• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.37-40
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• 2021

This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.229-234
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• 2014

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.591-605
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• 2010

Cool roofs are currently being emerged as one of important mechanism to save energy in relation to the building. This paper reviews worldwide experiences (USA, Japan and EU etc) for the potential benefits cool roofs offer in relation to building energy saving for comparison purposes. It is confirmed that there is a significant potential to the energy saving by introducing the cool roof in a Korean climate because of similarity in terms of HDD (Heating Degree Day) and CDD (Cooling Degree Day) as those countries reviewed. Such a comparative study highlights that the type of measurements performed and the quantitative parameters reported from the countries should be standardized in Korean context in order to implement further comparable experiments for scientifically sound investigations. It is anticipated that this research output could be used as a valuable reference in implementing a Nation-wide cool roofing strategy in the central and local governments since a suitable technical, more objective direction has been proposed based on the measured, fully quantitative performance of the involved components of a cool roof system in the global context. From this critical review, a very important step has been made concerning the practicality of cool roof in Korean context. Ultimately, the suggestion in this paper will greatly contribute to opening new possibilities for introducing cool roof in this country, proposed as an initial aim of this paper.

• Korean Journal of Cognitive Science
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• v.23 no.3
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• pp.295-322
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• 2012

In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.479-487
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• 2016

People can listen to almost every type of music by music streaming services without possessing music. Ironically it is difficult to choose what to listen to. A music recommendation system helps people in making a choice. However, existing recommendation systems have high computation complexity and do not consider context information. Emotion is one of the most important context information of music. Lyrics can be easily computed with various language processing techniques and can even be used to extract emotion of music from itself. We suggest a music-level similarity evaluation method using emotion and structure. Our result shows that it is important to consider semantic information when we evaluate similarity of music.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.59-66
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• 2005

The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

• Journal of Distribution Science
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• v.11 no.5
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• pp.63-76
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• 2013

Purpose - For the past several decades, behavioral economics or behavioral decision theory has undergone rapid development. This study provides a critical review of the development of behavioral economics with a focus on what are deemed to be core theories in the field. Starting from the utility function proposed by Daniel Bernoulli in the 18th century, the development history of utility functions until the emergence of the prospect theory is thoroughly reviewed. Some of the experimental results violating the traditionally assumed utility function and supporting the prospect theory value function are summarized. The most representative principles of rational choice are transitivity, independence from irrelevant alternatives (IIA), and regularity. The development of behavioral economics has been triggered by finding counter-examples to these principles. Some of the choice behaviors discussed in this study as counter-examples to the traditional theories of rational choice are the St. Petersburg paradox; the Allais paradox; gambling behavior; and the various context effects including the similarity effect, attraction effect, and the compromise effect. The Elimination-by-Aspects (EBA) model, which was proposed as an explanation for the similarity effect, is discussed in detail as well. Based on the literature review and further analysis, this study summarizes the relationship between the context effects, prospect theory, and EBA model. Research design, data, and methodology - This study provides an extensive literature review on several important theories in the field of behavioral decision theory and adds some critical comments to the theories and the relationships among them. This study first reviews the development of utility functions. Daniel Bernoulli introduced the concept of utility function to solve the St. Petersburg paradox. In the mid-20th century, Herbert Simon proposed the "satisficing" heuristic and presented a value function with a shape different from traditional utility functions. This study highlights the strengths and weaknesses of several utility functions proposed until the emergence of the prospect theory value function. Results - This study posits that prospect theory and EBA model are the two most important theories in the field of behavioral decision theory. They can explain various choice behaviors that traditional utility maximization analysis has been unable to. The application of these models to various fields is further increasing nowadays. This study explains how prospect theory and the EBA model can be used to explain the context effects. Conclusions - The traditional economic theory relies on a single variable called "utility" in explaining consumer choice. However, this study argues that, in investigating consumer choice, several other variables should also be considered. These are the similarity among alternatives, an alternative's prototypicality within the category, the dominance relationship between alternatives, and the reference point in evaluating alternatives. Due to the development of behavioral economics, we are now closer to a more complete understanding of consumer choice behavior than in the past when we had only a single tool called utility.

• Journal of the Korean Home Economics Association
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• v.36 no.11
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• pp.19-41
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• 1998

본 연구는 개인-환경 상호작용 가정을 바탕으로 한국의 두 가지 결혼 유형에 따른 배우자 선택과 결혼 적응의 메커니즘을 이해하기 위하여 개인, 과정, 맥락의 역할을 포함안 연구 모델 (person-process-context model)을 적용시켰다. 배우사 선택, 이에 따른 부부간 유사성과 결혼적응에 있어 개인과 사회적 특성의 상대적 기여도와 그 매커니즘을 조사하기 위해 154쌍의 한국 부부를 대상으로 설문조사 하였다. 연구결과에 의하면, 중매결혼과 연애결혼의 결혼유형에 관계없이 모두 동질혼의 경향을 보였다. 개인적 특성이 결혼 적응도와 높은 상관을 보인 반면, 부부간 유사성은 결혼 적응도와 유의한 상관이 업었다. 이는 결혼 적응에 있어서 환경적 요소(e. g. dyadic similarity)보다 개인적 요소가 중요하다는 것을 시사한다. 결혼유형에 따른 동질혼의 정도에는 유의한 차이가 없으며, 또한 동질혼의 정도에 따른 결혼적응도에는 유의한 차이가 발견되지 않았다. 연애결혼과 중매결혼의 중요한 차이는 결혼전 교제기간 이었다. 연애 결혼한 부부는 비교적 오랜 교제 기간을 통해 더 만족한 결혼생활을 영위하는 것으로 나타났다. 결혼전 교제기간의 효과를 통제한 후 두 결혼 유형의 결혼적응도에 대한 차이는 사라졌다. 연구결과들을 결혼과 성격에 관한 이론을 비탕으로 논의하였다.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.141-160
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• 2007

User interface has been regarded as a crucial issue to increase the acceptance of mobile services. In special, even though to what extent the machine as speaker communicates with human as listener in a timely and polite manner is important, fundamental studies to come up with these issues have been very rare. Hence, the purpose of this paper is to propose a methodology of estimating politeness level in a certain context-aware setting and then to design a context-aware system for polite mobile interface. We will focus on Korean language for the polite level estimation simply because the polite interface would highly depend on cultural and linguistic characteristics. Nested Minkowski aggregation model, which amends Minkowski aggregation model, is adopted as a privacy-preserving similarity evaluation for case retrieval under distributed computing environment such as ubiquitous computing environment. To show the feasibility of the methodology proposed in this paper, simulation-based experiment with drama cases has performed to show the performance of the methodology proposed in this paper.