ppxscal/embedding_network huggingface dataset:
Large area nanosize array stamp for UV-based nanoimprint lithography fabricated by size reduction process
Authors: Xiaoli Li, Qingkang Wang, Jing Zhang, Weimin Zhou, Yanbo Liu, Yongzhong Wan, Xiaoming Niu
Venue: Microelectronic Engineering (2009)

A novel size reduction process using electron beam lithography (EBL) combining with wet etching technique is developed as a possible solution for producing large area and low cost nanopattern stamp for UV-based nanoimprint lithography (UV-NIL). In the first step, a microstructure stamp with 1.4@mm periodical pore array and aspect ratio of 1:1 was formed over a 1inch^2 area on a quartz substrate. This process was carried out using common electron beam lithography (EBL) equipment, which was easily available in the modern integrated circuits (IC) semiconductor factory. Afterwards, with a controlled wet etching technique, the pore array was changed into tip patterns with the line width below 100nm and the period keeping as before. The uniformities and nanopattern accuracies were investigated to identify its possibility as a UV-NIL stamp by AFM and SEM. Finally, as a demonstration, the as obtained stamp was used as a positive stamp to replicate the nanotips into UV-curable resist successfully by a UV-NIL process. The method developed for the mold of nanoimprint lithography would be a simple and low price approach to fabricate large area UV-NIL stamp and the nanotip array structures would be widely used in two dimensional (2D) photonic crystal application.
A Personal Information Protection Model for Web Applications by Utilizing Mobile Phones
Authors: Michiru Tanaka, Jun Sasaki, Yutaka Funyu, Yoshimi Teshigawara
Venue: Proceeding of the 2008 conference on Information Modelling and Knowledge Bases XIX (2008)

In this paper, we propose a ring type information transfer model for improving personal information leakage problems on web based services. In order to materialize the model, we propose an applied method by utilizing mobile phones and matrix codes. In addition, we discuss leakage risks of the proposal method and show that the proposed method can reduce troubles on personal information leakage without changing user terminal environments.
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Authors: Linli Xu, Martha White, Dale Schuurmans
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unification of several supervised and unsupervised training principles through the concept of optimal reverse prediction: predict the inputs from the target labels, optimizing both over model parameters and any missing labels. In particular, we show how supervised least squares, principal components analysis, k-means clustering and normalized graph-cut can all be expressed as instances of the same training principle. Natural forms of semi-supervised regression and classification are then automatically derived, yielding semi-supervised learning algorithms for regression and classification that, surprisingly, are novel and refine the state of the art. These algorithms can all be combined with standard regularizers and made non-linear via kernels.
Visual software evolution reconstruction
Authors: Marco D'Ambros, Michele Lanza
Venue: Journal of Software Maintenance and Evolution: Research and Practice (2009)

The analysis of the evolution of large software systems is challenging for many reasons, such as the retrieval and processing of historical information and the large quantity of data that must be dealt with. While recent advances in research have led to the solutions to these problems, a central question remains: How do we deal with this information in a methodical way and where do we start with our analysis? We present a methodology based on interactive visualizations that support the reconstruction of the evolution of software systems. We propose several visualizations which help us to perform software evolution analysis of a system &lsquo;in the large&rsquo; and &lsquo;in the small&rsquo;, and apply them to two large systems. Copyright &copy; 2009 John Wiley & Sons, Ltd. The analysis of the evolution of large software systems is challenging for many reasons, such as the retrieval and processing of historical information and the large quantity of data that must be dealt with. We present a methodology based on interactive visualizations which support the reconstruction of the evolution of software systems. We propose several visualizations which help us to perform software evolution analysis of a system &lsquo;in the large&rsquo; and &lsquo;in the small&rsquo;, and apply them to two large systems. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Creating Contexts for Productive Peer Collaboration: Some Design Considerations
Authors: Amanda Harris, Rosemary Luckin, Nicola Yuill
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

Building technology enhanced learning contexts that work involves increasing our understanding of how we can model learners affective and cognitive profiles, the contexts within which they learn and the interactions between learner and context. In this paper we provide evidence that can inform the design of both models of learners and of their context. We explore the impact of children's goal orientation upon their collaborative interactions whilst completing computer-based tasks. This work suggests that mastery goals engender a willingness to engage in the process of argumentation and discussion that is an important feature of effective collaborative learning. By contrast, performance goals lead learners to try and demonstrate their ability using their collaborative partner to affirm their own competence. This work informs the design of motivational learner models in collaborative contexts. In addition, we found that it is possible to encourage a particular goal orientation in a learner through manipulations to the task presentation, and in so doing to engender more productive styles of collaborative interaction. This finding informs the design of the collaborative context.
Service invocation triggers: a lightweight routing infrastructure for decentralised workflow orchestration
Authors: Walter Binder, Ion Constantinescu, Boi Faltings
Venue: International Journal of High Performance Computing and Networking (2009)

Traditional, centralised workflow orchestration often leads to inefficient routing of messages. To solve this problem, we present a novel scheme to execute workflows in a fully decentralised way. We introduce service invocation triggers, a lightweight infrastructure that routes messages directly from the producing service to the consuming one, enabling fully decentralised workflow orchestration. An evaluation confirms that decentralised orchestration can significantly reduce the network traffic when compared with centralised orchestration.
AIDE: ad-hoc intents detection engine over query logs
Authors: Yunliang Jiang, Hui-Ting Yang, Kevin Chen-chuan Chang, Yi-Shin Chen
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

While keyword queries have become the "standard" query language of web search and many other database applications, their brevity and unstructuredness make it difficult to detect what users really want. In this demonstration, we aim to detect such hidden query intents, which we define as the frequent phrases that users co-ask with the query term, by exploring query logs. Toward building an online search system AIDE, we offer users the function to detect general and unique intents using arbitrary ad-hoc queries at run time. We will also demonstrate the effectiveness of the system which achieves indexing and searching over 14M MSN query log records.
Mathematical and Statistical Methods for Insurance and Finance, 1st edition
Authors: Cira Perna, Marilena Sibillo
Venue:  (2007)

The interaction between mathematicians and statisticians reveals to be an effective approach to the analysis of insurance and financial problems, in particular in an operative perspective. The Maf2006 conference, held at the University of Salerno in 2006, had precisely this purpose and the collection here published gathers some of the papers presented at the conference and successively worked out to this aim. They cover a wide variety of subjects in insurance and financial fields, all treated in light of the successful cooperation between the two quantitative methods.
A hybrid approach to mining frequent sequential patterns
Authors: Erich Allen Peterson, Peiyi Tang
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

The mining of frequent sequential patterns has been a hot and well studied area---under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)---for well over a decade. Yet researchers are still uncovering interesting problems, new algorithms, and ways to improve upon existing methods. In this paper, we marry state-of-the-art frequent sequential pattern mining algorithms (e.g., SPAM, FOF, PrefixSpan), data structures (e.g., aggregate tree, bitmap), and other tried-and-true methods for candidate generation (e.g., apriori), in an attempt to derive a new algorithm with the best qualities of the aforementioned algorithms. In this paper, we disseminate the new algorithm created, lessons learned, and future work to be done.
Design and performance analysis of an inductive QoS routing algorithm
Authors: Abdelhamid Mellouk, Saïd Hoceïni, Sherali Zeadally
Venue: Computer Communications (2009)

Routing mechanism is key to the success of large-scale, distributed communication and heterogeneous networks. Consequently, computing constrained shortest paths is fundamental to some important network functions such as QoS routing and traffic engineering. The problem of QoS routing with multiple additive constraints is known to be NP-complete but researchers have been designing heuristics and approximation algorithms for multi-constrained paths algorithms to propose pseudo-polynomial time algorithms. This paper introduces a polynomial time approximation quality of service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize lexicographically various QoS criteria. The originality of our approach is based on the fact that our system is capable to take into account the dynamics of the network where no model of the network dynamics is assumed initially. Our approach samples, estimates, and builds the model of pertinent aspects of the environment which is very important in heterogeneous networks. The algorithm uses a model that combines both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Multiple paths are searched in parallel to find the K best qualified ones. To improve the overall network performance, a load adaptive balancing policy is defined and depends on a dynamic traffic path probability distribution function. We conducted a performance analysis of the proposed QoS routing algorithm using OPNET based on a platform simulated network. The obtained results demonstrate substantial performance improvements as well as the benefits of learning approaches over networks with dynamically changing traffic.
Stress smoothing in hexaedrons using artificial neural networks
Authors: Leonardo Ivirma, Mary Vergara, Sebastian Provenzano, Francklin Rivas, Anna Perez, Francisco Fuenmayor
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

In this paper it is presented the use of artificial neural networks to improve the stress fields obtained from the finite element discretization method. It was significantly reduced the time needed to reach solutions, with accuracy similar to the areas stress smoothing methods: Superconvergent Patch Recovered (SPR) and Recovery by Equilibrium Patches (REP) improved. It is solved two cases that show the comparative advantages in terms of time spent by the neural network and the techniques described above for making improvements in the original solution: Artificial Neural Networks used only 7% and 70% respectively of the original time spent by the smoothing technique in such cases. As bigger is the magnitude of the problem, the greater the difference in the time required for the solutions, being better the neural network. Data used for this study come from cases of different features: with a smooth solution, a thick wall sphere exposed to inner pressure and one with singularities, a plate loaded with a lateral crack.
Manual Collaboration Systems: Decision Support or Support for Situated Choices
Authors: Reeva Lederman, Robert B. Johnston
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

This paper challenges the idea of calling the activity that occurs in many collaborative systems “decision making”. It suggests that the term decision-making implies a level of deliberation which does not appear to reflect the reality of how activity takes place in these systems. To examine this, the paper selects a type of system discussed previously in the CSCW literature, a whiteboard based scheduling system in an intensive care ward. It finds in fact that much of the activity that occurs in this system is reactive and routine. It shows why the design of this system reduces the need for actors to evaluate choices (when choosing is the hallmark of decision making) and instead allows activity to take place routinely through situated choices.
Attuning speech-enabled interfaces to user and context for inclusive design: technology, methodology and practice
Authors: Mark A. Neerincx, Anita H. M. Cremers, Judith M. Kessens, David A. van Leeuwen, Khiet P. Truong
Venue: Universal Access in the Information Society (2009)

This paper presents a methodology to apply speech technology for compensating sensory, motor, cognitive and affective usage difficulties. It distinguishes (1) an analysis of accessibility and technological issues for the identification of context-dependent user needs and corresponding opportunities to include speech in multimodal user interfaces, and (2) an iterative generate-and-test process to refine the interface prototype and its design rationale. Best practices show that such inclusion of speech technology, although still imperfect in itself, can enhance both the functional and affective information and communication technology-experiences of specific user groups, such as persons with reading difficulties, hearing-impaired, intellectually disabled, children and older adults.
Auralization: Fundamentals of Acoustics, Modelling, Simulation, Algorithms and Acoustic Virtual Reality, 1st edition
Authors: Michael Vorlnder
Venue: Rwthedition (2007)

Auralization is the creation of audible acoustic sceneries from computer-generated data. The term "auralization" is to be understood as being analogue to the well-known technique of "visualization". In visual illustration of scenes, data or any other meaningful information, in movie animation and in computer graphics, we describe the process of "making visible" as visualization. In acoustics, auralization is taking place when acoustic effects, primary sound signals or means of sound reinforcement or sound transmission, are processed to be presented by using electro-acoustic equipment. This book is organized as comprehensive collection of basics, methodology and strategies of acoustic simulation and auralization. With mathematical background of advanced students the reader will be able to follow the main strategy of auralization easily and work own implementations of auralization in various fields of applications in acoustic engineering, sound design and virtual reality. For readers interested in basic research the technique of auralization may be useful to create sound stimuli for specific investigations in linguistic, medical, neurological and psychological research and in the field of human-machine interaction.
An Introduction to Numerical Methods using MathCAD 14
Authors: K. A. Ansari
Venue:  (2008)

An Introduction to Numerical Methods using Mathcad is designed to be used in any introductory level numerical methods course. It provides excellent coverage of numerical methods while simultaneously demonstrating the general applicability of Mathcad to problem solving. This textbook also provides a reliable source of reference material to practicing engineers and scientists and in other junior and senior-level courses where Mathcad can be effectively utilized as a software tool in problem solving. A principal goal of this book is to furnish the background needed to create Mathcad documents for the generation of solutions to a variety of problems. Specific applications involving root-finding, interpolation, curve-fitting, matrices, derivatives, integrals and differential equations are discussed and the broad applicability of Mathcad demonstrated. Wherever appropriate, the use of Mathcad functions offering shortcuts and alternatives to otherwise long and tedious numerical solutions is also demonstrated. At the end of every chapter a set of problems is included to be solved covering the material presented. A solutions manual to these exercises can be made available to instructors. K. Akbar Ansari is a professor of mechanical engineering at Gonzaga University. He is currently involved in teaching courses in engineering mechanics, numerical methods, advanced engineering mathematics, vibrations, system dynamics and controls and machine design. Table of Contents Preface 1. Basics of Mathcad 2. Introduction to Numerical Methods 3. Roots of Equations 4. Matrices and Linear Algebra 5. Numerical Interpolation 6. Curve Fitting 7. Numerical Differentiation 8. Numerical Integration 9. Numerical Solution of Ordinary Differential Equations 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
Computer Supported Ubiquitous Learning Environment for Japanese Mimicry and Onomatopoeia with Sensors
Authors: Hiroaki Ogata, Tomoo Kondo, Chengjiu Yin, Yuqin Liu, Yoneo Yano
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This paper proposes a computer supported ubiquitous learning environment for language learning. Especially, this paper describes context-aware language-learning support system for learning Japanese mimicry and onomatopoeia (MIO) words, which is called JAMIOLAS (Japanese Mimicry and Onomatopoeia Learning Assisting System). This system provides learner the appropriate MIO expressions deriving the learner's situation and sensor data. Phidgets is used as sensors in order to get real-world data from the physical world, e.g., temperature, humidity, etc. This paper describes the implementation, the interface and usage scenario of JAMIOLAS.
On the Cubicity of Interval Graphs
Authors: L. Sunil Chandran, Mathew C. Francis, Naveen Sivadasan
Venue: Graphs and Combinatorics (2009)

A k-cube (or &#x201c;a unit cube in k dimensions&#x201d;) is defined as the Cartesian product $$R_1 \times \cdots \times R_k$$where R i (for 1&#x00a0;&#x2264;&#x00a0;i&#x00a0;&#x2264;&#x00a0;k) is an interval of the form [a i , a i &#x00a0;+&#x00a0;1] on the real line. The k-cube representation of a graph G is a mapping of the vertices of G to k-cubes such that the k-cubes corresponding to two vertices in G have a non-empty intersection if and only if the vertices are adjacent. The cubicity of a graph G, denoted as cub(G), is defined as the minimum dimension k such that G has a k-cube representation. An interval graph is a graph that can be represented as the intersection of intervals on the real line - i.e., the vertices of an interval graph can be mapped to intervals on the real line such that two vertices are adjacent if and only if their corresponding intervals overlap. We show that for any interval graph G with maximum degree &#x0394;, $${\rm cub} (G) \leq\lceil\log_2 \Delta\rceil +4$$. This upper bound is shown to be tight up to an additive constant of 4 by demonstrating interval graphs for which cubicity is equal to $$\lceil\log_2 \Delta\rceil$$.
An alignment based system for chord sequence retrieval
Authors: Pierre Hanna, Matthias Robine, Thomas Rocher
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Music retrieval systems for Western tonal music digital ibraries have to consider rhythmic, timbral, melodic and harmonic information. Most existing retrieval systems only take into account melodies. Melody comparison may induce errors since two musical pieces can be very similar whereas their melodies may differ in a significant way. In this paper, we propose to investigate and experiment a retrieval system based on the comparison of chord progressions. The definition of chords may be ambiguous but their properties can be precisely described and represented. We detail the adaptations of alignment algorithms, successfully applied for the estimation of symbolic melodic similarity, for chord progression retrieval. Several experiments, performed on symbolic databases, show that the system described is robust to variations and outperforms a recent chord retrieval system.
Investigating Stories in a Formal Dialogue Game
Authors: Floris Bex, Henry Prakken
Venue: Proceeding of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008 (2008)

In this paper we propose a formal dialogue game in which two players aim to determine the best explanation for a set of observations. By assuming an adversarial setting, we force the players to advance and improve their own explanations as well as criticize their opponent's explanations, thus hopefully preventing the well-known problem of 'tunnel vision'. A main novelty of our approach is that the game supports the combination of argumentation with abductive inference to the best explanation.
Georeferencing image points using visual pose estimation and DEM
Authors: Xavier Mateo, Xavier Binefa
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

In this paper a new method for the georeferencing of low-oblique images is presented. Our georeferencing approach is based on the estimation of the camera pose and the subsequent use of geographical data in order to find global coordinates for every pixel in the image. For this purpose, concepts like Ground Control Point (GCP) or Digital Elevation Model (DEM) are explained and applied, achieving good results in real situations.
Spectral clustering based on the graph p-Laplacian
Authors: Thomas Bühler, Matthias Hein
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvector of the graph p-Laplacian interpolates between a relaxation of the normalized and the Cheeger cut. Moreover, we prove that in the limit as p &rarr; 1 the cut found by thresholding the second eigenvector of the graph p-Laplacian converges to the optimal Cheeger cut. Furthermore, we provide an efficient numerical scheme to compute the second eigenvector of the graph p-Laplacian. The experiments show that the clustering found by p-spectral clustering is at least as good as normal spectral clustering, but often leads to significantly better results.