• Journal of Korean Biological Nursing Science
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• v.26 no.2
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• pp.71-82
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• 2024

Purpose: This study systematically analyzed the impact of aromatherapy on pain in individuals with diabetes. Methods: A search was performed in seven electronic databases based on the PICO-SD (Population, Intervention, Comparison, Outcome, Study Design) framework. The population (P) of interest was individuals with diabetes, and the intervention (I) included aromatherapy targeting pain reduction. The comparison (C) consisted of control groups that received no intervention, another intervention, or usual care. The outcome (O) measured was pain. The quality of the selected literature was assessed using the Joanna Briggs Institute checklist. In MIX 2.0 Pro, the pooled overall effect of pain was calculated using Hedge's g and a random-effects model, and heterogeneity was calculated using the Q statistic and Higgin's I2 values. Meta-regression and exclusion sensitivity analyses were performed. Results: Five articles and seven studies were included, showing a significant pooled overall effect of aromatherapy on diabetes-related pain (Hedge's g = -1.83, 95% CI: -2.76 to -0.91). Meta-regression demonstrated that effectiveness in reducing pain was associated with studies conducted in West Asia, those with IRB approval, and those receiving funding. Additionally, interventions involving subjects under 60, lavender oil (vs. turpentine oil or blended oils), massage therapy (vs. topical application), fewer hours per session, and more repeated measurements (vs. pre/post measurements) were associated with pain reduction. Conclusion: Aromatherapy, especially with lavender oil, effectively manages diabetes-related pain. Short-duration massage application is also effective. A personalized selection of oil type and application method could optimize therapeutic outcomes for individuals with diabetes.

• Journal of Distribution Science
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• v.22 no.7
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• pp.33-42
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• 2024

Purpose: The furniture industry has a huge potential for growth in Indonesia. Due to Indonesia's vast natural resources, furniture designers, makers, and retailers are given ease of access. The research analyzes the influence of service quality, promotion, product, and price on brand image and purchase intention in Indonesia's furniture distribution channels. Research design, data, and methodology: The variables used are service quality, promotion, product, price, brand image, and purchase intention. This research is cross-sectional research, which will be conducted among the furniture consumers in Indonesia, from the Instagram followers of a community as of 31 July 2023 with 837.5 thousand followers. The tools that will be used are surveys, conducted according to the sample size and processed using SMARTPLS 4 and the SEM-PLS model. Results: The findings urge that some variables have a significant influence on purchase intention directly but become less significant when influenced by brand image. Some variables can influence purchase intentions significantly through brand image, even if the certain variable did not have a significant influence on purchase intention directly. Conclusions: By knowing the significance of the variables towards brand image and purchase intention, ones with major influence can be implemented as a strategy to improve marketing in Indonesian furniture distributors.

• Advances in concrete construction
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• v.17 no.5
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• pp.245-255
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• 2024

The problem of carbonation-induced corrosion has become a concern in recent times, especially in the 21^st century, due to the increase in global temperatures and carbon dioxide (CO₂) concentration in the atmosphere possessing a significant threat to the durability of reinforced concrete (RC) structures worldwide, especially in inland tropical regions where carbonation is the most significant concrete degradation mechanism. Therefore, a study was conducted to predict the impact of global warming on the carbonation of RC structures in Lusaka, Zambia, and Tokyo, Japan. The Impact was estimated based on a carbonation meta-model that applies the analytic solution of Fick's 1st law using literature-based concrete mix design data and forecasted local temperature and CO₂ concentration data over a 100-year period with relative humidity assumed constant. The results showed that CO₂ diffusion increased between 17-31%, effecting a 40-45% rise in carbonation coefficient and a significant reduction in corrosion initiation time of 50-52% in the two cities. Moreover, for the same water-cement ratio, Lusaka showed almost twice higher carbonation coefficient values and one third shorter corrosion initiation time compared to Tokyo, mainly due to its higher temperature and low relative humidity. Additionally, the carbonation propagation depth at the end of 100 years was between 12-22 mm in Tokyo and 18-40 mm in Lusaka. These findings indicate that RC structures in these cities are at risk of rapid deterioration, especially in Lusaka, where they are more vulnerable.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.49-57
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• 2011

Stiff competition and skyrocketing prices of raw materials are increasingly demanding the optimal design and operation of iron and steel mills minimizing trial and error. Computer simulation can provide the methodology in accordance with requirements. The purpose of this paper is to suggest a simulator for the design and operation of the steelmaking and continuous casting mill. The simulator was developed using Arena, popular simulation software and input and output interface based on MS Excel. It allows easy access for the maintenance and extension of the model. One of distinct features of the proposed simulator is the inclusion of complex transportation modules composed of transfer cars and overhead cranes. The simulator can be used for evaluating various alternative designs of a projected mill via throughput analysis and material flow analysis. Also, one can utilize it effectively to search for the best product mix suitable for many types of situations. It could be an invaluable tool evaluating the performance of operation patterns and improving the accuracy.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• Smart Structures and Systems
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• v.25 no.2
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• pp.183-195
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• 2020

Mineral admixtures have been widely used to produce concrete. Pozzolans have been utilized as partially replacement for Portland cement or blended cement in concrete based on the materials' properties and the concrete's desired effects. Several environmental problems associated with producing cement have led to partial replacement of cement with other pozzolans. Furnace slag and fly ash are two of the pozzolans which can be appropriately used as partial replacements for cement in concrete. However, replacing cement with these materials results in significant changes in the mechanical properties of concrete, more specifically, compressive strength. This paper aims to intelligently predict the compressive strength of concretes incorporating furnace slag and fly ash as partial replacements for cement. For this purpose, a database containing 1030 data sets with nine inputs (concrete mix design and age of concrete) and one output (the compressive strength) was collected. Instead of absolute values of inputs, their proportions were used. A hybrid artificial neural network-genetic algorithm (ANN-GA) was employed as a novel approach to conducting the study. The performance of the ANN-GA model is evaluated by another artificial neural network (ANN), which was developed and tuned via a conventional backpropagation (BP) algorithm. Results showed that not only an ANN-GA model can be developed and appropriately used for the compressive strength prediction of concrete but also it can lead to superior results in comparison with an ANN-BP model.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.92-103
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• 2015

Box-Wilson experimental design method, known as central composite design, is the design of any information-gathering exercises where variation is present. This method was devised to gather as much data as possible in spite of the low design cost. This method was employed to model the effect of mixing factors on several performances of 60 MPa high strength self compacting concrete and to numerically calculate the optimal mix proportion. The nonlinear relations between factors and responses of HSSCC were approximated in the form of second order polynomial equation. In order to characterize five performances like compressive strength, passing ability, segregation resistance, manufacturing cost and density depending on five factors like water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content, the experiments were made at the total 52 experimental points composed of 32 factorial points, 10 axial points and 10 center points. The study results showed that Box-Wilson experimental design was really effective in designing the experiments and analyzing the relation between factor and response.

• Explosives and Blasting
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• v.25 no.1
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• pp.53-65
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• 2007

When doing a blasting demolition on RC structures made of scale models, scale model members considering both a proper scale factor and mechanical characteristics of materials have to be similar to prototype RC members to analyze the collapse behavior of RC structures. In this study. a similitude law considering the density of prototype materials is calculated. Both mix of concrete and arrangement of reinforcement have been described referring to Concrete Standard Specification as well as Design Standard of Concrete Structure. The scale factor on scaled concrete models considering maximum size of coarse aggregate is about one-fifth of a cross section of prototype concrete members. A scale factor on staled steel bar models is about one-fifth of a nominal diameter of prototype steel bar. According to the mechanical test results of scale models, it can be concluded that the modified similitude law may be similar to compressive strength of prototype concrete and yield strength of prototype steel bar.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.289-296
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• 2009

Natural frequency is a key parameter to determine the seismic and wind loading of tall flexible structures, and to assess the wind-induced vibration for serviceability check. In this study, natural frequencies and associated mode shapes were obtained from measured acceleration data and system identification technique. Subsequently, finite element(FE) models for a tall reinforced concrete buildings were built using a popular PC-based finite element analysis program and calibrated to match their natural frequencies and mode shapes to actual values. The calibration of the FE model included: 1) compensation of modulus of elasticity considering the mix design strength, 2) flexural stiffness of floor slabs, and 3) major non-structural components such as plain concrete walls. Natural frequencies and mode shapes from the final FE model showed best agreement with the measured values.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.69-73
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• 2022

In this paper, we propose a new method for measuring fine dust through a LoG(Laplacian of Gaussian)-based edge detection technique. CCTV-based images in a video are collected for fine dust measurement, and image ranges are designated through RoI(Region of Interest). After clustering by applying the GMM(Gaussian Mix Model) to the specified area, we detect edge through the LoG algorithm and measure the detected edge strength. The concentration of fine dust is determined based on the measured intensity data of the edge. In this paper, we propose algorithm as the effectiveness of experiment. As a result of collecting and applying CCTV image in the video installed around the laboratory of this school for a month from June to July, the measured result value was proved through this experiment to be sufficient to calculate the concentration and range of fine dust.