• Title/Summary/Keyword: basic set

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INTUITIONISTIC FUZZY IDEALS OF A RING

  • Hur, Kul;Jang, Su-Youn;Kang, Hee-Won
    • The Pure and Applied Mathematics
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    • v.12 no.3 s.29
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    • pp.193-209
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    • 2005
  • We introduce the notions of intuitionistic fuzzy prime ideals, intuitionistic fuzzy completely prime ideals and intuitionistic fuzzy weakly completely prime ideals. And we give a characterization of intuitionistic fuzzy ideals and establish relationships between intuitionistic fuzzy completely prime ideals and intuitionistic fuzzy weakly completely prime ideals.

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Analysis of National Basic Research System: The Case of South Korea

  • Kwon, Ki-Seok;Park, So-Yeon;Jang, Duckhee
    • Asian Journal of Innovation and Policy
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    • v.6 no.2
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    • pp.152-169
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    • 2017
  • In this paper, we analyze the basic research system in South Korea. We propose a national basic research system consisting of value, openness, input, transformation, and output. Based on this framework, we set up interview questionnaires, and 15 key informants have been interviewed. According to our results, first, in terms of value, basic research is recognized as an activity for creating knowledge in the understanding of nature. Second, as for openness, scientists and policy experts agree that active interaction with the global community is an important value for the national research system. Third, in terms of sustainable research resources, scientists are strongly required to effectively allocate research funding, maximizing the creativity of researchers and the efficient sharing of research equipment. Fourth, in transformation, basic researchers maintain that the Korean research system has is extremly dependent on the government's external control, and its self-regulative system has been weak for over half century onw. Fifth, for global competitiveness, the interviewees agreed that the quality of basic research in Korea is approaching that of its global competitors. Finally, we put forward some policy implications on the basis of these findings.

Electrical Properties of Phase Change Memory Device with Novel GST/TiAlN structure (Novel GST/TiAlN 구조를 갖는 상변화 메모리 소자의 전기적 특성)

  • Lee, Nam-Yeal;Choi, Kyu-Jeong;Yoon, Sung-Min;Ryu, Sang-Ouk;Park, Young-Sam;Lee, Seung-Yun;Yu, Byoung-Gon
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2005.07a
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    • pp.118-119
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    • 2005
  • PRAM (Phase Change Random Access Memory) is well known to use reversible phase transition between amorphous (high resistance) and crystalline (low resistance) states of chalcogenide thin film by electrical Joule heating. In this paper, we introduce a stack-type PRAM device with a novel GST/TiAlN structures (GST and a heating layer of TiAlN), and report its electrical switching properties. XRD analysis result of GST thin film indicates that the crystallization of the GST film start at about $200^{\circ}C$. Electrical property results such as I-V & R-V show that the phase change switching operation between set and reset states is observed, as various input electrical sources are applied.

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Rule of Combination Using Expanded Approximation Algorithm (확장된 근사 알고리즘을 이용한 조합 방법)

  • Moon, Won Sik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.3
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    • pp.21-30
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    • 2013
  • Powell-Miller theory is a good method to express or treat incorrect information. But it has limitation that requires too much time to apply to actual situation because computational complexity increases in exponential and functional way. Accordingly, there have been several attempts to reduce computational complexity but side effect followed - certainty factor fell. This study suggested expanded Approximation Algorithm. Expanded Approximation Algorithm is a method to consider both smallest supersets and largest subsets to expand basic space into a space including inverse set and to reduce Approximation error. By using expanded Approximation Algorithm suggested in the study, basic probability assignment function value of subsets was alloted and added to basic probability assignment function value of sets related to the subsets. This made subsets newly created become Approximation more efficiently. As a result, it could be known that certain function value which is based on basic probability assignment function is closely near actual optimal result. And certainty in correctness can be obtained while computational complexity could be reduced. by using Algorithm suggested in the study, exact information necessary for a system can be obtained.

A High speed Standard Basis GF(2$^{m}$ ) Multiplier with A Known Primitive Coefficient Set (Standard Basis를 기반으로 하는 유한체내 고속 GF($2^m$) 곱셈기 설계)

  • 최성수;이영규;박민경;김기선
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.333-336
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    • 1999
  • In this paper, a new high speed parallel input and parallel output GF(2$^{m}$ ) multiplier based on standard basis is proposed. The concept of the multiplication in standard basis coordinates gives an easier VLSI implementation than that of the dual basis. This proposed algorithm and method of implementation of the GF(2$^{m}$ ) multiplication are represented by two kinds of basic cells (which are the generalized and fixed basic cell), and the minimum critical path with pipelined operation. In the case of the generalized basic cell, the proposed multiplier is composed of $m^2$ basic cells where each cell has 2 two input AND gates, 2 two input XOR gates, and 2 one bit latches Specifically, we show that the proposed multiplier has smaller complexity than those proposed in 〔5〕.

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Design and Evaluation of Flexible Thread Partitioning System (융통성 있는 스레드 분할 시스템 설계와 평가)

  • Jo, Sun-Moon
    • Journal of Internet Computing and Services
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    • v.8 no.3
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    • pp.75-83
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    • 2007
  • Multithreaded model is an effective parallel system in that it can reduce the long memory reference latency time and solve the synchronization problems. When compiling the non-strict functional programs for the multithreaded parallel machine, the most important thing is to find an set of sequentially executable instructions and to partitions them into threads. The existing partitioning algorithm partitions the condition of conditional expression, true expression and false expression into the basic blocks and apply local partitioning to these basic blocks. We can do the better partitioning if we modify the definition of the thread and allow the branching within the thread. The branching within the thread do not reduce the parallelism, do not increase the number of synchronization and do not violate the basic rule of the thread partitioning. On the contrary, it can lengthen the thread and reduce the number of synchronization. In the paper, we enhance the method of the partition of threads by combining the three basic blocks into one of two blocks.

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CoMSIA 3D-QSAR Analysis of 3,4-Dihydroquinazoline Derivatives Against Human Colon Cancer HT-29 Cells

  • Kwon, Gi Hyun;Cho, Sehyeon;Lee, Jinsung;Sohn, Joo Mi;Byun, Joon Seok;Lee, Kyung-Tae;Lee, Jae Yeol
    • Bulletin of the Korean Chemical Society
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    • v.35 no.11
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    • pp.3181-3187
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    • 2014
  • A series of 3,4-dihydroquinazoline derivatives with anti-cancer activities against human colon cancer HT-29 cell were subjected to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) approaches. The most potent compound, BK10001 was used to align the molecules. As a result, the best prediction was obtained with CoMSIA combined electrostatic, hydrophobic, and hydrogen-bond acceptor fields ($q^2=0.648$, $r^2=0.882$). This model was validated by an external test set of six compounds giving satisfactory predictive $r^2$ values of 0.879. This model would guide the design of potent 3,4-dihydroquinazoline derivatives as anti-cancer agent for the treatment of human colon cancer.

A Domain Combination Based Probabilistic Framework for Protein-Protein Interaction Prediction (도메인 조합 기반 단백질-단백질 상호작용 확률 예측기법)

  • Han, Dong-Soo;Seo, Jung-Min;Kim, Hong-Soog;Jang, Woo-Hyuk
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2003.10a
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    • pp.7-16
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    • 2003
  • In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance pro-bability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated fur the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as foaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

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Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

  • Yeom, Ha-Neul;Hwang, Myunggwon;Hwang, Mi-Nyeong;Jung, Hanmin
    • Journal of Information Science Theory and Practice
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    • v.2 no.3
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    • pp.29-39
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    • 2014
  • In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.