• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1037-1044
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• 2014

A (t,n) threshold secret sharing scheme is the scheme which allows a trusted party to distribute the shares among n participants in such a way that any t of them can recover the original secret, but any group knowing only t-1 or fewer shares can not. Recently, Eslami et al. and Tadayon et al. proposed threshold multi-secret sharing schemes, respectively. They proposed that their schemes don't require secure channels. But, without secure channels in their schemes, everyone can get the shares and find the secrets. The proposed scheme does not use secure channels and only t participants can solve the equations of the system from the delivered share shadows and find the secrets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1278-1290
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• 2008

This paper proposes a preprocessing method and a neural network based character recognizer to enhance the overall performance of the license plate recognition system. First, plate outlines are extracted by virtual line matching, and then the 4 vertexes are obtained by calculating intersecting points of extracted lines. By these vertexes, plate image is reconstructed as rectangle-shaped image by bilinear transform. Finally, the license plate is recognized by the neural network based classifier which had been trained using delta-bar-delta algorithm. Various license plate images were used in the experiments, and the proposed plate normalization enhanced the recognition performance up to 16 percent.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.31-38
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• 2021

The precast-buckling restrained braces(PC-BRB) reinforced with engineering plastics that can compensate for the disadvantages in the manufacturing process of the existing buckling restrained brace. In this study, to examine the applicability of PC-BRB to actual structures, example structures similar to school facilities were selected and the reinforcement effect was analyzed analytically according to the damping design procedure of PC-BRB. Load-displacement curve through the incremental loading test appeared similar to the bilinear curve. Applying test result, Analytical model of PC-BRB model was constructed and applied to the example structure. As a result of the analysis, the PC-BRB showed stable hysteresis behavior without lowering the strength, and the inter story drift ratio and the shear force were reduced due to the damping effect. In addition, the reduction ratio of the shear force was similar to the reduction ratio assumed when designing the damping device.

• Composites Research
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• v.20 no.1
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• pp.8-14
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• 2007

Nonlinear aeroelastic analyses of composite wing with flap are performed considering free-play and dynamic stiffness of actuator. Doublet-Hybrid method is used for the calculation of subsonic unsteady aerodynamic forces. Free-play is modeled as a bilinear spring and is linearized by using the describing function method. Dynamic stiffness is obtained from governing equation of gear system and the aeroelastic analyses were performed according to ply-angle of laminate and material. The linear and nonlinear flutter analysis results show that the flutter characteristics are significantly dependent on the free-play and dynamic stiffness. from the nonlinear flutter analysis, various types of limit cycle oscillations are observed in a range of air speeds below or above the linear divergent flutter boundary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1687-1707
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• 2022

With the development of multiuser online meetings, more group-oriented technologies and applications for instance collaborative work are becoming increasingly important. Authenticated Group Key Agreement (AGKA) schemes provide a shared group key for users with after their identities are confirmed to guarantee the confidentiality and integrity of group communications. On the basis of the Public Key Cryptography (PKC) system used, AGKA can be classified as Public Key Infrastructure-based, Identity-based, and Certificateless. Because the latter type can solve the certificate management overhead and the key escrow problems of the first two types, Certificateless-AGKA (CL-AGKA) protocols have become a popular area of research. However, most CL-AGKA protocols are vulnerable to Public Key Replacement Attacks (PKRA) due to the lack of public key authentication. In the present work, we present a CL-AGKA scheme that can resist PKRA in order to solve impersonation attacks caused by those attacks. Beyond security, improving scheme efficiency is another direction for AGKA research. To reduce the communication and computation cost, we present a scheme with only one round of information interaction and construct a CL-AGKA scheme replacing the bilinear pairing with elliptic curve cryptography. Therefore, our scheme has good applicability to communication environments with limited bandwidth and computing capabilities.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.91-100
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• 2016

In FPGA-based real-time image warping systems, image caches are utilized for fast readout of image pixel data and reduction of memory access rate. However, a cache algorithm for a general computer system is not suitable for real-time performance because of time delays from cache misses and on-line computation complexity. In this paper, a simple image cache algorithm is presented for a FPGA-based real-time image warping system. Considering that pixel data access sequence is determined from the 2D coordinate transformation and repeated identically at every image frame, a cache load sequence is off-line programmed to guarantee no cache miss condition, and reduced on-line computation results in a simple cache controller. An overall system structure using a FPGA is presented, and experimental results are provided to show accuracy and validity of the proposed cache algorithm.

• Atmosphere
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• v.25 no.2
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• pp.271-281
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• 2015

The objectives of this study are to develop a hydrological drought outlook system using GloSea5 (Global Seasonal forecasting system 5) which has recently been used by KMA (Korea Meteorological Association) and to evaluate the forecasting capability. For drought analysis, the bilinear interpolation method was applied to spatially downscale the low-resolution outputs of GloSea5 and PR (Predicted Runoff) was produced for different lead times (i.e., 1-, 2-, 3-month) running LSM (Land Surface Model). The behavior of PR anomaly was similar to that of HR (Historical Runoff) and the estimated values were negative up to lead times of 1- and 2-month. For the evaluation of drought outlook, SRI (Standardized Runoff Index) was selected and PR_SRI estimated using PR. ROC score was 0.83, 0.71, 0.60 for 1-, 2- and 3-month lead times, respectively. It also showed the hit rate is high and false alarm rate is low as shorter lead time. The temporal Correlation Coefficient (CC) was 0.82, 0.60, 0.31 and Root Mean Square Error (RMSE) was 0.52, 0.86, 1.20 for 1-, 2-, 3-month lead time, respectively. The accuracy of PR_SRI was high up to 1- and 2-month lead time on local regions except the Gyeonggi and Gangwon province. It can be concluded that GloSea5 has high applicability for hydrological drought outlook.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.118-129
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• 2009

The ISO 18000-7 Active RFID standard, a single channel system operating in the 433Mhz, faces technical difficulties in supporting some recently introduced application demands because of its low transmission rates and radio interference between readers. We propose a new multi-channel active RFID system operating in the 2.4Ghz. The special feature of the proposed system is that a reader makes use of multiple interfaces to improve its performance like a multi-core processor. However if only a small part of interfaces are actually used, the performance improvement would not meet the expectation. To overcome this problem, a new multi-channel multi-interface active RFID protocol, which balances communication loads among all available interfaces, is necessary. 3 protocols, named as "Aggregated", "LP-Combined", "AP-Balanced", are proposed. Through simulation, we compare them for various conditions by changing number of tags, number of interfaces, tag data size. AP-Balanced shows the best performance and its performance increases almost linearly as the number of interface increases, which meets our expectation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.185-189
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• 2006

Time series analysis is a frequently effective method of constructing model and prediction in data processing of deformation monitoring. The monitoring data sample must to be as more as possible and time intervals are equal roughly so as to construct time series model accurately and achieve reliable prediction. But in the project practice of GPS deformation monitoring, the monitoring data sample can't be obtained too much and time intervals are not equal because of being restricted by all kinds of factors, and it contains many variates in the deformation model moreover. It is very important to study the data processing method for small samples and multi-variates time series in GPS deformation monitoring. A new method of establishing small samples and multi-variates deformation model and prediction model are put forward so as to resolve contradiction of small samples and multi-variates encountered in constructing deformation model and improve formerly data processing method of deformation monitoring. Based on the system theory, a deformation body is regarded as a whole organism; a time-dependence linear system model and a time-dependence bilinear system model are established. The dynamic parameters estimation is derived by means of prediction fit and least information distribution criteria. The final example demonstrates the validity and practice of this method.