• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.195-200
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• 2021

In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.177-186
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• 2022

A network QoS model for the joint integrated C4I structure was proposed for the integration of network infrastructure and network operations(NetOps) for NCOE. Detailed QoS requirements process of the joint integrated C4I systems are needs in the Multi-Domain Operation Environment(MDOE). A process is proposed for identifying QoS requirements and establishing in the MDOE using JMT(Joint Mission Thread) reference architecture and solution architecture. Mission analysis identify JCOAs(Joint Critical Operational Activities) and related activities based on JMT & System architecture's OVs, and Information analysis identify QoS attributes using System architecture's SVs. Identifying QoS attributes will be registered at PPS Registry by pre-regulated process, and will be set-up by NetOps. MDOE QoS requirement Process will support efficiently MUM-T and smart defense platform users under the future uncertain battlefield circumstances.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.7-15
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• 2023

Purpose: The purpose of this study is to investigate how consumers perceive electric vehicles and factors that affect attitude, satisfaction, and intention to use electric vehicles and to explore policy issues regarding climate change and global environment. By classifying actual and potential users, this study developed the following research questions: i) factors including economic feasibility, sociality, environmental sustainability, inefficiency, inconvenience, convenience, and uncertainty affect attitude to electric vehicles; ii) attitude to electric vehicles affects actual consumers' satisfaction; and iii) attitude to electric vehicles affects potential users' intention to use. Research design, data and methodology: This study conducted an online survey and applied factor and regression analyses and ANOVA to test hypotheses. Results: The results of this study found that economic feasibility and convenience factors significantly affect attitude in both cases of actual and potential users. How actual users perceive efficiency of electric vehicles negatively and uncertain issues such as battery technology affect attitude to electric vehicles. Conclusions: This study provides policy implications that foster promotional policies for the adoption of electric vehicles for environment and regulate negative aspects. This study also provides managerial implications for manufacturers to develop better technology competences to enhance reliability on electric vehicles.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2222-2229
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• 2023

Radon and radon progeny being natural radioactive pollutants, seriously affect the health of uranium miners. Radon reduction by ventilation is an essential means to improve the working environment. Firstly, the relational model is built between the radon exhalation rate of the loose body and the ventilation parameters in the stope with radon percolation-diffusion migration dynamics. Secondly, the model parameters of radon exhalation dynamics are uncertain and described by triangular membership functions. The objective functions of the left and right equations of the radon exhalation model are constructed according to different possibility levels, and their extreme value intervals are obtained by the immune particle swarm optimization algorithm (IPSO). The fuzzy target and fuzzy constraint models of radon exhalation are constructed, respectively. Lastly, the fuzzy aggregation function is reconstructed according to the importance of the fuzzy target and fuzzy constraint models. The optimal control decision with different possibility levels and importance can be obtained using the swarm intelligence algorithm. The case study indicates that the fuzzy aggregation function of radon exhalation has an upward trend with the increase of the cut set, and fuzzy optimization provides the optimal decision-making database of radon treatment and prevention under different decision-making criteria.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.169-176
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• 2013

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of Information Technology and Architecture
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• v.11 no.2
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• pp.187-199
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• 2014

The DoD of United State, the MoD of United Kingdom and NATO have developed and implemented not only the concepts of joint capability but also management system for the joint capability to respond the future uncertain operations effectively. The resources of the DoD in United State have been efficiently planning, programming, budgeting, execution and evaluation using the PPBEE system which developed based on the concept of joint capability. The joint capability of the DoD has been managing through the JCAMS (Joint Capability Area Management System) which constructed based on JCA, UJTL and so on. Recently the MND of Korea eager to try introducing concept of the JCMS and developing the JCMS like the JCAMS of DoD for the future joint operation in the uncertain environment. We propose the holistic mechanism to develop the JCMS (Joint Capability Management System) of MND which can implement during the constructing the JCMS of Korea efficiently and effectively.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Knowledge Management Research
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• v.19 no.2
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• pp.163-185
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• 2018

In order to solve problems in an uncertain and complicated management environment of the modern world, a creative solution that combines diverse perspectives, knowledge, and effort based on diversity within an organization is required. Smart work environment provides an opportunity to express the potential diversity of an individual, extending the source of ideas to the organization, enhancing communication, and linking and sharing information and knowledge. So, this results in increased creative behavior. The purpose of this study is to investigate the effect of the process of connecting and sharing information and knowledge of organizational members on creative behavior and the effect of smart work environment in the process. The purpose of this study is to identify roles of job autonomy, self-efficacy, knowledge sharing and smart work environment in creative process. For the study, 353 surveys with work use group(156 people) and unused group(197 people). Statistical analysis included validity and reliability analysis, structural model analysis. The results showed that self-efficacy and job autonomy had positive effects on creative behavior and knowledge sharing, and job autonomy had a positive effect on self-efficacy. Knowledge sharing has a positive effect on creative behavior, and mediates the relationship between self-efficacy, job autonomy and creative behavior. Particularly, knowledge sharing has a more positive effect on smart work use group. In case of smart work use group, self-efficacy and job autonomy have a relatively high influence on knowledge sharing rather than direct influence on creative behavior appear. This result implies that the achievements of smart work are revealed in terms of knowledge sharing and creative behavior.