ppxscal/embedding_network huggingface dataset:
Speaker adaptation based on combination of MAP estimation and weighted neighbor regression
Authors: Lei He
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

This paper describes a novel speaker adaptation method that combines the maximum a posteriori (MAP) estimation and the weighted neighbor regression (WNR). The primary disadvantage of MAP adaptation is that only the parameters of those models with adaptation data are updated, thus great deals of adaptation data are required. In this paper, a technique called WNR is presented, in which the information of model neighbors is used to overcome that problem. The parameter relationships between the speaker independent models and the speaker adaptation models are trained by applying the distance weighted regressions to a set of neighbor model parameters with and without MAP adaptation. It gives nearly 15 percent error rate reduction with 10 adaptation utterances and more than 51 percent with 250 utterances in Chinese syllable recognition. In addition, the vector field smoothing (VFS) can be proved to be a degenerate case of WNR.
Microhash: an efficient index structure for fash-based sensor devices
Authors: Demetrios Zeinalipour-Yazti, Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
Venue: Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4 (2005)

In this paper we propose the MicroHash index, which is an efficient external memory structure for Wireless Sensor Devices (WSDs). The most prevalent storage medium for WSDs is flash memory. Our index structure exploits the asymmetric read/write and wear characteristics of flash memory in order to offer high performance indexing and searching capabilities in the presence of a low energy budget which is typical for the devices under discussion. A key idea behind MicroHash is to eliminate expensive random access deletions. We have implemented MicroHash in nesC, the programming language of the TinyOS [7] operating system. Our trace-driven experimentation with several real datasets reveals that our index structure offers excellent search performance at a small cost of constructing and maintaining the index.
Parallel protein secondary structure prediction schemes using Pthread and OpenMP over hyper-threading technology
Authors: Wei Zhong, Gulsah Altun, Xinmin Tian, Robert Harrison, Phang C. Tai, Yi Pan
Venue: The Journal of Supercomputing (2007)

Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, tertiary classifiers for the protein secondary structure prediction are implemented on Denoeux Belief Neural Network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 matrix and PSSM matrix are experimented separately as the encoding schemes for DBNN. Hydrophobicity matrix, BLOSUM62 matrix and PSSM matrix are applied to DBNN architecture for the first time. The experimental results contribute to the design of new encoding schemes. Our accuracy of the tertiary classifier with PSSM encoding scheme reaches 72.01%, which is almost 10% better than the previous results obtained in 2003. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the Hyper-Threading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that Hyper-Threading technology for Intel architecture is efficient for parallel biological algorithms.
An automated data collection exercise: capacitance position sensor
Authors: J. Joseph
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

This exercise represents a semester long project in a course entitled Automated Data Collection. The course was broken into four parts. First, sensor design was discussed in general with a position sensor, implemented as a parallel plate capacitor with movable dielectric, as an example. Second, op amp circuits for signal conditioning were discussed. Third, analog filter design was developed for frequency alteration and anti-aliasing filtration. Fourth, analog-to-digital conversion (ADC) techniques were discussed. This exercise integrated the course content and allowed the students to simulate a position sensor data collection system. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Distributed Mobility Management for Target Tracking in Mobile Sensor Networks
Authors: Yi Zou, Krishnendu Chakrabarty
Venue: IEEE Transactions on Mobile Computing (2007)

Mobility management is a major challenge in mobile ad hoc networks (MANETs) due in part to the dynamically changing network topologies. For mobile sensor networks that are deployed for surveillance applications, it is important to use a mobility management scheme that can empower nodes to make better decisions regarding their positions such that strategic tasks such as target tracking can benefit from node movement. In this paper, we describe a distributed mobility management scheme for mobile sensor networks. The proposed scheme considers node movement decisions as part of a distributed optimization problem which integrates mobility-enhanced improvement in the quality of target tracking data with the associated negative consequences of increased energy consumption due to locomotion, potential loss of network connectivity, and loss of sensing coverage.
Assumed and effective priors in Bayesian MAP estimation
Authors: M. Nikolova
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

Bayesian maximum a posteriori estimation (MAP) is a very popular way to recover unknown signals and images by using jointly observed data and priors formulated as a probability law. In a variational context, a MAP estimate minimizes an objective function where the priors are seen as a regularization or diffusion term. Independently of such interpretations, MAP estimates are implicit functions of the data and of the functions expressing the priors. This point of view enabled the author to exhibit analytical relations between prior functions and the features of the relevant estimates. These results entail important consequences and questions which are the subject of this paper. Namely, they reveal an essential gap between prior models and the way these are effectively involved in a MAP estimate. Hence the question about the rationale of MAP estimation. At the same time, they give precious indications about the hyperparameters and suggest how to construct estimators which indeed respect the priors.
Is the shortcut the quickest way to go?: translating instructions for keyboard navigation and other stories
Authors: Anne Dickinson
Venue: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007)

The author works in Coventry University and has been engaged in tutoring a student with disabilities who had enrolled for a degree in Business and IT at Coventry University. To do this, the author drew upon previous experiences in the Further Education (FE) sector at a College in the Midlands, where she taught Information Technology (IT) to diverse groups of students who had varied abilities. The ages of the FE students ranged from pre-16, visiting the College from a local special school to attend "taster" sessions, to adults, some of whom were seniors, attending a day centre for disabled adults that had a special arrangement for College tutors to give classes. The degree student was a white cane user, read Braille and navigated the computer with screen reader software. During her time at University, she took on an ambassadorial role: she gave guided tours to prospective students around the University campus during open days! From time to time she would recount stories that she described as amusing but which clearly showed ignorance on the part of her tutors. The Degree course in Business and IT had several workshops in Computing including statistics where spreadsheets and specialist software were used. The author was asked to tutor the student for the IT workshops of a year-long module. This included translating the instructional handouts from mouse-based to keyboard-based, being aware of potential problems with specialist software and the quirks of the online learning system (WebCT) [1] and finding ways of working around them all. This "tips and techniques" session gives an account of some of these issues around the student's stories, creating and translating instructions for keyboard use navigating the keyboard using JAWS, and includes proposed solutions.
Higher-order semantic labelling for inductive datatype systems
Authors: Makoto Hamana
Venue: Proceedings of the 9th ACM SIGPLAN international conference on Principles and practice of declarative programming (2007)

We give a novel transformation for proving termination of higher-order rewrite systems in the format of Inductive Data Type Systems (IDTSs) by Blanqui, Jouannaud and Okada. The transformation called higher-order semantic labelling attaches algebraic semantics of the arguments to each function symbol. We systematically define the labelling and show that labelled systems give termination models in the frame-work of Fiore, Plotkin and Turi's binding algebras. As applications, we give simple proofs of termination of the explicit substitution system λ X and currying transformation via higher-order semantic labelling. Moreover, we prove a new result of modularity of termination of IDTSs by introducing the notion of solid IDTSs. We prove that termination is preserved under the disjoint union of an IDTS and a higher-order program scheme.
Evaluating XML retrieval effectiveness at INEX
Authors: Mounia Lalmas, Anastasios Tombros
Venue: ACM SIGIR Forum (2007)

The INitiative for the Evaluation of XML retrieval (INEX) was set up in 2002 to establish an infrastructure and provide means, in the form of large test collections and appropriate scoring methods, for evaluating the effectiveness of content-oriented XML retrieval systems. This report provides an overview of the evaluation methodology developed in INEX from 2002 to 2006.
Filter bank interpolation and reconstruction from generalized and recurrent nonuniform samples
Authors: Y. C. Eldar
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

This paper introduces a filter bank interpretation of various sampling strategies, which leads to efficient interpolation and reconstruction methods. An identity, referred to as the interpolation identity, is used to obtain particularly efficient discrete-time systems for interpolation to uniform Nyquist samples, either for further processing in that form or for conversion to continuous-time. The interpolation identity also leads to a new class of sampling theorems including an extension of Papoulis' (1997) generalized sampling expansion.
An efficient algorithm to extract components of a composite signal
Authors: O. Arikan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

An efficient algorithm is proposed to extract components of a composite signal. The proposed approach has two stages of processing in which the time-frequency supports of the individual signal components are identified and then the individual components are estimated by performing a simple time-frequency domain incision on the identified support of the component. The use of a previously developed time-frequency representation significantly improves the performance of the proposed approach by providing a very accurate description on the auto-Wigner terms of the composite signal. Then, simple fractional Fourier domain incision provides reliable estimates for each of the signal components in O(N log N) complexity for a composite signal of duration N.
Rate-distortion adaptive vector quantization for wavelet image coding
Authors: Qun Gu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

We propose a wavelet image coding scheme using rate-distortion adaptive tree-structured residual vector quantization. Wavelet transform coefficient coding is based on the pyramid hierarchy (zero-tree), but rather than determining the zero-tree relation from the coarsest subband to the finest by hard thresholding, the prediction in our scheme is achieved by rate-distortion optimization with adaptive vector quantization on the wavelet coefficients from the finest subband to the coarsest. The proposed method involves only integer operations and can be implemented with very low computational complexity. The preliminary experiments have shown some encouraging results: a PSNR of 30.93 dB is obtained at 0.174 bpp on the test image LENA (512/spl times/512).
Analyzing Cross-Sector Interdependencies
Authors: James P. Peerenboom, Ronald E. Fisher
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper discusses cross-sector infrastructure interdependencies and key risk considerations, analysis approaches, research and development needs, and the range of interdisciplinary skills required for comprehensive cross-sector analysis. Traditional analysis of interdependencies involves characterization of infrastructure-to-infrastructure linkages to identify the key infrastructure components that, if lost or degraded, could adversely affect the performance of other infrastructures. Such analysis is motivated by the recognition that a series of incidents could interact (cascade) across critical infrastructures to degrade the service upon which all depend. From a risk perspective, cross-sector analysis also must involve identifying and characterizing a wide range of threats (natural and accidental, systems related, and intentional), vulnerabilities (physical and cyber), and consequences of loss (e.g., health and safety, economic, national security, environmental, sociopolitical). Such information provides a foundation for making defensible, cost-effective infrastructure protection and operation decisions to ensure the security and reliability of our interdependent systems.
Prioritizing Warning Categories by Analyzing Software History
Authors: Sunghun Kim, Michael D. Ernst
Venue: Proceedings of the Fourth International Workshop on Mining Software Repositories (2007)

Automatic bug finding tools tend to have high false positive rates: most warnings do not indicate real bugs. Usually bug finding tools prioritize each warning category. For example, the priority of "overflow" is 1 and the priority of "jumbled incremental" is 3, but the tools' prioritization is not very effective. In this paper, we prioritize warning categories by analyzing the software change history. The underlying intuition is that if warnings from a category are resolved quickly by developers, the warnings in the category are important. Experiments with three bug finding tools (FindBugs, JLint, and PMD) and two open source projects (Columba and jEdit) indicate that different warning categories have very different lifetimes. Based on that observation, we propose a preliminary algorithm for warning category prioritizing.
State capture and resource control for java: the design and implementation of the aroma virtual machine
Authors: Niranjan Suri, Jeffrey M. Bradshaw, Maggie R. Breedy, Paul T. Groth, Gregory A. Hill, Raul Saavedra
Venue: Proceedings of the 2001 Symposium on JavaTM Virtual Machine Research and Technology Symposium - Volume 1 (2001)

Although Java is currently riding a rising wave of popularity, current versions fail to address many of the unique challenges posed by the new generation of distributed applications. In particular the advent of peer-to-peer computing models and the proliferation of software agents motivates various requirements that go beyond the capabilities of current Java Virtual Machines: • Full state capture. To support checkpointing and load balancing, the Virtual Machine (VM) must be able to capture its complete state including all threads, objects, and classes in the heap. To support requirements for strong "anytime" mobility and forced migration (such as when a host is about to go offline), the VM must be able to support asynchronous requests to capture execution state for a thread or thread group. • Dynamic access and resource control. The security model in Java 2 [4] provides a fairly comprehensive model for access control but does not allow for dynamic permission revocation. Once permission is granted to a process, that permission is in effect for the lifetime of that process. Furthermore, there is no way of specifying the amount of a resource that is granted, assuring a specific quality of service for each process. For example, one would like to be able to limit the quantity of hard disk, network, or CPU usage that is available to a given process or to determine the rate at which the resource may be used. Denial-of-service conditions on a host or network resulting from code that is poorly programmed, malicious, or has been tampered with are impossible to detect and interrupt without dynamic monitoring and control mechanisms for individual processes. • Resource accounting. Tracking of resource use, based on resource control mechanisms, enables accounting and billing mechanisms that hosts can use to calculate charges for resident programs. The same mechanisms can be used to detect patterns of resource abuse.
Efficient Affine-Invariant Similarity Retrieval
Authors: Sofie Haesevoets, Bart Kuijpers, Peter Revesz
Venue: Proceedings of the Geometric Modelling and Imaging (2007)

We describe novel image similarity measures that are affine-invariant. Based on these new similarity measures, we further describe efficient affine-invariant image indexing algorithms. We present also our experiments on a preliminary data set with 400 images.
Blind MIMO channel estimation method tolerating order overestimation
Authors: Yonghong Zeng
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 01 (2002)

A new second-order statistics (SOS) based blind algorithm for MIMO channel identification is proposed. It can give estimations of all channel impulse responses subject to a scalar matrix ambiguity which is intrinsic to all SOS based blind methods. As a generalization of the blind identification algorithm for SIMO system, this method is truly robust to channel order overestimation, i.e., it can accurately estimate the channels when only upper bounds for all MIMO channel orders are known.
The Role of Domain Ontology in Text Mining Applications: The ADDMiner Project
Authors: Ana Cristina B. Garcia, Inhauma Neves Ferraz, Fernando Pinto
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

Extracting insights from large text collections is an aspiration of any organization aiming to take advantage of their experience generally documented in textual documents. Textual documents, either digital or not, have been the most common form to register any organization transaction. Free text style is a very easy way to input data since it does not require users any special training. On the other hand, the text material easily collected becomes the major challenge for building automatic deciphering tools. In this paper we present ADDMiner, a text-mining model for extracting causality relationships from a large text collection of accident reports. Our model is based on using domain ontology as well as a corpus-based computational linguistics to guide the mining process. Examples from offshore oil platform accident reports illustrate the potential benefits of our approach.
Physical parameters reconstruction of a fixed-fixed mass-spring system from its characteristic data
Authors: Xiantong Huang, Xiyan Hu, Lei Zhang
Venue: Journal of Computational and Applied Mathematics (2007)

In this paper, an inverse problem of constructing a linear n degree of freedom mass-spring system from part of its physical parameters and part of modality of its maximal or minimal natural frequencies is considered. The solvability and the expression of the solution is derived. The numerical algorithms and some numerical examples are given.
DSP-based solution for ambient noise reduction in mobile phones
Authors: J. Chaoui
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

Using a mobile handset in noisy environments makes the far-end speech difficult to be perceived from the near-end user perspective. As he is surrounded by a loud background noise, the handset user needs to concentrate hard to understand the far-end speaker conversation. Ambient noise reduction algorithms provide an efficient solution to build a silent zone between the handset loudspeaker and the user ear, thus improving the speech understanding for the near-end speaker. This paper presents a description of an innovative ambient noise reduction system developed on a TI TMS320C54x DSP. This combines both theoretical and experimental considerations, raising potential issues that may be encountered when implementing these applications on a real system. It is shown that the advanced architecture of the TI TMS320C54x DSP makes the ambient noise reduction application possible in the same CPU performing time wireless digital cellular baseband processing.
Boolean Functions as Models for Quantified Boolean Formulas
Authors: Hans Kleine Büning, K. Subramani, Xishun Zhao
Venue: Journal of Automated Reasoning (2007)

In this paper, we introduce the notion of models for quantified Boolean formulas. For various classes of quantified Boolean formulas and various classes of Boolean functions, we investigate the problem of determining whether a model exists. Furthermore, we show for these classes the complexity of the model checking problem, which is to check whether a given set of Boolean functions is a model for a formula. For classes of Boolean functions, we establish some characterizations in terms of classes of quantified Boolean formulas that have such a model.
Signal processing for state estimation during sensor failure using mixed signal separation technique
Authors: S. Ravi, T. Jayasingh
Venue: Proceedings of the The 8th International Conference on Communication Systems - Volume 02 (2002)

One of the main source of concern in signal processing involves separation of unknown source signals from their linear mixtures when the transmission channel characteristics are unknown. In most cases this reduces to estimating the useful signal from a set of observable signals with noise. This paper discusses the structures that are used in separating instantaneously mixed signal sources. It is assumed that the only information available a priori is the set of observable signals. The separation of signals is done using independent component analysis. The proposed method is used in sensor signal processing for estimating the variations of a signal during faulty sensor situation.