• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.3
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• pp.160-165
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• 2005

Schools have significant and serious indoor environmental health problem, of which indoor air quality (IAQ) in school building may affect the health of the students and indirectly affect learning performance. Schools are of special concern when regarding indoor exposure to air pollutants, because students are particularly sensitive to pollutants and spend a significant amount of time in that environment. Therefore researches for improvement of indoor air quality have been developed such as installation of air cleaning device, ventilation system, titanium dioxide(TiO2) coating and so on. However, it is difficult to evaluate the magnitude of improvement of indoor air quality in field study because indoor air quality can be affected by source generation, outdoor air level, ventilation, decay by reaction, temperature, humidity, mixing condition and so on. In this study, evaluation of reduction of formaldehyde emission rate in school indoor environments by far-Infrared ray coating material was carried out using mass balance model in indoor environment. we proposed the evaluation method of magnitude of improvement in indoor air quality, considering outdoor level and ventilation. Since simple indoor concentration measurements could not properly evaluate the indoor air quality, outdoor level and ventilation should be considered when evaluate the indoor air quality.

• Journal of Environmental Health Sciences
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• v.32 no.4 s.91
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• pp.275-281
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• 2006

Indoor air quality is the dominant contributor to total personal exposure because most people spend a majority of their time indoors. Especially exposure to indoor air can potentially pose a greater threat than exposure to ambient air when indoor environments have sources of contaminants. In this study, volatile organic compounds (VOCs) and formaldehyde (HCHO) within newly constructed apartment have been determined in 27 houses of apartment in Seoul from December 2004 to March 2005. The measured indoor air pollutants were HCHO, volatile organic compounds including benzene, toluene, styrene, xylene, ethylbenzene and sampled on the standard method of Ministry of Environment in Korea. The indoor levels for benzene, xylene, toluene, ethylbenzene, styrene, and HCHO have significant increase trend after 5 hours closing of windows and doors. Levels of measured air pollutants concentrations between living rooms and bedrooms have not shown significant difference. Spearman correlation coefficient among the measured air pollutants ranged from 0.303 to 0.946, indicating similar source in building materials.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.5
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• pp.304-313
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• 2010

During recent years, various studies have demonstrated that indoor chemical pollution causes health problem and also negatively affect the performance of work by occupants. Building materials have been concerned as indoor chemical sources. Some of guidelines and certification system has been developed and resulted as dramatic decrease of harmful indoor chemicals such as formaldehyde and volatile organic compounds. Also, Home furniture and electrical devices has been concerned as one the primary influence the indoor chemical concentration in residential spaces. It is found that various kinds of electric home appliances have a significant source of chemical emission in indoor environments. In this study, the methodologies of detecting harmful chemicals from various kinds of products has been developed with large chamber measurement system and suggest some of the evaluation method for the chemicals from the home appliances as TV sets.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.4
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• pp.311-322
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• 2010

The common life with modern urban residence, spending more than 80~90% of daily life in indoor environment, makes the importance of indoor air quality (IAQ) even higher. Many efforts have made to improve indoor air quality (IAQ), which requires those systematic approaches for field practice. A recent study reported that no general approach cannot be made for IAQ improvement due to the great deal of variety in different indoor environments. Those indoor spaces included in Korean IAQ regulation were classified based on their characteristics and the IAQ guideline was suggested for each group of indoor spaces. Apart from those indoor spaces, the classroom in elementary school has different characteristics. By introducing the systematic approaches, the elementary classroom was surveyed and analyzed to understand its characteristics in due IAQ consideration. Based on the characteristics, there are several IAQ control measures suggested, including ventilation operation, dust mat installation, and white board. $CO_2$ and airborne dust were monitored and analyzed in order to evaluate the effectiveness of each control measure to IAQ. It was found that the general level of $CO_2$ concentration was managed under the IAQ guideline by applying the ventilator operation. The ventilation was also effective to the fugitive airborne particulate in elementary classroom environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.63-73
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• 2017

In contemporary society, it is increasingly common to spend more time indoors. As such, there is a continually growing desire to build comfortable and safe indoor environments. Along with this trend, however, there are some serious indoor-environment challenges, such as the quality of indoor air and Sick House Syndrome. To address these concerns the government implements various systems to supervise and manage indoor environments. For example, green building certification is now compulsory for public buildings. There are three categories of green building certification related to indoor air in Korea: Health-Friendly Housing Construction Standards, Green Standard for Energy & Environmental Design(G-SEED), and Indoor Air Certification. The first two types of certification, Health-Friendly Housing Construction Standards and G-SEED, evaluate data in a drawing plan. In comparison, the Indoor Air Certification evaluates measured data. The certification using data from a drawing requires a considerable amount of time compared to other work. A 2D tool needs to be employed to measure the area manually. Thus, this study proposes an automatic assessment process using a Building Information Modeling(BIM) model based on 3D data. This process, using open source Industry Foundation Classes(IFC), exports data for the certification system, and extracts the data to create an Excel sheet for the certification. This is expected to improve the work process and reduce the workload associated with evaluating indoor air conditions.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.837-845
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• 2016

Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.

• Spatial Information Research
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• v.16 no.4
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• pp.455-465
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• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.283-288
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• 2013

In this study, we introduce a 3D micro-cell simulator for radio wave propagation analysis in indoor environments. Previous studies treat only the path loss between the transmitter and receiver in 2D geometry. We provide the simulation results of indoor propagation prediction based on various ITU-R Recommendations. Simulation results described here indicate that the low and high frequency bands give quite different characteristics in presented indoor geometry. The propagation loss as a function of distance has two distinct regions. It is similar to that occurring in free space within 5-20m of the transmitter, however, increases significantly as the electromagnetic waves become obstructed by the walls at distances further away in the next region.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.11-18
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• 2021

We propose a method that combines learning in a virtual environment and a real environment for indoor autonomous driving through reinforcement learning. In case of learning only in the real environment, it takes about 80 hours, but in case of learning in both the real and virtual environments, it takes 40 hours. There is an advantage in that it is possible to obtain optimized parameters through various experiments through fast learning while learning in a virtual environment and a real environment in parallel. After configuring a virtual environment using indoor hallway images, prior learning was carried out on the desktop, and learning in the real environment was conducted by connecting various sensors based on Jetson Xavier. In addition, in order to solve the accuracy problem according to the repeated texture of the indoor corridor environment, it was possible to determine the corridor wall object and increase the accuracy by learning the feature point detection that emphasizes the lower line of the corridor wall. As the learning progresses, the experimental vehicle drives based on the center of the corridor in an indoor corridor environment and moves through an average of 70 steering commands.