• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.11
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• pp.1521-1530
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• 2002

This article proposes a pressure based method for predicting flows at all speeds. The compressible SIMPLE algorithm is extended to unstructured grid framework. Convection terms are discretized using second-order scheme with deferred correction approach. Diffusion term discretization is based on structured grid analogy that can be easily adopted to hybrid unstructured grid solver. This method also uses node centered scheme with edge based data structure for memory and computing time efficiency of arbitrary grid types. Both incompressible and compressible benchmark problems are solved using the above methodology. The demonstration of this method is extended to slip flow problem that has low Reynolds number but compressibility effect. It is shown that the proposed method can improve efficiency in memory usage and computing time without losing any accuracy.

• Journal of computational fluids engineering
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• v.18 no.2
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• pp.41-48
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• 2013

Ice accretion on the solid surface is an importance factor in assessing the performance of aircraft and wind turbine blade. Changes in the external shape due to ice accretion can greatly deteriorate the aerodynamic performance. In this study, a three-dimensional upwind-type second-order positivity-preserving finite volume CFD scheme based on the unstructured mesh topology is developed to simulate two-phase flow in atmospheric icing condition. The code is then validated by comparing with NASA IRT experimental data on the sphere. The present results of the collection efficiency are found to be in close agreement with experimental data and show improvement near the stagnation region.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.110-116
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• 2023

In this study describes the design of Exo-suit to assist those who work in unstructured positions. The present study aimed to analyze various types of work, especially those performed in unstructured postures by heavy industry workers. Based on the motion capture analysis results, an attempt was made to develop a shoulder muscle-assistive Exo-suit capable of assisting a wearer who is working using shoulder muscles. In the present study, as the first step of developing a shoulder muscle-assistive Exo-suit, different working scenarios were simulated, and the corresponding motion data were estimated using motion capture devices. The obtained motion data were reflected in the design of the Exo-suit. The main structure of the shoulder muscle-assistive Exo-suit was made of a carbon fiber-reinforced composite to obtain the weight reduction. The shoulder muscle assistive Exo-suit was designed to fully cover the range of motion for workers working in unstructured postures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• Knowledge Management Research
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• v.23 no.4
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• pp.69-89
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• 2022

As we enter a super-aged society, senior citizens' health issues are affecting a variety of fields, including medicine, economics, society, and culture. In this study, we intend to draw implications from unstructured data analysis such as text mining and social network analysis in order to apply digital health care service design for improving the cognitive ability of senior citizens. The research procedure of this study improved the service design methodology into a process suited to the analysis of unstructured data, and six steps were applied. Related keywords that exist on social media, focusing on cognitive improvement and healthcare for senior citizens, were collected and analyzed, and based on these results, the direction of healthcare service design for improving on the cognitive abilities of senior citizens was derived. The results of this study are expected to have academic and practical implications for expanding the scope of the use of big data analysis methods and improving existing healthcare service development methodologies.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.546-557
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• 2022

Recently, the demand to interpret image data with artificial intelligence in various fields is rapidly increasing. Object recognition and detection techniques using deep learning are mainly used, and video integration analysis to determine unstructured object recognition is a particularly important problem. In the case of natural disasters or social disasters, there is a limit to the object recognition structure alone because it has an unstructured shape. In this paper, we propose intelligent video integration analysis system that can recognize unstructured objects based on video turning point and object detection. We also introduce a method to apply and evaluate object recognition using virtual augmented images from 2D to 3D through GAN.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.63-73
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• 2014

As the advance of WWW, unstructured data including texts are taking users' interests more and more. These unstructured data created by WWW users represent users' subjective opinions thus we can get very useful information such as users' personal tastes or perspectives from them if we analyze appropriately. In this paper, we provide various analysis efficiently for unstructured text documents by taking advantage of OLAP (On-Line Analytical Processing) multidimensional cube technology. OLAP cubes have been widely used for the multidimensional analysis for structured data such as simple alphabetic and numberic data but they didn't have used for unstructured data consisting of long texts. In order to provide multidimensional analysis for unstructured text data, however, Text Cube model has been proposed precently. It incorporates term frequency and inverted index as measurements to search and analyze text databases which play key roles in information retrieval. The primary goal of this paper is to apply this text cube model to a real data set from in an Internet site sharing hotel information and to provide multidimensional analysis for users' reviews on hotels written in texts. To achieve this goal, we first build text cubes for the hotel review data. By using the text cubes, we design and implement the system which provides multidimensional keyword search features to search and to analyze review texts on various dimensions. This system will be able to help users to get valuable guest-subjective summary information easily. Furthermore, this paper evaluats the proposed systems through various experiments and it reveals the effectiveness of the system.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.1-10
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• 2005

An unstructured parallel overset mesh method has been developed for the simulation of unsteady flows around multiple bodies in relative motion. For this purpose, an efficient and robust search method is proposed for the unstructured grid system. A new data-structure is also proposed to handle the variable number of data on parallel sub-domain boundary. The interpolation boundary is defined for data communication between grid systems. An interpolation method to retain second-order spatial accuracy and to treat the points inside the neighboring solid bodies are also suggested. A single store separating from the Eglin/Pylon configuration is calculated and the result is compared with experimental data for validation. Simulation of unsteady flows around multiple bodies in relative motion is also performed.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.67-73
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• 2018

Researchers have increased their interest in effectively managing the disaster that appear in large scale and complex form. There are two types of disaster information, which are unstructured text data and structured data. Unstructured text data usually refers to text documents that have been referenced by disaster management personnel such as disaster manuals and related regulations, while structured data refers to various disaster information build in the disaster related organization system. This paper proposes a methodology of constructing a disaster information sharing system that enables joint use of disaster related organizations through the establishment of a mutual linkage system by utilizing both unstructured and structured form of disaster information. Especially, Based on the linkage information between structured earthquake information in earthquake related system and earthquake manuals and countermeasures against earthquake disaster, we propose a service that provides the necessary information for earthquake management. It is expected that the task manager will perform effective earthquake state management by acquiring the integrated structured and unstructured earthquake information of the ministries and related organizations.