ppxscal/embedding_network huggingface dataset:
Web Service Request Transformatter
Authors: Wei-Chun Chang, Wei-Cheng Teo, Cheng-Chang Oh Yang
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

A tool designed to serve for the transformation of Web service description is described. The fundamentals of service --oriented architecture are heavily relied on the eXtensible Markup Language (XML) to describe the interfaces of web services and the access protocol. The automation process to transform the input of user requests into XML-based representation can facilitate the service composition. We proposed a solution tool to collect user requirements and transform them into XML-based document automatically. The tool is illustrated through a domain-specific task flow.
Option pricing in the presence of random arbitrage return
Authors: Jungmin Choi, Max Gunzburger
Venue: International Journal of Computer Mathematics (2009)

We consider option pricing problems when we relax the condition of no arbitrage in the Black-Scholes model. Assuming random noise in the interest rate process, the derived pricing equation is in the form of stochastic partial differential equation. We used Karhunen-Loeve expansion to approximate the stochastic term and a combined finite difference/finite element method to effect temporal and “spatial” discretization. Computational examples in which the noise is assumed to be a Ornstein-Uhlenbeck process are provided that illustrate not only the discretization methods used, but the type of results relevant to option pricing that can be obtained from the model.
The Art of Lean Software Development: A Practical and Incremental Approach, 1st edition
Authors: Curt Hibbs, Steve Jewett, Mike Sullivan
Venue:  (2009)

This succinct book explains how you can apply the practices of Lean software development to dramatically increase productivity and quality. Based on techniques that revolutionized Japanese manufacturing, Lean principles are being applied successfully to product design, engineering, the supply chain, and now software development. With The Art of Lean Software Development, you'll learn how to adopt Lean practices one at a time rather than taking on the entire methodology at once. As you master each practice, you'll see significant, measurable results. With this book, you will: Understand Lean's origins from Japanese industries and how it applies to software development Learn the Lean software development principles and the five most important practices in detail Distinguish between the Lean and Agile methodologies and understand their similarities and differences Determine which Lean principles you should adopt first, and how you can gradually incorporate more of the methodology into your process Review hands-on practices, including descriptions, benefits, trade-offs, and roadblocks Learn how to sell these principles to management The Art of Lean Software Development is ideal for busy people who want to improve the development process but can't afford the disruption of a sudden and complete transformation. The Lean approach has been yielding dramatic results for decades, and with this book, you can make incremental changes that will produce immediate benefits. "This book presents Lean practices in a clear and concise manner so readers are motivated to make their software more reliable and less costly to maintain. I recommend it to anyone looking for an easy-to-follow guide to transform how the developer views the process of writing good software." -- Bryan Wells, Boeing Intelligence & Security Sytems Mission System "If you're new to Lean software development and you're not quite sure where to start, this book will help get your development process going in the right direction, one step at a time." -- John McClenning, software development lead, Aclara
Centroid defuzzification and the maximizing set and minimizing set ranking based on alpha level sets
Authors: Ying-Ming Wang
Venue: Computers and Industrial Engineering (2009)

Centroid defuzzification and the maximizing set and minimizing set methods are two commonly used approaches to ranking fuzzy numbers and often require membership functions to be known. In this paper, the two methods are reinvestigated when explicit membership functions are not known but alpha level sets are available. Two analytical formulas are derived under the assumption that the exact membership functions can be approximated by using piecewise linear functions based on alpha level sets. The derived analytical formulas are of significant importance and provide very useful decision supports for a wide variety of applications of the two methods in industrial engineering and other areas. Numerical examples are offered to test the derived formulas and illustrate their computational processes and applications in risk assessment of a software development.
MALT-a Multi-lingual Adaptive Language Tutor
Authors: Matthias Scheutz, Michael Heilman, Aaron Wenger, Colleen Ryan-Scheutz
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

We describe a “Multi-lingual Adaptive Language Tutor” (MALT) that uses natural language parsing and text generation to create various kinds of grammar exercises for learners of any language. These exercises can be restricted to specific topics by the instructor such as transformation of verb tenses. MALT generates novel exercises focusing on the specific difficulties of language learners as determined from their past mistakes, helping them overcome individual difficulties faster. We also present the first preliminary results from employing MALT in the foreign language classroom at Notre Dame.
New algorithmic techniques for large scale volumetric data visualization on parallel architectures
Authors: Joseph Jaja
Venue:  (2008)

Volume visualization is widely used as an effective approach for the visual exploration, computational analysis, and manipulation of volumetric datasets. Due to the dramatic advances in imaging instruments and computing technologies, such datasets are now appearing at a very fast rate with increasingly larger sizes in many engineering, science and medical applications. Isosurface and direct volume rendering(DVR) are two of the most widely used techniques to render such datasets. This dissertation introduces novel techniques for rendering isosurfaces and volumes, and extends these techniques to multiprocessor architectures. We first focus on cluster-based techniques for isosurface extraction and rendering using polygonal approximation. We present a new simple indexing scheme and data layout approach, which enable scalable and efficient isosurface generation. This algorithm is the first known parallel algorithm to achieve provable load balancing on multiprocessor systems. We also develop an algorithm to generate isosurfaces using ray-casting on multi-core processors. Our method is based on a hybrid strategy that begins with an object order traversal of the data followed by ray-casting on ordered sets of an adaptive number of subcubes, one set for each small group of pixels on the image. We develop a multithreaded implementation, which uses new dynamic load balancing techniques that start with an image partitioning for the initial stage and then perform dynamic allocation of groups of ray-casting tasks among the different threads. The strategy ensures almost equal loads among the cores while maintaining spatial data locality. This scheme is extended to perform direct volume rendering and is shown to achieve similar improvements in terms of overall performance, load balancing, and scalability. We conduct a large number of tests for all our algorithms on the University of Maryland Visualization Cluster and on the 8-core Clovertown platform using a wide variety of datasets such as Richtmyer-Meshkov Instability dataset (7.5GB for each time step) and Visible Human dataset (&sim;1GB). We obtain results that consistently validate the efficiency and the scalability of our algorithms. In particular, the overall performance of our hybrid ray-casting scheme achieves an interactive rendering rate on high resolution (1024 2) screens for all the datasets tested.
A thresholding method based on two-dimensional fractional differentiation
Authors: A. Nakib, H. Oulhadj, P. Siarry
Venue: Image and Vision Computing (2009)

In this paper, we present a new thresholding technique based on two-dimensional fractional differentiation, that was obtained through the extension of the one-dimensional fractional differentiation. A new geometric interpretation of the two-dimensional fractional differentiation is also presented in the paper. The proposed method exploits the properties and the interpretations of the two-dimensional fractional differentiation. It is based on the assumption that there is a dependency between the pixels' gray-levels, that is translated into a correlation between pixels describing the same object. The effectiveness of the proposed method is demonstrated by using examples from real-world and synthetic images.
Identification and modeling for non-linear dynamic system using neural networks type MLP
Authors: Hernán González Acuña, Max Suell Dutra, Omar Lengerke
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

In control systems, the model dynamics of linear systems is the principal and most important phase of a project, but when working with dynamic of non-linear systems obtain the model becomes a very complex task can be used techniques of system identification. This article show the use of one technique for identification and modeling of dynamic linear systems and nonlinear systems using dynamics neural networks type multilayer perceptron, obtaining approximate results in the identification of non-linear system.
Mind and Body: Dialogue and Posture for Affect Detection in Learning Environments
Authors: Sidney D'mello, Arthur Graesser
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

We investigated the potential of automatic detection of a learner's affective states from posture patterns and dialogue features obtained from an interaction with AutoTutor, an intelligent tutoring system with conversational dialogue. Training and validation data were collected from the sensors in a learning session with AutoTutor, after which the affective states of the learner were rated by the learner, a peer, and two trained judges. Machine learning experiments with several standard classifiers indicated that the dialogue and posture features could individually discriminate between the affective states of boredom, confusion, flow (engagement), and frustration. Our results also indicate that a combination of the dialogue and posture features does improve classification accuracy. However, the incremental gains associated with the combination of the two sensors were not sufficient to exhibit superadditivity (i.e., performance superior to an additive combination of individual channel). Instead, the combination of posture and dialogue reflected a modest amount of redundancy among these channels.
Digital Watermarking and Steganography: Fundamentals and Techniques, 1st edition
Authors: Frank Y. Shih
Venue:  (2007)

In addition to providing students, researchers, and other professionals with mechanical information regarding digital watermarking and steganography, this work also provides them with the framework needed to develop extensive advanced algorithms. It shows how robust high-capacity watermarking techniques can be successfully used to enlarge the hiding capacity while maintaining the robustness of the watermark. Several robust algorithms are presented to illustrate the framework and provide assistance in understanding and implementing fundamental principles. Alternatives to traditional strategies are presented. The principles taught are illustrated with plentiful graphs and examples in order to simplify the problems and make highly complicated theories readily understandable. 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
New mathematical models of axial cutting force and torque in drilling 20MoCr130 stainless steel
Authors: Mihaiela Iliescu, Aurelian Vlase
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Stainless steels represent materials which have known a continuous extend into various and interesting industrial fields application. Most of the time they needs machining and, one important procedure is drilling. The paper present aspects of the experimental research developed in the purpose of determining new and, more adequate, mathematical models of the cutting force and torque, in drilling 20MoCr130 stainless steel. Graphs, as well as further application of the obtained relationships are also, mentioned.
Lifting parameterisation of the 9/7 wavelet filterbank and its application in lossless image compression
Authors: Tilo Strutz
Venue: Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation (2009)

The description of filter banks using lifting structures does not only benefit low-complexity implementation in software or hardware, but is also advantageous for the design of filter banks because of the guaranteed perfect reconstruction property. This paper proposes a new design method for wavelet filter banks, which is explained based on a single lifting structure suitable for 9/7 filter pairs. The modification of the standard design constraints leads to a family of related filter pairs with varying characteristics. The filters are derived directly, the factorisation of known filters is not necessary. The application of the designed filters to lossless image compression is investigated.
Theoretical aspects of the application of convolution quadrature to scattering of acoustic waves
Authors: Antonio R. Laliena, Francisco-Javier Sayas
Venue: Numerische Mathematik (2009)

In this paper we address several theoretical questions related to the numerical approximation of the scattering of acoustic waves in two or three dimensions by penetrable non-homogeneous obstacles using convolution quadrature (CQ) techniques for the time variable and coupled boundary element method/finite element method for the space variable. The applicability of CQ to waves requires polynomial type bounds for operators related to the operator &#x0394; &#x2212; s 2 in the right half complex plane. We propose a new systematic way of dealing with this problem, both at the continuous and semidiscrete-in-space cases. We apply the technique to three different situations: scattering by a group of sound-soft and -hard obstacles, by homogeneous and non-homogeneous obstacles.
Identifying linguistic structure in a quantitative analysis of dialect pronunciation
Authors: Jelena Prokić
Venue: Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop (2007)

The aim of this paper is to present a new method for identifying linguistic structure in the aggregate analysis of the language variation. The method consists of extracting the most frequent sound correspondences from the aligned transcriptions of words. Based on the extracted correspondences every site is compared to all other sites, and a correspondence index is calculated for each site. This method enables us to identify sound alternations responsible for dialect divisions and to measure the extent to which each alternation is responsible for the divisions obtained by the aggregate analysis.
The Handbook of Computer Networks
Authors: Hossein Bidgoli
Venue:  (2007)

The Handbook of Computer Networks is the first single, comprehensive treatment of the subject available. Written by noted author and expert Hossein Bidgoli, this three-volume masterpiece presents an in-depth understanding of computer networks that is broad in scope and practical in application. Each volume covers a wide range of topics with state-of-the-art information, practical applications, and emerging issues. Whether youre an IT manager, researcher, or student, this is the ideal resource on every aspect of networking.
SIMPS: using sociology for personal mobility
Authors: Vincent Borrel, Franck Legendre, Marcelo Dias De Amorim, Serge Fdida
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Assessing mobility in a thorough fashion is a crucial step toward more efficient mobile network design. Recent research on mobility has focused on two main points: analyzing models and studying their impact on data transport. These works investigate the consequences of mobility. In this paper, instead, we focus on the causes of mobility. Starting from established research in sociology, we propose SIMPS, a mobility model of human crowds with pedestrian motion. This model defines a process called sociostation, rendered by two complimentary behaviors, namely socialize and isolate, that regulate an individual with regard to her/his own sociability level. SIMPS leads to results that agree with scaling laws observed both in small-scale and large-scale human motion. Although our model defines only two simple individual behaviors, we observe many emerging collective behaviors (group formation/splitting, path formation, and evolution).
Photoshop For Right-Brainers: The Art of Photomanipulation, 3rd edition
Authors: Al Ward
Venue:  (2009)

Learn how to tap into the creative part of your brain to create amazing digital art in Photoshop CS4. This exciting, full-color guide is designed especially for artists and photographers who want to harness the thrilling potential of the new release of Photoshop. Youll go beyond cookie-cutter techniques and discover unique ideas for creative expression so you can create melting landscapes, perform face lifts, and find other lesser-known effects. Timesaving techniques allow you to devote more time to the creative process.
Application of two non-linear prediction tools to the estimation of tunnel boring machine performance
Authors: S. Yagiz, C. Gokceoglu, E. Sezer, S. Iplikci
Venue: Engineering Applications of Artificial Intelligence (2009)

Predicting tunnel boring machine (TBM) performance is a crucial issue for the accomplishment of a mechanical tunnel project, excavating via full face tunneling machine. Many models and equations have previously been introduced to estimate TBM performance based on properties of both rock and machine employing various statistical analysis techniques. However, considering the nature of the problem, it is relatively difficult to estimate tunnel boring machine performance by linear prediction models. Artificial neural networks (ANNs) and non-linear multiple regression models have great potential for establishing such prediction models. The purpose of the present study is the construction of non-linear multivariable prediction models to estimate TBM performance as a function of rock properties. For this purpose, rock properties and machine data were collected from recently completed TBM tunnel project in the City of New York, USA and consequently the database was established to develop performance prediction models utilizing the ANN and the non-linear multiple regression methods. This paper presents the results of study into the application of the non-linear prediction approaches providing the acceptable precise performance estimations.
When is 'nearest neighbour' meaningful: A converse theorem and implications
Authors: Robert J. Durrant, Ata Kabán
Venue: Journal of Complexity (2009)

Beyer et al. gave a sufficient condition for the high dimensional phenomenon known as the concentration of distances. Their work has pinpointed serious problems due to nearest neighbours not being meaningful in high dimensions. Here we establish the converse of their result, in order to answer the question as to when nearest neighbour is still meaningful in arbitrarily high dimensions. We then show for a class of realistic data distributions having non-i.i.d. dimensions, namely the family of linear latent variable models, that the Euclidean distance will not concentrate as long as the amount of 'relevant' dimensions grows no slower than the overall data dimensions. This condition is, of course, often not met in practice. After numerically validating our findings, we examine real data situations in two different areas (text-based document collections and gene expression arrays), which suggest that the presence or absence of distance concentration in high dimensional problems plays a role in making the data hard or easy to work with.
Interleaved pattern composition and scaffolded learning
Authors: David Ginat
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

One of the essential skills required in the design of computer programs is the composition of design patterns in an interleaved way. We expect both beginners and senior students to demonstrate competence with this skill. Are they competent? Not quite. We found that both novices and seniors demonstrate disturbing difficulties with interleaved pattern composition. In order to address these difficulties, we developed a scaffolding instruction approach, which we applied with students. We display our findings, our approach, and the approach implementation.
PL-Tags: Detecting Batteryless Tags through the Power Lines in a Building
Authors: Shwetak N. Patel, Erich P. Stuntebeck, Thomas Robertson
Venue: Proceedings of the 7th International Conference on Pervasive Computing (2009)

We present a system, called PL-Tags, for detecting the presence of batteryless tags in a building or home through the power lines. The excitation (or interrogation) and detection of these tags occurs wirelessly entirely using the powerline infrastructure in a building. The PL-Tags proof-of-concept consists of a single plug-in module that monitors the power line for the presence of these tags when they are excited. A principal advantage of this approach is that it requires very little additional infrastructure to be added to a space, whereas current solutions like RFID require the deployment of readers and antennas for triggering tags. An additional benefit of PL-Tags is that the tags are wirelessly excited using an existing phenomenon over the power line, namely electrical transient pulses that result from the switching of electrical loads over the power line. We show how these energy rich transients, which occur by simply turning on a light switch, fan, television, etc., excite these tags and how they are detected wirelessly over the power line. We contend that the PL-Tag system is another class of potential batteryfree approaches researchers can use for building pervasive computing applications that require minimal additional infrastructure.