• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.439-448
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• 2017

It is news from nowhere that post-quantum cryptography has side-channel analysis vulnerability. Side-channel analysis attack method and countermeasures for code-based McEliece cryptosystem and lattice-based NTRU cryptosystem have been investigated. Unfortunately, the investigation of the ring-LWE cryptosystem in terms of side-channel analysis is as yet insufficient. In this paper, we propose a chosen ciphertext simple power analysis attack that can be applied when ring-LWE cryptography operates on 8-bit devices. Our proposed attack can recover the key only with [$log_2q$] traces. q is a parameter related to the security level. It is used 7681 and 12289 to match the common 128 and 256-bit security levels, respectively. We identify the vulnerability through experiment that can reveal the secret key in modular add while the ring-LWE decryption performed on real 8-bit devices. We also discuss the attack that uses a similarity measurement method for two vectors to reduce attack time.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.68-76
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• 1999

The intuitive understanding of the dynamic pattern generation in asymmetric networks may be useful for developing models of dynamic information processing. In this paper, dynamic behavior of the ring connection neural network in which each neuron is only to its nearest neurons with binary synaptic weights of ±1, has been inconnected vestigated Simulation results show that dynamic behavior of the network can be classified into only three categories: fixed points, limit cycles with basin and limit cycles with no basin. Furthermore, the number and the type of limit cycles generated by the networks have been derived through analytical method. The sufficient conditions for a state vector of n-neuron network to produce a limit cycle of n- or 2n-period are also given The results show that the estimated number of limit cycle is an exponential function of n. On the basis of this study, cyclic connection neural network may be capable of storing a large number of dynamic information.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.387-394
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• 2019

In this study, a new method of audio high-band coding based on autoencoder with side information is proposed. The proposed method operates in the MDCT domain, and improves the performance by using additional side information consisting of the previous and current low bands, which is different from the conventional autoencoder that only inputs information to be encoded. Moreover, the side information in a time-frequency domain enables the high-band coder to utilize temporal characteristics of the signal. In the proposed method, the encoder transmits a 4-dimensional latent vector computed by the autoencoder and a gain variable using 12 bits for each frame. The decoder reconstructs the high band by applying the decoded low bands in the previous and current frames and the transmitted information to the autoencoder. Subjective evaluation confirms that the proposed method provides equivalent performance to the SBR at approximately half the bit rate of the SBR.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.62-73
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• 2000

In this paper, we propose a criteria which can be applied to classify conventional color feature based Content Based Image Retrieval (CBIR) methods with its application areas, and a new image retrieval method which can represent sufficient spatial information in the image and is powerful in invariant searching to translation, rotation and enlargement transform. As the conventional color feature based CBIR methods can not sufficiently include the spatial information in the image, in general, they have drawbacks, which are weak to the translation or rotation, enlargement transform. To solve it, they have represented the spatial information by partitioning the image. Retrieval efficiency, however, is decreased rapidly as increasing the number of the feature vectors. We classify conventional methods to ones using 1st order relations and ones using 2nd order relations as their color object relation, and propose a new method using 3rd order relation of color objects which is good for the translation, rotation and enlargement transform. It makes quantized 24 buckets and selects 3 high scored histogram buckets and calculates 3 mean positions of pixels in 3 buckets and 3 angles. Then, it uses them as feature vectors of a given image. Experiments show that the proposed method is especially good at enlarged images and effective for its small calculation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.575-582
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• 2008

In this paper we described the process and the results of real-time implementation of G.729.1 wideband speech codec which is standardized in SG15 of ITU-T. To apply the codec on ARM926EJ-S(R) processor core. we transformed some parts of the codec C program including basic operations and arithmetic functions into assembly language to operate the codec in real-time. G.729.1 is the standard wideband speech codec of ITU-T having variable bit rates of $8{\sim}32kbps$ and inputs quantized 16 bits PCM signal per sample at the rate of 8kHz or 16kHz sampling. This codec is interoperable with the G.729 and G.729A and the bandwidth extended wideband($50{\sim}7,000Hz$) version of existing narrowband($300{\sim}3,400Hz$) codec to enhance voice quality. The implemented G.729.1 wideband speech codec has the complexity of 31.2 MCPS for encoder and 22.8 MCPS for decoder and the execution time of the codec takes 11.5ms total on the target with 6.75ms and 4.76ms respectively. Also this codec was tested bit by bit exactly against all set of test vectors provided by ITU-T and passed all the test vectors. Besides the codec operated well on the Internet phone in real-time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.4
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• pp.42-50
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• 2008

The real-time bio-signal monitoring system based on the ZigBee and SIP/RTP has proposed and implemented for telemedicine but that has some problems at the stabilities to transmit bio-signal from the sensors to the other sides. In this paper, we designed and implemented a real-time bio-signal monitoring system that is focused on the reliability and efficiency for transmitting bio-signal at real-time. We designed the system to have enhanced architecture and performance in the ubiquitous sensor network, SIP/RTP real-time transmission and management of the database. The Bluetooth network is combined with ZigBee network to distribute traffic of the ECG and the other bio-signal. The modified and multiplied RTP session is used to ensure real-time transmission of ECG, other bio-signals and speech information on the internet. The modified ECG compression method based on DWLT and MSVQ is used to reduce data rate for storing ECG to the database. Finally we implemented a system that has improved performance for transmitting bio-signal from the sensors to the monitoring console and database. This implemented system makes possible to make various applications to serve U-health care services.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.