ppxscal/embedding_network huggingface dataset:
Advanced Maintenance Simulation by Means of Hand-Based Haptic Interfaces
Authors: Michele Nappi, Luca Paolino, Stefano Ricciardi, Monica Sebillo, Giuliana Vitiello
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

Aerospace industry has been involved in virtual simulation for design and testing since the birth of virtual reality. Today this industry is showing a growing interest in the development of haptic-based maintenance training applications, which represent the most advanced way to simulate maintenance and repair tasks within a virtual environment by means of a visual-haptic approach. The goal is to allow the trainee to experiment the service procedures not only as a workflow reproduced at a visual level but also in terms of the kinaesthetic feedback involved with the manipulation of tools and components. This study, conducted in collaboration with aerospace industry specialists, is aimed to the development of an immersive virtual capable of immerging the trainees into a virtual environment where mechanics and technicians can perform maintenance simulation or training tasks by directly manipulating 3D virtual models of aircraft parts while perceiving force feedback through the haptic interface. The proposed system is based on ViRstperson, a virtual reality engine under development at the Italian Center for Aerospace Research (CIRA) to support engineering and technical activities such as design-time maintenance procedure validation, and maintenance training. This engine has been extended to support haptic-based interaction, enabling a more complete level of interaction, also in terms of impedance control, and thus fostering the development of haptic knowledge in the user. The user's "sense of touch" within the immersive virtual environment is simulated through an Immersion CyberForce® hand-based force-feedback device. Preliminary testing of the proposed system seems encouraging.
Stability Criterions for a Class of Switched Linear Systems
Authors: Hongbo Zou, Renquan Lu, Ouguan XU
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

The problem of stability analysis for a class of switched linear systems is studied in this paper based on the theory of matrix measure. The matrix measures of all sub systems are used to determine the stability of the switched linear systems. Based on this, sufficient conditions are reached, which can be used to determine the stability or instability of switched linear systems under arbitrary switching law. If a switching sequence satisfies some conditions, a theorem in this paper can be used to verify if it can stabilize the systems.The obtained conditions are simpler than the reported methods such as multi-Lyapunov functions and hence are easier to check. Numerical examples are used to demonstrate these conditions.
Arguing on the computer in scientific and non-scientific domains
Authors: Kalypso Iordanou, Deanna Kuhn
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

A method is employed to promote development of argumentation skills utilizing instant-messaging software as the medium of discourse. A major question investigated is transfer of argumentation skills across content domains. Forty sixth graders engaged in electronic discourse on a controversial topic, for half dinosaur extinction (the science topic) and for the other half homeschooling (the social topic). Participants collaborated with a sameside peer in arguing against successive pairs of peers on the opposing side of an issue; in addition they engaged in some reflective activities. Another 18 sixth graders served in a control condition. Although transfer occurred in both directions, science condition participants exhibited transfer of skills to the social topic to a greater extent than did social condition participants to the science topic. Results show the transfer of developing skills but also suggest the importance as well as feasibility of fostering argument skills in physical as well as social science domains.
A latent variable model for generative dependency parsing
Authors: Ivan Titov, James Henderson
Venue: Proceedings of the 10th International Conference on Parsing Technologies (2007)

We propose a generative dependency parsing model which uses binary latent variables to induce conditioning features. To define this model we use a recently proposed class of Bayesian Networks for structured prediction, Incremental Sigmoid Belief Networks. We demonstrate that the proposed model achieves state-of-the-art results on three different languages. We also demonstrate that the features induced by the ISBN's latent variables are crucial to this success, and show that the proposed model is particularly good on long dependencies.
Investigating Demographic Influences for HIV Classification Using Bayesian Autoassociative Neural Networks
Authors: Jaisheel Mistry, Fulufhelo V. Nelwamondo, Tshilidzi Marwala
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

This paper presents a method of determining whether demographic properties such as education, race, age, physical location, gravidity and parity influence the ability to classify the HIV status of a patient. The degree to which these variables influence the HIV classification is investigated by using an ensemble of autoassociative neural networks that are trained using the Bayesian framework. The HIV classification is treated as a missing data problem and the ensemble of autoassociative neural networks coupled with an optimization technique are used to determine a set of possible estimates. The set of possible estimates are aggregated together to give a predictive certainty measure. This measure is the percentage of the most likely estimate from all possible estimates. Changes to the state of each of the demographic properties are made and changes in the predictive certainty are recorded. It was found that the education level and the race of the patients are influential on the predictability of the HIV status. Significant knowledge discovery about the demographic influences on predicting a patients HIV status is obtained by the methods presented in this paper.
Selection of Subsets of Ordered Features in Machine Learning
Authors: O. Seredin, A. Kopylov, V. Mottl
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

The new approach of relevant feature selection in machine learning is proposed for the case of ordered features. Feature selection and regularization of decision rule are combined in a single procedure. The selection of features is realized by introducing weight coefficients, characterizing degree of relevance of respective feature. A priori information about feature ordering is taken into account in the form of quadratic penalty or in the form of absolute value penalty on the difference of weight coefficients of neighboring features. Study of a penalty function in the form of absolute value shows computational complexity of such formulation. The effective method of solution is proposed. The brief survey of author's early papers, the mathematical frameworks, and experimental results are provided.
On discriminative semi-supervised classification
Authors: Fei Wang, Changshui Zhang
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels should be sufficiently smooth with respect to the intrinsic data manifold. In this paper, we argue that rather than penalizing the label smoothness, we can directly punish the discriminality of the classification function to achieve a more powerful predictor, and we derive two specific algorithms: Semi-Supervised Discriminative Regularization (SSDR) and Semi-parametric Discriminative Semi-supervised Classification (SDSC). Finally many experimental results are presented to show the effectiveness of our method.
A Methodology of Requirement Analysis for Disaster Response Oriented Spatial Information
Authors: Biao Chen, Jinggao Zhang, Jun Lv, Zuo Zhang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Spatial information has been very influential to environment manager. Especially to disaster response, spatial information are more influential cause the pressure of space, time, and resources. In the past the research on spatial information system mostly focused on the technical field or limited on one specific function of the entire disaster management activity. More attention is needed to pay to the whole system of disaster management since it involves with more organizations, more accountabilities and more shared resources. This study put forward an analysis method to disaster response oriented spatial information requirement basing on project management principle.
A Non-rigid Registration Framework That Accommodates Resection and Retraction
Authors: Petter Risholm, Eigil Samset, Ion-Florin Talos, William Wells
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

Traditional non-rigid registration algorithms are incapable of accurately registering intra-operative with pre-operative images whenever tissue has been resected or retracted. In this work we present methods for detecting and handling retraction and resection. The registration framework is based on the bijective Demons algorithm using an anisotropic diffusion smoother. Retraction is detected at areas of the deformation field with high internal strain and the estimated retraction boundary is integrated as a diffusion boundary in the smoother to allow discontinuities to develop across the resection boundary. Resection is detected by a level set method evolving in the space where image intensities disagree. The estimated resection is integrated into the smoother as a diffusion sink to restrict image forces originating inside the resection from being diffused to surrounding areas. In addition, the deformation field is continuous across the diffusion sink boundary which allow us to move the boundary of the diffusion sink without changing values in the deformation field (no interpolation or extrapolation is needed). We present preliminary results on both synthetic and clinical data which clearly shows the added value of explicitly modeling these processes in a registration framework.
An Autonomous Algorithm for Generating and Merging Clinical Algorithms
Authors: Francis Real, David Riaño
Venue: Knowledge Management for Health Care Procedures: ECAI 2008 Workshop, K4HelP 2008, Patras, Greece, July 21, 2008, Revised Selected Papers (2009)

Procedural knowledge in medicine uses to come expressed as isolated sentences in Clinical Practice Guidelines (CPG) that describe how to act in front of specific health-care situations. Although CPGs gather all evidence available on concrete medical problems, their direct application has been proved to have some limitations. One of these limitations occurs when they have to be applied on co-morbid patients suffering from several simultaneous and mutually related diseases. In such cases, health-care professionals have to follow the indications of multiple CPGs and solve their interactions as they appear in the treatment of concrete patients. Clinical Algorithms (CA) are schematic models of the procedures appearing in a CPG. They are used to organize and summarize the recommendations contained in CPGs. Here, we extend a knowledge-based algorithm to merge CAs with a machine learning procedure to relax the knowledge dependence of that algorithm. The resulting algorithm has been tested on health-care data provided by the SAGESSA Group on hypertension patients. The results obtained prove that it is a good approach to the generation of CA from data though several improvements at the levels of prediction and medical interpretation are possible. Furthermore, the learned knowledge from the data generation process can be reused to improve the results of the merging process for similar diseases.
On a special class of regularized central paths for semidefinite programs
Authors: Anhua Lin
Venue: Mathematical Programming: Series A and B (2009)

We present a special class of regularized central paths for standard primal-dual semidefinite program (SDP) that can be used to design path-following algorithms for finding the projection of any symmetric matrix/vector onto the solution set of the SDP. We will study the existence, convergence, and analytical properties of these paths.
Multi-base Station Placement for Reprogramming Wireless Sensor Networks
Authors: Aoi Hashizume, Hiroshi Mineno, Tadanori Mizuno
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

Reprogramming sensor nodes is an effective way to improve wireless sensor networks. The latest reprogramming protocols use radio communication to distribute software data. In large-scale sensor networks, several base stations are placed to disseminate software fast, but performances of reprogramming protocols for multi-base station environments have not been discussed. In this paper, we evaluate the features of software dissemination for multi-base station sensor networks. Simulations revealed that the placement and the number of base stations were the key parameters in software dissemination.
Internal Aspects of the Relationship between Pressing Force and Training Difficulty
Authors: Daisuke Doyo
Venue: Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009 (2009)

In manual assembly work, parts are often assembled by applying force with a simple tool or by hand. A worker thus needs control the force he or she applies in working, as an appropriate level of force is requisite for minimizing work failures and improving efficiency. The object of this study is to clarify the relationship between the level of force (the "force") and level of training difficulty (the "training difficulty") in manual assembly work. Measurements of the training difficulty for 10 test subjects (persons being tested) at force gauges of 30, 40, 50, 60, 70, 80, 100, and 120N revealed a relationship between the force gauge internal to each test subject and the training difficulty.
Segmentation Study on Enterprise Customers Based on Data Mining Technology
Authors: Xin-an Lai
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In the current context of fierce market competition, Customer Relationship Management (CRM) has become the main means for enterprises to gain competitive advantage and an important option for enterprises to make strategic planning. As a core concept of CRM, customer segmentation can effectively lower the marketing costs of a company and help it achieve more visible and profitable market penetration. This paper begins by introducing the definition of data mining and data mining methods used in CRM; it then proceeds to analyze the advantage of customer segmentation based on data mining and establish the models for customer segmentation; in the end this paper probes into the application of clustering analysis technology of data mining in customer segmentation.
Hand Pressure Detection Among Image Sequence In Breast Self-Examination Multimedia System
Authors: Chen Shuyue, Cheng Qicai, Raouf N. G. Naguib, Andreas Oikonomou
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

The hand pressure applying on breast determines the possibilities of lump detection during breast self-examination. In the paper, a method of estimating hand pressure is presented by means of image entropy among image sequence obtained by a Web camera in breast self-examination based on multimedia system. Firstly, the breast self-examination multimedia system is described in detail. Then according to the statistic character of image entropy, calculating the difference between current and initial image and giving the entropy of the difference, we may obtain the estimation of the hand pressure. The estimated pressure is proved to be accurate through a human-like silicon breast experiment. The dynamic model of the breast is set up, close to Hook rule by means of verifying of the proposed pressure estimation. The algorithm is simple and the calculation is limited in a local region of the images, which is beneficial to real-time realization.
Screening Paper Runnability in a Web-Offset Pressroom by Data Mining
Authors: A. Alzghoul, A. Verikas, M. Hållander, M. Bacauskiene, A. Gelzinis
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

This paper is concerned with data mining techniques for identifying the main parameters of the printing press, the printing process and paper affecting the occurrence of paper web breaks in a pressroom. Two approaches are explored. The first one treats the problem as a task of data classification into "break" and "non break" classes. The procedures of classifier design and selection of relevant input variables are integrated into one process based on genetic search. The search process results in a set of input variables providing the lowest average loss incurred in taking decisions. The second approach, also based on genetic search, combines procedures of input variable selection and data mapping into a low dimensional space. The tests have shown that the web tension parameters are amongst the most important ones. It was also found that, provided the basic off-line paper parameters are in an acceptable range, the paper related parameters recorded online contain more information for predicting the occurrence of web breaks than the off-line ones. Using the selected set of parameters, on average, 93.7% of the test set data were classified correctly. The average classification accuracy of the break cases was equal to 76.7%.
Engineering User Centered Interaction Systems for Semantic Visualizations
Authors: Kawa Nazemi, Thomas Daniel Ullmann, Christoph Hornung
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)

For intuitive interaction with semantic visualizations, gesture-based interaction seems a promising way. However, the development of such ensembles is costly. To cut down the engineering effort, we propose a development model for interaction systems with semantic visualizations. In addition, we provide a set of evaluation tools to support the interaction developer engineer evaluating the engineering process.
Reasoning about attribute authenticity in a web environment
Authors: Thomas Wölfl
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

The reliable authentication of user attributes is an important prerequisite for the security of web based applications. Digital certificates are widely used for that purpose. However, practical certification scenarios can be very complex. Each certiticate carries a validity period and can be revoked during this period. Furthermore, the verifying user has to trust the issuers of certificates and revocations. This work presents a formal model which covers these aspects and provides a theoretical foundation for the decision about attribute authenticity even in complex scenarios. The model is based on the event calculus, an AI technique from the field of temporal reasoning. It uses Clark's completion to address the frame problem. An example illustrates the application of the model.
Termination Analysis by Dependency Pairs and Inductive Theorem Proving
Authors: Stephan Swiderski, Michael Parting, Jürgen Giesl, Carsten Fuhs, Peter Schneider-Kamp
Venue: Proceedings of the 22nd International Conference on Automated Deduction (2009)

Current techniques and tools for automated termination analysis of term rewrite systems (TRSs) are already very powerful. However, they fail for algorithms whose termination is essentially due to an inductive argument. Therefore, we show how to couple the dependency pair method for TRS termination with inductive theorem proving. As confirmed by the implementation of our new approach in the tool AProVE, now TRS termination techniques are also successful on this important class of algorithms.
A Decentralized Approach to Minimum-Energy Broadcasting in Static Ad Hoc Networks
Authors: Chris Miller, Christian Poellabauer
Venue: Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks (2009)

Due to the limited resources of most wireless ad hoc and sensor networks, minimizing the cost of commonly used broadcasts is of utmost importance. This has led to work in the minimum energy broadcasting problem. Most solutions require global topology knowledge, however, this information is typically not available in ad hoc applications. Decentralized approaches have been unable to match the energy efficiency of centralized methods. Previous approaches have also relied upon locality information to estimate link cost, which is unreliable. In this paper, we will describe a new distributed approach to the minimum energy broadcasting problem which targets multi-packet broadcast sessions. It constructs a broadcast tree in a distributed fashion using link quality measurements to more accurately estimate link cost. We show by simulation, and confirm through experimentation, that our protocol is capable of constructing a tree that is near to centralized approaches in energy cost.
Heuristic evaluation functions for general game playing
Authors: James Clune
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

A general game playing program plays games that it has not previously encountered. A game manager program sends the game playing programs a description of a game's rules and objectives in a well-defined game description language. A central challenge in creating effective general game playing programs is that of constructing heuristic evaluation functions from game descriptions. This paper describes a method for constructing evaluation functions that represent exact values of simplified games. The simplified games are abstract models that incorporate the most essential aspects of the original game, namely payoff, control, and termination. Results of applying this method to a sampling of games suggest that heuristic evaluation functions based on our method are both comprehensible and effective.