ppxscal/embedding_network huggingface dataset:
Fact Proposition Event, 1st edition
Authors: P. L. Peterson
Venue: Studies In Linguistics And Philosophy (2007)

`Peterson is an authority of a philosophical and linguistic industry that began in the 1960s with Vendler's work on nominalization. Natural languages distinguish syntactically and semantically between various sorts of what might be called `gerundive entities' -- events, processes, states of affairs, propositions, facts, ... all referred to by sentence nominals of various kinds. Philosophers have worried for millennia over the ontology of such things or `things', but until twenty years ago they ignored all the useful linguistic evidence. Vendler not only began to straighten out the distinctions, but pursued more specific and more interesting questions such as that of what entities the causality relation relates (events? facts?). And that of the objects of knowledge and belief. But Vendler's work was only a start and Peterson has continued the task from then until now, both philosophically and linguistically. Fact Proposition Event constitutes the state of the art regarding gerundive entities, defended in meticulous detail. Peterson's ontology features just facts, proposition, and events, carefully distinguished from each other. Among his more specific achievements are: a nice treatment of the linguist's distinction between `factive' and nonfactive constructions; a detailed theory of the subjects and objects of causation, which impinges nicely on action theory; an interesting argument that fact, proposition, events are innate ideas in humans; a theory of complex events (with implications for law and philosophy of law); and an overall picture of syntax and semantics of causal sentences and action sentences. Though Peterson does not pursue them here, there are clear and significant implications for the philosophy of science, in particular for our understanding of scientific causation, causal explanation and law likeness.' Professor William Lycan, University of North Carolina, Chapel Hill 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
Reconfigurable System Design and Verification, 1st edition
Authors: Pao-Ann Hsiung, Marco D. Santambrogio, Chun-Hsian Huang
Venue:  (2009)

Focusing on system-level design and verification techniques, this text allows readers to immediately grasp concepts and put them into practice. It starts with an overview of reconfigurable computing architectures and platforms and demonstrates how to develop reconfigurable systems. This sets up the discussion of the hardware, software, and system techniques that form the core of the text. The authors classify design and verification techniques into primary and secondary categories, allowing the appropriate ones to be easily located and compared. The techniques discussed range from system modeling and system-level design to co-simulation and formal verification. Case studies illustrate real-world applications. Multi Copy
Hardware Reconfiguration Capability for Third-Generation Sensor Nodes
Authors: Ali El Kateeb
Venue: Computer (2009)

Minimizing third-generation sensor nodes' power consumption will be vital to their successful deployment.
An adaptive fault detection scheme for wireless sensor networks
Authors: Jae-Young Choi, Sung-Jib Yim, Yoon Jae Huh, Yoon-Hwa Choi
Venue: Proceedings of the 8th WSEAS International Conference on Software engineering, parallel and distributed systems (2009)

In this paper, we present an adaptive fault detection scheme for wireless sensor networks. It uses local information from neighboring nodes to dynamically adjust critical parameters in distributed fault detection algorithms, resulting in high performance for a wide range of fault probabilities. Computer simulation shows that the scheme is scalable with the number of faulty nodes except for sparse networks where the average node degree is extremely low.
Knowledge Driven Optimization and Finite Element Analysis of Aircraft Structures
Authors: R. Curran, G. Gomis, A. Murphy, S. Castagne, P. Morenton, A. Rothwell
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

The paper presents a knowledge driven methodology for the global integration of aircraft structural design based on structural analysis and manufacturing cost optimization relative to weight. The initial design of a fuselage structure is generated from a numerical solution considering the weight and manufacturing cost of the structure relative to Direct Operating Cost. That baseline configuration is then used as the geometrical definition that is analyzed at a more detailed level using the Finite Element Analysis (FEA) method. Fuselage panels are made of a skin-stringer assembly that locally buckles under normal flight loads. The finite element method has the potential to give a representation of the buckled shape as well as a value for the local critical buckling load of any mode investigated. The paper investigates the potential for adopting a suit of integration tools in the Dassault V5 platform in order to implement an iterative design, structural analysis and optimization process for fuselage panels. It is convenient to use the platform in order to obtain structural data that would then be reused in the optimization workbench built within the platform. Results from the fuselage finite element model are compared to both experimental data and theoretical predictions before being linked to the optimization tool. The fuselage panel is then optimized for minimum weight while still resisting an applied compressive load without buckling. The optimization process parameters are analyzed using statistical methods. It is shown that a fully integrated way of designing and optimizing fuselage panels is achievable. The paper therefore presents a methodology to implement and run an integrated design optimization of a structure loaded in compression. Consequently, the tool facilitates a concurrent engineering approach to the product development phase, both compressing lead time and improving the sharing of relevant multidisciplinary information, which traditionally tends to be carried out in a more serial manner.
Analysis of periodic motions in relay feedback systems with saturation in plant dynamics
Authors: Nikolay Faldin, Alex Morzhov, Igor Boiko
Venue: International Journal of Systems Science (2009)

In this article a method of analysis of possible periodic motions in relay feedback systems that have saturation in plant dynamics is presented. Also, a methodology of analysis of local orbital stability of those periodic motions is proposed. The given analysis is based on the concept of the state locus of a relay feedback system. Techniques for computing the state locus are proposed. Also, a methodology of finding a periodic motion that involves the state locus is given. Finally, the proposed method is illustrated by an example.
The two states of the mind to teach UML
Authors: Luis de-Marcos, Fernando Flores, José-Javier Martínez
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

The University of Alcalá (Spain) and the Lund University (Sweden) have been collaborating for several years in the development of various courses at the in-between of the Computer Science and the Humanities fields. We are trying to join different expertise and to apply it to design new ways of teaching. Within this scope we present here a course that is aimed to teach the Unified Modeling Language (UML) to humanities students.
ASP.NET Data Presentation Controls Essentials: Master the standard ASP.NET server controls for displaying and managing data
Authors: Joydip Kanjilal
Venue:  (2007)

This book shows you how to get the most from the ASP.NET data presentation controls to easily display and manage complex data in your web applications The ASP.NET Data Presentation Controls are server controls to which you can bind data to organize and display it in different ways. This book shows you how to get the most from these controls to easily display and manage complex data in your web applications. It takes you through each of the major data presentation controls in ASP.NET, gets you started using them, and then shows you how to use them in your applications for managing your data. Systematic coverage of major ASP.NET data presentation controls Packed with re-usable examples of common data control tasksCovers LINQ and binding data to ASP.NET 3.5 (Orcas) controls Displaying tables of data with the Repeater, DataGrid, DataList, and GridView controlsDisplaying hierarchical data using ASP.NET data controlsPaging and sorting data using the Repeater, DataGrid, and GridView controlsBinding data to ASP.NET 2.0 controls like ObjectDataSource, AccessDataSource, and XMLDataSource Inserting, Updating, and Deleting data using all major data controls in ASP.NET Exporting GridView control to MS Excel and MS WordExtending the existing data controls to build custom controlsUsing LINQ to bind data to the new data controls introduced in ASP.NET 3.5 (Orcas) This book is for ASP.NET developers who want to display or manage data in ASP.NET applications. The code examples are in C#. 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
Application of modified homotopy perturbation method for solving the augmented systems
Authors: Xinlong Feng, Yinnian He, Jixiang Meng
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, a new approach is proposed for solving the augmented systems. Based on the modified homotopy perturbation method, we construct the new iterative methods and derive the sufficient and necessary conditions for guaranteeing its convergence. Some numerical experiments show that this method is more simple and effective.
On the Quantum Query Complexity of Local Search in&#x00a0;Two and Three Dimensions
Authors: Xiaoming Sun, Andrew Chi-Chih Yao
Venue: Algorithmica (2009)

The quantum query complexity of searching for local optima has been a subject of much interest in the recent literature. For the d-dimensional grid graphs, the complexity has been determined asymptotically for all fixed d&#x2265;5, but the lower dimensional cases present special difficulties, and considerable gaps exist in our knowledge. In the present paper we present near-optimal lower bounds, showing that the quantum query complexity for the 2-dimensional grid [n]2 is &#x03a9;(n 1/2&#x2212;&#x03b4; ), and that for the 3-dimensional grid [n]3 is &#x03a9;(n 1&#x2212;&#x03b4; ), for any fixed &#x03b4;>0. A general lower bound approach for this problem, initiated by Aaronson (based on Ambainis&#x2019; adversary method for quantum lower bounds), uses random walks with low collision probabilities. This approach encounters obstacles in deriving tight lower bounds in low dimensions due to the lack of degrees of freedom in such spaces. We solve this problem by the novel construction and analysis of random walks with non-uniform step lengths. The proof employs in a nontrivial way sophisticated results of S&#x00e1;rk&#x00f6;zy and Szemer&#x00e9;di, Bose and Chowla, and Hal&#x00e1;sz from combinatorial number theory, as well as less familiar probability tools like Esseen&#x2019;s Inequality.
Performance of Bulk Data Dissemination in Wireless Sensor Networks
Authors: Wei Dong, Chun Chen, Xue Liu, Jiajun Bu, Yunhao Liu
Venue: Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems (2009)

Wireless sensor networks (WSNs) have recently gained a great deal of attention as a topic of research, with a wide range of applications being explored. Bulk data dissemination is a basic building block for sensor network applications. The problem of designing efficient bulk data dissemination protocols has been addressed in a number of recent studies. The problem of mathematically analyzing the performance of these protocols, however, has not been addressed sufficiently in the literature. In this work, we show a way of analyzing mathematically the performance of bulk data dissemination protocols in WSNs. Our model can be applied to general networks by use of the shortest propagation path. Our model is accurate by considering topological information, impact of contention, and impact of pipelining. We validate the analytical results through detailed simulations, and we find the analytical results fit well with the simulation results. Further, we demonstrate that the analytical results can be used to aid protocol design for performance optimizations, e.g., page size tuning for shortening the completion time.
Application of Item Response Theory to Collaborative Filtering
Authors: Biyun Hu, Yiming Zhou, Jun Wang, Lin Li, Lei Shen
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

Although many approaches to collaborative filtering have been proposed, few have considered the data quality of the recommender systems. Measurement is imprecise and the rating data given by users is true preference distorted. This paper describes how item response theory, specifically the rating scale model, may be applied to correct the ratings. The theoretically true preferences were then used to substitute for the actual ratings to produce recommendation. This approach was applied to the Jester dataset and traditional k-Nearest Neighbors (k-NN) collaborative filtering algorithm. Experiments demonstrated that rating scale model can enhance the recommendation quality of k-NN algorithm. Analysis also showed that our approach can predict true preferences which k-NN cannot do. The results have important implications for improving the recommendation quality of other collaborative filtering algorithms by finding out the true user preference first.
Taint-based directed whitebox fuzzing
Authors: Vijay Ganesh, Tim Leek, Martin Rinard
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

We present a new automated white box fuzzing technique and a tool, BuzzFuzz, that implements this technique. Unlike standard fuzzing techniques, which randomly change parts of the input file with little or no information about the underlying syntactic structure of the file, BuzzFuzz uses dynamic taint tracing to automatically locate regions of original seed input files that influence values used at key program attack points (points where the program may contain an error). BuzzFuzz then automatically generates new fuzzed test input files by fuzzing these identified regions of the original seed input files. Because these new test files typically preserve the underlying syntactic structure of the original seed input files, they tend to make it past the initial input parsing components to exercise code deep within the semantic core of the computation. We have used BuzzFuzz to automatically find errors in two open-source applications: Swfdec (an Adobe Flash player) and MuPDF (a PDF viewer). Our results indicate that our new directed fuzzing technique can effectively expose errors located deep within large programs. Because the directed fuzzing technique uses taint to automatically discover and exploit information about the input file format, it is especially appropriate for testing programs that have complex, highly structured input file formats.
Transferring experience in reinforcement learning through task decomposition
Authors: Ioannis Partalas, Grigorios Tsoumakas, Konstantinos Tzevanidis, Ioannis Vlahavas
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Transfer learning refers to the process of conveying experience from a simple task to another more complex (and related) task in order to reduce the amount of time that is required to learn the latter task. Typically, in a transfer learning procedure the agent learns a behavior in a source task, and it uses the gained knowledge in order to speed up the learning process in a target task. Reinforcement Learning algorithms are time expensive when they learn from scratch, especially in complex domains, and transfer learning comprises a suitable solution to speed up the training process. In this work we propose a method that decomposes the target task in several instances of the source task and uses them to extract an advised action for the target task. We evaluate the efficacy of the proposed approach in the robotic soccer Keepaway domain. The results demonstrate that the proposed method helps to reduce the training time of the target task.
C preprocessor use in numerical tools: an empirical analysis
Authors: Edward B. Allen, Maheshwar Chandrasekar, Karolina A. Sarnowska
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

The C preprocessor is a significant aspect of C and C++ programming. Ernst, Badros, and Notkin analyzed usage of the C preprocessor by a general set of 26 software packages. This paper extends that work with a case study of eight numerical tools from the Advanced Computational Software (acts) collection.
How Does Multiple-Packet Reception Capability Scale the Performance of Wireless Local Area Networks?
Authors: Ying Jun (Angela) Zhang, Peng Xuan Zheng, Soung Chang Liew
Venue: IEEE Transactions on Mobile Computing (2009)

Due to its simplicity and cost efficiency, wireless local area network (WLAN) enjoys unique advantages in providing high-speed and low-cost wireless services in hot spots and indoor environments. Traditional WLAN medium-access-control (MAC) protocols assume that only one station can transmit at a time: simultaneous transmissions of more than one station cause the destruction of all packets involved. By exploiting recent advances in PHY-layer multiuser detection (MUD) techniques, it is possible for a receiver to receive multiple packets simultaneously. This paper argues that such multipacket reception (MPR) capability can greatly enhance the capacity of future WLANs. In addition, the paper provides the MAC-layer and PHY-layer designs needed to achieve the improved capacity. First, to demonstrate MPR as a powerful capacity-enhancement technique, we prove a "superlinearity” result, which states that the system throughput per unit cost increases as the MPR capability increases. Second, we show that the commonly deployed binary exponential backoff (BEB) algorithm in today's WLAN MAC may not be optimal in an MPR system, and the optimal backoff factor increases with the MPR capability, the number of packets that can be received simultaneously. Third, based on the above insights, we design a joint MAC-PHY layer protocol for an IEEE 802.11-like WLAN that incorporates advanced PHY-layer signal processing techniques to implement MPR.
Robust bounds for classification via selective sampling
Authors: Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reason it can be efficiently run in any RKHS. Unlike previous margin-based semi-supervised algorithms, our sampling condition hinges on a simultaneous upper bound on bias and variance of the RLS estimate under a simple linear label noise model. This fact allows us to prove performance bounds that hold for an arbitrary sequence of instances. In particular, we show that our sampling strategy approximates the margin of the Bayes optimal classifier to any desired accuracy &epsilon; by asking &Otilde; (d/&epsilon;2) queries (in the RKHS case d is replaced by a suitable spectral quantity). While these are the standard rates in the fully supervised i.i.d. case, the best previously known result in our harder setting was &Otilde; (d3/&epsilon;4). Preliminary experiments show that some of our algorithms also exhibit a good practical performance.
A level set framework using a new incremental, robust Active Shape Model for object segmentation and tracking
Authors: Michael Fussenegger, Peter Roth, Horst Bischof, Rachid Deriche, Axel Pinz
Venue: Image and Vision Computing (2009)

Level set based approaches are widely used for image segmentation and object tracking. As these methods are usually driven by low level cues such as intensity, colour, texture, and motion they are not sufficient for many problems. To improve the segmentation and tracking results, shape priors were introduced into level set based approaches. Shape priors are generated by presenting many views a priori, but in many applications this a priori information is not available. In this paper, we present a level set based segmentation and tracking method that builds the shape model incrementally from new aspects obtained by segmentation or tracking. In addition, in order to tolerate errors during the segmentation process, we present a robust Active Shape Model, which provides a robust shape prior in each level set iteration step. For the tracking, we use a simple decision function to maintain the desired topology for multiple regions. We can even handle full occlusions and objects, which are temporarily hidden in containers by combining the decision function and our shape model. Our experiments demonstrate the improvement of the level set based segmentation and tracking using an Active Shape Model and the advantages of our incremental, robust method over standard approaches.
Understanding the impact of offshore outsourcing on information technology positions
Authors: Kewal K. Verma
Venue:  (2008)

Offshore outsourcing, also known as offshoring, of information technology (IT) means moving or relocating computer related business functions to a location outside the country. Improvements in technology, lower labor cost, and rise in skill levels in developing countries such as India have contributed to the shift of IT positions from the United States to developing countries. Consulting and research firms, such as Forrester Research and Mckinsey Company, predicted various job losses in the United States and other Western European nations because of offshoring. Current findings on this topic are controversial. Some studies argued the benefits of offshoring and others presented a gloomy picture. In this dissertation, a quantitative correlational method is used to understand the impact of offshoring of IT positions on technological innovations as well as on quality of life in the United States. The research design included collecting data from various sources including the United States Government web sites, NASSCOM (National Association of Software Service Companies) in India, and a survey instrument. The research findings indicate the statistically significant relationship between offshoring of IT positions and innovation. On the other hand, the study showed weak relationship between number of IT positions offshored and quality of life. The key recommendation of this study is that further investigations are needed to explore the impact of offshoring of other business functions including accounting, human resources, and medicine.