ppxscal/embedding_network huggingface dataset:
CENSREC-3: Data Collection for In-Car Speech Recognition and Its Common Evaluation Framework
Authors: Masakiyo Fujimoto, Satoshi Nakamura, Toshiki Endo, Kazuya Takeda, Chiyomi Miyajima, Shingo Kuroiwa, Takeshi Yamada, Norihide Kitaoka, Kazumasa Yamamoto, Mitsunori Mizumachi, Takanobu Nishiura, Akira Sasou
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

This paper introduces a common database, an evaluation framework, and its baseline recognition results for in-car speech recognition, CENSREC-3, as an outcome of IPSJ-SIG SLP Noisy Speech Recognition Evaluation Working Group. CENSREC-3 which is a sequel of AURORA-2J is designed as the evaluation framework of isolated word recognition in real driving car environments. Speech data was collected using 2 microphones, a close-talking microphone and a hands-free microphone, under carefully controlled 16 different driving conditions, i.e., combinations of 3 car speeds and 5 car conditions. CENSREC-3 provides 6 evaluation environments which are designed using speech data collected in these car conditions.
Numerical simulation of dyebath and the influence of dispersion factor on dye transport
Authors: Renzo Shamey, Xiaoming Zhao, Roger H. Wardman
Venue: Proceedings of the 37th conference on Winter simulation (2005)

In order to model the mass transfer in a fluid, a "dispersion" model is frequently used. When the flow behavior does not drastically deviate from plug flow, the model performs well. The dispersive flow properties of liquids within fibrous textile assemblies however, have not been fully explored. In the mass transfer model, the dispersive flow is assumed to reduce the concentration gradient of dye liquor flowing through the package. This paper illustrates the influence of dispersion term on dye transport based on numerical simulation of dyebath. The transfer of dye through the package is described by a set of time-dependent partial differential equations, which govern convection, dispersion, and adsorption of dyes in the dyebath and across the yarn package. The simulation results prove, theoretically, that the inclusion of the dispersion term in the dyeing model improves the results of the dyeing process in terms of dye uptake and levelness.
Dissociable Processes for Learning the Surface Structure and Abstract Structure of Sensorimotor Sequences
Authors: Peter F. Dominey, Taïssia Lelekov, Jocelyne Ventre-dominey, Marc Jeannerod
Venue: Journal of Cognitive Neuroscience (1998)

A sensorimotor sequence may contain information structure at several different levels. In this study,we investigated the hypothesis that two dissociable processes are required for the learning of surface structure and abstract structure, respectively, of sensorimotor sequences. Surface structure is the simple serial order of the sequence elements, whereas abstract structure is defined by relationships between repeating sequence elements. Thus, sequences ABCBAC and DEFEDF have different surface structures but share a common abstract structure, 123213, and are therefore isomorphic. Our simulations of sequence learning performance in serial reaction time (SRT) tasks demonstrated that (1) an existing model of the primate fronto-striatal system is capable of learning surface structure but fails to learn abstract structure, which requires an additional capability, (2) surface and abstract structure can be learned independently by these independent processes, and (3) only abstract structure transfers to isomorphic sequences. We tested these predictions in human subjects. For a sequence with predictable surface and abstract structure, subjects in either explicit or implicit conditions learn the surface structure, but only explicit subjects learn and transfer the abstract structure. For sequences with only abstract structure, learning and transfer of this structure occurs only in the explicit group. These results are parallel to those from the simulations and support our dissociable process hypothesis. Based on the synthesis of the current simulation and empirical results with our previous neuropsychological findings, we propose a neurophysiological basis for these dissociable processes: Surface structure can be learned by processes that operate under implicit conditions and rely on the fronto-striatal system, whereas learning abstract structure requires a more explicit activation of dissociable processes that rely on a distributed network that includes the left anterior cortex.
LearningWeights for Linear Combination of Forecasting Methods
Authors: Ricardo B. C. Prudencio, Teresa B. Ludermir
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

The linear combination of forecasts is a procedure that has improved the forecasting accuracy for different time series. We present here the use of machine learning techniques to define numerical weights for the linear combination of forecasts. In this approach, a machine learning technique uses features of the series at hand to define the adequate weights for a pre-defined number of forecasting methods. In order to evaluate this solution, we implemented a prototype that uses a MLP network to combine two widespread methods. The performed experiments revealed significantly accurate forecasts.
Mathematics Computing Environment on the Web
Authors: Li Liu, Yi Yang, Lian Li
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

With the rapid evolution of web technology and Internet, the mathematical web has emerged as a new research trend, which changes the traditional manner of mathematical scientific researching, mathematical production sharing, mathematical knowledge engineering and mathematical education. In addition, the acquisition of mathematical knowledge and the integration of diversiform of mathematical software are also taken into considers on the web environment. In this paper, we will present a web-based, user adaptive learning and grid computing environment that employs content encoded in a semantic representation of mathematical knowledge and integrates mathematics software as services. We have brought forward a concept which makes the mathematical computing environment working more efficiently. This mathematics computing environment mainly offers a powerful and convenient mathematics computing environment for end users and service providers. From the view of computing, this environment is a web-based service-oriented environment, built on three-layered resource model. From the view of end users, the formal representation allows semantics-based retrieval of distributed mathematical facts, giving mathematicians a tool and an easy-to-learn mathematical language to access and query the present mathematical knowledge and services. On the other hand, we use grid toolkits, which have the capabilities to aggregate and coordinate the computational power of geographically distributed, heterogeneous and dynamic resources efficiently, to organize and manage the mathematical resources.
MultiSOM: A Multiview Neural Model for Accurately Analyzing and Mining Complex Data
Authors: Jean-Charles Lamirel, Shadi Al Shehabi
Venue: Proceedings of the Fourth International Conference on Coordinated & Multiple Views in Exploratory Visualization (2006)

In the procedure of information analysis, like in the domain of patent analysis, the complexity of the studied topics and the accuracy of the question to be answered may often lead the analyst to partition his reasoning into viewpoints. Most of the classical information analysis tools can only manage an analysis of the studied domain in a global way. The information analysis tool is considered in this paper is the MultiSOM tool, whose core model represents a significant extension of the classical Kohonen SOM neural model. The MultiSOM neural-based tool introduces the concepts of viewpoints and dynamics into the information analysis with its multi-maps displays and its inter-map communication process. The dynamic information exchange between maps can be exploited by an analyst in order to perform cooperative deduction between several different analyzes that have been performed on the same data. This paper demonstrates the efficiency of a viewpoint-oriented analysis as compared to a global analysis in the domain of patents. Both objective and subjective quality criteria are taken into account for quality evaluation.
A corpus-based approach to help-desk response generation
Authors: Ingrid Zukerman, Yuval Marom
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 are developing a corpus-based approach for the prediction of help-desk responses from features in customers' emails, where responses are represented at two levels of granularity: document and sentence. We present an automatic evaluation of the responses generated by our system, as well as a manual one involving human judges. The automatic evaluation involves textual comparisons between generated responses and responses composed by the help-desk operators. The results show that both levels of granularity produce good responses, addressing inquiries of different kinds. The human-based evaluation measures response informativeness, and confirms our conclusion that both levels of granularity produce useful responses.
Systematic topology analysis and generation using degree correlations
Authors: Priya Mahadevan, Dmitri Krioukov, Kevin Fall, Amin Vahdat
Venue: ACM SIGCOMM Computer Communication Review (2006)

Researchers have proposed a variety of metrics to measure important graph properties, for instance, in social, biological, and computer networks. Values for a particular graph metric may capture a graph's resilience to failure or its routing efficiency. Knowledge of appropriate metric values may influence the engineering of future topologies, repair strategies in the face of failure, and understanding of fundamental properties of existing networks. Unfortunately, there are typically no algorithms to generate graphs matching one or more proposed metrics and there is little understanding of the relationships among individual metrics or their applicability to different settings. We present a new, systematic approach for analyzing network topologies. We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. Increasing values of d capture progressively more properties of G at the cost of more complex representation of the probability distribution. Using this series, we can quantitatively measure the distance between two graphs and construct random graphs that accurately reproduce virtually all metrics proposed in the literature. The nature of the dK-series implies that it will also capture any future metrics that may be proposed. Using our approach, we construct graphs for d=0, 1, 2, 3 and demonstrate that these graphs reproduce, with increasing accuracy, important properties of measured and modeled Internet topologies. We find that the d=2 case is sufficient for most practical purposes, while d=3 essentially reconstructs the Internet AS-and router-level topologies exactly. We hope that a systematic method to analyze and synthesize topologies offers a significant improvement to the set of tools available to network topology and protocol researchers.
1-V bulk-driven CMOS analog programmable winner-takes-all circuit
Authors: Yu-Cherng Hung, Bin-Da Liu, Chung-Yang Tsai
Venue: Analog Integrated Circuits and Signal Processing (2006)

In this paper, a 1-V bulk-driven analog winner-takes-all circuit with programmable k-winners capability is proposed. By presetting a set of binary bits, the desired k-winners-take-all or k-losers-take-all function is programmable. The proposed upward-and-downward searching greatly improves the response time. The chip has been fabricated with a 0.25-¿m CMOS technology. Simulated results show that the response time of the winner-takes-all circuit is 50 ¿s under 5-mV identified resolution. The input range is approximately to be rail-to-rail.
Building Simple, Easy-to-Use Grids with Styx Grid Services and SSH
Authors: J. D. Blower, K. Haines
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Grid systems have a reputation for being difficult to build and use. We describe how the ease of use of the Styx Grid Services (SGS) software can be combined with the security and trusted nature of the Secure Shell (SSH) to build simple Grid systems that are secure, robust and easy to use and administer. We present a case study of how this method is applied to a science project (GCEP), allowing the scientists to share resources securely and in a manner that does not place unnecessary load on system administrators. Applications on the Grid can be run exactly as if they were local programs from the point of view of the scientists. The resources in the GCEP Grid are diverse, including dedicated clusters, Condor pools and data archives but the system we present here provides a uniform interface to all these resources. The same methods can be used to access Globus resources via Condor-G or GSISSH if required.
Some New Efficient Second-Order Spectral-Null Codes with Small Lookup Tables
Authors: Ching-Nung Yang, Dong-Jing Lee
Venue: IEEE Transactions on Computers (2006)

Tallini and Bose introduced a recursive method to construct second-order spectral-null codes which result in short (information length 16) base optimal second-order spectral-null codes that can be easily implemented either with table lookup or enumerative coding. In this brief contribution, the extended base suboptimal second-order spectral-null codes (17 information length 32) obtained from two short base codes by lookup table are used to reduce the overall code length.
Symbolic interval time series forecasting using a hybrid model
Authors: Andre Luiz S. Maia, Francisco de A. T. de Carvalho, Teresa B. Ludermir
Venue: Proceedings of the Ninth Brazilian Symposium on Neural Networks (2006)

This paper presents two approaches to symbolic interval time series forecasting. The first approach is based on the autoregressive moving average (ARMA) model and the second is based on a hybrid methodology that combines both ARMA and artificial neural network (ANN) models. In the proposed approaches, two models are respectively fitted to the mid-point and range of the interval values assumed by the symbolic interval time series in the learning set. The forecast of the lower and upper bounds of the interval value of the time series is accomplished through the combination of forecasts from the mid-point and range of the interval values. The evaluation of the proposed models is based on the estimation of the average behaviour of the mean absolute error and mean square error in the framework of a Monte Carlo experiment.
On the parallelization of irregular and dynamic programs
Authors: Oscar Plata, Rafael Asenjo, Eladio Gutiérrez, Francisco Corbera, Angeles Navarro, Emilio L. Zapata
Venue: Parallel Computing (2005)

Current compilers show ineffective when optimizing complex applications, both analyzing dependences and exploiting data locality and extracting parallelism. Complex applications may be characterized as irregular and dynamic. Irregular applications arrange data as multi-dimensional arrays and memory is referenced through array indirections. Dynamic applications organize data as pointer-based structures (lists, trees,...) and memory is referenced through pointers. In this paper we discuss a methodology we designed to develop efficient parallelization techniques for irregular and dynamic applications, that proceeds in three stages: recognizing the complex program structure, data analysis and program parallelization based on code/data transformations. Two case examples are analyzed in detail in the context of this methodology: irregular reductions and shape analysis for dynamic data structures.
People Tracking Using a Time-of-Flight Depth Sensor
Authors: Alessandro Bevilacqua, Luigi Di Stefano, Pietro Azzari
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Visually track several moving persons engaged in close interactions is known to be a very hard problem, though 3-D approaches based on stereo vision and plan-view maps offer much promise for dealing effectively with major issues such as occlusions and quick changes in body pose and appearance. However, in case of untextured scenes due to homogeneous objects or poor illumination, stereo-based tracking systems rapidly drop their performance. In this work, we present a real time people tracking system able to work even under severe low-lighting conditions. The system relies on a novel active sensor that provides brightness and depth images based on a Time of Flight (TOF) technology. The tracking algorithm is simple yet efficient, being based on geometrical constraints and invariants. Experiments accomplished under changing lighting conditions and involving multiple people closely interacting with each other have proved the reliability of the system.
Advanced Meta-PSO
Authors: Christian Veenhuis
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

One issue in applying PSO is to find a good working set of parameters. The standard settings are often work sufficiently but don't exhaust the possibilities of PSO. This paper proposes an extended Meta-PSO approach to optimize the PSO parameters as well as the neighborhood topology for a given problem by PSO itself. It is applied to four typical benchmark functions known from literature. The good results indicate that PSO is capable of optimizing itself.
Grid-Based System for Product Design Optimization
Authors: Tomasz Haupt, Anupama Voruganti, Anand Kalyanasundaram, Igor Zhuk
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This paper describes the progress of developing a Grid-based system for product design optimizations to increase the engineer's productivity by saving him tedious, manual, and error-prone work of organizing, maintaining, submitting and monitoring computational workflows comprising hundreds of jobs in a heterogeneous distributed environment. The approach is that once the optimization process is interactively defined through a GUI, the process runs asynchronously, automatically, and autonomously. This goal is being achieved through horizontal integration by employing a Service Oriented Architecture. The developed cyberinfrastructure comprises a collection of Grid services that automates creation, submission and monitoring of jobs. In addition, support is provided for accessing information needed to identify the reasons of failures, should any occur, The front end of the system augments a commercial, state-of-the-art user graphical interface (Abacus CAE) for defining a finite element analysis problem with custom GUI components for specifying the optimization problem and providing access to remote resources. The access to remote resources is achieved by embedding clients of Grid services in the Abacus CAE.
Some practical considerations of ethical issues in VR research
Authors: Katharina-Maria Behr, Andreas Nosper, Christoph Klimmt, Tilo Hartmann
Venue: Presence: Teleoperators and Virtual Environments (2005)

As scientific laboratories are an important domain of application of VR technology, ethical issues of VR have to be discussed with respect to research and the treatment of research subjects. Exposing participants to VR systems may raise ethical problems due to motion sickness, information overload, intensification of experience, and difficulties with reentry into the real world. The ethical guidelines which are typically applied to psychological research do not cover all of these problems in detail and have to be reconsidered, since they have not been developed with regard to the use of VR systems. Therefore, practical strategies to cope with the addressed ethical problems in VR research are recommended.
Comparing Educational Modeling Languages on a Case Study
Authors: Laurence Vignollet, Jean-Pierre David, Christine Ferraris, Christian Martel, Anne Lejeune
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

In the field of learning design, IMS has standardized EML, the Educational Modeling Language proposed by OUNL. However, it remains to be seen whether it will be widely adopted. Moreover, evolutions of IMS-LD and competing models are proposed by several teams. The objective of this workshop is to confront the approaches (models, tools, methodologies) through modeling and implementation experiences of collaborative learning activities. To facilitate the comparison, a case study is proposed. The outcomes of this workshop will be discussed during the panel "Learning Design of Collaborative Learning Activities: languages, models and tools".
A reconstruction-based algorithm for classification rules hiding
Authors: Juggapong Natwichai, Xue Li, Maria E. Orlowska
Venue: Proceedings of the 17th Australasian Database Conference - Volume 49 (2006)

Data sharing between two organizations is common in many application areas e.g. business planing or marketing. Useful global patterns can be discovered from the integrated dataset. However, some sensitive patterns that should have been kept private could also be discovered. In general, disclosure of sensitive patterns could decrease the competitive ability of the data owner. Therefore, sensitive patterns should be hidden before data sharing starts. To address this problem, released datasets must be modified unavoidably. However, if the overall characteristics of the dataset can be maintained, the dataset is still usable perfectly. Therefore, not only the privacy should be concerned, but also the usability. In this paper, we propose a new algorithm to preserve the privacy of the classification rules by using reconstruction technique for categorical datasets. Firstly, all discovered classification rules in the released dataset are presented to the data owner to identify sensitive rules that should be hidden. Subsequently, remained non-sensitive rules along with extracted characteristics information of the dataset are used to build a decision tree. Finally, the new dataset which contains only non-sensitive classification rules is reconstructed from the tree. From empirical studies, our algorithm can preserve the privacy effectively. Additionally, the usability of the datasets can also be preserved.