ppxscal/embedding_network huggingface dataset:
Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis
Authors: Jieping Ye, Ravi Janardan, Qi Li
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

High-dimensional data appear in many applications of data mining, machine learning, and bioinformatics. Feature reduction is commonly applied as a preprocessing step to overcome the curse of dimensionality. Uncorrelated Linear Discriminant Analysis (ULDA) was recently proposed for feature reduction. The extracted features via ULDA were shown to be statistically uncorrelated, which is desirable for many applications. In this paper, an algorithm called ULDA/QR is proposed to simplify the previous implementation of ULDA. Then, the ULDA/GSVD algorithm is proposed, based on a novel optimization criterion, to address the singularity problem which occurs in undersampled problems, where the data dimension is larger than the sample size. The criterion used is the regularized version of the one in ULDA/QR. Surprisingly, our theoretical result shows that the solution to ULDA/GSVD is independent of the value of the regularization parameter. Experimental results on various types of data sets are reported to show the effectiveness of the proposed algorithm and to compare it with other commonly used feature reduction algorithms.
A High-Level Architecture of a Metadata-based Ontology Matching Framework
Authors: Malgorzata Mochol, Elena Paslaru Bontas Simperl
Venue: Proceedings of the 17th International Conference on Database and Expert Systems Applications (2006)

One of the pre-requisites for the realization of the Semantic Web vision are matching techniques which are capable of handling the open, dynamic and heterogeneous nature of the semantic data in a feasible way. Currently this issue is not being optimally resolved; the majority of existing approaches to ontology matching are (implicitly) restricted to processing particular classes of ontologies and thus unable to guarantee a predictable result quality on arbitrary inputs. Accounting for the empirical findings of two case studies in ontology engineering, we argue that a possible solution to cope with this situation is to design a matching strategy which strives for an optimization of the matching process whilst being aware of the inherent dependencies between algorithms and the types of ontologies these are able to process successfully. We introduce a matching framework that, given a set of ontologies to be matched described by ontology metadata, takes into account the capabilities of existing matching algorithms (matcher metadata) and suggests, by using a set of rules, appropriate ones.
Towards a "personal cost" model for end-user development
Authors: Roderick A. Farmer, Baden Hughes
Venue: Proceedings of the 7th ACM SIGCHI New Zealand chapter's international conference on Computer-human interaction: design centered HCI (2006)

Software cost estimation techniques are used to provide a useful measure of the complexities, efforts, and costs involved in system development. Despite three decades of research on software cost estimation, the research community has yet to provide a viable model for End-User Development (EUD) environments. This is both surprising and significant as EUD has been estimated to account for somewhere between 80--95% of all personal software development activities worldwide. As EUD is predominantly idiosyncratic, self-determined and opportunistic, existing cost estimation techniques are either inappropriate, overly complex or insufficient. In response, we present a novel "personal cost" estimation model for EUD. This model reflects key features of non-professional programming, and provides a qualitative evaluation of personal cost as motivation, and hence, likely project success.
Striatal Contribution to Cognition: Working Memory and Executive Function in Parkinson's Disease before and after Unilateral Posteroventral Pallidotomy
Authors: M. Jahanshahi, J. Rowe, T. Saleem, R. G. Brown, P. Limousin-dowsey, J. C. Rothwell, D. G. T. Thomas, N. P. Quinn
Venue: Journal of Cognitive Neuroscience (2002)

The basal ganglia are intimately connected to the frontal cortex via five fronto-striatal circuits. While the role of the frontal cortex in cognition has been extensively studied, the contribution of the basal ganglia to cognition has remained less clear. In Parkinson's disease, posteroventral pallidotomy (PVP) involves surgical lesioning of the internal section of the globus pallidus (GPi, the final output pathway from the basal ganglia) to relieve the motor symptoms of the disorder. PVP in Parkinson's disease provides a unique opportunity to investigate the impact of disruption of striatal outflow to the frontal cortex on cognition. We assessed executive function and working memory after withdrawal of medication in 13 patients with Parkinson's disease before and 3 months after unilateral PVP compared to 12 age- and IQ-matched normals assessed twice with an interval of 3 months. The tests used were: Wisconsin Card Sorting (WCST), Self-Ordered Random Number Sequences, Missing Digit Test, Paced Visual Serial Addition Test (PVSAT), and Visual Conditional Associative Learning Test (VCALT). After PVP, the patients performed significantly better on the Self-Ordered Random Number Sequences and the WCST, an improvement that was also observed in the normals across the two assessment and is therefore likely to reflect practice effects. Relative to the normals, the patients showed significant differential change following PVP on the Missing Digit Test and PVSAT, on which they performed worse after compared to before surgery, while the controls performed better on the second assessment. For the patients, performance on the VCALT also indicated deterioration after PVP, but the changes approached significance. The side of PVP had no effect on the results. The pattern of change observed 3 months after PVP was maintained at 15-month follow-up. The results suggest that striatal outflow to the frontal cortex may be essential for those aspects of executive function that showed deterioration after PVP.
Super Tangrams: a child-centered approach to designing a computer supported mathematics learning environment
Authors: Kamran Sedighian, Maria Klawe
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

In this paper we describe our experience in designing and evaluating a computer supported mathematics learning environment. This experience is part of an ongoing long-term study aimed at investigating design features of mathematical computer activities which promote reflective cognition and thinking in children and improve their conceptual understanding of and attitude towards formal school subjects. This experience covers a period of over two years of close collaboration between a university researcher, almost 50 students in grades 6 and 7 (10 to 12 year old children), and their teacher, and, we believe, can provide useful insights on issues of importance in the design of electronic learning environments for children.
Octree-Based Topology-Preserving Isosurface Simplification
Authors: Ying Bai, Xiao Han, Jerry L. Prince
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Isosurface generation has many important applications in medical imaging. Standard isosurface algorithms generate very large triangle meshes when high resolution volumetric data is available, which increases rendering time and storage requirements. Most existing mesh simplification algorithms either do not guarantee non-intersecting meshes or require large cost to prevent self-intersection. We present an octree-based isosurface generation and simplification method that preserves topology, guarantees no selfintersections, and generates a surface that approximates the true isosurface of the underlying data. Rather than focusing on directly simplifying the surface mesh, the new strategy is to generate an octree grid from the original volumetric grid in a way that guarantees these desired properties of the generated isosurface. The new method demonstrates savings of 70% in mesh nodes for real 3D medical data with highly complicated shapes such as the human brain cortex and the pelvis. The simplified surface stays within a userspecified distance bound from the original finest resolution surface, preserves the original topology and has no selfintersections.
A two-phase screening procedure for simulation experiments
Authors: Susan M. Sanchez, Hong Wan, Thomas W. Lucas
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Analysts examining complex simulation models often conduct screening experiments to identify the most important factors. Controlled sequential bifurcation (CSB) is a screening procedure, developed specifically for simulation experiments, that uses a sequence of hypothesis tests to classify the factors as either important or unimportant. CSB controls the probability of Type I error for each factor, and the power at each bifurcation step, under heterogeneous variance conditions. CSB does, however, require the user to correctly state the directions of the effects prior to running the experiments. Experience indicates that this can be problematic with complex simulations.We propose a hybrid two-phase approach, FF-CSB, to relax this requirement. Phase 1 uses an efficient fractional factorial experiment to estimate the signs and magnitudes of the effects. Phase 2 uses these results in controlled sequential bifurcation. We describe this procedure and provide an empirical evaluation of its performance.
Incontrol Enterprise Dynamics: ShowFlow
Authors: Stephen Webb
Venue: Proceedings of the 37th conference on Winter simulation (2005)

ShowFlow is the software product designed to model, simulate, animate and analyze processes in commerce, logistics, manufacturing and materials handling. ShowFlow was developed from the renowned Taylor II system. ShowFlow 2, released in March 2005, contains many interesting features: screen resolutions beyond 1024x768 now supported in all visualization modes; model files are associated with ShowFlow and can be opened by clicking on them; long file names are supported; completely redesigned and many more speed bar buttons; extensively revised help file with many more hints and tips. If you want to introduce simulation into your organization and are looking for a low-budget powerful simulator, visit our product presentation - we will demonstrate the potential of ShowFlow with a number of reference projects.
Fault-Tolerant Rate-Monotonic Scheduling Algorithm in Uniprocessor Embedded Systems
Authors: Hakem Beitollahi, Geert Deconinck
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

The general approach to fault tolerance in uniprocessor systems is to use time redundancy in the schedule so that any task instance can be re-executed in presence of faults during the execution. In this paper a scheme is presented to add enough and efficient time redundancy to the Rate- Monotonic (RM) scheduling policy for periodic real-time tasks. This scheme can be used to tolerate transient faults during the execution of tasks. For performance evaluation of this idea a tool is developed.
Evaluation of methods used to detect warm-up period in steady state simulation
Authors: Prasad S. Mahajan, Ricki G. Ingalls
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper reviews the performance of various methods used to detect the warm up length in steady state discrete event simulation. An evaluation procedure is used to compare the methods. The methods are applied to the output generated by a simple job shop model. The performance of the methods is tested at different levels of utilizations. Various measures of goodness are used to assess the effectiveness of the methods.
A smart home agent for plan recognition
Authors: Bruno Bouchard, Abdenour Bouzouane, Sylvain Giroux
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We propose a formal framework to keyhole plan recognition based on lattice theory and action description logic. This framework minimizes the uncertainly about the prediction of the observed agent's behaviour by dynamically generating new implicit intentions. This approach offers an effective solution to actual recognition of ADL in a smart home, in order to provide assistance to persons suffering from cognitive deficiencies.
Fast communication: Non-linear RLS-based algorithm for pattern classification
Authors: Emilio Soria-Olivas, Gustavo Camps-Valls, José D. Martín-Guerrero, Javier Calpe-Maravilla, Joan Vila-Francés, Antonio J. Serrano-López
Venue: Signal Processing (2006)

A new non-linear recursive least squares (RLS) algorithm is presented in the context of pattern classification problems. The algorithm incorporates the non-linearity of the filter's output in the updating rules of the classical RLS algorithm. The proposed method yields lower stationary error levels when compared to the standard LMS and RLS algorithms in a classical application of pattern classification, such as the channel equalization problem.
Steganographic Scheme for VQ Compressed Images Using Progressive Exponential Clustering
Authors: Yue Li, Chang-Tsun Li
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

In this work, we propose a steganographic scheme for embedding secret message in VQ-compressed images, which aims to achieve high embedding capacity while keeping distortion low. To achieve these objectives, we develop a progressive exponential clustering (PEC) algorithm for partitioning the VQ codebook into a set of clusters. To embed the secret message based on the clustering, we substitute the indexes of the codewords with others within the same cluster according to the size of the cluster and the secret message bits.
Displacement-covariant time-frequency energy distributions
Authors: F. Hlawatsch, H. Bolcskei
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

Important classes of quadratic time-frequency representations (QTFRs), such as Cohen's (1966) class and the affine, hyperbolic, and power classes, are special cases within a general theory of displacement-covariant QTFRs. We present a theory of quadratic time-frequency energy distributions that satisfy a covariance property and generalized marginal properties. The theory coincides with the characteristic function method of Cohen and Baraniuk (see Proc. ICASSP-94, vol.3, p.357-360, 1994) in the special case of "conjugate operators".
Design of a Fuzzy Decision-Making Model and Its Application to Software Functional Size Measurement
Authors: Xunmei Gu, Guoxin Song, Lizhong Xiao
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

COSMIC-FFP as a Functional Size Measurement method has greatly improved the estimation of real-time software system. Based on math expectation and variance, this paper puts forward the concepts of fuzzy expectation and fuzzy variance. And then the fuzzy regression analysis is formed on the basis of these concepts. The effort estimation decision-making model, which can determine regression frequency according to actual needs, is established based on this fuzzy regression analysis. This effort estimation decision-making model can also make the disturbance of morbid data and bad information in regression analysis to the decision result decrease bit by bit until we are satisfied. When applying this estimation model to software metrics of COSMIC-FFP, we can estimate the effort accurately, which leads to a correct decision.
Quality of Service (QoS) Contract Specification, Establishment, and Monitoring for Service Level Management
Authors: Changzhou Wang, Guijun Wang, Haiqin Wang, Alice Chen, Rodolfo Santiago
Venue: Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops (2006)

This paper describes an approach and the architecture of Quality of Service (QoS) contract specification, establishment, and monitoring for Service Level Management (SLM). Contract is an essential concept in SLM. The service consumer side and the service provider side must share common understanding of QoS characteristics and agree on the common language for specifying desired QoS parameters in the form of QoS contracts. A service consumer must also negotiate with a service provider to establish mutually agreed QoS contracts for an interactive session. The service provider must consider QoS contracts already agreed upon with existing consumers and system resource conditions in establishing a new QoS contract. Similarly, a service consumer must be prepared in revising its contract with the service provider as conditions change over time. Once a QoS contract is established, SLM must provide monitoring to make sure that the service is provided at agreed QoS parameter range. If necessary, SLM must activate adaptation mechanisms to bring the service quality to the desired level. A case study is presented to validate the QoS contract management design approach and architecture for SLM.
Panoramic Appearance Map (PAM) for Multi-camera Based Person Re-identification
Authors: Tarak Gandhi, Mohan M. Trivedi
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

This paper proposes a concept of panoramic appearance map to perform reidentification of a people who leave the scene and reappear after some time. The map is a compact signature of appearance information of a person extracted from multiple cameras. The person is detected and tracked in multiple cameras and triangulation is used to accurately localize the person in 3-D. A virtual cylinder is formed around the person's location and mapped onto an image with the horizontal axis representing the azimuth angle and vertical axis representing the height. Each bin in the map image gets the appearance information from all the cameras which can observe it. The maps between different tracks are matched using a weighted metric. Experimental results showing person matching and reidentification show the effectiveness of the approach.
Dynamic Hierarchical Distributed Intrusion Detection System Based on Multi-Agent System
Authors: Jun Wu, Chong-jun Wang, Jun Wang, Shi-fu Chen
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

At present, distributed intrusion detection systems are taking on more and more characteristic of distributing and intelligence. Multi-agent system (MAS), which shows its intelligence by the interaction of a group of intelligent agents, is a popular tool for building novel intrusion detection systems (IDSs). The BDI (Belief-Desire- Intention) model is a well studied architecture of agency for intelligent agents situated in complex and dynamic environments. Traditional MAS-based distributed IDSs commonly do their detection work within a framework that employs the method of distributed data collection and hierarchical data analysis. This is a simple and strict method, but it restricts the characteristic of distributing, intelligence and real-time response badly. In this paper, we present a dynamically-created hierarchical framework, and then bring forward the basic algorithm system to support it. We introduce the opponent BDI model to our agents, and realize the detection based on multi-agent cooperation, which effectively improves the traditional distributed intrusion detection.
Motion-based selection of relevant video segments for video summarisation
Authors: N. Peyrard, P. Bouthemy
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

We present a method for motion-based video segmentation and segment classification as a step towards video summarisation. The sequential segmentation of the video is performed by detecting changes in the dominant image motion, assumed to be related to camera motion. It is achieved by analysing the temporal variations of coefficients of the global 2D affine motion model (robustly) estimated. The obtained video segments supply reasonable temporal regions to apply a classification algorithm. To this end, we adopt a statistical representation of the residual motion content of the video scene, relying on the distribution of temporal cooccurrences of local motion-related measurements. Pre-identified classes of dynamic events are learned off-line from a training set of video samples of the genre of interest. Each video segment is then classified according to a maximum likelihood (ML) principle. Finally, excerpts of the relevant classes can be selected for video summarisation.
Mass preserving finite element implementations of the level set method
Authors: Daniele A. Di Pietro, Stefania Lo Forte, Nicola Parolini
Venue: Applied Numerical Mathematics (2006)

In the last two decades, the level set method has been extensively used for the numerical solution of interface problems in different domains. The basic idea is to embed the interface as the level set of a regular function. In this paper we focus on the numerical solution of interface advection equations appearing in free-surface fluid dynamics problems, where naive finite element implementations are unsatisfactory. As a matter of fact, practitioners in fluid dynamics often complain that the mass of each fluid component is not conserved, a phenomenon which is therefore often referred to as mass loss. In this paper we propose and compare two finite element implementations that cure this ill-behaviour without the need to resort to combined strategies (such as e.g. particle level set). The first relies on a discontinuous Galerkin discretization, which is known to give very good performance when facing hyperbolic problems; the second is a stabilized continuous FEM implementation based on the stabilization method presented in [N. Parolini, Computational fluid dynamics for Naval engineering applications, PhD thesis, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, June 2004], which is free from many of the problems that classical methods exhibit when applied to unsteady problems.
Non-parametric identification of QAM constellations in noise
Authors: Q. Zhu, M. Kam, R. Yeager
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

The objective of the proposed classifier is the correct identification of a signal which belongs to a set of equally likely quadrature amplitude modulation (QAM) constellations and is received in additive noise. The parametric solution for this task which maximizes the average probability of correct decision is a maximum-likelihood (ML) classifier. However, this classifier needs the exact density function of the noise, which is often unknown. The alternative undertaken here is to develop a non-parametric classifier. Its decision statistic is the location of the first zero-crossing (FZC) in the characteristic function of the received symbols. The FZC-based classifier is inferior to the ML classifier in terms of the nominal performance. However, it puts only mild technical conditions on the probability density function of the noise and does not require additional information. Analytical expressions for the performance of the FZC-based classifier are derived, and performance is compared with that of the fully-informed ML classifier. The comparison is performed by evaluating the signal-to-noise ratio and the number of symbols that are needed for the two classifiers to have the same average correct-classification rate. Overall the FZC-based decision-maker provides a robust and practical alternative to the optimal, but often impractical, ML classifier.