Avoiding Latch Formation in Regular Expression Recognizers

Specialized silicon compilers, or module generators, are promising tools for automating the design of custom VLSI chips. In particular, generators for regular language recognizers have many applications. A problem called latch formation that causes regular expression recognizers to be more complex than they would first appear is identified. if recognizers are constructed in the most straightforward way from certain regular expressions, they may contain extraneous latches that cause incorrect operation. After identifying the problem, the article presents a source-to-source transformation that converts regular expressions that cause latch formation into expressions that do not. This transformation allows regular expression recognizers to be simpler, smaller, and faster, thus adding to the advantages of specialized silicon compilers

Modeling Concurrency in Parallel Debugging

We propose a description language, Data Path Expressions (DPEs), for modeling the behavior of parallel programs. We have designed DPEs as a high-level debugging language, where the debugging paradigm is for the programmer to describe the expected program behavior and for the debugger to compare the actual program behavior during execution to detect program errors. We classify DPEs into five subclasses according to syntactic criteria, and characterize their semantics in terms of a hierarchy of extended Petri Net models. The characterization demonstrates the power of DPEs for modeling (true) concurrency. We also present predecessor automata as a mechanism for implementing the third subclass of DPEs, which expresses bounded parallelism. Predecessor automata extend finite state automata to recognize or generate partial ordering graphs as well as strings, and provide efficient event recognizers for parallel debugging. We briefly describe the application of DPEs race conditions, deadlock and starvation

Simulation and Design of Biological and Biologically-Motivated Computing Systems

In life science, there is a great need in understandings of biological systems for therapeutics, synthetic biology, and biomedical applications. However, complex behaviors and dynamics of biological systems are hard to understand and design. In the mean time, the design of traditional computer architectures faces challenges from power consumption, device reliability, and process variations. In recent years, the convergence of computer science, computer engineering and life science has enabled new applications targeting the challenges from both engineering and biological fields. On one hand, computer modeling and simulation provides quantitative analysis and predictions of functions and behaviors of biological systems, and further facilitates the design of synthetic biological systems. On the other hand, bio-inspired devices and systems are designed for real world applications by mimicking biological functions and behaviors. This dissertation develops techniques for modeling and analyzing dynamic behaviors of biologically realistic genetic circuits and brain models and design of brain-inspired computing systems. The stability of genetic memory circuits is studied to understand its functions for its potential applications in synthetic biology. Based on the electrical-equivalent models of biochemical reactions, simulation techniques widely used for electronic systems are applied to provide quantitative analysis capabilities. In particular, system-theoretical techniques are used to study the dynamic behaviors of genetic memory circuits, where the notion of stability boundary is employed to characterize the bistability of such circuits. To facilitate the simulation-based studies of physiological and pathological behaviors in brain disorders, we construct large-scale brain models with detailed cellular mechanisms. By developing dedicated numerical techniques for brain simulation, the simulation speed is greatly improved such that dynamic simulation of large thalamocortical models with more than one million multi-compartment neurons and hundreds of synapses on commodity computer servers becomes feasible. Simulation of such large model produces biologically meaningful results demonstrating the emergence of sigma and delta waves in the early and deep stages of sleep, and suggesting the underlying cellular mechanisms that may be responsible for generation of absence seizure. Brain-inspired computing paradigms may offer promising solutions to many challenges facing the main stream Von Neumann computer architecture. To this end, we develop a biologically inspired learning system amenable to VLSI implementation. The proposed solution consists of a digitized liquid state machine (LSM) and a spike-based learning rule, providing a fully biologically inspired learning paradigm. The key design parameters of this liquid state machine are optimized to maximize the learning performance while considering hardware implementation cost. When applied to speech recognition of isolated word using TI46 speech corpus, the performance of the proposed LSM rivals several existing state-of-art techniques including the Hidden Markov Model based recognizer Sphinx-4

Proceedings of the NASA Conference on Space Telerobotics, volume 1

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty

Moral Agents in a Moral World: A New Account of Moral Realism and Moral Perception

The purpose of this thesis is to provide a metaphysic for moral realism and moral perception. This thesis is in two parts. The first is concerned with basic ontology. I begin in chapter 1 with an analysis of causation, demonstrating that substance theory is superior to Humeanism at accounting for our observations; thus I defend a substance ontology. In chapter 2, I address human agency, demonstrating that reasons internalism does not allow for incompatibilist freedom; hence, I affirm reasons are states of affairs. I move on to qualia in chapter 3, demonstrating that arguments both for and against qualia realism involve question begging. In response, I argue that qualia realism is just as reasonable as anti-realism, and affirm realism. Given this, I address the mind-body problem in chapter 4, demonstrating the failure of physicalists to account for mental causation. I conclude that panpsychism, idealism, and substance dualism are equal reasonable alternatives: each allows for intrinsic properties, which are integral to substance ontology. The second part builds a moral ontology, along with an account of moral perceptual knowledge, compatible with the above basic ontology. In chapter 5, I reject moral properties as monadic since this would bar mapping moral concepts onto mind-independent reality. Instead, I argue that moral properties are relations. More specifically, in chapter 6, I make the case that they are features of relations, relations themselves being the total complex states of affairs between one or more substances. This allows moral properties to have their own nonreducible phenomenal quality. To account for moral normativity, I argue that moral features are actually a class of causal features, and briefly argue that final causes determine the normative causal trajectory of all substances. In chapter 7, I conclude this thesis with addressing possible objections to my theory of perception and perceptual knowledge

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Knowing about Genocide

This book is freely available in an open access edition thanks to TOME (Toward an Open Monograph Ecosystem)—a collaboration of the Association of American Universities, the Association of University Presses, and the Association of Research Libraries—and the generous support of the University of Minnesota. Learn more at the TOME website, available at openmonographs.org. How do victims and perpetrators generate conflicting knowledge about genocide? Using a sociology of knowledge approach, Savelsberg answers this question for the Armenian genocide committed in the context of the First World War. Focusing on Armenians and Turks, he examines strategies of silencing, denial, and acknowledgment in everyday interaction, public rituals, law, and politics. Drawing on interviews, ethnographic accounts, documents, and eyewitness testimony, Savelsberg illuminates the social processes that drive dueling versions of history. He reveals counterproductive consequences of denial in an age of human rights hegemony, with implications for populist disinformation campaigns against overwhelming evidence

Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing