Point pattern matching is the basis of image recognition and computer vision. Point pattern matching in three dimensional space with the presence of noise and outlier is an important research focus. In this paper, we ...
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Wireless Sensor Networks (WSNs) are made up of tiny sensor nodes which sense the data and communicate to the base station via other nodes. These sensor nodes are inexpensive portable devices with limited processing po...
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Wireless Sensor Networks (WSNs) are made up of tiny sensor nodes which sense the data and communicate to the base station via other nodes. These sensor nodes are inexpensive portable devices with limited processing power and energy resources which make them in need of smart clustering protocols. Many clustering and routing protocols were proposed in the literature to serve large networks of such tiny devices. In this paper, we have implemented and analyzed different clustering protocols, namely LEACH, LEACH-C, LEACH-1R, and HEED using MATLAB environment. These clustering protocols are compared in different terms such as residual energy, data delivery to the base station, maximum number of rounds and the number of live nodes. Experimental results showed a better performance of the LEACH protocols when compared to the different versions of HEED. Moreover, LEACH-1R proved to be efficient in terms of network lifetime.
Most of the microarray expression data have tens of thousands of genes but very small number of samples. Feature selection has been widely used to extract the subset of informative genes. Though many feature selection...
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This paper has presented a method of facial age estimation using a hybrid of Support Vector Machines (SVMs) and Fuzzy Logic (FL). The proposed method has taken facial features from wrinkles and skin color on the human...
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This paper has presented a method of facial age estimation using a hybrid of Support Vector Machines (SVMs) and Fuzzy Logic (FL). The proposed method has taken facial features from wrinkles and skin color on the human face to estimate the age group and age in point. SVMs was used to estimate the five age-groups of human age. Then, FL was implemented to estimate the age in point corresponding in each group resulting from SVMs. For performance evaluation, k-fold cross validation was carried out using FG-NET and PAL databases consisting of 700 and 500 faces, respectively. The proposed method was evaluated in comparison with five advanced methods in literature. The results showed that the proposed method provided 88.84% and 90.88% of accuracy in aging group estimation in FG-NET and PAL databases, respectively. In addition, the proposed method reported 4.81 and 3.12 for MAE (mean absolute error) for point age estimation using FG-NET and PAL, respectively. In this regard, the proposed method provided the higher performance on accuracy and MAE superior to the compared methods.
Negotiations among autonomous agents have gained a mass of attention from a variety of communities in the past decade. This paper deals with a prominent type of automated negotiations, namely, multilateral multi-issue...
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ISBN:
(纸本)9781509001644
Negotiations among autonomous agents have gained a mass of attention from a variety of communities in the past decade. This paper deals with a prominent type of automated negotiations, namely, multilateral multi-issue negotiation that runs under real-time constraints and in which the negotiating agents have no prior knowledge about their opponents' preferences over the space of negotiation outcomes. We propose a novel negotiation approach which enables an agent to reach an efficient agreement with multiple opponents. The proposed approach achieves that goal by, 1) employing sparse pseudo-input Gaussian processes to model the behavior of opponents, 2) learning fuzzy opponent preferences to increase the satisfaction of other parties, and 3) adopting an adaptive decision-making mechanism to handle uncertainty in negotiation. The experimental results show, both from the standard mean-score perspective and the perspective of empirical game theory, that the agent applying the proposed approach outperforms the state-of-the-art negotiation agents from the recent Automated Negotiating Agents Competition (ANAC) in a variety of negotiation domains.
Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of n...
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Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high e±ciency. In the registration algorithm, we firstly segmented the reference image and °oat image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.
Nowadays, there are many events reported by News Media everyday, which contains a massive number of news. People are getting more and more interested in understanding how an event evolves after it happens. News relate...
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ISBN:
(纸本)9781450327657
Nowadays, there are many events reported by News Media everyday, which contains a massive number of news. People are getting more and more interested in understanding how an event evolves after it happens. News related to the same event or similar events usually has more common entities and stronger topic correlations, which is a new perspective to study news event. Due to the complexity of event evolving process, event visualization has been a big challenge for a long time. In this paper, we design a novel four-phase framework NEI(News Event Insight) that focuses on visualizing a news event properly and clearly, namely (1)Entity Topic Modeling. We extract topics and entities through timeline. (2)Temporal Topic Correlation Analysis. Based on the topic modeling result, we design two methods to select hot topics and build links for them. (3)Keyword Extraction. Specially, we combine string frequency with syntax features and use language models to acquire candidate keywords for representing topics. (4)Visualization. Visualization demonstrates the quantifying properties of topics related to a certain event. A case study shows our framework achieves promising results on both single event and similar events. Copyright 2014 ACM.
Paraphrase generation is widely used for various natural language processing (NLP) applications such as question answering, multi-document summarization, and machine translation. In this study, we identify the problem...
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ISBN:
(纸本)9786165518871
Paraphrase generation is widely used for various natural language processing (NLP) applications such as question answering, multi-document summarization, and machine translation. In this study, we identify the problems occurring in the process of applying existing probabilistic model-based methods to agglutinative languages, and provide solutions by reflecting the inherent characteristics of agglutinative languages. More specifically, we propose and evaluate a sentential paraphrase generation (SPG) method for the Korean language using Support Vector Machines (SVM) with a string kernel. The quality of generated paraphrases is evaluated using three criteria: (1) meaning preservation, (2) grammaticality, and (3) equivalence. Our experiment shows that the proposed method outperformed a probabilistic model-based method by 12%, 16%, and 17%, respectively, with respect to the three criteria. Copyright 2014 by Hancheol Park, Gahgene Gweon, Ho-Jin Choi, Jeong Heo, and Pum-Mo Ryu.
Query expansion adds related words to a user query in order to improve retrieval results. It's an important step in information retrieval. Most of current query expansion methods pay attention to specific expansio...
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Query expansion adds related words to a user query in order to improve retrieval results. It's an important step in information retrieval. Most of current query expansion methods pay attention to specific expansion strategies or algorithms, while neglecting the query itself. In reaction to the phenomenon, a multistrategy query expansion method based on semantics was proposed. This method started by analyzing the semantic structure of user query, and adopted corresponding strategy to select expansion terms. The expansion words are derived from three parts: WordNet, massive web page set and search engine performance evaluation data, which were merged semantically in each expansion algorithm later. The experiment showed this method can improve retrieval results to some extent.
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