ppxscal/embedding_network huggingface dataset:
Supplying Instantaneous Video-on-Demand Services Using Controlled Multicast
Authors: Lixin Gao, Don Towsley
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

In this paper, we propose and evaluate the performance of a multicast technique, called controlled CIWP, for supplying video-on-demand services. Similar to batching schemes, controlled CIWP allows two clients that request the same video to share a channel. Unlike batching, the controlled CIWP scheme does not delay the earlier request in order to promote sharing. Instead, sharing is ensured by permitting the client with the later arrival time to join an ongoing multicast session started for the earlier request. However, controlled CIWP does not let a client join an ongoing multicast session whenever possible. A threshold is used to control the frequency at which new multicast sessions are started. We derive the optimal threshold that minimizes the number of server channels required. Our simulation study shows that the controlled CIWP significantly improves the performance of the VOD service.
AORTE for Recognizing Textual Entailment
Authors: Reda Siblini, Leila Kosseim
Venue: Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing (2009)

In this paper we present the use of the AORTE system in recognizing textual entailment. AORTE allows the automatic acquisition and alignment of ontologies from text. The information resulted from aligning ontologies created from text fragments is used in classifying textual entailment. We further introduce the set of features used in classifying textual entailment. At the TAC RTE4 challenge the system evaluation yielded an accuracy of 68% on the two-way task, and 61% on the three way task using a simple decision tree classifier.
Implementation and performance modeling of deterministic particle transport (Sweep3D) on the IBM Cell/B.E.
Authors: Olaf Lubeck, Michael Lang, Ram Srinivasan, Greg Johnson
Venue: Scientific Programming (2009)

The IBM Cell Broadband Engine (BE) is a novel multi-core chip with the potential for the demanding floating point performance that is required for high-fidelity scientific simulations. However, data movement within the chip can be a major challenge to realizing the benefits of the peak floating point rates. In this paper, we present the results of implementing Sweep3D on the Cell/B.E. using an intra-chip message passing model that minimizes data movement. We compare the advantages/disadvantages of this programming model with a previous implementation using a master-worker threading strategy. We apply a previously validated micro-architecture performance model for the application executing on the Cell/B.E. (based on our previous work in Monte Carlo performance models), that predicts overall CPI (cycles per instruction), and gives a detailed breakdown of processor stalls. Finally, we use the micro-architecture model to assess the performance of future design parameters for the Cell/B.E. micro-architecture. The methodologies and results have broader implications that extend to multi-core architectures.
Study on Extend Kalman Filter at Low Speed in Sensorless PMSM Drives
Authors: Shan-Mao Gu, Feng-You He, Hui Zhang
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

The application of an Extended Kalman Filter (EKF) as nonlinear speed and position observer in PMSM drives has been a mature research project. However, one significant problem still unsolved is the weakly performance at low speed of PMSM drive system that yield to the best estimation performance on high speed range (>5Hz). This paper proposes a novel method--Adjustable DC bus voltage, for low speed EKF sensorless control of permanent magnet synchronous motor (PMSM) drives. The findings from the experiment that the better performance at low speed (>2Hz) by adjusting the DC Bus voltage according to the system reference speed are also presented. Simulation and Experimental results are given to confirm the effectiveness of the proposed method.
An application of quantum finite automata to interactive proof systems
Authors: Harumichi Nishimura, Tomoyuki Yamakami
Venue: Journal of Computer and System Sciences (2009)

Quantum finite automata have been studied intensively since their introduction in late 1990s as a natural model of a quantum computer working with finite-dimensional quantum memory space. This paper seeks their direct application to interactive proof systems in which a mighty quantum prover communicates with a quantum-automaton verifier through a common communication cell. Our quantum interactive proof systems are juxtaposed to Dwork-Stockmeyer's classical interactive proof systems whose verifiers are two-way probabilistic finite automata. We demonstrate strengths and weaknesses of our systems by studying how various restrictions on the behaviors of quantum-automaton verifiers affect the power of quantum interactive proof systems.
Improving the average delay of sorting
Authors: Andreas Jakoby, Maciej Likiewicz, Rüdiger Reischuk, Christian Schindelhauer
Venue: Theoretical Computer Science (2009)

In previous work we have introduced an average case measure for the time complexity of Boolean circuits. Instead of fixed circuit depth, for each input we take the minimal number of time steps necessary to perform the computation for that particular input using gates that forward their output values as soon as possible. This measure is called delay. Based on it, the complexity of a whole class of functions that can be described as prefix computations has been analysed in detail. Here we consider the problem to sort large integers that are given in binary notation. Contrary to a word comparator sorting circuitC where a basic computational element, a comparator, is charged with a single time step to compare two elements, in a bit comparator circuitC^' a comparison of two binary numbers has to be implemented by a Boolean subcircuit CM called comparator module that is built from Boolean gates of bounded fanin. Thus, compared to C, the depth of C^' will be larger by a factor up to the depth of CM. Our goal is to minimize the average delay of bit comparator sorting circuits. The worst-case delay can be estimated by the depth of the circuit. For this worst-case measure two topologically quite different designs seem to be appropriate for the comparator modules: a tree-like one if the inputs are long numbers, otherwise a linear array working in a pipelined fashion. Inserting these into a word comparator circuit we get bit level sorting circuits for binary numbers of length m, for which the depth is either increased by a multiplicative factor of order logm or by an additive term of order m. We show that these obvious solutions can be improved significantly by constructing efficient sorting and merging circuits for the bit model that only suffer a constant factor time loss on the average if the inputs are uniformly distributed. This is done by designing suitable hybrid architectures of tree compaction and pipelining. These results can also be extended to classes of nonuniform distributions if we put a bound on the complexity of the distributions themselves.
Robust 3D Face Tracking on Unknown Users with Dynamical Active Models
Authors: Dianle Zhou, Patrick Horain
Venue: Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling (2009)

The Active Appearance Models [1] and the derived Active Models (AM) [4] allow to robustly track the face of a single user that was previously learnt, but works poorly with multiple or unknown users. Our research aims at improving the tracking robustness by learning from video databases. In this paper, we study the relation between the face texture and the parameter gradient matrix, and propose a statistical approach to dynamically fit the AM to unknown users by estimating the gradient and update matrices from the face texture. We have implemented this algorithm for real time face tracking and experimentally demonstrate its robustness when tracking multiple or unknown users' faces.
Generating Interactive Learning Objects from Configurable Samples
Authors: Peng Han, Bernd J. Krämer
Venue: Proceedings of the 2009 International Conference on Mobile, Hybrid, and On-line Learning (2009)

Pedagogically well-designed interactive learning objects (LOs) can help students to better understand complex concepts and processes. Such LOs can stimulate higher-level cognitive skills by involving students in interactive learning activities. The design and implementation of interactive LOs is, however, time-consuming and requires special skills. LOs are also often localized and tightly connected with particular educational scenarios, which strongly limits their reuse in different contexts. In this article, we present a methodology of developing and reusing interactive learning objects relying on a heuristic principle. It suggests keeping content and educational context separate at design time and connecting both facets of LOs only at reuse time. We illustrate this principle both for Java applets and for interactive Flash animations. Building on top of Adobe's Flex technology, we also suggest to separate the design of generic Flash animation templates from the pedagogically motivated interaction logics. Three simple examples illustrate our method.
Statistical methods to estimate vehicle count using traffic cameras
Authors: Peng Zhuang, Yi Shang, Bei Hua
Venue: Multidimensional Systems and Signal Processing (2009)

Traffic camera has played an important role in enabling intelligent and real-time traffic monitoring and control. In this paper, we focus on establishing a correlation model for the traffic cameras' vehicle counts and increase the spatial-resolution of a city's vehicle counting traffic camera system by means of correlation-based estimation. We have developed two methods for constructing traffic models, one using statistical machine learning based on Gaussian models and the other using analytical derivation from the origin-destination (OD) matrix. The Gaussian-based method outperforms existing correlation coefficient based methods. When training data are not available, our analytical method based on OD matrix can still perform well. When there is only a limited number of cameras, we develop heuristic algorithms to determine the most desirable locations to place the cameras so that the errors of traffic estimations at the locations without traffic cameras are minimized. We show some improvements in the performance of our proposed methods over an existing method in a variety of simulations.
Values as lived experience: evolving value sensitive design in support of value discovery
Authors: Christopher A. Le Dantec, Erika Shehan Poole, Susan P. Wyche
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

The Value Sensitive Design (VSD) methodology provides a comprehensive framework for advancing a value-centered research and design agenda. Although VSD provides helpful ways of thinking about and designing value-centered computational systems, we argue that the specific mechanics of VSD create thorny tensions with respect to value sensitivity. In particular, we examine limitations due to value classifications, inadequate guidance on empirical tools for design, and the ways in which the design process is ordered. In this paper, we propose ways of maturing the VSD methodology to overcome these limitations and present three empirical case studies that illustrate a family of methods to effectively engage local expressions of values. The findings from our case studies provide evidence of how we can mature the VSD methodology to mitigate the pitfalls of classification and engender a commitment to reflect on and respond to local contexts of design.
Arbitrary norm support vector machines
Authors: Kaizhu Huang, Danian Zheng, Irwin King, Michael R. Lyu
Venue: Neural Computation (2009)

Support vector machines (SVM) are state-of-the-art classifiers. Typically L2-norm or L1-norm is adopted as a regularization term in SVMs, while other norm-based SVMs, for example, the L0-norm SVM or even the L∞-norm SVM, are rarely seen in the literature. The major reason is that L0-norm describes a discontinuous and nonconvex term, leading to a combinatorially NP-hard optimization problem. In this letter, motivated by Bayesian learning, we propose a novel framework that can implement arbitrary norm-based SVMs in polynomial time. One significant feature of this framework is that only a sequence of sequential minimal optimization problems needs to be solved, thus making it practical in many real applications. The proposed framework is important in the sense that Bayesian priors can be efficiently plugged into most learning methods without knowing the explicit form. Hence, this builds a connection between Bayesian learning and the kernel machines. We derive the theoretical framework, demonstrate how our approach works on the L0-norm SVM as a typical example, and perform a series of experiments to validate its advantages. Experimental results on nine benchmark data sets are very encouraging. The implemented L0-norm is competitive with or even better than the standard L2-norm SVM in terms of accuracy but with a reduced number of support vectors,-9.46% of the number on average. When compared with another sparse model, the relevance vector machine, our proposed algorithm also demonstrates better sparse properties with a training speed over seven times faster.
Improving Participation, Accessibility and Compliance for Campus-Wide Mobile Emergency Alerting Systems
Authors: Helen T. Sullivan, Markku T. Häkkinen, Dana Piechocinski
Venue: Mobile Response: Second International Workshop on Mobile Information Technology for Emergency Response, MobileResponse 2008. Bonn, Germany, May 29-30, 2008, Revised Selected Papers (2009)

University campus communities face a variety of hazards, from natural and technological disasters to terrorism and violence. In response to recent events, many campuses within the United States have begun to implement emergency notification systems utilizing email, text, and telephone-based messaging. These alerts are designed to reach members of the campus community, including faculty, staff, and students and most rely upon an opt-in model for participation. The present design of both the registration process and the notification messages raise several concerns as to the effectiveness of notification systems. This research presents findings from an examination of emergency notification systems on one campus and discusses approaches to improve such systems for all members of the campus population.
Exploring future challenges for haptic, audio and visual interfaces for mobile maps and location based services
Authors: Charlotte Magnusson, Konrad Tollmar, Stephen Brewster, Tapani Sarjakoski, Tiina Sarjakoski, Samuel Roselier
Venue: Proceedings of the 2nd International Workshop on Location and the Web (2009)

In this article we give an overview of some challenges in how to make geospatial information more useable and accessible. We also suggest a roadmap for dealing with these challenges -- and introduce a new EU project HaptiMap.
A Hybrid Approach for Clustering-Based Data Aggregation in Wireless Sensor Networks
Authors: Woo-Sung Jung, Keun-Woo Lim, Young-Bae Ko, Sang-Joon Park
Venue: Proceedings of the 2009 Third International Conference on Digital Society (2009)

In a wireless sensor network application for tracking multiple mobile targets, large amounts of sensing data can be generated by a number of sensors. These data must be controlled with efficient data aggregation techniques to reduce data transmission to the sink node. Several clustering methods were used previously to aggregate the large amounts of data produced from sensors in target tracking applications. However, such clustering based data aggregation algorithms show effectiveness only in restricted type of sensing scenarios, while posing great problems when trying to adapt to various environment changes. To alleviate the problems of existing clustering algorithms, we propose a hybrid clustering based data aggregation scheme. The proposed scheme can adaptively choose a suitable clustering technique depending on the status of the network, increasing the data aggregation efficiency as well as energy consumption and successful data transmission ratio. Performance evaluation via simulation has been made to show the effectiveness of the proposed scheme.
A method for solving nth order fuzzy linear differential equations
Authors: T. Allahviranloo, E. Ahmady, N. Ahmady
Venue: International Journal of Computer Mathematics (2009)

In this paper, an analytic method (eigenvalue-eigenvector method) for solving nth order fuzzy differential equations with fuzzy initial conditions is considered. In this method, three cases are introduced, in each case, it is shown that the solution of differential equation is a fuzzy number. In addition, the method is illustrated by solving several numerical examples.
Least squares twin support vector machines for pattern classification
Authors: M. Arun Kumar, M. Gopal
Venue: Expert Systems with Applications: An International Journal (2009)

In this paper we formulate a least squares version of the recently proposed twin support vector machine (TSVM) for binary classification. This formulation leads to extremely simple and fast algorithm for generating binary classifiers based on two non-parallel hyperplanes. Here we attempt to solve two modified primal problems of TSVM, instead of two dual problems usually solved. We show that the solution of the two modified primal problems reduces to solving just two systems of linear equations as opposed to solving two quadratic programming problems along with two systems of linear equations in TSVM. Classification using nonlinear kernel also leads to systems of linear equations. Our experiments on publicly available datasets indicate that the proposed least squares TSVM has comparable classification accuracy to that of TSVM but with considerably lesser computational time. Since linear least squares TSVM can easily handle large datasets, we further went on to investigate its efficiency for text categorization applications. Computational results demonstrate the effectiveness of the proposed method over linear proximal SVM on all the text corpuses considered.
Investigations on Detection Model of Large Scale Rotation Shaft Torsional Vibration in Precision Heavy Machinery
Authors: Zhao Wu
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

For solving on-line extract torsional vibrating parameter detecting and metrical problem of spanless point of complex and precise heavy machinery large scale rotary driving shaft, a new torsional vibration continuous shaft segment mass detecting and analytic model was proposed by using kinetics theory and measuring theory. The new method established the vibrational transmission relationship between the measurable point and the spanless point. New model was verified correctness, feasibility and effectiveness by means of gathering torque signal in the production field and comparing the consistency between measured value and theoretical calculation value of spanless point torque signal. Based on the experiment’s result, new model can supply a engineered means for acquiring the vibration detailed information of the point on precise heavy machinery large scale driving shaft which was inconvenience fitted sensor. It also can program composition for implement on-line monitor and fault forecast on rotary shaft and then guarantee the precise heavy complex rotary machine even running.
On the accuracy of Monte Carlo Potts models for grain growth
Authors: Qiang Yu, Michael Nosonovsky, Sven K. Esche
Venue: Journal of Computational Methods in Sciences and Engineering (2008)

Monte Carlo (MC) Potts models have been widely used to study various microstructural phenomena. The efficiency and accuracy of the method is very critical in order to apply it to industrially relevant engineering problems. This paper provides new insights into the conventional MC (CMC) algorithm for grain growth. It was believed earlier that an unphysical finite-size effect is likely to dominate the simulated grain growth in small grain size regimes and that the decrease of the probability for successful reorientation attempts significantly affects the microstructural evolution leading to low grain growth exponents. We show that the simulated grain growth is affected by the decrease of this probability only in the very early stage, and furthermore that no such unphysical finite-size effect is observed. Alternatively, the strong random nature of the CMC algorithm is partially responsible for the lower values of the grain growth exponent. A three-parameter nonlinear regression analysis is used to obtain the classical power-law grain-growth kinetics with a more accurate growth exponent. Therefore, large lattice systems are not required for accurate modeling of the microstructure evolution, which reduces the computing time considerably, especially for three-dimensional applications.
Logic Engines as Interactors
Authors: Paul Tarau
Venue: Proceedings of the 24th International Conference on Logic Programming (2008)

We introduce a new programming language construct, Interactors, supporting the agent-oriented view that programming is a dialog between simple, self-contained, autonomous building blocks.We define Interactors as an abstraction of answer generation and refinement in Logic Engines resulting in expressive language extension and metaprogramming patterns.Interactors extend language constructs like Ruby, Python and C#'s multiple coroutining block returns through yield statements and they can emulate the action of monadic constructs and catamorphisms in functional languages.The full version of this paper [1] describes source level emulation of Prolog's dynamic database and various built-ins in terms of an Interactor API and design patterns for algorithms involving combinatorial generation and infinite answer streams.
Operation assignment and capacity allocation problem in automated manufacturing systems
Authors: Selin Bilgin, Meral Azizoğlu
Venue: Computers and Industrial Engineering (2009)

We address an operation assignment and capacity allocation problem that arises in semiconductor industries and flexible manufacturing systems. We assume the automated machines have scarce time and tool magazine capacities and the tools are available in limited quantities. The aim is to select a subset of operations with maximum total weight. We show that the problem is NP-hard in the strong sense, develop two heuristics and a Tabu Search procedure. The results of our computational tests have revealed that our Tabu Search procedure produces near optimal solutions very quickly.
A Review of Mobile Terminal-Based Applications for Self-Management of Patients with Diabetes
Authors: Naoe Tatara, Eirik Årsand, Heidi Nilsen, Gunnar Hartvigsen
Venue: Proceedings of the 2009 International Conference on eHealth, Telemedicine, and Social Medicine (2009)

Peer-reviewed studies of mobile terminal-based applications for self-management of patients with diabetes were reviewed. Databases of medical and engineering studies were searched for relevant publications, and 39 publications describing 28 studies were identified as examining feasibility, acceptability or effectiveness using empirical methods, preferably involving prospective users. Research methods, application design, and findings were summarized. The current status is that the key features of successful applications for diabetes management have not yet been clarified because of the difficulties in statistical comparison between studies and the limitations of each study. The importance of clarifying the key feature for enhancing motivation in long-term self-management of diabetes taking human-factor-engineering methods into account is discussed.