ppxscal/embedding_network huggingface dataset:
A Model of Non-elemental Associative Learning in the Mushroom Body Neuropil of the Insect Brain
Authors: Jan Wessnitzer, Barbara Webb, Darren Smith
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

We developed a computational model of the mushroom body (MB), a prominent region of multimodal integration in the insect brain, and tested the model's performance for non-elemental associative learning in visual pattern avoidance tasks. We employ a realistic spiking neuron model and spike time dependent plasticity, and learning performance is investigated in closed-loop conditions. We show that the distinctive neuroarchitecture (divergence onto MB neurons and convergence from MB neurons, with an otherwise non-specific connectivity) is sufficient for solving non-elemental learning tasks and thus modulating underlying reflexes in context-dependent, heterarchical manner.
SSML for Arabic Language
Authors: Noor Shaker, Mohamed Abou-Zleikha, Oumayma Al Dakkak
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

This paper introduces SSML for using with Arabic language. SSML is part of a larger set of markup specifications for voice browsers developed through the open processes of the W3C. The essential role of the markup language is to give authors of synthesizable content a standard way to control aspects of speech output such as pronunciation, volume, pitch, rate, etc. across different synthesis-capable platforms. We study SSML, the validity to extend SSML for Arabic language by building Arabic SSML project for parsing SSML document and extracting the speech output.
Bayesian shrinkage prediction for the regression problem
Authors: Kei Kobayashi, Fumiyasu Komaki
Venue: Journal of Multivariate Analysis (2008)

We consider Bayesian shrinkage predictions for the Normal regression problem under the frequentist Kullback-Leibler risk function. Firstly, we consider the multivariate Normal model with an unknown mean and a known covariance. While the unknown mean is fixed, the covariance of future samples can be different from that of training samples. We show that the Bayesian predictive distribution based on the uniform prior is dominated by that based on a class of priors if the prior distributions for the covariance and future covariance matrices are rotation invariant. Then, we consider a class of priors for the mean parameters depending on the future covariance matrix. With such a prior, we can construct a Bayesian predictive distribution dominating that based on the uniform prior. Lastly, applying this result to the prediction of response variables in the Normal linear regression model, we show that there exists a Bayesian predictive distribution dominating that based on the uniform prior. Minimaxity of these Bayesian predictions follows from these results.
Transitioning multiagent technology to UAV applications
Authors: Paul Scerri, Tracy Von Gonten, Gerald Fudge, Sean Owens, Katia Sycara
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track (2008)

This paper describes the transition of academically developed multiagent technology for UAV coordination to an industrially developed application. The specific application is the use of lightweight UAVs with small Received Signal Strength Indicator sensors to cooperatively locate targets emitting radio frequency signals in a large area. It is shown that general techniques can be effectively transitioned, sometimes with minimal changes. However, clear differences in engineering and testing requirements of academia and commercialization require extensive effort in developing simulation and live flight testbeds. Although the technology has not yet been commercialized, initial live flight testing shows the potential of the approach.
Neural Networks to Predict Schooling Failure/Success
Authors: María Angélica Pinninghoff Junemann, Pedro Antonio Salcedo Lagos, Ricardo Contreras Arriagada
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

This paper depicts an already developed experience in search for a predictable mechanism with respect to the future performance of a student considering the numerous factors that influence in its failure/success. The use of different neural networks configurations in conjunction with a large data volume on top of detailed attributes consideration for each student makes for an adequate base for the results obtained to be analyzed. The idea behind this paper is to arrange a mechanism that allows us to estimate before hand taking into consideration data from the student in reference to family, social and wealth surroundings for the student future performance identifying those factors that favors the tendency to failure or success.
Japanese Hand Sign Recognition System
Authors: Hirotada Fujimura, Yuuichi Sakai, Hiroomi Hikawa
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper discusses a Japanese hand sign recognition system with a simple classifier network. In the system, input hand images are preprocessed through horizontal/vertical projection followed by discrete Fourier transforms (DFTs) that calculate the magnitude spectrum. The magnitude spectrum is used as the feature vector. Use of the magnitude spectrum makes the system very robust against the position changes of the hand image. The final classification is carried out by the classifier network, which uses simple neurons. Each neuron evaluates the possibility of the input vector belonging to assigned cluster. From the evaluation results, the hand sign is identified. The feasibility of the system is verified by simulations. The simulation results show that the average recognition rate of the system is 93% even though the hand positions are changed randomly.
A Causal Analysis for the Expenditure Data of Business Travelers
Authors: Rob Law, Gang Li
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Determining the causal relation among attributes in a domain is a key task in the data mining and knowledge discovery. In this paper, we applied a causal discovery algorithm to the business traveler expenditure survey data [1]. A general class of causal models is adopted in this paper to discover the causal relationship among continuous and discrete variables. All those factors which have direct effect on the expense pattern of travelers could be detected. Our discovery results reinforced some conclusions of the rough set analysis and found some new conclusions which might significantly improve the understanding of expenditure behaviors of the business traveler.
Automatic Presentations for Cancellative Semigroups
Authors: Alan J. Cain, Graham Oliver, Nik Ruškuc, Richard M. Thomas
Venue: Language and Automata Theory and Applications: Second International Conference, LATA 2008, Tarragona, Spain, March 13-19, 2008. Revised Papers (2008)

This paper studies FA-presentable structures and gives a complete classification of the finitely generated FA-presentable cancellative semigroups. We show that a finitely generated cancellative semigroup is FA-presentable if and only if it is a subsemigroup of a virtually abelian group.
Traffic sign shape classification and localization based on the normalized FFT of the signature of blobs and 2D homographies
Authors: Pedro Gil Jiménez, Saturnino Maldonado Bascón, Hilario Gómez Moreno, Sergio Lafuente Arroyo, Francisco López Ferreras
Venue: Signal Processing (2008)

The main goal of a traffic sign recognition system is the detection and recognition of every traffic sign present in the scene. Frequently, the image processing system is divided into three parts, namely, segmentation, detection and recognition. In this work, we will focus on the detection block, dividing it into two sub-blocks that perform shape classification and localization of the sign, respectively. The classification of the shape is performed by means of the signature of the connected components. Object rotations are tackled with the use of the FFT, and the normalization of the object eccentricity improves the performance in the presence of projection distortions. The effect of occlusions are lowered removing the concave parts of the shape. Finally, we propose a novel algorithm, which computes a 2D homography, to re-orientate the sign for further steps, like sign recognition. Experimental results, evaluated using a huge set of randomly generated synthetic images are also given, showing a great robustness of the algorithm to object scaling, rotation, projective deformation, partial occlusions and noise.
What's My Challenge? The Forgotten Part of Problem Solving in Computer Science Education
Authors: Ralf Romeike
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

In this paper we present a teaching framework that extends the traditional problem solving method in computer science education in order to increase student motivation. It replaces problems by so-called challenges and in particular emphasizes the learning situation and inspiration of the students. Furthermore it combines several pedagogical principles and applies them in a process of how students learn in a motivating and self-regulated way. In order to justify the necessity of a new concept, problems in the traditional problem solving approaches in general high school education are highlighted. Implications from research addressing similar issues are summarized. In order for addressing students' motivation changes are necessary; challenges can provide a basis to start from.
PLS Mixture Model for Online Dimension Reduction
Authors: Jiro Hayami, Koichiro Yamauchi
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This article presents an online learning method for modeling high dimensional input data. This method approximates a nonlinear function by summing up several local linear functions. Each linear function is represented as the weighted sum of a small number of dominant variables, which are extracted by the partial least squares (PLS) regression method. Moreover, a radial function, which represents the respective input area of each linear function, is also redefined using the dominant variables. This article also presents an online deterministic annealing expectation maximization (DAEM) algorithm which includes a temperature control mechanism for acquireing the most suitable system parameters. Experimental results show the effective learning behavior of the new method.
Formal Description and Verification of Web Service Composition Based on OOPN
Authors: Jindian Su, Shanshan Yu, Heqing Guo
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

To overcome the shortcomings of unable to demonstrate the characteristics of encapsulation, reusability and message-driven when using Petri nets to model Web service composition, this paper proposes object oriented Petri nets (OOPN) as the formal description and verification tool for Web service composition. Some basic concepts of OOPN, including class net, inheritance, object net and object net system, are given in the paper respectively and the mechanisms of "Gate" and "Port" are used to describe message transfer and synchronization relationships among objects. The OOPN expressions of various basic control flow structure and message synchronization relationships of Web service composition are also stated. Finally, we give a case study to show that our proposed method can more naturally and accurately demonstrate the encapsulation and message-driven characteristics of Web services.
Improved MCMC sampling methods for estimating weighted sums in Winnow with application to DNF learning
Authors: Qingping Tao, Stephen D. Scott
Venue: Machine Learning (2008)

A Markov chain Monte Carlo method has previously been introduced to estimate weighted sums in multiplicative weight update algorithms when the number of inputs is exponential. However, the original algorithm still required extensive simulation of the Markov chain in order to get accurate estimates of the weighted sums. We propose an optimized version of the original algorithm that produces exactly the same classifications while often using fewer Markov chain simulations. We also apply three other sampling techniques and empirically compare them with the original Metropolis sampler to determine how effective each is in drawing good samples in the least amount of time, in terms of accuracy of weighted sum estimates and in terms of Winnow's prediction accuracy. We found that two other samplers (Gibbs and Metropolized Gibbs) were slightly better than Metropolis in their estimates of the weighted sums. For prediction errors, there is little difference between any pair of MCMC techniques we tested. Also, on the data sets we tested, we discovered that all approximations of Winnow have no disadvantage when compared to brute force Winnow (where weighted sums are exactly computed), so generalization accuracy is not compromised by our approximation. This is true even when very small sample sizes and mixing times are used.
An Approach to a Visual Semantic Query for Document Retrieval
Authors: Paul Villavicencio, Toyohide Watanabe
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

This paper presents an approach to design an interface for document retrieval, based on techniques from the semantic web combined with interactive graphical features. The purpose of this study is to enhance the user's knowledge while he/she browses the information through a graphical interface. In this paper, two aspects are considered: Fist, interactive features such as object movability, animation, etc. are discussed. Second, a method for visually integrating the search queries and the query outputs is addressed in order to retrieve documents. The visual features and the querying method are combined taking account the semantical relations among extracted information from the documents. This combination is evaluated as a means to determine the most suitable location for the results inside the interface.
A second-order medium? The Internet as a source of electoral information in 25 European countries
Authors: Wainer Lusoli
Venue: Information Polity (2005)

There is growing interest worldwide concerning new communication technologies and the electoral process. Studies of online elections have yielded a sizeable body of knowledge on the strategies of electoral actors in an increasing range of countries. Although in the US data are routinely gathered regarding citizens' use of the Internet as a source of electoral information, limited cross-sectional evidence originates from the EU. None of this is comparative. Using data from Flash EuroBarometer 161, this article examines European citizens' use of the Internet for electoral information regarding the 2004 European Parliament election. Specifically, it discusses use of the Internet for political information in relation to location, technological development, traditional media, individual social position, political attitudes and voting turnout in 25 countries. At micro, individual level, a model is built that controls for traditional predictors of electoral media consumption, such as age, gender, education, political interest, and electoral connectedness and activity. At the macro, country level, the article explores the import of the electoral system and rules, compulsory voting, GDP per capita, levels of electoral engagement of traditional mediators (governments, parties, press) and voting turnout on the use of the Internet for electoral information. Overall, the article introduces original evidence and analysis of the role of the Internet in European elections, and contributes to the debate on the media and elections in a comparative perspective.
Slide rule: making mobile touch screens accessible to blind people using multi-touch interaction techniques
Authors: Shaun K. Kane, Jeffrey P. Bigham, Jacob O. Wobbrock
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

Recent advances in touch screen technology have increased the prevalence of touch screens and have prompted a wave of new touch screen-based devices. However, touch screens are still largely inaccessible to blind users, who must adopt error-prone compensatory strategies to use them or find accessible alternatives. This inaccessibility is due to interaction techniques that require the user to visually locate objects on the screen. To address this problem, we introduce Slide Rule, a set of audio-based multi-touch interaction techniques that enable blind users to access touch screen applications. We describe the design of Slide Rule, our interaction techniques, and a user study in which 10 blind people used Slide Rule and a button-based Pocket PC screen reader. Results show that Slide Rule was significantly faster than the button-based system, and was preferred by 7 of 10 users. However, users made more errors when using Slide Rule than when using the more familiar button-based system.
Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions
Authors: Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados Suárez, Eva Stauch
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Conventional approaches to similarity search and case-based retrieval, such as nearest neighbor search, require the specification of a global similarity measure which is typically expressed as an aggregation of local measures pertaining to different aspects of a case. Since the proper aggregation of local measures is often quite difficult, we propose a novel concept called similarity skyline. Roughly speaking, the similarity skyline of a case base is defined by the subset of cases that are most similar to a given query in a Pareto sense. Thus, the idea is to proceed from a d-dimensional comparison between cases in terms of d (local) distance measures and to identify those cases that are maximally similar in the sense of the Pareto dominance relation [2]. To refine the retrieval result, we propose a method for computing maximally diverse subsets of a similarity skyline. Moreover, we propose a generalization of similarity skylines which is able to deal with uncertain data described in terms of interval or fuzzy attribute values. The method is applied to similarity search over uncertain archaeological data.
Prediction of structures and related properties of silicon clusters
Authors: Marta B. Ferraro
Venue: Journal of Computational Methods in Sciences and Engineering (2007)

Silicon is one of the most important semi conducting materials employed in microelectronic technologies. This chapter is dedicated to review the enormous effort made during the last years to develop confident methods to determinate the geometries and related properties of silicon clusters. Searching employing full global optimization of the energy surface, using techniques like Molecular Dynamics (MD), algorithms, and local optimization of structures built onto generic structural motifs are reported. Hybrid methodologies combining tight-binding (TB) with global optimization methods also contribute to the state of the art in the prediction of the structures, and calculation of properties of silicon clusters, based on all-electron DFT methods are also included.
Digital Hardware Implementation of High Dimensional Fuzzy Systems
Authors: Pablo Echevarria, M. Victoria Martínez, Javier Echanobe, Inés Campo, Jose M. Tarela
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

This paper presents an algorithm to compute high dimensional piecewise linear (PWL) functions with simplicial division of the input domain, and introduces the circuit scheme for its implementation in a FPGA. It is also investigated how to modify this algorithm and implementation to compute a class of PWL fuzzy systems.
Building a user interface test automation framework using the data model
Authors: Kenneth Magel
Venue:  (2008)

Software testing is an expensive stage in the software project lifecycle. Testing automation is expected to reduce the cost of testing. Graphical User Interface (GUI) testing is increasingly taking a major role in the entire project validation. GUI test automation is a major challenge for software testing and test automation. Most of the current GUI test automation tools are partially automated. They require the involvement of the users or testers in several stages of the testing process. This research is about developing a framework and an application for user interface testing with the least user involvement. Fully user interface testing that does not need user supervision is not a practical solution. Users can be involved and are required to test some aspects of the user interface validation. GUI's code has some characteristics that distinguish it from the rest of the project code. Generating test cases from the GUI code requires different algorithms from those usually applied in test-case generation. We developed several GUI test generation automated algorithms that do not need any user involvement and that ensure code or branch coverage in the generated test cases. The test cases are generated from an XML GUI model or tree that represents the GUI structure. GUI execution and verification is accomplished through simulating the user interactions and then comparing the output of the execution to the input or the generated test cases.
Wireless Digital Water Meter with Low Power Consumption for Automatic Meter Reading
Authors: Young-Woo Lee, Seongbae Eun, Seung-Hyueb Oh
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Recently, several papers for reading meters remotely using RFID/USN technologies have been presented. In the case of wireless water meters, there has been neither commercial product nor paper. In this paper, we describe the design and implementation of wireless digital water meter with low power consumption. We use magnetic hole sensors to compute the amount of water consumption. The meter of water consumption is transferred via ZigBee wireless protocol to a gateway. Low power consumption design is essential since a battery should last till the life time of water meter. We suggest that dual batteries having 3V, 3000mAh, would last 8 years by analyzing the real power consumption of our water meter.
A Scenario Demonstrating Design Support in Chemical Engineering
Authors: R. Schneider, B. Westfechtel
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

The IMPROVE demonstrator is an integrated research prototype of a novel design environment for chemical engineering. Throughout the IMPROVE project, it has been considered essential to evaluate concepts and models by building innovative tools. Moreover, an integrated prototype was seen as a driving force to glue research activities together. Two versions of the demonstrator were implemented. The first version was demonstrated after the first phase of the project (from 1997 to 2000). The second demonstrator built upon the first one and was prepared at the end of the second phase (lasting from 2000 to 2003).This section describes the second demonstrator, which shows interdisciplinary cooperation (between chemical and plastics engineering), interorganizational cooperation (between a chemical engineering company and an extruder manufacturer), and synergistic tool integration.