• The Journal of Bigdata
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• v.1 no.2
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• pp.1-8
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• 2016

User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.147-154
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• 2023

With the recent popularity of smartphones, many games are being developed on mobile-based platforms. As a result, it has brought about many changes in the way mobile game is developed. Especially mobile platforms, which are divided into Android and IOS, can now be applied to each platform without additional development through cross-platform. This means that it is necessary to move away from the method of developing each using separate development tools and implement the development process through cross-platform unique features. In this paper, we studied various methods to increase the productivity and quality of game development for the development of mobile games, and a formal framework considering the development process was developed. The framework consists of process, development domain, and platform support parts, each playing its own role. Items of the detailed framework must be reflected so that detailed response data for efficient application of game development can be established in actual mobile game development. The framework was developed by approaching it from two domains, the need for a framework and the framework implementation of key item response data.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.221-248
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• 2008

Data provenance is the background knowledge that enables a piece of data to be interpreted and used correctly within context. The importance of tracking provenance is widely recognized, as witnessed by significant research in various areas including e-science, homeland security, and data warehousing and business intelligence. In order to further advance the research on data provenance, however, one must first understand the research that has been conducted to date and identify specific topics that merit further investigation. In this work, we develop a framework based on semiotics theory to assist in analyzing and comparing existing provenance research at the conceptual level. We provide a detailed review of data provenance research and compare and contrast the research based on d semiotics framework. We conclude with an identification of challenges that will drive future research in this field.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.101-120
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• 2019

The cognition of Research Record Management (RRM) scholars about research framework is important as a pre-condition for future Linked Open Data (LOD). Researchers will be directly engaged to the research data-process with Cloud Computing Data-Infra, which is considered as a Nation-wide R&D Data Projects. The purpose of this paper is to diagnose researcher's cognition of research framework and to provide some guidance of finding a new meaning of the structural requirements of resarch record.

• Human Ecology Research
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• v.52 no.6
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• pp.573-586
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• 2014

The purpose of this study was to review the conceptual framework of social constructionism and critical social constructionism in the research area of multi-cultural family homes, using a literature review. Fopp argued that social constructionism had an objectivation problem that only considered the actor side as a policy object; therefore he suggested a weaker social constructionist perspective with moderate relativism and the application of feminist epistemology to marginal life for maximizing objectivity. This article explores a conceptual framework for studying the reality of housing of multi-cultural families in Korea in the light of constructionist ideas and presents a review of empirical positivist data to support the framework. Based on results, using the social constructionist framework, five contexts (structural, institutional, organizational, operational, and intersubjective) were reviewed and ideas were suggested to develop an appropriate future situation for multi-cultural family homes. For a weaker social constructionist framework, three National Survey of Multi-Cultural Family Homes data sets were reviewed to determine the real condition of multi-cultural family homes. Further, from a feminist perspective, the empirical data of marginalized multi-cultural family homes were reviewed from the perspectives of gender inequality of decision making, cultural adaptation, and differentiation in housing related areas. In conclusion, two perspectives were useful for understanding multi-cultural family housing in Korea but must be compensated with substantial empirical data for a holistic approach.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.167-177
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• 2024

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results. This framework aims to provide comprehensive and in-depth information on each model's training and testing outcomes to optimize bovine iris segmentation performance. In the experiment, U-Net with a VGG16 backbone was identified as the optimal combination of encoder and decoder models for the dataset, achieving an accuracy and dice coefficient score of 99.50% and 98.35%, respectively. Notably, the selected model accurately segmented even corrupted images without proper annotation data. This study contributes to the advancement of iris segmentation and the establishment of a reliable DNN training framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4624-4644
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• 2019

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.168-170
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• 2003

In this paper, we discuss the concept of Spatio-Temporal Data Warehouse and analyze the organization model of spatio-temporal data. Based on the above, we found the framework of Spatio-Temporal Data Warehouse composed of data source, processing tools and application, which covers the whole process from building warehouse to supplying services.

• Educational Technology International
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• v.24 no.2
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• pp.295-329
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• 2023

The recent development of metaverse-related technology has led to efforts to overcome the limitations of time and space in education by creating a virtual educational environment. To make use of this platform efficiently, applying learning analytics has been proposed as an optimal instructional and learning decision support approach to address these issues by identifying specific rules and patterns generated from learning data, and providing a systematic framework as a guideline to instructors. To achieve this, we employed an inductive, bottom-up approach for framework modeling. During the modeling process, based on the activity system model, we specifically derived the fundamental components of the learning analytics framework centered on learning activities and their contexts. We developed a prototype of the framework through deduplication, categorization, and proceduralization from the components, and refined the learning analytics framework into a 7-stage framework suitable for application in the metaverse through 3 steps of Delphi surveys. Lastly, through a framework model evaluation consisting of seven items, we validated the metaverse learning analytics framework, ensuring its validity.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.734-741
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• 2015

Coating is a type of paint. It protects a product forming a film layer on the product and assigns various properties to the product. Coating is one of the fields which is being studied actively in the polymer industry. Importance of coating in various industries is more increased. However, mixing process has been performing in dependence on operator's experience. In this paper, we found the relationship between each data from coating formulation process. We propose a framework to analyze the coating formulation process as well. It can improve the coating formulation process. In particular, the suggested framework may reduce degradation and loss costs due to absence of standard data which is accurate formulation criteria. Also it suggests responses to errors which can be occurred in the future through the analysis of the error data generated in mixing step.