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4D Printing – Fused Deposition Modeling Printing with Thermal-Responsive Shape Memory Polymers
Son Thai Ly,김주용 한국정밀공학회 2017 International Journal of Precision Engineering and Vol.4 No.3
Shape memory polymers (SMPs), as stimuli-responsive shape-changing polymers, change their deformed shape to pre-determined one under external stimuli, such as temperature, chemicals, light, etc. This research as part of the project in which employs four-dimensional (4D) printing technology to develop smart textile and wearable products. It describes the 4D printing process of the SMPs and their carbon nanotube composites. More specifically, the process begins with the SMPs pellet treatment for making the filament as input material for fused deposition modeling (FDM) type three-dimensional (3D) printer, then printing and finally testing the printed objects. The printed objects effectively perform the characteristics of SMPs in experiments as presented. Based on the achieved results, this process could be easily adapted to other research that related to 4D printing using SMPs. More research is needed to implement the 4D printing technology for the project and low-cost and mass production further.
A High-Quality Reversible Image Authentication Scheme Based on Adaptive PEE for Digital Images
( Thai-son Nguyen ),( Chin-chen Chang ),( Tso-hsien Shih ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.1
Image authentication is a technique aiming at protecting the integrity of digital images. Reversible image authentication has attracted much attention of researcher because it allows to authenticate tampered regions in the image and to reconstruct the stego image to its original version losslessly. In this paper, we propose a new, reversible image authentication scheme based on adaptive prediction error expansion (PEE) technique. In the proposed scheme, each image block is classified into smooth or complex regions. Then, according to the characteristic of each block, the authentication code is embedded adaptively to achieve high performance of tamper detection. The experimental results demonstrated that the proposed scheme achieves good quality of stego images. In addition, the proposed scheme has ability to reconstruct the stego image to its original version, if no modification is performed on it. Also demonstrated in the experimental results, the proposed scheme provides higher accuracy of tamper detection than state-of-the-art schemes.
Optimum Design of Cable Nets by Using Genetic Algorithm
Son Thai,김남일,이재홍,강주원 한국강구조학회 2017 International Journal of Steel Structures Vol.17 No.3
This paper presents a generalized procedure to optimize cable nets by using the Genetic Algorithm (GA). The finite element program employing 2-, 3- and 4-node isoparametric curved cable elements is utilized to deal with the nonlinear behavior of cable nets under static loads. The allowable stress and the maximum displacement are considered as optimization constraints while the minimum volume is selected as an objective function. To validate the accuracy and efficiency of the proposed procedure, four optimization examples originated from nonlinear analysis problems of cable nets are introduced.
Reversible Data Hiding Algorithm Based on Pixel Value Ordering and Edge Detection Mechanism
Thai-Son Nguyen,Hoang-Nam Tram,Phuoc-Hung Vo 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.10
Reversible data hiding is an algorithm that has ability to extract the secret data and to restore the marked image to its original version after data extracting. However, some previous schemes offered the low image quality of marked images. To solve this shortcoming, a new reversible data hiding scheme based on pixel value ordering and edge detection mechanism is proposed. In our proposed scheme, the edge image is constructed to divide all pixels into the smooth regions and rough regions. Then, the pixels in the smooth regions are separated into non overlapping blocks. Then, by taking advantages of the high correlation of current pixels and their adjacent pixels in the smooth regions, PVO algorithm is applied for embedding secret data to maintain the minimum distortion. The experimental results showed that our proposed scheme obtained the larger embedding capacity. Moreover, the greater image quality of marked images are achieved by the proposed scheme than that other previous schemes while the high EC is embedded.
Adaptive Lossless Data Hiding Scheme for SMVQ-Compressed Images using SOC Coding
Thai-Son Nguyen,Chin-Chen Chang,Meng-Chieh Lin 한국산학기술학회 2014 SmartCR Vol.4 No.3
Lossless data hiding recovers original images precisely after secret data are extracted. Therefore, it has received considerable attention among researchers. This paper offers an adaptive lossless data hiding scheme that is based on the search-order coding (SOC) algorithm for side match vector quantization (SMVQ) compressed images. By combining SOC coding with the SMVQ algorithm, compression performance is further improved while a large amount of free space is generated to hide secret data during the data embedding phase. In the extracting phase, simple steps are used to extract that embedded secret data. The same index table can be reconstructed on the receiver side, which ensures that this proposed scheme can restore the original cover image exactly. Experimental results have demonstrated that the proposed scheme yields a higher embedding rate and a lower compression rate than other related VQ and SMVQ based data hiding schemes.
A Tamper-Detection Scheme for BTC-Compressed Images with High-Quality Images
( Thai-son Nguyen ),( Chin-chen Chang ),( Ting-feng Chung ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.6
This paper proposes a novel image authentication scheme, aiming at tampering detection for block truncation coding (BTC) compressed image. The authentication code is generated by using the random number generator with a seed, and the size of the authentication code is based on the user`s requirement, with each BTC-compressed image block being used to carry the authentication code using the data hiding method. In the proposed scheme, to obtain a high-quality embedded image, a reference table is used when the authentication code is embedded. The experimental results demonstrate that the proposed scheme achieves high-quality embedded images and guarantees the capability of tamper detection.
Gesture-Based Emotion Recognition by 3D-CNN and LSTM with Keyframes Selection
Son Thai Ly,이귀상,김수형,양형정 한국콘텐츠학회 2019 International Journal of Contents Vol.15 No.4
In recent years, emotion recognition has been an interesting and challenging topic. Compared to facial expressions and speech modality, gesture-based emotion recognition has not received much attention with only a few efforts using traditional hand-crafted methods. These approaches require major computational costs and do not offer many opportunities for improvement as most of the science community is conducting their research based on the deep learning technique. In this paper, we propose an end-to-end deep learning approach for classifying emotions based on bodily gestures. In particular, the informative keyframes are first extracted from raw videos as input for the 3D-CNN deep network. The 3D-CNN exploits the short-term spatiotemporal information of gesture features from selected keyframes, and the convolutional LSTM networks learn the long-term feature from the features results of 3D-CNN. The experimental results on the FABO dataset exceed most of the traditional methods results and achieve state-of-the-art results for the deep learning-based technique for gesture-based emotion recognition.