• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.62-71
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• 2017

This study classified cities across South Korea according to their urban characteristics, selecting representative cities for respective types, and drawing a relationship among urban characteristic elements, carbon emissions, and the energy consumption of cities. For the classification of cities, the elements of the urban characteristics were examined through a review of the related literature. Factor analysis was then carried out to select the variables from among these elements. The absolute coefficient value found in the analysis was set as a standard. A classification of cities across the country was performed using these variables, and representative cities were chosen for a comparison of the characteristics of each type. For an analysis of the relationships among the urban characteristics according to the type of city, the greenhouse gases, and the energy consumption of cities, emissions of greenhouse gases, electricity consumption, and oil consumption of the representative cities were compared and analyzed by correlation analysis. The analysis results indicated that the cause of greenhouse gas emissions and electricity consumption varies according to the elements of the characteristics of the representative cities, even when they show similar emissions and consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4865-4885
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• 2019

We propose a FPGA based design that performs real-time power-efficient analysis of heterogeneous sensor data using adaptive ANN on edge gateway of smart military wearables. In this work, four independent ANN classifiers are developed with optimum topologies. Out of which human activity, BP and toxic gas classifier are multiclass and ECG classifier is binary. These classifiers are later integrated into a single adaptive ANN hardware with a select line(s) that switches the hardware architecture as per the sensor type. Five versions of adaptive ANN with different precisions have been synthesized into IP cores. These IP cores are implemented and tested on Xilinx Artix-7 FPGA using Microblaze test system and LabVIEW based sensor simulators. The hardware analysis shows that the adaptive ANN even with 8-bit precision is the most efficient IP core in terms of hardware resource utilization and power consumption without compromising much on classification accuracy. This IP core requires only 31 microseconds for classification by consuming only 12 milliwatts of power. The proposed adaptive ANN design saves 61% to 97% of different FPGA resources and 44% of power as compared with the independent implementations. In addition, 96.87% to 98.75% of data throughput reduction is achieved by this edge gateway.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1771-1776
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• 2017

Recently, IoT(Internet of Things) has been utilized in various fields provide a service to users by configuring a smart environment in a particular place. However, since the existing system does not change the operation and the task of the device according to the change of the surrounding environment, the user must operate passively every time the environment and the situation change. In this paper, we propose Situation-specific Task Control System based on real-time data classification. Sensor data is sent to the server and classified into real-time and non-real-time data, and then inserted into the decision tree to identify tasks according to the situation. In addition, the danger situation is divided into two stages, such as gas leakage and fire, and a warning message is sent. Therefore, it is possible to reduce the waste of electric power and the occurrence of malfunction, and it can be expected that the service with increased work efficiency will be provided.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.5
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• pp.303-313
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• 2021

Recently, quality control of the Liquefied Natural Gas Carrier (LNGC) cargo hold and block-erection interference areas using 3D scanners have been performed, focusing on large shipyards and the international association of classification societies. In this study, as a part of the research on LNGC cargo hold quality management advancement, a study on deep-learning-based scaffolding system 3D point cloud object detection and post-processing were conducted using a LNGC cargo hold 3D point cloud. The scaffolding system point cloud object detection is based on the PointNet deep learning architecture that detects objects using point clouds, achieving 70% prediction accuracy. In addition, the possibility of improving the accuracy of object detection through parameter adjustment is confirmed, and the standard of Intersection over Union (IoU), an index for determining whether the object is the same, is achieved. To avoid the manual post-processing work, the object detection architecture allows automatic task performance and can achieve stable prediction accuracy through supplementation and improvement of learning data. In the future, an improved study will be conducted on not only the flat surface of the LNGC cargo hold but also complex systems such as curved surfaces, and the results are expected to be applicable in process progress automation rate monitoring and ship quality control.

• Safety and Health at Work
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• v.10 no.3
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• pp.305-313
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• 2019

Background: The oil and gas industry is one of the riskiest industries for confined space injuries. This study aimed to understand an overall picture of the causal factors of confined space accidents through analyzing accident reports and the use of a qualitative approach. Methods: Twenty-one fatal occupational accidents were analyzed according to the Human Factors Analysis and Classification System approach. Furthermore, thirty-three semistructured interviews were conducted with employees in different roles to capture their experiences regarding the contributory factors. The content analyses of the interview transcripts were conducted using MAXQDA software. Results: Based on accident reports, the largest proportions of causal factors (77%) were attributed to the organizational and supervisory levels, with the predominant influence of the organizational process. We identified 25 contributory factors in confined space accidents that were causal factors outside of the original Human Factors Analysis and Classification System framework. Therefore, modifications were made to deal with factors outside the organization and newly explored causal factors at the organizational level. External Influences as the fifth level considered contributory factors beyond the organization including Laws, Regulations and Standards, Government Policies, Political Influences, and Economic Status categories. Moreover, Contracting/Contract Management and Emergency Management were two extra categories identified at the organizational level. Conclusions: Preventing confined space accidents requires addressing issues from the organizational to operator level and external influences beyond the organization. The recommended modifications provide a basis for accident investigation and risk analysis, which may be applicable across a broad range of industries and accident types.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1516-1516
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• 2001

During the recent years, wine analysis has played an increasing role due the health benefits of phenolic ingredients in red wine [1]. On the other hand there is the need to be able to distinguish between different wine varieties. Consumers want to know if a wine is an adulterated one or if it is based on the pure grape. Producers need to certificate their wines in order to ensure compliance with legal regulations. Up to now, the attempts to investigate the origin of wines were based on high-performance liquid chromatography (HPLC), gas chromatography (GC) and pyrolysis mass spectrometry (PMS) [l,2,3]. These methods need sample pretreatment, long analysis times and therefore lack of high sample throughput. In contradiction to these techniques using near infrared spectroscopy (NIRS), no sample pretreatment is necessary and the analysis time for one sample is only about 10 seconds. Hence, a near infrared spectroscopic method is presented that allows a fast classification of wine varieties in bottled red wines. For this, the spectra of 50 bottles of Cabernet Sauvignon, Lagrein and Sangiovese (Chianti) were recorded without any sample pretreatment over a wavelength range from 1000 to 2500 nm with a resolution of 12 cm$\^$-1/. 10 scans were used for an average spectrum. In order to yield best reproducibility, wines were thermostated at 23$^{\circ}C$ and a optical layer thickness of 3 mm was used. All recorded spectra were partitioned into a calibration and validation set (70% and 30%). Finally, a 3d scatter plot of the different investigated varieties allowed to distinguish between Cabernet Sauvignon, Lagrein and Sangiovese (Chianti). Considering the short analysis times this NRS-method will be an interesting tool for the quality control of wine verification and also for experienced sommeliers.

• Journal of the Korean Institute of Gas
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• v.17 no.6
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• pp.73-82
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• 2013

With remarkable development of industry and technology, various chemical articles are developed to improve the quality of human life, yet some of chemicals are hazardous to human and the environment. However, safety control of chemical articles such as transportation, storage, and handling is emerging as a major issue lately. The road transportation needs well-organized safety management system, especially it has high probability of accidents. In this research, we point out problems in current state and related regulation of transportation of dangerous goods to compare the regulation in UN-RTDG. In addition, we suggest the enhancement law, the plan for standardization of classification in road transportation of dangerous goods and harmonization of labeling in transportation of dangerous goods to contribute to human health and environment protection.

• Journal of Environmental Science International
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• v.1 no.2
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• pp.33-48
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• 1992

Since November 1990, the observations of methane (CH4) level have been carried out at Tae-ahn Peninsula (TAP) in Korea. Analysis on atmospheric data obtained in the period from November 1990 to August 1992 is carried out and the results are included in this study. We 임ole that CIL does not have a clear seasonal cycle with a minor maximum in August- september and with a minimum in June-July. The variations in monthly average level are much larger with 1765.01∼ 1857.21 pub (amplitude 92.20 ppb). The occurrence of a minimum in June-July is due to the inflow of the North Pacific air, an increase of OH radical and due to a decrease in CH4 emission from rice paddy. A maximum in August and September appears to result from an increase in organic materials in agriculture (rice paddy) and forests, inputs of local sources due to weak airflows, stagnation of the warm and moist air and from a decrease in OH radical.'rho present analysis indicates that according to CH4 data from Mongolia and from several sites in North Pacific TAP is influenced as much as 31 pub in average from the inputs of Chinese omission. When the atmospheric CH4 of TAP is compared with data observed at Korea National University of Education (KNU), the values of KNU are higher (127 ppb) than those of TAP. It is clear that air samples taken at KNU are influenced strongly by local sources in central Korea than those at TAP. According to analysis of trajectories and airflows, we find that there are 4 types in classification. Firstly, when an air flow is originated mainly in China values of CH4 gas are in medium ranges. Secondly, when an airflow is from both local (Korea) and China we find higher values. Thirdly, with an airflow from both local (Korea) and Japan origins medium values are recorded. Fourths)r, when an airflow of maritime origin arrives low values of atmospheric CH4 are observed at TAP.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.94-102
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• 2010

These days the land category is the most specific basis of legal for land use or land use form that is determined by the main use of land. Even if same land building site, it is used very various like a detached house, a row house, a multiplex house, a villa, an apartment, a mixed-use Apartments, commercial building, fallow land etc. There is a need of variety analysis in order to apply greenhouse gas emission or statistics assessment for standard of classification. Therefore, This study measured carbon dioxide by for different government agencies of maps by land use time, season, elevation, space, area of floating population. As a result, The emission characteristic was high l.78 times, on average of l.35 times in winter compared with summer, when the temperatures increased 11C, the carbon dioxide is 22ppm high in the afternoon, A commercial building is high 4.04 times compare with detached house.

• Journal of Ginseng Research
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• v.42 no.1
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• pp.57-67
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• 2018

Background: Ginseng contains many small metabolites such as amino acids, fatty acids, carbohydrates, and ginsenosides. However, little is known about the relationships between microorganisms and metabolites during the entire ginseng fermentation process. We investigated metabolic changes during ginseng fermentation according to the inoculation of food-compatible microorganisms. Methods: Gas chromatography mass spectrometry (GC-MS) datasets coupled with the multivariate statistical method for the purpose of latent-information extraction and sample classification were used for the evaluation of ginseng fermentation. Four different starter cultures (Saccharomyces bayanus, Bacillus subtilis, Lactobacillus plantarum, and Leuconostoc mesenteroide) were used for the ginseng extract fermentation. Results: The principal component analysis score plot and heat map showed a clear separation between ginseng extracts fermented with S. bayanus and other strains. The highest levels of fructose, maltose, and galactose in the ginseng extracts were found in ginseng extracts fermented with B. subtilis. The levels of succinic acid and malic acid in the ginseng extract fermented with S. bayanus as well as the levels of lactic acid, malonic acid, and hydroxypruvic acid in the ginseng extract fermented with lactic acid bacteria (L. plantarum and L. mesenteroide) were the highest. In the results of taste features analysis using an electronic tongue, the ginseng extracts fermented with lactic acid bacteria were significantly distinguished from other groups by a high index of sour taste probably due to high lactic acid contents. Conclusion: These results suggest that a metabolomics approach based on GC-MS can be a useful tool to understand ginseng fermentation and evaluate the fermentative characteristics of starter cultures.