• Environmental Analysis Health and Toxicology
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• v.9 no.1_2
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• pp.37-51
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• 1994

To evaluate the genotoxicities of workers exposed to glue and glue cleaning solution, ambient air monitoring of working place, animal study and human monitoring were carried out. By GC-MS analysis, air samples collected from shoesmaking plant were found to be toluene, xylene, cyclohexane, n-hexane, methyl ethyl ketone, trichloroethylene, butylacetate, isopropyl alcohol. Glue and glue cleaning solution from shoesmaking plant were applicated topically to the CD-1 mice. DNA was isolated from skin 24 hr following the application and analysed for DNA-adducts using the nuclease $P_1$version of $^{32}$P-postlabelling assay. RAL (Relative Adduct Labelling, adducts$10^8$ nucleotides) was significantly increased in a dose-dependent manner in the glue cleaning solution treated mice skin. Peripheral blood DNA-adducts of workers exposed to glue and glue cleaning solution were also analysed by the same method, but there were not significant differences in the peripheral blood DNA-adducts level between exposed and control workers. In addition, glue cleaning solution from shoes factory was evaluated for mutagenicity in the Salmonella plate incorporation assay using strains TA 100 and TA 1535 in the presence and absence of Arochlor 1254-induced rat liver S$_{9}$. There was evident mutagenicity for cleaning solution in TA 100 regardless of $S_9$, but TA 1535 showed positive only in the absence of $S_9$when predicted by Stead model of mutagenicity prediction (p=0.0000). The urine concentrates from workers and controls were also assayed for mutagenicity towards strain TA 100 of Salmonella typhimurium in the presence of $S_9$ using Kado's microsuspension assay, but their mutagenic activities were not found to be significant. These data suggest that shoesmaking workers are exposed to genotoxic compounds and need to be monitored by testing the mutagenicity of human urines. However, $^{32}$P-postlabelling application requires further validation for the routine monitoring of human exposure.osure.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.499-509
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• 2019

This paper discusses energy use monitoring and analysis as part of a study on a low-cost energy supply management system that links an existing database with weather information with no real-time monitor for energy demand of buildings using renewable energy, generator and energy storage systems. This study is targeted at small and medium-sized buildings and aims to monitor energy use with a small number of sensors at low cost by applying an energy management system (EMS). The present study can help overcome the limitations of high-cost EMS applied to large commercial and public buildings. We developed current, indoor temperature and human motion sensors and installed them in an office of a company in a sample building. Through these sensors, we analyzed energy use patterns and the effects of weather information and human motion on the energy use. Furthermore, we analyzed the correlations between the total KEPCO energy use of the sample building and weather by comparing these two data. The results showed that the office energy use of a company was more affected by human motions than by weather information. The comparison between the total energy use of the Building and weather information found that external temperature had an effect on the energy use.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.27 no.1
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• pp.17-27
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• 2001

A cell-based assay system for monitoring NF-$textsc{k}$B activity was developed to determine the influence of activated NF-$textsc{k}$B in human HaCaT cells. The pNF-$textsc{k}$B-SEAP-NPT plasmid that permits expression of the secreted alkaline phosphatase (SEAP) reported gene in response to the NF-$textsc{k}$B activity and contains neomycin phosphotransferase (NPT) gene for the geneticin resistance in host cells was constructed and transfected into human keratinocyte cell line HaCaT. Human HaCaT transfectant cells secreted the SEAP enzyme into the culture medium in a time-dependent manner until 72h. NF-$textsc{k}$B activities were measured in the SEAP reporter gene assay using a fluorescent detection method. The treatment of HaCaT cell transfectants with known antioxidants [e.g., N-acetyl-L-cysteine and vitamin C] showed inhibition of NF-$textsc{k}$B activity in a time-and concentration-dependent manner. The phorbol 12-myristate 13-acetate (PMA) known as a stimulator of NF-$textsc{k}$B expression demonstrated that it increased NF-$textsc{k}$B activity in a time- and concentration-dependent manner. This assay system could be used to determine the quantitative measurement of NF-$textsc{k}$B activity in the human skin and allow the screening of anti-inflammatory agents from various synthetic chemicals and natural products for dermatological purpose. Abbrevitions used: NF-$textsc{k}$B, nuclear factor kappa B; I-$textsc{k}$B, Inhibitory kappa B; SEAP, secreted alkaline phosphatase; NPT, neomycin phosphotransferease; PCR, polymerase chain reaction: dNTP, deoxynucleoside triphosphates; DMEM, dulbecco’s modified eagle medium; FBS, fetal bovine serum; PBs, phosphate-buffered saline; MUP, 4-methylumbellifery phosphate; NAC, N-acetyl-L-cysteine; DMSO, dimethyl sulfoxide; PMA, phorbol 12-myristate 13-acetate.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.319-324
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• 2024

In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.22-31
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• 2023

Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.

• Journal of Ecology and Environment
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• v.41 no.3
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• pp.72-77
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• 2017

The world of technology is pleasantly evolving to a stage where small robotic aid may be used to ease the work of researchers, and to one day bring more accurate results than the current human abilities allow. In the research field of species monitoring in biology, unmanned aerial vehicles (UAVs) have begun to play an important role in how research is approached, analyzed, and then applied for further investigation, particularly by focusing on a single species. This paper uses data that has been collected from June to October 2015, to demonstrate how the innovative idea of using UAVs to monitor a particular species will bring a positive development in conservation research, and what it was able to achieve in this research field so far. More precisely, we examine the potential of UAVs to take center stage in future research, as well as their current accuracy. This paper describes the use of the commercially available Phantom 2 Vision+ for the detection, assessment, and monitoring of the butterfly species Libythea celtis, demonstrating how it can help the monitoring of butterflies and how it could be developed for even more adventurous and detailed research in the future.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Environmental Analysis Health and Toxicology
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• v.19 no.2
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• pp.161-167
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• 2004

Air quality monitoring is a primary activity for industrial and social environment. The government identifies the pollutants that each industry must monitor. Especially, the VOCs (Volatile Organic Compounds), which are very harmful to human body and environment atmosphere, should be controlled under the government policy. However, the VOCs, which have not been confirmed in emission sources are very difficult to monitor. It is needed to develop the monitoring system that allow the continuous and in situ measurement of VOCs mixture in different environmental matrices. Gas chromatography and mass spectrometry are the most prevalent current techniques among those available for the analysis of VOCs. But, they need a large size analytical instrument, which costs a great deal for purchase and operation. In addition, it has some limitations for realtime environmental monitoring such as location problems and slow processing time. Recently, several companies have commercialized a portable VOCs measurement systems, which cannot classify various kinds of VOCs but total quantities. We have developed a VOCs measurement system, which recognizes various kinds and quantities of VOCs, such as benzene, toluene, and xylene (BTX). Also, it can be used as a stand- alone type and/or fixed type in the vehicle with rack for real -time environmental monitoring.

• Journal of Soil and Groundwater Environment
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• v.18 no.2
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• pp.19-26
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• 2013

This study developed the classification of National Soil Quality Monitoring Network (NSQM) and its site selection criteria to meet the recently established purposes of the NSQM. The NSQM were suggested by this study to classify into the six-purposes site groups from the current classification of land uses. The six purposes site groups were 1) intensive observation sites, 2) contaminant loading sites, 3) human activity sites, 4) background sites, 5) river soil sites, and 6) sites near the groundwater quality monitoring wells. Furthermore, this study developed the site selection criteria of NSQM utilizing the accumulated NSQM data, road traffic data, chemical emission data, census, soil information, and the literature related to soil quality variation due to contaminant loads. For selecting suitable sites for NSQM, this study used road traffic, chemical emission, the distance from the contaminant sources, and population information as specific criteria. The suggested site classification and criteria were appled for the current 100 NSQM sites for evaluation. Forty sites were met to the criteria suggested by this study, but sixty sites were not met to the criteria. However, some of the sixty sites also included the obscure sites that their addresses were not apparent to find them.