• The Journal of the Acoustical Society of Korea
• /
• v.14 no.1
• /
• pp.90-107
• /
• 1995

In this paper, we propose the time relation model among the media with the concept of time and space on hypermedia system. This model classifies time proceeding relations in the node and among media connected with the link which is extended to internal link (while a current node remains, a destination node of internal link proceeds) and external link(a current node is replaced by a destination node of external link). Using this model, hypermedia system for hypermedia presentation is designed and implemented. This hypermedia system provides editing tools and controllers to created and edit nodes with time relation information, link tool to construct associative relations among nodes and navigation tool to control context flows.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.9
• /
• pp.1680-1691
• /
• 1994

We propose an extended hypertext data model based on object oriented paradigm that can easily the real world and semantics. We use the BNF notation to formalize the model. In our model, We introduce conceptional navigation by associating semantics on links and drive intelligent navigation using weights on links to alleviate user disorientation problem which is currently somewhat vague. We functionally classify the hypertext node into three types:Indexing node, Content node, Extract node and likewise classify the link into Alink type, Rlink type, Slink type. We believe that the typed node and typed link approach accommodate efficient query/search in hypertext.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.25 no.3
• /
• pp.51-60
• /
• 2017

Estimation of the taxi-out and taxi-in times of aircraft on a airport surface is one of the essential features of Departure Manager (DMAN). Especially for an airport with multiple runways and large ramp areas, estimation of the taxi-out and taxi-in times are mainly dependent on the taxi routes on airport surface. This paper described the method of automatic extraction of the the taxi routes using the ASDE track data and the Dijkstra algorithm based on the node-link model of a airport surface movements. In addition, we analyzed the ground operation status of Incheon International Airport using the extracted taxi routes.

• Journal of Intelligence and Information Systems
• /
• v.7 no.2
• /
• pp.19-33
• /
• 2001

Link weight analysis approach is suggested as a heuristic for selection of input nodes in artificial neural network for bankruptcy prediction. That is to analyze each input node\\\\`s link weight-absolute value of link weight between an input node and a hidden node in a well-trained neural network model. Prediction accuracy of three methods in this approach, -weak-linked-neurons elimination method, strong-linked-neurons selection method and integrated link weight model-is compared with that of decision tree and multivariate discrimination analysis. In result, the methods suggested in this study show higher accuracy than decision tree and multivariate discrimination analysis. Especially an integrated model has much higher accuracy than any individual models.

• Journal of Korea Water Resources Association
• /
• v.40 no.4
• /
• pp.313-324
• /
• 2007

An irregular cell-based numerical model was developed to analyze underground space flooding. In this model, the flow characteristics in underground space were computed by link-node system. Also, the model can simulate the underground flood flow related to the influence of stairs and wall-structures. Empirical discharge formula were introduced to analyze weir-type flow for shopping mall, and channel-type flow for subway railroad respectively. The simulated results matched in reasonable range compared with the observed depth. The dual-drainage inundation analysis model and the underground space flood analysis model were integrated using visual basic application of ArcGIS system. The developed model can help the decision support system of flood control authority for redesigning and constructing flood prevention structures and making the potential inundation zone, and establishing flood-mitigation measures.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.2
• /
• pp.20-29
• /
• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.8
• /
• pp.3766-3788
• /
• 2017

A blockchain is an underlying technology and basic infrastructure of the Bitcoin system. At present, blockchains and their applications are developing rapidly. However, the basic research of blockchain technology is still in the early stages. The efficiency and reliability of blockchain communication is one of the research problems that urgently need to be studied and addressed. Existing algorithms may be less feasible for blockchain-based communication because they only consider a single communication factor (node communication capability or node trust degree) and only focus on a single communication performance parameter(communication time or communication reliability). In this paper, to shorten the validation time of blockchain transactions and improve the reliability of blockchain-based communication, we first establish a multi-link concurrent communication model based on trust degree, and then we propose a novel integrated factor communication tree algorithm (IFT). This algorithm comprehensively considers the node communication link number and the node trust degree and selects several nodes with powerful communication capacity and high trust as the communication sources to improve the concurrency and communication efficiency. Simulation results indicate that the IFT algorithm outperforms existing algorithms. A blockchain communication routing scheme based on the IFT algorithm can increase communication efficiency by ensuring communication reliability.

• Journal of Intelligence and Information Systems
• /
• v.27 no.4
• /
• pp.73-95
• /
• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1999.04a
• /
• pp.226-233
• /
• 1999

When we numerically model the bridge under seismic condition, the full model combining the super-structure and the sub-structure is considered for the more accurate results than the separate model. In this case, the super-structure is connected with the sub-structure by the elastic pad shoe that is difficult to model, because it has the three translational elastic stiffness and the three rotational elastic stiffness. The two-node General Link element is derived in finite element equation representing such a pad shoe, and it is verified by comparing the one General Link element model with the corresponding three legacy spring element model. It is easy to model the pad shoe, if the General Link finite element is used. And the seismic analysis result of the bridge full model structure, which is modeled with the General Link element, has been compared with the one of the separate model structure. The present study gives. more conservative result than that of the separate model, which does not consider the dynamic behaviour of the sub-structure.

• Proceedings of the Korea Association of Information Systems Conference
• /
• 2002.11a
• /
• pp.289-312
• /
• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.