• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.40-48
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• 2024

Quantum computers can likely perform computations that are unattainable by classical computers, and they represent the next generation of computing technologies. Due to high costs and complex maintenance, direct ownership of quantum computers by individuals users is challenging. Future utilization is predicted to involve quantum computing servers performing delegated computations for clients lacking quantum capabilities, similar to the current utilization of supercomputing. This delegation model allows several users to benefit from quantum computing without requiring ownership, thereby providing innovation potential in various fields. Ensuring data privacy and computational integrity in this model is critical for ensuring the reliability of quantum cloud computing services. However, these requirements are difficult to achieve because classical security techniques cannot be directly applied to quantum computing. We review research on security protocols for the delegation of quantum computing with focus on data privacy and integrity verification. Our analysis covers the background of quantum computing, privacy-preserving quantum computational models, and recent research trends. Finally, we discuss challenges and future directions for secure quantum delegated computations, highlighting their importance for the commercialization and widespread adoption of quantum computing.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1424-1434
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• 2009

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

• The Journal of Information Systems
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• v.16 no.2
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• pp.69-91
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• 2007

The mobile computing environment has already matured and mobile services are activated throughout many industries. In the following years, these changes are expected to evolve into a ubiquitous computing environment. In the meantime, whether newly developed information technologies will thrive or diminished depends on user's intention to adopt them. Hence, the necessity of user-centered research considering ubiquitous computing in mobile computing environment is obvious. This study, thus, investigated ubiquitous factors in various literature related to ubiquitous computing and technology acceptance and it proposes a research model of the ubiquitous factors affecting user's intention to use mobile services, in terms of meaning(connectivity, mobility), service(contextual offer), compatibility(compatibility), and infrastructure(privacy, truth). The proposed model is expected to help both researchers and practitioners extend their understanding about the ubiquitous factors in mobile computing environment

• Journal of Information Technology Services
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• v.10 no.2
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• pp.189-202
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• 2011

It is important issue how to evaluate the economic feasibility of computing factors in the real world when we build ubiquitous spaces. In this paper, we propose a simple model that can evaluate the economic feasibility of mobile RFID-based ubiquitous computing system which enables seamless communication between offline and online via embedded computing factors in the real world. To achieve this, we explore the meaning of mobile RFID system, the difference between our research and extant researches concerning the evaluation of economic feasibility in RFID system, and propose the so-called 'Tag-based Evaluation Model' (TEM) which is an evaluation model to access the economic feasibility of mobile RFID systems. We also analyze the TEM via simulation cases based on proposed model and discuss the future of TEM.

• Journal of the Korean Society of Systems Engineering
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• v.1 no.2
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• pp.5-11
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• 2005

Ubiquitous computing is an emerging technic for various areas such as public, private (individual), military, industrial, medical sectors. The applications of ubiquitous computing are expected to be prevailed from home to office. Unfortunately, it is not effective to apply existing system/software development methodologies into this emerging ubiquitous computing applications. In this paper, MBASE (Model-Based system Architecting and Software Engineering) is applied as a development method of ubiquitous computing applications. The advantage of MBASE is to identify mismatches of product, process, property, and success models and resolve them in developing the ubiquitous computing applications. A SmartView, a ubiquitous computing application, is presented as a case study o f MBASE.

• The Journal of Information Systems
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• v.31 no.2
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• pp.63-88
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• 2022

Purpose The purpose of this study is to empirically analyze the factors affecting the intention to use cloud computing in the smart work environment. This study is meaningful in that it examines the characteristics of smart work and the fit of cloud computing characteristics, and it is a study that reveals the factors affecting the intention to use cloud computing by applying the integrated model of TTF and TAM. Design/methodology/approach In order to understand the factors affecting the intention to use cloud computing in the smart work environment, a research model that integrates TTF and TAM with the hypothesis was proposed. In order to verify the research hypothesis, this study conducted a survey on individuals with experience in smart work and cloud computing. And with the data 280 collected in the survey, path analysis was performed using the PLS structural equation. Findings As a result, it was found that task characteristics and technology characteristics had a positive (+) effect on task-skill fit, and task-skill fit had a positive (+) effect on perceived ease of use and usefulness. Also, task-skill fit, perceived ease of use, and perceived usefulness were found to have a positive (+) effect on intention to use.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.13-23
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• 2011

Grid computing is a new generation computing technology which organizes virtual high-performance computing system by connecting and sharing geographically distributed heterogeneous resources, and performing large-scaled computing operations. In order to maximize the performance of grid computing, job scheduling is essential which allocates jobs to resources effectively. Many studies have been performed which minimize total completion times, etc. However, resource costs are also important, and through the minimization of resource costs, the overall performance of grid computing and economic efficiency will be improved. So in this paper, we propose a multi-objective job scheduling model considering both time and cost. This model derives from the optimal scheduling solution using NSGA-II, which is a multi objective genetic algorithm, and guarantees the effectiveness of the proposed model by executing experiments with those of existing scheduling models such as Min-Min and Max-Min models. Through experiments, we prove that the proposed scheduling model minimizes time and cost more efficiently than existing scheduling models.

• Journal of Digital Convergence
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• v.7 no.4
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• pp.43-56
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• 2009

The concept causing all the fuss is "the utility computing or the usage-based IT service", which now represents the future for IT asset in all aspects of the way they work in business, the commercial and public sector. The core of "utility computing or usage-based IT service" is changing the IT assert from "ownership" to "borrowing", which enables managers to get greater utilization of data-centre resources at lower operating costs. This trend is spreaded in public sector centering the Governmental Internet data Center of Korea(NCIA). So, it has need to make an usage-based IT service model that is suitable for public sector. In this paper, we propose the usage-based IT service model that is composed of IT service framework, service pricing model and IT service architecture.