ppxscal/embedding_network huggingface dataset:
Neural networks-based metaheuristics for solving optimization problems
Authors: Sahin Selcuk Erenguc, Anurag Agarwal
Venue:  (2006)

In this research, we propose two neural networks-based metaheuristic approaches for solving various well-known optimization problems in the literature. The first metaheuristic is called Augmented Neural Networks (AugNN). In this approach, traditional neural networks are augmented to allow embedding domain and problem-specific knowledge. The network architecture is problem specific and complex neural functions are used to (i) capture the constraints of the problem and (ii) apply a priority rule-based heuristic. Such an approach combines the advantages of known heuristics and the iterative learning of neural networks. We apply this approach to the classical open-shop scheduling problem (OSSP) and to the parallel schedule generation of resource-constrained project scheduling problem (RCPSP). The second metaheuristic that we propose is the Adaptive Learning Approach (ALA). This approach employs a one-pass heuristic to give a good starting solution in the search space and uses a weight parameter to perturb the data of the original problem in order to obtain improved solutions. The weights are then adjusted employing a search strategy which involves reinforcement and backtracking. The random perturbation allows a non-deterministic local search. We apply the improvement-heuristic approach to the flow shop scheduling problem (FSSP) in conjunction with three well-known heuristics in the literature. We also use this approach for the serial schedule generation of the RCPSP and multi-mode resource constrained project scheduling problem (MRCPSP). We empirically test our proposed approaches for each problem type on several benchmark instances in the literature and on some new problem instances generated in this study. We compare our results with lower-bound and best-known upper bound solutions. The results are extremely competitive with existing techniques such as genetic algorithms, simulated annealing, tabu search and ant colonies, in terms of both solution quality and computational times.
An Error-Resilient Algorithm Based on Partitioning of the Wavelet Transform Coefficients for a DIRAC Video Codec
Authors: Myo Tun, W. A. C. Fernando
Venue: Proceedings of the conference on Information Visualization (2006)

Video transmission over the wireless or wired network require protection from channel errors since compressed video streams are very sensitive to transmission errors because of the use of predictive coding and variable length coding. In this paper, we propose a method to achieve robustness to transmission errors to the compressed bit-stream of wavelet based open source video codec, Dirac. By partitioning the wavelet transform coefficients into groups and independently processing each group using arithmetic and Turbo coding, we could achieve the robustness to transmission errors of the compressed video stream in the packet erasure wired network. Simulation results show that the proposed technique can achieve up to 5dB PSNR gain over the un-partitioning method.
Multispectral Iris Analysis: A Preliminary Study51
Authors: Christopher Boyce, Arun Ross, Matthew Monaco, Lawrence Hornak, Xin Li
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

This paper explores the possibility of using multispectral iris information to enhance the recognition performance of an iris biometric system. Commercial iris recognition systems typically sense the iridal reflection pertaining to the near-infrared (IR) range of the electromagnetic spectrum. This work examines the iris information represented in the visible and IR portion of the spectrum. It is hypothesized that, based on the color of the eye, different components of the iris are highlighted at multiple wavelengths. To this end, an acquisition procedure for obtaining co-registered multispectral iris images associated with the IR, Red, Green and Blue wavelengths of the electromagnetic spectrum, is first discussed. The components of the iris that are revealed in multiple spectral channels/wavelengths based on the color of the eye are studied. An adaptive histogram equalization scheme is invoked to enhance the iris structure. The performance of iris recognition across multiple wavelengths is next evaluated. Experiments indicate the potential of using multispectral information to enhance the performance of iris recognition systems.
Specialization of CML message-passing primitives
Authors: John Reppy, Yingqi Xiao
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

Concurrent ML (CML) is a statically-typed higher-order concurrent language that is embedded in Standard ML. Its most notable feature is its support for first-class synchronous operations. This mechanism allows programmers to encapsulate complicated communication and synchronization protocols as first-class abstractions, which encourages a modular style of programming where the underlying channels used to communicate with a given thread are hidden behind data and type abstraction.While CML has been in active use for well over a decade, little attention has been paid to optimizing CML programs. In this paper, we present a new program analysis for statically-typed higher-order concurrent languages that enables the compile-time specialization of communication operations. This specialization is particularly important in a multiprocessor or multicore setting, where the synchronization overhead for general-purpose operations are high. Preliminary results from a prototype that we have built demonstrate that specialized channel operations are much faster than the general-purpose operations.Our analysis technique is modular (i.e.,, it analyzes and optimizes a single unit of abstraction at a time), which plays to the modular style of many CML programs. The analysis consists of three steps: the first is a type-sensitive control-flow analysis that uses the program's type-abstractions to compute more precise results. The second is the construction of an extended control-flow graph using the results of the CFA. The last step is an iterative analysis over the graph that approximates the usage patterns of known channels. Our analysis is designed to detect special patterns of use, such as one-shot channels, fan-in channels, and fan-out channels. We have proven the safety of our analysis and state those results.
Motor Cortical Activity during Interception of Moving Targets
Authors: Nicholas L. Port, Wolfgang Kruse, Daeyeol Lee, Apostolos P. Georgopoulos
Venue: Journal of Cognitive Neuroscience (2001)

The single-unit activity of 831 cells was recorded in the arm area of the motor cortex of two monkeys while the monkeys intercepted a moving visual stimulus (interception task) or remained immobile during presentation of the same moving stimulus (no-go task). The moving target traveled on an oblique path from either lower corner of a screen toward the vertical meridian, and its movement time (0.5, 1.0, or 1.5 sec) and velocity profile (accelerating, decelerating, or constant velocity) were pseudorandomly varied. The moving target had to be intercepted within 130 msec of target arrival at an interception point. By comparing motor cortical activity at the single-neuron and population levels between the interception and no-go tasks, we tested whether information about parameters of moving target is represented in the primary motor cortex to generate appropriate motor responses. A substantial number of neurons displayed modulation of their activity during the no-go task, and this activity was often affected by the stimulus parameters. These results suggest a role of motor cortex in specifying the timing of movement initiation based on information about target motion. In addition, there was a lack of systematic relation between the onset times of neural activity in the interception and no-go tasks, suggesting that processing of information concerning target motion and generation of hand movement occurs in parallel. Finally, the activity in the most motor cortical neurons was modulated according to an estimate of the time-to-target interception, raising the possibility that time-to-interception may be coded in the motor cortical activity.
Model order reduction and parameterization of nonlinear numerical models
Authors: H. Muller, S. Gotz, M. Bestehorn
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 4 (2003)

We describe techniques of model order reduction (MOR) for weakly nonlinear finite difference and finite element (FE) models. In our approach we combine the parameter identification based on linearized systems for a behavioral description of weakly nonlinear effects by means of a Taylor series expansion. To get manageable nonlinear behavioral models, we use projection based on MOR-methods (on the base of Krylov subspace and singular perturbation approaches for the linear case). We therefore take advantage of using the linearized model description in nonlinear MOR without the necessity of having an explicit formulation of the nonlinearities - such providing, for example, nonlinear MOR techniques to simulations with commercial FE software. We demonstrate the applicability of the methods on a time depending of heat transfer including material and thermal radiation nonlinearities.
Efficient Techniques for Clustering and Scheduling onto Embedded Multiprocessors
Authors: Vida Kianzad, Shuvra S. Bhattacharyya
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

Multiprocessor mapping and scheduling algorithms have been extensively studied over the past few decades and have been tackled from different perspectives. In the late 1980's, the two-step decomposition of scheduling—into clustering and cluster-scheduling—was introduced. Ever since, several clustering and merging algorithms have been proposed and individually reported to be efficient. However, it is not clear how effective they are and how well they compare against single-step scheduling algorithms or other multistep algorithms. In this paper, we explore the effectiveness of the two-phase decomposition of scheduling and describe efficient and novel techniques that aggressively streamline interprocessor communications and can be tuned to exploit the significantly longer compilation time that is available to embedded system designers. We evaluate a number of leading clustering and merging algorithms using a set of benchmarks with diverse structures. We present an experimental setup for comparing the single-step against the two-step scheduling approach. We determine the importance of different steps in scheduling and the effect of different steps on overall schedule performance and show that the decomposition of the scheduling process indeed improves the overall performance. We also show that the quality of the solutions depends on the quality of the clusters generated in the clustering step. Based on the results, we also discuss why the parallel time metric in the clustering step may not provide an accurate measure for the final performance of cluster-scheduling.
Bias and controversy: beyond the statistical deviation
Authors: Hady W. Lauw, Ee-Peng Lim, Ke Wang
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a 'data-centric approach' where the evaluation data is assumed to represent the 'ground truth'. The standard statistical approaches take evaluation and deviation at face value. We argue that attention should be paid to the subjectivity of evaluation, judging the evaluation score not just on 'what is being said' (deviation), but also on 'who says it' (reviewer) as well as on 'whom it is said about' (object). Furthermore, we observe that bias and controversy are mutually dependent, as there is more bias if there is higher deviation on a less controversial object. To address this mutual dependency, we propose a reinforcement model to identify bias and controversy. We test our model on real-life data to verify its applicability.
Ordinary User Oriented Model Construction for Assisting Conversational Agents
Authors: David Leray, Jean-Paul Sansonnet
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

In this paper, we defend the idea of integrating the actual cognitive features of novice users in the creation process of the applications to significantly increase the quality of the function of assistance. First we present a framework dedicated to the recording of novice user natural language utterances in assisting situations. Then we propose a first analysis of the collected corpus in terms of the perceptual features appearing in the linguistic referential expressions.
Genome Rearrangement Based on Reversals that Preserve Conserved Intervals
Authors: Matthias Bernt, Daniel Merkle, Martin Middendorf
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2006)

The order of genes in the genomes of species can change during evolution and can provide information about their phylogenetic relationship. An interesting method to infer the phylogenetic relationship from the gene orders is to use different types of rearrangement operations and to find possible rearrangement scenarios using these operations. One of the most common rearrangement operations is reversals, which reverse the order of a subset of neighbored genes. In this paper, we study the problem to find the ancestral gene order for three species represented by their gene orders. The rearrangement scenario should use a minimal number of reversals and no other rearrangement operations. This problem is called the Median problem and is known to be NP--complete. In this paper, we describe a heuristic algorithm for finding solutions to the Median problem that searches for rearrangement scenarios with the additional property that gene groups should not be destroyed by reversal operations. The concept of conserved intervals for signed permutations is used to describe such gene groups. We show experimentally, for different types of test problems, that the proposed algorithm produces very good results compared to other algorithms for the Median problem. We also integrate our reversal selection procedure into the well-known MGR and GRAPPA algorithms and show that they achieve a significant speedup while obtaining solutions of the same quality as the original algorithms on the test problems.
Frontal and Temporo-Parietal Lobe Contributions to Theory of Mind: Neuropsychological Evidence from a False-Belief Task with Reduced Language and Executive Demands
Authors: Ian A. Apperly, Dana Samson, Claudia Chiavarino, Glyn W. Humphreys
Venue: Journal of Cognitive Neuroscience (2004)

A model of the functional and anatomical basis of belief reasoning is essential for understanding the relationship between belief reasoning and other cognitive processes in both normal development and pathology. Studies of brain-damaged patients can give valuable insights into the nature of belief processing but pose unique methodological problems. The current study addresses these problems by using a nonlinguistic belief-reasoning task with substantially reduced executive demands. A case series of 12 brain-damaged patients is presented. The belief-reasoning errors of four patients with damage to the prefrontal cortex appeared to arise from these patients' executive function problems. The belief-reasoning errors of three patients with damage to the temporo-parietal junction could not easily be accounted for in this way, raising the possibility that this brain region has a necessary role in representing beliefs, rather than handling the executive demands of belief-reasoning tasks. We discuss the importance of gaining empirical evidence about the scope of ''theory of mind'' impairments, and the important role for neuropsychological studies in this project.
IT Value Management: Creating a Balanced Program
Authors: Michael McShea
Venue: IT Professional (2006)

An ITVM methodology that addresses only individual project decisions will inevitably fall short. To take an IT program to the next level, it must be managed as a multidimensional portfolio of projects.
Probabilistic, Multi-staged Interpretation of Spoken Utterances
Authors: Ingrid Zukerman, Michael Niemann, Sarah George
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)

We describe Scusi?, a multi-stage, spoken language interpretation mechanism designed to be part of a robotmounted dialogue system. Scusi?'s interpretation process maps spoken utterances to conceptual graphs, and the nodes in these graphs to concepts in the world. Maximum posterior probability is used to rank the (partial) interpretations produced at each stage of this process. We show how the features of our interpretation process yield desirable behaviours that support robust and flexible system performance.
Unpacking the mediation of invented representations
Authors: Joshua A. Danish, Noel Enyedy
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

In this paper we compare two contexts where students were inventing representations; a 2nd and 3rd grade classroom creating a shared representation, and a kindergarten and 1st grade classroom creating unique representations. Contexts for developing shared representations are those in which a class attempts to jointly construct one representational form to solve a given problem. In contrast, contexts for inventing unique representations emphasize individual representational choices with no explicit attempt to create a shared representational form. Drawing on and comparing data from two recent studies we use the Negotiated Representational Mediators (NeRM) framework to analyze young children's activities oriented towards the production, evaluation, and modification of representational forms. Both cultural contexts lead to a convergence toward normative representations as well as continuing to diverge in the form of individual acts of creativity and agency. We argue that despite these similar trends, the different contexts support unique aspects of representational practice.
Nonlinear positional formulation for space truss analysis
Authors: M. Greco, F. A. R. Gesualdo, W. S. Venturini, H. B. Coda
Venue: Finite Elements in Analysis and Design (2006)

This paper presents a new geometric nonlinear formulation for static problems involving space trusses. Based on the finite element method (FEM), the proposed formulation uses nodal positions rather than nodal displacements to describe the problem. The strain is determined directly from the proposed position concept, using a Cartesian coordinate system fixed in space. Bilinear constitutive hardening relations are considered here to model the elastoplastic effects, but any other constitutive model can be used. The proposed formulation is simple and yields good results, as shown in the example section. Four examples are presented here to validate the formulation.
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition
Authors: Frank DiMaio, Jude Shavlik
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with a pairwise potential function. An efficient inference algorithm -- based on belief propagation (BP) -- finds the optimal layout of parts, given some input image. We introduce AggBP, a message aggregation scheme for BP, in which groups of messages are approximated as a single message. For objects consisting of N parts, we reduce CPU time and memory requirements from O( N^2 ) to O(N). We apply AggBP on synthetic data as well as a real-world task identifying protein fragments in three-dimensional images. These experiments show that our improvements result in minimal loss in accuracy in significantly less time.
A stochastic model for planning swine facilities
Authors: Lluís M. Plà-Aragonés
Venue: Proceedings of the 37th conference on Winter simulation (2005)

A simulation model and its application for planning swine facilities are presented. Swine production is becoming more and more specialized, hence the sizing of a farm producing piglets is the main strategic decision concerning farmers who invest in sow production, since a farm comprises a big range of facilities with many possible sizes. The classical approach is deterministic, including sometimes some security margins without considering variations in future sow performance or in the management policy. The stochastic model presented here has revealed practical differences with respect to deterministic approaches. As result, simulation is useful to determine accurately the capacity, improve farm design, prevent practical problems and fit housing cost. Furthermore, the implementation in Extend allows potential users to perform efficiently different kinds of analyses.
Dynamic Scene Reconstruction for Efficient Remote Surveillance
Authors: Alessandro Calbi, Carlo S. Regazzoni, Lucio Marcenaro
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

In this paper a system is presented able to reproduce the actions of multiple moving objects into a 3D model. A multi-camera surveillance system is used for automatically detect, track and classify the objects. Data fusion from multiple sensors allows to get a more precise estimation of the position of detected moving objects and to solve occlusions problem. These data are then used to automatically place and animate objects avatars in a 3D virtual model of the scene, thus allowing a human operator to remotely visualize the dynamic 3D reconstruction by selecting a arbitrary point of view.
Set Size Effects in the Macaque Striate Cortex
Authors: Rogier Landman, Henk Spekreijse, Victor A. F. Lamme
Venue: Journal of Cognitive Neuroscience (2003)

Attentive processing is often described as a competition for resources among stimuli by mutual suppression. This is supported by findings that activity in extrastriate cortex is suppressed when several stimuli are presented simultaneously, compared to a single stimulus. In this study, we randomly varied the number of simultaneously presented figures (set size) in an attention-demanding change detection task, while we recorded multiunit activity in striate cortex (V1) in monkeys. After figure&ndash;background segregation, activity was suppressed as set size increased. This effect was stronger and started earlier among cells stimulated by the background than those stimulated by the figures themselves. As a consequence, contextual modulation, a correlate of figure&ndash;background segregation, increased with set size, approximately 100 msec after its initial generation. The results indicate that suppression of responses under increasing attentional demands differentially affects figure and background responses in area V1.