ppxscal/embedding_network huggingface dataset:
Creating an automatic question answering text skimming system for non-visual readers
Authors: Debra Yarrington, Kathleen McCoy
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

This poster describes an approach to creating a system that will allow blind, low vision, dyslexic, and other non-visual readers to skim through documents for answers to questions. The ultimate goal is a system that gives the users information similar to that which a sighted individual obtains while skimming through a document for an answer to a question. To create this system, we will be incorporating open domain question answering (QA) techniques, word clustering techniques, and data gathered from visual readers skimming through documents. Ultimately the system will take a question and a text document and return a list of rated links that suggest where the answers within a document are likely to be located. This poster focuses on results of data gathered from individuals skimming through documents.
Autotuning Configurations in Distributed Systems for Performance Improvements Using Evolutionary Strategies
Authors: Anooshiravan Saboori, Guofei Jiang, Haifeng Chen
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Distributed systems usually have many configurable parameters such as those included in common configuration files. Performance of distributed systems is partially dependent on these system configurations. While operators may choose default settings or manually tune parameters based on their experience and intuition, the resulted settings may not be the optimal one for specific services running on the distributed system. In this paper, we formulate the problem of autotuning configurations as a black-box optimization problem. This problem becomes quite challenging since the joint parameter search space is huge and also no explicit relationship between performance and configurations exists. We propose to use a well known evolutionary algorithm called Covariance Matrix Adaptation (CMA) to automatically tune system parameters. We compare CMA algorithm to another existing techniques called Smart Hill Climbing (SHC) and demonstrate that CMA algorithm outperforms SHC algorithm both on synthetic data and in a real system.
A Robust Digital Watermarking of Chinese Texts Based on Watermarking Structure and Embedding Strategy
Authors: Xinmin Zhou, Weidong Zhao, Zhicheng Wang, Rui Peng, Gang Wei
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

A novel robust text watermarking algorithm based on watermarking structure and embedding Strategy is proposed to solve the problem of copyright protection in this paper. This method obtains structure types and strokes of Chinese characters based on the thought of the mathematical expression of a Chinese character, and then the whole document is divided into two blocks by utilizing structure types of Chinese characters. In each block, the position chosen as a candidate of embedding is determined by not only the watermarking bit but also the Chinese character's strokes. Embedding is implemented through setting underlines to Chinese characters and hiding them. Watermarking can be extracted without original document and primitive watermarking information. When the watermarking bit is destroyed, its position can be recorded, and it can be recovered by block-checkout and hamming-checkout. The experimental results indicate that the proposed algorithm is more robust and transparent than the counterpart methods.
An image based interactive digital library of mechanical engineering objects
Authors: Muhammad Abuzar Fahiem, Saadia Jehangir
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Digital libraries are evolving day by day to provide a collection of logically related digital data. In this paper, we discuss an image based digital library specially meant for mechanical engineering objects. Our library is versatile since it stores images of engineering objects as (scalable vector graphics) SVG representations and supports textual as well as interactive search queries. The library can be populated dynamically by the user. Such a library is very useful in computer aided designing and for information interchange over the web. This library is an extension of our previous work [1] on SVG for information interchange of engineering documents over World Wide Web.
SICTA Modifications with Single Memory Location and Resistant to Cancellation Errors
Authors: Sergey Andreev, Eugeny Pustovalov, Andrey Turlikov
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

In this paper we consider a cross-layer MAC-PHY technique that combines the collision resolution tree algorithm (TA) with the possibility of successive interference cancellation (SIC). The overview of the previous work shows that no simple protocol has been proposed to use a single memory location for the captured signal. We, consequently, propose two such protocols that demonstrate the throughput - implementation complexity trade-off. Further, we address the system operation during which interference cancellation errors are possible. We propose the third protocol that is resistant to cancellation errors. A simple yet effective technique is applied to address the throughput performance of all three protocols to demonstrate their superiority over known conventional TA protocols.
A Knowledge Based Approach for Capturing Rich Semantic Representations from Text
Authors: Peter Z. Yeh, Daniel R. Farina, Alex Kass
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

In this paper, we present a knowledge based approach to capture semantic representations from natural language for a class of applications where the representations of interest are known in advance. Our approach performs this task by generating phrases from these representations and matching these phrases against text using a set of syntactic and semantic transformations. The representation that best matches a piece of text is selected as its meaning. We evaluate our approach on a corpus of news articles collected from over 150 online news sources, and show how our approach performs well on capturing semantic representations from text.
Loading OpenMP to Cell: An Effective Compiler Framework for Heterogeneous Multi-core Chip
Authors: Haitao Wei, Junqing Yu
Venue: Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era (2007)

The Cell employs a multi-core-on-chip design that integrates 9 processing elements, local memory and communication hardware into one chip. We present a source to source OpenMP compiler framework which translates the program with OpenMP directives to the necessary codes for PPE and SPE to exploit the parallelism of a sequential program through the different processing elements of the Cell. Some effective mapping strategies are also presented to conduct the thread creating and data handling between the different processors and reduce the overhead of system performance. The experimental results show that such compiler framework and mapping strategy can be effective for the heterogeneous multi-core architecture.
Shoe-Print Extraction from Latent Images Using CRF
Authors: Veshnu Ramakrishnan, Manavender Malgireddy, Sargur N. Srihari
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

Shoeprints are one of the most commonly found evidences at crime scenes. A latent shoeprint is a photograph of the impressions made by a shoe on the surface of its contact. Latent shoeprints can be used for identification of suspects in a forensic case by narrowing down the search space. This is done by elimination of the type of shoe, by matching it against a set of known shoeprints (captured impressions of many different types of shoes on a chemical surface). Manual identification is laborious and hence the domain seeks automated methods. The critical step in automatic shoeprint identification is Shoeprint Extraction - defined as the problem of isolating the shoeprint foreground (impressions of the shoe) from the remaining elements (background and noise). We formulate this problem as a labeling problem as that of labeling different regions of a latent image as foreground (shoeprint) and background. The matching of these extracted shoeprints to the known prints largely depends on the quality of the extracted shoeprint from latent print. The labeling problem is naturally formulated as a machine learning task and in this paper we present an approach using Conditional Random Fields(CRFs) to solve this problem. The model exploits the inherent long range dependencies that exist in the latentprint and hence is more robust than approaches using neural networks and other binarization algorithms. A dataset comprising of 45 shoeprint images was carefully prepared to represent typical latent shoeprint images. Experimental results on this data set are promising and support our claims above.
End-to-End Scientific Data Management Using Workflows
Authors: Yogesh Simmhan
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Workflows have evolved as the natural tool for scientists to model their eScience experiments. With the scientific world producing data at an explosive rate, workflows have an important part to play in the end to end management of scientific data. To illustrate, workflow can help with fault tolerance and ease of administration when ingesting massive quantities of data using commodity hardware. The ability for workflows to automatically collect provenance on derived scientific data improves data discovery and publication capabilities. With better support for interoperating with data centric tools, workflows can become ubiquitous systems for scientific collaboration.
Neural integrator: A sandpile model
Authors: Maxim Nikitchenko, Alexei Koulakov
Venue: Neural Computation (2008)

We investigated a model for the neural integrator based on hysteretic units connected by positive feedback. Hysteresis is assumed to emerge from the intrinsic properties of the cells. We consider the recurrent networks containing either bistable or multistable neurons. We apply our analysis to the oculomotor velocity-to-position neural integrator that calculates eye positions using the inputs that carry information about eye angular velocity. By analyzing this system in the parameter space, we show the following. The direction of hysteresis in the neuronal response may be reversed for the system with recurrent connections compared to the case of unconnected neurons. Thus, for the NMDA receptor-based bistability, the firing rates after ON saccades may be higher than after OFF saccades for the same eye position. The reversal of hysteresis occurs in this model only when the size of hysteresis differs from neuron to neuron. We also relate the macroscopic leak time constant of the integrator to the rate of microscopic spontaneous noise-driven transitions in the hysteretic units. Finally, we investigate the conditions under which the hysteretic integrator may have no threshold for integration.
Text Pre-processing for Document Clustering
Authors: Seemab Latif, Mary Mcgee Wood
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

The processing performance of vector-based document clustering methods is improved if automatic summarisation is used in addition to established forms of text pre-processing.
Identifying Chinese E-Mail Documents' Authorship for the Purpose of Computer Forensic
Authors: Jianbin Ma, Ying Li, Guifa Teng
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Nowadays, computer crimes involving e-mail increases rapidly. To prevent these phenomena from happening, the authorship identification methods for Chinese e-mail documents were described in this paper, which could provide evidence for the purpose of computer forensic. The theoretical framework was presented. Various style features including linguistic features, structural characteristics and format features were analyzed. The support vector machine algorithm was used for learning algorithm. To validate the methods, experiments were made on limited dataset. The results were satisfying, which proved that the methods were effective and feasible to apply to computer forensic.
Symbolic Manipulation of Bspline Basis Functions with Mathematica
Authors: A. Iglesias, R. Ipanaqué, R. T. Urbina
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Bspline curves and surfaces are the most common and most important geometric entities in many fields, such as computer design and manufacturing (CAD/CAM) and computer graphics. However, up to our knowledge no computer algebra package includes especialized symbolic routines for dealing with Bsplines so far. In this paper, we describe a new Mathematica program to compute the Bspline basis functions symbolically. The performance of the code along with the description of the main commands are discussed by using some illustrative examples.
An Optimized Fuzzy Based Short Term Object Motion Prediction for Real-Life Robot Navigation Environment
Authors: Vijay S. Rajpurohit, M. M. Manohara Pai
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

Short term motion prediction for moving objects in a real life Robotic navigation environment involves uncertainty and temporal validity of the results.Prediction of accurate position of a moving object and responding with quick action are the main objectives of Robot motion planning. This paper proposes a novel algorithm for short term motion prediction involving a fuzzy based predictor. Because of the multi valued nature of the fuzzy logic, this approach enjoys high robustness in dealing with noisy and uncertain data. The knowledge captured by the Rulebase has been optimized by defining directional space. In the proposed work the predictor has been evaluated with three well known defuzzification techniques. Based on the analysis of results, it has been found that Mean Of Maximum defuzzification technique has lower response time and better accuracy. The predictor is tested for various motion patterns in real life environment.
Giving Design Advice
Authors: Rebecca J. Wirfs-Brock
Venue: IEEE Software (2007)

Cognitive biases exist, and designers are remiss if we ignore them. By becoming aware of some common cognitive biases in design discussions, you can learn when it's worthwhile to tweak your message to increase the likelihood of it being accepted.
Human motion analysis and action recognition
Authors: Adem Karahoca, Murat Nurullahoglu
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

The goal of human activity recognition systems is to build a system that can automatically infer a range of predefined activities, such as running, handclapping, etc, from recorded video sequences. Such a computerized system would be of great use for a variety of applications ranging from video surveillance for security to human-machine interaction. Typically, pattern recognition is the key component of such a system, where the goal is to classify, or more specifically "recognize" the data, based on a priori knowledge or statistical information extracted from the patterns. In this study, we presented a comparison of several well-known pattern recognition techniques for a human activity recognition system. We used Motion History Images (MHI) to describe these activities in a qualitative way and computed Hu moments, a widely used and well-known feature set to describe 2D or 3D shape, for further processing. Several feature extraction and classification methods were compared using different combinations and the results were analyzed. These methods are Principle Component Analysis and Linear Discriminant Analysis. Then we tested features with Support Vector Machines and K Nearest Neighbours classifiers.
ProUD: Probabilistic Ranking in Uncertain Databases
Authors: Thomas Bernecker, Hans-Peter Kriegel, Matthias Renz
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

There are a lot of application domains, e.g. sensor databases, traffic management or recognition systems, where objects have to be compared based on vague and uncertain data. Feature databases with uncertain data require special methods for effective similarity search. In this paper, we propose an effective and efficient probabilistic similarity ranking algorithm that exploits the full information given by inexact object representations. Thereby, we assume that the objects are given in form of discrete probabilistic object locations in particular several object snapshots with confidence values. Based on the given object representations, we suggest diverse variants of probabilistic ranking schemes. In a detailed experimental evaluation, we demonstrate the benefits of our probabilistic ranking approaches. The experiments show that we can achieve high quality query results while keeping the computational cost quite small.
Checkpointing schemes for Grid workflow systems
Authors: Zhongwen Li, Yang Xiang
Venue: Concurrency and Computation: Practice Experience (2008)

One of the major challenges in wide use of Grid workflow systems is fault tolerance and avoidance. Checkpointing schemes provide a way of fault detection and recovery. In our research, we focus on the performance optimization of checkpointing schemes and dynamic voltage scaling (DVS) for Grid workflow systems. We propose offline checkpointing schemes with DVS and online adaptive checkpointing schemes that dynamically adjust the checkpointing intervals by using store checkpoints and compare checkpoints. When combined with DVS, offline adaptive checkpointing schemes not only are fault tolerant but also lead to reduce average execution time of tasks. These schemes can efficiently utilize comparison and storage operations and significantly improve the performance. Further, these schemes can calculate the optimal numbers of checkpoints by which the mean execution time can be minimized. We also expand the online adaptive checkpointing schemes from single-task execution scenarios to multi-task execution scenarios. Simulation results show that these online schemes outstandingly increase the likelihood of timely task completion when faults occur. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Scheduling for Speed Bounded Processors
Authors: Nikhil Bansal, Ho-Leung Chan, Tak-Wah Lam, Lap-Kei Lee
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We consider online scheduling algorithms in the dynamic speed scaling model, where a processor can scale its speed between 0 and some maximum speed T. The processor uses energy at rate s&alpha; when run at speed s, where &alpha;> 1 is a constant. Most modern processors use dynamic speed scaling to manage their energy usage. This leads to the problem of designing execution strategies that are both energy efficient, and yet have almost optimum performance. We consider two problems in this model and give essentially optimum possible algorithms for them. In the first problem, jobs with arbitrary sizes and deadlines arrive online and the goal is to maximize the throughput, i.e. the total size of jobs completed successfully. We give an algorithm that is 4-competitive for throughput and O(1)-competitive for the energy used. This improves upon the 14 throughput competitive algorithm of Chan et al. [10]. Our throughput guarantee is optimal as any online algorithm must be at least 4-competitive even if the energy concern is ignored [7]. In the second problem, we consider optimizing the trade-off between the total flow time incurred and the energy consumed by the jobs. We give a 4-competitive algorithm to minimize total flow time plus energy for unweighted unit size jobs, and a (2 + o(1)) &alpha;/ln &alpha;-competitive algorithm to minimize fractional weighted flow time plus energy. Prior to our work, these guarantees were known only when the processor speed was unbounded (T = &infin;) [4].
Towards a Unified Model of Social and Environment-Directed Agent Gaze Behaviour
Authors: Christopher Peters
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

When considering the gaze behaviours of embodied agents, and necessarily the underlying processes of visual attention that help to guide them, most work to date has been focused either on models aimed at controlling gaze in social situations, for example when one or more ECA's and humans are interacting, or for controlling gaze directed at the environment in a more general sense, typically for helping AVA's accomplish tasks such as navigation. We are designing a model of visual attention that attempts to amalgamate these concepts into a unified design in order to produce intelligent virtual agents that can behave in a social manner with social stimuli while also being attentive to events when mobile in the more general environment.
Diagrammatic Modeling of Architectural Decisions
Authors: Andrzej Zalewski, Marcin Ludzia
Venue: Proceedings of the 2nd European conference on Software Architecture (2008)

The paper presents a semi formal model of architectural decisions referred to as Maps of Architectural Decisions (MAD). In a form of a diagram they represent the most important components of architectural decisions (concerns, possible choices, constraints etc.) as well as logic of architectural decision making, i.e. dependencies between architectural decisions. This increases the level of formalism of the architectural decisions documentation, improves its readability and makes architectural knowledge gathered during the decision making process easier to comprehend, share and maintain.
Model-Checking First-Order Logic: Automata and Locality
Authors: Anuj Dawar
Venue: Proceedings of the 21st international workshop and the 16th Annual Conference of the EACSL on Computer Science Logic (2007)

The satisfaction problem for first-order logic, namely to decide, given a finite structure $\mathbb{A}$ and a first-order formula ¿, whether or not $\mathbb{A} \models \phi$ is known to be PSpace-complete. In terms of parameterized complexity, where the length of ¿ is taken as the parameter, the problem is AW[ ¿ ]-complete and therefore not expected to be fixed-parameter tractable (FPT). Nonetheless, the problem is known to be FPT when we place some structural restrictions on A. For some restrictions, such as when we place a bound on the treewidth of $\mathbb{A}$, the result is obtained as a corollary of the fact that the satisfaction problem for monadic second-order logic (MSO) is FPT in the presence of such restriction [1]. This fact is proved using automata-based methods. In other cases, such as when we bound the degree of $\mathbb{A}$, the result is obtained using methods based on the locality of first-order logic (see [3]) and does not extend to MSO. We survey such fixed-parameter tractability results, including the recent [2] and explore the relationship between methods based on automata, locality and decompositions.