• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.169-172
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• 2005

Genetic algorithm based predictor for lossless image compression is propsed. We describe a genetic algorithm to learn predictive model for lossless image compression. The error image can be further compressed using entropy coding such as Huffman coding or arithmetic coding. We show that the proposed algorithm can be feasible to lossless image compression algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1131-1134
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• 2003

Unknown parameters of a nonlinear system were estimated using a signal compression method. The estimated parameters were natural frequency and tile damping coefficient. This study applied a algorithm using tile comparison of the cross-correlation coefficient between the impulse response from a model and it from the signal compression method. The impulse through linear element included in a nonlinear system could be obtained by the signal compression method. The unknown parameters of the linear element could be estimated by comparing the Bode plots of system's impulse response with them of model's response. In this study, a LSCM(LabVIEW-Signal-Compression-Method) was developed to identify a nonlinear system. The LSCM consisted of National Instrument's (NI) Data Acquisition (DAQ) Board (Model PCI-1200), a monitoring program using LabVIEW software package, DAQ Signal Accessory Board, and 2nd-order electric circuits. The designed electric circuits consisted of resistors, inductors and capacitors. To evaluate the performance of the LSCM, the response from model with known parameters is compared with the response from the real system using the monitoring program. The results from simulation of experiment showed that the developed LSCM provided a reliable estimation performance.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.109-118
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• 2008

In mapping a texture image into a 3D mesh model for photo-realistic graphic applications, the compression of texture image is as important as geometry of 3D mesh. Typically, the size of the (compressed) texture image of 3D model is comparable to that of the (compressed) 3D mesh geometry. Most 3D model compression techniques are to compress the 3D mesh geometry, rather than to compress the texture image. Well-known image compression standards (i.e., JPEG) have been extensively used for texture image compression. However, such techniques are not so efficient when it comes to compress an image with texture patches, since the patches are little correlated. In this paper, we proposed a preprocessing method to substantially improve the compression efficiency of texture compression. From the experimental results, the proposed method was shown to be efficient in compression with a bit-saving from 23% to 45%.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.42-54
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• 2023

It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

• Structural Engineering and Mechanics
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• v.66 no.6
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• pp.783-792
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• 2018

This paper presents a detailed theoretical study of the sleeved compression members based on a mechanical model. In the mechanical model, the core protrusion above sleeve and the contact force between the core and sleeve are specially taken into account. Via the theoretical analyses, load-displacement relationships of the sleeved compression members are obtained and verified by the experimental results. On the basis of the core moment distribution changing with the increase of the applied axial load, failure mechanism of the sleeved compression members is assumed and proved to be consistent with the experimental results in terms of the failure modes and the ultimate bearing capacities. A parametric study is conducted to quantify how essential factors including the core protrusion length above sleeve, stiffness ratio of the core to sleeve, core slenderness ratio and gap between the core and sleeve affect the mechanical behaviors of the sleeved compression members, and it is concluded that the constrained effect of the sleeve is overestimated neglecting the core protrusion; the improvement of ultimate bearing capacity for the sleeved compression member is considered to be decreasing with the decrease of the core slenderness ratio and for the sleeved compression member with core of small slenderness ratio, small gap and small stiffness ratio are preferred to obtain larger ultimate bearing capacity and stiffness.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.34 no.2
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• pp.151-156
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• 2008

Different kinds of forces can be applied to the biological tissue. The analysis of the applied force is highly important to explain the mechanism of cellular response. In this study, the applied force to the collagen gel was analyzed by the finite elements analysis. The model received two different kinds of static force (compression and tension). The force range was 50g to 400g. In results, von Mises stress was concentrated in the peripheral region in the compression model. It was concentrated in the central area in the tension model. However, the compressive force was high in the peripheral area of the compression model and the tensional force was also high in the same area of the tension model. In conclusion, the applied force could be different to the region and it should be considered in the experiment to analyze the effects of the mechanical force on the cells.

• Steel and Composite Structures
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• v.12 no.1
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• pp.53-72
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• 2012

In this study, the physically-based failure models for matrix and fibers in compression and tension loading are introduced. For the 3D stress based fiber kinking model a modification is proposed for calculation of the fiber misalignment angle. All of these models are implemented into the finite element code by using the advantage of damage variable and the numerical results are discussed. To investigate the matrix failure model, purely in-plane transverse compression experiments are carried out on the specimens made by Glass/Epoxy to obtain the fracture surface angle and then a comparison is made with the calculated numerical results. Furthermore, shear failure of $({\pm}45)_s$ model is investigated and the obtained numerical results are discussed and compared with available experimental results. Some experiments are also carried out on the woven laminated composites to investigate the fracture pattern in the matrix failure mode and shown that the presented matrix failure model can be used for the woven composites. Finally, the obtained numerical results for stress based fiber kinking model and improved ones (strain based model) are discussed and compared with each other and with the available results. The results show that these models can predict the kink band angle approximately.

• Journal of the Korean Geotechnical Society
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• v.28 no.1
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• pp.55-66
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• 2012

The load transfer mechanism of hybrid model of soil-nailing and compression anchor is studied in this paper. The hybrid model is composed of an anchor bar (installed at the tip) with two PC strands and a steel bar. It can make active behavior of skin friction by applying the pre-stress. In this paper, the load transfer mechanisms of soil-nailings, compression anchors, and hybrid models, respectively, are obtained from skin friction theory and load transfer theory. Field pullout tests are performed to identify the load transfer mechanism and experimental results are compared with analytical solution. In case of soil-nailings, the tension load is transferred from face to tip, however, in case of compression anchors, the compression load is transferred from tip to face. The experimental behavior of the hybrid model is similar to that of compression anchor when only pre-stress is applied. If the pullout test is performed by simultaneously pulling out the anchor and the nail, the compression load is dominant at the tip and tension load is dominant at the face. The load transfer mechanism of the hybrid model shows the combined behavior of soil-nailings with compression anchors.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.125-132
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• 2022

Sentence compression is a natural language processing task that generates concise sentences that preserves the important meaning of the original sentence. For grammatically appropriate sentence compression, early studies utilized human-defined linguistic rules. Furthermore, while the sequence-to-sequence models perform well on various natural language processing tasks, such as machine translation, there have been studies that utilize it for sentence compression. However, for the linguistic rule-based studies, all rules have to be defined by human, and for the sequence-to-sequence model based studies require a large amount of parallel data for model training. In order to address these challenges, Deleter, a sentence compression model that leverages a pre-trained language model BERT, is proposed. Because the Deleter utilizes perplexity based score computed over BERT to compress sentences, any linguistic rules and parallel dataset is not required for sentence compression. However, because Deleter compresses sentences only considering perplexity, it does not compress sentences by reflecting the linguistic information of the words in the sentences. Furthermore, since the dataset used for pre-learning BERT are far from compressed sentences, there is a problem that this can lad to incorrect sentence compression. In order to address these problems, this paper proposes a method to quantify the importance of linguistic information and reflect it in perplexity-based sentence scoring. Furthermore, by fine-tuning BERT with a corpus of news articles that often contain proper nouns and often omit the unnecessary modifiers, we allow BERT to measure the perplexity appropriate for sentence compression. The evaluations on the English and Korean dataset confirm that the sentence compression performance of sentence-scoring based models can be improved by utilizing the proposed method.

• Computers and Concrete
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• v.11 no.4
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• pp.291-304
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• 2013

By considering the creep characteristics of concrete core under eccentric compression, a creep model of concrete filled steel tubes (CFT) columns under eccentric compressive loads is proposed based on the concrete creep model B3. In this proposed model, a discrete element method is introduced to transform the eccentric loading into axial loading. The validity of the model is verified by comparing the predicting results with the published creep experiments results on CFT specimens under compressive loading, together with the predicting values based on other concrete creep models, such as ACI209, CEB90, GL2000 and elastic continuation and plastic flow theory. By using the proposed model, a parameters study is carried out to analysis the effects of practical design parameters, such as concrete mix (e.g. water to cement ratio, aggregate to cement ratio), steel ratio and eccentricity ratio, on the creep of CFT columns under eccentric compressive loading.