• Convergence Security Journal
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• v.24 no.1
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• pp.35-42
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• 2024

Multi-tenancy architecture plays a crucial role in cloud-based services and applications, and data isolation within such environments has emerged as a significant security challenge. This paper investigates various data isolation methods including schema-based isolation, logical isolation, and physical isolation, and compares their respective advantages and disadvantages. It evaluates the practical application and effectiveness of these data isolation methods, proposing security considerations and selection criteria for data isolation in the development of multi-tenant websites. This paper offers important guidance for developers, architects, and system administrators aiming to enhance data security in multi-tenancy environments. It suggests a foundational framework for the design and implementation of efficient and secure multi-tenant websites. Additionally, it provides insights into how the choice of data isolation methods impacts system performance, scalability, maintenance ease, and overall security, exploring ways to improve the security and stability of multi-tenant systems.

• Journal of the Korea Convergence Society
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• v.6 no.3
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• pp.103-109
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• 2015

TOLED(Transparent, Organic Light Emitting Diodes) based edutainment system has been studied to solve the actual feeling training and educational experience problem of e-learning. However, edutainment system using TOLED has a problem for the non-detection of multi marker array and rotate marker array, and it has problem for the dissonance phenomena caused by Illumination Environment between real world and virtual object. It also has a do not provide services through a variety of devices problem. Therefore, in this paper, we designed a system that provides a realistic actual feeling edutainment contents by recognizes the marker array rotation and a plurality of marker arrangement via an improved marker detection technique. And to unify the real space and virtual space of the lighting environment through a nested block layer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.15-22
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• 2012

For the construction of safe and clear urban environment, it is necessary that we identify the rubbish waste volume and we know the accuracy volume. In this paper, we developed the algorithm which computes the waste volume using the stereo camera for enhancing the environment of waste repository. Using the stereo vision camera, we first computed the distortion parameters of stereo camera and then we obtained the points cloud of the object surface by measuring the target object. Regarding the points cloud as the input of the volume calculation algorithm, we obtained the waste volume of the target object. For this purpose, we suggested two volume calculation algorithm based on the uniform meshing method. The difference between the measured volume such as today's one and yesterday's one gives the reposit of waste volume. Using this approach, we can get the change of the waste volume repository by reading the volume reports weekly, monthly and yearly, so we can get quantitative statistics report of waste volume.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1195-1207
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• 2020

With the development of GeoWeb technology, 2D/3D spatial information services through the web are also has been used increasingly in the application of disaster management. This paper is suggested to construct a web-based 3D geo-spatial information mapping platform to visualize various spatial information collected at the disaster site in a web environment. This paper is presented a web-based geo-spatial information mapping service plan for the various types of 2D/3D spatial data and large-volume LiDAR point cloud data collected at the disaster accident site using HTML5/WebGL, web development standard technology and open source. Firstly, the collected disaster site survey 2D data is constructed as a spatial DB using GeoServer's WMS service and PostGIS provided an open source and rendered in a web environment. Secondly, in order to efficiently render large-capacity 3D point cloud data in a web environment, a Potree algorithm is applied to simplifies point cloud data into 2D tiles using a multi-resolution octree structure. Lastly, OpenLayers3 based 3D web mapping pilot system is developed for web visualization of 2D/3D spatial information by implementing basic and application functions for controlling and measuring 3D maps with Graphic User Interface (GUI). For the further research, it is expected that various 2D survey data and various spatial image information of a disaster site can be used for scientific investigation and analysis of disaster accidents by overlaying and visualizing them on a built web-based 3D geo-spatial information system.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.397-419
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• 2020

Business analytics is a management tool for achieving significant business performance improvements. Many organizations fail to or only partially achieve their business objectives and goals from business analytics. Business analytics adoption is a multi-stage complex activity consisting of evaluation, adoption, and assimilation stages. Several research papers have been published in the field of business analytics, but the research on multi-stage BA adoption is fewer in number. This study contributes to the scant literature on the multi-stage adoption model by identifying the critical themes for evaluation, adoption, and assimilation stages of business analytics. This study uses the thematic content analysis of peer-reviewed published academic papers as a research technique to explore the key themes of business analytics adoption. This study links the critical themes with the popular theoretical foundations: Resource-Based View (RBV), Dynamic Capabilities, Diffusion of Innovations, and Technology-Organizational-Environmental (TOE) framework. The study identifies twelve major factors categorized into three key themes: organizational characteristics, innovation characteristics, and environmental characteristics. The main organizational factors are top management support, organization data environment, centralized analytics structure, perceived cost, employee skills, and data-based decision making culture. The major innovation characteristics are perceived benefits, complexity, and compatibility, and information technology assets. The environmental factors influencing BA adoption stages are competition and industry pressure. A conceptual framework for the multi-stage BA adoption model is proposed in this study. The findings of this study can assist the practicing managers in developing a stage-wise operational strategy for business analytics adoption. Future research can also attempt to validate the conceptual model proposed in this study.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.118-128
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• 2015

Recently BIM technology has been expanded for using in construction project. Due to the high-cost of BIM infrastructure development, lack of regulations, lack of process and so forth, usage of BIM has been delayed than initial expectations. In design phase, especially, collaboration based on BIM system has been a key factor for successful next generation building project. Through the analysis of current research trends about IT technologies, virtualization and BIM service, data exchange such as drawings, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. The purpose of this study is to enable the cloud computing BIM server to provide several main functions such as editing models, 3D model viewing and checking, mark-up and snapshot in high-performance quality by proper design of VDI system. Concurrent client connection performance is a main technical index of VDI. Through testing of test-bed server client, developed VDI system's multi-connect control is evaluated. Performance-test result of BIM server VDI effect to development direction of cloud computing BIM service for commercialization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1091-1110
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• 2016

Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.151-152
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• 2016

최근 컴퓨터 자원을 효율적으로 사용 가능한 클라우드 컴퓨팅 기술의 활용이 증가하고 있다. 특히, 클라우드 컴퓨팅 환경에서 단순 하나의 클라우드 컴퓨팅 서비스의 제약을 넘어 2개 이상의 클라우드 서비스를 활용할 수 있는 멀티 클라우드에 대한 연구가 활발히 진행되고 있다. 멀티 클라우드란 2개 이상의 클라우드 서비스가 상호 협약을 통해 사용자에게 컴퓨팅 자원을 추가적으로 지원해주는 기술로, 기존 환경에서는 각각의 클라우드 서비스에 인증을 해야 하는 다중 인증 기술이 활용 되었다. 본 논문에서는 기존의 멀티 인증 과정을 단순히 하기 위해, 사용자가 특정 클라우드 서비스에 가입 후, 다른 클라우드 서비스 이용 시 브로커를 활용하여 유저가 추가적인 인증 과정 없이 2개 이상의 클라우드 서비스 이용이 가능한 인증 기법을 제안하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.287-288
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• 2009

Multi-query optimization (MQO) is a critical research issue in the real-time data stream management system (DSMS). We propose to address this problem in the ubiquitous GIS (u-GIS) environment, focusing on grouping 'similar' spatio-temporal queries incrementally into N clusters so that they can be processed virtually as N queries. By minimizing N, the overlaps in the data requirements of the raw queries can be avoided, which implies the reducing of the total disk I/O cost. In this paper, we define the spatio-temporal query clustering problem and give a data cubing approach (Q-cube), which is expected to be implemented in the cloud computing paradigm.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.60-70
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• 2018

A software defined storage (SDS) is being deployed in cloud environment to allow multiple users to virtualize physical servers, but a solution for optimizing space efficiency with limited physical resources is needed. In the conventional data deduplication system, it is difficult to deduplicate redundant data uploaded to distributed storages. In this paper, we propose a distributed deduplication method using similarity-based clustering and multi-layer bloom filter. Rabin hash is applied to determine the degree of similarity between virtual machine servers and cluster similar virtual machines. Therefore, it improves the performance compared to deduplication efficiency for individual storage nodes. In addition, a multi-layer bloom filter incorporated into the deduplication process to shorten processing time by reducing the number of the false positives. Experimental results show that the proposed method improves the deduplication ratio by 9% compared to deduplication method using IP address based clusters without any difference in processing time.