• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.617-636
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• 2021

This paper presents a privacy-preserving data aggregation scheme deals with the multidimensional data. It is essential that the multidimensional data is rarely mentioned in all researches on smart grid. We use the Paillier Cryptosystem and blinding factor technique to encrypt the multidimensional data as a whole and take advantage of the homomorphic property of the Paillier Cryptosystem to achieve data aggregation. Signature and efficient batch verification have also been applied into our scheme for data integrity and quick verification. And the efficient batch verification only requires 2 pairing operations. Our scheme also supports fault tolerance which means that even some smart meters don't work, our scheme can still work well. In addition, we give two extensions of our scheme. One is that our scheme can be used to compute a fixed user's time-of-use electricity bill. The other is that our scheme is able to effectively and quickly deal with the dynamic user situation. In security analysis, we prove the detailed unforgeability and security of batch verification, and briefly introduce other security features. Performance analysis shows that our scheme has lower computational complexity and communication overhead than existing schemes.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2005년도 춘계학술대회 발표 논문집
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• pp.65-78
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• 2005

Nowadays, large amounts of XML documents are available on the Internet. Thus, we need to analyze them multi-dimensionally in the same way as relational data. In this paper, we propose a new frame-work for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where every fact data as well as dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new multidimensional expression language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate the measure data. They specify text mining operators for aggregating text constituting the measure data. We evaluate XML-OLAP by applying it to a U.S. patent XML warehouse. We use XML-MDX queries, which demonstrate that XML-OLAP is effective for multi-dimensionally analyzing the U.S. patents.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1135-1143
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• 2007

The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.

• 한국식생활문화학회지
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• 제15권1호
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• pp.51-58
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• 2000

This study is designed to 1) understand customers' choice behavior and preference of foodservices in campus and 2) provide recommendation on management strategies for university foodservice manager. Individual interview and focus group interview were used to identify important selection attributes. The questionnaire was developed and distributed to 480 Yonsei university students and statistical data analysis was completed using SPSS WIN/7.5 for descriptive analysis, multidimensional scaling and conjoint analysis. The results of this study were summarized as follows: Students evaluated four foodservices in different ways, and strength/weakness points could be identified from the evaluation patterns. Most students(51.1%) were frequently used 'A' foodservice, though they preferred other foodservices, and cost, mainly, caused the difference. Perceptual map from multidimensional scaling showed that preference and patronage were close with different attributes. Cost was most relatively important attribute to select foodservice in campus from conjoint analysis. Therefore, relative importance of attributes should be considered in customer preference survey for constructing management plan.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.400-407
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• 2022

Innovations significantly affect the efficiency of the socioeconomic systems of the regions, acting as a system-forming element of their development. Modern models of economic development also consider innovation activity, intellectual potential, knowledge as the basic factors for stimulating the economic growth of the region. The purpose of the study is to develop methodological foundations for evaluating the effectiveness of a regional innovation system based on a multidimensional analysis of its effects. To further study the effectiveness of RIS, we have used one of the methods of multidimensional statistical analysis - canonical analysis. The next approach allows adding another important requirement to the methodological provision of evaluation of the level of innovation development of industries and regions, namely - the time factor, the formalization of which is realized in autoregressive dynamic economic and mathematical models and can be used in our research. Multidimensional Statistical Analysis for RIS effectiveness estimation was used to model RIS by typological regression. Based on it, multiple regression models were built in groups of regions with low and relatively high innovation potential. To solve the methodological problem of RIS research, we can also use the approach to the system as a "box" with inputs and outputs.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4373-4391
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• 2022

Marine reactor systems experience platform movement, and therefore, the system thermal-hydraulic analysis code needs to reflect the motion effect on the fluid to evaluate reactor safety. A moving reactor model for MARS-KS was developed to simulate the hydrodynamic phenomena in the reactor under motion conditions; however, its applicability does not cover the MULTID component used in multidimensional flow analyses. In this study, a moving reactor model is implemented for the MULTID component to address the importance of multidimensional flow effects under dynamic motion. The concept of the volume connection is generalized to facilitate the handling of the junction of MULTID. Further, the accuracy in calculating the pressure head between volumes is enhanced to precisely evaluate the additional body force. Finally, the Coriolis force is modeled in the momentum equations in an acceleration form. The improvements are verified with conceptual problems; the modified model shows good agreement with the analytical solutions and the computational fluid dynamic (CFD) simulation results. Moreover, a simplified gravity-driven injection is simulated, and the model is validated against a ship flooding experiment. Throughout the verifications and validations, the model showed that the modification was well implemented to determine the capability of multidimensional flow analysis under ocean conditions.

• 한국멀티미디어학회논문지
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• 제11권5호
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• pp.567-578
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• 2008

인터넷에 있는 방대한 양의 웹 페이지들을 분석하기 위해서는 웹 페이지에 내재된 정보를 추출하는 것이 필요하다. 본 논문에서는 웹 페이지로부터 정보를 추출하고 이를 XML 문서로 변환하여 다차원적으로 분석하는 방법을 제안한다. 웹 페이지로부터 정보를 추출하기 위하여 두 종류의 언어를 제안한다. 하나는 객체지향 모델에 의거하여 웹 정보 추출 규칙을 기술하기 위한 것이고, 다른 하나는 추출하고자 하는 정보를 찾기 위한 HTML 태그 패턴을 정규식으로 기술하기 위한 것이다. XML 문서에 대한 다차원 분석을 위하여 관계형 데이터에 대해 하는 것처럼 웨어하우스를 구축하고 이로부터 다양한 큐브를 생성하는 방법을 제안한다. 마지막으로 본 논문에서 제안한 방법을 미국특허 웹 페이지에 적용한 예를 통해 그 타당성을 보인다.

• 센서학회지
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• 제23권2호
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• pp.99-104
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• 2014

Sensor arrays based on chemical sensors produce multidimensional patterns of data that may be used discriminate between different chemicals. For the human observer, visualization of multidimensional data is difficult, since the eye and brain process visual information in two or three dimensions. To devise a simple means of data inspection from the response of sensor arrays, PCA (Principal Component Analysis) or Sammon's nonlinear mapping technique can be applied. The PCA, which is a well-known statistical method and widely used in data analysis, has disadvantages including data distortion and the axes for plotting the dimensionally reduced data have no physical meaning in terms of how different one cluster is from another. In this paper, we have investigated two techniques and proposed a combination technique of PCA and nonlinear Sammom mapping for visualization of multidimensional patterns to two dimensions using data sets from odor sensing system. We conclude the combination technique has shown more advantages comparing with the PCA and Sammon nonlinear technique individually.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.838-855
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• 2019

Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.

• 정보화연구
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• 제11권1호
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• pp.63-73
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• 2014

웹의 발달로 텍스트 등으로 이루어진 비정형 데이터의 활용에 대한 관심이 높아지고 있다. 웹상에서 사용자들이 작성한 대부분의 비정형 데이터는 사용자의 주관이 담겨져 있어 이를 적절히 분석할 경우 사용자의 취향이나 주관적인 관점 등의 아주 유용한 정보를 얻을 수 있다. 이 논문에서는 이러한 비정형 텍스트 문서를 다양한 차원으로 분석하기 하는데 OLAP(온라인 분석 처리)의 다차원 데이터 큐브 기술을 활용한다. 다차원 데이터 큐브는 간단한 문자나 숫자 형태의 정형적인 데이터에 대해 다차원 분석하는데 널리 사용되었지만, 텍스트 문장으로 이루어진 비정형 데이터에 대해서는 활용되지 않았다. 이러한 텍스트 데이터베이스에 포함된 정보를 다차원으로 분석하기 위한 방법으로 텍스트 큐브 모델이 최근에 제안되었는데, 이 텍스트 큐브는 정보 검색에서 널리 사용하는 용어 빈도수(Term Frequency)와 역 인덱스(Inverted Index)를 측정값으로 이용하여 텍스트 데이터베이스에 대한 다차원 분석을 지원한다. 이 논문에서는 이러한 다차원 텍스트 큐브를 활용하여 실제 서비스되고 있는 호텔 정보 공유 사이트의 리뷰 데이터 분석에 활용하였다. 이를 위해 호텔 리뷰 데이터에 대한 다차원 텍스트 큐브를 생성하였으며, 이를 이용하여 다차원 키워드 검색 기능을 제공하여 사용자 중심의 의미있는 정보 검색이 가능한 시스템을 설계 및 구현하였다. 또한, 본 논문에서 제안하는 시스템에 대해 다양한 실험을 수행하였으며 이를 통해 제안된 시스템의 실효성을 검증하였다.