ppxscal/embedding_network huggingface dataset:
Evaluating Groupware Accessibility
Authors: John G. Schoeberlein, Yuanqiong (Kathy) Wang
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

Accessibility has been one of the biggest problems that people with disabilities face in the work place, due to today's rapid change in computer technology. This paper presents the evaluation of several console-based and web-based groupware applications including Outlook, AIM, Google Blog, and Group System's ThinkTank in terms of their accessibility. These applications were evaluated for accessibility based on various characteristics of the applications such as accessible front-end, hierarchy or list structures, input support, output support; screen reader adaptability; and keyboard access. Additionally, web-based groupware applications were evaluated using Web Content Accessibility Guidelines (WCAG) and U.S. Government's Section 508 guidelines. Fujitsu's Web Accessibility Inspector tool was also utilized to help evaluate the web-based applications. It is found that groupware applications have very limited accessibility through the support of keyboard access. Additional audio support and flattened hierarchies should be considered, to enable some persons with disabilities easy access to groupware applications. Future research should include persons with disabilities in evaluating groupware applications, to determine preferences. Since many groupware applications provide Application Program Interfaces (API), custom front-ends should be developed to include audio content and to flatten hierarchies and lists.
Identifying the Original Contribution of a Document via Language Modeling
Authors: Benyah Shaparenko, Thorsten Joachims
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

One major goal of text mining is to provide automatic methods to help humans grasp the key ideas in ever-increasing text corpora. To this effect, we propose a statistically well-founded method for identifying the original ideas that a document contributes to a corpus, focusing on self-referential diachronic corpora such as research publications, blogs, email, and news articles. Our statistical model of passage impact defines (interesting) original content through a combination of impact and novelty, and the model is used to identify each document's most original passages. Unlike heuristic approaches, the statistical model is extensible and open to analysis. We evaluate the approach both on synthetic data and on real data in the domains of research publications and news, showing that the passage impact model outperforms a heuristic baseline method.
Enhanced Web Page Content Visualization with Firefox
Authors: Lorand Dali, Delia Rusu, Dunja Mladenić
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

This paper aims at presenting how natural language processing and machine learning techniques can help the internet surfer to get a better overview of the pages he is reading. The proposed demo is a Firefox extension which can show a semantic graph of the text in the page that is currently loaded in the browser. The user can also get a summary of the web page she is looking at by choosing to display only the more important nodes in the semantic graph representation of the document, where importance of the nodes is obtained by machine learning techniques.
Both a nicotinic single nucleotide polymorphism (snp) and a noradrenergic snp modulate working memory performance when attention is manipulated
Authors: Pamela M. Greenwood, Ramya Sundararajan, Ming-Kuan Lin, Reshma Kumar, Karl J. Fryxell, Raja Parasuraman
Venue: Journal of Cognitive Neuroscience (2009)

We investigated the relation between the two systems of visuospatial attention and working memory by examining the effect of normal variation in cholinergic and noradrenergic genes on working memory performance under attentional manipulation. We previously reported that working memory for location was impaired following large location precues, indicating the scale of visuospatial attention has a role in forming the mental representation of the target. In one of the first studies to compare effects of two single nucleotide polymorphisms (SNPs) on the same cognitive task, we investigated the neurotransmission systems underlying interactions between attention and memory. Based on our previous report that the CHRNA4 rs#1044396 C/T nicotinic receptor SNP affected visuospatial attention, but not working memory, and the DBH rs#1108580 G/A noradrenergic enzyme SNP affected working memory, but not attention, we predicted that both SNPs would modulate performance when the two systems interacted and working memory was manipulated by attention. We found the scale of visuospatial attention deployed around a target affected memory for location of that target. Memory performance was modulated by the two SNPs. CHRNA4 C/C homozygotes and DBH G allele carriers showed the best memory performance but also the greatest benefit of visuospatial attention on memory. Overall, however, the CHRNA4 SNP exerted a stronger effect than the DBH SNP on memory performance when visuospatial attention was manipulated. This evidence of an integrated cholinergic influence on working memory performance under attentional manipulation is consistent with the view that working memory and visuospatial attention are separate systems which can interact.
Computer Networks, 1st edition
Authors: S. S. Manvi
Venue:  (2009)

Computer Networks provides research directions in all types of computer networks covering research challenges such as, security in wired/wireless networks, mobility management in 4G networks, routing in wireless and high speed networks, wired/wireless multimedia communications, performance analysis of WLAN and WMAN, quantum cryptography, game theory in wireless networks, mobile agents in MANETs, physical layer communications, interference in WLAN and WMAN, ATM networks and web mining. 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
Watermark Embedding and Recovery in the Presence of C-LPCD De-synchronization Attacks
Authors: Andrea Abrardo, Mauro Barni, Cesare Maria Carretti
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

The development of a watermarking system that is robust against de-synchronization attacks (DAs) is a major challenge. In this paper we make two steps towards the development of such a system by: i) proposing a fast algorithm for exhaustive watermark detection in the presence of C-LPCD DAs; ii) introducing a new watermarking system that by pre-distorting the watermark to be embedded greatly improves the performance of the exhaustive watermark detector. The validity of the proposed system is tested by means of Monte Carlo simulation on Gaussian white sequences. The results we obtained are rather promising thus suggesting to apply the newly proposed system to the watermarking of real audio sequences.
Detection of a Hand Holding a Cellular Phone Using Multiple Image Features
Authors: Hiroto Nagayoshi, Takashi Watanabe, Tatsuhiko Kagehiro, Hisao Ogata, Tsukasa Yasue, Hiroshi Sako
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Detection of a hand holding a cellular phone was developed to recognize whether someone is using a cellular phone while operating an automated teller machine (ATM). The purpose is to prevent money transfer fraud. Since a victim is told a bogus reason to transfer money and how to operate the machine through a cellular phone, detecting a working cellular phone is necessary.However, cellular phone detection was not realistic due to variable colors and shapes. We assumed that a user's hand beside the face was holding a cellular phone and decided to detect it.The proposed method utilizes color, shape, and motion. Color and motion were used to compare the input to the face. Shape was used to compare the input to the standard hand pattern. The experimental result was a detection rate of 90.0% and a false detection rate of 3.2%, where 7,324 and 20,708 images were used respectively.
Bridging the Gap between User Attributes and Service Policies with Attribute Mapping
Authors: Davide Cerri, Francesco Corcoglioniti
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

People, companies, and public authorities can now have a strong on-line presence and a huge amount of interactions on the Internet, made possible by the impressive growth of the World Wide Web and of Web technologies. Many independent parties provide services and exchange information in a plural, dynamic, and open environment. This scenario, where interacting parties are often strangers, naturally brings to attribute-based access control solutions, as traditional identity-based systems are usually inadequate to large open environments. User attributes certified by external authorities, however, tend to be rather general-purpose and to reflect a user point of view, thus they often do not coincide with the concepts that are relevant for the service. In this paper we propose a framework to decouple the user point of view and the service point of view on user attributes: following our model, the service access control policy can focus on the concepts that are relevant for the service logic, whereas a separate attribute mapping policy establishes the bridge between the two domains.
Recognizing and Responding to Student Affect
Authors: Beverly Woolf, Toby Dragon, Ivon Arroyo, David Cooper, Winslow Burleson, Kasia Muldner
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual student's affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.
Cooperative Caching Routing Discovery Protocol in MANETs Based on Improvement of the Expanding Ring Search
Authors: Jin Tan, Chou Fan, HangXia Zhou
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Finding cached data in cooperative caching system for mobile ad-hoc networks is a very important in order to save the energy, bandwidth of communication and to improve accessibility of data. Because the address of cached node (destination) is unknown, the expanding ring search (ERS) methods in multi-hop wireless environment are not suitable for routing cooperative caching discovery in mobile ad-hoc networks. A new routing discovery protocol is presented base on improvement of ERS in this paper; it uses RREQs,RREQc and RREP messages, and controls overhead with hops HSk from requested node k to real source node as TTL value. The analytic result indicates that our protocol is more advantaged then traditional ERS like increment TTL in search times initiated by requested node and broadcast cost in packet forward.
User Behavior Patterns: Gathering, Analysis, Simulation and Prediction
Authors: Lucas Stephane
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

This paper presents methods and tools for gathering, analyzing and predicting behavior patterns. Considered both for a single user and for groups of users, behavior patterns may impact at a local and/or global level. The first part explains how to gather behaviors in various situations and how to drill from overt behaviors into deeper cognitive processes. The rationale of cognitive modeling and guidelines to perform it are provided. The second part deals with analysis methods that enable to detect behavior patterns. Bottom-up analysis based on existing data is augmented with top-down analysis based on conceptual design choices and hypotheses. The last part emphasizes the needs of data storage and data sharing in the organization. Beyond data storage and sharing, it presents the benefits of using Adaptive Business Intelligence in order to simulate and predict possible situations as well as the appropriated behavior patterns that enable to adapt.
Improving Agent Bidding in Power Stock Markets through a Data Mining Enhanced Agent Platform
Authors: Anthony C. Chrysopoulos, Andreas L. Symeonidis, Pericles A. Mitkas
Venue: Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers (2009)

Like in any other auctioning environment, entities participating in Power Stock Markets have to compete against other in order to maximize own revenue. Towards the satisfaction of their goal, these entities (agents - human or software ones) may adopt different types of strategies - from na?ve to extremely complex ones - in order to identify the most profitable goods compilation, the appropriate price to buy or sell etc, always under time pressure and auction environment constraints. Decisions become even more difficult to make in case one takes the vast volumes of historical data available into account: goods' prices, market fluctuations, bidding habits and buying opportunities. Within the context of this paper we present Cassandra, a multi-agent platform that exploits data mining, in order to extract efficient models for predicting Power Settlement prices and Power Load values in typical Day-ahead Power markets. The functionality of Cassandra is discussed, while focus is given on the bidding mechanism of Cassandra's agents, and the way data mining analysis is performed in order to generate the optimal forecasting models. Cassandra has been tested in a real-world scenario, with data derived from the Greek Energy Stock market.
Membrane Dissolution and Division in P
Authors: Damien Woods, Niall Murphy, Mario J. Pérez-Jiménez, Agustín Riscos-Núñez
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Membrane systems with dividing and dissolving membranes are known to solve PSPACE problems in polynomial time. However, we give a P upperbound on an important restriction of such systems. In particular we examine systems with dissolution, elementary division and where each membrane initially has at most one child membrane. Even though such systems may create exponentially many membranes, each with different contents, we show that their power is upperbounded by P.
Pricing of Bi-direction European Option Under a Kind of Jump Diffusion Model
Authors: Zhou Zhidan, Peng Bo
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

The main purpose of this paper is to study the stock price jump process is more common than Poisson process -a kind of special renewal process-the incident time interval is independent random variable sequence and identical subordinate to Gamma distribution. The object of study is European bi-direction option, It also known as the double two-way options.Also, European bi-direction option is an exotic option. Then, build up stochastic differential equation under the circumstance of the market no arbitrage based on stochastic analysis and martingale theory. Based on the above discussion, we obtain the European bi-direction option pricing formulas under jump diffusion model by simple mathematical induce by means of martingale method.
Diophantine Equations and Computation
Authors: Martin Davis
Venue: Proceedings of the 8th International Conference on Unconventional Computation (2009)

Unless otherwise stated, we'll work with the natural numbers: $$N = \{0,1,2,3, \dots\}.$$ Consider a Diophantine equation F(a1,a2,...,an,x1,x2,...,xm) = 0 with parameters a1,a2,...,an and unknowns x1,x2,...,xm For such a given equation, it is usual to ask: For which values of the parameters does the equation have a solution in the unknowns? In other words, find the set: $$ \{ \mid \exists x_1,\ldots,x_m [F(a_1,\ldots,x_1,\ldots)=0] \}$$ Inverting this, we think of the equation F = 0 furnishing a definition of this set, and we distinguish three classes: a set is called Diophantine if it has such a definition in which F is a polynomial with integer coefficients. We write $\cal D$ for the class of Diophantine sets.a set is called exponential Diophantine if it has such a definition in which F is an exponential polynomial with integer coefficients. We write $\cal E$ for the class of exponential Diophantine sets.a set is called recursively enumerable (or listable)if it has such a definition in which F is a computable function. We write $\cal R$ for the class of recursively enumerable sets. 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
Feature Selection by Transfer Learning with Linear Regularized Models
Authors: Thibault Helleputte, Pierre Dupont
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervision to smoothly favor the selection of some dimensions (genes) on a new dataset to be classified. The dimensions to be favored are previously selected from similar datasets in large microarray databases, hence performing inductive transfer learning at the feature level. This technique relies on a feature selection method embedded within a regularized linear model estimation. A practical approximation of this technique reduces to linear SVM learning with iterative input rescaling. The scaling factors depend on the selected dimensions from the related datasets. The final selection may depart from those whenever necessary to optimize the classification objective. Experiments on several microarray datasets show that the proposed method both improves the selected gene lists stability, with respect to sampling variation, as well as the classification performances.
Dynamically reconfigurable hardware-software architecture for partitioning networking functions on the SoC platform
Authors: Youngmann Kim, E. K. Park, Sungwoo Tak
Venue: Journal of Systems and Software (2009)

We present an issue of the dynamically reconfigurable hardware-software architecture which allows for partitioning networking functions on a SoC (System on Chip) platform. We address this issue as a partition problem of implementing network protocol functions into dynamically reconfigurable hardware and software modules. Such a partitioning technique can improve the co-design productivity of hardware and software modules. Practically, the proposed partitioning technique, which is called the ITC (Inter-Task Communication) technique incorporating the RT-IJC^2 (Real-Time Inter-Job Communication Channel), makes it possible to resolve the issue of partitioning networking functions into hardware and software modules on the SoC platform. Additionally, the proposed partitioning technique can support the modularity and reuse of complex network protocol functions, enabling a higher level of abstraction of future network protocol specifications onto the SoC platform. Especially, the RT-IJC^2 allows for more complex data transfers between hardware and software tasks as well as provides real-time data processing simultaneously for given application-specific real-time requirements. We conduct a variety of experiments to illustrate the application and efficiency of the proposed technique after implementing it on a commercial SoC platform based on the Altera's Excalibur including the ARM922T core and up to 1 million gates of programmable logic.
JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA
Authors: Yonghong Yan, Max Grossman, Vivek Sarkar
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

A recent trend in mainstream desktop systems is the use of general-purpose graphics processor units (GPGPUs) to obtain order-of-magnitude performance improvements. CUDA has emerged as a popular programming model for GPGPUs for use by C/C++ programmers. Given the widespread use of modern object-oriented languages with managed runtimes like Java and C#, it is natural to explore how CUDA-like capabilities can be made accessible to those programmers as well. In this paper, we present a programming interface called JCUDA that can be used by Java programmers to invoke CUDA kernels. Using this interface, programmers can write Java codes that directly call CUDA kernels, and delegate the responsibility of generating the Java-CUDA bridge codes and host-device data transfer calls to the compiler. Our preliminary performance results show that this interface can deliver significant performance improvements to Java programmers. For future work, we plan to use the JCUDA interface as a target language for supporting higher level parallel programming languages like X10 and Habanero-Java.
Two-Dimensional Windowing in the Structural Similarity Index for the Colour Image Quality Assessment
Authors: Krzysztof Okarma
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

This paper presents the analysis of the usage of the Structural Similarity (SSIM) index for the quality assessment of the colour images with variable size of the sliding window. The experiments have been performed using the LIVE Image Quality Assessment Database in order to compare the linear correlation of achieved results with the Differential Mean Opinion Score (DMOS) values. The calculations have been done using the value (brightness) channel from the HSV (HSB) colour space as well as commonly used YUV/YIQ luminance channel and the average of the RGB channels. The analysis of the image resolution's influence on the correlation between the SSIM and DMOS values for varying size of the sliding window is also presented as well as some results obtained using the nonlinear mapping based on the logistic function.
Process-Based Governance in Public Administrations Using Activity-Based Costing
Authors: Jörg Becker, Philipp Bergener, Michael Räckers
Venue: Proceedings of the 8th International Conference on Electronic Government (2009)

Decision- and policy-makers in public administrations currently lack on missing relevant information for sufficient governance. In Germany the introduction of New Public Management and double-entry accounting enable public administrations to get the opportunity to use cost-centered accounting mechanisms to establish new governance mechanisms. Process modelling in this case can be a useful instrument to help the public administrations decision- and policy-makers to structure their activities and capture relevant information. In combination with approaches like Activity-Based Costing, higher management level can be supported with a reasonable data base for fruitful and reasonable governance approaches. Therefore, the aim of this article is combining the public sector domain specific process modelling method PICTURE and concept of activity-based costing for supporting Public Administrations in process-based Governance.