ppxscal/embedding_network huggingface dataset:
Tracing the meta-level: PyPy's tracing JIT compiler
Authors: Carl Friedrich Bolz, Antonio Cuni, Maciej Fijalkowski
Venue: Proceedings of the 4th workshop on the Implementation, Compilation, Optimization of Object-Oriented Languages and Programming Systems (2009)

We attempt to apply the technique of Tracing JIT Compilers in the context of the PyPy project, i.e., to programs that are interpreters for some dynamic languages, including Python. Tracing JIT compilers can greatly speed up programs that spend most of their time in loops in which they take similar code paths. However, applying an unmodified tracing JIT to a program that is itself a bytecode interpreter results in very limited or no speedup. In this paper we show how to guide tracing JIT compilers to greatly improve the speed of bytecode interpreters. One crucial point is to unroll the bytecode dispatch loop, based on two kinds of hints provided by the implementer of the bytecode interpreter. We evaluate our technique by applying it to two PyPy interpreters: one is a small example, and the other one is the full Python interpreter.
CREAM-MAC: An efficient Cognitive Radio-enAbled Multi-Channel MAC protocol for wireless networks
Authors: Hang Su, Xi Zhang
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Cognitive radio technology has emerged as the novel and effective approach to improve the utilization of precious radio spectrum. Employing the cognitive radio technology, secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that constrains the level of interference to the primary (licensed) users. However, there are many new challenges associated with cognitive radio based wireless networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability is different for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the spectrum sensing at physical layer and packet scheduling at MAC layer, over the wireless networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. In addition, we develop the analytical models to quantitatively analyze our proposed CREAM-MAC protocol in the saturated network case. We also conduct simulation experiments to validate our developed analytical models.
Nikon COOLPIX Digital Field Guide
Authors: J. Dennis Thomas
Venue:  (2007)

The Nikon COOLPIX Digital Field Guide is filled with everything you need to know in order to take amazing photographs using any Nikon COOLPIX camera. This full-color portable guide walks you through the essential controls, features, and functions of the Nikon COOLPIX point-and shoot camera line using step-by-step instructions and full-color images of each menu screen. This robust guide not only shows you how to adjust a variety of settings on your Nikon COOLPIX, it also teaches you when and why you should adjust them. The Nikon COOLPIX Digital Field Guide goes beyond camera settings to offer you a friendly guide to the principles of digital photography, covering the essentials of lighting and composition. Filled with amazing examples, this book also presents a variety of techniques for getting great photos, including specific tips and tricks for capturing portraits, candids, sports and action shots, travel pictures, macro photography, and much more. 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
Hindsight Bias, Risk Perception, and Investment Performance
Authors: Bruno Biais, Martin Weber
Venue: Management Science (2009)

Once they have observed information, hindsight-biased agents fail to remember how ignorant they were initially; “they knew it all along.” We formulate a theoretical model of this bias, providing a foundation for empirical measures and implying that hindsight-biased agents learning about volatility will underestimate it. In an experiment involving 66 students from Mannheim University, we find that hindsight bias reduces volatility estimates. In another experiment, involving 85 investment bankers in London and Frankfurt, we find that more biased agents have lower performance. These findings are robust to differences in location, information, overconfidence, and experience.
Research on fault diagnosis for CNC machine of flexible manufacturing system
Authors: Li Hui, Mao Jun, Li Xinhong, Xin Zhongwei
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

In order to find and treat fault or abnormal occurrences in numerically controlled machine tool of flexible manufacturing system in real-time, a study for computer numerically controlled (CNC) on-line fault diagnostics system has been carried out. The system can look up one or more sticking points of numerically controlled machine tool fault simply, locate CNC faults rapidly and accurately, but solve the problem between fault diagnosis and knowledge application. To provide CNC apparatus terminal with reliable trouble shooting suggestion, give a deep analysis between servo control subassembly and background service, make a description of fault database and test procedure design. The research has solved the problem of system maintenance, expansion and upgrade.
Engineering the cloud from software modules
Authors: Jan S. Rellermeyer, Michael Duller, Gustavo Alonso
Venue: Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (2009)

Cloud computing faces many of the challenges and difficulties of distributed and parallel software. While the service interface hides the actual application from the remote user, the application developer still needs to come to terms with distributed software that needs to run on dynamic clusters and operate under a wide range of configurations. In this paper, we outline our vision of a model and runtime platform for the development, deployment, and management of software applications on the cloud. Our basic idea is to turn the notion of software module into a first class entity used for management and distribution that can be autonomously managed by the underlying software fabric of the cloud. In the paper we present our model, outline an initial implementation, and describe a first application developed using the ideas presented in the paper.
Hierarchy and equivalence of multi-letter quantum finite automata
Authors: Daowen Qiu, Sheng Yu
Venue: Theoretical Computer Science (2009)

Multi-letter quantum finite automata (QFAs) are a new one-way QFA model proposed recently by Belovs, Rosmanis, and Smotrovs [A. Belovs, A. Rosmanis, J. Smotrovs, Multi-letter reversible and quantum finite automata, in: Proceedings of the 13th International Conference on Developments in Language Theory, DLT'2007, Harrachov, Czech Republic, in: Lecture Notes in Computer Science, vol. 4588, Springer, Berlin, 2007, pp. 60-71], and they showed that multi-letter QFAs can accept with no error some regular languages ((a+b)^*b) that are unacceptable by the one-way QFAs. In this paper, we continue to study multi-letter QFAs. We mainly focus on two issues: (1) we show that (k+1)-letter QFAs are computationally more powerful than k-letter QFAs, that is, (k+1)-letter QFAs can accept some regular languages that are unacceptable by any k-letter QFA. A comparison with the one-way QFAs is made by some examples; (2) we prove that a k"1-letter QFA A"1 and another k"2-letter QFA A"2 are equivalent, if and only if, they are (n"1+n"2)^4+k-1-equivalent, and the time complexity of determining the equivalence of two multi-letter QFAs using this method is O(n^1^2+k^2n^4+kn^8), where n"1 and n"2 are the numbers of states of A"1 and A"2, respectively, and k=max(k"1,k"2). Some other issues are addressed for further consideration.
Computing galled networks from real data
Authors: Daniel H. Huson, Regula Rupp, Vincent Berry, Philippe Gambette, Christophe Paul
Venue: Bioinformatics (2009)

Motivation: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and level-k networks, that are more tractable, but have the practical draw-back that a given set of clusters will usually not possess such a representation. Results: In this article, we argue that galled networks (a generalization of galled trees) provide a good trade-off between level of generality and tractability. Any set of clusters can be represented by some galled network and the question whether a cluster is contained in such a network is easy to solve. Although the computation of an optimal galled network involves successively solving instances of two different NP-complete problems, in practice our algorithm solves this problem exactly on large datasets containing hundreds of taxa and many reticulations in seconds, as illustrated by a dataset containing 279 prokaryotes. Availability: We provide a fast, robust and easy-to-use implementation of this work in version 2.0 of our tree-handling software Dendroscope, freely available from http://www.dendroscope.org. Contact: huson@informatik.uni-tuebingen.de
ChAT: a time-linked system for conversational analysis
Authors: Michelle L. Gregory, Douglas Love, Stuart Rose, Anne Schur
Venue: Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech (2006)

We present a system for analyzing conversational data. The system includes state-of-the-art natural language processing components that have been modified to accommodate the unique nature of conversational data. In addition, we leverage the added richness of conversational data by analyzing various aspects of the participants and their relationships to each other. Our tool provides users with the ability to easily identify topics or persons of interest, including who talked to whom, when, entities that were discussed, etc. Using this tool, one can also isolate more complex networks of information: individuals who may have discussed the same topics but never talked to each other. The tool includes a UI that plots information over time, and a semantic graph that highlights relationships of interest.
Towards Business Interestingness in Actionable Knowledge Discovery
Authors: Dan Luo, Longbing Cao, Chao Luo, Chengqi Zhang, Weiyuan Wang
Venue: Proceeding of the 2008 conference on Applications of Data Mining in E-Business and Finance (2008)

From the evolution of developing a pattern interestingness perspective, data mining has experienced two phases, which are Phase 1: technical objective interestingness focused research, and Phase 2: technical objective and subjective interestingness focused studies. As a result of these efforts, patterns mined are of significant interest to technical concern. However, technically interesting patterns are not necessarily of interest to business. In fact, real-world experience shows that many mined patterns, which are interesting from the perspective of the data mining method used, are out of business expectations when they are delivered to the final user. This scenario actually involves a grand challenge in next-generation KDD (Knowledge Discovery in Databases) studies, defined as actionable knowledge discovery. To discover knowledge that can be used for taking actions to business advantages, this paper addresses a framework that extends the evolution process of knowledge evaluation to Phase 3 and Phase 4. In Phase 3, concerns with objective interestingness from a business perspective are added on top of Phase 2, while in Phase 4 both technical and business interestingness should be satisfied in terms of objective and subjective perspectives. The introduction of Phase 4 provides a comprehensive knowledge actionability framework for actionable knowledge discovery. We illustrate applications in governmental data mining showing that the considerations and adoption of the framework described in Phase 4 has potential to enhance both sides of interestingness and expectation. As a result, knowledge discovered has better chances to support action-taking in the business world.
Active Fingerprint Ridge Orientation Models
Authors: Surinder Ram, Horst Bischof, Josef Birchbauer
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This paper proposes a statistical model for fingerprint ridge orientations. The active fingerprint ridge orientation model (AFROM) iteratively deforms to fit the orientation field (OF) of a fingerprint. The OFs are constrained by the AFROM to vary only in ways according to a training set. The main application of the method is the OF estimation in noisy fingerprints as well as the interpolation and extrapolation of larger OF parts. Fingerprint OFs are represented by Legendre Polynomials. The method does not depend on any pre-alignment or registration of the input image itself. The training can be done fully automatic without any user interaction. We show that the model is able to extract the significant appearance elements of fingerprint flow patterns even from noisy training images. Furthermore, our method does not depend on any other computed data, except a segmentation. We evaluated both, the generalisation as well as the prediction capability of the proposed method. These evaluations assess our method very good results.
Internet Policy and Economics: Challenges and Perspectives, 2nd edition
Authors: William Lehr, Lorenzo Maria Pupillo
Venue:  (2009)

For over a decade, William Lehr, Lorenzo Pupillo, and their colleagues in academia, industry, and policy have been on the electronic frontier, exploring the implications of the technologies that are revolutionizing communication and culture. In 2002, Cyber Policy and Economics in an Internet Age featured essays that focused on such emerging economic and policy-related issues of universal access, appropriate content, spectrum allocation, taxation, consumer protection, and regulation, with respect to the Internet. In this fully revised and updated edition, entitled Internet Policy and Economics: Challenges and Perspectives, the editors and contributors tackle the most current topics and issues, as the Internet continues to permeate all facets of society. New chapters cover dynamics in the developing world, the implications of e-commerce for fiscal policy, and the impact of peer-to-peer networks on music and the arts, as well as debates over intellectual property rights, privacy issues, and cybercrime. Applying insights from economics, political science, law, business, and communications, the book will serve as essential resource for researchers and students, policymakers and regulators, and industry analysts and practitioners.
Can information foraging pick the fix? A field study
Authors: Joseph Lawrance, Rachel Bellamy, Margaret Bumett, Kyle Rector
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Previous findings have revealed the ability of information foraging to model or predict where developers will navigate within source code. However, the previous investigation did not consider whether the places developers went were the right places to go. In this paper, we present afield study in which we investigated over 200 open source bug reports and feature requests. We analyzed the textual similarity of these issues in relation to the source code, and determined what files developers had changed to fix these issues. Our results demonstrate that information scent can narrow down quite well where developers should make fixes, implying that future software navigation tools can predict the appropriate places to make fixes based solely on the contents of the issue and the source code.
Noise-Reduced TPS Interpolation of Primary Vector Fields for Fiber Tracking in Human Cardiac DT-MRI
Authors: Feng Yang, Xin Song, Stanislas Rapacchi, Laurent Fanton, Pierre Croisille, Yue-Min Zhu
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Denoising and interpolation of primary vector fields in DT-MRI are essential for tracking myocardial fibers of the human heart. In this paper, a noise-reduced interpolation method for 3-D primary vector fields in human cardiac DT-MRI is proposed. The method consists of first localizing the noise-corrupted vectors using local statistical properties of the vector fields, then restoring the noise-corrupted vectors by means of Thin Plate Spline (TPS) interpolation method, and finally applying a global TPS interpolation to gain higher resolution in the spatial domain. Experiments and results show that the proposed method allows us to obtain higher resolution and reduce noise, while improving direction-coherence (DC) of vector fields, preserving details, and improving fiber tracking.
A Simulation-based Approach for Solving Generalized Semi-Markov Decision Processes
Authors: Emmanuel Rachelson
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Time is a crucial variable in planning and often requires special attention since it introduces a specific structure along with additional complexity, especially in the case of decision under uncertainty. In this paper, after reviewing and comparing MDP frameworks designed to deal with temporal problems, we focus on Generalized Semi-Markov Decision Processes (GSMDP) with observable time. We highlight the inherent structure and complexity of these problems and present the differences with classical reinforcement learning problems. Finally, we introduce a new simulation-based reinforcement learning method for solving GSMDP, bringing together results from simulation-based policy iteration, regression techniques and simulation theory. We illustrate our approach on a subway network control example.
FearNot!: providing children with strategies to cope with bullying
Authors: Lynne Hall, Susan Jones, Ana Paiva, Ruth Aylett
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

This paper presents FearNot!, an innovative anti-bullying intervention for 8-12 year old children, illustrating the potential of Virtual Learning Environments in providing supportive secure experiential learning for challenging social situations. The innovative technological approach taken to FearNot! is briefly described, along with an overview of the evaluation approach used to assess FearNot! with over 800 children in the UK and Germany. The demo of FearNot! provides participants with the opportunity to experience leading edge technology adopted for a classroom intervention.
Perspectives of Neural-Symbolic Integration, 1st edition
Authors: Barbara Hammer, Barbara Hammer, Pascal Hitzler
Venue: Studies In Computational Intelligence (2007)

The human brain possesses the remarkable capability of understanding, interpreting, and producing language, structures, and logic. Unlike their biological counterparts, artificial neural networks do not form such a close liason with symbolic reasoning: logic-based inference mechanisms and statistical machine learning constitute two major and very different paradigms in artificial intelligence with complementary strengths and weaknesses. Modern application scenarios in robotics, bioinformatics, language processing, etc., however require both the efficiency and noise-tolerance of statistical models and the generalization ability and high-level modelling of structural inference meachanisms. A variety of approaches has therefore been proposed for combining the two paradigms. This carefully edited volume contains state-of-the-art contributions in neural-symbolic integration, covering `loose' coupling by means of structure kernels or recursive models as well as `strong' coupling of logic and neural networks. It brings together a representative selection of results presented by some of the top researchers in the field, covering theoretical foundations, algorithmic design, and state-of-the-art applications in robotics and bioinformatics.
Interconnection networks synthesis and optimization
Authors: Chung-Kuan Cheng
Venue:  (2008)

The advent of new technologies brings revolutions in the fields of VLSI design and high performance computing. On one hand, the increasing number of processing elements, both in on-chip multi-core systems and supercomputer systems, demands high bandwidth communications. On the other hand, the performance of the system, usually measured by the latency and power consumption, is gradually being dominated by the interconnection networks. These facts raise challenges in synthesizing and optimizing interconnection networks. In this dissertation, we study methodologies and algorithms to perform the interconnection network synthesis and optimization in both on-chip networks and supercomputer systems. We explore a wide range of network topologies and physical implementations, and evaluate the performance of multi-commodity flow (MCF) algorithms. We design efficient approximation schemes to solve different variations of MCF problems, which incorporate different practical constraints. The automated design flows discover much larger design space than the traditional methods and therefore achieve promising results. In the study of Network-on-Chip (NoC), we are optimizing the communication latency and power consumption, which are two competing design objectives. With an improved fully polynomial approximation algorithm, power optimal design of a structured 8 &times; 8 NoC can be found for given average latency constraints with certain communication bandwidth requirements. Our methodology explores a large number of topologies, introduces a variety of wire styles into NoC design, and incorporates latency constraints and power minimization objectives into a unified MCF model, with simultaneous optimization on network topologies, physical embedding, and interconnect wire styles. The results demonstrate the strengths of the optimized networks and indicate the clear trend of power and latency tradeoffs. In the synthesis and optimization of networks in supercomputer systems, we use the packaging framework of the Blue Gene/L supercomputer as an example to demonstrate the advantages of our design flow, which has incorporated real design issues, such as board dimensions and pin numbers. Using real benchmark traces, the experiments show that the best topologies identified by our algorithm can achieve better average latency compared to the existing 3-dimensional torus networks.