ppxscal/embedding_network huggingface dataset:
EMPATH: A Neural Network that Categorizes Facial Expressions
Authors: Matthew N. Dailey, Garrison W. Cottrell, Curtis Padgett, Ralph Adolphs
Venue: Journal of Cognitive Neuroscience (2002)

There are two competing theories of facial expression recognition. Some researchers have suggested that it is an example of "categorical perception." In this view, expression categories are considered to be discrete entities with sharp boundaries, and discrimination of nearby pairs of expressive faces is enhanced near those boundaries. Other researchers, however, suggest that facial expression perception is more graded and that facial expressions are best thought of as points in a continuous, low-dimensional space, where, for instance, "surprise" expressions lie between "happiness" and "fear" expressions due to their perceptual similarity. In this article, we show that a simple yet biologically plausible neural network model, trained to classify facial expressions into six basic emotions, predicts data used to support both of these theories. Without any parameter tuning, the model matches a variety of psychological data on categorization, similarity, reaction times, discrimination, and recognition difficulty, both qualitatively and quantitatively. We thus explain many of the seemingly complex psychological phenomena related to facial expression perception as natural consequences of the tasks' implementations in the brain.
Error resilient locally adaptive data compression
Authors: Hsien-Wen Tseng, Chin-Chen Chang
Venue: Journal of Systems and Software (2006)

A data compression scheme that exploits locality of reference has been proposed by Bentley et al. in 1986 [Bentley, J.L., Sleator, D.D., Tarjan, R.E., Wei, V.K., 1986. A locally adaptive data compression scheme. Commun. ACM 29 (4), 320-330]. The scheme is based on a self-organizing move-to-front word list. However, a single error occurred on transmission channel could cause the lists of the encoder and decoder to differ, which could corrupt all reference data that follows. To reduce the impact of losing synchronization, a new list structure for the locally adaptive data compression scheme is proposed in this paper. From our analysis and experiments, the proposed scheme can enhance error resiliency of locally adaptive data compression while preserving high compression performance.
Getting the Most Out of Ensemble Selection
Authors: Rich Caruana, Art Munson, Alexandru Niculescu-Mizil
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

We investigate four previously unexplored aspects of ensemble selection, a procedure for building ensembles of classifiers. First we test whether adjusting model predictions to put them on a canonical scale makes the ensembles more effective. Second, we explore the performance of ensemble selection when different amounts of data are available for ensemble hillclimbing. Third, we quantify the benefit of ensemble selection's ability to optimize to arbitrary metrics. Fourth, we study the performance impact of pruning the number of models available for ensemble selection. Based on our results we present improved ensemble selection methods that double the benefit of the original method.
Second-order nonlinear trajectory smoother for position control of linear switched reluctance motor
Authors: J. Wang, K. M. Tsang, N. C. Cheung
Venue: International Journal of Modelling and Simulation (2006)

Second-order nonlinear trajectory smoother is coupled with conventional cascade control for the position control of linear switched reluctance motor (LSRM) to reduce output ripples. Force and position to phase current conversion based on neural network is implemented for the modeling of the nonlinear magnetic behaviour of LSRM. The reference currents generated are used by the inner current control loop. Load observer is also introduced to tackle unknown disturbances and change of system parameters. The proposed control scheme guarantees robustness against change of system parameter and load disturbances. Simulation studies are included to demonstrate the effectiveness of the proposed control scheme.
On preparation of the atomic W-states
Authors: V. N. Gorbachev, A. A. Rodichkina, A. I. Trubilko, A. I. Zhiliba
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

We analyse possibilities for quantum state engineering offered by the resonance Raman type interaction of light with ensembles of two-level atoms taking account relaxation to prepare and control of entangled states. It is found that atomic entanglement of the W-class can be obtained during evolution of atoms interacted with a single mode squeezed light. Two schemes, involving projection measurements that result in multipartite W-like states, are introduced.
A Bridging Framework for Universal Interoperability in Pervasive Systems
Authors: Jin Nakazawa, Hideyuki Tokuda, W. Keith Edwards, Umakishore Ramachandran
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

We explore the design patterns and architectural tradeoffs for achieving interoperability across communication middleware platforms, and describe uMiddle, a bridging framework for universal interoperability that enables seamless device interaction over diverse platforms. The proliferation of middleware platforms that cater to specific devices has created isolated islands of devices with no uniform protocol for interoperability across these islands. This void makes it difficult to rapidly prototype pervasive computing applications spanning a wide variety of devices. We discuss the design space of architectural solutions that can address this void, and detail the trade-offs that must be faced when trying to achieve cross-platform interoperability. uMiddle is a framework for achieving such interoperability, and serves as a powerful platform for creating applications that are independent of specific underlying communication platforms.
RANSAC for (Quasi-)Degenerate data (QDEGSAC)
Authors: Jan-Michael Frahm, Marc Pollefeys
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

The computation of relations from a number of potential matches is a major task in computer vision. Often RANSAC is employed for the robust computation of relations such as the fundamental matrix. For (quasi-)degenerate data however, it often fails to compute the correct relation. The computed relation is always consistent with the data but RANSAC does not verify that it is unique. The paper proposes a framework that estimates the correct relation with the same robustness as RANSAC even for (quasi-)degenerate data. The approach is based on a hierarchical RANSAC over the number of constraints provided by the data. In contrast to all previously presented algorithms for (quasi-)degenerate data our technique does not require problem specific tests or models to deal with degenerate configurations. Accordingly it can be applied for the estimation of any relation on any data and is not limited to a special type of relation as previous approaches. The results are equivalent to the results achieved by state of the art approaches that employ knowledge about degeneracies.
Packet Design and Signal Processing for OFDM-Based Mobile Broadband Wireless Communication Systems
Authors: Jianhua Liu, Jian Li
Venue: IEEE Transactions on Mobile Computing (2006)

We consider improving the performance of orthogonal frequency-division multiplexing (OFDM)-based mobile broadband wireless communication (MBWC) systems. We show that a recently approved packet-based MBWC standard can cause the resulting systems to suffer from severe performance degradations for time-varying channels due to the lack of a mechanism for tracking the time-varying channels needed for coherent detection. We consider both packet design and signal processing to deal with time-varying channels. For the packet design, we segment an entire packet into multiple subpackets—with each subpacket having zero tail bits to reset the convolutional channel encoder—so that the detection/decoding result of each subpacket can be used to update the channel response for this subpacket. For signal processing, we use weighted polynomial fitting and prediction at the receiver to improve the channel tracking accuracy. Simulation results show that the coherent detection based on our new scheme can significantly outperform the commonly suggested differential modulation/detection methods.
Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners
Authors: Yan Zhang, Xingquan Zhu, Xindong Wu
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Empirical studies on supervised learning have shown that ensembling methods lead to a model superior to the one built from a single learner under many circumstances [1], especially when learning from imperfect, such as biased or noise infected, information sources. In this paper, we provide a novel corrective classification (C2) design, which incorporates error detection, data cleansing and Bootstrap sampling to construct base learners that constitute the classifier ensemble. The essential goal is to reduce noise impacts and eventually enhance the learners built from noise corrupted data. We further analyze the importance of both the accuracy and diversity of base learners in ensembling, in order to shed some light on the mechanism under which C2 works. Experimental comparisons will demonstrate that C2 is not only superior to the learner built from the original noisy sources, but also more reliable than Bagging [2] or the Aggressive Classifier Ensemble (ACE) [3], which are two degenerate components/variants of C2.
Overview and Introduction to the Workshop on Best Practice in Software Engineering: The Role of Industry in Software Engineering
Authors: J. Barrie Thompson, Helen M. Edwards
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

The interactions between Industry and Universities are examined in this open event with the aim of producing inputs to an international project that is concerned with gaining knowledge of industrial Software Engineering (SE) practices together with the development of a framework that will assist in the classification and evaluation of such practices. The key objectives for the workshop are to (i) identify the types and range of interaction between industry and academia, which enable knowledge to be gained of industrial SE practices, (ii) identify those areas in SE where best practices are most likely to be found, (iii) identify the mechanisms which could be used in the analysis of the interactions between industry and academia and which would assist in the classification and evaluation of industrial SE practices, and (iv) produce a prototype framework which would support these evaluation activities.
Simultaneous Interconnect Delay and Crosstalk Noise Optimization through Gate Sizing Using Game Theory
Authors: Narender Hanchate, Nagarajan Ranganathan
Venue: IEEE Transactions on Computers (2006)

The continuous scaling trends of interconnect wires in deep submicron (DSM) circuits result in increased interconnect delay and crosstalk noise. In this work, we develop a new postlayout gate sizing algorithm for simultaneous optimization of interconnect delay and crosstalk noise. The problem of postlayout gate sizing is modeled as a normal form game and solved using Nash equilibrium. The crosstalk noise induced on a net depends on the size of its driver gate and the size of the gates driving its coupled nets. Increasing the gate size of the driver increases the noise induced by the net on its coupled nets, whereas increasing the size of the drivers of coupled nets increases the noise induced on the net itself, resulting in a cyclic order dependency leading to a conflicting situation. It is pointed out in [1] that solving the postroute gate sizing problem for crosstalk noise optimization is difficult due to its conflicting nature. Game theory provides a natural framework for handling such conflicting situations and allows optimization of multiple parameters. By utilizing this property of game theory, the cyclic dependency of crosstalk noise on its gate sizes can be solved as well as the problem of gate sizing for simultaneous optimization of interconnect delay and crosstalk noise can be effectively modeled, whose objective function is again conflicting in nature. We have implemented two different strategies in which games are ordered according to 1) the noise criticality and 2) delay criticality of nets. The time and space complexities of the proposed gate sizing algorithm are linear in terms of the number of gates in the design. Experimental results for a noise critically ordered game theoretic approach on several medium and large open core designs indicate average improvements of 15.48 percent and 18.56 percent with respect to Cadence place and route tools in terms of interconnect delay and crosstalk noise, respectively, without any area overhead or the need for rerouting. Further, the algorithm performs significantly better than simulated annealing and genetic search as established through experimental results. A mathematical proof of existence for the Nash equilibrium solution for the proposed gate sizing formulation is also provided.
Citizenship Education Using Human- and Agent-Based Participatory Gaming Simulation
Authors: Reiko Hishiyama, Toru Ishida
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In this paper, we describe new methodologies for reinforcing the social consensus building of the multicultural coexistence assistance using participatory simulation in civil societies. In this methodology, both human and intelligent software agents participate in a participatory gaming simulation. This simulation, which has mutual interaction between humans and agents, can achieve the gathering and analyzing of beneficial information to solve problems in multicultural civil societies. This type of simulation will help to provide knowledge for the formulation of social consensus, and to create new opportunities for discussion with people with different cultures and social backgrounds.
Segmentation of Vessels Using Weighted Local Variances and an Active contour Model
Authors: W. K. Law, Albert C. S. Chung
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Performing segmentation of vasculature with blurry and low contrast boundaries in noisy images is a challenging problem. This paper presents a novel approach to segmenting blood vessels using weighted local variances and an active contour model. In this work, the vessel boundary orientation is estimated locally based on the orientation that minimizes the weighted local variance. Such estimation is less sensitive to noise compared with other common approaches. The edge clearness is measured by the ratio of weighted local variances obtained along different orientations. It is independent of the edge intensity contrast and capable of locating weak boundaries. Integrating the orientation and clearness of edges, an active contour model is employed to align contours that match the contour tangent direction and edge orientation. The proposed method is validated by two synthetic images and two real cases. It is experimentally shown that our method is suitable for dealing with noisy images which consist of structures having blurry and low contrast boundaries, such as blood vessels.
Design of Secure Dynamic Clustering Algorithm using SNEP and µTESLA in Sensor network
Authors: Kun-Won Jang, Sang-Hun Lee, Moon-Seog Jun
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02 (2006)

Contrary to general network, sensor network has many restrictions such as energy recharge. Accordingly, security mechanism used to general network cannot be applied to sensor network. Many researchers propose method of security and energy efficiency separately. To maximize energy efficiency, the methods to support data aggregation and clusterhead selection algorithm are proposed. To strengthen the security, the methods to support encryption techniques and manage a secret key that is applicable to sensor network are proposed. However, energy and security issues are trade-off. This paper is devoted to design secure routing protocol combining conventional routing protocol with security protocol. This new protocol is that encryption algorithm and key management method are applied to specific routing protocol.
A Management Framework to Recommend and Review Learning Objects in a Web-based Learning Environment
Authors: Julien Broisin, Philippe Vidal
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In previous work, we suggested a model driven approach allowing for tracking and management of both learning objects' usage and content-related activities of users involved in a wide-distributed Webbased Learning Environment. Here we present an extension of our previous model in order to provide end-users with a personalized search tool. This application recommends learning resources according to their preferences and does not require users to fill in an electronic form; the tool also offers them the opportunity to review learning content by adding tags, comments and ratings. Moreover, work is in progress to automate execution of actions that will facilitate users to be up-to-date with new learning resources matching with their preferences and created by the whole community of actors involved in the learning environment.
Different Brain Mechanisms Mediate Sensitivity to Sensory Consonance and Harmonic Context: Evidence from Auditory Event-Related Brain Potentials
Authors: Pascaline Regnault, Emmanuel Bigand, Mireille Besson
Venue: Journal of Cognitive Neuroscience (2001)

The goal of this study was to analyze the time-course of sensory (bottom-up) and cognitive (top-down) processes that govern musical harmonic expectancy. Eight-chord sequences were presented to 12 musicians and 12 nonmusicians. Expectations for the last chord were manipulated both at the sensory level (i.e., the last chord was sensory consonant or dissonant) and at the cognitive level (the harmonic function of the target was varied by manipulating the harmonic context built up by the first six chords of the sequence). Changes in the harmonic function of the target chord mainly modulate the amplitude of a positive compo nent peaking around 300 msec (P3) after target onset, reflecting top-down influences on the perceptual stages of processing. In contrast, changes in the acoustic structure of the target chord (sensory consonance) mainly modulate the amplitude of a late positive component that develops between 300 and 800 msec after target onset. Most importantly, the effects of sensory consonance and harmonic context on the event-related brain potentials associated with the target chords were found to be independent, thus suggesting that two separate processors contribute to the building up of musical expectancy.
The Effects of Guided Inquiry Approach in a Web-based Learning Environment on the Achievement of Students with Different Cognitive Style
Authors: Irfan Naufal Umar, Sajap Maswan
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Many educationists advocate the use of Web-based learning (WBL) as a platform to deliver information. Although thousands of WBL environments have been developed, most of them are tutorial-based. A guided inquiry approach offers an alternative as it allows the users to explore the environment based on a given problem. This study investigated the effectiveness of two learning approaches in a WBL environment (guided inquiry, GIA and tutorial, TuA) on the achievement of students with different cognitive styles (Field Independent, FI and Field Dependent, FD). The findings revealed that: (1) the GIA group performed significantly better than the TuA group, (2) the FI students performed significantly better than the FD students, and (3) the FI students in the GIA group performed significantly better than the FI students in the TuA group. These findings suggest that Guided Inquiry has the potential to be an effective learning approach in a web environment.
The Directed Steiner Network Problem Is Tractable for a Constant Number of Terminals
Authors: Jon Feldman, Matthias Ruhl
Venue: SIAM Journal on Computing (2006)

We consider the Directed Steiner Network problem, also called the Point-to-Point Connection problem. Given a directed graph G and p pairs {(s1,t1),...,(sp,tp)} of nodes in the graph, one has to find the smallest subgraph H of G that contains paths from si to ti for all i. The problem is NP-hard for general p, since the Directed Steiner Tree problem is a special case. Until now, the complexity was unknown for constant p \geq 3. We prove that the problem is polynomially solvable if p is any constant number, even if nodes and edges in G are weighted and the goal is to minimize the total weight of the subgraph H. In addition, we give an efficient algorithm for the Strongly Connected Steiner Subgraph problem for any constant p, where given a directed graph and p nodes in the graph, one has to compute the smallest strongly connected subgraph containing the p nodes.
Affine Parameter Estimation from the Trace Transform
Authors: Alexander Kadyrov Maria Petrou
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

In this paper, we assume that we are given the images of two segmented objects, one of which may be an affinely distorted version of the other, and wish to recover the values of the parameters of the affine transformation between the two images. The images may also differ by the overall level of illumination. The multiplicative constant of such difference may also be recovered. We present a generic theoretical framework to solve this problem. In terms of this framework, other proposed methods may be interpreted. We show how, in this framework, one can recover the affine parameters in a way that is robust to various effects, such as occlusion and illumination variation. The proposed method is generic enough to be applicable also to matching two images that do not depict the same scene or object.
A Multiresolution Terrain Model for Efficient Visualization Query Processing
Authors: Kai Xu Xiaofang Zhou
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

Multiresolution Triangular Mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods.