• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.18-37
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• 2016

Cloud computing is an upcoming technology and emerging concept in the field of information technologies. Companies have begun to invest in cloud computing with the expectation that it will improve their business performances, operations, and processes. However, many companies are not so much aware of the cloud computing, so they can hesitate to adopt this new technology. The aims of the study are analyzing factors affecting the adoption of cloud computing and applying structural equation modeling technique to analyze the important dimensions of the adoption. Concordantly, previous studies are examined and expert interviews are arranged. Based on both our literature review and expert interviews, a model is proposed to measure the adoption of cloud computing. It is obvious that there are scarce researches about cloud computing adoption in the literature. Thus, the originality of the paper lies on that it proposes a research model for cloud computing adoption and it investigates various dimensions of cloud computing adoption in detail.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.1-11
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• 2015

The growing company that provides high quality service to every customer by introducing a cloud-system organization. However, the information needs of diverse and different, so every cloud system, and acts as a barrier to entry for cloud services provide appropriate. Cloud services are becoming complicated and diversified depending on concerns about cloud security continues, the growing need of professionalism held by the cloud service(Cloud Service Brokerage) CSB companies. Thus, to analyze the various services, find my support legislation, security and compatibility issues, the services of the best new business through service offerings tailored to the environment, and will implement the necessary management services which brokerage (CSB) is. This study presents a brokerage(CSB) development model, and suggested policy measures that apply to the co-op that I am having difficulties in cloud services business models.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.155-171
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• 2012

With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners' effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.

• Smart Structures and Systems
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• v.30 no.5
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• pp.501-511
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• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.132-144
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• 2014

Information always comes with security and risk problems. There is the saying that, "The tall tree catches much wind," and the risks from cloud services will absolutely be more varied and more severe. Nowadays, handling these risks is no longer just a technology problem. So far, a good deal of literature that focuses on risk or security management and frameworks in information systems has already been submitted. This paper analyzes the causal risk factors in cloud environments through critical success factors, from a business perspective. We then integrated these critical success factors into a business model for information security by mapping out 10 principles related to cloud risks. Thus, we were able to figure out which aspects should be given more consideration in the actual transactions of cloud services, and were able to make a business-level and general-risk control model for cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4197-4219
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• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.239-251
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• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.208-221
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• 2019

The inference for this research was concentrated on client's data protection in cloud computing i.e. data storages protection problems and how to limit unauthenticated access to info by developing access control model then accessible preparations were introduce after that an access control model was recommend. Cloud computing might refer as technology base on internet, having share, adaptable authority that might be utilized as organization by clients. Compositely cloud computing is software's and hardware's are conveying by internet as a service. It is a remarkable technology get well known because of minimal efforts, adaptability and versatility according to client's necessity. Regardless its prevalence large administration, propositions are reluctant to proceed onward cloud computing because of protection problems, particularly client's info protection. Management have communicated worries overs info protection as their classified and delicate info should be put away by specialist management at any areas all around. Several access models were accessible, yet those models do not satisfy the protection obligations as per services producers and cloud is always under assaults of hackers and data integrity, accessibility and protection were traded off. This research presented a model keep in aspect the requirement of services producers that upgrading the info protection in items of integrity, accessibility and security. The developed model helped the reluctant clients to effectively choosing to move on cloud while considerate the uncertainty related with cloud computing.

• The Journal of Information Systems
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• v.30 no.3
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• pp.65-91
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• 2021

Purpose In this study, we investigated the impact of perceived risk and switching costs on switching intention to cloud service based on PPM (Pull-Push-Mooring) model. Design/methodology/approach We focused on revealing the switching factors of the switching intention to the cloud services. The switching factors to the cloud services were defined as perceived risk consisting of performance risk, economic risk, and security risk, and switching costs consisting of financial and learning costs. On the PPM model, we defined the pull factors consisting of perceived usefulness and perceived ease of use, and the push factor as satisfaction of the legacy system, and the mooring factor as policy supports. Findings The results of this study as follows; (1) Among the perceived risk factors, performance risk has a negative effect on the ease of use of pull factors, and finally it was found to affect the switching intention to the cloud services. Therefore, cloud service providers need to improve trust in cloud services, service timeliness, and linkage to the legacy systems. And it was found that economic risk and security risk among the perceived risk factors did not affect the switching intention to the cloud services. (2) Of the perceived risk factors, financial cost and learning cost did not affect the satisfaction of the legacy system, which is a push factor. It indicates that the respondents are positively considering switching to cloud service in the future, despite the fact that the respondents are satisfied with the use of the legacy system and are aware of the switching cost to cloud service. (3) Policy support was found to improve the switching intention to cloud services by alleviating the financial and learning costs required for cloud service switching.