• The KIPS Transactions:PartC
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• v.13C no.5 s.108
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• pp.575-582
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• 2006

Guaranteeing network bandwidth and system performance becomes important technical matters to make seamless delivery of bulky data at high speed. Tuning system and network parameters including jumbo frame, kernel buffer size, and interrupt coalescence determines end-to-end transmission throughput. Additionally, fine-tuning of the parameters alleviates workload on high-end systems. Until now, many studies have concentrated on how to increase transmission throughput but rarely discussed how to mitigate system workload. In this paper, we have investigated various tuning parameters, which positively affect networking and processing performance of uncompressed HDTV system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.57-63
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• 2015

There are increasing demands for the transmission of high speed and non-compressed video informations. The video data usually compressed before transmission for reducing the data. And the received data uncompressed at a receiver, consequently the processing delay is unavoided. In this paper, we implement a 60 GHz band wireless transmission system for real time multimedia contents transmission, and successfully transmit the full HD class uncompressed video information at 4 Gbps with 20 m apart. Hence the non-compressed video data from a remote camera or a smart phone can be transmitted and displayed in a large screen in real time via the developed transceiver system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.454-475
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• 2018

This paper presents a novel Android malware classification model planned to classify and categorize Android malicious code at Drebin dataset. The amount of malicious mobile application targeting Android based smartphones has increased rapidly. In this paper, Restricted Boltzmann Machine and Deep Belief Network are used to classify malware into families of Android application. A texture-fingerprint based approach is proposed to extract or detect the feature of malware content. A malware has a unique "image texture" in feature spatial relations. The method uses information on texture image extracted from malicious or benign code, which are mapped to uncompressed gray-scale according to the texture image-based approach. By studying and extracting the implicit features of the API call from a large number of training samples, we get the original dynamic activity features sets. In order to improve the accuracy of classification algorithm on the features selection, on the basis of which, it combines the implicit features of the texture image and API call in malicious code, to train Restricted Boltzmann Machine and Back Propagation. In an evaluation with different malware and benign samples, the experimental results suggest that the usability of this method---using Deep Belief Network to classify Android malware by their texture images and API calls, it detects more than 94% of the malware with few false alarms. Which is higher than shallow machine learning algorithm clearly.

• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.37-43
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• 1994

Optimization study was conducted for preparation of uncompressed soy protein isolate(SPI) tofu in the aspects of water addition ratio, second heating temperature and amounts of oil and dextrin added. The SPI tofu was prepared without compression step with SPI-oil-dextrin mixture and $CaSO_4-GDL$ mixed coagulants. The data were statistically analyzed by multiple regresstion and response surface methodology(RSM). Addition of dextrin increased the hardness of tofu, particularly for the second heating at $85^{\circ}C$ and 8 times of water to SPI. RSM figure showed that the effect of dextrin on hardness became to be less as the heating temperature increased. The hardness increase effect was no significant except addition of 25% oil and 8 times of water and second heating at $85^{\circ}C$. The addition of 25% oil and $10{\sim}15%$ dextrin and second heating at $90^{\circ}C$ for $45{\sim}60$ minutes resulted hardness and cohesive tofu. The optimal method proposed for uncompressed SPI tofu on the basis of textural and sensory properties was first heating of homogenized SPI-oil-dextrin(100:25:15) with addition of 8 times of water(on the basis of SPI) at $100^{\circ}C$ for 6 minutes, cooling to $40^{\circ}C$, additon of mixed coagulants of $CaSO_{4}-GDL$(0.07 g, 0.0075 g/SPI) and second heating at $90^{\circ}C$ for 45 minutes.

• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.31-36
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• 1994

In order to prepare SPI tofu without compression step, amounts of water added to SPI suspension was studied for textural properties of uncompressed SPI tofu prepared by first heating at $100^{\circ}C$ for 6 minutes and second heating at $75^{\circ}C$ for 25 minutes and use of $CaSO_{4}-GDL$(0.07g, 0.0075 g/g SPI) as coagulants. The hardness and uniformity were gradually increased as the water addition ratio $(gH_{2}O/g\;SPI)$ raised from 6.0 to 8.0 and cohesiveness was rather decreased. The increase in second heating time increased the hardness and gumminess and relativity higher values in hardness were measured for those tofu heated at $85^{\circ}C$ than those at $75^{\circ}C$ or $95^{\circ}C$. A multiple regression equation calculated and RSM figure showed that the effects of water addition ratio was become to be less as the heating time and temperature increased. Addition of 8 g of water per g SPI and second heating at $85^{\circ}C$ for $30{\sim}60$ minutes were found as optimal conditions to prepare uncompressed SPI tofu.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.708-712
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• 2001

디지털 데이터의 저작권 보호를 위하여 최근 디지털 워터마킹에 관하여 많은 연구가 이루어지고 있다. 디지털 워터마킹이란 인간의 시각이나 청각이 인지할 수 없는 범위 내에서 디지털 데이터의 값을 약간 변경함에 따라 워터마크라고 하는 저작권 정보를 몰래 삽입하는 방법이다. 본 논문에서는 비 압축 비디오 계열(uncompressed video sequence)에 디지털 워터마크를 삽입하기 위한 방법을 보여준다. 대역 확산 기법을 이용하여 비디오에 pseudo-noise signal을 눈에 보이지 않도록 추가하고, 여러 조작에 대해 강하도록 구성하였다. 성능을 평가하기 위하여 비디오에 워터마크를 삽입하고 그 유효성을 보인다.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.259-262
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• 2002

We propose a new algorithm to detect shot change, which is necessary in retrieval of video data. In order to solve the problems of abrupt brightness change and similar brightness between frames in the typical shot change methods, we propose the hi-polarity histogram method which takes into account the distribution and magnitude of brightness changes in consecutive frames. We evaluate our algorithm with compressed and uncompressed video data and demonstrate its improved performance.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.193-196
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• 2008

In this paper a detail study of existing steganographic methods are presented. An example is given of LSB substitution with uncompressed domain i.e., BMP image. In case of compressed domain JPEG image steganography is presented. Almost all popular steganographic algorithms, such as JPEG JSteg, F3, F4 and Selective Block Steganography (SBS) are described. The applications of steganographic methods are also presented briefly.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1197-1205
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• 2014

Recently signal transmission of ultra high-definition(4K-UHD) video system is transferred as uncompressed high speed data. However, this has a limit to compose the system because EMI between separate cables of high speed interface section and skew bring distortion of the video signal and jitter. In this paper we applied V-by-One HS interface technique to transfer uncompressed high speed data. We analyzed HSD(High Speed Differential) transmission line signal integrity. Also we applied RF transmission technique instead of UHD video pattern control interface PCB design. When we measured V-by-One HS video signal of designed 4K-UHD class signal generator, We found that the transmission performance has been signal standard.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.7-10
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• 2000

There are many Problems such as low detection ratio, velocity and increase of false hit ratio on the detection of gradual scene changes with the previous shot transition detection algorithms. In this paper, we Propose an improved dissolve detection method using color information on low-frequency subband and edge elements on high-frequency subband. The Possible dissolve transition are found by analyzing the edge change ratio in the high-frequency subband with edge elements of each direction. Using the double chromatic difference on the lowest frequency subband, we have the improvement of the dissolve detection ratio. The simulation results show that the performance of the proposed algorithm is better than the conventional one for dissolve detection on a diverse set of uncompressed video sequences.