ppxscal/embedding_network huggingface dataset:
Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
Venue: North American Chapter Of The Association For Computational Linguistics (2007)

In the recent years, we have seen rapid adoption of dialog systems in commercial applications. They range from telephone-based services, in-car interactive systems, to online conversational service agents and talking characters in computer games. Openstandard platforms such as VoiceXML have been adopted by the industry, and become the driving force for the faster adoption of dialog applications. The widespread dialog applications in industry setting pose challenge for researchers in both industrial and academic worlds. Progress from academic world has not benefited the real world applications to a satisfactory extent. The purpose of this one-day workshop is to provide a forum to bring industrial and academic researchers together to share their experiences and visions in the dialog technology development, and to identify topics that are of interest to both camps. There are total 13 papers accepted for presentation at this workshop, with 8 papers for long presentation and 5 for short presentation. These papers are almost evenly divided between the industry and academic communities. In addition, two panels on the related dialog topics have been arranged during the workshop, with distinguished panelists of various backgrounds from academic, industrial, and standardization communities.
Frontal-view gait recognition by intra- and inter-frame rectangle size distribution
Authors: Olivier Barnich, Marc Van Droogenbroeck
Venue: Pattern Recognition Letters (2009)

Current trends seem to accredit gait as a sensible biometric feature for human identification, at least in a multimodal system. In addition to being a robust feature, gait is hard to fake and requires no cooperation from the user. As in many video systems, the recognition confidence relies on the angle of view of the camera and on the illumination conditions, inducing a sensitivity to operational conditions that one may wish to lower. In this paper we present an efficient approach capable of recognizing people in frontal-view video sequences. The approach uses an intra-frame description of silhouettes which consists of a set of rectangles that will fit into any closed silhouette. A dynamic, inter-frame, dimension is then added by aggregating the size distributions of these rectangles over multiple successive frames. For each new frame, the inter-frame gait signature is updated and used to estimate the identity of the person detected in the scene. Finally, in order to smooth the decision on the identity, a majority vote is applied to previous results. In the final part of this article, we provide experimental results and discuss the accuracy of the classification for our own database of 21 known persons, and for a public database of 25 persons.
Decision with uncertainties, feasibilities, and utilities: towards a unified algebraic framework
Authors: Cédric Pralet, Gérard Verfaillie, Thomas Schiex
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

Several formalisms exist to express and solve decision problems. Each is designed to capture different kinds of knowledge: utilities expressing preferences, uncertainties on the environment, or feasibility constraints on the decisions, with a possible sequential aspect. Despite the fact that every framework relies on specific properties exploited by dedicated algorithms, these formalisms present interesting similarities. In this paper, we show that it is possible to capture these similarities in a generic algebraic framework for sequential decision making with uncertainties, feasibilities, and utilities. This framework subsumes several existing approaches, from constraint satisfaction problems to quantified boolean formulas, Bayesian networks or possibilistic Markov decision processes. We introduce this framework using a toy example, increasingly sophisticated by uncertainties, feasibilities and possible observations. This leads to a formal definition of the framework together with dedicated queries representing usual decision problems. Generic algorithms for solving the considered queries should allow to both factorize existing algorithmic works and allow for cross-fertilization between the subsumed formalisms.
Self-tuning BPEL processes
Authors: Adina D. Mosincat, Walter Binder
Venue: Proceedings of the 6th international conference on Autonomic computing (2009)

The performance of BPEL processes depends on the composing web services. Monitoring web service performance and adapting to changes in service performance are essential for creating self-tuning BPEL processes. Unfortunately, BPEL supports neither performance monitoring nor dynamic adaptation mechanisms. In this paper, we present a monitoring and rebinding infrastructure for BPEL that transparently enhances existing BPEL processes with self-tuning behavior.
Cross network and layer approach for video transmission over the future internet
Authors: GyeongCheol Lee, Sangchun Han, Hwangjun Song
Venue: Proceedings of the 4th International Conference on Future Internet Technologies (2009)

In this paper, we present the integrated video transmission system that is suitable for future internet environment. The goal of the proposed system is to provide a stable video streaming service over heterogeneous networks. First, we investigate what is the important aspect to supporting end-to-end QoS. Second, we propose an effective integrated video transmission system that combines cross network and layer approach to satisfy end-to-end QoS in order to enhance video quality. Finally, the proposed system will be implemented in software and tested in real environments.
The good, the bad, and the unknown: morphosyllabic sentiment tagging of unseen words
Authors: Karo Moilanen, Stephen Pulman
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

The omnipresence of unknown words is a problem that any NLP component needs to address in some form. While there exist many established techniques for dealing with unknown words in the realm of POS-tagging, for example, guessing unknown words' semantic properties is a less-explored area with greater challenges. In this paper, we study the semantic field of sentiment and propose five methods for assigning prior sentiment polarities to unknown words based on known sentiment carriers. Tested on 2000 cases, the methods mirror human judgements closely in three- and two-way polarity classification tasks, and reach accuracies above 63% and 81%, respectively.
Semantic graphics for more effective visual communication
Authors: Vidya Setlur
Venue: Proceedings of Graphics Interface 2009 (2009)

Computers are becoming faster, smaller and more interconnected, creating a shift in their primary function from computation to communication. This trend is exemplified by ubiquitous devices such as mobile phones with cameras, personal digital assistants with video, and information displays in automobiles. As communication devices and viewing situations become more plentiful, we need imagery that facilitates visual communication across a wide range of display devices. In addition, producing effective and expressive visual content currently requires considerable artistic skill and can consume days. There is a growing need to develop new techniques and user interfaces that enhance visual communication, while making it fast and easy to generate compelling content. New algorithms in semantic graphics, i.e. combining concepts and methods from visual art, perceptual psychology, information processing, and cognitive science, help facilitate users in creating, understanding and interpreting computer imagery. In this talk, Vidya Setlur will present the usage of semantic graphics for various information visualization goals.
Software self-reconfiguration: a BDI-based approach
Authors: Fabiano Dalpiaz, Paolo Giorgini, John Mylopoulos
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Software self-reconfiguration is the capability of software systems to change autonomously their current configuration to a better one. This is a more and more requested feature, particularly for software systems that operate in critical domains when human intervention is not possible or not convenient. The Belief-Desire-Intention (BDI) architecture proposes a structured Monitor-Diagnose-Compensate cycle that partially meets self-reconfiguration requirements. We propose a realization of the abstract BDI control loop and we draw generic solutions to support the self-reconfiguration process. We aim at supporting traceability and runtime monitoring of requirements and we base our solution on Tropos goal models to structure agents' internal state.
How to organize continuing studies at an academic institution?
Authors: Lech Banachowski, Jerzy Paweł Nowacki
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

The aim of this paper is to explore possibilities of using resources of institutions of higher education to support processes of life-long learning of its students, graduates and academic teachers. In the first part we will analyze needs and possibilities of organizing continuing studies. In the second part we will describe the features to be added to a standard LMS system in order to achieve a system supporting continuous, lifelong learning. Our examples refer to the studies in Information Technology at PJIIT and to the LMS system called Edu supporting them.
Toward a multi-agent model for the care of patients at the emergency department
Authors: Amani Daknou, Hayfa Zgaya, Slim Hammadi, Herve Hubert
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Though multi-agent systems have been explored in a wide variety of medical settings, their role at the emergency department care level has been relatively little investigated. In this paper, we propose a tool to assist decision-making process for the care of patients at the emergency department. This tool aims to improve the quality of care within the emergency departments with rapid access to pertinent data, integration of care's protocols and assures knowledge of the quantity and the quality of medical activity. This multi-agent model was adopted to define the behavior of entities by distributing data and tasks in an attempt to explain and predict events in the emergency department. The agents of our model acts as a collaborative team of specialists.
High performance network i/o in virtual machines over modern interconnects
Authors: D. K. Panda
Venue:  (2008)

With the increasing size and complexity of modern computing systems, a balance between performance and manageability is becoming critical to achieve high performance as well as high productivity computing. Virtual Machine (VM) technology provides various features that help management issues on large-scale computing systems; however, performance concerns have largely blocked the deployment of VM-based computing, especially in the High-Performance Computing (HPC) area. This dissertation aims at reducing the virtualization overhead and achieving the co-existence of performance and manageability through VM technologies. We focus on I/O virtualization, designing an experimental VM-based computing framework, and addressing performance issues at different levels of the system software stack. We design VMM-bypass I/O, which achieves native I/O performance in VMs by taking advantage of the OS-bypass interconnects. Also with the OS-bypass interconnects, we propose high performance VM migration with Remote Direct Memory Access (RDMA), which drastically reduces the VM management cost. To further improve the communication efficiency on multi-core systems, we design Inter-VM Communication (IVC), a VM-aware communication library to allow efficient shared memory communication among VMs on the same physical host. Finally, we design MVAPICH2-ivc, an MPI library that is aware of VM-based environments and can transparently benefit HPC applications with our proposed designs. The dissertation concludes that performance should no longer be a barrier to deploying VM-based computing, which enhances productivity by achieving much improved manageability with very little sacrifice in performance.
Research and development of online simulation learning and assessment management system
Authors: Ting-Sheng Weng
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

With the rapid development of information technology, e-learning is an irresistible global trend. In order to instantly understand and supervise learning effects, this study develops learning portfolio provided by digital learning platforms to make evaluations. Then we can manage learning conditions and effects, and further provide individual assistance, reduce achievement difference and increase learners' learning abilities.
Controlled natural languages for interface agents
Authors: Tamás Mészáros, Tadeusz Dobrowiecki
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Interface agents help users to deal with the complexity of today's computer systems. It is commonly required that these agents should employ natural language to communicate with humans. Natural language processing is, however, a complex and difficult task for agent designers. Authors propose a new framework that significantly reduces the complexity of building such interfaces. It relies on the concepts of application-specific controlled natural languages, a guided user interface, and a conceptual model of the interface functions that allows the automatic generation of controlled language.
The Cox--Ingersoll--Ross model with delay and strong convergence of its Euler--Maruyama approximate solutions
Authors: Fuke Wu, Xuerong Mao, Kan Chen
Venue: Applied Numerical Mathematics (2009)

Stochastic delay differential equations (SDDEs) have recently been developed to model various financial quantities. In general, SDDEs have no explicit solution, so numerical methods for approximations have become one of the most powerful techniques in the valuation of financial quantities. In this paper, we will concentrate on the Euler-Maruyama (EM) scheme for Cox-Ingersoll-Ross model with delay, whose diffusion coefficient is nonlinear and non-Lipschitz continuous such that some standard results cannot be appealed. We prove existence of the nonnegative solution and the strong convergence of its EM approximate solution.
Fast winner determination for agent coordination with SBB auctions
Authors: Kenny Daniel, Sven Koenig
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

The runtime of winner determination for each round of a sequential bundle-bid auction (= SBB auction) has recently been shown to be linear in the number of submitted bids, which makes SBB auctions appealing for solving cooperative task-assignment problems. In this paper, we introduce the Shrewd (= SHrewd Resource Efficient Winner Determination) algorithm, whose runtime is linear in the number of submitted bids but typically much smaller than the runtime of the existing winner-determination algorithm for SBB auctions, making them feasible for larger bundle sizes.
Representing, Querying and Transforming Social Networks with RDF/SPARQL
Authors: Mauro San Martín, Claudio Gutierrez
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

As social networks are becoming ubiquitous on the Web, the Semantic Web goals indicate that it is critical to have a standard model allowing exchange, interoperability, transformation, and querying of social network data.In this paper we show that RDF/SPARQL meet this desiderata. Building on developments of social network analysis, graph databases and Semantic Web, we present a social networks data model based on RDF, and a query and transformation language based on SPARQL meeting the above requirements. We study its expressive power and complexity showing that it behaves well, and present an illustrative prototype.
Using web information for author name disambiguation
Authors: Denilson Alves Pereira, Berthier Ribeiro-Neto, Nivio Ziviani, Alberto H.F. Laender, Marcos André Gonçalves, Anderson A. Ferreira
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

In digital libraries, ambiguous author names may occur due to the existence of multiple authors with the same name (polysemes) or different name variations for the same author (synonyms). We proposed here a new method that uses information available on the Web to deal with both problems at the same time. Our idea consists of gathering information from input citations and submitting queries to a Web search engine, aiming at finding curricula vitae and Web pages containing publications of the ambiguous authors. From the content of documents in the answer sets returned by the Web search engine, useful information that can help in the disambiguation process is extracted. Using this information, author names are disambiguated by leveraging a hierarchical clustering method that groups citations in the same document together in a bottom-up fashion. Experimental results show that the our method yields results that outperform those of two state-of-the-art unsupervised methods and are statistically comparable with those of a supervised one, but requiring no training. We observe gains of up to 65.2% in the pairwise F1 metric when compared with our best unsupervised baseline method.
MANET management: Industry challenges & potential solutions
Authors: Latha Kant, Ritu Chadha
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Characterized by their flexibility to be deployed in relatively short time spans and ability to function in remote and hostile environments, mobile ad hoc networks (MANETs) are becoming the basis for on-demand peer-to-peer wireless networking in the commercial and military sectors. However, the power and dynamism of MANETs renders their management a significant challenge. For example, unpredictable link qualities render quality of service assurance to the mission critical/platinum services very challenging. Likewise, lack of fixed infrastructure coupled with intermittent connectivity place a significant burden on network management systems that are expected to provide seamless recovery amidst random network failures. Additionally, the network management operations in MANETs need to be automated to a large extent. This paper discusses the challenges associated with two key MANET aspects of interest to the Industry: (a) providing and maintaining QoS guarantees and (b) fault management and self-healing in MANETs, and discusses potential solutions that can be implemented in practice.
David Busch's Quick Snap Guide to Using Digital SLR Lenses, 1st edition
Authors: David D. Busch
Venue:  (2007)

Are you ready to go beyond the basics with your digital SLR camera but are unsure which interchangeable lens or two to buy and more importantly, how and when to use each lens? "David Buschs Quick Snap Guide to Using Digital SLR Lenses" offers focused, concise information and techniques on how to use different lenses to take great photographs. Youll begin with a quick overview of how lenses work and the types of lenses available, including normal, telephoto, wide-angle, prime, and zoom. Then youll explore typical lens controls and features such as focus rings, depth-of-field scales, and image stabilization, and how particular settings can help improve your photography. Once you have the basics down youll learn how to create cool effects using lens filters and accessories, and how to select the best lens aperture for particular types of photos. Finally, youll go in-depth with telephoto, wide-angle, and macro lenses. Each topic or concept is explained using a clear, two- or fourpage spread, and beautiful, full-color images illustrate the results of photographing with each setting, technique, or lens. A mini-glossary will help you define unfamiliar terms as you go. Get ready to enhance your photographs using the versatility of interchangeable lenses on your digital SLR! 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
Utilization of virtual samples to facilitate cancer identification for DNA microarray data in the early stages of an investigation
Authors: Der-Chiang Li, Yao-Hwei Fang, Yung-Yao Lai, Susan C. Hu
Venue: Information Sciences: an International Journal (2009)

DNA microarray datasets are generally small in size, high dimensional with many non-discriminative genes, and non-linear with outliers. Their size/dimension ratio suggests that DNA microarray datasets are identified as small-sample problems. Recently, researchers have developed various gene selection algorithms to discover genes that are most relevant to a specific disease, and thus to reduce computation. Most gene selection algorithms improve learning performance and efficiency, but still suffer from the limitation of insufficient training samples in the datasets. Moreover, in the early stage of diagnosing a new disease, very limited data can be obtained. Therefore, the derived diagnostic model is usually unreliable to identify the new disease. Consequently, the diagnostic performance cannot always be robust, even with the gene selection algorithms. To solve the problem of very limited training dataset with non-linear data or outliers, we propose the method GVSG (Group Virtual Sample Generation), which is a non-linear Virtual Sample Generation algorithm. This non-linear method detects the characteristics in the very limited data, forms discrete groups of each discriminative gene, and systematically generates virtual samples for each of these to accelerate and stabilize the modeling process. The results show that this method significantly improves the learning accuracy in the early stage of DNA microarray data.