• International journal of advanced smart convergence
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• v.13 no.3
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• pp.176-182
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• 2024

Looking at the recent game market, classic games released in the past are being re-released with high-quality visuals, and users are generally satisfied. It can be said that the realization of realistic digital actors, which was not possible in the past, is now becoming a reality. Epic Games launched the MetaHuman Creator website in September 2021, allowing anyone to easily create realistic human characters. Since then, the number of animations created using MetaHumans has been increasing. As the characters become more realistic, the movement and expression animations expected by the audience must also be convincingly realized. Until recently, traditional methods were the primary approach for producing realistic character animations. For facial animation, Epic Games introduced an improved method on the Live Link app in 2023, which provides the highest quality among mobile-based techniques. In this context, this paper compares the results of animation produced using both keyframe facial capture and mobile-based capture. After creating an emotional expression animation with four sentences, the results were compared using Unreal Engine. While the facial capture method is more natural and easier to use, the precise and exaggerated expressions possible with the keyframe method cannot be overlooked, suggesting that a hybrid approach using both methods will likely continue for the foreseeable future.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.166-177
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• 2006

The cache size tends to grow in the embedded processor as technology scales to smaller transistors and lower supply voltages. However, larger cache size demands more energy. Accordingly, the ratio of the cache energy consumption to the total processor energy is growing. Many cache energy schemes have been proposed for reducing the cache energy consumption. However, these previous schemes are concerned with one side for reducing the cache energy consumption, dynamic cache energy only, or static cache energy only. In this paper, we propose a hybrid scheme for reducing dynamic and static cache energy, simultaneously. for this hybrid scheme, we adopt two existing techniques to reduce static cache energy consumption, drowsy cache technique, and to reduce dynamic cache energy consumption, way-prediction technique. Additionally, we propose a early wake-up technique based on program counter to reduce penalty caused by applying drowsy cache technique. We focus on level 1 data cache. The hybrid scheme can reduce static and dynamic cache energy consumption simultaneously, furthermore our early wake-up scheme can reduce extra program execution cycles caused by applying the hybrid scheme.

• Resources Recycling
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• v.23 no.2
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• pp.3-16
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• 2014

Car exhaust $CO_2$ gas reduction and fuel efficiency of the car lighter for the current era is a big challenge. The developments of high-performance Nd magnets, Li-ion secondary battery and exhaust gas purification performance of PGM catalysts used in the lightweight EV and HEV are activated. Country in order to improve the car lighter and function that use the resources of rare metals are ubiquitous imported from China because of export supply control, as soaring prices have unstable supply and demand. Compared to the emissions from the next-generation automotive recycling, waste scarce resources need to be. This study investigated the recycling technology analysis and development of the information technology, or delivered to the researchers by giving national car industry aims to contribute to the development. Findings, pulmonary high-performance motor vehicle emissions in the exhaust gas purification PGM Catalysts, Li-ion battery and Nd magnets recycling technology, such as pre- and post-processing techniques to classify technology, pre-urban mining technology mechanical separation by screening techniques under development, the study and post-processing technology has, pyro and hydro metallurgical smelting technology is established. Waste Recycling in terms of economic efficiency of mechanical components for the intensive study of screening techniques is needed.

• Journal of Bio-Environment Control
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• v.24 no.4
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• pp.317-325
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• 2015

This paper attempts to present a review about simulation of different greenhouse parameters and energy supplying techniques by using building energy simulation, to find out the optimal solution for keeping greenhouse microclimate favorable for the crop production. The objectives of conducting this study were, to describe the various energy systems and techniques used for the greenhouse energy management and efficiency analysis of these technologies by using building energy simulation. We describe different models to understand the behavior of the energy saving technologies with respect to the resources available and different outside climatic conditions. We identified main features of the building energy simulation software, that enable users, to simulate hybrid agricultural building projects by using user defined parameters. At the end of the paper we draw some important concluding remarks on the basis of reviewing all the investigators contributions for the developments of simulation model of agricultural greenhouse energy management, using a building energy simulation software specifically TRNSYS. In conclusion, this paper provides information that TRNSYS have great potential for agricultural buildings energy simulation along with the renewable energy resources and energy saving techniques. This review paper provides aid to greenhouse researcher and energy planner for the future studies of greenhouses energy planning.

• Cartoon and Animation Studies
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• s.45
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• pp.27-50
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• 2016

The present study argues that documentary-animation films, which are based on actual human voices, on the level of representation, constitute a new expansion for the medium of animation films, which serve as testimonies to the real world. Animation films are produced using very diverse techniques so that they are complex to the degree of being indefinable, and documentary films, though based on objective representation, increase in complexity in that there exist various types of artificial interventions such as direction and digital image processing. Having emerged as a hybrid genre of the two media, documentary-animation films draw into themselves actual events and elements so that they conceptually share reality-based narratives and are visually characterized by the trappings of animation films. Generally classified as 'animated documentaries', this genre triggered discussions following the release of , a work that is mistaken as having used rotoscoping transforming live action in terms of the technique. When analyzed in detail, however, this work is presented as an ambiguous medium where the characteristics of animation films, which are virtual simulacra without reality, and of documentaries, which are based on the objective indexicality of the referents, coexist because of its mixed use of typical animation techniques, 3D programs, and live-action images. Discussed in the present study, , , and share the characteristics of the medium of documentaries in that the narratives develop as testimonies of historical figures but, at the same time, are connected to animation films because of their production techniques and direction characteristics. Consequently, this medium must be discussed as a new expansion rather than being included in the existing classification system, and such a presupposition is an indispensable process for directly facing the reality of the works and for developing discussions. Through works that directly use the interviewees' voices yet do not transcend the characteristics of animation films, the present study seeks to define documentary-animation films and to discuss the possibility of the medium, which has expanded as a testimony to the real world.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.2
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• pp.138-149
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• 2000

Various modeling techniques for ultrasonic wave propagation and scattering problems in finite solid media are presented. Elastodynamic boundary value problems in inhomogeneous multi-layered plate-like structures are set up for modal analysis of guided wave propagation and numerically solved to obtain dispersion curves which show propagation characteristics of guided waves. As a powerful modeling tool to overcome such numerical difficulties in wave scattering problems as the geometrical complexity and mode conversion, the Boundary Element Method(BEM) is introduced and is combined with the normal mode expansion technique to develop the hybrid BEM, an efficient technique for modeling multi mode conversion of guided wave scattering problems. Time dependent wave forms are obtained through the inverse Fourier transformation of the numerical solutions in the frequency domain. 3D BEM program development is underway to model more practical ultrasonic wave signals. Some encouraging numerical results have recently been obtained in comparison with the analytical solutions for wave propagation in a bar subjected to time harmonic longitudinal excitation. It is expected that the presented modeling techniques for elastic wave propagation and scattering can be applied to establish quantitative nondestructive evaluation techniques in various ways.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.973-980
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• 2024

Fuzzing is an automated testing technique that generates a lot of testcases and monitors for exceptions to test a program. Recently, fuzzing research using machine learning has been actively proposed to solve various problems in the fuzzing process, but a comprehensive evaluation of fuzzing research using machine learning is lacking. In this paper, we analyze recent research that applies machine learning to scheduling techniques for fuzzing, categorizing them into reinforcement learning-based and supervised learning-based fuzzers. We evaluated the coverage performance of the analyzed machine learning-based fuzzers against real-world programs with four different file formats and bug detection performance against the LAVA-M dataset. The results showed that AFL-HIER, which applied seed clustering and seed scheduling with reinforcement learning outperformed in coverage and bug detection. In the case of supervised learning, it showed high coverage on tcpdumps with high code complexity, and its superior bug detection performance when applied to hybrid fuzzing. This research shows that performance of machine learning-based fuzzer is better when both machine learning and additional fuzzing techniques are used to optimize the fuzzing process. Future research is needed on practical and robust machine learning-based fuzzing techniques that can be effectively applied to programs that handle various input formats.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.29-40
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• 2005

According as base of digital hologram has been magnified, discussion of compression technology is expected as a international standard which defines the compression technique of 3D image and video has been progressed in form of 3DAV which is a part of MPEG. As we can identify in case of 3DAV, the coding technique has high possibility to be formed into the hybrid type which is a merged, refined, or mixid with the various previous technique. Therefore, we wish to present the relationship between various image/video coding techniques and digital hologram In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video and image. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. Finally the proposed hybrid compression algorithm is all of these methods. The tool for still image coding is JPEG2000, and the toots for video coding include various international compression algorithm such as MPEG-2, MPEG-4, and H.264 and various lossless compression algorithm. The proposed algorithm illustrated that it have better properties for reconstruction than the previous researches on far greater compression rate above from four times to eight times as much. Therefore we expect that the proposed technique for digital hologram coding is to be a good preceding research.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.148-157
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• 2014

Various techniques have been developed for efficient compression of stereoscopic 3D videos. Mixed-resolution based approach is one representative bit-rate saving method based on the characteristics of human visual system that the mixed-resolution stereoscopic videos are perceived close to the higher resolution. However, when the difference between the left and right image resolutions is bigger than a certain threshold level, it causes the perceived quality degradation of the 3D images. Subsequently, several researches tried to find the correlation between the difference in resolution and the level of the perceived quality degradation, but they conducted the experiments just considering the difference in resolution without considering the viewing distances, so thereby different results were retrieved from test to test. In this work, we calculated the optimal viewing distance based on the human visual system, and conducted the subjective tests with the calculated viewing distance. With the results, we demonstrate that the fixed and mobile hybrid 3DTV, which is based on mixed-resolution stereoscopic images, can provide the high quality 3D services.