ppxscal/embedding_network huggingface dataset:
RFID Painting Demonstration
Authors: Olivier Haberman, Romain Pellerin, Eric Gressier-Soudan, Ugo Haberman
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

This demonstration challenges the conventional art experience. It brings together the fields of art, science, and software integration. The goal was to create a new kind of painting based on embedded technology, experimenting with a new media: paintings augmented with RFIDs. The aim was to achieve interaction between the artist's paintings and art gallery visitors.
Credit Risk Handling in Telecommunication Sector
Authors: Monika Szczerba, Andrzej Ciemski
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

This article presents an application of data mining methods in telecommunication sector. This sector becomes a new area of research for particular problem solving e.g. churn prediction, cross-up selling marketing campaigns, fraud detection, customer segmentation and profiling, data classification, association rules discovery, data clustering, parameter importance analysis etc. Credit risk prediction became a new research domain in pattern recognition area aimed to find the most risky customers. This article is devoted to assessing credit risk from the moment of opening a customer account to the moment of closing an account due to non-payment. Algorithms are used to identify and insolvency of a debtor. Credit scoring is presented in a form of activation models, which are used to predict customers' debt as well as indicate clients with the highest, medium and smallest credit risk. Practical part of the article is based on the real customer database in a telecommunication company.
Weighted automata and weighted logics with discounting
Authors: Manfred Droste, George Rahonis
Venue: Theoretical Computer Science (2009)

We introduce a weighted logic with discounting and we establish the Buchi-Elgot theorem for weighted automata over finite words and arbitrary commutative semirings. Then we investigate Buchi and Muller automata with discounting over the max-plus and the min-plus semiring. We show their expressive equivalence with weighted MSO-sentences with discounting. In this case our logic has a purely syntactic definition. For the finite case, we obtain a purely syntactically defined weighted logic if the underlying semiring is additively locally finite.
SVM Based Decision Analysis and Its Granular-Based Solving
Authors: Tian Yang, Xinjie Lu, Zaifei Liao, Wei Liu, Hongan Wang
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

This paper proposes an approach to decision analysis for complex industrial process without enough knowledge of input-output model, which is based on the two-class SVM method. It first proposes a SVM Based Decision Analysis Model to improve the accuracy of determinant of whether a decision is acceptable/ unacceptable by verifying the `soft margin' of a SVM. This makes it only allow misclassification of only one class in a two-class classification. Then a granular-based approach is presented to solving this model. It is proved that this granular approach can reach an upper bound of the original SVM model. An algorithm then is presented to determine whether a decision is acceptable. According to our analysis and experiments, the two types of SVM have better accuracy on judging its target class then traditional SVM, and the granular-based SVM solving can reduce the running time.
Protecting intellectual property and sensitive information in academic campuses from trusted insiders: leveraging active directory
Authors: Dattatraya S. Bhilare, Ashwini K. Ramani, Sanjay K. Tanwani
Venue: Proceedings of the ACM SIGUCCS fall conference on User services conference (2009)

Insider threat has been the major Information Security issue for business houses for long time. But, Information Security Managers of academic campuses are yet to pay similar attention to this challenge. As direct financial losses resulting due to this are not of similar magnitude. However, universities and colleges have sensitive academic and personal records. Also, many institutes are engaged in advanced research and creating valuable intellectual property, which need to be protected. Monitoring insider threats in academic campuses is particularly difficult because of complexity of networks, diverse mix of systems and resistance for strict restrictions. Major challenges include, less disciplined users compared to industry users, sharing of terminals, inadequate budgets and fast turnover of student population. There are almost thirty percent new enrollments every year. Existing monitoring and control methods are inadequate for two reasons: they are able to trace source IP addresses but fail to identify the precise user, performing suspicious or non-sanctioned activities. Secondly, they do not provide real-time actions, as user profile is not known. Given these security challenges and the complexity of protecting information assets across diverse servers, applications, and heterogeneous environment, a new approach is proposed. Identity issue is addressed by capturing detailed network user actions across most major applications and correlating it with directory context to track and enforce institutional policies. This is different from existing approaches, where a traffic oriented view of user activity is provided. The proposed approach provides a low cost and quickly deployable solution as no network changes are required. Proposed real-time tracking and alerting mechanism ensures early warning and also proactively stops transactions in progress without degrading performance. It also facilitates audit automation using rule engine, which is constantly updated by an Intelligent Rule Builder.
Compression of Probabilistic XML Documents
Authors: Irma Veldman, Ander Keijzer, Maurice Keulen
Venue: Proceedings of the 3rd International Conference on Scalable Uncertainty Management (2009)

Database techniques to store, query and manipulate data that contains uncertainty receives increasing research interest. Such UDBMSs can be classified according to their underlying data model: relational, XML, or RDF. We focus on uncertain XML DBMS with as representative example the Probabilistic XML model (PXML) of [10,9]. The size of a PXML document is obviously a factor in performance. There are PXML-specific techniques to reduce the size, such as a push down mechanism, that produces equivalent but more compact PXML documents. It can only be applied, however, where possibilities are dependent. For normal XML documents there also exist several techniques for compressing a document. Since Probabilistic XML is (a special form of) normal XML, it might benefit from these methods even more. In this paper, we show that existing compression mechanisms can be combined with PXML-specific compression techniques. We also show that best compression rates are obtained with a combination of PXML-specific technique with a rather simple generic DAG-compression technique.
Rapidly deploying grammar-based speech applications with active learning and back-off grammars
Authors: Tim Paek, Sudeep Gandhe, David Maxwel Chickering
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

Grammar-based approaches to spoken language understanding are utilized to a great extent in industry, particularly when developers are confronted with data sparsity. In order to ensure wide grammar coverage, developers typically modify their grammars in an iterative process of deploying the application, collecting and transcribing user utterances, and adjusting the grammar. In this paper, we explore enhancing this iterative process by leveraging active learning with back-off grammars. Because the back-off grammars expand coverage of user utterances, developers have a safety net for deploying applications earlier. Furthermore, the statistics related to the back-off can be used for active learning, thus reducing the effort and cost of data transcription. In experiments conducted on a commercially deployed application, the approach achieved levels of semantic accuracy comparable to transcribing all failed utterances with 87% less transcriptions.
Dominating Induced Matchings
Authors: Domingos M. Cardoso, Vadim V. Lozin
Venue: Graph Theory, Computational Intelligence and Thought: Essays Dedicated to Martin Charles Golumbic on the Occasion of His 60th Birthday (2009)

We study the problem of determining whether or not a graph G has an induced matching that dominates every edge of the graph, which is also known as efficient edge domination. This problem is known to be NP-complete in general as well as in some restricted domains, such as bipartite graphs or regular graphs. In this paper, we identify a graph parameter to which the complexity of the problem is sensible and produce results of both negative (intractable) and positive (solvable in polynomial time) type.
An Embrace-and-Extend Approach to Managing the Complexity of Future Heterogeneous Systems
Authors: Rainer Buchty, Mario Kicherer, David Kramer, Wolfgang Karl
Venue: Proceedings of the 9th International Workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2009)

In this paper, we present a particularly lightweight, integrative approach to programming and executing applications targeting heterogeneous, dynamically reconfigurable parallel systems. Based on an analysis of existing approaches, we strictly focused on compatibility and lightweightedness. Our approach therefore follows an embrace-and-extend strategy and achieves desired functionality by adopting and augmenting existing system services, achieving the desired properties. We implemented this concept using the Linux OS and demonstrated its suitability with a heterogeneous platform comprising IA32 multicore processors and current FPGA accelerator hardware using state-of-the-art HyperTransport interconnection technology.
Translating names and technical terms in Arabic text
Authors: Bonnie Glover Stalls, Kevin Knight
Venue: Proceedings of the Workshop on Computational Approaches to Semitic Languages (1998)

It is challenging to translate names and technical terms from English into Arabic. Translation is usually done phonetically: different alphabets and sound inventories force various compromises. For example, Peter Streams may come out as [Abstract contained text which could not be captured.] bytr strymz. This process is called transliteration. We address here the reverse problem: given a foreign name or loanword in Arabic text, we want to recover the original in Roman script. For example, an input like [Abstract contained text which could not be captured.] bytr strymz should yield an output like Peter Streams. Arabic presents special challenges due to unwritten vowels and phonetic-context effects. We present results and examples of use in an Arabic-to-English machine translator.
Crawling and Extracting Process Data from the Web
Authors: Yaling Liu, Arvin Agah
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

In this paper, we address the design and implementation of a supporting system for process-based searches. This supporting system can efficiently crawl the Web and extract processes from obtained data. The retrieved processes can then be used in a Process-Based Search Engine (PBSE). In this work, a process is defined as a sequence of activities for achieving a goal. A PBSE uses the extracted processes to transform an original query into multiple sub-queries, and then performs keyword search for each transformed sub-query. To facilitate effective process-based searches, a large number of high quality processes are required. This paper focuses on how to efficiently and effectively build a database of processes by exploring the Web.
What Properties Make Scenarios Useful in Design for Usability?
Authors: Kentaro Go
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

As described herein, we propose heuristics of scenario for designing usable products. From a structural viewpoint, a similarity exists between the definition of usability in ISO 9241-11 and the concept of scenario for designing a product, which suggests what elements a scenario should include and how designers should incorporate it into a human-centered design process. Particularly, this paper presents the argument that a scenario should include what a user accomplishes, sees, hears, and thinks, and how the user does them so that designers become capable of evaluating the effectiveness, efficiency, and satisfaction of goal achievement from a usability perspective.
A Semi-automated Method for the Measurement of the Fetal Nuchal Translucency in Ultrasound Images
Authors: Ezio Catanzariti, Giovanni Fusco, Francesco Isgrò, Salvatore Masecchia, Roberto Prevete, Matteo Santoro
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Nowadays the measurement of the nuchal translucency thickness is being used as part of routine ultrasound scanning during the end of the first trimester of pregnancy, for the screening of chromosomal defects, as trisomy 21. Currently, the measurement is being performed manually by physicians. The measurement can take a long time for being accomplished, needs to be performed by highly skilled operators, and is prone to errors. In this paper we present an algorithm that automatically detects the border of the nuchal translucency, once a region of interest has been manually identified. The algorithm is based on the minimisation of a cost function, and the optimisation is performed using the dynamic programming paradigm. The method we present overcomes several of the drawbacks present in the state of the art algorithms.
Rapid Texture-based Volume Rendering
Authors: Chen Shihao, He Guiqing, Hao Chongyang
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Nowadays, man can get a great number of 3D data sets from different sources is common in medical diagnosis but how to explore the information contents of these data sets is still a problem. One effective method is with computer aid rendering the volume. As the 3D datasets are usually in large scalar, the capability of a single CPU to rendering is not sufficient to achieve interactivity. Direct volume rendering via 3D textures has positioned itself as an efficient tool for the display and visual analysis of volumetric scalar fields. In this paper a rapid texture based volume visualization method is proposed. The method exploits hardware-assisted texture mapping, re-samples volume data, represented as a stack of 3D texture, onto a sampling surface or so called proxy geometry. For each Texel of a slice it perform a fetch to the 3D texture and performs fusion and shading using a fragment shadier. In order to speed up the rendering, the integration of acceleration techniques to reduce per-fragment operations for texture based volume rendering also will be addressed. At last we demonstrate the effectiveness of our method with several data sets on the GeForce 8800 GTX graphics card. It proved that the proposed method can generate high-quality visual representations of the 3D data sets at interactive rates.
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Authors: Samantha Ng, Adel Fakih, Adam Fourney, Pascal Poupart, John Zelek
Venue: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision (2009)

Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the majority of current markerless vision systems focus on estimating 2D and 3D walking motion in the sagittal plane, we wish to estimate the 3D pose of rollator users' lower limbs from observing image sequences in the coronal (frontal) plane. Our apparatus poses a unique set of challenges: a single monocular view of only the lower limbs and a frontal perspective of the rollator user. Since motion in the coronal plane is relatively subtle, we explore multiple cues within a Bayesian probabilistic framework to formulate a posterior estimate for a given subject's leg limbs. This paper describes four cues based on three features to formulate a pose estimate: image gradients, colour and anthropometric symmetry. Our appearance model is applied within a non-parametric (particle) filtering system to track the lower limbs. Our tracking system does not rely on any detection for automatic initialization. Preliminary experiments are promising, showing that the algorithm may provide an indication of relative depth for each lower limb.
Sensor selection for active information fusion
Authors: Yongmian Zhang, Qiang Ji
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Active information fusion is to selectively choose the sensors so that the information gain can compensate the cost spent in information gathering. However, determining the most informative and cost-effective sensors requires an evaluation of all possible sensor combinations, which is computationally intractable, particularly, when information-theoretic criterion is used. This paper presents a methodology to actively select a sensor subset with the best tradeoff between information gain and sensor cost by exploiting the synergy among sensors. Our approach includes two aspects: a method for efficient mutual information computation and a graph-theoretic approach to reduce search space. The approach can reduce the time complexity significantly in searching for a near optimal sensor subset.
Blind Maximum-Likelihood Estimation of Traffic Matrices in Long Range Dependent Traffic
Authors: Pier Luigi Conti, Livia Giovanni, Maurizio Naldi
Venue: Traffic Management and Traffic Engineering for the Future Internet: First Euro-NF Workshop, FITraMEn 2008, Porto, Portugal, December 11-12, Revised Selected Papers (2009)

A method is proposed to estimate traffic matrices in the presence of long-range dependent traffic, while the methods proposed so far for that task have been designed for short-range dependent traffic. The method employs the traffic measurements on links and provides the maximum likelihood estimate of both the traffic matrix and the Hurst parameter. It is "blind", i.e. it does not exploit any model neither for the traffic intensity values (e.g. the gravity model) nor for the mean-variance relationship (e.g. the power-law model). In the application to a sample network the error on traffic intensities decays rapidly with the traffic intensity down to below 30%. The estimation error of the Hurst parameter can be reduced to a few percentage points with a proper choice of the measurement interval. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Style & topic language model adaptation using HMM-LDA
Authors: Bo-June (Paul) Hsu, James Glass
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

Adapting language models across styles and topics, such as for lecture transcription, involves combining generic style models with topic-specific content relevant to the target document. In this work, we investigate the use of the Hidden Markov Model with Latent Dirichlet Allocation (HMM-LDA) to obtain syntactic state and semantic topic assignments to word instances in the training corpus. From these context-dependent labels, we construct style and topic models that better model the target document, and extend the traditional bag-of-words topic models to n-grams. Experiments with static model interpolation yielded a perplexity and relative word error rate (WER) reduction of 7.1% and 2.1%, respectively, over an adapted trigram baseline. Adaptive interpolation of mixture components further reduced perplexity by 9.5% and WER by a modest 0.3%.
Piecewise linear dynamic programming for constrained POMDPs
Authors: Joshua D. Isom, Sean P. Meyn, Richard D. Braatz
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

We describe an exact dynamic programming update for constrained partially observable Markov decision processes (CPOMDPs). State-of-the-art exact solution of unconstrained POMDPs relies on implicit enumeration of the vectors in the piecewise linear value function, and pruning operations to obtain a minimal representation of the updated value function. In dynamic programming for CPOMDPs, each vector takes two valuations, one with respect to the objective function and another with respect to the constraint function. The dynamic programming update consists of finding, for each belief state, the vector that has the best objective function valuation while still satisfying the constraint function. Whereas the pruning operation in an unconstrained POMDP requires solution of a linear program, the pruning operation for CPOMDPs requires solution of a mixed integer linear program.
Genre classification of web documents
Authors: Elizabeth Sugar Boese, Adele Howe
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

Retrieving relevant documents over the Web is an overwhelming task when search engines return thousands of Web documents. Sifting through these documents is time-consuming and sometimes leads to an unsuccessful search. One problem is that most search engines rely on matching a query to documents based solely on topical keywords. However, many users of search engines have a particular genre in mind for the desired documents. The genre of a document concerns aspects of the document such as the style or readability, presentation layout, and meta-content such as words in the title or the existence of graphs or photos. By including genre in Web searches, we hypothesize that Web document retrieval could greatly improve accuracy by better matching documents to the user's information needs. Before implementing a search engine capable of discriminating on both genre and topic, a feasibility analysis of genre classification is needed. Our previous research achieved 91% classification accuracy across ten genres, whereas similar research range between 60 and 85% accuracy. However, the ten genres used in our research were mostly distinct and only exemplar Web documents (consisting of only one genre) were chosen. This paper discusses our current work which involves an in-depth analysis of maintaining high accuracy rates among genres that are very similar.
A Negotiation Framework for Service-Oriented Product Line Development
Authors: Jaejoon Lee, Gerald Kotonya, Daniel Robinson
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

Software product line engineering offers developers a low-cost means to rapidly create diverse systems that share core assets. By modeling and managing variability developers can create reconfigurable software product families that can be specialised at design- or deployment-time. Service-orientation offers us an opportunity to extend this flexibility by creating dynamic product-lines. However, integrating service-orientation in product line engineering poses a number of challenges. These include difficulty in i) ensuring product specific service compositions with the right service quality levels at runtime, ii) maintaining system integrity with the dynamically composed services, and iii) evaluating actual service quality level and reflecting this information for future service selections. In this paper, we propose a negotiation framework that alleviates these difficulties by providing a means of achieving the dynamic flexibility of service-oriented systems, while ensuring the user-specific product needs can be also satisfied.