ppxscal/embedding_network huggingface dataset:
Evaluation of Novice and Expert Interpersonal Interaction Skills with a Virtual Patient
Authors: Patrick G. Kenny, Thomas D. Parsons, Jonathan Gratch, Albert A. Rizzo
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

Interactive Virtual Standardized Patients (VP) can provide meaningful training for clinicians. These VP's portray interactive embodied conversational characters with realistic representations of a mental or physical problem to be diagnosed or discussed. This research is a continuation of evaluating of our VP "Justina" [2] which suffers from Posttraumatic Stress Disorder (PTSD) from a sexual attack and presents the results of comparing novices, test subjects without medical training, and experts interacting with `Justina' to find out if they could elicit the proper responses to make a diagnosis and to investigate the topics and questions the novices asked for coverage of the categories and criteria of PTSD as defined in the DSM-IV [1]. It is assumed that novices will perform better than experts, however the main investigation is to gather empirical data and understand why this is true and how this can be used to improve the system. There have not been, to the authors' knowledge, any studies in evaluating experts and non-experts with virtual human characters in the psychological domain.
Pseudo Ridgelet Transform for Image Denoising
Authors: Xin Wang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Wavelet transforms have been successfully used in many scientific fields such as image denoising. Ridgelets is a new system of representations, which deals effectively with line singularities in 2-D. However, the discrete version of the ridgelet transform would result in either redundancy or non-reconstruction. In this paper, a pseudo ridgelet transform is developed to overcome this weakness. Since a moving window-based pyramid is employed, the multiscale filter architecture is obtained. Simplicity and effectiveness make it attractive in image denoising.
Probabilistic modal logic
Authors: Afsaneh Shirazi, Eyal Amir
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

A modal logic is any logic for handling modalities: concepts like possibility, necessity, and knowledge. Artificial intelligence uses modal logics most heavily to represent and reason about knowledge of agents about others' knowledge. This type of reasoning occurs in dialog, collaboration, and competition. In many applications it is also important to be able to reason about the probability of beliefs and events. In this paper we provide a formal system that represents probabilistic knowledge about probabilistic knowledge. We also present exact and approximate algorithms for reasoning about the truth value of queries that are encoded as probabilistic modal logic formulas. We provide an exact algorithm which takes a probabilistic Kripke stntcture and answers probabilistic modal queries in polynomial-time in the size of the model. Then, we introduce an approximate method for applications in which we have very many or infinitely many states. Exact methods are impractical in these applications and we show that our method returns a close estimate efficiently.
Knowledge Management in Distributed Scientific Software Development
Authors: Adel Taweel, Brendan Delaney, Lei Zhao
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

Global multidisciplinary scientific research collaborations are increasingly becoming a necessity to create global solutions. However to attain the potential benefits of such collaborations, there is a critical need for a more efficient management and exchange of knowledge between the distributed teams. Unlike traditional software projects, the knowledge management requirements of such teams is much more complex and requires different types of interaction and knowledge management environments to support such collaboration. In such projects, the need is to capture not just software artefacts, but also the scientific research process and its artefacts and their translation to their respective software needs. This paper discusses the knowledge management needs in distributed scientific projects based on experiences drawn from an international research project. It presents the different types of knowledge in such projects and outlines a mechanism to capture them.
Phototropic memories
Authors: Claudio L. Midolo
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

This paper illustrates the thesis research and process that led me to conceive, design and evaluate the Phototropic Memories device, a novel interface supporting the intimate sharing of personal visual memories over spatial and temporal distance, between two emotionally bound persons.
Optimization Design of Shear Probe for Measurement of Ocean Turbulence
Authors: Lei Gu, Shuxin Wang, Yu Wang, Zilong Wang, Yuhong Liu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Shear probe is a sensor which is used to measure ocean turbulence. Shell and inner structure of shear probe are critical. Shell structure affects liquid field, and inner structure affects sensitivity of shear probe. It is difficult to calculate the interaction between the shell and liquid field. Charge produced by piezoceramics of shear probe is complex to compute. In order to resolve these problems, FLUENT is used to compute liquid field near the shear probe and optimize shell structure, and ANSYS is used to analyze the deformation and charge produced by inner structure. Experiment shows it is an effective way to optimize devise of shear probe.
Tractable induction and classification in first order logic via stochastic matching
Authors: Michele Sebag, Celine Rouveirol
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

Learning in first-order logic (FOL) languages suffers from a specific difficulty: both induction and classification are potentially exponential in the size of hypotheses. This difficulty is usually dealt with by limiting the size of hypotheses, via either syntactic restrictions or search strategies. This paper is concerned with polynomial induction and use of FOL hypotheses with no size restrictions. This is done via stochastic matching: instead of exhaustively exploring the set of matchings between any example and any short candidate hypothesis, one stochastically explores the set of matchings between any example and any candidate hypothesis. The user sets the number of matching samples to consider and thereby controls the cost of induction and classification. One advantage of this heuristic is to allow for resource-bounded learning, without any a priori knowledge about the problem domain. Experiments on a real-world problem pertaining to organic chemistry fully demonstrate the potentialities of the approach regarding both predictive accuracy and computational cost.
Object Scanning Using a Sensor Frame
Authors: Soonmook Jeong, Taehoun Song, Gihoon Go, Keyho Kwon, Jaewook Jeon
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This paper focuses on object scanning using sensors. The objects are articles in daily use. Everyday objects, such as cups, bottles and vessels are good models to scan. The sensor scan represents the objects as 3D images on the computer monitor. Our research proposes a new device to scan real world objects. The device is a square frame, similar to a picture frame, but, except for the frame, is empty. The infrared sensors are arranged on the device frame. These sensors detect the object and extract the coordinates from the detected object. These coordinates are transmitted to the computer and the 3D creation algorithm represents these coordinates as a 3D image. The operating principle is simple, similar to scanning a person at a checkpoint. The user passes the object through the sensor frame to obtain the 3D image, creating the 3D image corresponding to the real object. Thus, the user can easily obtain the 3D object image. This approach uses a low-cost infrared sensor, rather than a high-cost sensor, such as a laser.
Merging argumentation systems
Authors: Sylvie Coste-Marquis, Caroline Devred, Sébastien Konieczny, Marie-Christine Lagasquie-Schiex, Pierre Marquis
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

In this paper, we address the problem of deriving sensible information from a collection of argumentation systems coming from different agents. A general framework for merging argumentation systems from Dung's theory of argumentation is presented. Each argumentation system gives both a set of arguments and the way they interact (i.e. attack or non-attack) according to the corresponding agent. The aim is to define the argument system (or the set of argument systems) that best represents the group. Our framework is general enough to handle the case when agents do not share the same set of arguments. Merging argumentation systems is shown as a valuable approach for defining (sets of) arguments acceptable by the group.
Optimizing user interaction for mobile web browsing
Authors: Dong Zhou, Ajay Chander, Hiroshi Inamura
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

The small form-factor of mobile handsets and the longer, variable latency of cellular networks negatively affect user experience in mobile web related activities. In this paper we describe the design and prototype implementation of a framework for improving mobile web interaction based on monitored interaction history and runtime interaction context. Our framework predicts future interaction sequences and optimizes predicted user interactions with navigation shortcuts and automatic text copying and formfilling
A Transfer Fault Diagnosing Method for Protocol Conformance Test Based on FSMs
Authors: Xinchang Zhang, Wanming Luo, Xiaodong Li, Baoping Yan
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

An efficient fault diagnosis is very helpful to save the time and resource of revising the found faults in the protocol conformance test procedure. However, it is very difficult to diagnose transfer faults accurately and quickly. This paper proposes a test precondition (called input-correct precondition) which is satisfied through the local test in the system development procedure. We further presents a transfer fault diagnosing method based on the finite state machine (FSM), which is applied to diagnose the possible transfer faults in an implementation that satisfies the input-correct precondition. The diagnosing method attempts to provide desirable transfer fault hints or locate some transfer faults accurately in terms of the protocol conformance test results.
LGA Method for 1D Sound Wave Simulation in Inhomogeneous Media
Authors: Valentina Markova
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

The Lattice Gas Automata (LGA) models are based on a microscopic model of physical process and can be considered as an adjunct to the traditional numerical methods to the spatial dynamics simulation. Here we consider two simple LGA models (HPPrp and HPP). They are based on a regular two-dimensional four-neighbors Euclidean lattice. Lattice nodes can be occupied by the moving particles and the moving. In this paper, the possibility of the LGA models to simulate sound wave process in inhomogeneous media formed from two gases (helium and methane) are investigated.
A bubble-stabilized least-squares finite element method for steady MHD duct flow problems at high Hartmann numbers
Authors: Po-Wen Hsieh, Suh-Yuh Yang
Venue: Journal of Computational Physics (2009)

In this paper we devise a stabilized least-squares finite element method using the residual-free bubbles for solving the governing equations of steady magnetohydrodynamic duct flow. We convert the original system of second-order partial differential equations into a first-order system formulation by introducing two additional variables. Then the least-squares finite element method using C^0 linear elements enriched with the residual-free bubble functions for all unknowns is applied to obtain approximations to the first-order system. The most advantageous features of this approach are that the resulting linear system is symmetric and positive definite, and it is capable of resolving high gradients near the layer regions without refining the mesh. Thus, this approach is possible to obtain approximations consistent with the physical configuration of the problem even for high values of the Hartmann number. Before incoorperating the bubble functions into the global problem, we apply the Galerkin least-squares method to approximate the bubble functions that are exact solutions of the corresponding local problems on elements. Therefore, we indeed introduce a two-level finite element method consisting of a mesh for discretization and a submesh for approximating the computations of the residual-free bubble functions. Numerical results confirming theoretical findings are presented for several examples including the Shercliff problem.
A Computation of the Maximal Order Type of the Term Ordering on Finite Multisets
Authors: Andreas Weiermann
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

We give a sharpening of a recent result of Aschenbrenner and Pong about the maximal order type of the term ordering on the finite multisets over a wpo. Moreover we discuss an approach to compute maximal order types of well-partial orders which are related to tree embeddings.
Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Venue: European Chapter Meeting of the ACL (2006)

The papers reproduced here were presented at the poster and demo sessions of EACL-2006 in Trento, April 3--7, 2006. Both sessions contained short papers reporting on late-breaking results (in the case of the poster session) or describing implemented systems (in the case of the demo session). We were pleased to receive a total of 71 submissions, 21 for the demo session and 50 for the poster session. Each submission was reviewed by three members of the program committee. Based on these reviews, we accepted 31 submissions in total, 19 for the poster session and 12 for the demo session.
A model of inductive bias learning
Authors: Jonathan Baxter
Venue: Journal of Artificial Intelligence Research (2000)

A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem being learnt, yet small enough to ensure reliable generalization from reasonably-sized training sets. Typically such bias is supplied by hand through the skill and insights of experts. In this paper a model for automatically learning bias is investigated. The central assumption of the model is that the learner is embedded within an environment of related learning tasks. Within such an environment the learner can sample from multiple tasks, and hence it can search for a hypothesis space that contains good solutions to many of the problems in the environment. Under certain restrictions on the set of all hypothesis spaces available to the learner, we show that a hypothesis space that performs well on a sufficiently large number of training tasks will also perform well when learning novel tasks in the same environment. Explicit bounds are also derived demonstrating that learning multiple tasks within an environment of related tasks can potentially give much better generalization than learning a single task.
A programmable spike-timing based circuit block for reconfigurable neuromorphic computing
Authors: Thomas Jacob Koickal, Luiz C. Gouveia, Alister Hamilton
Venue: Neurocomputing (2009)

A generic programmable spike-timing based circuit which forms the building block of a reconfigurable neuromorphic array is implemented in analog VLSI. An array of programmable spike time event coded circuit blocks is configured to implement functional circuit blocks of a spike time based neuromorphic model. A reconfigurable neuromorphic array chip with 10 event blocks is fabricated using Austria Microsystems 0.35@mm CMOS technology to demonstrate the functionality of the circuits in silicon.
Animacy encoding in English: why and how
Authors: Annie Zaenen, Jean Carletta, Gregory Garretson, Joan Bresnan, Andrew Koontz-Garboden, Tatiana Nikitina, M. Catherine O'Connor, Tom Wasow
Venue: Proceedings of the 2004 ACL Workshop on Discourse Annotation (2004)

We report on two recent medium-scale initiatives annotating present day English corpora for animacy distinctions. We discuss the relevance of animacy for computational linguistics, specifically generation, the annotation categories used in the two studies and the interannotator reliability for one of the studies.
Digital Photography For Seniors For Dummies
Authors: Mark Justice Hinton
Venue: For Dummies (2009)

Take the mystery out of digital photography and join the fun! You don't need to be a professional photographer or a technology expert to take great digital photos! This down-to-basics guide makes it easy to choose the right camera, understand all its dials and controls, take good pictures, make them look even better with your computer, and print them or share them online for friends and family to enjoy. Do your homework compare camera features to choose those you need at the price you can afford Practice, practice, practice learn to use camera settings, how to compose good shots, and how light affects a picture The darkroom is now digital use free software to organize and edit your photos Learn to share print your pictures at home or through a service, e-mail them to friends, set up an online photo album, or show them off in a digital picture frame Open the book and find: How to pick the camera that best fits your budget and needs Tips for taking great travel photos Accessories you might want for your camera How to get really good pictures of kids and pets Easy ways to get photos from your camera to your computer Tips and tricks for editing pictures on a computer Good reasons for putting your pictures online 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
High-Performance Local Search for Task Scheduling with Human Resource Allocation
Authors: Bertrand Estellon, Frédéric Gardi, Karim Nouioua
Venue: Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics (2009)

In this paper, a real-life problem of task scheduling with human resource allocation is addressed. This problem was approached by the authors in the context of the ROADEF 2007 Challenge, which is an international competition organized by the French Operations Research Society. The subject of the contest, proposed by the telecommunications company France Télé com, consists in planning maintenance interventions and teams of technicians needed for their achievements. The addressed combinatorial optimization problem is very hard: it contains several NP-hard subproblems and its scale (hundreds of interventions and technicians) induces a huge combinatorics. An effective and efficient local-search heuristic is described to solve this problem. This algorithm was ranked 2nd of the competition (over the 35 teams who have submitted a solution). Moreover, a methodology is revealed to design and engineer high-performance local-search heuristics for solving practically discrete optimization problems.
Application of Security Ontology to Context-Aware Alert Analysis
Authors: Hui Xu, Debao Xiao, Zheng Wu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

With rapid development of computer networks, users need a new solution for network security management, aiming at integration. This paper focuses on context-aware alert analysis, which is one of its key functionalities. A practical and efficient approach to guarantee unified representation of context information, background knowledge and attack knowledge for security alerts is still lacking these days. This paper applies security ontology by means of OWL+SWRL+OWL-S based on CIM Schema to describe context information and security knowledge in a unified manner. We argue that, our proposed approach improves existing alert analysis techniques by providing formal representations with the use of security ontology, which may possibly be an important stage for implementation of unified network security management.
A Function Based Approach towards Adaptive Interfaces for Elderly Users
Authors: Edmund Wascher, Gerhard Rinkenauer, Michael Falkenstein
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Addressing Diversity. Part I: Held as Part of HCI International 2009 (2009)

Recent information technologies may support elderly people in living independently even when they become immobile. Most computer systems, however, are hard to use when age-related impairments increase. While sensory and motor deficits can be alleviated by built in accessibility tools, cognitive alterations with increasing age are often not addressed. Here, we present an approach that intends to evaluate the adaptation of interfaces based on individual capabilities.
Modeling Distributed Signal Processing Applications
Authors: Werner Kurschl, Stefan Mitsch, Johannes Schoenboeck
Venue: Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks (2009)

Wireless Sensor Networks in general and Body Sensor Networks in particular enable sophisticated applications in pervasive healthcare, sports training and other domains,where interconnected nodes work together. Their main goal is to derive context from raw sensor data with feature extraction and classification algorithms. Body sensor networks not only comprise a single sensor type or family but demand different hardware platforms, e.g., sensors to measure acceleration or blood-pressure, or tiny mobile devices to communicate with the user. The problem arises how to efficiently deal with these heterogeneous platforms and programming languages. This paper presents a distributed signal processing framework based on TinyOS and nesC. The framework forms the basis for a Model-Driven Software Development approach. By raising the level of abstraction formal models hide implementation specifics of the framework in a Platform Specific Model. A Platform Independent Model further lifts modeling to functional and non-functional requirements independent from platforms. Thereby we promote cooperation between domain experts and software engineers and facilitate reusability of applications across different platforms.