• 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.

• 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.

• The Korean Journal of Franchise Management
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• v.13 no.3
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• pp.31-43
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• 2022

Purpose: Service quality is a topic of constant interest in marketing research and practitioners. Service quality is an important factor influencing performance even in the context of coffee shops, and research on service quality management strategies continues by coffee shop researchers and practitioners. The service quality of coffee shops is a source of competitive advantage and is an important factor in enhancing customer and business performance. This study aims to identify the effects of cognitive evaluation on emotional and behavioral responses using a cognitive-emotional-behavioral framework and SOR model in the coffee shop context. Cognitive evaluation (service quality) consists of tangibles, responsiveness, assurance, reliability, and empathy dimensions. Research design, data, and methodology: In the proposed model, positive and negative emotions and satisfaction mediate the relationship between service quality and money to spend and visit frequency. The data were collected from customers who visited a coffee shop within the last 1 month. The survey was conducted for about one month. Among a total of 300 distributed questionnaires 261 responses were used for data analysis. The data were analyzed using frequency analysis, measurement model analysis, and structural equation modeling analysis with SPSS 28.0 and SmartPLS 4.0. Results: Tangibles, responsiveness, assurance, and empathy had significant positive effects on positive emotion, while only reliability had a significant negative effect on negative emotion. Both positive and negative emotions had significant positive effects on customer satisfaction, but not on money to spend and visit frequency. Lastly, customer satisfaction had significant positive effects on money to spend and visit frequency. Conclusions: The study revealed the relative weight of cognitive factors on customer emotions and confirmed the validity of SOR model. The fact that tangibility is the most important factor in increasing positive emotions and reliability is the most important factor in reducing negative emotions provides a direction for emotional branding strategies using the service quality mix of coffee shops. This study confirmed the full mediating role of satisfaction between positive and negative emotions and consumer behaviors (money to spend and visit frequency). This infers that when a coffee shop increases customer satisfaction through customer emotion management, the customer's money to spend and visit frequency in the coffee shop increases.

• The Korean Journal of Franchise Management
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• v.9 no.4
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• pp.7-19
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• 2018

Purpose - Recently, global management in Korea franchise industry is becoming an important keyword. As an important branch market, Chinese market plays a major role not only by making experience of the competitiveness among global brands which offers a foothold to become a top global brand, but also by actualizing an economies of scale in production, sales, etc. Therefore, it is necessary to identify key successful factor influencing customer evaluation and responses of Korean franchise restaurant targeting Chinese consumers in China context. The purpose of this study is to examine the effects for Korean franchise restaurant selection attributes on perceived value, customer satisfaction and customer loyalty in Chinese context with SmartPLS 3 and Artifical Neural Network(ANN). Research design, data, and methodology - For these purposes, the authors developed several hypotheses. A questionnaire survey was conducted on the panel of online survey companies for Chinese consumers who have visited Korean franchise restaurants. A total of 404 data were analyzed using structural equation modeling(SEM) and artifical neural network(ANN) with SPSS 22.0 and SmartPLS 3.0. Result - The findings of this study are as follows: First, the alternative model findings show that facilities & atmosphere, employee service, and menu influenced on utilitarian value, customer satisfaction, and customer loyalty directly. Second, employee service influenced on customer satisfaction. Third, menu influenced on hedonic value. Fourth, brand reputation influenced on utilitarian value. Fifth, hedonic value increase customer satisfaction and customer loyalty. Sixth, hedonic value increase customer loyalty. Seventh, customer increase customer loyalty. And, the ANN analysis shows that utilitarian value is the first most important factor influencing customer satisfaction, followed by hedonic value, facilities & atmosphere, menu and employee service. However, the ANN analysis shows that customer satisfaction is the first most important factor influencing customer loyalty, followed by utilitarian value, hedonic value, brand reputation, menu, and employee service. Conclusions - This study provides practical implications for enhancing customer satisfaction and customer loyalty by applying the ANN technique that complements the limitations of the linear structural relationship analysis using the proposed model and the alternative model. In other words, the SEM-ANN model provides guidelines on how Korean franchise restaurants should formulate facilities & atmosphere, employee service, and menu mix strategies in China. In addition, ANN 's analysis shows that restaurant brand reputation plays a pivotal role in increasing customer loyalty. The fact suggests that Korean franchise companies should establish their domestic brand reputation prior to their entry into overseas markets such as China.