923 research outputs found
Chu Culture Modeling Elements and Their Inspiration for Urban Visual Image Design
This paper will concentrate on the artifact culture of Hubei, the cradle of Chu culture. It begins with the analysis of visual elements in ancient Chu culture, including the forms, colors, ornamentations, etc. Based on that, it explores the possibility of adopting the essence of visual art in Chu culture into contemporary urban visual design of Hubei province
Safety Model Checking with Complementary Approximations
Formal verification techniques such as model checking, are becoming popular
in hardware design. SAT-based model checking techniques such as IC3/PDR, have
gained a significant success in hardware industry. In this paper, we present a
new framework for SAT-based safety model checking, named Complementary
Approximate Reachability (CAR). CAR is based on standard reachability analysis,
but instead of maintaining a single sequence of reachable- state sets, CAR
maintains two sequences of over- and under- approximate reachable-state sets,
checking safety and unsafety at the same time. To construct the two sequences,
CAR uses standard Boolean-reasoning algorithms, based on satisfiability
solving, one to find a satisfying cube of a satisfiable Boolean formula, and
one to provide a minimal unsatisfiable core of an unsatisfiable Boolean
formula. We applied CAR to 548 hardware model-checking instances, and compared
its performance with IC3/PDR. Our results show that CAR is able to solve 42
instances that cannot be solved by IC3/PDR. When evaluated against a portfolio
that includes IC3/PDR and other approaches, CAR is able to solve 21 instances
that the other approaches cannot solve. We conclude that CAR should be
considered as a valuable member of any algorithmic portfolio for safety model
checking
PROTS-RF: A Robust Model for Predicting Mutation-Induced Protein Stability Changes
The ability to improve protein thermostability via protein engineering is of great scientific interest and also has significant practical value. In this report we present PROTS-RF, a robust model based on the Random Forest algorithm capable of predicting thermostability changes induced by not only single-, but also double- or multiple-point mutations. The model is built using 41 features including evolutionary information, secondary structure, solvent accessibility and a set of fragment-based features. It achieves accuracies of 0.799,0.782, 0.787, and areas under receiver operating characteristic (ROC) curves of 0.873, 0.868 and 0.862 for single-, double- and multiple- point mutation datasets, respectively. Contrary to previous suggestions, our results clearly demonstrate that a robust predictive model trained for predicting single point mutation induced thermostability changes can be capable of predicting double and multiple point mutations. It also shows high levels of robustness in the tests using hypothetical reverse mutations. We demonstrate that testing datasets created based on physical principles can be highly useful for testing the robustness of predictive models
LTLf satisfiability checking
We consider here Linear Temporal Logic (LTL) formulas interpreted over
\emph{finite} traces. We denote this logic by LTLf. The existing approach for
LTLf satisfiability checking is based on a reduction to standard LTL
satisfiability checking. We describe here a novel direct approach to LTLf
satisfiability checking, where we take advantage of the difference in the
semantics between LTL and LTLf. While LTL satisfiability checking requires
finding a \emph{fair cycle} in an appropriate transition system, here we need
to search only for a finite trace. This enables us to introduce specialized
heuristics, where we also exploit recent progress in Boolean SAT solving. We
have implemented our approach in a prototype tool and experiments show that our
approach outperforms existing approaches
Fast LTL Satisfiability Checking by SAT Solvers
Satisfiability checking for Linear Temporal Logic (LTL) is a fundamental step
in checking for possible errors in LTL assertions. Extant LTL satisfiability
checkers use a variety of different search procedures. With the sole exception
of LTL satisfiability checking based on bounded model checking, which does not
provide a complete decision procedure, LTL satisfiability checkers have not
taken advantage of the remarkable progress over the past 20 years in Boolean
satisfiability solving. In this paper, we propose a new LTL
satisfiability-checking framework that is accelerated using a Boolean SAT
solver. Our approach is based on the variant of the \emph{obligation-set
method}, which we proposed in earlier work. We describe here heuristics that
allow the use of a Boolean SAT solver to analyze the obligations for a given
LTL formula. The experimental evaluation indicates that the new approach
provides a a significant performance advantage
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