This paper describes the principles underlying an efficient implementation of a lazy functional language, compiling to code for ordinary computers. It is based on combinator-like graph reduction: the user defined func...
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This paper describes the principles underlying an efficient implementation of a lazy functional language, compiling to code for ordinary computers. It is based on combinator-like graph reduction: the user defined functions are used as rewrite rules in the graph. Each function is compiled into an instruction sequence for an abstract graph reduction machine, called the G-machine, the code reduces a function application graph to its value. The G-machine instructions are then translated into target code. Speed improvements by almost two orders of magnitude over previous lazy evaluators have been measured;we provide some performance figures.
作者：
NANCY MERRITTTERRY FAINSUSAN TURNERExtensive experience conducting justice system policy studies at the state and local level. As a Policy Analyst with the RAND Corporation and government agencies
she designed and directed studies focused on the development implementation and evaluation of sentencing policy as well as juvenile and adult correctional programs. Her current work focuses on the implementation and impact of mandatory sentencing laws cross-jurisdictional variations in their application and the effects of prosecutorial discretion. Additional areas of interest include the development implementation and evaluation of juvenile justice programming. Ms. Merritt received her M.S. from the Pennsylvania State University University Park and is a Ph.D. candidate with the Rutgers University School of Criminal Justice. M.A.
M.S. is a Senior project associate in the Behavioral Sciences Department at RAND Corporation. He has extensive research experience in criminal justice and substance abuse. He is expert in computer statistical techniques as well as in managing large datasets. He has conducted analysis for many RAND projects and is author or co-author of numerous publications both from RAND and in peer-reviewed journals. His research interests include alternatives to incarceration substance abuse and treatment racial disparities in prison admissions and research collaborations with state and local justice agencies. Professor in the Department of Criminology
Law and Society at the University of California's Irvine campus. She received her Ph.D. in Social Psychology from the University of North Carolina at Chapel Hill. She has led a variety of research projects including studies on racial disparity field experiments of private sector alternatives for serious juvenile offenders work release day fines and a 14–site evaluation of intensive supervision probation. Dr. Turner's areas of expertise include the design and implementation of randomized field experiments and research collaborations with state and local justice agencies. He
Research Summary: Oregon's Measure 11, a mandatory minimum sentencing policy passed in 1994, had fewer negative system impacts than had been anticipated by many state and local criminal justice administrators, due...
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Research Summary: Oregon's Measure 11, a mandatory minimum sentencing policy passed in 1994, had fewer negative system impacts than had been anticipated by many state and local criminal justice administrators, due largely to the fact that prosecutors exercised the discretion provided them under the law to selectively prosecute cases. Consequently, fewer Measure 11-eligible cases were sentenced under the relevant statues than before passage of the measure, and more were sentenced to lesser related offenses. At the same time, incarceration rates and sentence lengths increased for both Measure 11 and lesser related offenses. Trial rates increased for two years after Measure 11 took effect before reverting to previous levels. Policy Implications: The “unintended consequences” that Measure 11 produced should not have been unexpected. Our research indicates that the entire system will quickly adapt to mitigate the more draconian outcomes predicted by those who assume a simplistic implementation, which underscores the importance of understanding system dynamics and inter-relationships before implementing reform, as well as the pitfalls of designing legislation for either symbolic appeal or formal logic rather than for actual effect.
We determine the weakest failure detectors to solve several fundamental problems in distributed message-passing systems, for all environments - i.e., regardless of the number and timing of crashes. The problems that w...
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ISBN:
(纸本)9781581138023
We determine the weakest failure detectors to solve several fundamental problems in distributed message-passing systems, for all environments - i.e., regardless of the number and timing of crashes. The problems that we consider are: implementing an atomic register, solving consensus, solving quittable consensus (a variant of consensus in which processes have the option to decide 'quit' if a failure occurs), and solving non-blocking atomic commit.
Rapid single flux quantum (RSFQ) logic is a digital circuit technology that in recent years has presented itself as an alternative to semiconductors in the application of ultra high speed, very low power applications....
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Rapid single flux quantum (RSFQ) logic is a digital circuit technology that in recent years has presented itself as an alternative to semiconductors in the application of ultra high speed, very low power applications. The optimal timing of digital circuits operating at hundreds of GHz is still a complex problem for both RSFQ and semiconductor technologies. The fact that most RSFQ gates require a clock signal to function makes this even more complex. Various RSFQ timing schemes have been adapted from semiconductor design methodologies, and some have been designed specifically for RSFQ. Currently, synchronous clocking schemes outperform other schemes, but with the scale of RSFQ circuits ever increasing, the proper use of timing schemes are becoming more crucial. This paper describes a new asynchronous self-timing scheme where the details of clock distribution and clocking are built into the logic gates. Tests were done on the newly developed asynchronous logic gates and an asynchronous full adder was implemented and tested
Using Genetic programming difficult optimization problems can be solved, even if the candidate solutions are complex objects. In such cases, it is a costly procedure to correct or replace the invalid individuals that ...
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In this paper we propose a secure autoconfiguration model for Manet. Our design is based in a distributed and self-organization certification service, which provides node identification and authentication for the auto...
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Ubiquitous computing and universal network connectivity have given rise to expectations of building a Digital Society, where many aspects of business and social activities may be accomplished by remote participants. I...
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Ubiquitous computing and universal network connectivity have given rise to expectations of building a Digital Society, where many aspects of business and social activities may be accomplished by remote participants. Intelligent, context-aware, and workflow-centric collaboration is an essential prerequisite to fulfill that expectation. EkSarva is a framework, which enables realization of such collaborations in diverse domains. This is accomplished by identifying the key concepts and their inter-relationships (dubbed the PPP/SST paradigm), which form the foundation of this framework. The key concepts include: (a) Project, (b) Person, (c) Place, (d) Signal, (e) Situation, and (f) Transcript. This paper describes how these concepts collectively can give rise to an intelligent collaboration environment.
Algorithm visualizations graphically illustrate how algorithms work. In prior ethnographic studies of a computer science course in which students were required to construct and present their own algorithm visualizatio...
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Algorithm visualizations graphically illustrate how algorithms work. In prior ethnographic studies of a computer science course in which students were required to construct and present their own algorithm visualizations, we observed that visualizations based on storylines tended to stimulate increased audience interest and involvement. This observation, coupled with the empirical research that substantiates the value of stories as mnemonic devices, raises an interesting research question: Do visualizations with storylines actually help students remember the procedural behavior of an algorithm better than visualizations that do not involve storylines? To investigate this question, we conducted an experimental study that compared the memorability of algorithm descriptions involving differing degrees of spatial and verbal embellishment. The study failed to detect significant differences. We reflect on our lack of significant results, and suggest two alternative paths for future research into the value of story-based algorithm visualization
The paper studies the motion laws influence over the VIPAS1 industrial robot working. The motion differential equations, that govern the motion robot were established. Using them we can study the direct problem for th...
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