ppxscal/embedding_network huggingface dataset:
Teaching online: survival skills for the effective teacher
Authors: Yoram Eshet
Venue: ACM SIGCSE Bulletin (2007)

The rapid infiltration of instructional technologies into educational systems and corporations, confront teachers, trainers and instructors with situations that require the utilization of an ever-growing assortment of technical, cognitive, and sociological skills that are necessary in order to perform effectively in digital environments. These skills are termed collectively 'digital literacy'. However, unlike the common attitude towards digital literacy in most studies of instructional technologies, it is more than just the technical ability to use digital devices properly. Digital literacy comprises a variety of cognitive skills that are utilized when teaching or learning at a distance, such as the ability to divide attention between students in an online lecture, the ability to teach effectively in a non-linear environment, and the ability decipher information from visual representations, as in user interfaces. In fact, digital literacy has become today a "survival skill" for present-days teachers that use technology for instruction; a key that helps them to employ successfully complex instructional strategies in their teaching.
A Service-Oriented Blueprint for COTS Integration: the Hidden Part of the Iceberg
Authors: Vina Ermagan, Claudiu Farcas, Emilia Farcas, Ingolf H. Kruger, Massimiliano Menarini
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

The use of commercial off-the-shelf (COTS) software can greatly reduce the development cost and effort for complex software systems. Reusing software can also improve the general quality of a system by leveraging already proven implementations. One of the limiting factors in the adoption of COTS software is the complexity of integrating it with the rest of the system under development. Often, requirements do not entirely match the functionalities available in COTS components, increasing the complexity of the glue software that needs to be written. In this paper, we present the blueprint of a Service- Oriented Architecture that can guide the engineer both in specifying the functionalities of a complex software system and as a deployment architecture to seamlessly integrate COTS components implementing such functionalities. The COTS integration concern, typically a deployment issue, is addressed in the service architecture, and is treated as first-class citizen of the development process.
Hamiltonian systems for computation
Authors: Roger W. Brockett
Venue:  (2006)

Motivated by problems in neuroscience and other analog systems for computation, we develop a theory of interconnections for Hamiltonian systems. To this end, we endow Hamiltonian systems on arbitrary symplectic manifolds with an input-output structure where the input and output spaces are related by duality pairing. We show how an interconnection of several such systems can be described by a bilinear form on the output space and how, as a consequence, power conserving interconnections can be identified with two-forms on that output space. Our main contribution is the introduction and study of a symplectic form for the interconnected system, defined in terms of the interconnection, as well as the commutation relations of the control vector fields. This is the so called closed loop symplectic form. We also show how the analysis of this two-form can reveal constraints on the interconnected system. We apply these results to the Toda lattice and obtain a framework for the design of a general class of networks carrying pulses. In the second part, we show how to perform data clustering using a smooth dynamical system. We exhibit a relationship between the Lie algebra of n &times; n skew-symmetric matrices and clusterings of n points. This relationship is then used to design a differential equation which performs data clustering. Noteworthy aspects of this approach are that the number of clusters is not required a priori but is a result of the algorithm and the graph of the time evolution of the flow yields a dendrogram of the clustering. We provide several examples illustrating the algorithm.
A FPGA-based Viterbi algorithm implementation for speech recognition systems
Authors: F. L. Vargas
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

This work proposes a speech recognition system based on a hardware/software co-design implementation approach. The main advantage in this approach is an expressive processing time reduction in speech recognition, because part of the system is implemented by dedicated hardware. This work also discuss another way to implement "hidden Markov models" (HMM), a probabilistic model extensively used in speech recognition systems. In this new approach, the Viterbi algorithm, used to compute the HMM likelihood score, will be "built in" together with the HMM structure designed in hardware, and implementing probabilistic state machines that will run as parallel processes one for each word in the vocabulary handled by the system. So far, we have a dramatic speed up performance, getting measures around 500 times faster than a classic implementation with the correctness comparable with others isolated word recognition systems.
Multimedia tutors for design for manufacturing
Authors: B. P. Woolf
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

Our group at the University of Massachusetts has built design for manufacturing (DFM) computer modules which instruct students on efficient procedures for designing parts for manufacture. The goal is to assist engineering students to gain a deeper understanding of the interaction between features of a part being designed and the corresponding manufacturing requirements of the part in the domains of injection molding and sheet metal stamping. We provide animated sequences of the processes indexed according to the possible designs. The tutors allow students to select a restricted set of parts for manufacture and demonstrate the tooling complexity through both 2D animations and 3D animations. An underlying internal representation of the part being designed provides a non-intrusive critique mechanism to provide feedback to the student.
Content based representation of colour image sequences
Authors: I. Kompatsiaris
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

A procedure is described for the spatiotemporal segmentation and tracking of objects in colour image sequences. For this purpose, we propose the novel procedure of the k-means with a connectivity constraint algorithm as a general segmentation algorithm combining several types of information including colour, motion and compactness. A new colour distance is also defined for this algorithm. The regularisation parameters are evaluated automatically using the min-max criterion. In this algorithm, the use of spatiotemporal regions is introduced since a number of frames is analyzed simultaneously and as a result the same region is present in consequent frames. Experimental results on real and synthetic colour data demonstrate the performance of the data.
On information energy of the image fuzzy sets
Authors: S. M. Taheri, R. Azizi
Venue: Information Sciences: an International Journal (2007)

Information energy is a measure of useful information obtained from a fuzzy set. This paper investigates the information energy change between the original fuzzy set and the image fuzzy set, through the extension principle. Some methods, by which the information energy of the image fuzzy set can be directly obtained without calculating its membership function, are studied. Useful formulas calculating the information energy of the image of the same shape fuzzy numbers are specifically introduced.
Multiuser blind identification using a linear parameterization of the channel matrix and second-order statistics
Authors: T. P. Krauss
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

We observe that the channel matrix in the standard multiuser, multichannel (MIMO) digital communications model is linear in the channel coefficients. Also, previous work incorporating "basis functions" suggests that the multipath channel itself is in a subspace formed by delayed versions of the transmission pulse. Hence the channel matrix is linear in the coefficients of this subspace. We propose two algorithms based on the sample covariance matrix of the received signal (i.e., second-order statistics) that take advantage of this linear parameterization: a new identification algorithm that estimates the outer product of the model coefficients via multiplication by a predetermined matrix, and a multiuser version of the previously presented "subspace method" that employs knowledge of the transmission pulse. While both methods are superior to the original non-parameterized subspace method in terms of computation and performance, the new method requires less computation and in some cases outperforms the other.
The Vortex: A Superscalar Asynchronous Processor
Authors: Andrew Lines
Venue: Proceedings of the 13th IEEE International Symposium on Asynchronous Circuits and Systems (2007)

The "Vortex" processor is a general purpose CPU with a novel architecture and instruction set. The pri- mary feature of the Vortex architecture is many par- allel function units which communicate through a cen- tral crossbar, instead of a traditional register file. In- structions are fetched in parallel by cache lines, as in a VLIW processor, but any data or structural dependen- cies are resolved deterministically by the hardware, as in a superscalar processor. The prototype Vortex CPU supports a 32-bit integer datapath and executes up to 9 instructions per cycle. It uses the "integrated pipelining" asynchronous design style, was fabricated in 2001 in TSMC's 0.15um G pro- cess, and runs at a typical frequency of 475MHz. Al- though the Vortex CPU itself has not been commercial- ized, many of its component circuits have been used in the products of Fulcrum Microsystems.
Lingua Franca: an IDL for structural subtyping distributed object systems
Authors: Patrick A. Muckelbauer, Vincent F. Russo
Venue: Proceedings of the USENIX Conference on Object-Oriented Technologies on USENIX Conference on Object-Oriented Technologies (COOTS) (1995)

Recently the trend has been towards applying object-oriented techniques to address problems of building scalable and maintainable distributed systems. Object-oriented programming increases modularity and data abstraction by supporting encapsulation through narrow, rigidly defined and strongly enforced interfaces to objects. Unfortunately, object-oriented interfaces and mechanisms are usually only accessible and enforced through language mechanisms or strict programming conventions. This severely limits the degree to which disjoint, unrelated components can interact in a multilingual, loosely coupled distributed system. An accepted solution to the language dependence problem is the use of high-level interface description languages (IDLs). IDLs provide a description mechanism for an object's interface that is independent of any programming language. In this paper we describe an interface description language and runtime support system that uses structural subtyping rules rather than the traditional interface name equivalence rules for conformance checking. We argue that the choice of structural subtyping rather than interface name equivalence leads to a less coupled and more extensible distributed system.
An Efficient Method for Very Large Scale Out-of-Core Terrain Visualization
Authors: Huijie Zhang, Jigui Sun, Haihong Yu, Changsong Qi
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

Large scale terrain visualization with high-resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. The hierarchical structure can decimate the elevation data that must be loaded into internal memory. Thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. The comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio.
XML Query Optimization Using the Binding Hash Method
Authors: Michael J. Brant, Karen C. Davis
Venue: Proceedings of the 24th British National Conference on Databases (2007)

XML query processing involves searching an XML document and returning results that satisfy a query while choosing the best method for the particular query and document. In this paper we develop a method called Binding Hash (BH) that performs a subset of XML query operations focusing on structural join. The BH method answers Xpath expressions directly or generates witness trees that can be used as intermediate results in a query processor. It uses pointer-based traversal and index-based access simultaneously to speed-up structural joins. A performance study indicates that the BH method performs better than existing competitive techniques for queries that are deeply nested and non-bushy. The BH method can be integrated into a larger system to be selected for an execution plan when it achieves the best performance.
Decoding optimal state sequence with smooth state likelihoods
Authors: I. Zeljkovic
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

A novel algorithm that allows the decoding of hidden Markov model (HMM) state sequences while constraining the state likelihoods to be more uniform is presented. In HMM-based speech recognizers, the decoded optimal state sequence is restricted by the HMM topology and the grammar. Thus, the most likely state sequence derived by the Viterbi algorithm can be influenced by a few states with very high likelihoods-often resulting in recognition errors. This paper presents a method for decoding state sequences with less volatile state probabilities by introducing penalties proportional to the difference of the current state likelihood and the highest state likelihood for the particular time frame. These penalties are added to the cumulative likelihoods in the Viterbi forward path at every time frame. This technique, referred to as the smooth state likelihood decoding algorithm (SSLDA), reduced recognition error-rates substantially on connected digit tests performed on two speech databases derived from field trials. The error rate was reduced by more than 40% on the one database and more than 60% on the other field trial database for variable length digit strings.
A spectral method for bonds
Authors: Javier de Frutos
Venue: Computers and Operations Research (2008)

We present an spectral numerical method for the numerical valuation of bonds with embedded options. We use a CIR model for the short-term interest rate. The method is based on a Galerkin formulation of the partial differential equation for the value of the bond, discretized by means of orthogonal Laguerre polynomials. The method is shown to be very efficient, with a high precision for the type of problems treated here and is easy to use with more general models with nonconstant coefficients. As a consequence, it can be a possible alternative to other approaches employed in practice, specially when a calibration of the parameters of the model is needed to match the observed market data.
An overview of anomaly detection techniques: Existing solutions and latest technological trends
Authors: Animesh Patcha, Jung-Min Park
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2007)

As advances in networking technology help to connect the distant corners of the globe and as the Internet continues to expand its influence as a medium for communications and commerce, the threat from spammers, attackers and criminal enterprises has also grown accordingly. It is the prevalence of such threats that has made intrusion detection systems-the cyberspace's equivalent to the burglar alarm-join ranks with firewalls as one of the fundamental technologies for network security. However, today's commercially available intrusion detection systems are predominantly signature-based intrusion detection systems that are designed to detect known attacks by utilizing the signatures of those attacks. Such systems require frequent rule-base updates and signature updates, and are not capable of detecting unknown attacks. In contrast, anomaly detection systems, a subset of intrusion detection systems, model the normal system/network behavior which enables them to be extremely effective in finding and foiling both known as well as unknown or ''zero day'' attacks. While anomaly detection systems are attractive conceptually, a host of technological problems need to be overcome before they can be widely adopted. These problems include: high false alarm rate, failure to scale to gigabit speeds, etc. In this paper, we provide a comprehensive survey of anomaly detection systems and hybrid intrusion detection systems of the recent past and present. We also discuss recent technological trends in anomaly detection and identify open problems and challenges in this area.
Discriminative training via linear programming
Authors: K. A. Papineni
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

This paper presents a linear programming approach to discriminative training. We first define a measure of discrimination of an arbitrary conditional probability model on a set of labeled training data. We consider maximizing discrimination on a parametric family of exponential models that arises naturally in the maximum entropy framework. We show that this optimization problem is globally convex in R/sup n/, and is moreover piecewise linear on R/sup n/. We propose a solution that involves solving a series of linear programming problems. We provide a characterization of global optimizers. We compare this framework with those of minimum classification error and maximum entropy.
Adjustable Cost Estimation Model for COTS-Based Development
Authors: Poom Naunchan, Daricha Sutivong
Venue: Proceedings of the 2007 Australian Software Engineering Conference (2007)

The use of commercial off-the-shelf (COTS) products to develop systems has become increasingly prominent due to schedule and cost benefits. However, COTS integration requires considerable effort and time, and an accurate estimate of an integration cost can help a project manager plan and ensure an ontime completion of the project. The COCOTS model is a widely-used method to estimate effort in COTS-based development (CBD), but the model does not address duration estimation directly or allows for a user-customized integration process, which may differ across organizations and projects. This paper proposes an adjustable model for estimating effort and duration of the integration process of CBD. The methodology integrates three existing approaches, namely COCOTS model for cost estimation, system dynamics for software process simulation, and communication overhead assumption. The proposed framework models COTS development in three phases: 1) tailoring phase 2) glue code development phase 3) system-level integration and test phase. Contrary to the traditional models, the proposed approach allows users to adapt the integration process pattern and specify productivity factors that are appropriate for their organizations. In addition to estimating the required workforce for each time period, the proposed model also finds the minimal effort needed as well as the optimal group member allocation for the COTS integration process.
Application of MVDR beamforming to reject turbulence noise in a duct
Authors: D. J. Sebald
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

In active noise control (ANC) on air duct/fan systems it is desirable to achieve noise cancellation using the shortest possible duct length. A barrier to this goal is the presence of air turbulence at the duct input due to the fan driving the system. Turbulent pressure fluctuations contaminate measurement of the acoustic noise in the duct, resulting in degraded noise cancellation performance. We investigate the use of adaptive array processing techniques to suppress the effects of turbulence. Based upon the spatial correlation and temporal spectral characteristics of turbulence, we propose a hybrid generalized sidelobe canceller (GSC) which is constrained to adapt only in the frequency range where both acoustic noise and turbulent noise contribute correlated components to the multivariate input covariance. The effectiveness of this method is demonstrated using actual experimental data.
Multipath Identification Using Steepest Gradient Method for Dynamic Inventory in UHF RFID
Authors: Jin Mitsugi, Yu Shibao
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (2007)

UHF passive RFID has been already in practice. Industrial applications sometimes suffer insufficient tag readability. Engineering may be needed to enhance the readability, accordingly. One of the factor to deteriorate the readability is the multipath fading. Identification of principal reflecting paths is essential to improve the readability deterioration by, for example, using antenna diversity and usage of microwave absorbance materials to suppress reflections. In this paper, a path identification method for UHF RFID using the measured power profile is presented. The method only requires a series of the received power measurement at the position of the target tag. By applying the steepest gradient method, we can optimize the parameters that defines the reflecting plane and eventually identifies the path direction. Together with theoretical development of the method, numerical example shows the validity of the method.
A 2 GHz Low Power Down-conversion Quadrature Mixer in 0.18-μm CMOS
Authors: Shaikh K. Alam
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

This paper describes a 1.5-V 2 GHz I/Q down conversion mixer for a WCDMA front-end receiver in a 0.18-ìm CMOS process. The mixer achieves a conversion gain of 20.55 dB within 1-dB compression point (iCP1dB) of -9.2 dBm. It also achieves a double side band (DSB) noise figure (NF) of 8.96 dB. The mixer acquires the third order input referred intercept point (IIP3) of -0.54 dBm. The mixer consumes only 4.0 mA of current from a 1.5-V power supply.