• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1333-1336
• /
• 2015

감성분석은 최근 오피니언 마이닝에서 주목받고 있는 분야로써, 특정 주제, 상품, 유명인사 등에 대한 사람들의 반응을 긍정 또는 부정으로 구분하거나 점수를 이용하여 긍정 또는 부정의 강도를 분석하는데 이용되고 있다. PMI(pointwise mutual information)와 SO-PMI(semantic orientation from pointwise mutual information)는 비교적 빠르고 간편하게 극성을 판단할 수 있다는 장점이 있지만, 어휘와 기준 어휘 사이의 극성 값이 넓은 범위를 갖는다는 단점이 있다. 본 논문에서는 일상적인 언어 사용 환경에서 나타나는 어휘로부터 감성을 분석하고자 하였다. 특히 어휘의 극성 값 편차로 인해 나타날 수 있는 어려움을 보완하기 위해 NPMI(normalized pointwise mutual information)를 이용하여 어휘의 감성을 분석하였다. PMI와 NPMI를 비교 분석한 결과 어휘의 감성 강도를 나타내는 데 있어서 밀집도에서 큰 차이를 보였다.

• Journal of Environmental Science International
• /
• v.22 no.8
• /
• pp.953-963
• /
• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• Journal of Navigation and Port Research
• /
• v.30 no.7
• /
• pp.579-583
• /
• 2006

The purpose of this paper is to study a relationship between alliance success factors and performances of strategic alliance. In order to achieve the purpose of this research, factor analysis, reliability and validity and regression method are used. In conclusion, alliance success factors can be divided as mutual complementarity and information sharing factor, sharing and mutual agreement of vision and goal factor, performance management factor and culture and organization factor. According to regression results, all of four factors affects significantly dependent variables. Among them, mutual complementarity and information sharing mostly affects each dependent variable.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.32A no.1
• /
• pp.61-69
• /
• 1995

a numerical method to the problem of mutual admittance between two slots is considered by use of conservation of complex power. Calculation of mutual admittance is compared with other results. And mutual admittance obtained by the method is used in the analysis for the broadband rectangular microstrip antenna geometry using E0plane gap coupling. The theoretical results for both return loss and radiation pattern of the broadband antenna are compared with experimental results. Good agreement between calculated and measured values has been observed.

• Korean Management Science Review
• /
• v.24 no.2
• /
• pp.57-72
• /
• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• Journal of Communications and Networks
• /
• v.10 no.1
• /
• pp.89-97
• /
• 2008

Anomaly detection systems playa significant role in protection mechanism against attacks launched on a network. The greatest challenge in designing systems detecting anomalous exploits is defining what to measure. Effective yet simple, Shannon entropy metrics have been successfully used to detect specific types of malicious traffic in a number of commercially available IDS's. We believe that Renyi entropy measures can also adequately describe the characteristics of a network as a whole as well as detect abnormal traces in the observed traffic. In addition, Renyi entropy metrics might boost sensitivity of the methods when disambiguating certain anomalous patterns. In this paper we describe our efforts to understand how Renyi mutual information can be applied to anomaly detection as an offline computation. An initial analysis has been performed to determine how well fast spreading worms (Slammer, Code Red, and Welchia) can be detected using our technique. We use both synthetic and real data audits to illustrate the potentials of our method and provide a tentative explanation of the results.

• Genomics & Informatics
• /
• v.18 no.4
• /
• pp.41.1-41.8
• /
• 2020

We provide an algorithm for the construction and analysis of autocorrelation (information) functions of gene nucleotide sequences. As a measure of correlation between discrete random variables, we use normalized mutual information. The information functions are indicative of the degree of structuredness of gene sequences. We construct the information functions for selected gene sequences. We find a significant difference between information functions of genes of different types. We hypothesize that the features of information functions of gene nucleotide sequences are related to phenotypes of these genes.

• Journal of Korean Society of Rural Planning
• /
• v.23 no.3
• /
• pp.37-51
• /
• 2017

There has been a growing concern on ontology especially in recent knowledge-based industry and defining a field-customized semantic word network is essential for building it. In this paper, a word network for ontology is established with 785 publications of Korean Society of Rural Planning(KSRP), from 1995 to 2017. Semantic relationships between words in the publications were quantitatively measured with the 'normalized pointwise mutual information' based on the information theory. Appearance and co-appearance frequencies of nouns and adjectives in phrases are analyzed based on the assumption that a 'noun phrase' represents a single 'concept'. The word network of KSRP was compared with that of $WordNet^{TM}$, a world-wide thesaurus network, for the verification. It is proved that the KSRP's word network, established in this paper, provides words' semantic relationships based on the common concepts of Korean rural planning research field. With the results, it is expecting that the established word network can present more opportunity for preparation of the fourth industrial revolution to the field of the Korean rural planning.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 1994.02a
• /
• pp.163-172
• /
• 1994

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.9
• /
• pp.2405-2423
• /
• 2012

In a traditional Single Sign-On (SSO) scheme, the user and the Service Providers (SPs) have given their trust to the Identity Provider (IdP) or Authentication Service Provider (ASP) for the authentication and correct assertion. However, we still need a better solution for the local/native true SSO to gain user confidence, whereby the trusted entity must play the role of the ASP between distinct SPs. This technical gap has been filled by Trusted Computing (TC), where the remote attestation approach introduced by the Trusted Computing Group (TCG) is to attest whether the remote platform integrity is indeed trusted or not. In this paper, we demonstrate a Trustworthy Mutual Attestation (TMutualA) protocol as a proof of concept implementation for a local true SSO using the Integrity Measurement Architecture (IMA) with the Trusted Platform Module (TPM). In our proposed protocol, firstly, the user and SP platform integrity are checked (i.e., hardware and software integrity state verification) before allowing access to a protected resource sited at the SP and releasing a user authentication token to the SP. We evaluated the performance of the proposed TMutualA protocol, in particular, the client and server attestation time and the round trip of the mutual attestation time.