• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3254-3272
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• 2017

With the development of wireless access technologies and the popularity of mobile intelligent terminals, cloud computing is expected to expand to mobile environments. Attribute-based encryption, widely applied in cloud computing, incurs massive computational cost during the encryption and decryption phases. The computational cost grows with the complexity of the access policy. This disadvantage becomes more serious for mobile devices because they have limited resources. To address this problem, we present an efficient verifiable outsourced scheme based on the bilinear group of prime order. The scheme is called the verifiable outsourced computation ciphertext-policy attribute-based encryption scheme (VOC-CP-ABE), and it provides a way to outsource intensive computing tasks during encryption and decryption phases to CSP without revealing the private information and leaves only marginal computation to the user. At the same time, the outsourced computation can be verified by two hash functions. Then, the formal security proofs of its (selective) CPA security and verifiability are provided. Finally, we discuss the performance of the proposed scheme with comparisons to several related works.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.387-396
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• 2004

In order to keep and increase a competitive potential, industrial enterprises have to reduce their costs for product development as well as shorten lead time in product development processes. Moreover they have to respond to market factors and conditions such as increasing demands for functionality and individuality of products, short product life cycles, high pressure on prices and time to market. The improved functional requirement in connection with high time and cost pressure lead to high risk in product development. Technological fine improvements in connection with high time and cost pressure lead to high development risk. To cope with these challenges many enterprises have to collaborate globally. The collaborative engineering in product development is aimed to create distributed collaborative corporations and to facilitate the management of design conflicts. This paper provides a methodology for analyzing collaborative design process as well as the tools and the framework to support collaborative product development. The methodology can identify the interdependences among design tasks and teams. The tools and framework are implemented to facilitate the management of product development process.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.78-84
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• 2008

This paper presents a fast modeling technique of virtual pottery using force feedback based on a circular sector element method. Previous techniques for simulating deformable objects such as finite element method (FEM) are limited in real-time haptic rendering due to their complexity and expensive computational cost. In our model, circular sector elements which fully represent features of pottery's shape are closely gathered and piled together. This allows efficient deformable object modeling through a decrease in the number of elements and reducing computational cost.

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.41-46
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• 2015

This paper describes study results on the development of an automatic program for generating surface-panel grid for the aircraft optimal design. The aerodynamic analysis is combined into a PIDO tool in conjunction with a number of programs in order to integrate processes for the optimal design. Due to design optimization's iterative feature, it may require lots of time and cost. To relieve this problem, cost-reduction of computation time for aerodynamic analysis is pursued by using the Panel-method, and reduction of grid generation time by automating surface panelling.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2262-2267
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• 2018

In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.

• Korean Management Science Review
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• v.29 no.3
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• pp.107-120
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• 2012

In this paper we propose an effective genetic algorithm for solving the integrated inventory and routing problem of supply chain composed of multi-warehouses and multi-retailers. Unlike extant studies dealing with integrated inventory and routing problem of supply chain, our model incorporates more realistic aspect such as positive inventory at the multi-warehouses under the assumption of inventory policy of power of two-replenishment-cycle. The objective is to determine replenishment intervals for the retailers and warehouses as well as the vehicles routes so that the total cost of delivery and inventory cost is minimized. A notable feature of our algorithm is that the procedure for evaluating the fitness of objective function has the computational complexity closing to linear function. Computational results show effectiveness of our algorithm.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.225-233
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• 2012

A comprehensive research effort in order to develop and disseminate modernized Korean housing (Hanok) has recently been initiated by Korean government. This large scale research project encompasses a wide spectrum of housing development including public policy, architectural plans, modules, construction materials and methods, prefabricated assemblies, automated production, construction management, and advanced information systems. For the purpose of integrating and automating the whole processes from an industry perspective, it is of great importance to develop a standard classification system and project numbering system (PNS) for the modernized Korean housing. This paper focuses on the standard classification systems and PNS for cost and schedule control. The distinct characteristics and managerial requirements were explored and embedded into the proposed classifications for modernized Hanok.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.134-139
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• 1992

This study introduces simple derivation of optimum load factors based on both cornell's MFOSM (Mean First Order End Moment) methods and Lind - Hasofers AFOSM (Advanced First Order 2nd Moment) methods and demonstrates the relationship between the optimum reliability, the load factors, the probability distributions selected to model the load, and a measure of relative failure cost. Although some of the cost parameters cannot be evaluated accurately and the upper tail characteristics of the distributions of the random loads remain uncertainty, this optimum reliability formulation provides insight on which Parameters are most significant in selecting appropriate load criteria for structure design.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1881-1897
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• 1994

This paper presents a neural network-based computational scheme to generate the optimized robotic assembly sequence for an assembly product consisting of a number of parts. An assembly sequence is considered to be optimal when it meets a number of conditions : it must satisfy assembly constraints, keep the stability of in-process subassemblies, and minimize assembly cost. To derive such an optimal sequence, we propose a scheme using both the Hopfield neural network and the expert system. Based upon the inferred precedence constraints and the assembly costs from the expert system, we derive the evolution equation of the network. To illustrate the suitability of the proposed scheme, a case study is presented for industrial product of an electrical relay. The result is compared with that obtained from the expert system.