• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2005.05a
• /
• pp.1033-1039
• /
• 2005

Parallel and distributed simulation is concerned with the efficient execution of large-scale discrete event simulation models on multiprocessors and distributed platforms. After the development of WWW, many efforts in the parallel and distributed simulation have been made for modeling, particularly building simulation languages and creating model libraries that can be assembled and executed over WWW. However, web-based parallel and distributed simulation is restricted by heterogeneous computing environments. Recently, the advent of XML and web services technology has made these efforts enter upon a new phase. Especially, the web services as a distributed information technology have demonstrated powerful capabilities for scalable interoperation of heterogeneous systems. This paper aims to develop and evaluate the parallel and distributed simulation using the web services technology. In particular, a prototype multi-pass simulation framework is implemented using Java-based web services technology. It focuses on the efficiency of multi-pass simulation used for optimization through the distribution of simulation replication to several simulation service providers. The development of parallel and distributed simulation using web services will help solve efficiently large-scale problems and also guarantee interoperability among heterogeneous networked systems.

• Information Systems Review
• /
• v.22 no.1
• /
• pp.33-57
• /
• 2020

Although cryptocurrency which can promote innovation in the blockchain ecosystem is published for many useful purposes, in Korea, cryptocurrency is recognized only as a means of investment for the profit. The fact emphasizes only the speculative nature of the cryptocurrency, so investor negates the fundamental purpose of cryptocurrency and hinders innovation in the blockchain ecosystem. The purpose of this study is to investigate the cause of cryptocurrency perception and speculative behavior of domestic cryptocurrency investors from an academic perspective. We use a model that reflects the traditional considerations and cryptocurrency's characteristics in investment. Using the model, we can explain the cause of misperception of cryptocurrency through the theory of bounded rationality. In building the research model, we use variables of venture and angel investor's consideration used in investment decisions and collect the keywords from indexes of whitepaper to reflect the properties of cryptocurrency. This study mentions that, due to the imitations presented by Simon, individuals are forced to perceive cryptocurrency as a means of speculation and to make irrational decisions that impair ecosystem health. We analyze whether there is a significant difference in rationality in decision made by the sample under limited knowledge and imperfect information constraints. As a result, imperfect information constraints led investors to consider only irrational criteria in decision making. From this result, this study suggests that information asymmetry needs to be relaxed so that investment can be pursued together with rational investment and development of blockchain ecosystem. In addition, the industry can capture strategic insights for successful financing through ICO by enabling better understanding of investor decision-making.

• Spatial Information Research
• /
• v.13 no.3 s.34
• /
• pp.221-237
• /
• 2005

This study attempts at building a GIS computing environment that incorporates object-relational spatio-temporal database for the time geography model with space-time path, space-time prism and space-time accessibility. The proposed computing environment is composed of ( i ) mobile GIS application for collecting spatio-temporal trajectory data of an individual, ( ii ) spatio-temporal database server that includes time geography model, and (iii) geovisualization client that performs time geographic queries to the spatio-temporal database. The spatio-temporal trajectory data collected by GPS-PDA client is automatically processed and sent to server through data management middleware. The spatio-temporal database implemented by extending a generic DBMS provides spatio-temporal objects, functions, and SQL. The geovisualization client illustrates 3D visual results of the queries about space-time path, space-time prism, and space-time accessibility. This study confirms the possibility of integrating mobile GIS and DBMS for time geography model, and it presents the appropriate database model with spatio-temporal objects and functions that may handle very large data for time geography application.

• The Korean Journal of Archival Studies
• /
• no.3
• /
• pp.33-64
• /
• 2001

This essay introduces the basic method and program required to meet some necessary conditions of building university archives. By the phrase 'method and program', I intend the effective means of regularly but circumstantially controling the ways to the archival purposes proper which can be defined as the keeping of evidences and the broadening of information pool in terms of the evidential and informational natures or values of records. My starting point is about the matters of overcoming a standard method of induction which has long prescribed much passive procedures in the archival work. Considering the differences in the records and archives management-practices between West and Korea, I tentatively try to add some active elements to the archival work among which the collection for the expanding evidences and informations may firstly emphasized. While this collecting activity normally depends on the existing 'collections' and 'manuscripts', I cannot exclude the possibility of collections the materials, being likely to be registered in any poor or insufficient record groups. In the similar context, this kind of activity may and must be expanded beyond the university boundaries so at to arrange the cornerstones of archive-based local studies in the various disciplines. Here I premise another role of university archives, the role as 'science archives'. These archives within university archives seem likely to function in likewise the special collections within Western university libraries. What I mean here, however, is the archival groups purposedly gathered or acquisited according to more detail and narrower plan in order to meet the various demands from the different disciplines for the primary sources. The archival procedures from this revised method and program may, I hope, satisfy some of the preconditions of building university archives before the archives will actually function as a sub-institution of an university preserving legal, administrative and financial evidences, thus keeping identity and continuity of the university on the one hand, and as a local information center of supplying the archival contents on effectual demand from the field of local studies on the other. Finally, I conclude with a suggestion concerning the cooperation of all the parties of archival works. Proposing the 'Regional Research Center Program' in the field of technology and engineering as a model for the cooperation, I suggest that universities, private/public organizations, and central and local governments may work together for surveying the scattered ancient and modern documents as well as for building archives under the matching fund.

• Korean Journal of Construction Engineering and Management
• /
• v.19 no.6
• /
• pp.86-93
• /
• 2018

Infrastructure which mandatory in human life causes large environmental loads when they are being installed and maintained. Especially, maintenance is performed over a long period of time. Also, there is a limit to suggest a reliable estimated value because environmental loads are changed according to methods of maintenance and periods. In this study, we developed a Environmental Load Estimating Model to evaluate value and plan as soon as possible in the Early Design Phases while maintaining a tunnel. To estimate environmental loads by using brief design information, we analyze a calculation methodology of environmental loads in maintenance phases. Furthermore, we apply periods of maintenance work and maintenance factors considered a characteristic of long-term maintenance. Finally, a main purpose is that this program makes all users estimate environmental loads in maintenance phases easily and quickly. Accordingly, it is considered that the Environmental Load Estimating Model offer assistance to eco-friendly maintenance of the road and tunnel construction.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.2
• /
• pp.104-113
• /
• 2019

The road management institute needs lots of cost to repair road surface damage. These damages are inevitable due to natural factors and aging, but maintenance technologies for efficient repair of the broken road are needed. Various technologies have been developed and applied to cope with such a demand. Recently, maintenance technology for road surface damage repair is being developed using image information collected in the form of a black box installed in a vehicle. There are various methods to extract the damaged region, however, we will discuss the image recognition technology of the deep neural network structure that is actively studied recently. In this paper, we introduce a new neural network which can estimate the road damage and its location in the image by region-based convolution neural network algorithm. In order to develop the algorithm, about 600 images were collected through actual driving. Then, learning was carried out and compared with the existing model, we developed a neural network with 10.67% accuracy.

• Computers and Concrete
• /
• v.6 no.3
• /
• pp.203-223
• /
• 2009

Regression analysis (RA) can establish an explicit formula to predict the strength of High-Performance Concrete (HPC); however, the accuracy of the formula is poor. Back-Propagation Networks (BPNs) can establish a highly accurate model to predict the strength of HPC, but cannot generate an explicit formula. Genetic Operation Trees (GOTs) can establish an explicit formula to predict the strength of HPC that achieves a level of accuracy in between the two aforementioned approaches. Although GOT can produce an explicit formula but the formula is often too complicated so that unable to explain the substantial meaning of the formula. This study developed a Backward Pruning Technique (BPT) to simplify the complexity of GOT formula by replacing each variable of the tip node of operation tree with the median of the variable in the training dataset belonging to the node, and then pruning the node with the most accurate test dataset. Such pruning reduces formula complexity while maintaining the accuracy. 404 experimental datasets were used to compare accuracy and complexity of three model building techniques, RA, BPN and GOT. Results show that the pruned GOT can generate simple and accurate formula for predicting the strength of HPC.

• International journal of advanced smart convergence
• /
• v.12 no.3
• /
• pp.104-108
• /
• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Computers and Concrete
• /
• v.5 no.1
• /
• pp.1-20
• /
• 2008

In this study, the effects and the interactions of water content, SP-binder ratio, and water-binder ratio on the workability performance of concrete were investigated. The experiments were designed based on flatted simplex-centroid experiment design modified from standard simplex-centroid one. The data gotten from the design was used to build the concrete slump model using neural networks. Research reported in this paper shows that a small number of slump experiments can be performed and meaningful data obtained with the experiment design. Such data would be suitable for building slump model using neural networks. The trained network can be satisfactorily used for exploring the effects of the components and their interactions on the workability of concrete. It has found that a high water content and a high SP/b ratio is essential for high workability, but achieving this by increasing these parameters will not in itself guarantee high workability. The w/b played a very important role in producing workability and had rather profound effects; however, the medium value about 0.4 is the best w/b to reach high slump without too much effort on trying to find the appropriate water content and SP/b.

• Asia Pacific Journal of Business Review
• /
• v.5 no.2
• /
• pp.19-44
• /
• 2021

Sub Saharan Africa (SSA) is receiving increased investments in the energy sector under the belt and road initiative (BRI) project since its inception in 2013. SSA has a worse energy efficiency ratio coupled with deficient electricity access, through analysis showed varied impacts on the SSA countries due to the BRI initiative. This study dilves into the influencing factors for Energy Efficiency (EE) in 38 SSA countries, applying the probit and logit approach for 2000-2018. The Multiple-regression model shows significant results of some variables such as foreign direct investment, gross domestic product, and port infrastructure quality being significant on EE under BRI initiative countries. However, the logit and probit models produce similar results and the marginal effect for the entire variable, except energy imports that do not likely impact EE. Furthermore, the interaction of quality of port infrastructure and foreign direct investment variables produces significant results, highlighting the increased investments SSA receives under the BRI initiative in the energy and transport sectors. The model Percent correctly predicted (PCP) value was about 84%, indicating it correctly classified the variables and about 16% not classified. The study recommends EE performance standards should be incorporated on energy projects in SSA to ensure that these projects are energy efficient and decouple SSA's energy demand from economic growth. The research proffers suggestions for policy regarding the BRI initiative in SSA and the implications on sustainable energy and building a community with a shared future.