ppxscal/embedding_network huggingface dataset:
Plenary lecture 2: statistical performance analysis of communications channels in real-time
Authors: Stamatios Kartalopoulos
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

Measuring the performance of communication channels is very critical for service availability, service performance sustainability, as well as quality of service in telecommunication Networks. One of the key metrics is the Bit Error Performance (BER), which is measured using complex and expensive instruments, and bit error detecting correcting codes (EDC) embedded in the signal of the information channel. However, EDCs are although indispensable for their bit error correcting ability, require many frames of information to provide a good statistical BER value for each channel. In this lecture, we describe a statistical analytical method based on which we estimate synchronously the performance parameters of all incoming communication channels in microseconds and thus in real-time. This method provides estimation of BER, SNR, NF, Q, and min-max signal levels of current and previous values. In addition, we describe the realization of the method with a simple CMOS circuit. We also describe the benefits of the method and compare with well-established methods.
Surprising parser actions and reading difficulty
Authors: Marisa Ferrara Boston, John Hale, Reinhold Kliegl, Shravan Vasishth
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

An incremental dependency parser's probability model is entered as a predictor in a linear mixed-effects model of German readers' eye-fixation durations. This dependency-based predictor improves a baseline that takes into account word length, n-gram probability, and Cloze predictability that are typically applied in models of human reading. This improvement obtains even when the dependency parser explores a tiny fraction of its search space, as suggested by narrow-beam accounts of human sentence processing such as Garden Path theory.
Variability modeling to support customization and deployment of multi-tenant-aware Software as a Service applications
Authors: Ralph Mietzner, Andreas Metzger, Frank Leymann, Klaus Pohl
Venue: Proceedings of the 2009 ICSE Workshop on Principles of Engineering Service Oriented Systems (2009)

More and more companies are offering their software by following the Software as a Service (SaaS) model. The promise of the SaaS model is to exploit economies of scale on the provider side by hosting multiple customers (or tenants) on the same hardware and software infrastructure. However, to attract a significant number of tenants, SaaS applications have to be customizable to fulfill the varying functional and quality requirements of individual tenants. In this paper, we describe how variability modeling techniques from software product line engineering can support SaaS providers in managing the variability of SaaS applications and their requirements. Specifically, we propose using explicit variability models to systematically derive customization and deployment information for individual SaaS tenants. We also demonstrate how variability models could be used to systematically consider information about already deployed SaaS applications for efficiently deploying SaaS applications for new tenants. We illustrate our approach by a running example for a meeting planning application.
Study of detonation process: numerical approach
Authors: Jerzy Malachowski
Venue: Proceedings of the 2nd conference on European computing conference (2008)

This paper is based on non-linear finite element analysis of the effects of the blast wave on structures, caused by the detonation of explosive materials. Dynamic response of a pipeline subjected to the shock wave produced by the detonation of high explosive materials is presented in this paper. Coupled Euler and Lagrange formulation are used in the finite element analysis of such problems to accurately represent the detonation phenomenon. Preliminary results allow for detailed analysis of the blast wave propagation and its influence on the pipeline.
Comparing Chinese and German blogs
Authors: Thomas Mandl
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Blogs in different countries do not only differ in the language of their texts but in many other aspects as well. This study explores how these differences can be identified and related to known cultural differences. A thorough intellectual analysis of several hundreds of blog pages from China and Germany revealed culturally diverse patterns. Chinese blogs are more graphically oriented. They emphasize the communication between bloggers and commentators. Especially, the distinction between high and low context communication in both cultures seems to have a large impact on the blog communication.
Simulation and characterization of inter-process interference on multithreaded and multicore architectures
Authors: Daniel Connors
Venue:  (2008)

As limitations on design complexity and the twin problems of power and heat limit performance gains in single-context architectures, designers have increasingly turned to multithreaded and multicore designs to achieve higher process throughput. In fact, such designs are virtually ubiquitous in the PC, server, and increasingly even in the low-power and embedded markets. When independent processes run simultaneously on such systems, the performance is dependent on the competition for shared resources. Understanding and measuring this interference has many applications throughout the design process and in optimizing the performance of implemented hardware. Unfortunately, directly measuring each combination of program behaviors is effectively impossible due to the prohibitively large number of possible combinations. Further compounding the problem is that applications rarely exhibit monolithic behavior throughout their execution and there are no limitations on the relative position of co-scheduled processes.This work presents a methodology for developing performance models of multithreaded and multicore architectures through a three step process. First, highly efficient and accurate sampled architectural simulation is performed through a technique called Co-Phase Guided, Small-Sample Simulation which can also be applied to single context architectures. Data from simulation is used to characterize a small subset of possible behaviors which is then used to develop mathematical models which are used to predict the behaviors of unmeasured co-phases. Finally, a mathematical model is used to determine the contribution of each possible co-phase across all possible process offsets. Together, these techniques allow extremely fast characterization of multithreaded and multicore systems which is vital during design space exploration and in analyzing real systems.
A Kind of Instruction-Learning Model Division Method Based on Information Technology
Authors: Yongjiang Zhong, Shaochun Zhong, Jiaying Tong, Yamei Zhang
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

At present, the information technology played an important role in elementary and middle schools' elementary education application aspect, but one reason is insufficient research on teaching and learning style based on the information technology. This article summarizes existent teaching and learning models, proposes one new teaching and learning style analysis method based on the usage of information technology. We propose the analysis method incorporating network usage, cooperation style, independence degree three dimensions. Our results help to improve modern teaching and learning planning.
On the parameters estimation of the Duffing system by systems synchronization
Authors: C. Aguilar-Ibañez, E. Hernáadez-Rubio, M. S. Suárez-Castañón, A. Barrañón
Venue: Proceedings of the 1st WSEAS international conference on Nanotechnology (2009)

The Lyapunov based approach for synchronizing and identifying the unknown parameters in the Duffing system is presented in this paper. The strategy consists of proposing a slave system which has to follow asymptotically the desired Duffing system. The gains of the slave system are adjusted continually according to a convenient adaptation control law, until the measurable output error converges to zero. The convergence analysis is carried out by using Barbalat's Lemma.
Locally Adjusted Robust Regression for Human Age Estimation
Authors: Guodong Guo, Yun Fu, Thomas S. Huang, Charles R. Dyer
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Automatic human age estimation has considerable potential applications in human computer interaction and multimedia communication. However, the age estimation problem is challenging. We design a locally adjusted robust regressor (LARR) for learning and prediction of human ages. The novel approach reduces the age estimation errors significantly over all previous methods. Experiments on two aging databases show the success of the proposed method for human aging estimation.
An Introduction to Programming with Java Applets, 3rd edition
Authors: Elizabeth Sugar Boese
Venue:  (2009)

An Introduction to Programming with Java Applets provides a clear introduction to the art of programming for the one-term course. It prepares students with the tools they need to create sophisticated programs efficiently and with ease. Boese assumes no prior programming knowledge, and begins with an introduction to computing, then gradually moves into programming, giving students the opportunity to create their own programs. The text focuses on the essentials and places more detailed information in "Advanced Concept" sections for those who would like to delve deeper into particular concepts. With numerous practice exercises and an accompanying student-learning Web site, Introduction to Programming with Java Applets is the clear choice for your introductory course!
The WordNet Weaver: Multi-criteria Voting for Semi-automatic Extension of a Wordnet
Authors: Maciej Piasecki, Bartosz Broda, Michał Marcińczuk, Stan Szpakowicz
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

The WordNet Weaver application supports extension of a new wordnet. One of its functions is to suggest lexical units semantically close to a given unit. Suggestions arise from activation-area attachment --- multi-criteria voting based on several algorithms that score semantic relatedness. We present the contributing algorithms and the method of combining them. Starting from a manually constructed core wordnet and a list of over 1000 units to add, we observed a linguist at work.
Contexts in Educational Topic Maps
Authors: Christo Dichev, Darina Dicheva
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper explores the idea of using contexts to support more efficient information search in Topic Maps-based digital libraries. The notion of context is perceived as abstraction of grouping of domain concepts and resources based on the existing semantic relationships between them. The proposed model of context is used for context representation in the TM4L environment.
Qualitative Assessment of Video Stabilization and Mosaicking Systems
Authors: Chao Zhang, Prakash Chockalingam, Ankit Kumar, Peter Burt, Arvind Lakshmikumar
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Image stabilization is a key preprocessing step in dynamic image analysis, which deals with the removal of unwanted motion in a video sequence. It is principally understood as the warping of video sequences resulting in a total or partial removal of image motion. Stabilization is invaluable for motion analysis, structure from motion, independent motion detection, geo-registration and mosaicking, autonomous vehicle navigation, model-based compression, and many others. Given the usefulness of image stabilization for many applications, a variety of algorithms have been proposed to perform this task, and many real-time systems have been built to stabilize the real-time videos and provide motion data for tracking and geo-registrations. However, even though there are on-line libraries that provide test videos, there has been no established methods or industrial standards based on which the performance of a stabilization algorithm or system can be measured. This paper aims to address this gap and suggests an evaluation methodology which would provide us the ability to qualitatively measure the performance of a given stabilized system. We propose a performance measurement system and define the performance metrics in this paper. We then apply the assessment to two typical stabilization systems. The discussed methods can be used to benchmark video stabilization systems.
Brief paper: Robust adaptive observer for nonlinear systems with unmodeled dynamics
Authors: Yusheng Liu
Venue: Automatica (Journal of IFAC) (2009)

Unmodeled dynamics exist in almost all applications of observers due to the impossibility of using exact and detailed models. It is highly desired that the observers can dominate the effects of unmodeled dynamics independently to prevent the state estimations from diverging and to get the precise estimations. Based on adaptive nonlinear damping, this paper presents a robust adaptive observer for multiple-input multiple-output nonlinear systems with unknown parameters, uncertain nonlinearities, disturbances and unmodeled dynamics. The observer only has one adaptive parameter no matter how high the order of the system is and how many unknown parameters there are. With the proposed observer, neither estimating the unknown parameters or solving linear matrix inequalities is needed. It is shown that the state estimation error is uniformly bounded and can be made arbitrarily small.
A revised r*-tree in comparison with related index structures
Authors: Norbert Beckmann, Bernhard Seeger
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

In this paper we present an improved redesign of the R*-tree that is entirely suitable for running within a DBMS. Most importantly, an insertion is guaranteed to be restricted to a single path because re-insertion could be abandoned. We re-engineered both, subtree choice and split algorithm, to be more robust against specific data distributions and insertion orders, as well as peculiarities often found in real multidimensional data sets. This comes along with a substantial reduction in CPU-time. Our experimental setup covers a wide range of different artificial and real data sets. The experimental comparison shows that the search performance of our revised R*-tree is superior to that of its three most important competitors. In comparison to its predecessor, the original R*-tree, the creation of a tree is substantially faster, while the I/O cost required for processing queries is improved by more than 30% on average for two- and three-dimensional data. For higher dimensional data, particularly for real data sets, much larger improvements are achieved.
Classification Based on Hybridization of Parametric and Nonparametric Classifiers
Authors: Probal Chaudhuri, Anil K. Ghosh, Hannu Oja
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

Parametric methods of classification assume specific parametric models for competing population densities (e.g., Gaussian population densities can lead to linear and quadratic discriminant analysis) and they work well when these model assumptions are valid. Violation in one or more of these parametric model assumptions often leads to a poor classifier. On the other hand, nonparametric classifiers (e.g., nearest-neighbor and kernel-based classifiers) are more flexible and free from parametric model assumptions. But, the statistical instability of these classifiers may lead to poor performance when we have small numbers of training sample observations. Nonparametric methods, however, do not use any parametric structure of population densities. Therefore, even when one has some additional information about population densities, that important information is not used to modify the nonparametric classification rule. This paper makes an attempt to overcome these limitations of parametric and nonparametric approaches and combines their strengths to develop some hybrid classification methods. We use some simulated examples and benchmark data sets to examine the performance of these hybrid discriminant analysis tools. Asymptotic results on their misclassification rates have been derived under appropriate regularity conditions.
Discovering and securing shared resources on the internet
Authors: Bobby Bhattacharjee, Neil Spring
Venue:  (2008)

The Internet is a collection of shared resources. Internet users share bandwidth and processing resources both in the network at routers and on the network&rsquo;s edge at servers. However, the Internet&rsquo;s architecture does not prevent nodes from consuming disproportionate resources. In practice, resource exhaustion does occur due to inefficiently scaling systems, selfish resource consumption, and malicious attack. The current Internet architecture has limited support for both securing and identifying shared Internet resources. This dissertation has two main contributions. First, I demonstrate the existence of end-host protocols that protect the availability of shared Internet resources. I consider resource sharing with respect to cooperative, selfish, and malicious user models, and for each case design a protocol that protects resource availability without modifying the existing Internet infrastructure. Second, I design and validate measurement techniques for discovering shared Internet resources including links and routers. Specifically, I improve the completeness and accuracy of resource maps by combining embedding probes, disjunctive logic programming, and information from the record route IP option. We validate and quantify the improvement of our maps by comparison to publicly available research networks.
Intelligent Automation in Collaborative Systems
Authors: Joshua Introne, Richard Alterman
Venue: Proceeding of the 2006 conference on Cooperative Systems Design: Seamless Integration of Artifacts and Conversations -- Enhanced Concepts of Infrastructure for Communication (2006)

Intelligent automation has been a source of research and debate within the design community for several decades. When adding intelligent automation to single-user systems, two critical issues must be addressed. First, sufficient knowledge must be acquired about the user and her context to make high-level inferences at runtime. Second, the automation must be useful and delivered in a manner that does not impair the user's domain activity. These issues are equally relevant for collaborative systems. However, collaborative systems offer a potential solution to these problems by virtue of their privileged position as mediating artifacts within a collaborative process. Because coordination information must be exchanged through the system, there is an opportunity for the system to gain insights into user activities and context. Because mediating artifacts add structure to the information that passes through them to improve coordination, this information is made more accessible to standard AI algorithms. Thus, within a design solution for coordination problems in groupware, a solution to some of the issues with intelligent automation can also be found. Empirical evidence from a testbed domain is presented that validates this approach, along with a discussion of how the approach can be generalized to other collaborative systems.
Computational Upscaling of Inertia Effects from Porescale to Mesoscale
Authors: Małgorzata Peszyńska, Anna Trykozko, Kyle Augustson
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We propose algorithms for computational upscaling of flow from porescale (microscale) to lab scale (mesoscale). In particular, we solve Navier-Stokes equations in complex pore geometries and average their solutions to derive properties of flow relevant at lab scale such as permeability and inertia coefficients. We discuss two variants of traditional discretizations: a simple algorithm which works well in periodic isotropic media and can be used when coarse approximations are needed, and a more complex one which is well suited for nonisotropic geometries. Convergence of solutions and averaging techniques are major concerns but these can be relaxed if only mesoscopic parameters are needed. The project is a proof-of-concept computational laboratory for porous media which delivers data needed for mesoscale simulations by performing microscale computational simulations. 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
Information integration: the semantic-model approach
Authors: Rada Chirkova
Venue:  (2008)

This dissertation describes a multiple-coordinator system for large-scale information integration and interoperability, presents algorithms for query processing and optimization based on semantic-model approach, and experimentally evaluates the algorithms on real-life and synthetic data. In addition to supporting gradual large-scale information integration and efficient inter-source processing, the semantic-model approach eliminates the need for mediation in deriving the global schema, thus addressing the main limitation of information-integration systems. This dissertation focuses on performance-related characteristics of several alternative approaches proposed for efficient query processing in the semantic-model environment. The theoretical results and practical algorithms are of independent interest and can be used in any information-integration system that avoids loading all the data into a single repository. Query-processing approaches proposed in this dissertation are applicable both to the original stored data and to materialized views, including restructured views, which are a framework for representing, e.g., the pivot operation available in many database-management systems. These approaches account for the practical issues of information overlap across data sources and of inter-source processing. While most of these algorithms are platform- and implementation-independent, XML-specific optimization techniques that allow for system-level tuning of query-processing performance are proposed as well. Finally, using real-life datasets and the implementation of an information-integration system shell, this dissertation provides experimental results that demonstrate that these algorithms are efficient and competitive in the information-integration setting.
Doppler spectrum estimation by Ramanujan-Fourier Transform (RFT)
Authors: Mohand Lagha, Messaoud Bensebti
Venue: Digital Signal Processing (2009)

This work deals with the spectrum parameters estimation of a weather radar signal, namely velocity, variance and spectrum width. A new tool - based on the Ramanujan sums, c"q(n), which come from the arithmetic functions of the number theory - has been introduced in signal processing. As compared to pulse pair and Fourier algorithms, new results have been obtained by the use of the Ramanujan-Fourier Transform (RFT) for the Doppler spectrum estimation of a real weather data provided by terminal pulse Doppler radar (WSR-88D).