• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.101-108
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• 2013

In this paper, we propose a method in which the negative acknowledge (NACK) message is used as command for cooperation and spectrum sharing. This allows for an automatic request for cooperation and sharing when the direct link of the primary user is in outage, and also allows for saving the number of control messages in cooperation-spectrum sharing based paradigm. In the sharing phase, the selected relay shares a power fraction of $1-{\alpha}$ for secondary transmitted signal while the remaining of ${\alpha}$ is for primary retransmitted signal. In the case of no relay collected, primary transmitter uses NACK as a command to retransmit the signal with fully power fraction (${\alpha}=1$). Both systems are assumed to employ BPSK signals. In this scheme, we propose the joint optimal decoding in the secondary user. The frame error rate (FER) performance at both systems is then analyzed. The theoretical and simulation results validate the analysis and confirm the efficiency of the protocol.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.1-8
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• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Journal of Welding and Joining
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• v.35 no.2
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• pp.43-51
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• 2017

The automatic welding systems, have received much attention in recent years, because they are highly suitable not only to increase the quality and productivity, but also to decrease manufacturing time and cost for a given product. Automatic welding work in semiconductor or space industry to be carried out in pipe line and butt joint mostly and plasma arc welding(PAW) is actively applied. To get the desired quality welds in automated welding system is challenging, a mathematical model is needed that has complete control over the relevant process parameters in order to obtain the required mechanical properties. However, In various industries the welding process mathematical model is not fully formulated for the process parameter and on the welding conditions, therefore only partial variables can be predicted. Therefore, this paper investigates the interaction between the welding parameters and mechanical properties for predicting the weld bead geometry by analyzing the S/N ratio.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1509-1516
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• 2017

In first-person perspective training system, the users needs realistic experience. For providing this experience, the system should offer the users virtual and real images at the same time. We propose an automatic a persons's arm segmentation and image composition method. It consists of arm segmentation part and image composition part. Arm segmentation uses an arbitrary image as input and outputs arm segment or alpha matte. It enables end-to-end learning because we make use of FCN in this part. Image composition part conducts image combination between the result of arm segmentation and other image like road, building, etc. To train the network in arm segmentation, we used arm images through dividing the videos that we took ourselves for the training data.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.277.1-277.1
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• 2013

Molecular diagnostics consists of three processes, which are a sample pretreatment, a nucleic acid amplification, and an amplicon detection. Among three components, sample pretreatment is an important process in that it can increase the limit of detection by purifying nucleic acid in biological sample from contaminants that may interfere with the downstream genetic analysis such as nucleic acid amplification and detection. To achieve point-of-care virus detection system, the sample pretreatment process needs to be simple, rapid, and automatic. However, the commercial RNA extraction kits such as Rneasy (Qiagen) or MagnaPure (Roche) kit are highly labor-intensive and time-consuming due to numerous manual steps, and so it is not adequate for the on-site sample preparation. Herein, we have developed a rotary microfluidic system to extract and purify the RNA without necessity of external mechanical syringe pumps to allow flow control using microfluidic technology. We designed three reservoirs for sample, washing buffer, and elution buffer which were connected with different dimensional microfluidic channels. By controlling RPM, we could dispense a RNA sample solution, a washing buffer, and an elution buffer successively, so that the RNA was captured in the sol-gel solid phase, purified, and eluted in the downstream. Such a novel rotary sample preparation system eliminates some complicated hardwares and human intervention providing the opportunity to construct a fully integrated genetic analysis microsystem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1252-1271
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• 2013

Automatic image annotation has become an increasingly important research topic owing to its key role in image retrieval. Simultaneously, it is highly challenging when facing to large-scale dataset with large variance. Practical approaches generally rely on similarity measures defined over images and multi-label prediction methods. More specifically, those approaches usually 1) leverage similarity measures predefined or learned by optimizing for ranking or annotation, which might be not adaptive enough to datasets; and 2) predict labels separately without taking the correlation of labels into account. In this paper, we propose a method for image annotation through collaborative similarity metric learning from dataset and modeling the label correlation of the dataset. The similarity metric is learned by simultaneously optimizing the 1) image ranking using structural SVM (SSVM), and 2) image annotation using correlated label propagation, with respect to the similarity metric. The learned similarity metric, fully exploiting the available information of datasets, would improve the two collaborative components, ranking and annotation, and sequentially the retrieval system itself. We evaluated the proposed method on Corel5k, Corel30k and EspGame databases. The results for annotation and retrieval show the competitive performance of the proposed method.

• Progress in Superconductivity and Cryogenics
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• v.19 no.1
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• pp.5-8
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• 2017

A series of high gradient superconducting magnetic separator (HGMS) for kaolin has been developed. It is used for processing kaolin to increase the brightness or whiteness whether it is for paper or ceramic applications. The HGMS system mainly consists of a solenoid magnet with a zero boil-off helium cryostat, a double reciprocating canisters system, and a PLC (Process Logic Controller) fully automatic control system based on SCADA (Supervisory Control and Data Acquisition) system. We have successfully developed CGC-5.5/300 and CGC-5.0/500 HGMS systems in the recent years, and now three sets of them are on-site operation in different customers. This paper will present recent progress of the HGMS system, the results of some experiments on processing kaolin clay used HGMS, and the on-site operation.

• International Journal of Fluid Machinery and Systems
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• v.8 no.3
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• pp.142-154
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• 2015

Nowadays, computational fluid dynamics is commonly used by design engineers to evaluate and compare losses in hydraulic components as it is less expensive and less time consuming than model tests. For that purpose, an automatic tool for casing and distributor analysis will be presented in this paper. An in-house mesh generator and a Reynolds Averaged Navier-Stokes equation solver using the standard $k-{\omega}$ shear stress transport (SST) turbulence model will be used to perform all computations. Two solvers based on the C++ OpenFOAM library will be used and compared to a commercial solver. The performance of the new fully coupled block solver developed by the University of Lucerne and Andritz will be compared to the standard 1.6ext segregated simpleFoam solver and to a commercial solver. In this study, relative comparisons of different geometries of casing and distributor will be performed. The present study is thus aimed at validating the block solver and the tool chain and providing design engineers with a faster and more reliable analysis tool that can be integrated into their design process.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.171-176
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• 2002

This paper describes a new automated analysis system for model plane engine. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy knowledge processing and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes, ANSYS, and one of commercial solid modelers, Designbase, The system allows a geometry model of concern to be automatically converted to different FE models, depending on physical phenomena of plane engine to be analyzed, i.e. deformation analysis, thermal analysis and so on. The FE models are then automatically analyzed by the FE analysis code. Among a whole process of analysis, the definition of a geometry model, the designation of local node patterns, the assignment of material properties and boundary conditions onto the geometry model are only the interactive processes to be done by a user. The interactive operations can be processed in a few minutes. The other processes which are time consuming and labour-intensive in conventional CAE systems are fully automatically performed in a personal computer environment. The proposed analysis system is successfully applied to evaluate a model plane entwine.