• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.79-86
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• 2005

The Qis visualizational spreadsheet environment is shown to be extremely effective in supporting the organized visualization of multi-dimensional data sets. The Qis consists of the reconfigurative 2D arrangement of spreadsheet elements at run time and each spreadsheet element has a novel framestack. As the feature, it supports 3D data structure of each element on the Qis. It enables the visualization spreadsheet to effectively manage, rapidly organize, and compactly encapsulate multi-dimensional data sets for visualization. Using several experiments with scientific users, the Qis has been demonstrated to be a highly interactive visual browsing tool for the analysis of multidimensional data, displaying 2D and 3D graphics, and rendering in each frame of the spreadsheet.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.509-525
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• 2005

In this paper, we propose the index structure based on a vector approximation for efficiently supporting the similarity search of multi-dimensional data. The proposed index structure splits a region with the space partition method and allocates to the split region dynamic bits according to the distribution of data. Therefore, the index structure splits a region to the unoverlapped regions and can reduce the depth of the tree by storing the much region information of child nodes in a internal node. Our index structure represents the child node more exactly and provide the efficient search by representing the region information of the child node relatively using the region information of the parent node. We show that our proposed index structure is better than the existing index structure in various experiments. Experimental results show that our proposed index structure achieves about $40\%$ performance improvements on search performance over the existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.480-502
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• 2022

This work assesses the degree of satisfaction tourists receive as final recipients in a tourism destination based on the fact that satisfied tourists can make a significant contribution to the growth and continuous improvement of a tourism business. The work considers Pokhara, the tourism capital of Nepal as a prefecture of study. A stratified sampling methodology with open-ended survey questions is used as a primary source of data for a sample size of 1019 for both international and domestic tourists. The data collected through a survey is processed using a data mining tool to perform multi-dimensional analysis to discover information patterns and visualize clusters. Further, supervised machine learning algorithms, kNN, Decision tree, Support vector machine, Random forest, Neural network, Naive Bayes, and Gradient boost are used to develop models for training and prediction purposes for the survey data. To find the best model for prediction purposes, different performance matrices are used to evaluate a model for performance, accuracy, and robustness. The best model is used in constructing a learning-enabled model for predicting tourists as satisfied, neutral, and unsatisfied visitors. This work is very important for tourism business personnel, government agencies, and tourism stakeholders to find information on tourist satisfaction and factors that influence it. Though this work was carried out for Pokhara city of Nepal, the study is equally relevant to any other tourism destination of similar nature.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.69-77
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• 2009

Stream service environment demands real-time query processing for voluminous data which are ceaselessly delivered from tremendous sources. Typical R-tree based query processing technologies cannot efficiently handle such situations, which require repetitive and inefficient exploration from the tree root on every data event. However, many stream data including sensor readings show high locality, which we exploit to reduce the search space of queries to explore. In this paper, we propose a query processing scheme exploiting the locality of stream data. From the simulation, we conclude that the proposed scheme performs much better than the traditional ones in terms of scalability and exploration efficiency.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.100-103
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• 2008

Recently Development of construction system that subjective operators share and control information efficiently based on the three-dimensional space and design information throughout life cycle of construction project is progressing dynamically. In case of civil structures which are infrastructure, Demand for structure of complex system which has multi-functions such as super and smart bridges and express rails is increasing and system development which computerizes and integrates process of structure design is in need. For that, research about link way between three dimensional modeling data and structure analysis programs should be preceded. In this research, therefore, research about interface design between three dimensional virtual modeling data to automate efficient civil-structure-design and nonlinear finite element analysis program which is made up of reinforced concrete material model that express material's character clearly.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.187-193
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• 1999

Dimensional difference by welding deformation is usually occurred at steel bridge manufacturting or multi-pass welding used at joining of thick plates. Be this, root gap out of standard is frequently developed at butt weld joints. For example, although standard root gap below 6mm at butt weld joints of plates under 15mm thickness, maximum 30mm root opening is developed at the weld field. At this case, 24mm parts out of standard is generally built up. But, there are no accumulated data and restriction about this built up welding pars. In this study, therefore, the accumulation of data for built up parts and the verification of the mechanical properties of weld part as root gap is performed. It is included that tensile, bending, impact, hardness test and microstructural review for each welding specimen of 0mm, 6mm, 30mm root opening.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.240-241
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• 2015

As buildings and especially eco-friendly facilities are increasing, maintenance of the aged buildings are interested by many maintenance companies. Therefore, a lot of companies are increasing by the maintenance form. These Earned Value should try to minimize the increasing forms. Therefore, this study has an effort to gather data related to earned value of building facility maintenance and analyze the data in terms of local dimension, used duration dimension, building types dimension and so on in order to prevent the building deterioration.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.91-92
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• 2014

Public organizations and enterprises have repeated to invest in development or operation of their information systems. However, these investment projects have been not taken care of in the field of administration and evaluation. Since these information systems projects have unique characteristics such as technology sensitiveness, network effectiveness, embeddedness, and externality, it is not easy to manage and monitor them. Returns of investment for information systems should nonetheless need efficient monitoring and effective analysis for them. In this research, we propose a multi-dimensional management model on the basis of process in order to evaluate information systems.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.267-279
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• 2021

A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3815-3835
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• 2022

Density-based outlier detection is one of the hot issues in data mining. A point is determined as outlier on basis of the density of points near them. The existing density-based detection algorithms have high time complexity, in order to reduce the time complexity, a new outlier detection algorithm DODMD (Density-based Outlier Detection in Multidimensional Datasets) is proposed. Firstly, on the basis of ZH-tree, the concept of micro-cluster is introduced. Each leaf node is regarded as a micro-cluster, and the micro-cluster is calculated to achieve the purpose of batch filtering. In order to obtain n sets of approximate outliers quickly, a greedy method is used to calculate the boundary of LOF and mark the minimum value as LOF_min. Secondly, the outliers can filtered out by LOF_min, the real outliers are calculated, and then the result set is updated to make the boundary closer. Finally, the accuracy and efficiency of DODMD algorithm are verified on real dataset and synthetic dataset respectively.