• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.625-627
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• 2017

Cardiovascular disease is the leading cause of death in America [1]. This kind of situation leads researcher to find out how to analyze the disease without using a living human heart. Computer simulation is the solution. Based on the existed clinical data and mathematical formulas from the journals, we can simulate a human heart activity using a computer. Moreover, we can also use the existed biological data in our simulation program, such as CellML (Cell Markup Language) [2].

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1520-1542
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• 2020

Traditional software testing typically uses many physical resources to manually build various test environments, resulting in high resource costs and long test time due to limited resources, especially for small enterprises. Cloud computing can provide sufficient low-cost virtual resources to alleviate these problems through the virtualization of physical resources. However, the provision of various test environments and services for implementing software testing rapidly and conveniently based on cloud computing is challenging. This paper proposes a multilayer cloud testing model based on cloud computing and implements a hybrid cloud testing system based on virtual machines (VMs) and networks. This system realizes the automatic and rapid creation of test environments and the remote use of test tools and test services. We conduct experiments on this system and evaluate its applicability in terms of the VM provision time, VM performance and virtual network performance. The experimental results demonstrate that the performance of the VMs and virtual networks is satisfactory and that this system can improve the test efficiency and reduce test costs through rapid virtual resource provision and convenient test services.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.530-535
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• 2004

This paper considers a state set estimation (SSE) based model predictive control (MPC) for linear parameter- varying (LPV) systems with input constraint. We estimate, at each time instant, a feasible set of all states which are consistent with system model, measurements and a priori information, rather than the state itself. By combining a state-feedback MPC and an SSE, we design an SSE-based MPC algorithm that stabilizes the closed-loop system. The proposed algorithm is solved by semi-de�nite program involving linear matrix inequalities. A numerical example is included to illustrate the performance of the proposed algorithm.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10539-10542
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• 2015

A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps, firstly choosing the risk factors by combining two feature selection algorithms, then providing the predictive value by neural network. Based on the method framework, an algorithm LCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practical applications. The proposed method is suitable for health monitoring and self-testing. Experiments showed it can actually provide satisfactory accuracy under low dimensions of risk factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2480-2495
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• 2014

This paper describes a hierarchical method for image-based age estimation that combines age group classification and age value estimation. The proposed method uses a coarse-to-fine strategy with different appearance features to describe facial shape and texture. Considering the damage to continuity between neighboring groups caused by fixed divisions during age group classification, a dynamic grouping technique is employed to allow non-fixed groups. Based on the given group, an ordinal hyperplane ranking (OHRank) model is employed to transform age estimation into a series of binary enquiry problems that can take advantage of the intrinsic correlation and ordinal information of age. A set of experiments on FG-NET are presented and the results demonstrate the validity of our solution.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1503-1516
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• 2019

In this paper, to improve the accuracy of long sentence similarity calculation, we proposed a sentence similarity calculation method based on a system similarity function. The algorithm uses word2vector as the system elements to calculate the sentence similarity. The higher accuracy of our algorithm is derived from two characteristics: one is the negative effect of penalty item, and the other is that sentence similar function (SSF) based on word2vector similar elements doesn't satisfy the exchange rule. In later studies, we found the time complexity of our algorithm depends on the process of calculating similar elements, so we build an index of potentially similar elements when training the word vector process. Finally, the experimental results show that our algorithm has higher accuracy than the word mover's distance (WMD), and has the least query time of three calculation methods of SSF.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.471-472
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• 2007

We have demonstrated that the light extraction efficiency of GaN based light emitting diodes (LEDs) can be significantly enhanced by using photonic crystal and microcavity (PCMC) effects. It was found that the extraction efficiency of the PCMC-LEDs is 9.5 times larger than that of the normal LEDs.

• Journal of Electrical Engineering and Technology
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• v.2 no.1
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• pp.68-80
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• 2007

This paper covers switched reluctance generator (SRG) and its comparison with induction and synchronous machines for distributed generation. The SRG is simple in design, robust in construction, and fault tolerant in operation; it can also withstand very high temperatures. However, the performance and cost of the SRG power electronics driver are highly affected by the topology and design of the converter. IGBT and MOSFET based converters are not suitable for very high power applications. This paper presents thyristor-based resonant converters which are superior candidates for very high power applications. Operations of the converters are analyzed and their characteristics and dynamics are determined in terms of the system parameters. The resonant converters are capable of handling high currents and voltages; these converters are highly efficient and reliable as well. Therefore, they are suitable for high power applications in the range of 1MW or larger for distributed generation.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.970-986
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• 2017

Certificateless public key cryptography (CL-PKC) is a new benchmark in modern cryptography. It not only simplifies the certificate management problem of PKC, but also avoids the key escrow problem of the identity based cryptosystem (ID-PKC). In this article, we propose a certificateless blind signature protocol which is based on elliptic curve cryptography (CLB-ECC). The scheme is suitable for the wireless communication environment because of smaller parameter size. The proposed scheme is proven to be secure against attacks by two different kinds of adversaries. CLB-ECC is efficient in terms of computation compared to the other existing conventional schemes. CLB-ECC can withstand forgery attack, key only attack, and known message attack. An e-cash framework, which is based on CLB-ECC, has also been proposed. As a result, the proposed CLB-ECC scheme seems to be more effective for applying to real life applications like e-shopping, e-voting, etc., in handheld devices.