ppxscal/embedding_network huggingface dataset:
Thread motion: fine-grained power management for multi-core systems
Authors: Krishna K. Rangan, Gu-Yeon Wei, David Brooks
Venue: ACM SIGARCH Computer Architecture News (2009)

Dynamic voltage and frequency scaling (DVFS) is a commonly-used power-management scheme that dynamically adjusts power and performance to the time-varying needs of running programs. Unfortunately, conventional DVFS, relying on off-chip regulators, faces limitations in terms of temporal granularity and high costs when considered for future multi-core systems. To overcome these challenges, this paper presents thread motion (TM), a fine-grained power-management scheme for chip multiprocessors (CMPs). Instead of incurring the high cost of changing the voltage and frequency of different cores, TM enables rapid movement of threads to adapt the time-varying computing needs of running applications to a mixture of cores with fixed but different power/performance levels. Results show that for the same power budget, two voltage/frequency levels are sufficient to provide performance gains commensurate to idealized scenarios using per-core voltage control. Thread motion extends workload-based power management into the nanosecond realm and, for a given power budget, provides up to 20% better performance than coarse-grained DVFS.
An efficient search method of e-government information using knowledge of search history
Authors: Keiichiro Mitani, Masakazu Takahashi, Kazuhiko Tsuda
Venue: International Journal of Computer Applications in Technology (2009)

Basic information gathering is a vital element of the work of research firms when they begin new research. Search sources vary; they include not only site information but also documents on office shelves, and objectives include both accuracy and efficiency in producing results. Inexperienced members of research groups cannot easily define objective terms for doing their searches with the result that they take a long time to identify appropriate information. This paper looks at reference methods for special terms and business-world terms when searching e-government material. It also looks at expressions of vague numerical information often found in government reports and proposes how these can be taken into consideration and efficiently searched.
GRE: hybrid recommendations for NSDL collections
Authors: Todd C. Will, Anand Srinivasan, Michael Bieber, Il Im, Vincent Oria, Yi-Fang (Brook) Wu
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Recommendation systems have been proven to reduce the time and effort required by users to find relevant items, but there are only sporadic reports on their application in digital libraries. The General Recommendation Engine (GRE) is composed of the text search system Lucene augmented by the well-understood content based and collaborative filtering techniques and the first application of knowledge based recommendation in digital libraries to recommend items from 22 National Science Digital Library collections. In this study comprised of 60 subjects, the GRE outperformed the baseline system Lucene in all areas of evaluation.
Non-linear matrix factorization with Gaussian processes
Authors: Neil D. Lawrence, Raquel Urtasun
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

A popular approach to collaborative filtering is matrix factorization. In this paper we develop a non-linear probabilistic matrix factorization using Gaussian process latent variable models. We use stochastic gradient descent (SGD) to optimize the model. SGD allows us to apply Gaussian processes to data sets with millions of observations without approximate methods. We apply our approach to benchmark movie recommender data sets. The results show better than previous state-of-the-art performance.
Towards distributed network classification for mobile ad hoc networks
Authors: Dimitrios Antonellis, Ahmed Mansy, Konstantinos Psounis, Mostafa H. Ammar
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Mobile ad hoc networks range from traditional MANETs where end-to-end paths exist from sources to destinations, to DTNs where no contemporaneous end-to-end paths exist and communication is achieved by the store, carry, and forward model of routing. Hence, nodes of these networks need to identify the level of connectivity of the network they belong to and classify it as a MANET or a DTN, in order to properly select appropriate protocols to achieve end-to-end communication. What is more, since mobile ad hoc networks change over time and space, nodes need to periodically re-access their network classification to adapt to the always changing environment. Recently, there has been an effort to classify the various types of mobile ad hoc networks assuming there is a centralized authority that has complete knowledge of the network and its dynamics. In this paper we design distributed mechanisms for nodes to perform the above classification on the fly, based only on local information that they collect as they move and encounter other nodes. The mechanisms take advantage of a combination of measurements and analytical techniques. We investigate the accuracy of our mechanisms by comparing the network classification of the centralized authority to that of a node using our schemes.
Pose Invariant Palmprint Recognition
Authors: Chhaya Methani, Anoop M. Namboodiri
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

A palmprint based authentication system that can work with a multi-purpose camera in uncontrolled circumstances, such as those mounted on a laptop, mobile device or those for surveillance, can dramatically increase the applicability of such a system. However, the performance of existing techniques for palmprint authentication fall considerably, when the camera is not aligned with the surface of the palm. The problems arise primarily due to variations in appearance introduced due to varying pose, but is compounded by specularity of the skin and blur due to motion and focus. In this paper, we propose a method to deal with variations in pose in unconstrained palmprint imaging. The method can robustly estimate and correct variations in pose, and compute a similarity measure between the corrected test image and a reference image. Experimental results on a set of 100 user's palms captured at varying poses show a reduction in Equal Error Eate from 22.4% to 8.7%.
Green Cell Phones and Mobile Skype Finally Arrive
Authors: Maria Ebling, Mark Corner
Venue: IEEE Pervasive Computing (2009)

This installment of New Products covers new green cell phones, a universal charger, cellular femtocells, Skype on mobile phones, a service that turns on street lights from your phone, and a de-identify caller ID.
Optimal link weights for IP-based networks supporting hose-model VPNs
Authors: Jian Chu, Chin-Tau Lea
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

From traffic engineering point of view, hose-model VPNs are much easier to use for customers than pipe-model VPNs. In this paper we explore the optimal weight setting to support hose-model VPN traffic in an IP-based hop-by-hop routing network. We try to answer the following questions: 1) What is the maximum amount of hose-model VPN traffic with bandwidth guarantees that can be admitted to an IP-based hop-by-hop routing network (as opposed to an MPLS-based network), and 2) what is the optimal link weight setting that can achieve that? We first present a mixed-integer programming formulation to compute the optimal link weights that can maximize the ingress and egress VPN traffic admissible to a hop-by-hop routing network. We also present a heuristic algorithm for solving the link weight searching problem for large networks. We show simulation results to demonstrate the effectiveness of the search algorithm.
The role of compression and refinement in visualization tools for crime analysts
Authors: Susan W. Van den Braak, Herre Van Oostendorp, Gerard A. W. Vreeswijk, Henry Prakken
Venue: Proceedings of the 8th international conference on International conference for the learning sciences - Volume 3 (2008)

This paper presents the results of a study that tested the effect of compression and refinement, as implemented in the AVERs graph visualization software for crime analysts, on the quality of the users' analysis of a simple crime case and their understanding of this case. In this study professional crime analysts and students who used these methods outperformed users that were only allowed to use conventional methods to handle large graphs.
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Authors: Wei Jin, Hung Hay Ho, Rohini K. Srihari
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Merchants selling products on the Web often ask their customers to share their opinions and hands-on experiences on products they have purchased. Unfortunately, reading through all customer reviews is difficult, especially for popular items, the number of reviews can be up to hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision. The OpinionMiner system designed in this work aims to mine customer reviews of a product and extract high detailed product entities on which reviewers express their opinions. Opinion expressions are identified and opinion orientations for each recognized product entity are classified as positive or negative. Different from previous approaches that employed rule-based or statistical techniques, we propose a novel machine learning approach built under the framework of lexicalized HMMs. The approach naturally integrates multiple important linguistic features into automatic learning. In this paper, we describe the architecture and main components of the system. The evaluation of the proposed method is presented based on processing the online product reviews from Amazon and other publicly available datasets.
A novel fair random access scheme with throughput optimization using fuzzy controller for wireless systems
Authors: M. R. M. Rizk, M. I. Dessouky, Sami A. El-Dolil, Mohammed Abd-Elnaby
Venue: International Journal of Network Management (2009)

Good backoff algorithms should be able to achieve high channel throughput while maintaining fairness among active nodes. In this paper, we propose a novel backoff algorithm to improve the fairness of random access channels, while maximizing channel throughput. The mechanism of the proposed backoff algorithm uses backoff delay (retransmission delay) and channel-offered traffic to dynamically control the backoff interval, so that each active node increases its backoff interval in the case of collision by a factor which exponentially decreases as the backoff delay increases, and decreases its backoff interval in the case of successful transmission by a factor which exponentially decreases as the backoff delay of previous retransmission attempts increases. Also, the backoff interval is controlled according to the channel offered, traffic using a fuzzy controller to maximize channel throughput. Furthermore, the operation of the proposed backoff algorithm does not depend on knowledge of the number of active nodes. A computer simulation is developed using MATLAB to evaluate the performance of the proposed backoff algorithm and compare it with the binary exponential backoff (BEB) scheme, which is widely used owing to its high channel throughput, while its fairness is relatively poor. It is shown that the proposed backoff algorithm significantly outperforms the BEB scheme in terms of improving the performance of fairness, and converges to the ideal performance as the minimum backoff interval increases, while achieving high channel throughput.
Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining
Authors: Kouzou Ohara, Masahiro Hara, Kiyoto Takabayashi, Hiroshi Motoda, Takashi Washio
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

Given a set of graphs with class labels, discriminative subgraphs appearing therein are useful to construct a classification model. A graph mining technique called Chunkingless Graph-Based Induction (Cl-GBI) can find such discriminative subgraphs from graph structured data. But, it sometimes happens that Cl-GBI cannot extract subgraphs that are good enough to characterize the given data due to its time and space complexities. Thus, to improve its efficiency, we propose pruning methods based on the upper-bound of information gain that is used as a criterion for discriminability of subgraphs in Cl-GBI. The upper-bound of information gain of a subgraph is the maximal one that its super graph can achieve. By comparing the upper-bound of each subgraph with the best information gain at the moment, Cl-GBI can exclude unfruitful subgraphs from its search space. Furthermore, we experimentally evaluate the effectiveness of the pruning methods on a real world and artificial datasets.
Ontologies for Self-Regulated Learning
Authors: Moma de la Torre, Raymund Sison
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Self-regulated learning is the key for students to be masters of their own learning processes. These self-initiated processes enable these students to become controllers of their learning experiences. The objective of this research is to maximize the use of domain ontology to develop self-regulated learning skills. Also defines activities that support self-regulation from the Self-Regulated Learning (SRL) ontology, and make use of it during learning scenarios. The three-phase model of Zimmerman is used as a theoretical framework for organizing the elements in the SRL ontology. This ontology gives rise to the structured elements that form the taxonomy for the definition and development of SRL environments. The basic idea of this work is to exploit the domain ontology as a tool to develop SRL skills. Furthermore, the SRL ontology is used to identify SRL activities needed for the learner in his learning scenarios.
Reasoning about imperative and higher-order programs
Authors: Mitchell Wand
Venue:  (2008)

Contextual equivalence, namely the property that two expressions are indistinguishable inside any program context, is a fundamental property of program expressions. Discovering methods that enable formal reasoning about contextual equivalence is hard and highly dependent on the features of the programming language.In this dissertation we present a technique for systematically deriving reasoning methods for contextual equivalence, which are sound and complete in a variety of languages, but also useful for proving many equivalences. The advantages of the derived reasoning methods are that they successfully deal with imperative as well as higher-order features.We demonstrate our technique by deriving sound and complete methods for proving contextual equivalence in the call-by-value lambda calculus, a lambda calculus with higher-order store, the nu-calculus, an imperative object calculus, and an imperative core of Java.
Using opponent models for efficient negotiation
Authors: Koen Hindriks, Catholijn Jonker, Dmytro Tykhonov
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Information about the opponent is essential to improve automated negotiation strategies for bilateral multi-issue negotiation. In this paper we propose a negotiation strategy that combines a Bayesian technique to learn the preferences of an opponent during bidding and a Tit-for-Tat-like strategy to avoid exploitation by the opponent. The learned opponent model is used to achieve two important goals in negotiation. It may be used to increase the efficiency of negotiation by searching for Pareto optimal bids and to avoid exploitation by making moves that mirror the move of the other party. The performance of the proposed negotiation strategy is analyzed in a tournament setup.
Identification of Dynamical Systems
Authors: Rolf Isermann, Marco Munchhof
Venue: Advanced Textbooks In Control And Signal Processing (2009)

For many applications, ranging from controls engineering to natural sciences and economics, precise dynamic models must be derived. In the vast majority of applications, such precise models cannot be derived by theoretical considerations only. The book discusses methods, which allow the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification respectively. After a short introduction into the required methodology of continuous-time and discrete-time linear systems, the focus is first on the identification of non-parametric models with continuous-time signals employing methods such as Fourier transform, measurement of the frequency response and correlation analysis. Then, the parameter estimation for parametric models is presented with a focus on the method of Least Squares, followed by some of its most prominent modifications.Issues such as parameter estimation for time-variant processes, parameter estimation in closed-loop, parameter estimation for differential equations, continuous time processes and efficient implementations of the algorithms are discussed. The different methods are compared and an outlook is given on non-linear system identification methods, such as neural networks and look-up tables. Real experimental data are given on CD-ROM, allowing to test many of the methods presented in the book with real measurements. Powerpoint slides for a 12-14 week graduate level course can be made available to teachers.
Optimal Error Estimates for the Fully Discrete Interior Penalty DG Method for the Wave Equation
Authors: Marcus J. Grote, Dominik Schötzau
Venue: Journal of Scientific Computing (2009)

In Grote et al. (SIAM J. Numer. Anal., 44:2408---2431, 2006) a symmetric interior penalty discontinuous Galerkin (DG) method was presented for the time-dependent wave equation. In particular, optimal a-priori error bounds in the energy norm and the L 2-norm were derived for the semi-discrete formulation. Here the error analysis is extended to the fully discrete numerical scheme, when a centered second-order finite difference approximation ("leap-frog" scheme) is used for the time discretization. For sufficiently smooth solutions, the maximal error in the L 2-norm error over a finite time interval converges optimally as O(h p+1+Δt 2), where p denotes the polynomial degree, h the mesh size, and Δt the time step.
TOFU: a socially expressive robot character for child interaction
Authors: Ryan Wistort, Cynthia Breazeal
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

The TOFU project introduces a robotic platform for enabling new opportunities in robot based learning with emphasis on storytelling and artistic expression. This project introduces a socially expressive robot character designed to mimic the expressive abilities of animated characters. This demonstration proposal describes the expressive abilities and operator interface to the TOFU project. In this demonstration session, participants will have the opportunity to physically interact with the TOFU project and puppeteer the behavior of the robotic character through a simple joystick interface.
A joint design of admission control and transmission rate adaptation for VoIP over wireless network
Authors: Youngkyu Choi, Sunghyun Choi
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

The ideal design for VoIP should be able to maximize the number of concurrent users while each admitted user enjoys the satisfactory quality of voice communication. In a recent packet-based wireless system, the quality-of-service (QoS) provisioning for VoIP raises several challenging issues including correlated delay performance among users and the rate-reliability tradeoff in managing multiple transmission rates on top of the inherent difficulty originating from the dependency of QoS on end-to-end delay. For these reasons, it is rarely found in the literature the work which presents the admission criteria for VoIP in an explicit manner. In this paper, our major contributions include 1) deriving the link-level QoS requirement from the E-model; 2) presenting the admission criteria in an explicit manner; 3) proposing a transmission rate adaptation algorithm specialized for VoIP application; and 4) illustrating the feasibility of our proposed schemes by getting the necessary information from the measurement. In addition to the theoretical justification, through the intensive simulation study in the Rayleigh fading environment, we prove that our joint designs composed of the rate adaptation, measurement-based admission control algorithm, and its extension to supporting the cell-boundary users indeed work well. Also, we evaluate the impact of various parameters including the average SNR, the Doppler rate, and the wireline delay.
Nodal Discontinuous Galerkin Methods: Algorithms, Analysis, and Applications, 1st edition
Authors: Jan S. Hesthaven, Tim Warburton
Venue:  (2007)

The text offers an introduction to the key ideas, basic analysis, and efficient implementation of discontinuous Galerkin finite element methods (DG-FEM) for the solution of partial differential equations. All key theoretical results are either derived or discussed, including an overview of relevant results from approximation theory, convergence theory for numerical PDEs, orthogonal polynomials etc. Through embedded Matlab codes, the algorithms are discussed and implemented for a number of classic systems of PDEs, e.g., Maxwells equations, Euler equations, incompressible Navier-Stokes equations, and Poisson- and Helmholtz equations. These developments are done in detail inone and two dimensions on general unstructured grids with high-order elements and all essential routines for 3D extensions are also included and discussed briefly. The three appendices contain an overview of orthogonal polynomials and associated library routines used throughout, a brief introduction to grid generation, and an overview of the associated software (where to get it, list of variables etc). A variety of exercises are included at the end of most chapters.
Deadlock freedom through object ownership
Authors: Eric Kerfoot, Steve McKeever, Faraz Torshizi
Venue: International Workshop on Aliasing, Confinement and Ownership in Object-Oriented Programming (2009)

Active objects are an attractive method of introducing concurrency into Java-like languages by decoupling method execution from invocation. In this paper, we show how ownership is used in the Java [14] subset language CoJava [17] to prevent deadlock associated with active object method calls. This approach builds on existing type-based approaches that eliminates data races and data-based deadlock in concurrent systems. The novel addition is the use of ownership to organize active objects, thus preventing deadlock from arising when objects are allowed to block awaiting responses from others. Typechecking is used to prevent threads from sharing mutable data, thus CoJava is free of data races and data-based deadlock. Behavioural deadlock is prevented by the use of promise objects which prevent clients from blocking indefinitely while awaiting responses. Ownership imposes a hierarchy on active objects; this allows owners to safely block while waiting for responses from owned objects. The paper also discusses the implications of this approach to specification with JML, formal reasoning about programs, and the consequences to runtime assertion checking.