• Korean Journal of Optics and Photonics
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• v.19 no.4
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• pp.262-269
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• 2008

In this paper, we propose an image watermark method using multiple decoding keys. The advantages of this method are that the multiple original images are reconstructed by using multiple decoding keys in the same watermark image, and that the quality of reconstructed images is clearly enhanced based on the idea of Walsh code without any side lobe components in the decoding process. The zero-padded original images, multiplied with random-phase pattern to each other, are Fourier transformed. Encoded images are then obtained by taking the real-valued data from these Fourier transformed images. The embedding images are obtained by the product of independent Walsh codes, and these spreaded phase-encoded images which are multiplied with new random-phase images. Also we obtain the decoding keys by multiplying these random-phase images with the same Walsh code images used in the embedding images. A watermark image is then made from the linear superposition of the weighted embedding images and a cover image, which is multiplied with a new independent Walsh code. The original image is simply reconstructed by the inverse-Fourier transform of the despreaded image of the multiplication between the watermark image and the decoding key. Computer simulations demonstrate the efficiency of the proposed watermark method with multiple decoding keys and a good robustness to the external attacks such as cropping and compression.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.59-69
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• 2019

The present study explored consumer's perception and preference on providing information of fashion products by using QR code and suggested the possibility for consumer-to-consumer and consumer-to-company connection. A survey was conducted on males and females in their 20s-a population among whom the rate of smart phone penetration is higher than in any other age group and who tend to exchange information online. The results showed that consumers are dissatisfied with the amount of information, terms of instructions, and ambiguous washing symbols currently provided. Therefore, the study identified the need for better methods of providing information and found that QR code, which is able to deliver high-quality information on fashion products, can be an efficient alternative. Moreover, respondents felt the need for detailed washing instructions, information on handling, and functionality of material on high-involvement fashion products such as outdoor, padding, suit, and underwear worn next to the skin. They also desire styling tips or purchasing information such as SNS OOTD (Outfit Of The Day) utilizing the product, other products that may go well with the one purchased, and similar products on casual wear and coat used on a daily basis. Therefore, QR code used as a link to information web pages or a social network can help consumers to satisfy information needs and to use the products effectively.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.104-123
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• 2022

Style transfer based on neural network provides very high quality results by reflecting the high level structural characteristics of images, and thereby has recently attracted great attention. This paper deals with the problem of resolution limitation due to GPU memory in performing such neural style transfer. We can expect that the gradient operation for style transfer based on partial image, with the aid of the fixed size of receptive field, can produce the same result as the gradient operation using the entire image. Based on this idea, each component of the style transfer loss function is analyzed in this paper to obtain the necessary conditions for partitioning and padding, and to identify, among the information required for gradient calculation, the one that depends on the entire input. By structuring such information for using it as auxiliary constant input for partition-based gradient calculation, this paper develops a recursive algorithm for super high-resolution image style transfer. Since the proposed method performs style transfer by partitioning input image into the size that a GPU can handle, it can perform style transfer without the limit of the input image resolution accompanied by the GPU memory size. With the aid of such super high-resolution support, the proposed method can provide a unique style characteristics of detailed area which can only be appreciated in super high-resolution style transfer.