• Applied Chemistry for Engineering
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• v.2 no.1
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• pp.70-76
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• 1991

Water soluble poly(sulfonated styrene-co-acrylic acid) was polymerized with sulfonated styrene and acrylic acid in the presence of silver sulfate at $99^{\circ}C$ for 4 hrs. The complex formation of poly(sulfonated styrene-co-acrylic acid) with Cu(II) was carried out. The maximum absorption wavelength of the poly(sulfonated styrene-co-acrylic)-Cu(II) system at different pH values was observed at 274 nm and 295 nm. The reduced viscosity of the poly(sulfonated styrene-co-acrylic acid)-Cu(II) complex were measured in the various pH ranges. The formation constants and stability constants of poly(sulfonated styrene-co-acrylic acid)-Cu(II) complex were calculated from Bjerrum method. The changes of enthalpy, free energy and entropy in the above reaction were determined by Ringbom method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.479-488
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• 2016

For a secure communication system, it is necessary to use secure cryptographic algorithms and keys. Modern cryptographic system generates high entropy encryption key through standard key derivation functions. Using recent progress in quantum key distribution(QKD) based on quantum physics, it is expected that we can enhance the security of modern cryptosystem. In this respect, the study on the dual key agreement is required, which combines quantum and modern cryptography. In this paper, we propose two key derivation functions using dual key agreement based on QKD and RSA cryptographic system. Furthermore, we demonstrate several simulations that estimate entropy of derived key so as to support the design rationale of our key derivation functions.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.31-37
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• 2024

Conventional secret sharing techniques often derive shares from randomly generated polynomials or planes, resulting in lengthy and complex shares that are challenging to memorize and/or manage without the aid of a separate computer or specialized device. Modifying existing secret sharing methods to use a predetermined value, such as a memorizable password or bio-metric information, offers a solution. However, this approach raises concerns about security, especially when the predetermined value lacks randomness or has low entropy. In such cases, adversaries may deduce a secret S with just (t - 1) shares by guessing the predetermined value or employing brute force attacks. In this paper, we introduce a share hardening method designed to ensure the security of secret sharing while enabling the use of memorizable passwords or biometric information as predetermined shares.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2299-2308
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• 1997

While most machine learning research has been primarily concerned with the development of systems that implement one type of learning strategy, we use a multistrategy approach which integrates rule induction learning and instance-based learning, and show how this marriage allows for overall better performance. In the rule induction learning phase, we derive an entropy function, based on Hellinger divergence, which can measure the amount of information each inductive rule contains, and show how well the Hellinger divergence measures the importance of each rule. We also propose some heuristics to reduce the computational complexity by analyzing the characteristics of the Hellinger measure. In the instance-based learning phase, we improve the current instance-based learning method in a number of ways. The system has been implemented and tested on a number of well-known machine learning data sets. The performance of the system has been compared with that of other classification learning technique.

• Archives of design research
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• v.17 no.2
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• pp.67-76
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• 2004

The main stream of consumption about the products is tend to transfer from low price value with mass production, to the second value of products, such as pleasure, familiarity, humor, and metaphor. This second value is closely connected to a redundancy which are also related to modern science as well as product design. These terms such as matrials, identity, and gravitation, disappeared gradually, and these are substituted with an uncertainty principle, a fortuity, a contradictory concept, entropy etc. In sum this study focuses on the tendency of intelligency issue the recent design trends. This result shows that The 4th Column Thinking and Formation System which is related to an expansion and diversity of design intellectual ideas.

• Broadcasting and Media Magazine
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• v.16 no.4
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• pp.59-71
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• 2011

오디오와 음성 압축 기술적 근간은 서로 다르지만, 최근의 모바일 멀티미디어 기기 시장의 컨버전스 현상에 따라 압축하고자 하는 신호가 혼용되고 있으며, 비슷한 목표 전송률과 음질로 수렴하고 있다. 현재는 동일 기기에서 서로 다른 압축 기술을 적용하고 있으나, 음성과 음악이 동시에 서비스 되는 멀티미디어 기기에서는 단일 압축 방식으로 처리하고자 하는 이슈가 부각되고 있다. 특히, 스마트 폰 및 음악 콘텐츠 포탈 서비스의 대중화를 고려할 때, 음성 및 음악 신호 모두를 효율적으로 압축하는 음악 및 음성 신호의 융합 압축 기술이 더욱 필요해 보인다. 본 고에서는 MPEG 오디오 그룹에서 가장 최근 진행한 Unified Speech and Audio Coding(USAC)의 탄생 배경 및 표준화 현황을 소개한다. USAC는 64kbps 이하에서 기술적으로 최고 성능을 지닌 AMR-WB+ 및 HE-AAC v2보다도 우월한 음질을 보이며, 높은 비트율에서도 동등한 음질을 보장한다. 이런 우수한 음질에 기여한 USAC의 스위칭 구조와 더불어 기술적으로 향상된 주요 모듈인 파라미터 기반 스테레오 및 고주파 압축, 그리고 엔트로피 코딩 방식에 대해서 살펴 본다. 향후, 다양한 오디오 신호를 효율적으로 압축하는 USAC는 디지털 라디오, 모바일 TV, 그리고 오디오 북과 같은 사용자 시나리오에서 사용될 확률이 높아 보인다. 또한, USAC는 배경 잡음이나 배경 음악이 있는 경우에도 성능이 우수하기 때문에 YouTube 및 podcast 등과 같이 사용자가 콘텐츠를 생성할 때도 유용하게 사용 될 수 있다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.257-262
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• 2009

This paper studies an automatic expansion of dialogue examples using the logs of an example-based dialogue system. Conventional approaches to example-based dialogue system manually construct dialogue examples between humans and a Chatbot, which are labor intensive and time consuming. The proposed method automatically classifies natural utterance pairs and adds them into dialogue example database. Experimental results show that lexical, POS and modality features are useful for classifying natural utterance pairs, and prove that the dialogue examples can be automatically expanded using the logs of a dialogue system.

• Journal of the Korean Chemical Society
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• v.32 no.6
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• pp.513-519
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• 1988

The effect of pressure and temperature on the stabilities of hexamethylbenzene-1,3,5-trinitrobenzene charge transfer complex in carbon tetrachloride has been investigated by spectrophotometric measurements. The absorption spectra of charge transfer complexes were measured at 25, 40, $50^{\circ}C$ under 1, 200, 500, 1000, 1400 bar in this experiments. The equilibrium constants of the complex were increased with pressure and decreased with temperature rising. The absorption coefficients were increased with pressure and temperature. Change of volume, enthalpy, free energy and entropy for the formation of complexes were calculated from the equilibrium constants. The red-shift observed at a higher pressure, the blue-shift at a higher temperature and the relation between pressure and oscillator strength were discussed by means of thermodynamic fuctions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.11
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• pp.504-511
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• 2014

The objective of this study is to theoretically analyze the performance of an open wet air-cycle refrigeration system, which nowadays is increasingly generating environmental concern. The temperature and relative humidity of the outside air are selected as the most important parameters. As the temperature and relative humidity of the outside air increase, the pressure ratio of the ACM compressor is determined to be nearly constant, the air temperature at the exit of the system increases, and the amount of condensed water, the cooling capacity, the COP, and the total entropy production rate increase overall. The effects of the effectiveness of the heat exchanger and the efficiency of the turbine on the performance are greater than that of the efficiency of the ACM compressor. Also, the performance of the wet air-cycle refrigeration system with two heat exchangers is enhanced, with a high COP and low total entropy production rate, compared to the system with a single heat exchanger.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.883-892
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• 2021

This paper provides a process for developing deep learning-based aerial object detection models that can run in realtime on onboard. To improve object detection performance, we pre-process and augment the training data in the training stage. In addition, we perform transfer learning and apply a weighted cross-entropy method to reduce the variations of detection performance for each class. To improve the inference speed, we have generated inference acceleration engines with quantization. Then, we analyze the real-time performance and detection performance on custom aerial image dataset to verify generalization.