ppxscal/embedding_network huggingface dataset:
Uncertainty and sensitivity ratio of parameters in estimating and promoting retrieval accuracy
Authors: Xihan Mu, Guangjian Yan, Zhao-Liang Li
Venue: International Journal of Remote Sensing (2008)

Inversion is an important process in remote sensing. To estimate the accuracy of retrieved parameters before inversion, we defined an Uncertainty and Sensitivity Ratio in the inversion of remote sensing models. It is a ratio of the priori uncertainty and sensitivity of one input parameter in the forward model to the sum of all parameters' uncertainty and sensitivity. USR was shown to reflect the variance of the retrieved parameter by error propagation theory. Subsequently, we took numeric experiments to illustrate the property of USR for typical vegetation cover scenes. Forty-eight multiangular datasets of Bidirectional Reflectance Factors were generated for these scenes by adding random noise to the Light Scattering by Arbitrarily Inclined Leaves model output. Seven parameters were retrieved for each scene. The results suggested that the Mean Square Error of the inversion results is highly correlated with USR. Based on this ratio, we selected two different angular observations in red and near-infrared (NIR) band to get a new Normalized Difference Vegetation Index (NDVI), which could produce less uncertainty to retrieve the Leaf Area Index (LAI) than using the conventional single-angular observations. The new NDVI was tested by retrieving LAI using the simulated multispectral and multiangular datasets. It was found that the inversion results of LAI are more accurate by using this new NDVI than using the traditional one.
Object detection and segmentation algorithm implemented on a reconfigurable embedded platform based FPGA
Authors: Slami Saadi, Hamza Mekki, Abderrezak Guessoum
Venue: WSEAS Transactions on Signal Processing (2008)

In this article, we present a mixed software/hardware Implementation on a Xilinx's Microblaze Soft core based FPGA platform. The reconfigurable embedded platform designed to support an important algorithm in image processing which is region color image segmentation for detecting objects based on RGB to HSL transformation. The proposed work is implemented and compiled on the embedded development kit EDK6.3i and the synthesis software ISE6.3i available with Xilinx Virtex-II FPGA using C++ language. The basic motivation of our application to radio isotopic images and neutron tomography is to assist physicians in diagnostics by taking out regions of interest. The system is designed to be integrated as an extension to the nuclear imaging system implemented around our nuclear research reactor. The proposed design can significantly accelerate the algorithm and the possible reconfiguration can be exploited to reach a higher performance in the future, and can be used for many image processing applications.
Creating Flash Widgets with Flash CS4 and ActionScript 3.0, 1 edition
Authors: John Arana
Venue: Firstpress (2008)

Creating Flash Widgets with Flash CS4 and ActionScript 3.0 is an introduction to developing widgets for the Internet using the new features of Flash CS4 and ActionScript 3.0. Many social-networking sites, blogs, and personal home pages have adopted the use of widgets and Flash developers can create and distribute their own widgets for others to use. A step-by-step example demonstrates how to design and develop your own Flash widgets and integrate them with XML. In addition, publishing, promoting, and capitalizing on your Flash widgets is discussed. What you'll learn Using the new tools in Flash CS4 Basic differences of ActionScript 3.0 Designing and developing widgets Utilizing XML with widgets Publishing widgets to the Internet Promoting and capitalizing on widgets Who is this book for? Creating Flash Widgets with Flash CS4 and ActionScript 3.0 targets novice to intermediate Flash designers/developers interested in learning how to create and publish widgets for the Internet.
Document cleanup using page frame detection
Authors: Faisal Shafait, Joost van Beusekom, Daniel Keysers, Thomas M. Breuel
Venue: International Journal on Document Analysis and Recognition (2008)

When a page of a book is scanned or photocopied, textual noise (extraneous symbols from the neighboring page) and/or non-textual noise (black borders, speckles, ...) appear along the border of the document. Existing document analysis methods can handle non-textual noise reasonably well, whereas textual noise still presents a major issue for document analysis systems. Textual noise may result in undesired text in optical character recognition (OCR) output that needs to be removed afterwards. Existing document cleanup methods try to explicitly detect and remove marginal noise. This paper presents a new perspective for document image cleanup by detecting the page frame of the document. The goal of page frame detection is to find the actual page contents area, ignoring marginal noise along the page border. We use a geometric matching algorithm to find the optimal page frame of structured documents (journal articles, books, magazines) by exploiting their text alignment property. We evaluate the algorithm on the UW-III database. The results show that the error rates are below 4% each of the performance measures used. Further tests were run on a dataset of magazine pages and on a set of camera captured document images. To demonstrate the benefits of using page frame detection in practical applications, we choose OCR and layout-based document image retrieval as sample applications. Experiments using a commercial OCR system show that by removing characters outside the computed page frame, the OCR error rate is reduced from 4.3 to 1.7% on the UW-III dataset. The use of page frame detection in layout-based document image retrieval application decreases the retrieval error rates by 30%.
Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks
Authors: Cunqing Hua, Tak-Shing Peter Yum
Venue: IEEE/ACM Transactions on Networking (TON) (2008)

An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. The objective is to maximize the network lifetime by jointly optimizing data aggregation and routing. We adopt a model to integrate data aggregation with the underlying routing scheme and present a smoothing approximation function for the optimization problem. The necessary and sufficient conditions for achieving the optimality are derived and a distributed gradient algorithm is designed accordingly. We show that the proposed scheme can significantly reduce the data traffic and improve the network lifetime. The distributed algorithm can converge to the optimal value efficiently under all network configurations.
Pictures from the Skype
Authors: Dario Rossi, Silvio Valenti, Paolo Veglia, Dario Bonfiglio, Marco Mellia, Michela Meo
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

This paper focuses on the characterization and classification of Skype traffic, a nowadays very popular and fashionable VoIP application. Building over previous work, we develop a software tool which can be used to examine the evolution of Skype call classification in an interactive fashion. The demonstrator software focuses on the main aspects of Skype traffic characterization and presents the traffic patterns Skype generates during a call or while idle. In addition, the demonstrator shows the evolution of the internal indexes the Skype classifiers use. After describing the classification process and the demonstrator software, we use the tool to demonstrate the feasibility of online Skype traffic identification, considering both accuracy and computational costs. Experimental results show that few seconds of observation are enough to allow the classifier engines to correctly identify the presence of Skype flows. Moreover, results indicate that the classification engine can cope with multi-Gbps links in real-time using common off-the-shelf hardware.
Simrank++: query rewriting through link analysis of the click graph
Authors: Ioannis Antonellis, Hector Garcia Molina, Chi Chao Chang
Venue: Proceedings of the VLDB Endowment (2008)

We focus on the problem of query rewriting for sponsored search. We base rewrites on a historical click graph that records the ads that have been clicked on in response to past user queries. Given a query q, we first consider Simrank [7] as a way to identify queries similar to q, i.e., queries whose ads a user may be interested in. We argue that Simrank fails to properly identify query similarities in our application, and we present two enhanced versions of Simrank: one that exploits weights on click graph edges and another that exploits "evidence." We experimentally evaluate our new schemes against Simrank, using actual click graphs and queries from Yahoo!, and using a variety of metrics. Our results show that the enhanced methods can yield more and better query rewrites.
Nowhere to Hide: Finding Plagiarized Documents Based on Sentence Similarity
Authors: Nathaniel Gustafson, Maria Soledad Pera, Yiu-Kai Ng
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of on-line publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1 and D2 based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates agraphical view of sentences that are similar (or the same) in D1 and D2. Experimental results verify that SimPaD is highly accurate in detecting (non-) plagiarized documents and outperforms existing plagiarism-detection approaches.
An Agent Memory Model Enabling Rational and Biased Reasoning
Authors: Annerieke Heuvelink, Michel C. A. Klein, Jan Treur
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

This paper presents an architecture for a memory model that facilitates versatile reasoning mechanisms over the beliefs stored in an agent’s belief base. Based on an approach for belief aggregation, a model is introduced for controlling both the formation of abstract and complex beliefs and the retrieval of them based on their activation history. An implementation of the presented mechanisms illustrates how it can be used in intelligent agents that exhibit human-like (biased) reasoning as well as rational reasoning.
MultiML: a general purpose representation language for multimodal human utterances
Authors: Manuel Giuliani, Alois Knoll
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

We present MultiML, a markup language for the annotation of multimodal human utterances. MultiML is able to represent input from several modalities, as well as the relationships between these modalities. Since MultiML separates general parts of representation from more context-specific aspects, it can easily be adapted for use in a wide range of contexts. This paper demonstrates how speech and gestures are described with MultiML, showing the principles - including hierarchy and underspecification - that ensure the quality and extensibility of MultiML. As a proof of concept, we show how MultiML is used to annotate a sample human-robot interaction in the domain of a multimodal joint-action scenario.
An adaptive fusion algorithm based on ANFIS for radar/infrared system
Authors: Q. Yuan, C. Y. Dong, Q. Wang
Venue: Expert Systems with Applications: An International Journal (2009)

In order to improve tracking ability, an adaptive fusion algorithm based on adaptive neuro-fuzzy inference system (ANFIS) for radar/infrared system is proposed, which combines the merits of fuzzy logic and neural network. Fuzzy adaptive fusion algorithm is a powerful tool to make the actual value of the residual covariance consistent with its theoretical value. To overcome the defect of the dependence on the knowledge of the process and measurement noise statistics of Kalman filter, neural network is introduced, which has the ability to learn from examples and extract the statistical properties of the examples during the training sessions. The fusion system mainly consists of Kalman filters, ANFIS sensor confidence estimators (ASCEs) based on contextual information (CI) theory, knowledge base (KB) and track-to-track fusion algorithms. Experimental data are implemented to train ASCEs to obtain sensor confidence degree. Simulation results show that the algorithm can effectively adjust the system to adapt contextual changes and has strong fusion capability in resisting uncertain information.
A dynamic cloud masking and filtering algorithm for MSG retrieval of land surface temperature
Authors: F. Baroncini, F. Castelli, F. Caparrini, S. Ruffo
Venue: International Journal of Remote Sensing (2008)

A dynamic cloud masking and filtering algorithm is proposed for the Land Surface Temperature (LST) retrieval from infrared imagery of geostationary satellites. The algorithm uses a modified Kalman Filter (KF) to separate the non-Gaussian error due to clouds from the reference cloud-free LST retrieval error, in order to discriminate and possibly correct for different levels of cloud contamination. This approach was intended to make better use of the important features of the new generation of geostationary satellites, such as the Meteosat Second Generation (MSG) satellites, including their high sampling frequency and the extensive real-time availability of images. The reference surface energy balance model on which the KF is based was simplified to the extent that no information other than top-of-atmosphere solar radiation was required to force the system together with LST measurements. The overall accuracy of the new algorithm, named Cloud Masking with Kalman Filter (CMKF), was tested on the LST retrievals over the Italian peninsula for a 15-day summer period from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the MSG satellite. As a verification dataset, analogous retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used. The higher spatial resolution of the MODIS LST maps and accompanying cloud masks also allowed us to analyse the results in terms of different levels of fractional cloud cover. The results of these first verification experiments show that the application of the proposed dynamic algorithm improves the LST retrieval, with respect to cloud masking with a classical static algorithm, in two different ways: first, there is a more consistent identification of cloud-free LST data; and second, and more importantly, there is a substantial increase in the quantity of final LST estimates, up to four times more in very cloudy conditions, with the use of prior model predictions at a cost of a very modest increase in the LST root mean squared error (RMSE). Moreover, the higher coefficient of determination in both cases indicates that the algorithm provides LST estimates over a wider range, as it is capable of reconstructing with some accuracy certain lower LST values under cloud cover.
Non-Cooperative Tree Creation
Authors: Martin Hoefer
Venue: Algorithmica (2009)

In this paper we consider the connection game, a simple network design game with independent selfish agents that was introduced by Anshelevich et al. (Proc. 35th Ann. ACM Symp. Theo. Comp. (STOC), pp.&#x00a0;511&#x2013;520, 2003). Our study concerns an important subclass of tree games, in which every feasible network is guaranteed to be connected. It generalizes the class of single-source games considered by Anshelevich et&#x00a0;al. We focus on the existence, quality, and computability of pure-strategy exact and approximate Nash equilibria. For tree connection games, in which every player holds two terminals, we show that there is a Nash equilibrium as cheap as the optimum network. In contrast, for single-source games, in which every player has at most three terminals, the price of stability is at least k&#x2212;2, and it is $\mathsf{NP}$-complete to decide the existence of a Nash equilibrium. Hence, we propose polynomial time algorithms for computing approximate Nash equilibria, which provide relaxed stability and cost efficiency guarantees. For the case of two terminals per player, there is an algorithm to find a (2+&#x03b5;,1.55)-approximate Nash equilibrium. It can be generalized to an algorithm to find a (3.1+&#x03b5;,1.55)-approximate Nash equilibrium for general tree connection games. This improves the guarantee of the only previous algorithm for the problem, which returns a (4.65+&#x03b5;,1.55)-approximate Nash equilibrium. Tightness results for the analysis of all algorithms are derived. Our algorithms use a novel iteration technique for trees that might be of independent interest.
Non-smooth SOR for L1-Fitting: Convergence Study and Discussion of Related Issues
Authors: R. Glowinski, T. Kärkkäinen, T. Valkonen, A. Ivannikov
Venue: Journal of Scientific Computing (2008)

In this article, the denoising of smooth (H 1-regular) images is considered. To reach this objective, we introduce a simple and highly efficient over-relaxation technique for solving the convex, non-smooth optimization problems resulting from the denoising formulation. We describe the algorithm, discuss its convergence and present the results of numerical experiments, which validate the methods under consideration with respect to both efficiency and denoising capability. Several issues concerning the convergence of an Uzawa algorithm for the solution of the same problem are also discussed.
Adaptivity and Personalization in Ubiquitous Learning Systems
Authors: Sabine Graf, Kinshuk
Venue: Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work (2008)

Ubiquitous learning is an emerging research field, allowing students to learn anywhere and anytime. Adaptivity and personalization issues play an important role in ubiquitous learning systems, enabling those systems not only to allow learners to learn whenever and wherever they want, but also in a personalized and adaptive way, considering the situation, characteristics, and needs of learners. In this paper, an overview of adaptivity and personalization issues in ubiquitous learning systems is provided and current and future research directions are discussed.
An audio-haptic interface based on auditory depth cues
Authors: Delphine Devallez, Federico Fontana, Davide Rocchesso
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

Spatialization of sound sources in depth allows a hierarchical display of multiple audio streams and therefore may be an efficient tool for developing novel auditory interfaces. In this paper we present an audio-haptic interface for audio browsing based on rendering distance cues for ordering sound sources in depth. The haptic interface includes a linear position tactile sensor made by conductive material. The touch position on the ribbon is mapped onto the listening position on a rectangular virtual membrane, modeled by a bidimensional Digital Waveguide Mesh and providing distance cues of four equally spaced sound sources. Furthermore a knob of a MIDI controller controls the position of the mesh along the playlist, which allows to browse the whole set of files. Subjects involved in a user study found the interface intuitive and entertaining. In particular the interaction with the stripe was highly appreciated.
Randomness Preserving Deletions on Special Binary Search Trees
Authors: Michaela Heyer
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Deletions in binary search trees are difficult to analyse as they are not randomness preserving. We will present a new kind of tree which differs slightly from the standard binary search tree. It will be referred to as an ordered binary search tree as it stores a history element in its nodes, which provides information about the order in which the nodes were inserted. Using this extra information it is possible to design a new randomness preserving and order preserving deletion algorithm.
Three scenarios on enhancing learning by providing universal access
Authors: Renate Motschnig-Pitrik, Michael Derntl
Venue: Universal Access in the Information Society (2008)

This paper presents three simple and effective technology-enhanced learning scenarios, specifically reaction sheets, cooperative writing, and self evaluation. These scenarios address universal access by providing web-based support and services with a potential for enhancing the learners&#x2019; capacity of gaining access to both personal and technical resources. While the web as an open space tends to support experiential learning, its enhancement as a service to address the learners&#x2019; intellect, social skills, and attitudes substantially depends on constructive interpersonal relationships and thoughtfully designed learning scenarios. The tree proposed scenarios aim to address these interpersonal and technology-related issues. A uniform description template is used for each scenario, including intent, motivation, conceptual model, and research context. This is complemented by reports on the authors&#x2019; experiences with applying the scenarios in recent years and by qualitative and quantitative results from multiple action research cycles.
PoooL
Authors: Han Zhang, Hsin-Chou Yang, Yaning Yang
Venue: Bioinformatics (2008)

Motivation: Pooling DNA is a cost-effective alternative to individual genotyping method. It is often used for initial screening in genome-wide association analysis. In some studies, large pools with sizes up to several hundreds were applied in order to significantly reduce genotyping cost. However, method for estimating haplotype frequencies from large DNA pools has not been available due to computational complexity involved. Methods: We propose a novel constrained EM algorithm, PoooL, to estimate frequencies of single-nucleotide polymorphism (SNP) haplotypes from DNA pools. A quantity called importance factor is introduced to measure the contribution of a haplotype to the likelihood. Under the assumption of asymptotic normality of the estimated allele frequencies and a system of linear constraints on haplotype frequencies the importance factor remains a constant in the iterative maximization process. The maximization problem in the EM algorithm is then formulated into a constrained maximum entropy model and solved by the improved iterative scaling method. Results: Simulation study shows that our algorithm can efficiently estimate haplotype frequencies from DNA pools with arbitrarily large sizes. The algorithm works equally well for large pools with sizes up to hundreds or thousands and for pools with sizes as small as one or two individuals. The computational complexity of the PoooL algorithm is independent of pool sizes, and the computational efficiency for large pools is thus substantially improved over existing estimating methods. Simulation results also show that the proposed method is robust to genotype errors and population admixture. Availability: http://staff.ustc.edu.cn/~ynyang/poool Contact:zhanghan@mail.ustc.edu.cn; ynyang@ustc.edu.cn