31 Slices
Medium 9781601323231

Session - Information and Knowledge Engineering and Management + Feature Extraction and AI

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF
Medium 9781601323231

Multi Hybrid Keyword Processing for Topic Decision of Unstructured Data

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

150

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

Multi Hybrid Keyword Processing for Topic Decision of Unstructured Data

Jinwoo Lee, Hyoungmin Ma, Gitae Lee, Kihong Ahn, Sukyoung Kim

Abstract— Amount of information and difficulty of the user's information selection has direct proportion relation. Also title is consists of exaggerated expression.

Since, authors want to summarize about document.

Therefore title is almost different from contents. If these case are more increased, offering information by simple keyword search will be reached to the limit. In this study, to solve these problems, we applied TF-IDF to extract keyword in particular documents which have scarcity words in all documents and applied LDA algorithm for to find topic about single document.

Finally, we have proposed the methodologies that add description on scarcity word and topic through to extract the Trigram of the entire document. In this study, to verify the accurate of methodology, we made supervised data and compared these data with data that made by suggested methodology.

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Medium 9781601323231

Large Scale Desalination: A Comparative Cost Affective Economic Analyses Of Nuclear, Gas and Solar Powered Plants

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

120

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

Large Scale Desalination:

A Comparative Cost Affective Economic Analyses

Of Nuclear, Gas and Solar Powered Plants

Mohammed H. S. Al Ashry

Shaqra University

The Community College

Abstract: The main objective, here, is to explore the economic viability of the solar powered desalination method through a cost and benefit comparative and contrast study.

Using the initial construction expenditure, the annual maintenance cost, and energy consumed or produced a variance ratio test of the random walk hypothesis will be implemented to determine their relative financial efficiency.

This paper will also utilize the first order autoregressive multivariate estimation model to analyze the methods and identify the most productive process with most financial promise for future investment. The total deviations of the estimated variables from the actual are accounted for by the variations of the variances of the estimates from the actual.

The higher the percentage of the unexplained deviation the higher the risk involved. The portfolio variance will be utilized to measure the investment risk in the three desalination industries.

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Medium 9781601323231

Faces Recognition with Image Feature Weights and Least Mean Square Learning Approach

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'14 |

21

Faces Recognition with Image Feature Weights and Least Mean Square

Learning Approach

Wei-Li Fang, Ying-Kuei Yang and Jung-Kuei Pan

Dept. of Electrical Engineering, National Taiwan Uni. of Sci. & Technology, Taipei, Taiwan

Email: yingkyang@yahoo.com

Abstract - Most of 2DPCA-enhanced approaches improve face recognition rate while at the expense of computation load.

In this paper, an approach is proposed to greatly improve face recognition rate with slightly increased computation load.

In this approach, the 2DPCA is applied against a face image to extract important image features for selection. A weight is then assigned to each of selected image features according to the feature’s importance to face recognition. The least mean square (LMS) algorithm is further applied to optimize the feature weights based on the recognition error rate during learning process in order to improve face recognition performance. The experiments have been conducted against

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Medium 9781601323231

Session - Knowledge and Information Visualization + Imaging Science and Applications

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, George Jandieri, Ashu M. G. Solo, and Fernando G. Tinetti CSREA Press PDF

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