ppxscal/embedding_network huggingface dataset:
Structuring CSed research studies: connecting the pieces
Authors: Arnold N. Pears, Mats Daniels
Venue: ACM SIGCSE Bulletin (2003)

Changing conditions for teaching increase our motivation to understand the teaching and learning process. First time investigators of educational settings often feel uncertain about what aspects are involved and how to design a meaningful investigation. This paper develops and describes an applied research model with the objective of providing computer science (CS) academics of with a structured overview of the inter-disciplinary research components of CS education research.The paper argues that adopting such a model has the potential to enhance the maturity, significance and applicability of CS education research studies by placing them in a more complete research context. This helps to make the outcomes more readily transportable to other teaching and learning situations.One aim of publicizing the model is to help inspire the growing numbers of people who are becoming interested in CS education research. In addition we hope to simplify the task of gaining a rapid understanding of the research design issues and options that are typically involved.
Concurrent Placement and Routing in the Design of Integrated Circuits
Authors: A. I. Erzin, J. D. Cho
Venue: Automation and Remote Control (2003)

For the problem arising in the design of integrated chips, an efficient heuristic approach was proposed. It unites the stages of placing the logical elements (devices) on the chip and performing their detailed routing. At that, it minimizes both the critical (maximum) delay and the chip area required for routing.
Memory of Distributed Computer Systems: Distinctive Features of Their Architectural-Structural Organization and Use
Authors: Yu. S. Yakovlev
Venue: Cybernetics and Systems Analysis (2003)

Distinctive features of architectural-structural organization and use of memory networks are considered with the aim of choosing an optimal configuration in designing distributed computer systems.
Mediating the tension between information privacy and information access: the role of digital government
Authors: George T. Duncan, Stephen F. Roehrig
Venue: Public information technology: policy and management issues (2003)

Government agencies collect and disseminate data that bear on the most important issues of public interest. Advances in information technology, particularly the Internet, have multiplied the tension between demands for evermore comprehensive databases and demands for the shelter of privacy. In mediating between these two conflicting demands, agencies must address a host of difficult problems. These include providing access to information while protecting confidentiality, coping with health information databases, and ensuring consistency with international standards. The policies of agencies are determined by what is right for them to do, what works for them, and what they are required to do by law. They must interpret and respect the ethical imperatives of democratic accountability, constitutional empowerment, and individual autonomy. They must keep pace with technological developments by developing effective measures for making information available to a broad range of users. They must both abide by the mandates of legislation and participate in the process of developing new legislation that is responsive to changes that affect their domain. In managing confidentiality and data access functions, agencies have two basic tools: techniques for disclosure limitation through restricted data and administrative procedures through restricted access. The technical procedures for disclosure limitation involve a range of mathematical and statistical tools. The administrative procedures can be implemented through a variety of institutional mechanisms, ranging from privacy advocates, through internal privacy review boards, to a data and access protection commission.
Computation of multiphase systems with phase field models
Authors: V. E. Badalassi, H. D. Ceniceros, S. Banerjee
Venue: Journal of Computational Physics (2003)

Phase field models offer a systematic physical approach for investigating complex multiphase systems behaviors such as near-critical interfacial phenomena, phase separation under shear, and microstructure evolution during solidification. However, because interfaces are replaced by thin transition regions (diffuse interfaces), phase field simulations require resolution of very thin layers to capture the physics of the problems studied. This demands robust numerical methods that can efficiently achieve high resolution and accuracy, especially in three dimensions. We present here an accurate and efficient numerical method to solve the coupled Cahn-Hilliard/Navier-Stokes system, known as Model H, that constitutes a phase field model for density-matched binary fluids with variable mobility and viscosity. The numerical method is a time-split scheme that combines a novel semi-implicit discretization for the convective Cahn-Hilliard equation with an innovative application of high-resolution schemes employed for direct numerical simulations of turbulence. This new semi-implicit discretization is simple but effective since it removes the stability constraint due to the nonlinearity of the Cahn-Hilliard equation at the same cost as that of an explicit scheme. It is derived from a discretization used for diffusive problems that we further enhance to efficiently solve flow problems with variable mobility and viscosity. Moreover, we solve the Navier-Stokes equations with a robust time-discretization of the projection method that guarantees better stability properties than those for Crank-Nicolson-based projection methods. For channel geometries, the method uses a spectral discretization in the streamwise and spanwise directions and a combination of spectral and high order compact finite difference discretizations in the wall normal direction. The capabilities of the method are demonstrated with several examples including phase separation with, and without, shear in two and three dimensions. The method effectively resolves interfacial layers of as few as three mesh points. The numerical examples show agreement with analytical solutions and scaling laws, where available, and the 3D simulations, in the presence of shear, reveal rich and complex structures, including strings.
Active security-constrained optimal power flow using modified hopfield neural network
Authors: M. El-Hawary
Venue:  (2002)

A Hopfield neural network is modified to handle inequality constraints by introducing an exterior penalty function. The use of a penalty function converts constrained optimization problems into unconstrained problems. The optimal power flow is a general non-linear programming problem with a non-linear objective function and non-linear functional equality and inequality constraints. Security Constrained Dispatch is defined as an Optimal Power Flow problem, in which the objective function is the total cost of generations and the security constraints are placed on the bus voltage magnitudes, phase angles and the generated active powers. This thesis presents an alternative method for solving optimal active power flow and active security-constrained dispatch using a modified Hopfield neural network. The objective function of security-constrained dispatch is the incremental generation cost function in quadratic form which is expanded in a second-order Taylor series. The equality and inequality constraints are modelled using a linearized network and appended to the objective function using suitable penalty functions to form an augmented cost function. The goal of this research is to model and study the applicability of the modified Hopfield Neural Network for solving optimal active power flow and security-constrained dispatch problem. In addition, this thesis aims to discover the advantages and disadvantages of using this technique instead of the methods that currently exist. The Hopfield Neural Network was simulated on a digital computer for four standard IEEE test systems varying in size from a 5-bus system to a 57-bus system. The optimal solution obtained using this approach is consistent with the solution obtained using the conventional method. The advantage of this method is in the ease of formalization of the problem. It is simple, straightforward, and easy to apply. The method requires modest memory resources and is efficient in computation time. This representation is applicable to many problems other than the economic load-dispatching problem.
An Exponentiation Unit for an OpenGL Lighting Engine
Authors: David Harris
Venue: IEEE Transactions on Computers (2004)

Abstract--The OpenGL geometry pipeline lighting stage requires raising a number in the range [0, 1] to a power between [1, 128] to compute specular reflections and spotlights. The result need only be accurate to a number of bits related to the color depth of the output device. This paper describes a hardware implementation of such an exponentiation unit based on a logarithm lookup table, a multiplier, and an inverse log table. The inputs arrive in IEEE single-precision floating-point format and the output is a floating-point color component in the range [0,1] with 8-10 bits of accuracy. The log lookup table is partitioned into subintervals to reduce table size and each subinterval is computed from a bipartite table to further reduce size. A synthesized design uses 32k gates to achieve 10-bit accuracy with a latency of 9.4 ns in a 180 nm process. Although the system is tailored to the OpenGL application, the same principles can be applied to the design of other exponentiation units.
Matching Software Practitioner Needs to Researcher Activities
Authors: Martin S. Feather, Tim Menzies, Judith R. Connelly
Venue: Proceedings of the Tenth Asia-Pacific Software Engineering Conference Software Engineering Conference (2003)

We present an approach to matching softwarepractitioners' needs to software researchers' activities. Ituses an accepted taxonomical software classificationscheme as intermediary, in terms of which practitionersexpress needs, and researchers express activities. Adecision support tool is used to combine theseexpressions of needs/activities, and to assist in studyingthe implications of that combined knowledge. Thisenables identification of fruitful connections betweenresearchers and practitioners, of areas of commoninterest among researchers, and practitioners, and of"gaps": areas of unfulfilled needs or unmotivatedresearch.We discuss the software engineering underpinning thisapproach, illustrating its utility by reporting onexperiments with a real-world dataset gathered fromresearchers and practitioners. We also suggest that thissame approach would be applicable to understanding thedistribution of interests represented by presenters andattendees of a conference such as APSEC.
Monitoring hard disks with smart
Authors: Bruce Allen
Venue: Linux Journal (2004)

Keep an eye on your drives' health with an easy-to-configure tool.
Developing and Evaluating the Social Network Analysis System for Virtual Teams in Cyber Communities
Authors: Fu-ren Lin, Chun-hung Chen
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 8 - Volume 8 (2004)

By social network analysis, users can know how information flows through social ties, how people acquire information and resources, and how cleavages and coalitions operate. In this research, based on social network theories, we develop a social network analysis system to facilitate teams' collaboration and then evaluate the system's performance. The system can draw graphs to present a team's social networks both ego-centered and whole network, and calculate the values of attributes characterizing the social network. The resulting system can facilitate understanding for both team leaders and general members and help them to see relations and interaction patterns of their teams. The evaluation results indicate that the social network analysis is acceptable by users in terms of simplicity, utility, certainty, and novelty for developing virtual teams of a cyber community.
A user-friendly self-similarity analysis tool
Authors: Thomas Karagiannis, Michalis Faloutsos, Mart Molle
Venue: ACM SIGCOMM Computer Communication Review (2003)

The concepts of self-similarity, fractals, and long-range dependence (LRD) have revolutionized network modeling during the last decade. However, despite all the attention these concepts have received, they remain difficult to use by non-experts. This difficulty can be attributed to a relative complexity of the mathematical basis, the absence of a systematic approach to their application and the absence of publicly available software. In this paper, we introduce SELFIS, a comprehensive tool, to facilitate the evaluation of LRD by practitioners. Our goal is to create a stand-alone public tool that can become a reference point for the community. Our tool integrates most of the required functionality for an in-depth LRD analysis, including several LRD estimators. In addition, SELFIS includes a powerful approach to stress-test the existence of LRD, Using our tool, evidence are presented that the widely-used LRD estimators can provide misleading results. It is worth mentioning that 25 researchers have acquired SELFIS within a month of its release, which clearly demonstrates the need for such a tool.
Blind source separation and channel equalization: an epsilon-approximation algorithm and finite alphabet approach
Authors: Qingyu Li
Venue:  (2003)

In this thesis, we shoe, that a blind separator/equalizer can be obtained without using any high order including second order statistical information on the input by formulating the blind source separation/channel equalization problem into a quadratic optimization with binary constraints. Then, efficient &epsis;-approximation algorithms are presented and applied to find the separator/equalizer coefficients. Identifiability conditions are derived and simulations verify the theoretical results. The method is extended to slowly time-varying as well as nonlinear systems. Different implementation for OFDM systems is also provided. The proposed approach applies to non-minimum phase channels and converges to an &epsis; neighborhood of the global optimum. A discussion for Blind Source Separation when second order statistics are available is also presented.
A two-way visualization method for clustered data
Authors: Yehuda Koren, David Harel
Venue: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (2003)

We describe a novel approach to the visualization of hierarchical clustering that superimposes the classical dendrogram over a fully synchronized low-dimensional embedding, thereby gaining the benefits of both approaches. In a single image one can view all the clusters, examine the relations between them and study many of their properties. The method is based on an algorithm for low-dimensional embedding of clustered data, with the property that separation between all clusters is guaranteed, regardless of their nature. In particular, the algorithm was designed to produce embeddings that strictly adhere to a given hierarchical clustering of the data, so that every two disjoint clusters in the hierarchy are drawn separately.
An Inexact Newton-CG-Type Active Contour Approach for the Minimization of the Mumford-Shah Functional
Authors: Michael Hintermüller, Wolfgang Ring
Venue: Journal of Mathematical Imaging and Vision (2004)

The problem of segmentation of a given gray scale image by minimization of the Mumford-Shah functional is considered. The minimization problem is formulated as a shape optimization problem where the contour which separates homogeneous regions is the (geometric) optimization variable. Expressions for first and second order shape sensitivities are derived using the speed method from classical shape sensitivity calculus. Second order information (the shape Hessian of the cost functional) is used to set up a Newton-type algorithm, where a preconditioning operator is applied to the gradient direction to obtain a better descent direction. The issue of positive definiteness of the shape Hessian is addressed in a heuristic way. It is suggested to use a positive definite approximation of the shape Hessian as a preconditioner for the gradient direction. The descent vector field is used as speed vector field in the level set formulation for the propagating contour. The implementation of the algorithm is discussed in some detail. Numerical experiments comparing gradient and Newton-type flows for different images are presented.
Packet Erasure Protection for Multicasting
Authors: Vladimir Stankovic, Zixiang Xiong
Venue: Proceedings of the Conference on Data Compression (2004)

Priority encoding transmission is an efficient forward error correction system for the robust transmission of scalable image and video data over packeterasure networks. For a memoryless packet erasure channel we first study thesensitivity of an optimal protection solution to a change in the packet erasurerate and in the number of packets. We then propose a practical error protectionalgorithm for multicasting and broadcasting applications. Instead of computing an optimal solution for each client independently, we show that comparableresults can be obtained much faster by refining protections already computedfor other clients. We also consider the situation where clients share a bottleneck link and develop layered multiple description codes that provide a betterquality trade-off among all clients than previous solutions.
False-Noise Analysis for Domino Circuits
Authors: A. Glebov, S. Gavrilov, V. Zolotov, Chanhee Oh, R. Panda, M. Becer
Venue: Proceedings of the conference on Design, automation and test in Europe - Volume 2 (2004)

High-performance digital circuits are facing increasingly severe noise problems due to cross-coupled noise injection. Traditionally, noise analysis tools use the conservative assumption that all neighbors of a net can switch simultaneously, producing the worst-case noise. However, due to logic correlations in the circuit, this worst-case noise may not be realizable, resulting in a so-called false noise failure. Some techniques for computing logiccorrelations have been designed targeting static CMOS circuits. However high performance microprocessors commonly use domino logic for their ALU. The domino circuits have lower noise margins than static CMOS circuits and are more sensitive to coupled noise. Any unnecessary pessimism of the noise analysis tool results in large number of false noise violations and either requires additional extensive SPICE simulations or circuit over-design. Unfortunately false noise analysis developed for static CMOS circuits [11] fails to compute many logic correlations in domino circuits. In this paper we propose a novel technique of computing logic correlations in domino circuits. It takes into account the fact that both pull up and pull down networks of a domino gate can be in non conducting state. The proposed technique generates additional logic correlations for such states of domino gates. In order toimprove the capability of logic correlation derivation technique we combine the resolution method with recursive learning algorithm [12]. The proposed technique is implemented in an industrial noise analysis tool and tested on high performance ALU blocks.
Predicting distribution of a new forest disease using one-class SVMs
Authors: Qinghua Guo, Maggi Kelly, Catherine Graham
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

In California, a newly discovered virulent pathogen(Phytophthora ramorum) has killed thousands of nativeoak trees. Mapping the potential distribution of thepathogen is essential for decision makers to assess therisk of the pathogen and aid in preventing its furtherspread. Most methods used to map potential ranges ofspecies (e.g. multivariate or logistic regression) requireboth presence and absence data, the latter of which is notalways feasibly collected. In this study, we present theone-class Support Vector Machine (SVM) to predict thepotential distribution of Sudden Oak Death in California.The model was developed using presence data collectedthroughout the state, and tested for accuracy using a 5-fold cross-validation approach. The model performedwell, and provided 91% predicted accuracy. We believeone-class SVM when coupled with GeographicalInformation Systems (GIS) will become a very usefulmethod to deal with presence-only data in ecologicalanalysis over a range of scales.
Estimation of Energy Aliasing Error for Nonbandlimited Signals
Authors: J. L. Brown,  Jr.
Venue: Multidimensional Systems and Signal Processing (2004)

In this paper, we investigate the problem of approximating a given (not necessarily bandlimited) signal, x( t), by a (bandlimited) &ldquo;interpolation&rdquo; or &ldquo;sampling&rdquo; series of the form: {\rm {x}}_{\sigma} (t) \underline{\underline {\Delta}}\sum_{-\infty}^{\infty}{\rm x(nT)}{{\sin\sigma(t-{\rm nT})}\over{\sigma(t-{\rm nT})}}, {\rm T}={{\pi}\over{\sigma}}, t \in {\bf {R}}, where &sigma; is a given positive parameter, the approximation error being measured in the L 2( R) norm.When {\rm {x(t)}}={{1}\over{2\pi}}\int\nolimits_{-\infty}^{\infty}{\rm {X}}(\omega)e^{i\omega t}d\omega for all t &isin; R with X( &omega;) &isin; L 1( R), approximation in the uniform norm yields the well-known error estimate, \mid {\rm x}(t)-{\rm x}_{\sigma}(t)\mid\le {{1}\over{\pi}}\int\limits_{\mid\omega\mid > \sigma}\mid{\bf X}(\omega)\mid d\omega.An analogous result using the L 2 &minus; norm, \parallel {\rm x}(t)-{\rm x}_{\sigma}(t)\parallel_{2}^{2}\le c \int\limits_{\mid\omega\mid > \sigma}\mid{\bf X}(\omega)\mid^{2}d\omega, \eqno {(*)} has been reported in the recent literature [1], [2] for x( t) &isin; C ( R) &cap; L 1( R), X( &omega;) &isin; L 1 &cap; L 2( R) and c an absolute constant independent of x( t).Our principal result is the following:Given absolute constants &beta; > 0 and &sigma; > 0, a continuous, bandlimited signal x &beta;( t) &isin; L 1 &cap; L 2( R) can be constructed with \eqalign{{\rm x}_{\beta}&(t)={{1}\over{2\pi}}\int\limits_{-\infty}^{\infty}{\rm X_{\beta}}(\omega)e^{i\omega t}d\omega ; {\bf X}_{\beta}(\omega)\in L^{1}\cap L^{2} ({\bf R}) \ {\rm {such \ that}}\cr \parallel {\rm x}_{\beta}&(t)-{\rm x}_\sigma (t)\parallel_{2}^{2}\ge \beta \int\limits_{\mid\omega\mid > \sigma}\mid {\rm X}_{\beta}(\omega)\mid^{2} d\omega.\cr}This shows that a result of the form (*) with an absolute constant c cannot hold in general, even with the added restriction to finite bandwidth signals.