• Computers and Concrete
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• v.1 no.3
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• pp.303-324
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• 2004

The Component-Based Software Development (CBSD) has established itself as a sound paradigm in the software engineering discipline and has gained wide spread acceptance in the industry. The CBSD relies on the availability of standard software components for encapsulation of specific functionality. This paper presents the framework for the development of a software component for the design of general member cross-sections. The proposed component can be used in component-based structural engineering software or as a stand-alone program developed around the component. This paper describes the use-case scenarios for the component, its design patterns, object models, class hierarchy, the integrated and unified handling of cross-section behavior and implementation issue. It is expected that a component developed using the proposed patterns and model can be used in analysis, design and detailing packages to handle reinforced concrete, partially prestressed concrete, steel-concrete composite and steel sections. The component can provide the entire response parameters of the cross section including determination of geometric properties, elastic stresses, flexural capacity, moment-curvature, and ductility ratios. The component can also be used as the main computational engine for stand-alone section design software. The component can be further extended to handle the retrofitting and strengthening of cross-sections, shear and torsional response, determination of fire-damage parameters, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.370-378
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• 2014

It is well known that data mining plays a crucial role in varities of real-world applications, by which extracts knowledge from large volume of datasets. Among functionalties provided by data mining, frequency mining over given multisets is a basic and essential one. However, most of users would like to obtain the frequency over their multisets without revealing their own multisets. In this work, we come up with a novel way to achive this goal and prove its security rigorously. Our scheme has several advantages over existing work as follows: Firstly, our scheme has the most efficient computational complexity in the cardinality of multisets. Further our security proof is rigorously in the simulation paradigm. Lastly our system assumption is general.

• Journal of Engineering Education Research
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• v.22 no.6
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• pp.3-11
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• 2019

To evaluate the suitability of UML (Unified Modelling Language) in terms of educating novice software engineers, we have conducted a survey study with 102 students who were enrolled in a mandatory course for sophomores in computer science and engineering department. The results indicate that UML 1) has high satisfaction rate among software novices as an education material, 2) improves computational thinking and problem-solving skills, and 3) increases the efficacy of learning when the education program is implemented in the order of UML, programming practice, and physical computing. This paper suggests the applicability of UML as a new education paradigm in software education.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.924-926
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• 2006

Sensor networks are an emerging area of mobile computing. Networked sensors represent a new design paradigm enabled by advances in micro electro-mechanical systems (MEMS) and low power technology. Created with integrated circuit (IC) technology and combined with computational logic, these 'smart' sensors have the benefit of small size, low cost and power consumption, and, the capability to perform on-board computation. Though this recent technological innovation has shown a significant promise in many application domains, it has also exposed several technical limitations that must be improved. In this paper, we discuss the system deploy issues for infrared thermo sensor camera calibration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.117-129
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• 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average- and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed- and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.257-267
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• 2014

Distributed compressive video sensing (DCVS) is a low cost sampling paradigm for video coding based on the compressive sensing and the distributed video coding. In this paper, we propose using a skip-mode coding in DCVS under the assumption that in case of high temporal correlation, temporal interpolation can guarantee sufficiently good quality of nonkey frame, therefore no need to transmit measurement data in such a nonkey frame. Furthermore, we extend it to use a hierarchical structure for better temporal interpolation. Simulation results show that the proposed skip-mode coding can save the average subrate of whole video sequence while the PSNR is reduced only slightly. In addition, by using the proposed scheme, the computational complexity is also highly decreased at decoder on average by 43.75% for video sequences that have strong temporal correlation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.25-32
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• 2005

The spread of mobile devices, PDAs and sensors has enabled the construction of ubiquitous computing environments, transforming regular physical spaces into 'Smart space' augmented with intelligence and enhanced with services. However, the deployment of this computing paradigm in real-life is disturbed by poor security, particularly, the lack of proper authentication and authorization techniques. Also, it is very important not only to find security measures but also to preserve user privacy in ubiquitous computing environments. In this Paper, we propose efficient user authentication and authorization model with anonymity for the privacy-preserving for ubiquitous computing environments. Our model is suitable for distributed environments with the computational constrained devices by using MAC-based anonymous certificate and security association token instead of using Public key encryption technique. And our Proposed Protocol is better than Kerberos system in sense of cryptographic computation processing.