• Korean Journal of Occupational Health Nursing
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• v.25 no.1
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• pp.65-74
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• 2016

Purpose: The purpose of this study is to predict industrial accident rate using time series analysis. Methods: The rates of industrial accident and occupational injury death were analyzed using industrial accident statistics analysis system of the Korea Occupational Safety and Health Agency from 2001 to 2014. Time series analysis was done using the most recent data, such as raw materials of Economically Active Population Survey, Economic Statistics System of the Bank of Korea, and e-National indicators. The best-fit model with time series analysis to predict occupational injury was developed by identifying predictors when the value of Akaike Information Criteria was the lowest point. Variables into the model were selected through a series of expertises' consultations and literature review, which consisted of socioeconomic structure, labor force structure, working conditions, and occupational accidents. Results: Indexes at the meso- and macro-levels predicting well occurrence of occupational accidents and occupational injury death were labor force participation rate for ages 45-49 and budget for small scaled workplace support. The rates of industrial accident and occupational injury death are expected to decline. Conclusion: For reducing industrial accident continuously, we call for safe employment policy of economically active middle aged adults and support for improving safety work environment of small sized workplace.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.318-326
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• 2022

Marketing stress testing is a new method of identifying the company's strengths and weaknesses in a turbulent environment. Technically, this is a complex procedure, so it involves artificial intelligence and machine learning. The main problem is currently the development of methodological approaches to the development of the company's digital model, which will provide a framework for machine learning. The aim of the study was to identify and develop an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. This aim provided the company's activities to be considered as a set of elements (business processes, products) and factors that affect them (marketing environment). The article proposes an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. The proposed approach includes four main elements that are subject to parameterization: elements of the company's internal environment, factors of the marketing environment, the company' core competency and factors impacting the company. Matrices for evaluating the results of the work of expert groups to determine the degree of influence of the marketing environment factors were developed. It is proposed to distinguish between mega-level, macro-level, meso-level and micro-level factors depending on the degree of impact on the company. The methodological limitation of the study is that it involves the modelling method as the only one possible at this stage of the study. The implementation limitation is that the proposed approach can only be used if the company plans to use machine learning for marketing stress testing.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.242-252
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• 2009

The purpose of this study was to develop a Multi-metric Water Quality Assessment (MWQA) model and apply it to dataset sampled from Paldang and Daechung reservoir in 2008. The various water dataset used to this study included 5 year data sets (2003${\sim}$2007) in Korean reservoirs which were obtained from the Ministry of Environment, Korea. In this study, suggested MWQA model has 4 metrics that were composed of 4 parameters such as chemical, physical, biological, and hydrological variables. And, each of the variables attributed total phosphorus (TP) concentration in water, secchi depth (SD) measure in water, chlorophyll-${\alpha}$(Chl-${\alpha}$) concentration in water and the ratio of inflow of water into lakes and efflux of water from lakes, input/output (I/O). First, we established the criteria for trophic boundaries. The boundary between oligotrophic and mesotrophic categories was defined by the lower third of the cumulative distribution of the values. The mesotrophic-eutrophic boundary was defined by the upper third of the distribution. Second, each metric was given by a point-oligo=1, meso=3, eu=5. And then, obtained total score from each metric was divided 5 grade-Excellent, Good, Fair, Poor, and Very poor. As the results of applying the proposed MWQA model, the Paldang reservoir obtained "Fair" or "Poor" grade and Daechung reservoir obtained "Excellent" or "Good" grade. The suggested MWQA model through these procedures will enable to manage efficiently the reservoir. And, more studies such as metric numbers and attributes should be done for the accurate application of the new model.

• Clean Technology
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• v.24 no.3
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• pp.239-248
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• 2018

In this study, pervaporation experiments of water, ethanol and IPA (Isopropyl alcohol) single components and water/ethanol, water/IPA mixtures were carried out using zeolite 4A membranes developed by Fine Tech Co. Ltd. Those membranes were fabricated by hydrothermal synthesis (growth in hydrothermal condition) after uniformly dispersing the zeolite seeds on the tubular alumina supports. They have a pore size of about $4{\AA}$ by ion exchange of $Na^+$ to the LTA structure with Si/Al ratio of 1.0, and shows strong hydrophilic property. Physical characteristics of prepared membranes were evaluated by using SEM (surface morphology), porosimetry (macro- or meso- pore analysis), BET (micropore analysis), and load tester (compressive strength). Pervaporation experiments with various temperature and concentration conditions confirmed that the zeolite 4A membrane can selectively separate water from ethanol and IPA. Water/ethanol separation factor was over 3,000 and water/IPA separation factor was over 1,500 (50 : 50 wt%, initial feed concentration). Pervaporation behaviors of single components and binary mixtures were predicted using ACM (activity coefficient model), GMS (generalized Maxwell Stefan) model and DGM (Dusty Gas Model). The adsorption and diffusion coefficients of the zeolite top layer were obtained by parameter estimation using GA (Genetic Algorithm, stochastic optimization method). All the calculations were carried out using MATLAB 2018a version.

• Journal of the Korean Institute of Gas
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• v.8 no.3 s.24
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• pp.43-51
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• 2004

In this study, gas permeation and separation characteristics of $CO_2$ and $N_2$ on nano-porous TPABr(Tetrapropylammoniumbromide) templating silica/alumina composite membrane were studied by using GMS (Generalized Maxwell Stefan) model. Since the transport mechanisms of meso-porous alumina support are Knudsen diffusion and viscous diffusion(or poiseulle flow), they can be identified by DGM (dusty gas model). The transport mechanism of TPABr templating silica layer, which would contribute mainly to the separation of $N_2/CO_2$ mixture, showed surface diffusion rather than pore diffusion. Therefore, the oermeationjseparation mechanisms in multi-component suface diffusion were successfully analyzed by the GMS model. In the separation of $N_2/CO_2$ mixture using the composite membrane, $CO_2$, the strongadsorbate, was permeated through the membrane more than Na due to the pore-blocking phenomena of $CO_2$ by adsorption isotherm and solace diffusion.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.222-234
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• 2021

Airborne-pests can be introduced into Korea from overseas areas by wind, which can cause considerable damage to major crops. Meteorological models have been used to estimate the wind trajectories of airborne insects. The objective of this study is to analyze the effect of input settings on the prediction of areas where airborne pests arrive by wind. The wind trajectories were predicted using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The HYSPLIT model was used to track the wind dispersal path of particles under the assumption that brown plant hopper (Nilaparvata lugens) was introduced into Korea from sites where the pest was reported in China. Meteorological input data including instantaneous and average wind speed were generated using meso-scale numerical weather model outputs for the domain where China, Korea, and Japan were included. In addition, the calculation time intervals were set to 1, 30, and 60 minutes for the wind trajectory calculation during early June in 2019 and 2020. It was found that the use of instantaneous and average wind speed data resulted in a considerably large difference between the arrival areas of airborne pests. In contrast, the spatial distribution of arrival areas had a relatively high degree of similarity when the time intervals were set to be 1 minute. Furthermore, these dispersal patterns predicted using the instantaneous wind speed were similar to the regions where the given pest was observed in Korea. These results suggest that the impact assessment of input settings on wind trajectory prediction would be needed to improve the reliability of an approach to predict regions where airborne-pest could be introduced.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.629-642
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• 2018

Future variability of the spatial patterns of rainfall events is the point of water-related risks and impacts of climate change. Recent related researches are mostly conducted based on the outcomes from General Circulation Models (GCMs), especially Coupled Model Intercomparison Project, phase 5 (CMIP5) GCMs which are the most advanced version of climate modeling system. GCM data have been widely used for various studies as the data utility keep getting improved. Meanwhile the model performances especially for raw GCM outputs are rarely evaluated prior to the applications although the process would essential for reasonable use of model forecasts. This study attempt to quantitatively evaluate the skills of 29 CMIP5 GCMs in reproducing spatial climatologies of precipitation in East Asia. We used 3 different gridded observational data as the references available over the study area and calculated correlation and errors of spatial patterns simulated by GCMs. As a result, the study presented diversity of the GCM evaluation in the performance, rank, or accuracy by different configurations, such as target area, evaluation method, and observation data. Yet, we found that Hadley-centre affiliated models comparatively performs better for the meso-scale area in East Asia and MPI_ESM_MR and CMCC family showed better performance specifically for the korean peninsula. We expect that the results and thoughts of this study would be considered in screening suitable GCMs for specific area, and finally contribute to extensive utilization of the results from climate change related researches.

• Journal of Energy Engineering
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• v.12 no.3
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• pp.231-240
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• 2003

Reactivity of Char-CO$_2$ gasification of five coals for power generation was investigated with PTGA in the temperature range 850∼1000$^{\circ}C$ and the pressure range 0.5∼2.0 MPa. The effect of coal rank, initial char characteristics and pressure on the reaction rate was evaluated for five chars. The reactivity of low lank coal char was better than that of high rank coal char, and this could be explained with the initial pore structure and surface area of char. Meso/macro-pores of char seems to markedly affect char reactivity by way of providing channels for diffusion of reactant gas into the reactive surface area. For the range of tested pressure, the reaction rate is proportional to CO$_2$ partial pressure and the reaction order ranges from 0.4 to 0.7 for five chars. The effect of total pressure on the reaction rate was small, and kinetic parameters, based on the unreacted core model, were obtained for five chars.

• Computers and Concrete
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• v.8 no.6
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• pp.647-675
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• 2011

Our ability to predict hydration behavior is becoming increasingly relevant to the concrete community as modelers begin to link material performance to the dynamics of material properties and chemistry. At early ages, the properties of concrete are changing rapidly due to chemical transformations that affect mechanical, thermal and transport responses of the composite. At later ages, the resulting, nano-, micro-, meso- and macroscopic structure generated by hydration will control the life-cycle performance of the material in the field. Ultimately, creep, shrinkage, chemical and physical durability, and all manner of mechanical response are linked to hydration. As a way to enable the modeling community to better understand hydration, a review of hydration models is presented offering insights into their mathematical origins and relationships one-to-the-other. The quest for a universal model begins in the 1920's and continues to the present, and is marked by a number of critical milestones. Unfortunately, the origins and physical interpretation of many of the most commonly used models have been lost in their overuse and the trail of citations that vaguely lead to the original manuscripts. To help restore some organization, models were sorted into four categories based primarily on their mathematical and theoretical basis: (1) mass continuity-based, (2) nucleation-based, (3) particle ensembles, and (4) complex multi-physical and simulation environments. This review provides a concise catalogue of models and in most cases enough detail to derive their mathematical form. Furthermore, classes of models are unified by linking them to their theoretical origins, thereby making their derivations and physical interpretations more transparent. Models are also used to fit experimental data so that their characteristics and ability to predict hydration calorimetry curves can be compared. A sort of evolutionary tree showing the progression of models is given along with some insights into the nature of future work yet needed to develop the next generation of cement hydration models.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.305-312
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• 2018

The quality of the radar and profiler network was estimated to forecast difficult meteorological situations. A network of UHF Doppler wind profilers and Doppler weather radars have been deployed all over the Korean Peninsular, with dense spatial resolution between instruments. The radar network allows to retrieve the three dimensional dynamics and to analyze the numerical model outputs at small and meso scales. This work has seldom been performed in any other place of the world, with such a high resolution. The wind field from radar network is a good agreement with the background wind fields based on the numerical modeling. This study will be helpful to forecast severe weathers as well as local meteorological phenomena.