distribution of continuous measurements or features in a biometric system‚ such as vocal-tract related spectral features in a speaker recognition system. GMM parameters are estimated from training data using the iterative Expectation-Maximization (EM) algorithm or Maximum A Posteriori (MAP) estimation from a well-trained prior model. Main Body Text Introduction A Gaussian mixture model is a weighted sum of M component Gaussian densities as given by the equation‚ M wi g(x|µi ‚ Σi )‚ p(x|λ) =
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sensor networks‚” Proceedings of ACM International Workshop on Underwater Networks ‚ Sep 2007. [12] D. Niculescu‚ B. Nath‚ “Ad-hoc positioning system‚” in proc: IEEE Globecom‚ 2001. [13] C. Savarese‚ K. Langendoen‚ J. Rabaey‚ “Robust positioning algorithms for distributed ad-hoc wireless sensor networks‚” in USENIX Technical Annual Conference‚ CA‚ pp. 317-328‚ 2002. [14] A. Savvides‚ H. Park‚ M. Srivastava‚ “The bits and flops of the N-hop multilateration primitive for node localization problems‚”
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the process of customer segmentation. Presented research is supported by implementation of proposed approach by which experiments were conducted. Additionally‚ the experimental results showed that proposed method performed very close to k-means algorithm which indicate the correctness of the proposed approach. Keywords: customer segmentation‚ CRM‚ Social CRM‚ clusterization‚ SOM‚ unsupervised learning‚ ANN‚ data mining. 1 Introduction To acquire competitive advantage many companies use
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filtering approach to detecting objects‚ called template matching. Object Segmentation We can extend the region-growing algorithm to detect objects in color images. The basic algorithm must be modified to compute distance on the YUV or Lab coordinates. In addition‚ a raster scan of the pixels can detect undefined pixels in an outer loop added around the preceding algorithm. Each pass through this outer loop will define a separate region‚ and the threshold T will determine the number of regions
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AEROMAN: A Novel Architecture to Evaluate Routing Protocols for Multi-hop Ad-hoc Networks Lan Tien Nguyen School of Information Science Japan Advanced Institute of Science and Technology Email: lannt@jaist.ac.jp Razvan Beuran Hokuriku Research Center National Institute of Information and Communications Technology Email: razvan@nict.go.jp Yoichi Shinoda School of Information Science Japan Advanced Institute of Science and Technology Email: shinoda@jaist.ac.jp Abstract—In this paper‚ we
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Literature Survey 4. Analysis of the Existing Algorithms 5. Conclusions 6. References Abstract Ants: Small animals (insects) that live in colonies in/on the ground. With this real life definition‚ ant colony optimization is an optimization method in which imaginary agents are used. Daemon Actions: These are the actions that can be taken to centralize the solution. The aim of Daemon Actions is to prevent quick convergence of the algorithm. Decentralized Control: A term which is related
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4. The Medium Access Sub Layer Broadcast channels [or multi-access channels] are a category of networks and the key issue is how to determine who gets to use the channel when there is competition for it. The protocols which define these factors belong to a sub layer of data link layer called the MAC(medium access control)sub layer. ALOHA: Norman Abramson devised a new and elegant method to solve the channel allocation problem called the “ALOHA” system which used ground-based Radio broad
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Object: Automated essay scoring is the computer tech-niques and algorithms that evaluate and score essays automat-ically. Compared with human rater‚ automated essay scoring has the advantage of fairness‚ less human resource cost and timely feedback. In previous work‚ automated essay scoring is regarded as a classification or regression problem. Machine learning techniques such as K-nearest-neighbor (KNN)‚ multi-ple linear regression have been applied to solve this problem. In this paper‚ we regard
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Numerical algorithms have been identified and devised to segment and classify remote sensing imagery and LiDAR data into land and water pixels‚ to form and enhance land and water objects‚ and to trace and vectorize the boundaries between land and water objects as shoreline features. A contouring routine is developed as an alternative method for extracting shoreline features from LiDAR data. While most of numerical algorithms are implemented using C++ programming language‚ some algorithms use available
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ABSTRACT: "Claytronics" is an emerging field of engineering concerning reconfigurable nanoscale robots designed to form much larger scale machines or mechanisms. Also known as "programmable matter"‚ the catoms will be sub-millimeter computers that will eventually have the ability to move around‚ communicate with each others‚ change color‚ and electrostatically connect to other catoms to form different shapes. The forms made up of catoms could morph into nearly any object‚ even replicas of human
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