ppxscal/embedding_network huggingface dataset:
Probing the use of charts and graphs in technical documentation through analysis and pragmatic collaboration
Authors: Challen Pride-Thorne, Steve Murphy, Sandra Seenauth
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

A continuous priority for technical writers is to increase user comprehension of concepts and statistical information in technical documentation. Improvements in the written language such as consistent terminology, use of an established writing style, accurate indexing, advanced search capabilities, and so on, address some of the user pain points. The complexities of certain topics do not always translate well into writing; therefore, there is a need for other aids such as information graphics to assist with visualization and to increase the efficacy of information communication [1]. The benefits of information graphics in documentation and learning modules are well documented by the works of Levin and Pane [2, 3]. The conclusion is simple according to Davison, Pane, and Bertrancourt: if graphics are crafted correctly with the intent to enhance understanding then the quality of the documentation will improve and ultimately enrich the user experience and comprehension [4, 5, 6]. With this sage advice, one might expect implementation to be straightforward, perhaps even easy. This is unfortunately not the case. Careful consideration is necessary to construct an information graphic. Many questions may arise during the process, such as how many graphics, and which type, are needed, and where best to insert them in order to convey the concept clearly. Some information graphics, such as charts and graphs, require further thought since their visual representation is derived from data. In this case, the challenge lies in shaping the data into what is truly useful for users' comprehension, and in skillfully rendering the graphics with sound design principles. This paper presents the authors' recent experiences in collaborative design of charts and graphs, and demonstrates that the responsibility of communicating effectively should not lie on one person's shoulders alone, but rather on all development and documentation professionals who bring their collective expertise to fruition in a partnership.
Strength of shoulder during one-handed pushing in constrained conditions
Authors: Krystyna Gielo-Perczak
Venue: Human Factors in Ergonomics Manufacturing (2009)

This study hypothesizes that, by isolating the influences of contact surface friction, back foot support, and forward-leaning body posture during pushing, the magnitude of recorded strength will be a closer estimate of physical capabilities of the shoulder. The shoulder strength of twelve participants during one-handed pushing in constrained conditions in the coronal (frontal) plane, in a range from 5 to 30 degrees, was correlated with the anthropometric measures and two anatomical parameters of the shoulder joint. The data indicated that the acceptable loads at the handle for all the participants were lower than the recommended standards. Right arm length had the highest correlation coefficient with shoulder strength among anthropometric data, and the radius of the humerus bone among anatomical parameters. The findings from this study of one-handed pushing will be used to help modify existing physical strength standards in an effort to reduce the high frequency of recorded shoulder injuries. &copy; 2009 Wiley Periodicals, Inc. 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
Certified and Fast Computation of Supremum Norms of Approximation Errors
Authors: Sylvain Chevillard, Mioara Joldes, Christoph Lauter
Venue: Proceedings of the 2009 19th IEEE Symposium on Computer Arithmetic (2009)

In many numerical programs there is a need for a high-quality floating-point approximation of useful functions f, such as such as exp, sin, erf. In the actual implementation, the function is replaced by a polynomial p, which leads to an approximation error (absolute or relative) eps = p-f or eps = p/f-1. The tight yet certain bounding of this error is an important step towards safe implementations.The problem is difficult mainly because that approximation error is very small andthe difference p-f is subject to high cancellation. Previous approaches for computing the supremum norm in this degenerate case, have proven to be unsafe, not sufficiently tight or too tedious in manual work.We present a safe and fast algorithm that computes a tight lower and upper bound for the supremum norms of approximation errors. The algorithm is based on a combination of several techniques, including enhanced interval arithmetic, automatic differentiation and isolation of the roots of a polynomial. We have implemented our algorithm and give timings on several examples.
Security Monitor Inlining for Multithreaded Java
Authors: Mads Dam, Bart Jacobs, Andreas Lundblad, Frank Piessens
Venue: Proceedings of the 23rd European Conference on ECOOP 2009 --- Object-Oriented Programming (2009)

Program monitoring is a well-established and efficient approach to security policy enforcement. An implementation of program monitoring that is particularly appealing for application-level policy enforcement is monitor inlining: the application is rewritten to push monitoring and policy enforcement code into the application itself. The intention is that the inserted code enforces compliance with the policy (security), and otherwise interferes with the application as little as possible (conservativity and transparency).For sequential Java-like languages, provably correct inlining algorithms have been proposed, but for the multithreaded setting, this is still an open problem. We show that no inliner for multithreaded Java can be both secure and transparent. It is however possible to identify a broad class of policies for which all three correctness criteria can be obtained. We propose an inliner that is correct for such policies, implement it for Java, and show that it is practical by reporting on some benchmarks.
Path Partitions, Cycle Covers and Integer Decomposition
Authors: András Sebő
Venue: Graph Theory, Computational Intelligence and Thought: Essays Dedicated to Martin Charles Golumbic on the Occasion of His 60th Birthday (2009)

A polyhedron P has the integer decomposition property, if every integer vector in kP is the sum of k integer vectors in P. We explain that the projections of polyhedra defined by totally unimodular constraint matrices have the integer decomposition property, in order to deduce the same property for coflow polyhedra defined by Cameron and Edmonds. We then apply this result to the convex hull of particular stable sets in graphs. Therebye we prove a generalization of Greene and Kleitman's well-known theorem on posets to arbitrary digraphs which implies recent and classical purely graph theoretical results on cycle covers, is closely related to conjectures of Berge and Linial on path partitions, and implies these for some particular values of the parameters.
An Improved Weighted Feature Abstracting Algorithm
Authors: Fanrong Meng, Mu Zhu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

In non-supervised data set, the importance of each feature is different. If the feature is setted with a proper weight, which can fully considers the lever of the influence on the cluster effect, then the clustering result will be improved. A feature evaluate function is proposed to obtain a set of feature weight vectors by minimizing the function, which is a multi-objective problem. So a fast and elitist multi-objective genetic algorithm is used to solve the problem and obtain the weight of feature. Finally, the weight of feature is introduced into the standard K-Means algorithm and the experiments on the UCI dataset show the validity of the algorithm.
Sign Language Recognition: Working with Limited Corpora
Authors: Helen Cooper, Richard Bowden
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

The availability of video format sign language corpora limited. This leads to a desire for techniques which do not rely on large, fully-labelled datasets. This paper covers various methods for learning sign either from small data sets or from those without ground truth labels. To avoid non-trivial tracking issues; sign detection is investigated using volumetric spatio-temporal features. Following this the advantages of recognising the component parts of sign rather than the signs themselves is demonstrated and finally the idea of using a weakly labelled data set is considered and results shown for work in this area.
Towards design-based knowledge-building practices in teaching
Authors: Huang-Yao Hong, Jianwei Zhang, Chewlee Teo, Marlene Scardamalia
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

This paper explores knowledge building in a community identified by Bielaczyc and Collins (2006) as a hotbed community--a community in which knowledge creation has taken on a life of its own. The practices of six elementary schoolteachers are analyzed to inform the development of teachers' knowledge-building practices and to better understand how teachers develop and sustain innovative knowledge-building practices.
Large-scale indexing of spatial data in distributed repositories: the SD-Rtree
Authors: Cédric Du Mouza, Witold Litwin, Philippe Rigaux
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2009)

We propose a scalable distributed data structure (SDDS) called SD-Rtree. We intend our structure for point, window and kNN queries over large spatial datasets distributed on clusters of interconnected servers. The structure balances the storage and processing load over the available resources, and aims at minimizing the size of the cluster. SD-Rtree generalizes the well-known Rtree structure. It uses a distributed balanced binary tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. A user/application manipulates the structure from a client node. The client addresses the tree through its image that can be possibly outdated due to later split. This may generate addressing errors, solved by the forwarding among the servers. Specific messages towards the clients incrementally correct the outdated images. We present the building of an SD-Rtree through insertions, focusing on the split and rotation algorithms. We follow with the query algorithms. We describe then a flexible allocation protocol which allows to cope with a temporary shortage of storage resources through data storage balancing. Experiments show additional aspects of SD-Rtree and compare its behavior with a distributed quadtree. The results justify our various design choices and the overall utility of the structure.
CORAAL --- Towards Deep Exploitation of Textual Resources in Life Sciences
Authors: Vít Nováček, Tudor Groza, Siegfried Handschuh
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Prominent biomedical literature search tools like ScienceDirect, PubMed Central or MEDLINE allow for efficient retrieval of resources based on key words. Due to vast amounts of data available in life sciences, key word search is not always sufficient, though. One would often welcome more intelligent search for knowledge, i.e., for concepts and their mutual relations. This is, however, still a major challenge, since getting the necessary machine-readable knowledge manually is virtually impossible in large scale, while its automatic extraction is not particularly reliable. We have researched a novel framework actually enabling practical exploitation of automatically extracted knowledge, though. On the top of the framework, we implemented CORAAL, a prototype for knowledge-based biomedical literature search. This paper describes its essential principles, innovative capabilities and current results.
Efficient Non-interactive Range Proof
Authors: Tsz Hon Yuen, Qiong Huang, Yi Mu, Willy Susilo, Duncan S. Wong, Guomin Yang
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

We propose the first constant size non-interactive range proof which is not based on the heuristic Fiat-Shamir transformation and whose security does not rely on the random oracle assumption. The proof consists of a constant number of group elements. Compared with the most efficient constant-size range proof available in the literature, our scheme has significantly reduced the proof size. We showed that our scheme achieves perfect completeness, perfect soundness and composable zero-knowledge under a conventional number-theoretic assumption, namely the Subgroup Decision Problem.
Using knowledge driven matrix factorization to reconstruct modular gene regulatory network
Authors: Yang Zhou, Zheng Li, Xuerui Yang, Linxia Zhang, Shireesh Srivastava, Rong Jin, Christina Chan
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Reconstructing gene networks from micro-array data can provide information on the mechanisms that govern cellular processes. Numerous studies have been devoted to addressing this problem. A popular method is to view the gene network as a Bayesian inference network, and to apply structure learning methods to determine the topology of the gene network. There are, however, several shortcomings with the Bayesian structure learning approach for reconstructing gene networks. They include high computational cost associated with analyzing a large number of genes and inefficiency in exploiting prior knowledge of co-regulation that could be derived from Gene Ontology (GO) information. In this paper, we present a knowledge driven matrix factorization (KMF) framework for reconstructing modular gene networks that addresses these shortcomings. In KMF, gene expression data is initially used to estimate the correlation matrix. The gene modules and the interactions among the modules are derived by factorizing the correlation matrix. The prior knowledge in GO is integrated into matrix factorization to help identify the gene modules. An alternating optimization algorithm is presented to efficiently find the solution. Experiments show that our algorithm performs significantly better in identifying gene modules than several state-of-the-art algorithms, and the interactions among the modules uncovered by our algorithm are proved to be biologically meaningful.
Efficient reinforcement learning with relocatable action models
Authors: Bethany R. Leffler, Michael L. Littman, Timothy Edmunds
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Realistic domains for learning possess regularities that make it possible to generalize experience across related states. This paper explores an environment-modeling framework that represents transitions as state-independent outcomes that are common to all states that share the same type. We analyze a set of novel learning problems that arise in this framework, providing lower and upper bounds. We single out one particular variant of practical interest and provide an efficient algorithm and experimental results in both simulated and robotic environments.
EEG-Based Spatial Navigation Estimation in a Virtual Reality Driving Environment
Authors: Chin-Teng Lin, Fu-Shu Yang, Te-Chung Chiou, Li-Wei Ko, Jeng-Ren Duann, Klaus Gramann
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Abstract—The aim of this study is to investigate the difference of EEG dynamics on navigation performance. A tunnel task was designed to classify subjects into allocentric or egocentric spatial representation users. Despite of the differences of mental spatial representation, behavioral performance in general were compatible between the two strategies subjects in the tunnel task. Task-related EEG dynamics in power changes were analyzed using independent component analysis (ICA), time-frequency and non-parametric statistic test. ERSP image results revealed navigation performance-predictive EEG activities which is is expressed in the parietal component by source reconstruction. For egocentric subjects, comparing to trails with well-estimation of homing angle, the power attenuation at the frequencies from 8 to 30 Hz (around alpha and beta band) was stronger when subjects overestimated homing directions, but the attenuated power was decreased when subjects were underestimated the homing angles. However, we did not found performance related brain activities for allocentric subjects, which may due to the functional dis-sociation between the use of allo- and egocentric reference frames.
Adaptive importance sampling with automatic model selection in value function approximation
Authors: Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama, Jan Peters
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are usually prohibitively expensive. A common approach is to use importance sampling techniques for compensating for the bias caused by the difference between data-sampling policies and the target policy. However, existing off-policy methods do not often take the variance of value function estimators explicitly into account and therefore their performance tends to be unstable. To cope with this problem, we propose using an adaptive importance sampling technique which allows us to actively control the trade-off between bias and variance. We further provide a method for optimally determining the trade-off parameter based on a variant of cross-validation. We demonstrate the usefulness of the proposed approach through simulations.
FEM-Mill: The Next Generation Virtual Machining Software ?FEM and AI? in reshaping CAD/CAM Technology
Authors: Jitender Kumar Rai, Paul Xirouchakis
Venue:  (2009)

The rigid body motion of flexible parts and deformations induced during milling are the main root causes of part errors and are governed mainly from the choice of process parameters. Therefore, to avoid failures and achieve better results it becomes necessary to judge the validity of a given process plan before performing the actual cut. This book describes a state of the art milling process plan verification and optimization system called FEM-Mill. The main novelties of FEM-Mill lies in its two important computational modules namely; (i) the FEM based 3D transient milling simulation environment, and (ii) The expert system for diagnosis and rectification of part error causes. The applicability of AI techniques like ANN and GA in predicting cutting loads and optimal selection of process parameters are also demonstrated. The outcomes of experimental validations are presented in detail. This book gives insight into the development of next generation CAD/CAM technology using the emerging numerical techniques like FEM and AI. FEM-Mill will be of interest to software developers, researchers and engineers involved in process planning, fixture design and CAD/CAM software development.
Determining the position of adverbial phrases in English
Authors: Huayan Zhong, Amanda Stent
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

In this paper we compare three approaches to adverbial positioning using lexical, syntactic, semantic and sentence-level features. We find that: (a), one- and two-stage classification-based approaches can achieve almost 86% accuracy in determining the absolute position of adverbials; (b) a classifier trained with only syntactic features gives performance close to that of a classifier trained with all features; and (c) a surface realizer incorporating a two-stage classifier for adverbial positioning as the second stage gives improvements of at least 10% in simple string accuracy over a baseline realizer for sentences containing adverbials.
On the effectiveness of secret key extraction from wireless signal strength in real environments
Authors: Suman Jana, Sriram Nandha Premnath, Mike Clark, Sneha K. Kasera, Neal Patwari, Srikanth V. Krishnamurthy
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

We evaluate the effectiveness of secret key extraction, for private communication between two wireless devices, from the received signal strength (RSS) variations on the wireless channel between the two devices. We use real world measurements of RSS in a variety of environments and settings. Our experimental results show that (i) in certain environments, due to lack of variations in the wireless channel, the extracted bits have very low entropy making these bits unsuitable for a secret key, (ii) an adversary can cause predictable key generation in these static environments, and (iii) in dynamic scenarios where the two devices are mobile, and/or where there is a significant movement in the environment, high entropy bits are obtained fairly quickly. Building on the strengths of existing secret key extraction approaches, we develop an environment adaptive secret key generation scheme that uses an adaptive lossy quantizer in conjunction with Cascade-based information reconciliation [7] and privacy amplification [14]. Our measurements show that our scheme, in comparison to the existing ones that we evaluate, performs the best in terms of generating high entropy bits at a high bit rate. The secret key bit streams generated by our scheme also pass the randomness tests of the NIST test suite [21] that we conduct.
Impact of the Norm on Optimal Locations
Authors: Marc Ciligot-Travain, Didier Josselin
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Our research sets in the field of k-facilities location-allocation problems. More precisely, we developed an approach, that aims to assess the sensitivity of centers to different metrics used to locate them, according to various spatial distributions of demands. We start by a concise state of the art. Then, we justify our approach with several examples on real or simulated data. Two mathematical formalisms of the 1---facility problem and the sensitivity estimation are provided. We finally propose different ways to assess the influence of points of demand on the centers, including exploratory spatial data analysis and random simulations on consequent samples.