ppxscal/embedding_network huggingface dataset:
A modified generalised Lloyd algorithm for VQ codebook design
Authors: Chen Chang-Qian, Koh Soo-Ngee, P. Sivaprakasapillai
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

The Linde-Buzo-Gray (LBG) algorithm, which consists of the splitting initialisation method and GLA, plays a basic and important role in codebook generation of VQ. Obviously, there are two approaches along which research efforts may be directed: (i) to improve GLA, and (ii) to improve the initialization procedure. In this paper, a selective GLA driven by a new specified organisation mechanism is proposed as an alternative to GLA. With the initial codebook obtained from a K-d tree based on the greatest co-ordinate variance, the selective GLA generates a better codebook than GLA and the splitting-initialized LBG algorithm. However, the improvement in performance is accompanied by a raise in the computational complexity involved in the design process. A novel version of partial GLA, whose framework is similar to that of the selective GLA, is also described in this paper. It is found to outperform GLA at the expense of an increased amount of computation.
Investing in Networkability to Improve Supply Chain Peformance
Authors: Wim Huisman, Martin Smits
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The main aim of this paper is to analyse and explicate the linkages between IT investments, networkability of an organization, the organizational performance, and the inter-organizational (supply chain) performance. A research model was developed linking IT-investments to networkability to information sharing and organizational dependency, and ultimately to organizational and networked performance. The model was applied in a B2B network of Aces Direct (an SME retailer) and Tech Data. Case analysis supports earlier findings that increased information sharing correlates with improved performance We found that SME investments in networkability can lead to higher business performance, but that SME success seems to depend on the type of IT investments.. Relation specific (1:1) investments seem to strengthen dependency while non-specific IT investments in the network business buses (1: n) seem to decrease dependency, increase the information sharing, and increase network performance.
iPod Forensics: Forensically Sound Examination of an Apple iPod
Authors: Jill Slay, Andrew Przibilla
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper reports on the development of a method for extracting and verifying an image of the hard drive of an iPod in a forensically sound manner via a USB2 connection, so as to create a standard operating procedure for Australian Law Enforcement. It also establishes an understanding of the nature of proprietary data stored on the iPod and indicates how this can be used as a guide within a forensic investigation. It also develops a sound understanding of the nature of any metadata stored on the iPod and reports on how the information gained, and the standard operating procedures developed from this research, may be applied to gain a better understanding of imaging issues in other portable electronic devices, such as music players and memory based devices, and how similar standard operating procedures may be constructed for the analysis of these devices.
Conceptual Graphs Based Information Retrieval in HealthAgents
Authors: Madalina Croitoru, Bo Hu, Srinandan Dasmahapatra, Paul Lewis, David Dupplaw, Alex Gibb, Margarida Julia-Sape, Javier Vicente, Carlos Saez, Juan Miguel Garcia-Gomez, Roman Roset, Francesc Estanyol, Xavier Rafael, Mariola Mier
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

This paper focuses on the problem of representing, in a meaningful way, the knowledge involved in the HealthAgents project. Our work is motivated by the complexity of representing Electronic Health- care Records in a consistent manner. We present HADOM (HealthAgents Domain Ontology) which conceptualises the required HealthAgents information and propose describing the sources knowledge by the means of Conceptual Graphs (CGs). This allows to build upon the existing ontology permit- ting for modularity and °exibility. The novelty of our approach lies in the ease with which CGs can be placed above other formalisms and their potential for optimised querying and retrieval.
Kinodynamic skinning using volume-preserving deformations
Authors: Alexis Angelidis, Karan Singh
Venue: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation (2007)

We present a new approach to character skinning where divergence-free vector fields induced by skeletal motion, describe the velocity of skin deformation. The joint transformations for a pose relative to a rest pose create a bend deformation field, resulting in pose-dependent or kinematic skin deformations, varying smoothly across joints. The bend deformation parameters are interactively controlled to capture the varying deformability of bone and other anatomic tissue within an overall fold-over free and volume-preserving skin deformation. Subsequently, we represent the dynamics of skeletal motion, tissue elasticity, muscular tension and the environment as forces that are mapped to vortices at tissue interfaces. A simplified Biot-Savart law in the context of elastic deformation recovers a divergence-free velocity field from the vorticity. Finally, we apply a new stable technique to efficiently integrate points along their deformation trajectories. Adding these dynamic forces over a window of time prior to a given pose provides a continuum of user controllable kinodynamic skinning. A comprehensive implementation using a typical animator workflow in Maya shows our approach to be effective for complex character skinning.
Privacy-preserving collaborative data mining
Authors: Zhijun Justin Zhan
Venue:  (2006)

Data mining is a process to extract useful knowledge from large amounts of data. To conduct data mining, we often need to collect data. However, sometimes the data are distributed among various parties. Privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. How multiple parties collaboratively conduct data mining without breaching data privacy presents a grand challenge. Theoretical results from the area of secure multi-party computation show that one may provide secure protocols for any multi-party computation with honest majority. However, the general methods are far from efficient and practical for computing complex functions on inputs consisting of large sets of data. Therefore, to efficiently tackle the problem that is formulated as Privacy-Preserving Collaborative Data Mining, we need to develop privacy-preserving solutions with adequate efficiency. The goal of this dissertation is to provide efficient solutions to the problem of knowledge extraction among multiple parties involved in a data mining task, without disclosing the data between the parties. The distributed data models considered are the vertical collaboration where diverse features of the same set of data are collected by different parties, and the horizontal collaboration where diverse sets of data, all sharing the same features, are gathered by different parties. We develop privacy-preserving protocols for multiple parties to conduct the desired computations. Specifically, we provide solutions for some common data mining algorithms including privacy-preserving association rule mining, privacy-preserving sequential pattern mining, privacy-preserving naive Bayesian classification, privacy-preserving decision tree classification, privacy-preserving k-nearest neighbor classification, privacy-preserving support vector machine classification, and privacy-preserving k-medoids clustering. Our goal is to provide efficient solutions to obtain accurate data mining results and minimize private data disclosure. The solutions are distributed, i.e., there is no central, trusted party having access to all the data. Instead, we define protocols using homomorphic encryption and digital envelope techniques to exchange the data while keeping it private.
Solving dynamic stochastic economic models by mathematical programming decomposition methods
Authors: Mercedes Esteban-Bravo, Francisco J. Nogales
Venue: Computers and Operations Research (2008)

Discrete-time optimal control problems arise naturally in many economic problems. Despite the rapid growth in computing power and new developments in the literature, many economic problems are still quite challenging to solve. Economists are aware of the limitations of some of these approaches for solving these problems due to memory and computational requirements. However, many of the economic models present some special structure that can be exploited in an efficient manner. This paper introduces a decomposition methodology, based on a mathematical programming framework, to compute the equilibrium path in dynamic models by breaking the problem into a set of smaller independent subproblems. We study the performance of the method solving a set of dynamic stochastic economic models. The numerical results reveal that the proposed methodology is efficient in terms of computing time and accuracy.
Modeling changing dependency structure in multivariate time series
Authors: Xiang Xuan, Kevin Murphy
Venue: Proceedings of the 24th international conference on Machine learning (2007)

We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations using undirected Gaussian graphical models, whose structure we estimate. We show how we can exactly compute the MAP segmentation, as well as how to draw perfect samples from the posterior over segmentations, simultaneously accounting for uncertainty about the number and location of changepoints, as well as uncertainty about the covariance structure. We illustrate the technique by applying it to financial data and to bee tracking data.
Feature Extraction for DNA Microarray Data
Authors: Yihui Liu
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

In this study we perform wavelet analysis on high dimensional microarray data. We perform two methods of feature extraction on microarray data, using approximation coefficients and detail coefficients. A set of orthogonal wavelet approximation coefficients based on wavelet decomposition are extracted to compress the gene profiles and reduce the dimensionality of microarray data. A set of orthogonal wavelet detail coefficients are extracted to characterize the localized features of gene profiles and reduce dimensionality. Experiments are performed on two datasets. The experimental results show a highly competitive accuracy is achieved compared to the best performance of other kinds of classification models using wavelet coefficients.
Guest Editors' Introduction: Recommender Systems
Authors: Alexander Felfernig, Gerhard Friedrich, Lars Schmidt-Thieme
Venue: IEEE Intelligent Systems (2007)

This special issue presents eight articles, five long and three short, on techniques to improve recommender systems. They cover improving such aspects as user interaction with recommenders, the quality of results presented to users, and user trust in presented recommendations. This article is part of a special issue on Recommender Systems.
Learning dynamic models of compartment systems by combining symbolic regression with fuzzy vector envisionment
Authors: Mehdi Khoury, Frank Guerin, George M. Coghill
Venue: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation (2007)

This paper is concerned with the learning of dynamic models of compartmental systems visualized as networks of interconnected tanks. This is intended as an intermediary step to learn more complex dynamic biological systems such as metabolic pathways. Our present aim is to learn systems of differential equations from time series data to capture physical models of increasing complexity (u-tube, cascaded tanks, and coupled tanks). To do so, we use Symbolic Regression in Genetic Programming and combine it with a fuzzy representation which has inherent differential capabilities (Fuzzy Vector Envisionment). We use the ECJ1 framework to implement the learner. Present results show that the system can approximate the target models and that the use of a weighted fitness function seems to accelerate the learning process.
Efficient space-time adaptive processing for airborne MTI-mode radar
Authors: J. R. Guerci
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

Space-time adaptive array processing has emerged as a key technology thrust area for the next generation of airborne radar systems due to its inherent potential for vastly improving moving target indicator (MTI) performance. Unfortunately, these performance gains come with a commensurate increase in on-line computational complexity if full degree-of-freedom (DOF) space time adaptive processing (STAP) processors are employed. In this paper we introduce a class of efficient STAP processors which exploit the fact that the full DOF space-time clutter covariance matrix is rank deficient with respect to a coherent processing interval.
Modeling, control, and motion planning of a climbing microrobot
Authors: Jizhong Xiao, Jun Xiao, Ning Xi, Hans Dulimarta, R. L. Tummala, Mark Minor, R. Mukherjee
Venue: Integrated Computer-Aided Engineering (2004)

This paper describes the design, modeling, control and motion planning analysis of a climbing microrobot. The microrobot is the smallest of bipedal robot found in the literature which is able to climb walls, walk on ceilings, crawl through pipes, and transit between two inclined planes. The underactuated structure contributes to the small size and light weight of the robot. The kinematic model in different locomotion modes is derived. The DSP-based embedded controller is presented. A hybrid configuration space is proposed to incorporate the continuous configuration space with discrete motion status space. Based on the motion pattern analysis, a motion planning approach is developed to generate an optimal collision-free path and a feasible motion sequence to allow the robot to travel along the path. Experimental and simulation results demonstrate the effective performance of the microrobot system.
Probing user values in the home environment within a technology driven Smart Home project
Authors: Victoria Haines, Val Mitchell, Catherine Cooper, Martin Maguire
Venue: Personal and Ubiquitous Computing (2007)

Smart Home technology looks set to become an increasingly common feature of domestic life. However commercial desire for technical innovation rather than explicit user needs are often the driving force behind the development of Smart Home products and services. This study adapts the Cultural Probe approach developed by Gaver et al. [2] to collect primarily visual data about what people value within their home environment. Whereas Cultural Probes are predominantly used to build empathy with users when designing product concepts, this approach attempted to provide similarly fun and engaging prompts for data collection when the design process and project context required more structured consideration of user needs. This paper presents the method developed, project findings and recommendations on how the method should be applied.
Improving World Wide Web and library research [for engineering students]
Authors: J. B. Stenger
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

In conducting reviews of pertinent literature and obtaining background material for research and design projects, students currently demonstrate an admirable knack for obtaining information using the World Wide Web. What they are not demonstrating, though, are critical analysis skills in assessing these sources. Also, students seem to feel that the World Wide Web is a complete source, and use library resources for only a search of the online "card catalogue", if at all. In this paper, the authors discuss current trends in the use of the World Wide Web for research and methods to insure the validity of the sources. Techniques to make students aware of the appropriate use of the Web are presented. Finally, they discuss the other library resources that students should be using and how to make them aware of these.
Innovative research and laboratory experiences for undergraduate students
Authors: K. L. Kitto
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 03 (1998)

Students majoring in Engineering Technology programs at Western Washington University (USA) have many opportunities to participate in unique undergraduate research experiences and innovative laboratory programs. This paper describes the methods used by the faculty to integrate innovative design experiences into the undergraduate programs at Western Washington University. The CIM projects in the Manufacturing Engineering Technology program are used to illustrate how undergraduate students can have their own creativity and learning stimulated by creating learning tools for K-12 programs. Faculty workload issues are also discussed. Finally, the paper describes another step in the integration process at Western Washington University-a new curricular model that will focus on high-end CAE packages and rapid prototyping to enhance laboratory experiences and undergraduate research programs. 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
A new approach to the design of multidimensional non-separable two-channel orthonormal filterbanks
Authors: D. Wei
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

We propose a novel approach to the design of multidimensional non-separable two-channel orthonormal filterbanks and wavelets, which has been a challenging problem. We perform spectral factorization of the multidimensional product filter by jointly optimizing the product filter and the lowpass filter. The optimization is performed using iterative quadratic programming. Examples show that the resulting filterbanks have negligible reconstruction error and hence can be treated as orthonormal filterbanks and wavelets in practice.
Fast QR based IIR adaptive filtering algorithm
Authors: M. Bhouri
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

In this paper, we present a new QR based algorithm for IIR adaptive filtering. This algorithm achieves a reduction of complexity with regard to the IIR-QR algorithm by using a block reduction transformation. Moreover, this new approach makes it possible to directly transform the fast FIR algorithm into fast O(N) versions of the IIR algorithm. Therefore, we derive a fast version of the algorithm from the rotation-based lattice algorithm (QR-LSL). Simulations, have proven the fast convergence and the good numerical properties of both algorithms for systems satisfying the strictly positive real (SPR) condition. 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
Modulating waveforms for OFDM
Authors: Z. Cvetkovic
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

Orthogonal frequency division multiplexing (OFDM) is a popular transmission technique that is employed in applications such as digital audio broadcasting, asymmetric digital subscriber line and wireless LAN. We consider design of modulating waveforms for OFDM in the presence of the delay spread and system impairments such as frequency offset and timing mismatch. We give a complete parameterization of OFDM modulating waveforms. Increasing robustness of OFDM to frequency offsets requires using long modulating waveforms. To make the implementation of OFDM systems with long modulating waveforms feasible we propose fast implementation algorithms. Some preliminary modulating waveform design examples are presented. The presented waveforms demonstrate that the robustness of OFDM systems to impairments can be improved by allowing certain degradation of unnecessarily good performances of the state of the art OFDM systems in ideal operating conditions. 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
Authentication and key establishment in computer and communication networks: no silver bullet
Authors: Lein Harn
Venue:  (2006)

Authentication and Key Establishment (AKE) in computer and communication networks refers to a process of enabling a group (of two or more members) to communicate securely with the confidence that no non-member can legibly eavesdrop or pretend to be a member of the group. The need for such a process can be realized in a variety of applications in computer and communication networks where two or more entities need to communicate over shared communication media. The fundamental question addressed by this dissertation is "How to enable two entities to communicate securely?" The computing and communication environments affect the overall design of the AKE solution. Since these environments vary from powerful computing devices on high-bandwidth networks to much smaller low-power sensor devices on low-bandwidth wire less networks, there is no single solution (no silver bullet) to solve the problem in every environment. This dissertation identifies the major constraints in typical environments and proposes solutions for each of the scenarios meeting the constraints. In this research, we first broadly classify the environments in three scenarios on the basis of available computation power, energy, and communication bandwidth. (1) High-end to High-end Communication; (2) High-end to Low-end Communication; (3) Low-end to Low-end Communication. We then propose solutions to AKE and related problems. For the first scenario, we propose the following solutions: (a) efficiently integrating Diffie-Hellman key exchange protocol into Digital Signature Algorithm, (b) a new design for discrete-logarithm-based, factoring-based, and elliptic-curve-based AKE protocol using single cryptographic assumption, (c) a new design for digital certificates to facilitate AKE.For the second scenario, we propose a solution to use a combination of symmetric-key cryptography and public-key cryptography to design efficient and secure AKE protocol in a wireless environment. For the third scenario, we propose the following solutions: (a) a modeling scheme for pairwise key establishment for random key distribution in large-scale sensor networks; (b) a scheme for key predistribution and shared-key discovery in sensor networks; (c) a source-routing-based scheme for pairwise key establishment in sensor networks.
Adaptive Web Data Extraction Policies
Authors: Giacomo Fiumara, Massimo Marchi, Alessandro Provetti
Venue: Proceedings of the Eighth IEEE International Workshop on Policies for Distributed Systems and Networks (2007)

Dynamo is a middleware that helps in generating informative RSS feeds out of legacy HTML Web sites. To produce timely and informative RSS feeds, and to be scalable, Dynamo needs a careful tuning and customization of its polling policies which have been evaluated against frequently-updated news portals.