ppxscal/embedding_network huggingface dataset:
Fast EMG-data driven skin deformation
Authors: Mustafa Kasap, Parag Chaudhuri, Nadia Magnenat-Thalmann
Venue: Computer Animation and Virtual Worlds (2009)

Virtual characters are being modeled and animated with increasing accuracy and photorealism in current games and virtual reality simulations. However, the detailed modeling of dynamic skin deformations due to movement of the muscles during articulation is still prohibitively expensive for real-time simulations. We present in this paper a fast approach for modeling such deformations driven by Electromyography (EMG) data. We demonstrate the method on the muscles of the upper leg during a gait cycle. A muscle map, created from a 3D muscle model, is applied as a deformation map to deform the skin surface as per the underlying muscle geometry. EMG signals recorded from a gait cycle are then used to dynamically vary the weights in the deformation map during animation thus producing the dynamic skin deformations. The whole operation is done on the GPU to make it very fast and suitable forreal-time simulations. Copyright &copy; 2009 John Wiley & Sons, Ltd. This paper presents a real-time, dynamic skin deformation technique driven by recorded EMG data and a displacement map created from an accurate 3D muscle model. This results in more realistic looking simulations that are very appropriate for games and virtual reality applications.
Beamformer-aided processing of EEG signals for analysing epileptic seizures
Authors: Aime Lay-Ekuakille, Giuseppe Vendramin, Amerigo Trotta
Venue: International Journal of Advanced Media and Communication (2009)

Automatic detection of epileptic seizures, by means of online or offline procedures, is a matter of continuous research that commits many research groups. Electroencephalographic (EEG) detection is affected by interference due to specific electrode interference that can be removed by different techniques, namely, beamforming, proposed in this paper. This technique allows improving epilepsy identification technique without performing a precise selecting of higher-order spectra. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9 10 May 2008, Ottawa, ON, Canada.
Effects of time-compressed audio and adjunct images on learner recall, recognition, and satisfaction
Authors: Ann E. Barron
Venue:  (2008)

The purpose of this study was to investigate the effect of time-compressed narration and representational adjunct images on undergraduate college students&rsquo; (1) ability to recall and recognize information in a multimedia learning environment, and (2) overall satisfaction with this type of learning environment. The goals of this research were to shed light on time-compression technology incorporated into multimedia learning environments, help fill the existing gap in the research literature by merging two disjoint bodies of research, and aid instructors and instructional designers to better understand time-compression technology while creating rigorous multimedia materials. This research was guided by the underlying principles of multimedia learning. The experiment was a 4 Audio Speeds (1.0 = normal vs. 1.5 = moderate vs. 2.0 = fast vs. 2.5 = fastest rate) x Adjunct Image (Image Present vs. Image Absent) factorial design. Audio speed and adjunct image both served as between subject conditions. Cued-recall, content recognition and learner satisfaction served as the dependent measures. Multimedia interventions were developed to execute this design. A total of 305 research participants were recruited from a public, southeastern university in the United States in this study. Fifty-five percent of the participants were male and 92% indicated that English was their primary language. Forty-nine percent of the participants were junior classification, 4% were freshman, 19% were sophomore, 26% were seniors, with the remaining indicating other. The median age of the participants was 22, and ranges in age from 18 to 53 years old. Data were analyzed using a series of factorial Analysis of Variance (ANOVA) procedures. Results showed statistically significant differences at 2.5 times the normal audio speed, in which performance on cued-recall and content recognition tasks was significantly lower than other audio speeds. Furthermore, representational adjunct images had a significant positive effect on cued-recall, but not content recognition. Participants in the normal audio speed and picture present groups were significantly more satisfied than other treatments. Recommendations for future research are provided as well as advice for instructors, instructional designers and learners interested in time-compression technology.
BeTelGeuse: A Platform for Gathering and Processing Situational Data
Authors: Joonas Kukkonen, Eemil Lagerspetz, Petteri Nurmi, Mikael Andersson
Venue: IEEE Pervasive Computing (2009)

BeTelGeuse is an extensible data collection platform for mobile devices, which also automatically infers higher level context from sensor data. In this article, the authors introduce BeTelGeuse's architecture and current features, and evaluate its impact on mobile phone performance.
Boosting Protein Threading Accuracy
Authors: Jian Peng, Jinbo Xu
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Protein threading is one of the most successful protein structure prediction methods. Most protein threading methods use a scoring function linearly combining sequence and structure features to measure the quality of a sequence-template alignment so that a dynamic programming algorithm can be used to optimize the scoring function. However, a linear scoring function cannot fully exploit interdependency among features and thus, limits alignment accuracy.This paper presents a nonlinear scoring function for protein threading, which not only can model interactions among different protein features, but also can be efficiently optimized using a dynamic programming algorithm. We achieve this by modeling the threading problem using a probabilistic graphical model Conditional Random Fields (CRF) and training the model using the gradient tree boosting algorithm. The resultant model is a nonlinear scoring function consisting of a collection of regression trees. Each regression tree models a type of nonlinear relationship among sequence and structure features. Experimental results indicate that this new threading model can effectively leverage weak biological signals and improve both alignment accuracy and fold recognition rate greatly.
Succinct representation of static packet classifiers
Authors: Wencheng Lu, Sartaj Sahni
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

We develop algorithms for the compact representation of the 1- and 2-dimensional tries that are used for Internet packet classification. Our compact representations are experimentally compared with competing compact representations for 1- and multi-dimensional packet classifiers and found to simultaneously reduce the number of memory accesses required for a lookup as well as the memory required to store the classifier.
Proceedings of the 1st International Workshop on Distributed Objects for the 21st Century
Authors: Tom Van Cutsem, Jorge Fox, Ole Lehrmann Madsen, Eric Jul
Venue: European Conference on Object-Oriented Programming (2009)

Distributed Objects for the 21st Century is a thematic workshop focusing on the latest trends in distributed object computing. This is the proceedings of the first edition of the workshop. This year, the workshop was hosted by the 23rd European Conference on Object-oriented Programming (ECOOP '09) in Genova, Italy. Four position papers were selected by the organizing committee based primarily on their relevance and originality.
A new fuzzy topsis method for material handling system selection problems
Authors: Mehdi Amiri Aref, Nikbakhsh Javadian
Venue: Proceedings of the 8th WSEAS International Conference on Software engineering, parallel and distributed systems (2009)

This paper presents a fuzzy multiple criteria group decision making (FMCGDM) problem with the Technique for Order Performance by Similarity ti Ideal Solution (TOPSIS) based on the concept of positive and negative ideal solution. Triangular fuzzy numbers (TEN) among decision making process is used to evaluate the weighted different alternatives versus criteria and a fuzzy group weight is made by different experts. Various decision makers' attitudes categorized into optimistic and pessimistic judgements are introduced. Eventually, a comparison between traditional fuzzy TOPSIS method and our new and simple fuzzy TOPSIS method and defuzzified TFN is also done. Different ranking for preferred material handling devices with our approach shows the efficiency of this one.
Associative Grammar Combination Operators for Tree-Based Grammars
Authors: Yael Sygal, Shuly Wintner
Venue: Journal of Logic, Language and Information (2009)

Polarized unification grammar (PUG) is a linguistic formalism which uses polarities to better control the way grammar fragments interact. The grammar combination operation of PUG was conjectured to be associative. We show that PUG grammar combination is not associative, and even attaching polarities to objects does not make it order-independent. Moreover, we prove that no non-trivial polarity system exists for which grammar combination is associative. We then redefine the grammar combination operator, moving to the powerset domain, in a way that guarantees associativity. The method we propose is general and is applicable to a variety of tree-based grammar formalisms.
Perspectives on gesture–sound relationships informed from acoustic instrument studies
Authors: Nicolas Rasamimanana, Florian Kaiser, Frederic Bevilacqua
Venue: Organised Sound (2009)

We present an experimental study on articulation in bowed strings that provides important elements for a discussion about sound synthesis control. The study focuses on bow acceleration profiles and transient noises, measured for different players for the bowing techniques detaché and martelé. We found that maximum of these profiles are not synchronous, and temporal shifts are dependent on the bowing techniques. These results allow us to bring out important mechanisms in sound and gesture articulation. In particular, the results reveal a potential shortcoming of mapping strategies using simple frame-by-frame data-stream procedures. We propose instead to consider input control data as time functions, and consider gesture co-articulation processes.
Web-Based Tools for Codification with Medical Ontologies in Switzerland
Authors: Thorsten Kurz, Kilian Stoffel
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

This paper presents three aspects through which code retrieval from an medical ontology can be improved. First, the recall of correct codes can be increased by the application of appropriate morphological operations on query terms and the enhancement of concept names with synonymous terms. Secondly, the efficiency of a manual selection process from a result set can be improved by structuring the result set correspondingly to the original ontology. Finally direct enhancements to the structure and content of the ontologies can be made in order to personalise it. These methods were implemented and evaluated in tools for two ontologies of major importance in the Swiss health care system: the ICD 10 and the TARMED ontology.
Theory and algorithms for modern problems in machine learning and an analysis of markets
Authors: Richard Cole, Mehryar Mohri
Venue:  (2008)

The unprecedented growth of the Internet over the past decade and of data collection, more generally, has given rise to vast quantities of digital information, ranging from web documents and images, genomic databases to a vast array of business customer information. Consequently, it is of growing importance to develop tools and models that enable us to better understand this data and to design data-driven algorithms that leverage this information. This thesis provides several fundamental theoretical and algorithmic results for tackling such problems with applications to speech recognition, image processing, natural language processing, computational biology and web-based algorithms. (1) Probabilistic automata provide an efficient and compact way to model sequence-oriented data such as speech or web documents. Measuring the similarity of such automata provides a way of comparing the objects they model, and is an essential first step in organizing this type of data. We present algorithmic and hardness results for computing various discrepancies (or dissimilarities) between probabilistic automata, including the relative entropy and the Lp distance; we also give an efficient algorithm to determine if two probabilistic automata are equivalent. In addition, we study the complexity of computing the norms of probabilistic automata. (2) Widespread success of search engines and information retrieval systems has led to large scale collection of rating information which is being used to provide personalized rankings. We examine an alternate formulation of the ranking problem for search engines motivated by the requirement that in addition to accurately predicting pairwise ordering, ranking systems must also preserve the magnitude of the preferences or the difference between ratings. We present algorithms with sound theoretical properties, and verify their efficacy through experiments. (3) Organizing and querying large amounts of digitized data such as images and videos is a challenging task because little or no label information is available. This motivates transduction, a setting in which the learning algorithm can leverage unlabeled data during training to improve performance. We present novel error bounds for a family of transductive regression algorithms and validate their usefulness through experiments. (4) Finally, price discovery in a market setting can be viewed as an (ongoing) learning problem. Specifically, the problem is to find and maintain a set of prices that balance supply and demand, a core topic in economics. This appears to involve complex implicit and possibly large-scale information transfers. We show that finding equilibrium prices, even approximately, in discrete markets is NP-hard and complement the hardness result with a matching polynomial time approximation algorithm. We also give a new way of measuring the quality of an approximation to equilibrium prices that is based on a natural aggregation of the dissatisfaction of individual market participants.
Computer Algorithms, 2nd edition
Authors: Ellis Horowitz, Sartaj Sahni, Sanguthevar Rajasekaran
Venue:  (2007)

Picking up where their classic Fundamentals of Computer Algorithms left off, the acclaimed Horowitz/Sahni team offers this new title, available in both Pseudocode and C++ versions. This well-researched text takes a solid, theoretical approach to the subject and lays a basis for more in-depth study while providing opportunities for hands-on learning. Computer Science Press Pseudocode Version
Knowledge delivery methods of mathematics to engineering students in developing countries
Authors: Nabil Moussa
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

In this paper some of the knowledge delivery methods of mathematics to engineering students in developing countries are discussed. The spectrum is extended between a theoretical approach, an applied approach, a combination of both theoretical and applied approaches, usage of computers for demonstration, usage of computers as helping tool, distance learning, e-learning, and mobile learning. A brief comparison between them is correspondingly given. The recommendations and conclusion are then stated.
Analyzing opportunities for using interactive augmented prototyping in design practice
Authors: Jouke Verlinden, Imre Horváth
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (2009)

The use of tangible objects is paramount in industrial design. Throughout the design process physical prototypes are used to enable exploration, simulation, communication, and specification of designs. Although much is known about prototyping skills and technologies, the reasons why and how such models are employed in design practice are poorly understood. Advanced techniques and design media such as virtual and augmented prototyping are being introduced without insight as to their benefits. We believe that an augmented prototyping system, that is, employing augmented reality technology to combine physical and digital representations, could positively influence the design process. However, we lack knowledge on why and how it might facilitate design. This paper reports on case studies performed in different domains of industrial design. At each of three Dutch design offices, a project was followed with particular attention to physical prototyping and group activities. The projects encompassed information appliance design, automotive design, and interior design. Although the studies vary in many aspects (product domain, stakeholders, duration), the findings can be applied in conceptualizing advanced prototyping systems to support industrial design. Furthermore, the data reveal that the roles of a prototype in current practice are not necessarily utilitarian; for example, the prototype may serve as a conversation piece or as seducer. Based on so-called “hints,” bottlenecks and best practices concerning concept articulation are linked to usage scenarios for augmented tangible prototyping. The results point to modeling and communication scenarios. Detailed study of the cases indicates that communication activities, especially design reviews, would benefit most from interactive augmented prototyping.
Embedded Systems: A Contemporary Design Tool, 1st edition
Authors: James K. Peckol
Venue:  (2007)

Embedded systems exposed! From operating our cars, to controlling the elevators we ride, to doing our laundry or cooking our dinner, the special computers we call embedded systems are quietly and unobtrusively doing their jobs. Embedded systems give us the ability to put increasingly large amounts of capability into ever-smaller devices. Embedded Systems: A Contemporary Design Tool introduces you to the theoretical and software foundations of these systems, and shows you how to apply embedded systems concepts to design practical applications that solve real-world challenges. Taking the user's problem and needs as your starting point, you'll delve into each of the key theoretical and practical aspects to consider when designing an application. Author James Peckol walks you through the formal hardware and software development process, covering: * How to break the problem down into major functional blocks * Planning the digital and software architecture of the system * Designing the physical world interface to external analog and digital signals * Debugging and testing throughout the development cycle * Improving performance Stressing the importance of safety and reliability in the design and development of embedded systems and providing a balance treatment of both the hardware and software aspects of embedded systems, Embedded Systems gives you the right tools for developing safe, reliable, and robust solutions in a wide range of embedded applications. 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
Application of VPRS model with enhanced threshold parameter selection mechanism to automatic stock market forecasting and portfolio selection
Authors: Kuang Yu Huang
Venue: Expert Systems with Applications: An International Journal (2009)

This study proposes a technique based upon Fuzzy C-Means (FCM) classification theory and related fuzzy theories for choosing an appropriate value of the Variable Precision Rough Set (VPRS) threshold parameter (@b) when applied to the classification of continuous information systems. The VPRS model is then combined with a moving Average Autoregressive Exogenous (ARX) prediction model and Grey Systems theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed mechanism, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data are then reduced using a GM(1,N) model, classified using a FCM clustering algorithm, and then supplied to a VPRS classification module which selects appropriate investment stocks in accordance with a pre-determined set of decision-making rules. Finally, a grey relational analysis technique is employed to weight the selected stocks in such a way as to maximize the rate of return of the stock portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The portfolio results obtained using the proposed hybrid model are compared with those obtained using a Rough Set (RS) selection model. The effects of the number of attributes of the RS lower approximation set and VPRS @b-lower approximation set on the classification are systematically examined and compared. Overall, the results show that the proposed stock forecasting and stock selection mechanism not only yields a greater number of selected stocks in the @b-lower approximation set than in the RS approximation set, but also yields a greater rate of return.
Tool support for working with sets of source code entities
Authors: Curtis Fraser, Chris Luce, Jamie Starke, Jonathan Sillito
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Previous research has identified several challenges that programmers face in answering questions about a code base. To explore ways to overcome those challenges, we have developed a prototypical programming tool called the Code Set tool. The tool allows programmers to work with sets of source code entities in novel ways, and this support allows programmers to more directly answer a range of questions about a code base. The tool also provides important contextual information for understanding the answers to those questions. The main focus of this paper is on the design and implementation of the Code Set tool. We also report on a small user study that serves as a first step in evaluating the effectiveness of the Code Set tool.
Friction and heat transfer in slip flow boundary layer at constant heat flux boundary conditions
Authors: M. H. Yazdi, S. Abdullah, I. Hashim, A. Zaharim, K. Sopian
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This paper presents a new analysis of friction and heat transfer in the slip flow boundary layer at constant heat flux boundary conditions for both liquids and gases. By using similarity solution, the fundamental equations of the boundary layer are transformed to ordinary differential equations containing a prandtl number. These ordinary differential equations are solved numerically by using a fourth order Runge-Kutta and shooting method. Consequently, the velocity profiles, temperature profiles, the wall shear stress and the local Nusselt number exhibit a dependence on the slip coefficient. It is shown that laminar boundary layer with slip flow can sufficiently reduce wall friction through slip flow conditions for both cases and increase heat transfer rate in liquids at constant heat flux boundary conditions.