ppxscal/embedding_network huggingface dataset:
Public participation and value advocacy in information design and sharing: Laying the foundations in advance of wide-scale public deployment
Authors: Alan Borning, Batya Friedman, Janet L. Davis, Brian T. Gill, Peter H. Kahn,  Jr., Travis Kriplean, Peyina Lin
Venue: Information Polity (2009)

Supporting public participation is often a key goal in the design of digital government systems. However, years of work may be required before a complex system, such as the UrbanSim urban simulation system, is deployed and ready for such participation. In this paper, we investigate laying the foundations for public participation in information design and sharing in advance of wide-scale public deployment, with the goal of having interaction designs ready when the system is put into such use. Moreover, in a highly politicized domain such as this one, value advocacy as well as factual information plays a central role. Using the theory and methods of Value Sensitive Design, we address three design goals toward public participation and value advocacy, and provide evidence that each of them was achieved: (1) enabling indirect stakeholders to become direct stakeholders (i.e. enabling more people to interact directly with UrbanSim in useful ways); (2) developing a participatory process by which these stakeholders can help guide the development of the system itself; and (3) enabling participating organizations to engage in value advocacy while at the same time enhancing overall system legitimation.
Seamless mobility in ubiquitous computing environments
Authors: Umakishore Ramachandran
Venue:  (2008)

Nominally, one can expect any user of modern technology to at least carry a handheld device of the class of an iPAQ (perhaps in the form of a cellphone). The availability of technology in the environment (home, office, public spaces) also continues to grow at an amazing pace. With advances in technology, it is feasible to remain connected and enjoy services that we care about, be it entertainment, sports, or plain work, anytime anywhere. We need a system that supports seamless migration of services from handhelds to the environment (or vice versa) and between environments. Virtualization technology is able to support such a migration by providing a common virtualized interface at both source and destination. In this dissertation, we focus on two levels of virtualization to address issues for seamless mobility. We first identify three different kinds of spaces and three axes to support mobility in these spaces. Then we present two systems that address these dimensions from different perspectives. For service level virtualization, we have built a system called MobiGo that can capture the application states and restore the service execution with saved states at the destination platform. It provides the architectural elements for efficiently managing different states in the different spaces. Evaluation suggests that the overhead of the system is relatively small and meets user&rsquo;s expectation. Service level virtualization has certain limitations, specifically when the application state and device state are not visible to the middleware. On the other hand, for device level virtualization, Chameleon is a Xen-like system level virtualization system to support device level migration and automatic capability adaptation at the operating system level. Chameleon is able to capture and restore device states and automatically accommodate the heterogeneity of devices to provide the migration of services. Device level virtualization can address some issues that cannot be addressed in service level virtualization. It also has less requirements than service level virtualization in order to be applied to existing systems. Through performance measurements, we demonstrate that Chameleon introduces minimal overhead while providing capability adaptation and device state migration for seamless mobility in ubiquitous computing environments.
Worst-case response time analysis of real-time tasks under fixed-priority scheduling with deferred preemption
Authors: Reinder J. Bril, Johan J. Lukkien, Wim F. Verhaegh
Venue: Real-Time Systems (2009)

Fixed-priority scheduling with deferred preemption (FPDS) has been proposed in the literature as a viable alternative to fixed-priority pre-emptive scheduling (FPPS), that obviates the need for non-trivial resource access protocols and reduces the cost of arbitrary preemptions.This paper shows that existing worst-case response time analysis of hard real-time tasks under FPDS, arbitrary phasing and relative deadlines at most equal to periods is pessimistic and/or optimistic. The same problem also arises for fixed-priority non-pre-emptive scheduling (FPNS), being a special case of FPDS. This paper provides a revised analysis, resolving the problems with the existing approaches. The analysis is based on known concepts of critical instant and busy period for FPPS. To accommodate for our scheduling model for FPDS, we need to slightly modify existing definitions of these concepts. The analysis assumes a continuous scheduling model, which is based on a partitioning of the timeline in a set of non-empty, right semi-open intervals. It is shown that the critical instant, longest busy period, and worst-case response time for a task are suprema rather than maxima for all tasks, except for the lowest priority task. Hence, that instant, period, and response time cannot be assumed for any task, except for the lowest priority task. Moreover, it is shown that the analysis is not uniform for all tasks, i.e. the analysis for the lowest priority task differs from the analysis of the other tasks. These anomalies for the lowest priority task are an immediate consequence of the fact that only the lowest priority task cannot be blocked. To build on earlier work, the worst-case response time analysis for FPDS is expressed in terms of known worst-case analysis results for FPPS. The paper includes pessimistic variants of the analysis, which are uniform for all tasks, illustrates the revised analysis for an advanced model for FPDS, where tasks are structured as flow graphs of subjobs rather than sequences, and shows that our analysis is sustainable.
A Type of Integrating Formula without Derivative
Authors: Aifang Long, Di Ning
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, A type of integrating formula is constructed, which requires function value at nodes without derivative. In addition, the formula needs less calculation than the Trapezoidal Rule, but the order of convergence is much better. Therefore a more effective .result is obtained.
Image recognition with neural classifiers in micromechanics and agriculture
Authors: Tatiana Baidyk, Ernst Kussul, Oleksandr Makeyev, Alejandro Vega
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

Neural classifier for multi-purpose image recognition systems is developed. One of the applications is an adaptive control system based on image recognition system for micromechanics where the limited receptive area (LIRA) neural classifier is proposed for texture recognition of mechanically treated metal surfaces. The performance of the proposed classifier was tested on image database with four texture types corresponding to metal surfaces after milling, polishing with sandpaper, turning with lathe and polishing with file. The promising recognition rate of 99.8% was obtained. Another application is agriculture, where vast amounts of pesticides are used against the insects. In order to decrease the required amount of pesticides it is necessary to locate the precise form distribution of the insects and caterpillars. In this case the use of pesticides will be local. In order to automate the task of recognition of caterpillars we propose to use a web-camera and a personal computer. In this article we propose the LIRA neural classifier for the tasks of recognition of texture images of metal surfaces and texture images of caterpillars. We use an image database of caterpillars of different forms, sizes and color, distributed in different amounts and positions. The main idea is to recognize the difference between the textures corresponding to the caterpillars and real world background. In the article we present the structure and the algorithms of recognition with LIRA neural classifier, and results of its application in both tasks.
A novel encoding algorithm for vector quantization using transformed codebook
Authors: Jim Z. C. Lai, Yi-Ching Liaw
Venue: Pattern Recognition (2009)

In this paper, a novel encoding algorithm for vector quantization is presented. Our method uses a set of transformed codewords and partial distortion rejection to determine the reproduction vector of an input vector. Experimental results show that our algorithm is superior to other methods in terms of the computing time and number of distance calculations. Compared with available approaches, our method can reduce the computing time and number of distance calculations significantly. Compared with the available best method of reducing the number of distance computations, our approach can reduce the number of distance calculations by 32.3-67.1%. Compared with the best encoding algorithm for vector quantization, our method can also further reduce the computing time by 19.7-23.9%. The performance of our method is better when a larger codebook is used and is weakly correlated to codebook size.
A comparison of two machine-learning techniques to focus the diagnosis task
Authors: Oscar Prieto, Aníbal Bregón
Venue: Proceeding of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium (2006)

This work considers a time series classification task: fault identification in dynamic systems. Two methods are compared: i) Boosting and ii) K-Nearest Neighbors with Dynamic Time Warping distance.
New LMT-based delay-dependent criterion for global asymptotic stability of cellular neural networks
Authors: Cheng-De Zheng, Lai-Bing Lu, Zhan-Shan Wang
Venue: Neurocomputing (2009)

The problem of global asymptotic stability analysis is studied for a class of cellular neural networks with time-varying delay. By defining a Lyapunov-Krasovskii functional, a new delay-dependent stability condition is derived in terms of linear matrix inequalities. The obtained criterion is less conservative than some previous literature because free-weighting matrix method and the Jensen integral inequality are considered. Three illustrative examples are given to demonstrate the effectiveness of the proposed results.
Investigating autonomic behaviours in grid-basedcomputational science applications
Authors: Shantenu Jha, Manish Parashar, Omer Rana
Venue: Proceedings of the 6th international conference industry session on Grids meets autonomic computing (2009)

Emerging Grid infrastructures present unprecedented opportunities for computational science and engineering, with the potential for fundamental insights into complex phenomenon. However, it also presents unprecedented challenges in terms of its scale, heterogeneity, dynamism and overall complexity that must be addressed before this potential can be realized. Autonomic computing concepts have been effectively used to address similar challenges in enterprise systems and applications; in this paper, we explore the role of autonomic computing to Grid-based computational science applications. Specifically, we use three representative computational applications to motivate Autonomic Computational Science (ACS). Using these applications, we develop a conceptual framework for ACS, consisting of mechanisms, strategies and objectives, and demonstrate how these concepts can be used to express autonomic behaviors. Finally we explore a research agenda towards realizing ACS behaviors and developing self-* patterns for large scale autonomic computational science application.
A More Agile Approach to Embedded System Development
Authors: Michael Smith, James Miller, Lily Huang, Albert Tran
Venue: IEEE Software (2009)

Given the plethora of advantages attributed to agile methodologies, why are there only infrequent reports of their application in the embedded systems world? We believe this has two principal causes. First, embedded applications go through a life cycle that differs from desktop life cycles, so that desktop application production processes must be significantly altered to meet the demands of this new domain. Second, without providing for full life-cycle tool support, no change to embedded production processes will ever succeed, and again desktop tools must be adapted to meet the new environment's constraints. Here, the authors discuss their thoughts on an XP-inspired embedded life cycle and their successes in developing, extending, and using embedded test-driven development frameworks for customers (Matlab-Fit and Embedded-FitNesse) and developers (MUnit and Embedded-Unit).
Exploring multi-core limitations through comparison of contemporary systems
Authors: Ashley M. DeFlumere, Sadaf R. Alam
Venue: The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations (2009)

Our research aims at evaluating the performance of contemporary multi-core platforms, the quad-core AMD Barcelona and the dual-core Intel Woodcrest, for scientific applications. We used the High Performance Computing Challenge (HPCC) benchmark suite, which contains test cases for quantifying performance of the memory and communication sub-systems. Analyzing the performance of multi-core devices allows us to identify system parameters and configurations that could yield optimal performance. Since these devices are building blocks of the fastest supercomputing systems, the insights into performance behavior provide guidance for designing future high performance computing resources. Our results demonstrate that without multi-core aware optimization the achievable performance decreases as the number of cores per socket increases.
Learning, indexing, and diagnosing network faults
Authors: Ting Wang, Mudhakar Srivatsa, Dakshi Agrawal, Ling Liu
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Modern communication networks generate massive volume of operational event data, e.g., alarm, alert, and metrics, which can be used by a network management system (NMS) to diagnose potential faults. In this work, we introduce a new class of indexable fault signatures that encode temporal evolution of events generated by a network fault as well as topological relationships among the nodes where these events occur. We present an efficient learning algorithm to extract such fault signatures from noisy historical event data, and with the help of novel space-time indexing structures, we show how to perform efficient, online signature matching. We provide results from extensive experimental studies to explore the efficacy of our approach and point out potential applications of such signatures for many different types of networks including social and information networks.
Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Demo Session
Venue: Human Language Technology Conference (2008)

Welcome to the proceedings of the demo session. We received 21 submissions, 9 of which were selected for inclusion in the program after review by at least two members of the program committee. 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
Developing a Bayes-net based student model for an External Representation Selection Tutor
Authors: Beate Grawemeyer, Richard Cox
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper describes the process by which we are constructing an intelligent tutoring system (ERST) designed to improve learners' external representation (ER) selection accuracy on a range of database query tasks. This paper describes how ERST's student model is being constructed-it is a Bayesian network seeded with data from experimental studies. The studies examined the effects of students' background knowledge-of-external representations (KER) upon performance and their preferences for particular information display forms across a range of database query types.
A survey of types of text noise and techniques to handle noisy text
Authors: L. Venkata Subramaniam, Shourya Roy, Tanveer A. Faruquie, Sumit Negi
Venue: Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data (2009)

Often, in the real world noise is ubiquitous in text communications. Text produced by processing signals intended for human use are often noisy for automated computer processing. Automatic speech recognition, optical character recognition and machine translation all introduce processing noise. Also digital text produced in informal settings such as online chat, SMS, emails, message boards, newsgroups, blogs, wikis and web pages contain considerable noise. In this paper, we present a survey of the existing measures for noise in text. We also cover application areas that ingest this noisy text for various tasks like Information Retrieval and Information Extraction.
Version space learning for possibilistic hypotheses
Authors: Henri Prade, Mathieu Serrurier
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)

In this paper, we are interested in learning stratified hypotheses from examples and counter-examples associated with weights that express their prototypical importance. It leads to an extension of the well-known version space learning framework. In order to do that, we emphasize that the treatment of positive and negative examples in version space learning is reminding of a bipolar revision process recently studied in the setting of possibilistic information representation. Bipolarity appears when the positive and negative sides of information are specified in a distinct way. Then, we use the possibilistic bipolar representation setting, which distinguishes between what is guaranteed to be possible, and what is simply not impossible, as a basis for extending version space learning to examples associated with possibility degrees. It allows us to define a formal framework for learning layered hypotheses.
Collaborative social modeling for designing a patient wellness tracking system in a nurse-managed health care center
Authors: Yuan An, Prudence W. Dalrymple, Michelle Rogers, Patricia Gerrity, Jennifer Horkoff, Eric Yu
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

There has been an increasing need for developing health information systems for improving clinical processes and outcomes. Deeply understanding and accurately capturing the information needs of the stakeholders is crucial to successfully designing and deploying such a system. Empirical study on "effective" methodologies for requirements analysis for information system design is one of the important aspects in design science research in information systems. In this paper, we present our case study on exploring a goal-oriented requirements analysis technique called the i* framework for eliciting and modeling the requirements for a patient wellness tracking (PWT) system in a nurse-managed health care services center. The center employs a transdisciplinary care approach for managing illnesses. The innovation and complexity in the health care approach brings about many challenges in designing a PWT system that always provides positive impacts on the current workflows at the center. The system is aimed to maintain information about a wide variety of health and wellness services provided to patients. We want to thoroughly elicit the requirements through modeling the socio-technical environment and analyzing the goals of stakeholders through a collaborative approach. For this purpose, we explored the i* framework and introduced two adaptations in order to meet our needs in eliciting and capturing requirements. Our preliminary experience in this case study demonstrates that using the i* approach with our adaptations is a potentially effective method for eliciting, modeling, capturing, and validating the requirements of healthcare information systems.
Immediate Reward Reinforcement Learning for Clustering and Topology Preserving Mappings
Authors: Colin Fyfe, Wesam Barbakh
Venue: Similarity-Based Clustering: Recent Developments and Biomedical Applications (2009)

We extend a reinforcement learning algorithm which has previously been shown to cluster data. Our extension involves creating an underlying latent space with some pre-defined structure which enables us to create a topology preserving mapping. We investigate different forms of the reward function, all of which are created with the intent of merging local and global information, thus avoiding one of the major difficulties with e.g. K-means which is its convergence to local optima depending on the initial values of its parameters. We also show that the method is quite general and can be used with the recently developed method of stochastic weight reinforcement learning [14].
Valuable Change Detection in Keyword Map Animation
Authors: Takuya Nishikido, Wataru Sunayama, Yoko Nishihara
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

This paper proposes a map animation interface that supports interpretations of difference between two keyword relationships with varying viewpoints. Finding keywords whose relationships drastically change is crucial because the value of keywords mainly consists inof their relationships in networks. Therefore, this interface outputs marks for keywords that drastically change in their relations when it shows animations between two relationships.
Space--time adaptive multiresolution methods for hyperbolic conservation laws: Applications to compressible Euler equations
Authors: Margarete O. Domingues, Sônia M. Gomes, Olivier Roussel, Kai Schneider
Venue: Applied Numerical Mathematics (2009)

Adaptive strategies in space and time allow considerable speed-up of finite volume schemes for conservation laws, while controlling the accuracy of the discretization. In this paper, a multiresolution technique for finite volume schemes with explicit time discretization is presented. An adaptive grid is introduced by suitable thresholding of the wavelet coefficients, which maintains the accuracy of the finite volume scheme of the regular grid. Further speed-up is obtained by local scale-dependent time stepping, i.e., on large scales larger time steps can be used without violating the stability condition of the explicit scheme. Furthermore, an estimation of the truncation error in time, using embedded Runge-Kutta type schemes, guarantees a control of the time step for a given precision. The accuracy and efficiency of the fully adaptive method is illustrated with applications for compressible Euler equations in one and two space dimensions.