• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.69-78
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• 2024

Recently, the use of CCTV to prevent crowd accidents has been promoted, but research is needed to compensate for the spatial limitations of CCTV. In this study, pedestrian density was measured using drone footage, and based on a review of existing literature, a threshold of 6.7 people/m² was selected as the cutoff risk level for crowd accidents. In addition, we conducted a preliminary study to determine drone parameters and found that the pedestrian recognition rate was high at a drone altitude of 20 meters and an angle of 60°. Based on a previous study, we selected a target area with a high concentration of pedestrians and measured pedestrian density, which was found to be 0.27~0.30 per m². The study shows it is possible to measure risk levels by determining pedestrian densities in target areas using drone images. We believe drone surveillance will be utilized for crowd safety management in the near future.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Journal of Korean Medicine Rehabilitation
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• v.34 no.2
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• pp.15-28
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• 2024

Objectives We used the D-galactose (D-gal) induced C2C12 myoblast senescence model to investigate whether ethanol extract of Perilla. fructescens leaves (EEPF) could delay cellular senescence and regulate related mechanisms. Methods C2C12 myogenic cells were cultured in an incubator under 37 ℃ and 5% CO₂ conditions. EEPF, dried perilla leaves were pulverized and extracted at 1:10 (v/v) at 50 ℃ for 4 hours. Cell counting kit-8 and western blot analysis was performed. Annexin V-FITC apoptosis detection kit and DAPI staining was applied. Catalase (CAT), glutathione peroxidase (GSH-Px), total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and malondialdehyde analysis kits were used. To measure the level of reactive oxygen species generation, staining and flow cytometry was used. To analyze the mitochondrial activity, membrane potential changes were measured using JC-1. 𝛽-gal activity was analyzed using SA-𝛽-gal staining solution, and DNA damage was analyzed by using 𝛾-H2AX. Quantikine ELISA kit was used to analyze inflammatory cytokine production. Results According to the results of this study, EEPF significantly alleviated the decrease in cell viability in C2C12 cells treated with D-gal and suppressed the decrease in the expression of proliferating cell nuclear antigen. EEPF also markedly blocked D-gal-induced C2C12 cell apoptosis and restored reduced activity of CAT, GSH-Px, T-AOC, SOD. In addition, EEPF suppressed the decrease in 𝛽-galactosidase activity, the induction of DNA damage and the increase in expression of senescence-associated secretory phenotype proteins such as p16, p53 and p21 in D-gal-treated C2C12 cells. Furthermore, EEPF significantly attenuated D-gal-induced production and expression of inflammatory cytokines such as interleukin (IL)-6 and IL-18. Conclusions The results of this study indicate that EEPF can be used as a potential candidate for the prevention and treatment of muscle aging.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.414-421
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• 2024

In this paper, we design and verify a system that can detect piping leakage noise in an environment with significant reverberation and reflection using a multi-channel acoustic sensor module as a technology to prevent major plant accidents caused by leakage. Four-channel microphones arranged in a tetrahedron are designed as a single sensor module to measure three-dimensional sound intensity vectors. In an environment with large effects of reverberation and reflection, the measurement error of each sensor module increases on average, so after placing multiple sensor modules in the field, measurement results showing locations with large errors due to effects such as reflection are excluded. Using the intersection between three-dimensional vectors obtained from several pairs of sensor modules, the coordinates where the sound source is located are estimated, and outliers (e.g., positions estimated to be outside the site, positions estimated to be far from the average position) are detected and excluded among the points. For achieving aforementioned goal, an excluding algorithm by deciding the outliers among the estimated positions was proposed. By visualizing the estimated location coordinates of the leakage sound on the site drawing within 1 second, we construct and verify a system that can detect the location of the leakage sound in real time and enable immediate response. This study is expected to contribute to improving accident response capabilities and ensuring safety in large plants.

• Herbal Formula Science
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• v.32 no.3
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• pp.235-245
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• 2024

Objective : The study's objective is to assess the components of Dendropanax morbifera (DM) utilizing UPLC-MS/MS and assess their antioxidant properties in order to establish fundamental information for quality control of herbal formulations. Methods : The DM leaves were ground into powder and extracted with water at 80℃. The extract was subsequently concentrated and subjected to freeze-drying for subsequent analysis. The LC-MS/MS analysis was performed using a 1260 series HPLC system and a 3200 QTrap tandem mass system in positive ion mode, with detection conducted at 280 nm. The Folin-Ciocalteu method was employed to measure the phenolic content, while a colorimetric method using aluminum chloride was used to determine the flavonoid content, with gallic acid and quercetin as standards, respectively. The evaluation of antioxidant activity was conducted through the measurement of DPPH radical scavenging activity, by adding the DPPH solution to the extract and recording the absorbance at 517 nm. Results : The UPLC-MS/MS analysis identified five polyphenolic compounds in the DM extract, specifically syringin, 6-hydroxyluteolin 7-O-laminaribioside, shaftoside, rutin, and kaempferol-3-O-rutinoside. The extract was found to contain a total phenolic content of 83.106 ± 0.21 mg GAE/g and a total flavonoid content of 87.963 ± 1.014 mg QE/g. The DM extract demonstrated substantial antioxidant properties, resulting in a reduction of DPPH radicals that was evident at concentrations as low as 40 ㎍/㎖. Conclusions : The study determined important polyphenolic compounds in DM and established its considerable antioxidant efficacy. These findings provide evidence for the efficacy of DM in disease prevention related to oxidative stress and establish a foundation for ensuring quality control in herbal preparations.

• Journal of the Mineralogical Society of Korea
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• v.28 no.3
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• pp.245-253
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• 2015

The performance of $TiO_2$ photo-catalytic oxidation process is significantly dependent on the amount of hydroxyl radicals produced during the process, and it is an essential prerequisite to quantify its production. However, precise and accurate methods for quantification of hydroxyl radicals have not been developed so far. For this reason, this study was initiated to compare existing methods for analysis of hydroxyl radicals produced by $TiO_2$ photo-catalytic oxidation and to propose a new method to overcome the limitation of established methods. To simulate $TiO_2$ photo-catalytic oxidation process, Degussa P25 which has been widely used as a standard $TiO_2$ photo-catalyst was used with the dose of 0.05 g/L. The light source of process was UVC mercury low-pressure lamp (11 W, $2,975mW/cm^2$). The results indicate that both potassium iodide (KI)/UV-vis spectrometer and terephthalic acid (TPA)/fluorescence spectrometer methods could be applied to qualitatively measure hydroxyl radicals via detection of triiodide ion ($I_3{^-}$) and 2-hydroxyterephthalic acid which are produced by reactions of iodine ion ($I^-$) and TPA with hydroxyl radicals, respectively. However, it was possible to quantitatively measure hydroxyl radicals using TPA method coupled with high-performance liquid chromatograph (HPLC). The analytical results using TPA/HPLC method show that hydroxyl radical of 0.013 M was produced after 8 hours operation of photo-catalytic oxidation under specific experimental conditions of this study. The proposed method is expected to contribute to precise the evaluation of the performance of photo-catalytic oxidation process.

• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.125-154
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• 2009

This paper describes the possibility of human physiological data, especially brain-wave activity, to detect cognitive overload, a phenomenon that may occur while learner uses an e-learning system. If it is found that cognitive overload to be detectable, providing appropriate feedback to learners may be possible. To illustrate the possibility, while engaging in cognitive activities, cognitive load levels were measured by EEG (electroencephalogram) to seek detection of cognitive overload. The task given to learner was a computerized listening and recall test designed to measure working memory capacity, and the test had four progressively increasing degrees of difficulty. Eight male, right-handed, university students were asked to answer 4 sets of tests and each test took from 61 seconds to 198 seconds. A correction ratio was then calculated and EEG results analyzed. The correction ratio of listening and recall tests were 84.5%, 90.6%, 62.5% and 56.3% respectively, and the degree of difficulty had statistical significance. The data highlighted learner cognitive overload on test level of 3 and 4, the higher level tests. Second, the SEF-95% value was greater on test3 and 4 than on tests 1 and 2 indicating that tests 3 and 4 imposed greater cognitive load on participants. Third, the relative power of EEG gamma wave rapidly increased on the 3rd and $4^{th}$ test, and signals from channel F3, F4, C4, F7, and F8 showed statistically significance. These five channels are surrounding the brain's Broca area, and from a brain mapping analysis it was found that F8, right-half of the brain area, was activated relative to the degree of difficulty. Lastly, cross relation analysis showed greater increasing in synchronization at test3 and $4^{th}$ at test1 and 2. From these findings, it is possible to measure brain cognitive load level and cognitive over load via brain activity, which may provide atimely feedback scheme for e-learning systems.

• Tuberculosis and Respiratory Diseases
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• v.51 no.6
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• pp.517-529
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• 2001

Background : Surfactant protein C(SP-C) is a hydrophobic 5,000 dalton molecule. SP-C has the primary roles in accelerating surface spreading of a surfactant phospholipid. The filter hybridization and solution hybridization assays are both rapid and sensitive and can be used to measure the RNAs complementary to any cloned DNA sequence. Methods : The authors measured the SP-C mRNA levels quantitatively using solution hybridization and filter hybridization assays to obtain a standard curve equation to quantify the mRNA of unknown samples comparatively. Results : 1. The minimum level of the specimens by solution hybridization was 3 pg for SP-C mRNA. 2. The standard curve equation of the solution hybridization assay between the counts per minute(Y) and the SP-C mRNA transcript input(X) was Y=6.46 X+244. The correlation coefficient was 0.99. 3. The minimum detection level of specimens by filter hybridization was 0.1 ng for SP-C mRNA. 4. The standard curve equation of the filter hybridization assay between the counts per minute(Y) and SP-C mRNA transcript input(X) is Y=2541.6 X+252.7. The correlation coefficient was 0.99. Conclusions : A comparison of CPM/filter in the linear range allowed an accurate and reproducible estimation of the SP-C mRNA copy number. Filter hybridization and solution hybridization assays are both rapid and sensitive and can be used to measure the RNAs complementary to any cloned DNA sequence. It is ideally suited to situations where accurate quantitation of multiple samples is required.