• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1539-1546
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• 2008

In the present age, a vehicle works important part in our lives and economical domain that transport people, freights, and everything. And both of its number and value are increasing more and more. But user's convenience, control system could not be archived improvement than technological success. In this paper, we suggest some kinds of administrative agendas; simplifying executive processes, designing vehicle information system using by RFID which includes Ubiquitous skill and optical communication network. Especially, this paper suggests public vehicle control model which ran simplify every executive processes of vehicle's life in the newest method. There are many kinds of RFID applicative products about transportation. And a dual invest should be interrupted for economical purpose. So we also proposes some way for problems of these types.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.23-29
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• 2019

Object recognition distinguish objects which are different from each other. But Face recognition distinguishes Identity of Faces with Similar Patterns. Feature extraction algorithm such as LBP, HOG, Gabor is being replaced with Deep Learning. As the technology that identify individual face with machine learning using Deep Learning Technology is developing, The Face Recognition Technology is being used in various field. In particular, the technology can provide individual and detailed service by being used in various offline environments requiring user identification, such as Smart Mirror. Face Recognition Technology can be developed as the technology that authenticate user easily by device like Smart Mirror and provide service authenticated user. In this paper, we present investigation about Face Recognition among various techniques for user authentication and analysis of Python source case of Face recognition and possibility of various service using Face Recognition Technology.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.407-412
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• 2019

In this paper, we propose a technique for processing of speech recognition in korean words. Speech recognition is a technology that converts acoustic signals from sensors such as microphones into words or sentences. Most foreign languages have less difficulty in speech recognition. On the other hand, korean consists of vowels and bottom consonants, so it is inappropriate to use the letters obtained from the voice synthesis system. That improving the conventional structure speech recognition can the correct words recognition. In order to solve this problem, a new algorithm was added to the existing speech recognition structure to increase the speech recognition rate. Perform the preprocessing process of the word and then token the results. After combining the result processed in the Levenshtein distance algorithm and the hashing algorithm, the normalized words is output through the consonant comparison algorithm. The final result word is compared with the standardized table and output if it exists, registered in the table dose not exists. The experimental environment was developed by using a smartphone application. The proposed structure shows that the recognition rate is improved by 2% in standard language and 7% in dialect.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.400-407
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• 2019

In this paper, the shadow detection and reconstruction method are proposed using intrinsic image, which does not change the essential characteristics under the influence of various illuminance, and multi-scale gamma correction. The shadow detection was estimated by the pixel change information between a grayscale and an intrinsic image of the color image, and the brightness of the image were adjusted by gamma correction in the shadow restoration process. Multi-scale gamma correction is performed for each channel of a color image due to the fact that the saturation can be changed by nonlinear adjustment to individual pixel values. Multi-scale gamma values are estimated based on the information of the crossed edge between shadows and non-shadowed regions in the color image, as a result, the shadows are reconstructed by correcting different region features with multi-scale gamma values. Experimental results show that the proposed method effectively reconstructs shadows in a single natural image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.47-54
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• 2019

In this paper, we consider a constant modulus (CM) based blind adaptive receiver design for downlink multi-carrier code-division multiple access (MC-CDMA) systems employing simple space-time block coding (STBC). In the paper, filter weight vectors used for the detection of the transmitted symbols are partitioned into its subvectors and then, special relations among the optimal subvectors minimizing the CM metric are derived. Using the special relations, we present a modified CM metric and propose a new blind adaptive stochastic-gradient CM algorithm (SG-CMA) by minimizing the modified CM metric. The proposed blind adaptive SG-CMA has faster convergence rate than the conventional SG-CMA because the filter weight vectors of the proposed scheme are updated in the region of satisfying the derived special relations. Computer simulation results are given to verify the superiority of the proposed SG-CMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.55-62
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• 2019

In this paper, we consider K-user multiple-input multiple-output (MIMO) interference channel and present a transceiver design for simultaneous wireless information and power transfer (SWIPT) systems. In addition, we consider a SWIPT system where an information decoding receiver and an energy harvesting receiver are co-located at the same receiver. In the proposed scheme, signal-to-leakage plus noise ratio (SLNR) is used as a cost function and a transceiver is designed to satisfy the threshold of the harvested energy. More specifically, transmitter precoding vector, receiver filter vector, and power spitting factor are simultaneously designed to maximize SLNR with a constraint on the harvested energy. Through computer simulation, we compare the signal-to-interference plus noise ratio (SINR) performance of the proposed and conventional schemes. When a special condition among the number of transmit antennas, receive antennas, and users is satisfied, the proposed scheme showed better SINR performance than the conventional scheme at low signal-to-noise ratio (SNR) range. Also, when the condition is not satisfied, the proposed scheme showed better performance than the conventional scheme at all SNR range.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.203-208
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• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.84-94
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• 2021

Graph databases have been developed to efficiently store and query graph data composed of vertices and edges to express relationships between objects. Since the query types of graph database show very different characteristics from traditional NoSQL databases, benchmarking tools suitable for graph databases to verify the performance of the graph database are needed. In this paper, we propose an efficient graph database benchmarking system that supports diversity in graph inputs and queries. The proposed system utilizes OrientDB to conduct benchmarking for graph databases. In order to support the diversity of input graphs and query graphs, we use LDBC that is an existing graph data generation tool. We demonstrate the feasibility and effectiveness of the proposed scheme through analysis of benchmarking results. As a result of performance evaluation, it has been shown that the proposed system can generate customizable synthetic graph data, and benchmarking can be performed based on the generated graph data.

• The Korean Journal of Archival Studies
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• no.20
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• pp.3-32
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• 2009

When the record management faces to the information environment, the practices based on self-judgment needs more open and considerate policies. New viewpoint that treat records as information and treat information as records will produce new mutual-conscious behavior that create records based on the value of information usage and maintain information data based on the reliability as an record. As the internal aspect how to create records well, how to transfer them well, and how to archives them well used to be the focus of record management, existing legislation, guidelines, and training seem to be mainly related to this front steps. We should also address issues according to the succeeding information services, including opening to the relevant, sharing, duplicating, information security, privacy protection, and constructing collections with continual supplement. This paper observe the confusion of the viewpoints in the recent reports, explain the need of fusion viewpoint, and suggest interconnecting feedback cycle between record management system and general information system.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.287-294
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• 2018

In this paper, it is practically difficult to obtain programming language education without having an algorithmic thinking ability, computing thinking ability, and problem solving ability of students with relatively low basic education. The results showed that students who took program language education in parallel with the EPL(Educational Programing Language), Scratch, compared to without using Scratch found to be helpful in improving their programming amd computing thinking ability, and problem-solving abilities as well as their satisfaction. This not only gave students confidence in their hard-thinking programming practices, but also helped prevent them from falling out of the middle.