ppxscal/embedding_network huggingface dataset:
Modeling human motion using manifold learning and factorized generative models
Authors: Ahmed Elgammal
Venue:  (2007)

Modeling the dynamic shape and appearance of articulated moving objects is essential for human motion analysis, tracking, synthesis, and other computer vision problems. Modeling the shape and appearance of human motion is challenging due to the high dimensionality of the articulated human motion, variations of shape and appearance from different views and in different people, and the nonlinearity in shape and appearance deformations in the observed sequences. Recent interest in modeling human motion is originated from the various potential real-world applications such as visual surveillance, human-computer interaction, video analysis, computer animation, etc.We present a novel framework to model dynamic shape and appearance using nonlinear manifold embedding and factorization. We investigate different representations to embed high-dimensional human motion sequences in low dimensional spaces by supervised and unsupervised manifold learning techniques to achieve representations that capture the intrinsic structure of the motion. Nonlinear dimensionality reduction techniques based on visual data and kinematic data are applied to discover low dimensional intrinsic manifold representation for body configuration. Also, we investigate the use of supervised manifold learning from a known manifold topology to model deformation of manifolds from an ideal case. By learning nonlinear mapping from the embedding space to the input shape or appearance, we can generate shape and appearance sequences according to the motion state on the embedded manifold.We present a decomposable generative model to analyze shape and appearance variations by different factors such as person&rsquo;s style, motion type, and view point. We use multilinear analysis in the nonlinear mapping coefficient space to factorize shape and appearance variations. Also, we investigate learning generative models to represent continuous body configuration and continuous view manifolds in a product space (i.e. body configuration manifold &times; view manifold). The proposed factorized generative models provide rich models for the analysis of dynamic shape and appearance of human motion. We applied the model in computer vision problems such as inferring 3D body pose from 2D images, tracking human motion with continuous view variations within the Bayesian framework, and gait recognition. We also applied our model for facial expression analysis, tracking, recognition and synthesis.
Fundamentals of .NET 2.0
Authors: Paul D. Sheriff
Venue:  (2007)

This book is designed for anyone that wants to learn how to use the .NET Framework to create business applications. This book focuses on the Framework classes, Namespaces, how to use Visual Studio, how to handle exceptions and how to debug applications. Emphasis will be on good programming standards and practices. After reading this book you will be able to use Visual Studio .NET effectively, be able to debug your applications, and be able to handle exceptions. By the end of reading this book you will have learned the basics of .NET Programming in both VB.NET and C#. You will learn the following: - What is .NET - How to effectively use VS.NET - Some of the most commonly used Framework classes - VB.NET Language Introduction - C# Language Introduction - Exception Handling - Using the Debugger 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
Brief paper: Enhancement of the immune system in HIV dynamics by output feedback
Authors: H. Chang, A. Astolfi
Venue: Automatica (Journal of IFAC) (2009)

The human immunodeficiency virus infection, that causes acquired immune deficiency syndrome, is a dynamic process that can be modeled via differential equations. In this paper we introduce an output feedback method designed for antiretroviral drug therapy to control the immune response. The purpose of the method is to steer the system to an equilibrium condition, the long-term nonprogressor, which corresponds to an infected patient who does not develop the symptoms of acquired immune deficiency syndrome. The suggested control idea guarantees that the immune state is enhanced to a certain level, which is enough for a typical patient to be driven into the long-term nonprogressor status.
Influence analysis with homogeneous linear restrictions
Authors: Klaus L. P. Vasconcellos, L. M. Zea Fernandez
Venue: Computational Statistics Data Analysis (2009)

We discuss the problem of influence analysis for the particular situation in which the observations must satisfy a set of homogeneous linear restrictions. We present the proof of a theoretical result showing, that for this situation, we can define a system of orthogonal influence directions, as in the unrestricted problem. As an illustration, we discuss a linear regression model where some of the explanatory variables are in the form of proportions, giving also an example with a numerical data set. Our example shows that the influence measure that is here discussed can be quite effective in identifying relevant perturbations.
Design and Optimization of an XYZ Parallel Micromanipulator with Flexure Hinges
Authors: Yangmin Li, Qingsong Xu
Venue: Journal of Intelligent and Robotic Systems (2009)

In this paper, a nearly decoupled XYZ translational compliant parallel micromanipulator (CPM) is designed for micro/nano scale manipulation with features of piezo-driven actuators and flexure hinges. The CPM structure improvement is made to enlarge the workspace and eliminate or reduce the stress stiffening, buckling phenomenon, and parasitic motions of the original XYZ CPM, which leads to a new CPM with a more compact structure. The CPM kinematics, parasitic motions, and workspace are determined analytically, and the mathematical models describing statics and dynamics of the CPM are established to evaluate its related performances, which are verified by the finite element analysis (FEA) undertaken in ANSYS environment. Based on the analytic models, the CPM dimensions have been optimized by resorting to the particle swarm optimization (PSO) approach, which produces a CPM having minimum parasitic motions and satisfying other performance specifications as validated by the FEA simulations.
The prediction of AIDS survival: a data mining approach
Authors: Rosma Mohd Dom, Sameem Abdul Kareem, Basir Abidin, Adeeba Kamaruzaman, Annapurni Kajindran
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

Data mining methods which combine techniques from database research, statistics and artificial intelligence have been applied to many research disciplines including engineering, finance and medicine. The objective of this paper is to describe the feasibility of applying a predictive data mining technique to predict the survival of AIDS. An adaptive fuzzy regression technique, FuReA, was used to predict the length of survival of AIDS patients based on their CD4, CD8 and viral load counts. Predictive ability of FuReA was measured and compared with fuzzy neural network prediction models. We found that both FuReA and fuzzy neural network models were able to predict the survival of AIDS with an accuracy of 60% to 100% based on selected dependent variables. These provisionary results demonstrate the viability of FuReA in predicting survival among AIDS patients.
Implementing relationships among classes of analysis pattern languages using aspects
Authors: Rosana T. Vaccare Braga, Rodrigo H. Roldão Marchesini
Venue: Proceedings of the Workshop on Relationships and Associations in Object-Oriented Languages (2009)

Patterns within an analysis pattern language are related to each other in several ways: the application of a pattern can result in the application of another, a pattern can be applied only if another pattern was applied (or was not applied), etc. Also, several variants of a pattern may co-exist, and the application of a particular variant can lead to the inclusion or removal of associations between classes that form the pattern. In this paper, we show how we have used aspect-oriented programming to implement relationships between classes of an analysis pattern or between classes shared by more than one pattern. This allows the incremental development of a framework to support the pattern language, and also eases the instantiation of patterns and pattern variants.
Genetic programming approach to predict a model acidolysis system
Authors: Ozan Nazım Çiftçi, Sibel Fadıloğlu, Fahrettin Göğüş, Aytaç Güven
Venue: Engineering Applications of Artificial Intelligence (2009)

This paper models acidolysis of triolein and palmitic acid under the catalysis of immobilized sn-1,3 specific lipase. A gene-expression programming (GEP), which is an extension to genetic programming (GP)-based model was developed for the prediction of the concentration of major reaction products of this reaction (1-palmitoyl-2,3-oleoyl-glycerol (POO), 1,3-dipalmitoyl-2-oleoyl-glycerol (POP) and triolein (OOO). Substrate ratio (SR), reaction temperature (T) and reaction time (t) were used as input parameters. The predicted models were able to predict the progress of the reactions with a mean standard error (MSE) of less than 1.0 and R of 0.978. Explicit formulation of proposed GEP models was also presented. Considerable good performance was achieved in modelling acidolysis reaction by using GEP. The predictions of proposed GEP models were compared to those of neural network (NN) modelling, and strictly good agreement was observed between the two predictions. Statistics and scatter plots indicate that the new GEP formulations can be an alternative to experimental models.
Motivating Students by Technologies: A Case Study on Adopting Tips Pedagogy in a General Physics Course
Authors: Yu-Fen Chen, Sung-Bin Chang, Chen-Chung Liu, Yi-Wen Chu, Ben Chang, Tak-Wai Chan
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

This paper describes a case study on adopting TIPS pedagogy in a general physics course. The TIPS pedagogy is reviewed with ARCS model on how to motivate students by technologies, such as network and IrDA devices. This study also proposed observations of students' motivation and changing behaviors.
Analysis and improvement method for an experimental/industrial process of hydrogen cryogenic distillation
Authors: Iuliana Stefan, Liviu Stefan, Carmen Moraru, Ioan Stefanescu, Ovidiu Balteanu, Ciprian Bucur
Venue: Proceedings of the 2nd conference on European computing conference (2008)

This paper present an analysis and improvement method for an experimental process of hydrogen cryogenic distillation. The method is based on a software development which uses as input data the information acquired from the process and provides, graphically and as a value, the operating parameters of the plant equipments. It is shown that the LabView platform can ensure the interface between automation (data acquisition) and thermodynamics and it can also be subsequently developed for the industrial model of a cryogenic distillation plant.
On Implementability of the Formal Specifications
Authors: Victor Malyshkin
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

The paper is devoted to the consideration of the problem of formal specifications implementability and program synthesis.
Safety loading in the annuity pension fund dynamics
Authors: Marilena Sibillo, Mariarosaria Coppola, Valeria D'Amato, Emilia Di Lorenzo
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

The portfolio consistency fund studied in the paper is referred to a pension scheme of beneficiaries entering in the retirement state at the same time. It arises from the payment stream consisting in cash flows due at the beginning of each year in case of life of the pensioner: in the deferment period, in the form of premiums entering in the fund, and during the retirement period, in the form of instalments getting out of it. The fund dynamic as function of the time of valuation evolves increasing thanks to the interest maturing on the accumulated fund and decreasing because of the benefits paid to the survivals. Both the mortality trend, determining the number of payments at each time, and the interest maturing on the fund, are considered deterministically unknown at the moment of the contract issue. Stochastic assumptions about the behaviour of the interest rate process and the description of the mortality trend betterment, most likely to be expected in very long periods and in civilized world, provide a dynamic description of the pension scheme and in particular of the pension fund. In the paper we want to deepen the aspect of the financial and demographic basis chosen for premium calculation with respect to the impact on the portfolio fund consistency and on the risk arising from the randomness in the choice of the survival model used for the valuations. To this aim, we will assume for the fund description different projection levels for the survival probabilities and the Vasicek hypotheses for the interest rates maturing on the fund itself; moreover, we will determine the premium amounts introducing different scenarios in a safety loading perspective. As evident, in the premium quantification lower interest rate jointly with higher survival probabilities constitute a form of implied loading. The numerical application presented in the paper shows how the change in the premium calculation conditions affects the portfolio fund consistency in the different scenarios and investigates on the impact they have on the Demographic Model Risk Measure. Useful information for managing aim can be derived.
Structural Considerations in Defining Executable Process Models
Authors: Borislava I. Simidchieva, Leon J. Osterweil, Alexander Wise
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

This paper examines the question of how to structure the representation of a process in order to assure that the representation is effective in supporting such diverse activities as process understanding, communication among process participants, and process execution. The paper uses the example of a negotiation process to demonstrate that one process structure (which we refer to as the narrative form) seems to be quite effective in supporting understanding and communication, but then indicates that this structure seems problematic in supporting process execution. The paper indicates that a different structure (which we refer to as the role-oriented form) seems much more appropriate and effective in supporting execution, but may be lacking at supporting communication. In addition to serving different purposes, the two structures seem to represent different underlying models---a static process model, and a similar, but more complex, execution model. The properties of these two complementary structures are then analyzed and evaluated. The paper then uses these observations to raise questions about the underlying needs for effective process representation, suggesting in particular that a single process representation may not be a suitable basis for supporting the range of needs that process representations are expected to address.
Middleware for Automated Implementation of Security Protocols
Authors: Béla Genge, Piroska Haller
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

We propose a middleware for automated implementation of security protocols for Web services. The proposed middleware consists of two main layers: the communication layer and the service layer. The communication layer is built on the SOAP layer and ensures the implementation of security and service protocols. The service layer provides the discovery of services and the authorization of client applications. In order to provide automated access to the platform services we propose a novel specification of security protocols, consisting of a sequential component, implemented as a WSDL-S specification, and an ontology component, implemented as an OWL specification. Specifications are generated using a set of rules, where information related to the implementation of properties such as cryptographic algorithms or key sizes, are provided by the user. The applicability of the proposed middleware is validated by implementing a video surveillance system.
Applications of Soft Computing: Updating the State of the Art, 1st edition
Authors: Erel Avineri, Erel Avineri, Mario Kppen, Keshav Dahal, Yos Sunitiyoso, Rajkumar Roy
Venue: Advances In Intelligent And Soft Computing (2009)

Soft Computing is a complex of methodologies that includes artificial neural networks, genetic algorithms, fuzzy logic, Bayesian networks, and their hybrids. It admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic the remarkable human capability of making decisions in real-life, ambiguous environments. Soft Computing has therefore become popular in developing systems that encapsulate human expertise. 'Applications of Soft Computing: Updating the State of Art' contains a collection of papers that were presented at the 12th On-line World Conference on Soft Computing in Industrial Applications, held in October 2007. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including design, intelligent control, optimization, signal processing, pattern recognition, computer graphics, production, as well as civil engineering and applications to traffic and transportation systems. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.
Scalable and Efficient Multiagent Platform Closer to the Operating System
Authors: Juan M. Alberola, Jose M. Such, Agustin Espinosa, Vicent Botti, Ana Garcia-Fornes
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

Agent technology demands support to build complex, open and large-scale applications. Therefore, efficient, scalable and robust Multiagent Platforms are needed. The performance of current Multiagent Platforms, which are usually developed in Java, has been tested in different studies. Results presented in these studies show that the performance of these Multiagent Platforms is not as good as one could expect. We present in this paper a different approach of a Multiagent Platform closer to the Operating System level to improve the performance achieved. This platform is focused on offering the main services required by a Multiagent platform and also improving the functionality of some of them, such as the messaging service. In this sense, we extend this functionality with advanced communication mechanisms such as agent groups and predefined interaction protocols. We also present a performance evaluation of the current platform implementation.
Clustering for user modeling in recommender e-commerce application: A RUP-based intelligent software life-cycle
Authors: Anastasios Savvopoulos, Maria Virvou, Dionysios N. Sotiropoulos, George A. Tsihrintzis
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

In this paper we will present an RUP based software life cycle on how to incorporate a clustering algorithm on a prototype system. The process has four major steps. Firstly, designing and building in an adaptive application. Secondly, evaluating the system and through this process obtaining data for the clustering algorithms. Thirdly, compare the clustering algorithms with the above data as input. Fourthly, incorporate the best clustering algorithm into the system and building stereotypes. In our case we used an adaptive e-shop application as a test bed in order to apply these methods. The adaptive e-shop application that provides personalised recommendations to users.
Semi-supervised learning using label mean
Authors: Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances in the efficient training of the (supervised) SVM. In this paper, we show that S3VMs, with knowledge of the means of the class labels of the unlabeled data, is closely related to the supervised SVM with known labels on all the unlabeled data. This motivates us to first estimate the label means of the unlabeled data. Two versions of the meanS3VM, which work by maximizing the margin between the label means, are proposed. The first one is based on multiple kernel learning, while the second one is based on alternating optimization. Experiments show that both of the proposed algorithms achieve highly competitive and sometimes even the best performance as compared to the state-of-the-art semi-supervised learners. Moreover, they are more efficient than existing S3VMs.
Extraction of tree adjoining grammars from a treebank for Korean
Authors: Jungyeul Park
Venue: Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (2006)

We present the implementation of a system which extracts not only lexicalized grammars but also feature-based lexicalized grammars from Korean Sejong Treebank. We report on some practical experiments where we extract TAG grammars and tree schemata. Above all, full-scale syntactic tags and well-formed morphological analysis in Sejong Treebank allow us to extract syntactic features. In addition, we modify Treebank for extracting lexicalized grammars and convert lexicalized grammars into tree schemata to resolve limited lexical coverage problem of extracted lexicalized grammars.
Cross-artifact traceability using lightweight links
Authors: Sukanya Ratanotayanon, Susan Elliott Sim, Derek J. Raycraft
Venue: Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering (2009)

Much research in traceability has focused on following requirements and features over the early phases of the software lifecycle. There has been comparatively little work on traceability into later phases and artifacts. In this paper, we tackle the problem of traceability across artifacts, including documents and source code, and maintaining traceability links through successive changes. We have developed Zelda, a prototype for associating arbitrary lines in text-based files with a feature map. This representation can be used to link together sections from many types of artifacts and can also contain annotations and notes. Zelda automatically tracks and presents the locations of these links in subsequent versions of the artifacts. We evaluated Zelda using 25 versions of jEdit, (260 KLOC). The overall precision for 419 links across the five features was 0.90 and the recall was 0.73. The average precision and recall per features is 0.78 and 0.69 respectively.