• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.349-352
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• 2004

4D system has applied to construction project as a management tool after the late 1990's. Various 4D systems have been developed, however they have some problems that should be improved. Especially, the 4D system for civil engineering project needs synthesized 3D model between natural ground condition and physical facility type. It is a different problem comparing with the system for building project. 1'his study suggests an automatically synthesizing methodology between ground triangulate network and design triangulate network. Furthermore the study develops an application methodology of multi-texturing technique defined in virtual reality modeling language (VRML) for skipping the 3D model synthesizing process from the 4D model development processes. The suggested methodology is applied to the prototype of real 4D system. The proposed technique for 3D modeling may be used as an essential methodology for developing 4D system for civil engineering projects.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.26-39
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• 2007

In recent years, rate control is an important technique in real time video communication applications using H.264/AVC. Many existing rate control algorithms employ the quadratic rate-distortion model, which is determine the target bits for each P frame. In this paper, a new rate control algorithm for transmission of H.264/AVC video bit stream through CBR(Constant Bit Rate) channel is proposed. The proposed algorithm predicts an adaptive QP(Quantization Parameter) for improving video distortion, due to high motion and abruptly scene change, which target bit rate and MAD(Mean of Absolute Difference) for current frame considering image complexity variance between previous and current frames. Additionally, it uses frame skip technique to maintain bit stream within a manageable range and protect buffer from overflow or underflow. Experimental results show that the proposed method gives a quality improvement of about 0.5dB when compared to previous rate control algorithm. Also our proposed algorithm encodes the video sequences with less frame skipping compared to the existing rate control for H.264/AVC.

• Cartoon and Animation Studies
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• s.40
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• pp.109-137
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• 2015

As Digital technology developed, drawing animation, using traditional production method which expresses many feelings with drawn lines loses the youth group, the primary audience, to the realism of the digital cinema. Drawing animation, which drew attention of the youth by the spectacles in the film such as hectic pace, dynamics and punch, declined for a while. However, it has been developed a way to express pace and dynamics of its own by establishing an effective directing method, which combines digital technology as it is needed. This study has a purpose to investigate what causes the dynamics and feeling of fast movement of the character in Japanese limited animation. Though some action-animated films that heroes with supernatural powers take the leading role that feeling of velocity and dynamics are emphasized we compare the directing method before and after the introduction of the digital technology. This research reaches the conclusion by factoring each Bergson and McLuhan's discussion to the intervention of indexical signs and the audience's participation according to skipping technique. This study has a significance of researching the element of drawing animation that maximizes the expansion of the senses by defying the limitation of the law of physics through its unique way of directing together with growth of the hero films, which will continue.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.311-328
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• 2022

Because of the spread of smartphones due to the development of information and communication technology, online shopping mall services can be used on computers and mobile devices. As a result, the number of users using the online shopping mall service increases rapidly, and the types of products traded are also growing. Therefore, to maximize profits, companies need to provide information that may interest users. To this end, the recommendation system presents necessary information or products to the user based on the user's past behavioral data or behavioral purchase records. Representative overseas companies that currently provide recommendation services include Netflix, Amazon, and YouTube. These companies support users' purchase decisions by recommending products to users using ratings, purchase records, and clickstream data that users give to the items. In addition, users refer to the ratings left by other users about the product before buying a product. Most users tend to provide ratings only to products they are satisfied with, and the higher the rating, the higher the purchase intention. And recently, e-commerce sites have provided users with the ability to vote on whether product reviews are helpful. Through this, the user makes a purchase decision by referring to reviews and ratings of products judged to be beneficial. Therefore, in this study, the correlation between the product rating and the helpful information of the review is identified. The valuable data of the evaluation is reflected in the recommendation system to check the recommendation performance. In addition, we want to compare the results of skipping all the ratings in the traditional collaborative filtering technique with the recommended performance results that reflect only the 4 and 5 ratings. For this purpose, electronic product data collected from Amazon was used in this study, and the experimental results confirmed a correlation between ratings and review usefulness information. In addition, as a result of comparing the recommendation performance by reflecting all the ratings and only the 4 and 5 points in the recommendation system, the recommendation performance of remembering only the 4 and 5 points in the recommendation system was higher. In addition, as a result of reflecting review usefulness information in the recommendation system, it was confirmed that the more valuable the review, the higher the recommendation performance. Therefore, these experimental results are expected to improve the performance of personalized recommendation services in the future and provide implications for e-commerce sites.