• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.964-975
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• 2012

Recently the attention on digital hologram that is regarded as to be the final goal of the 3-dimensional video technology has been increased. A digital hologram can be generated with a depth and a RGB image. We proposed a new system to capture RGB and depth images and to convert them to digital holograms. First a new cold mirror was designed and produced. It has the different transmittance ratio against various wave length and can provide the same view and focal point to the cameras. After correcting various distortions with the camera system, the different resolution between depth and RGB images was adjusted. The interested object was extracted by using the depth information. Finally a digital hologram was generated with the computer generated hologram (CGH) algorithm. All algorithms were implemented with C/C++/CUDA and integrated in LabView environment. A hologram was calculated in the general-purpose computing on graphics processing unit (GPGPU) for high-speed operation. We identified that the visual quality of the hologram produced by the proposed system is better than the previous one.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.1-11
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• 2020

As an important basic building block of the smart grid environment, smart meter provides real-time electricity consumption information to the utility. However, ensuring information security and privacy in the smart meter data aggregation process is a non-trivial task. Even though the secure data aggregation for the smart meter has been a lot of attention from both academic and industry researchers in recent years, most of these studies are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter system. Recently, blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. In particular, blockchains are identified as having the potential to bring significant benefits and innovation for the electricity consumption network. This study suggests a distributed, privacy-preserving, and simple secure smart meter data aggregation system, backed up by Blockchain technology. Smart meter data are aggregated and verified by a hierarchical Merkle tree, in which the consensus protocol is supported by the practical Byzantine fault tolerance algorithm.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.19-29
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• 2011

As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.182-188
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• 2008

The MLC(multi leaf collimator) in charge of important role in radiation therapy field recently have been exchanging from shielding block into it rapidly, owing to being convenient. However, MLC can be occurred the leakage dose of inter_leaves and the error of algorithm in imput and output from digital signal. We compared the difference of imput method to MLC made by Varian Cop. with the error and effective field induced by MLC shaper and film scanner based on XimaVision value as using MLC layer of various shapes. According to comparing standard value with them to basic MLC layer (test1-5), MLC shaper was $0{\sim}0.29cm$, $0.23{\sim}3.59cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. At the MLC layer to be applied in clinic, MLC shaper was $0{\sim}0.54cm$, $0.04{\sim}1.68cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. The more distance and field from axis of central line increase, the more bigger the error value increases. There is a few mm error from standard point at the process which imput various information to apply MLC in clinic. and effective field did not have variation of monitor unit and dose owing to being a few cm2 error against real field. But there are some problem to shield critical organs because some part of target volume induced by the movement of organs can be not included, therefore we have to pay attention on the process to imput MLC layer

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.4
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• pp.398-405
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• 2001

The rivet joint has typical structural feature that can be initiation site for the fatigue crack due to the combination of local stress concentration around rivet hole and the moisture trapping. From a viewpoint of structural assurance, it is crucial to evaluate the size of crack around the rivet holes by appropriate nondestructive evaluation techniques. Lamb wave that is one of guided waves, offers a more efficient tool for nondestructive inspection of plates. The neural network that is considered to be the most suitable for pattern recognition has been used by researchers in NDE field to classify different types of flaws and flaw sizes. In this study, clack size evaluation around the rivet hole using the neural network based on the back-propagation algorithm has been tarried out by extracting some features from the ultrasonic Lamb wave for A12024-T3 skin panel of aircraft. Special attention was paid to reduce the coupling effect between the transducer and the specimen by extracting some features related to time md frequency component data in ultrasonic waveform. It was demonstrated clearly that features extracted from the time and frequency domain data of Lamb wave signal were very useful to determine crack size initiated from rivet hole through neural network.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.871-880
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• 2018

Recently, the technology of recommendation of POI (Point of Interest) related technology is getting attention with the increase of big data related to consumers. Previous studies on POI recommendation systems have been limited to specific data sets. The problem is that if the study is carried out with this particular dataset, it may be suitable for the particular dataset. Therefore, this study analyzes the similarity and correlation between stores using the user visit data obtained from the integrated sensor installed in Seoul and Songjeong roads. Based on the results of the analysis, we study the preference prediction system which recommends the stores that new users are interested in. As a result of the experiment, various similarity and correlation analysis were carried out to obtain a list of relevant stores and a list of stores with low relevance. In addition, we performed a comparative experiment on the preference prediction accuracy under various conditions. As a result, it was confirmed that the jacquard similarity based item collaboration filtering method has higher accuracy than other methods.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.85-92
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• 2008

Magnetotelluric (MT) methods are widely applied as an effective exploration technique to geothermal surveys. Two-dimensional (2-D) analysis is frequently used to investigate a complicated subsurface structure in a geothermal region. A 2-D finite-element method (FEM) is usually applied to the MT analysis, but we must pay attention to the accuracy of so-called auxiliary fields. Rodi (1976) proposed an algorithm of improving the accuracy of auxiliary fields, and named it as the MOM method. Because it introduces zeros into the diagonal elements of coefficient matrix of the FEM total equation, a pivoting procedure applied to the symmetrical band matrix makes the numerical solution far less efficient. The MOM method was devised mainly for the inversion analysis, in which partial derivatives of both electric and magnetic fields with respect to model parameters are required. In the case of forward modeling, however, we do not have to resort to the MOM method; there is no need of modifying the coefficient matrix, and the auxiliary fields can be elicited from the regular FEM solution. The computational efficiency of the MOM method, however, can be greatly improved through a sophisticated rearrangement of the total equation.

• Phonetics and Speech Sciences
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• v.12 no.2
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• pp.29-37
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• 2020

Recently, the neural network-based deep learning algorithm has dramatically improved performance compared to the classical Gaussian mixture model based hidden Markov model (GMM-HMM) automatic speech recognition (ASR) system. In addition, researches on end-to-end (E2E) speech recognition systems integrating language modeling and decoding processes have been actively conducted to better utilize the advantages of deep learning techniques. In general, E2E ASR systems consist of multiple layers of encoder-decoder structure with attention. Therefore, E2E ASR systems require data with a large amount of speech-text paired data in order to achieve good performance. Obtaining speech-text paired data requires a lot of human labor and time, and is a high barrier to building E2E ASR system. Therefore, there are previous studies that improve the performance of E2E ASR system using relatively small amount of speech-text paired data, but most studies have been conducted by using only speech-only data or text-only data. In this study, we proposed a semi-supervised training method that enables E2E ASR system to perform well in corpus in different domains by using both speech or text only data. The proposed method works effectively by adapting to different domains, showing good performance in the target domain and not degrading much in the source domain.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.317-326
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• 2009

Recently, there have been many research efforts proposed on trajectory information. Most of them mainly focus their attention on those objects moving in Euclidean space. Many real-world applications such as telematics, however, deal with objects that move only over road networks, which are highly restricted for movement. Thus, the existing methods targeting Euclidean space cannot be directly applied to the road network space. This paper proposes a new clustering scheme for a large volume of trajectory information of objects moving over road networks. To the end, we first define a trajectory on a road network as a sequence of road segments a moving object has passed by. Next, we propose a similarity measurement scheme that judges the degree of similarity by considering the total length of matched road segments. Based on such similarity measurement, we propose a new clustering algorithm for trajectories by modifying and adjusting the FastMap and hierarchical clustering schemes. To evaluate the performance of the proposed clustering scheme, we also develop a trajectory generator considering the observation that most objects tend to move from the starting point to the destination point along their shortest path, and perform a variety of experiments using the trajectories thus generated. The performance result shows that our scheme has the accuracy of over 95% in comparison with that judged by human beings.