• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.183-191
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• 2018

In this study a traffic volume dependent displacement estimation model for Gwangan Bridge was developed using bridge monitoring big data. Traffic volume data for four different vehicle types and the vertical displacement data in the central position of the Gwangan Bridge were used to develop and validate the estimation model. Two statistical estimation models were developed using multiple regression analysis (MRA) and principal component analysis (PCA). Estimation performance of those two models were compared with actual values. The results show that both the MRA and the PCA based models are successfully estimating the vertical displacement of Gwangan Bridge. Based on the results, it is concluded that the developed model can effectively be used to predict the traffic volume dependent displacement behavior of Gwangan Bridge.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.634-645
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• 2014

VoIP (Voice over Internet Protocol) is a technology of transmitting and receiving voice and data over the Internet network. As the telecommunication industry is moving toward All-IP environment with growth of broadband Internet, the technology is becoming more important. Although the early VoIP services failed to gain popularity because of problems such as low QoS (Quality of Service) and inability to receive calls as the phone number could not be assigned, they are currently established as the alternative service to the conventional wired telephone due to low costs and active marketing by carriers. However, VoIP is vulnerable to eavesdropping and DDoS (Distributed Denial of Service) attack due to its nature of using the Internet. To counter the VoIP security threats efficiently, it is necessary to develop the criterion or the model for estimating the information security level of VoIP service providers. In this study, we developed reasonable security indicators through questionnaire study and statistical approach. To achieve this, we made use of 50 items from VoIP security checklists and verified the suitability and validity of the assessed items through Multiple Regression Analysis (MRA) using SPSS 18.0. As a result, we drew 23 indicators and calculate the weight of each indicators using Analytic Hierarchy Process (AHP). The proposed indicators in this study will provide feasible and reliable data to the individual and enterprise VoIP users as well as the reference data for VoIP service providers to establish the information security policy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.485-494
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• 2020

The study aims to identify and measure factors affecting the salaries of employees in manufacturing enterprises in Hanoi, the important area of Vietnam's economy. We conducted a questionnaire consisting of 31 observation variables with a 5-point Likert scale. Independent variables were measured from 1 "without effect" to 5 "strongly". Based on the literature review and results of interviews, a total of 350 questionnaires were sent to participants; 300 of them met the standards and were subject to be analyzed. The results of Exploratory Factor Analysis (EFA) and Multiple Regression Analysis (MRA) identify six main determinants influencing the salaries of employees in manufacturing enterprises in Hanoi, including Paying views of business leaders (PV), Financial ability of the enterprise (FA), Capacity of workers (CW), Capacity of the contingent of employees engaged in salary work (CC), Role of grassroots trade unions (TU), and State policies and laws on labor - salaries (STL). Based on the findings, some recommendations have been proposed to help the firm leaders design appropriate personnel policies for creating better job satisfactions for employees in the future. On this basis, the authors propose a number of recommendations to improve the salaries of employees in manufacturing enterprises in Hanoi.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.613-623
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• 2020

In recent years, many firms have built a good recruitment policy, focusing on the requirements set for candidates to meet the employers' satisfaction; they often have certain requirements for each accounting job's position. The study aims to identify and measure factors affecting the employers' satisfaction with accounting graduates in Hanoi, the important locus of firms' labor force. We conducted a questionnaire consisting of 16 observation variables with a 5-point Likert scale. Independent variables were measured from 1 "without effect" to 5 "strongly". Based on the literature review and results of interviews, a total of 150 questionnaires were sent to participants; 135 of them met the standards and were subject to be analyzed. The results of Cronbach's alpha, Exploratory Factor Analysis (EFA) and Multiple Regression Analysis (MRA) identify three main determinants influencing the employers' satisfaction with accounting graduates in Hanoi, including students' experience before graduating (SEG), reputation of universities (RU), and university's recruitment support policy (RSP). Based on the findings, some recommendations have been proposed to help universities design training programs for creating better satisfactions for employers in the future. On this basis, the authors propose a number of recommendations to improve the employers' satisfaction with accounting graduates in Hanoi.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.873-884
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• 2021

People are often motivated by money. The salary a worker is paid by his employer can have a great influence on his performance in the administration. The study aims to identify and measure the impact of collective bargaining on the income of employees in enterprises. Participants were given a questionnaire consisting of 21 observation variables with a 5-point Likert scale. Independent variables were measured from 1 "without effect" to 5 "strongly". Based on the literature review and results of interviews, a total of 285 questionnaires were sent to participants in 95 enterprises in three typical fields: industry, construction, textile, and garment; 255 of them met the standards and were subject to be analyzed. We use qualitative research methods combined with quantitative research methods. SPSS20 software is used to synthesize and analyze data. The results of Cronbach's alpha, Exploratory Factor Analysis (EFA) and Multiple Regression Analysis (MRA) identify, the objective for collective bargaining (MT), time to organize collective bargaining (TD), the competence of the parties of the collective bargaining (NL), collective bargaining organization process (QT) are positively correlated with the income of workers in enterprises; information provided for collective bargaining (TT) has a negative correlation with the income of employees in enterprises. Based on the findings, some suggestions have been given for collective bargaining to increase the income of employees in enterprises in Vietnam.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.68-76
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• 2014

The accurate estimation of construction cost is important to a successful development in construction projects. In previous studies, the construction cost are estimated by statistical methods. Among the statistical methods, support vector regression (SVR) has attracted a lot of attentions because of the generalization ability in the field of cost estimation. However, despite the simplicity of the parameter to be adjusted, it is not easy to find optimal parameters. Therefore, to build an effective SVR model, SVR's parameters must be set properly without additional data handling loads. So this study proposes a novel approach, known as genetic algorithm (GA), which searches SVR's optimal parameters, then adopt the parameters to the SVR model for estimating cost in the early stage of apartment housing projects. The aim of this study is to propose a GA-SVR model and examine the feasibility in cost estimation by comparing with multiple regression analysis (MRA). The experimental results demonstrate the estimating performance based on the percentage of estimations within 25% and find it can effectively do the accurate estimation without through the trial and error process.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.63-72
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• 2015

The importance of the appropriate use and procurement of Safety and Health Expense has been increasing along with the recent increase of construction projects in height, size and complexity. However, the current standards for deducting the Safety and Health Expense have shown limitations in applying the properties and environment of the construction project due to its Safety and Health Expense Rate's classification method. Therefore, the purpose of this study is to develop a prediction model for the Safety and Health Expense that enables the consideration of different environment and properties of construction projects. The study uses multiple regression analysis to analyze the Safety and Health Expense of Ordinary(A) of less than 0.5 billion WON. The research results have shown that the use of multiple regression analysis reduces the error rate to 4.38% which the current standard calculation method have shown 18.48%. Therefore, the use of the suggested model provides reliable Safety and Health Expense prediction values that considers the properties of the project. It is expected that the results of this study contributes to the effective safety management by providing the appropriate amount of Safety and Health Expense to the project. In this study, only projects of less than 5 billion WON have been considered in the analysis. Therefore, more data is required for future studies to suggest an overall Safety and Health Expense predict ion model that covers the whole construction industry.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.1
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• pp.1-11
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• 2010

In order to understand the biological environmental characteristics with temporal variations of the physico-chemical factors in 2012 Yeosu Expo site of Korea, we investigated at one station, once per week, from April 2006 to December 2007. The surface water temperature ranged from 6.8 to $27.8^{\circ}C$ and the bottom water temperature ranged from 6.3 to 25.9 $25.9^{\circ}C$. The salinity varied from 12.8 to 33.0 psu in the surface water and from 25.2 to 33.6 psu in the bottom water. A strong halocline was observed between the surface and bottom layers in the summer when a rapid decrease of salinity coincided with heavy rainfall. The DIN concentration ranged from 1.36 to $82.7{\mu}M$ in the surface water and from 0.82 to $25.2{\mu}M$ in the bottom water. Phosphate concentration varied from 0.06 to $2.13{\mu}M$ in the surface water and from 0.07 to $1.38{\mu}M$ in the bottom water. Silicate was $1.68-52.0{\mu}M$ in the surface water and $1.37-30.7{\mu}M$ in the bottom water. The nutrient concentrations were generally high during heavy rainfalls and low water temperature periods, and considerably decreased in spring and autumn. The N/P ratio ranged from 4.43 to 325 in the surface water and from 3.8 to 321 in the bottom water. It increased rapidly during the heavy rainfall season and remained at a value of approximately 16 in other periods. The chlorophyll a concentration ranged from 0.46 to $65.0{\mu}g$ $L^{-1}$ in the surface water and from 0.71 to $15.0{\mu}g$ $L^{-1}$ in the bottom water. $Chl-{\alpha}$ concentration remained low in periods of low water temperature, however rapidly increased in periods of high water temperature. From the results of principal component analysis (PCA) and multiple regression analysis (MRA), we conclude that temporal variations of physico-chemical and biological factors were greatly affected by the influx of fresh water, and that nutrients were well controlled by their uptake and assimilation by phytoplankton. Also, during the low water temperature periods, environmental structure in this study site was affected by recycled nutrients through nutrient cycling and mineralization.