ppxscal/embedding_network huggingface dataset:
Cubic Graphs Have Bounded Slope Parameter
Authors: Balázs Keszegh, János Pach, Dömötör Pálvölgyi, Géza Tóth
Venue: Graph Drawing: 16th International Symposium, GD 2008, Heraklion, Crete, Greece, September 21-24, 2008. Revised Papers (2009)

We show that every finite connected graph G with maximum degree three and with at least one vertex of degree smaller than three has a straight-line drawing in the plane satisfying the following conditions. No three vertices are collinear, and a pair of vertices form an edge in G if and only if the segment connecting them is parallel to one of the sides of a previously fixed regular pentagon. It is also proved that every finite graph with maximum degree three permits a straight-line drawing with the above properties using only at most seven different edge slopes.
FairCASH: Concepts and Framework
Authors: Yen Choon Ching, Heinz Kreft
Venue: Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies (2008)

This paper presents the framework for a true digital cash based payment system. The significant difference of this system as compared with previous system is that the value token is transferable among the users. This is achieved by using a tamper-resistant hardware to protect the value token. As a consequence of non-existing tamper-proof hardware, various measures are built into the system to detect and isolate fraud.
NLP for Shallow Question Answering of Legal Documents Using Graphs
Authors: Alfredo Monroy, Hiram Calvo, Alexander Gelbukh
Venue: Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing (2009)

Previous work has shown that modeling relationships between articles of a regulation as vertices of a graph network works twice as better than traditional information retrieval systems for returning articles relevant to the question. In this work we experiment by using natural language techniques such as lemmatizing and using manual and automatic thesauri for improving question based document retrieval. For the construction of the graph, we follow the approach of representing the set of all the articles as a graph; the question is split in two parts, and each of them is added as part of the graph. Then several paths are constructed from part A of the question to part B, so that the shortest path contains the relevant articles to the question. We evaluate our method comparing the answers given by a traditional information retrieval system--vector space model adjusted for article retrieval, instead of document retrieval--and the answers to 21 questions given manually by the general lawyer of the National Polytechnic Institute, based on 25 different regulations (academy regulation, scholarships regulation, postgraduate studies regulation, etc.); with the answer of our system based on the same set of regulations. We found that lemmatizing increases performance in around 10%, while the use of thesaurus has a low impact.
Learning by Propagability
Authors: Bingbing Ni, Shuicheng Yan, Ashraf Kassim, Loong Fah Cheong
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and optimal feature representation can constitute a harmonic system, namely, the data labels are invariant with respect to the propagation on the similarity-graph constructed by the optimal feature representation. Based on this philosophy, a unified formulation for learning by propagability is proposed for both supervised and semi-supervised configurations. Specifically, this formulation offers the semi-supervised learning two characteristics: 1) unlike conventional semi-supervised learning algorithms which mostly include at least two parameters, this formulation is parameter-free; and 2) the formulation unifies the label propagation and optimal representation pursuing, and thus the label propagation is enhanced by benefiting from the graph constructed with the derived optimal representation instead of the original representation. Extensive experiments on UCI toy data, handwritten digit recognition, and face recognition all validate the effectiveness of our proposed learning framework compared with the state-of-the-art methods for feature extraction and semi-supervised learning.
Wavelet-based cepstrum calculation
Authors: Fabrício Lopes Sanchez, Sylvio Barbon,  Júnior, Lucimar Sasso Vieira, Rodrigo Capobianco Guido, Everthon Silva Fonseca, Paulo Rogério Scalassara, Carlos Dias Maciel, José Carlos Pereira, Shi-Huang Chen
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper we present a new wavelet-based algorithm for low-cost computation of the cepstrum. It can be used for real time precise pitch determination in automatic speech and speaker recognition systems. Many wavelet families are examined to determine the one that works best. The results confirm the efficacy and accuracy of the proposed technique for pitch extraction.
A Dynamic Approach for Managing Stakeholder Credentials for Lightweight, Collaborative, Requirements Elicitation
Authors: Kurtis D. Todd, Jane Cleland-Huang
Venue: Proceedings of the 2008 First International Workshop on Managing Requirements Knowledge (2008)

As software projects increase in size and complexity, and involve stakeholders across geographic and organizational boundaries, it becomes increasingly important to develop new approaches and tools for supporting distributed, collaborative and scalable requirements elicitation processes. Such processes and related tools must support relatively open and inclusive collaborations, while simultaneously constraining stakeholders' contributions according to their areas and levels of expertise. This position paper proposes a new approach that uses information retrieval methods and group dynamics to manage stakeholder credentials and provide access permissions in a dynamically evolving, open-access, requirements elicitation process.
Visualizing Use Case Sets as BPMN Processes
Authors: Daniel Lübke, Kurt Schneider
Venue: Proceedings of the 2008 Requirements Engineering Visualization (2008)

The goal of many software projects is the support of business processes. A typical business process spans multiple Use Cases. This poses the difficulty of making the set of encompassing Use Cases consistent with each other and functionality-wise complete with regards to the overall busi- ness process. Manual arrangements and reviews of Use Cases are burdensome and time-intensive. Therefore, an automatic approach is needed that restores an overview of the Use Cases and visualizes the control-flow of the result- ing business process. Our approach uses pre-conditions, post-conditions, and triggers of Use Cases to automatically assemble business processes in BPMN notation in order to solve this problem.
Dynamics of a Collaborative Rating System
Authors: Kristina Lerman
Venue: Advances in Web Mining and Web Usage Analysis: 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers (2009)

The rise of social media sites, such as blogs, wikis, Digg and Flickr among others, underscores a transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. The social news aggregator Digg allows users to submit links to and vote on news stories. Like other social media sites, Digg also allows users to designate others as "friends" and easily track friends' activities: what new stories they submitted, commented on or liked. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide which stories to promote to the front page. We construct two mathematical models of collaborative decision-making on Digg. First, we study how collective rating of news stories emerges from the decisions made by many users. The model takes into account the effect that decisions made by a user's friends have on the user. We also study how user's influence, as measured by her rank, changes in time as she submits new stories and is befriended by other Digg users. Solutions of both models reproduce the observed dynamics of voting and user rank on Digg.The Digg model that enables users to collectively rate news stories can be generalized to the collaborative evaluation of document (or information) quality. Mathematical analysis can be used as a tool to explore different collaborative decision-making algorithms to select the most effective one before the algorithm is ever implemented in a real system.
Mobile healthcare applications: a study of access control
Authors: Michelle Watson
Venue: Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services (2006)

The use of electronic devices in healthcare can be used in the form of an ad hoc network to aid in the transfer and accuracy of personal health information. The devices of an hoc network can be used in three different modes: Standalone mode, Huddle mode, and Roaming mode, all of which will be discussed further for each of the scenarios. Various access control situations exist and are discussed specific to each healthcare personnel in each scenario, as well as various privacy and security issues relating to the transfer of medical records electronically. This paper outlines the use of the Meditech database currently used in many healthcare environments
Usefulness of quality click-through data for training
Authors: Craig Macdonald, Iadh Ounis
Venue: Proceedings of the 2009 workshop on Web Search Click Data (2009)

Modern Information Retrieval (IR) systems often employ document weighting models with many parameters that require to be appropriately set for effective retrieval performance. To obtain these parameter settings, quality training is usually required, where assessors have manually labelled the relevance of retrieved items for many queries. In this work, we examine the usefulness of high-quality click-through data for training an IR system, on searching the .gov vertical domain of the Web. We find that, compared to training using relevance judgements created using human assessors, the click-through trained settings are as good and occasionally better.
Extension to Corba Event Service for a Conference Control System
Authors: Joao Orvalho, Tiago Andrade, Fernando Boavida
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

Conferencing applications require an efficient conference control service. The present paper introduces the main features of a conference control service based on the CORBA Event Service using the Java platform, under development at the Communications and Telematic Services Group of the University of Coimbra. This framework is based on the ITU T.120 recommendations, with reliable multicasting communication for both data and control information.The control service extends the CORBA Event Service architecture with mechanisms for reliable IP multicast communication, with total ordering of the events transmission, filtering and fragmenting/reassembling of large messages.
Outage Performance and Average Symbol Error Rate of M-QAM for Maximum Ratio Combining with Multiple Interferers
Authors: Kyung Seung Ahn
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

In this paper, we investigate the performance of maximum ratio combining (MRC) in the presence of multiple cochannel interferences over a flat Rayleigh fading channel. Closed-form expressions of signal-to-interference-plus-noise ratio (SINR), outage probability, and average symbol error rate (SER) of quadrature amplitude modulation (QAM) with M-ary signaling are obtained for unequal-power interference-to-noise ratio (INR). We also provide an upper-bound for the average SER using moment generating function (MGF) of the SINR. Moreover, we quantify the array gain loss between pure MRC (MRC system in the absence of CCI) and MRC system in the presence of CCI. Finally, we verify our analytical results by numerical simulations.
Some Aspects of Parsing Expression Grammar
Authors: Roman R. Redziejowski
Venue: Fundamenta Informaticae (2008)

Parsing Expression Grammar (PEG) is a new way to specify syntax, by means of a topdown processwith limited backtracking. It can be directly transcribed into a recursive-descent parser. The parser does not require a separate lexer, and backtracking removes the usual LL(1) constraint. This is convenient for many applications, but there are two problems: PEG is not well understood as a language specification tool, and backtracking may result in exponential processing time. The paper consists of two parts that address these problems. The first part is an attempt to find out the language actually defined by a given parsing expression. The second part reports measurements of backtracking activity in a PEG-derived parser for the programming language C.
Implications of different classes of sensorimotor disturbance for cerebellar-based motor learning models
Authors: Adrian Haith, Sethu Vijayakumar
Venue: Biological Cybernetics (2009)

The exact role of the cerebellum in motor control and learning is not yet fully understood. The structure, connectivity and plasticity within cerebellar cortex has been extensively studied, but the patterns of connectivity and interaction with other brain structures, and the computational significance of these patterns, is less well known and a matter of debate. Two contrasting models of the role of the cerebellum in motor adaptation have previously been proposed. Most commonly, the cerebellum is employed in a purely feedforward pathway, with its output contributing directly to the outgoing motor command. The cerebellum must then learn an inverse model of the motor apparatus in order to achieve accurate control. More recently, Porrill et al. (Proc Biol Sci 271(1541):789&#x2013;796, 2004) and Porrill et al. (PLoS Comput Biol 3:1935&#x2013;1950, 2007a) and Porrill et al. (Neural Comput 19(1), 170&#x2013;193, 2007b) have highlighted the potential importance of these recurrent connections by proposing an alternative architecture in which the cerebellum is embedded in a recurrent loop with brainstem control circuitry. In this framework, the feedforward connections are not necessary at all. The cerebellum must learn a forward model of the motor apparatus for accurate motor commands to be generated. We show here how these two models exhibit contrasting yet complimentary learning capabilities. Central to the differences in performance between architectures is that there are two distinct kinds of disturbance to which a motor system may need to adapt (1) changes in the relationship between the motor command and the observed outcome and (2) changes in the relationship between the stimulus and the desired outcome. The computational distinction between these two kinds of transformation is subtle and has therefore often been overlooked. However, the implications for learning turn out to be significant: learning with a feedforward architecture is robust following changes in the stimulus-desired outcome mapping but not necessarily the motor command-outcome mapping, while learning with a recurrent architecture is robust under changes in the motor command-outcome mapping but not necessarily the stimulus-desired outcome mapping. We first analyse these differences theoretically and through simulations in the vestibulo-ocular reflex (VOR), then illustrate how these same concepts apply more generally with a model of reaching movements.
Letters: Dynamics analysis of impulsive stochastic Cohen-Grossberg neural networks with Markovian jumping and mixed time delays
Authors: Meng Dong, Huaguang Zhang, Yingchun Wang
Venue: Neurocomputing (2009)

In this paper, the problem of dynamics analysis for a class of new impulsive stochastic Cohen-Grossberg neural networks with Markovian jumping and mixed time delays is researched. Some criteria for the asymptotical stability in mean square are obtained based on linear matrix inequality (LMI) forms, which can be easily solved by LMI Toolbox in Matlab. An example is given to show the effectiveness of the obtained results.
Determination of body measurements of a cow by image analysis
Authors: Şakir Taşdemir, Murat Yakar, Abdullah Ürkmez, Şeref İnal
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

In this study, the subject is to determine the body measurements of a Holstein cow from its photographs with image analysis. For this operation, an environment for taking the photograph, a platform and 18 points with certain coordinates were prepared. Afterwards, the photos of a Holstein cow was taken on the platform by a Nikon D100 CCD camera from various directions. The photos were analyzed by PhotoModeler 5 software. The results of this image analysis were compared to real results that were previously measured. It was found out that the real measurements and measurements obtained from photos are close to each other which shows that this method can be safely used
Contextualized query sampling to discover semantic resource descriptions on the web
Authors: Jason J. Jung
Venue: Information Processing and Management: an International Journal (2009)

Resource description extracted by query-sampling method can be applied to determine which database sources a certain query should be firstly sent to. In this paper, we propose a contextualized query-sampling method to extract the resources which are most relevant to up-to-date context. Practically, the proposed approach is adopted to personal crawler systems (the so-called focused crawlers), which can support the corresponding user's web navigation tasks in real-time. By taking into account the user context (e.g., intentions or interests), the crawler can build the queries to evaluate candidate information sources. As a result, we can discover semantic associations (i) between user context and the sources, and (ii) between all pairs of the sources. These associations are applied to rank the sources, and transform the queries for the other sources. For evaluating the performance of contextualized query sampling on 53 information sources, we compared the ranking lists recommended by the proposed method with user feedbacks (i.e., ideal ranks), and also computed the precision of discovered subsumptions as semantic associations between the sources.
Enhancement of total transfer capability using SVC and TCSC
Authors: Sara Molazei, Malihe M. Farsangi, Hossein Nezamabadi-pour
Venue: Proceedings of the 6th conference on Applications of electrical engineering (2007)

In this paper, Particle Swarm Optimization (PSO) algorithm and Guaranteed Convergence PSO (GCPSO) are proposed to determine the allocation of Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) for maximizing the Total Transfer Capability (TTC) between source and sink area by considering voltage limits and thermal limits in a power system. The optimization is made on two parameters: the location and size of devices. Also, to have a comparison, Genetic Algorithm (GA) is applied to deal with the problem. Simulation results show that standard PSO failed to solve the problem but GA and GCPSO algorithms converge to similar optimal solutions.
Mashups'07: First International Workshop on Web APIs and Services Mashups
Authors: E. Michael Maximilien, Stefan Tai
Venue: Service-Oriented Computing - ICSOC 2007 Workshops: ICSOC 2007, International Workshops, Vienna, Austria, September 17, 2007, Revised Selected Papers (2009)

Services computing and Web 2.0 computing are converging into a programmable Web today. However, the interaction and integration of the two classes of technologies and approaches expose various issues and complexities that have to be addressed, especially as these new programmable Web solutions displace current legacy distributed system applications and middleware. Mashups'07 is an international workshop intended to foster a conversation around the challenges and issues that the services computing community is facing as the Web 2.0 technologies, approaches, and techniques and the Web services more mature approaches merge to help bring about the innovation potentials of the programmable Web. The following pages constitute the post-proceedings of Mashups'07 --- the inaugural workshop in an anticipated series of workshops that look specifically at the engineering, scientific, social, and business concerns and challenges encountered from end-user-oriented compositions of Web-accessible services, APIs, and content, that is of Web mashups.
Speech Recognition Using Zero-Crossing Features
Authors: Yin Yin Aye
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

Voice recognition system is very useful in several areas of computer science and mathematics. In this paper, text-dependent speaker identification method is used. This system contains training phase, testing phase and recognition phase. In the training phase, the feature word spoken is extracted. During the testing phase, feature matching takes place. The feature that extracted is stored in the database. During the recognition phase, the features are extracted by the same techniques and are compared with the template in the database. In this thesis, the feature of the extraction takes place by Zero-crossing features.
Numerical Integration with Complex Jacobi Weight Function
Authors: Gradimir V. Milovanović, Aleksandar S. Cvetković
Venue: Numerical Analysis and Its Applications: 4th International Conference, NAA 2008, Lozenetz, Bulgaria, June 16-20, 2008. Revised Selected Papers (2009)

In this paper we study the numerical integration on (&thinsp;&minus;&thinsp;1,1) with respect to the Jacobi weight function (1&thinsp;&minus;&thinsp;x) &alpha; (1&thinsp;+&thinsp;x) &beta; , where &alpha; and &beta; are complex parameters. The problem arises in some applications of computational models in quantum mechanics. We discuss two methods for integration. One is suitable for integration of analytic functions and the other is applicable to the general Riemann integrable functions.
Natural-language help in the Consul system
Authors: William Mark
Venue: Proceedings of the June 7-10, 1982, national computer conference (1982)

If we use the model of asking an expert, it is fairly clear what users want from a help system: a service that tells them how to do something they want to do. But current help systems aren't like this. They can tell the users about system capabilities, but not in relation to what they want to do. Most help systems are simply databases of online documentation---system manuals, not system experts. Like system manuals, using them to figure out how to do something or to figure out what went wrong is a last resort---when no one else is around. Providing real expert help requires reasoning in terms of models of what the user wants to do and what the system can do. These models also make it possible to provide facilities for natural-language understanding and generation. Thus, users can deal with the system in much the same way that they deal with a human expert: by asking questions and receiving advice in English. These ideas are being tested in the Consul system, a research prototype currently under development at the USC Information Sciences Institute.