ppxscal/embedding_network huggingface dataset:
A Framework for Assessing the Adequacy and Effectiveness of software development methodologies
Authors: James D. Arthur, Richard E. Nance
Venue:  (1991)

A framework for evaluating software development methodologies is described. Beginning with the issue of what constitutes a methodology, an evaluation procedure is presented that exploits defined linkages among objectives, principles, and attributes intrinsic to the software development process. The evaluation of software development methodologies reflects an assessment structured by the needs, process, and product sequence for system development. Linkages are defined from recognized software engineering sources, providing a foundation for both objective and subjective "analysis" of a given methodology. Application of the evaluation procedure to two software development methodologies currently used by the United States Navy establishes feasibility of the framework and reveals the inherent power of the evaluation procedure. 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 Simulation Study of Adaptive Scheduling Policies in Interactive Computer Systems
Authors: Samuel T. Chanson, C. Bishop
Venue:  (1977)

A number of adaptive processor scheduling algorithms (i.e, those that will adjust to varying workload conditions so as to maximize performance) for interactive computing systems are examined and new ones proposed. The performance indices chosen are the mean response time and the mean of those response times less than the x percentile for some x. The robustness of the algorithms are studied and a brief discussion on the overheads involved is included. Simulation is used throughout the study and because of this, the simulator and the workload used are described in some detail. The target machine is a somewhat simplied version of the UBC system which operates an IBM 370/168 running under MTS (Michigan Terminal System). The UBC system is principally used interactively.
A Project Oriented Course on Software Engineering
Authors: Sallie M. Henry
Venue:  (1990)

An undergraduate course in Software Engineering has been offered at the University of Wisconsin-LaCrosse for the past three years. The intent of the course is to present a broad overview of most of the areas of Software Engineering. Most Software Engineering courses offered will also cover the general aspects of Software Engineering. However, UW-LaCrosse students participate in a group project where they apply these Software Engineering concepts. Each team of students design a system, make a system design presentation, "hire" programmers, integrate the system modules, and document their systems. The administration of group projects is in general complicated; however, the administration of this type of project with the large amount of interaction among students is worse. This paper makes an attempt to outline this Software Engineering course with particular attention to the administration of the project. 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
Summaries of Three Critical Infrastructure Applications
Authors: J. Knight, M. Elder, J. Flinn, P. Marx
Venue:  (1997)

Modern society has grown to depend heavily upon a set of infrastructure services for day-to-day operations to proceed normally and efficiently. Examples of these infrastructure services include power distribution, telecommunications, transportation, and financial systems. In the event of widespread failure in any of these systems, normal activities would be severely disrupted; therefore, these systems are referred to as critical infrastructure applications. This report presents the results of a study of three particular critical infrastructure applications: the banking and finance domain, the rail transport industry, and the air traffic control system. An overview of each application area is provided, including major processes and information concerning system architecture and implementation. In addition, a detailed bibliography is provided for each application domain.
Lateral pile response due to interface yielding
Authors: W. D. Guo
Venue: Proceedings of the eighth international conference on The application of artificial intelligence to civil and structural engineering computing (2001)

In this paper, elastic-plastic solutions are developed for laterally loaded piles. The solutions can be reduced to the available solutions for some simple cases. Various explicit expressions were developed, which compare fairly well with published (experimental and numerical) results under different load levels. The solutions allow the effect of interface yielding (also the effect of a lower layer) to be explored, which occurs at a rather lower loading level. Thus elastic-plastic solution should be adopted in general design.
Scaleability of a Binary Tree on a Hypercube
Authors: Sanjay R. Deshpande
Venue:  (1988)

The concept of scalability is extended to a twin-tree structure composed of two n-1 level binary trees connected via a third link between the roots of the trees. The addendum contains a proof of the fact that the twin-tree structure is scalable on a hypercube.
Regularization Methods for Differential Equations and Their Numerical Solution
Authors: Ping Lin
Venue:  (1995)

The objectives of the thesis are to propose and to investigate approximate methods for various differential equations with or without constraints. Most attention is paid to ordinary and partial differential equations with constraints (where the solution is know to lie in an explicitly defined invariant manifold). We propose and analyze a regularization method called sequential regularization method (SRM) and its numerical approximation. A very important improvement of the SRM over usual regularization methods is that the problem after regularization need not be stiff. Hence explicit difference schemes can be used to avoid solving nonlinear systems. This makes the computation much simpler. The method is applied in several application fields such as mechanical constrained multi-body systems, nonstationary incompressible Navier-Stokes equations which is an example of partial differential equations with constraints (PDAE), and miscible displacement in porous media in reservoir simulation. Improvements over stabilization methods that stabilize the invariant manifold over long time intervals and extra benefits for these applied problems are also achieved. We finally discuss the numerical solution of several singular perturbation problems which come from many applied areas and regularized problems. Uniformly convergent schemes with respect to the perturbation parameter are constructed and proved. A spurious solution phenomenon for an upwinding scheme is analyzed.
Applying Decay Strategies to Branch Predictors for Leakage Energy Savings
Authors: Zhigang Hu, Philo Juang, Kevin Skadron, Douglas W. Clark, Margaret Martonosi
Venue:  (2001)

This paper shows that substantial reductions in leakage energy can be obtained by deactivating groups of branch-predictor entries if they lie idle for a sufficiently long time. Decay techniques, first introduced by Kaxiras et al. for caches, work by tracking accesses to cache lines and turning off power to those that lie idle for a sufficiently long period of time (the decay interval). Once deactivated, these lines essentially draw no leakage current. The key trick is in identifying opportunities where an item can be turned off without incurring significant performance or power cost. Branch predictors are, like caches, large array structures with significant leakage; as such, it is natural to consider applying decay techniques to them as well. Applying decay techniques to branch predictors is, however, not straightforward. The overhead for applying decay to individual counters in the predictor is prohibitive, so decay must be applied to groups of predictor entries. The most natural grouping is a row in the square data array used to implement the branch predictor, but then decay will only be successful if entire rows lie idle for sufficiently long periods of time. This paper shows that branch predictors do exhibit sufficient spatial and temporal locality to make decay effective for bimodal, gshare, and hybrid predictors, as well as the branch target buffer. In particular, decay is quite effective when applied intelligently to hybrid predictors, which use two predictors in parallel and are among the most accurate predictor organizations. Hybrid predictors are also especially amenable to decay, because inactive entries in one component can be left inactive if the other component is able to provide a prediction. Overall, this paper demonstrates that decay techniques apply more broadly than just to caches, but that careful policy and implementation make the difference between success and failure in building decay-based branch predictors.
A cooperative hypermedia solution to work management in real-time enterprises
Authors: Weigang Wang, Frank Lillehagen
Venue: Proceedings of the fourteenth ACM conference on Hypertext and hypermedia (2003)

Many enterprise resource planning (ERP) and project management systems are geared for monthly planning and analysis. Often, managers could not see what was going on in their businesses until it was too late to react. Real-time enterprises are emerging forms of agile organizations that can detect delays and respond fast. To meet the challenges met in supporting the emerging real-time enterprises, in this work, multiple complementary hypermedia services are developed in a cooperative hypermedia environment to support distributed project teams to create and modify a project plan cooperatively, to carry out the plan, and, more importantly, to monitor, analysis and adapt to changes in real time.
Theory Refinement of Bayesian Networks with Hidden Variables
Authors: Sowmya Ramachandran
Venue:  (1998)

Research in theory refinement has shown that biasing a learner with initial, approximately correct knowledge produces more accurate results than learning from data alone. While techniques have been developed to revise logical and connectionist representations, little has been done to revise probabilistic representations. Bayesian networks are well-established as a sound formalism for representing and reasoning with probabilistic knowledge, and are widely used. There has been a growing interest in the problem of learning Bayesian networks from data. However, there is no existing technique for learning or revising Bayesian networks with hidden variables (i.e. variables not represented in the data), that has been shown to be efficient, effective, and scalable through evaluation on real data. The few techniques that exist for revising such networks perform a blind search through a large space of revisions, and are therefore computationally expensive. This dissertation presents Banner, a technique for using data to revise a given Bayesian network with Noisy-Or and Noisy-And nodes, to improve its classification accuracy. Additionally, the initial network can be derived directly from a logical theory expressed as propositional Horn-clause rules. Banner can revise networks with hidden variables, and add hidden variables when necessary. Unlike previous approaches to this problem, Banner employs mechanisms similar to those used in logical theory refinement techniques for using the data to focus the search for effective modifications to the network. It can also be used to learn networks with hidden variables from data alone. We also introduce Banner-Pr, a technique for revising the parameters of a Bayesian network with Noisy-Or/And nodes, that directly exploits the computational efficiency afforded by these models. Experiments on several real-world learning problems in domains such as molecular biology and intelligent tutoring systems demonstrate that Banner can effectively and efficiently revise networks to significantly improve their accuracies, and thus learn highly accurate classifiers. Comparisons with the Naive Bayes algorithm show that using the theory refinement approach gives Banner a substantial edge over learning from data alone. We also show that Banner-Pr converges faster and produces more accurate classifiers than an existing algorithm for learning the parameters of a network.
A Model for Coordinating Interacting Agents
Authors: Paul Lalonde, Robert Walker, Jason Harrison, David Forsey
Venue:  (1993)

SPAM (Simulated Platform for Animating Motion) is a simulation software system designed to address synchronization issues pertaining to both animation and simulation. SPAM provides application programs with the manipulation, configuration, and synchronization tools needed when simulations are combined to create animations. It is designed to be used as the glue between applications that supply lists of the parameters to animate and the callback procedures to invoke when a user wishes to modify the parameters directly. SPAM does not impose a particular model of simulation, accommodating keyframing, physical simulation, or a variety of other models, providing they can be abstracted into a set of externally modifiable values. In SPAM we recognize that the important part of simulation is not the state of the system at each time step, but rather the change in states between steps. Thus SPAM uses an interval representation of time, explicitly representing the intervals over which change occurs. In a complex animation or simulation, multiple actions will access the same resource at the same time. SPAM defines a strategy for recognizing such conflicts that increases the use and re-use of sequences.
Evolving analog circuits by variable length chromosomes
Authors: Shin Ando, Mitsuru Ishizuka, Hitoshi Iba
Venue: Advances in evolutionary computing: theory and applications (2003)

This chapter proposes a framework of evolutionary analog circuits. This system features robustness to noise, optimized scaling, and high efficiency. These features solve the problems of the analog circuit design and manufacture. Methods utilized by this system are list-based chromosome, adjusted fitness, and two-stage evolution. Several experiments are conducted to examine the effectiveness of each of the methods. The first experiment compares other types of chromosome for the analog circuit design. The second experiment examines the robustness of evolutionary analog circuits. The other experiments are on the deduction of scaling and two-stage evolution.
Leaders Election Without a Conflict Resolution Rule - Fast and Efficient Randomized Simulations among CRCW PRAMs
Authors: Joseph Gil, Yossi Matias
Venue:  (1991)

We study the question of fast leaders election on TOLERANT, a CRCW PRAM model which tolerates concurrent write but does not support symmetry breaking. We give a randomized simulation of MAXIMUM (a very strong CRCW PRAM) on TOLERANT. The simulation is optimal, reliable, and runs in nearly doubly logarithmic time and linear space. This is the first simulation which is fast, optimal {\it and} space-efficient, and therefore grants true comparison of algorithms running on different CRCW PRAMs. Moreover, it implies that the memory to which concurrent read or concurrent write are assumed should {\it never} be more than linear-the rest of the memory can always be addressed under the EREW convention. The techniques presented in this paper tackle fundamental difficulties in the design of fast parallel algorithms.
0-1 LAWS FOR FRAGMENTS OF SECOND-ORDER LOGIC: AN OVERVIEW
Authors: Phokion G. Kolaitis, Moshe Y. Vardi
Venue:  (1990)

The probability of a property on the collection of all finite relational structures is the limit as n --< infinity of the fraction of structures with n elements satisfying the property, provided the limit exists. It is known that the 0-1 law holds for any property expressible in first-order logic, i.e., the probability of any such property exists and is either 0 or 1. Moreover, the associated decision problem for the probabilities is solvable. We investigate here fragments of existential second-order logic in which we restrict the patterns of first-order quantifiers. We focus on fragments in which the first-order part belongs to a prefix class. We show that the classifications of prefix classes of first-order logic with equality according to the solvability of the finite satisfiability problem and according to the 0-1 law for the corresponding Sigma_1^1 fragment are identical.
Upper Bounds for Sorting Integers on Random Access Machines
Authors: David G. Kirkpatrick, Stefan Reisch
Venue:  (1981)

Two models of Random Access Machines suitable for sorting integers are presented. Our main results show that i) a RAM with addition, subtraction, multiplication, and integer division can sort $n$ integers in the range $[0,2^{cn}]$ in $O(n \log c + n)$ steps; ii) a RAM with addition, subtraction, and left and right shifts can sort any $n$ integers in linear time; iii) a RAM with addition, subtraction, and left and right shifts can sort $n$ integers in the range $[0,n^{C}]$ in $O(n \log c + n)$ steps, where all intermediate results are bounded in value by the largest input.
A Homotopy Algorithm for the Combined H-squared/H-to Infinity Model Reduction Problem
Authors: Yuzhen Ge, Emmanuel G. Collins, Layne T. Watson, Dennis S. Bernstein
Venue:  (1993)

The problem of finding a reduced order model, optimal in the H-squared sense, to a given system model is a fundamental one in control system analysis and design. The addition of a H-to infinity constraint to the H-squared optimal model reduction problem results in a more practical yet computationally more difficult problem. Without the global convergence of probability-one homotopy methods the combined H-squared/H-to infinity model reduction problem is difficult to solve. Several approaches based on homotoppy methods have been proposed. The issues are the number of degrees of freedom, the well posedness of the finite dimensional optimization problem, and the numerical robustness of the resulting homotopy algorithm. Homotopy algorithms based on two formulations - input normal form; Ly, Bryson, and Cannon''s 2 x 2 block parametrization - are developed and compared here.
Systematic Segmentation of Mammograms
Authors: Ramachandran Chandrasekhar
Venue:  (1996)

Mammograms are at present the method of choice for screening the asymptomatic female population above fifty years for breast cancer. One way of assisting radiologists to cope with the increased workload from screening is to ``pre-read'''' or process mammograms ``intelligently'''' by computer. This thesis addresses the fundamental question of segmenting mammograms as the first stage of this processing. It presents systematic methods for : 1. obtaining the skin-air interface, separating breast from background; 2. locating the nipple; 3. delineating the pectoral muscle; and 4. identifying the adipose and fibroglandular tissue on mammograms. These steps represent a logical progression in the segmentation process. In each case, the methods developed recommend themselves on the basis of their simplicity, accuracy, generality or novelty. The separation of breast from background was accomplished by modelling the entire background, and portions of the breast contiguous with it, by a polynomial. The modelled image was subtracted from the original and further processed to yield a binary image of the breast and the background. An original, heuristic technique was developed to locate the nipple automatically on mammograms for which the skin-air interface had already been obtained. It was observed that at the nipple, there is a distinct change in the average gradient of the intensity in a direction normal to the skin-air interface, directed towards the breast. The value of the gradient and its orientation, along with the derivative of each with the vertical co-ordinate, yielded four descriptors that were sufficiently sensitive to locate the nipple, both when it was in profile and when it was not. Edge detection was considered most suitable for delineating the pectoral muscle. A careful analysis of mask-based edge detection revealed it to be the composition of four mathematical operations: conditioning, feature extraction, blending and scaling. Interesting insights were obtained about the feature extraction and blending steps. It was found that statistical measures such as the range and standard deviation of pixel values within a mask could serve as components of the edge feature vector just as well as conventional directed digital gradients. The function used to blend the components of the feature vectors could be defined analytically or computationally. This was particularly useful for mammograms where a single anatomical edge, like that of the pectoral muscle, could vary in strength across its length. By establishing a framework within which a variety of edge images could be systematically generated, this work has relevance beyond the application domain for which it was developed. Texture analysis was deemed appropriate to distinguish the fatty and fibroglandular components of the region within the breast. To this end, a new texture measure, the two-dimensional Hurst operator, was defined. It is a logical mathematical extension of a statistic
A Note on Graded Modal Logic
Authors: M. de Rijke
Venue:  (1996)

We introduce a notion of bisimulation for graded modal logic. Using these bisimulations the model theory of graded modal logic can be developed in a uniform manner. We illustrate this by establishing the finite model property, and proving invariance and definability results. 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
Dissipative Waves in Fluids Having Both Positive and Negative Nonlinearity
Authors: Mark S. Cramer, A. Kluwick, Layne T. Watson, Wolfgang Pelz
Venue:  (1986)

The present study examines weakly dissipative, weakly nonlinear waves in which the fundamental derivative changes sign. The undisturbed state is taken to be at rest, uniform and in the vicinity of the 0 locus. The cubic Burgers equation governing these waves is solved numerically; the resultant solutions are compared and contrasted to those of the invisced theory. Further results include the presentation of a natural scaling law and inviscid solutions not reported elsewhere.
A Logic-Based Analysis of Dempster Shafer Theory
Authors: Gregory M. Provan
Venue:  (1989)

We formulate Dempster Shafer Theory in terms of Propositional Logic, using the implicit notion of probability underlying Dempster Shafer Theory. Dempster Shafer theory can be modeled in terms of propositional logic by the tuple $(\Sigma , \varrho )$, where $\Sigma $ is a set of propositional clauses and $\varrho $ is an assignment of measure to each clause $\Sigma_i \in \Sigma $. We show that the disjunction of minimal support clauses for a clause $i$ with respect to a set $\Sigma $ of propositional clauses, $ \xi ( \Sigma_{i}, \Sigma )$, is a symbolic representation of the Dempster Shafer Belief function for $\Sigma_{i}$. The combination of Belief functions using Dempster''s Rule of Combination corresponds to a combination of the corresponding support clauses. The disjointness of the Boolean formulae representing DS Belief functions is shown to be necessary. Methods of computing disjoint formulae using Network Reliability techniques are discussed. \n In addition, we explore the computational complexity of deriving Dempster Shafer Belief functions, including that of the logic-based methods which are the focus of this paper. Because of Intractability even for moderately-sized problem instances, we propose the use of effluent approximation methods for such computations. Finally, we examine implementations of Dempster Shafer theory, based on domain restrictions of DS theory, hypertree embeddings, and the ATMS.