of a cell-phone software platform for reporting demographic, history and physical finding information, these CHWs visited 3150 women >age 18 and over they could find-- from 2356 households in 8 villages in rural Bangladesh. By 4 random assignments of villages, data were collected manually (Group 1), or with the cell-phone program alone (Group 2) or with management algorithms (Groups 3 and 4), and women adjudged to have a serious breast problem were shown a motivational video (Group 3), or navigated/accompanied to a breast problem center for evaluation (Group 4). Results: Only three visited women refused evaluation. The manual data acquisition group (1) had missing data in 80% of cases, and took an average of 5 minutes longer to acquire, versus no missing data in the cell phone-reporting groups (2,3 and 4). One woman was identified with stage III breast cancer, and was appropriately treated. Conclusions: Among very poor rural Bangladeshi women, there was very limited reluctance to undergo breast evaluation. The estimated rarity of clinical breast cancer is supported by these population-based findings. The feasibility and efficient use of mobile technology in this setting is supported. Successor studies may most appropriately be trials focusing on improving the suggested benefits of motivation and navigation, on increasing the numbers of cases found, and on stage of disease at diagnosis as the primary endpoint.

• Journal of IKEEE
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• v.24 no.2
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• pp.638-648
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• 2020

Currently, the method of user-follwoing in intelligent cooperative robots usually based in vision system and using Lidar is common and have excellent performance. But in the closed space of Corona 19, which spread worldwide in 2020, robots for cooperation with medical staff were insignificant. This is because Medical staff are all wearing protective clothing to prevent virus infection, which is not easy to apply with existing research techniques. Therefore, in order to solve these problems in this paper, the ultrasonic sensor is separated from the transmitting and receiving parts, and based on this, this paper propose that estimating the user's position and can actively follow and cooperate with people. However, the ultrasonic sensors were partially applied by improving the Median filter in order to reduce the error caused by the short circuit in communication between hard reflection and the number of light reflections, and the operation technology was improved by applying the curvature trajectory for smooth operation in a small area. Median filter reduced the error of degree and distance by 70%, vehicle running stability was verified through the training course such as 'S' and '8' in the result.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.25-33
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• 2013

The procedure of the arbitration which is the tag collision is essential because the multiple tags response simultaneously in the same frequency to the request of the Reader. This procedure is known as Anti-collision and it is a key technology in the RFID system. In this paper, we propose the 4-Bit Pattern Slot Allocation(4-BPSA) algorithm for the high-speed identification of the multiple tags. The proposed algorithm is based on the tree algorithm using the time slot and identify the tag quickly and efficiently through accurate prediction using the a slot as a 4-bit pattern according to the slot allocation scheme. Through mathematical performance analysis, We proved that the 4-BPSA is an O(n) algorithm by analyzing the worst-case time complexity and the performance of the 4-BPSA is improved compared to existing algorithms. In addition, we verified that the 4-BPSA is performed the average 0.7 times the query per the Tag through MATLAB simulation experiments with performance evaluation of the algorithm and the 4-BPSA ensure stable performance regardless of the number of the tags.