694287
Automatic trace analysis for logic of constraints
Verification of system designs continues to be a major challenge today. Simulation remains the primary tool for making sure that implementations perform as they should. We present algorithms to automatically generate trace checkers from formulas written in the formal quantitative constraint language, Logic Of Constraints (LOC), to analyze the simulation traces for functional and performance constraint violations. For many interesting formulas, the checkers exhibit linear time complexity and constant memory usage. We illustrate the usefulness and efficiency of this approach with large designs and traces.
1385145
Simulation based deadlock analysis for system level designs
In the design of highly complex, heterogeneous, and concurrent systems, deadlock detection and resolution remains an important issue. In this paper, we systematically analyze the synchronization dependencies in concurrent systems modeled in the Metropolis design environment, where system functions, high level architectures and function-architecture mappings can be modeled and simulated. We propose a data structure called the dynamic synchronization dependency graph, which captures the runtime (blocking) dependencies. A loop-detection algorithm is then used to detect deadlocks and help designers quickly isolate and identify modeling errors that cause the deadlock problems. We demonstrate our approach through a real world design example, which is a complex functional model for video processing and a high level model of function-architecture mapping.
1333400
Utilizing formal assertions for system design of network processors
System level modeling with executable languages such as C/C++ has been crucial in the development of large electronic systems from general processors to application specific designs. To make sure that the executable models behave as they should, the designers often have to "eye-ball" the simulation traces and at best, apply simple "assert" statements or write simple trace checkers in some scripting languages. The problem is the lack of a concise and formal method to specify and check desired properties, whether they be functional or performance in nature. In this paper, we apply assertion checking methodology to the system design of network processors. Functional and performance assertions, based on linear temporal logic and logic of constraints, are written during the design process. Trace checkers and simulation monitors are automatically generated to validate particular simulation runs or to analyze their performance characteristics. Several categories of assertions are checked throughout the design process, such as equivalence, functionality, transaction, and performance. We demonstrate that the assertion-based methodology is very useful for both system level verification and design exploration.
2109758
Case studies of model checking for embedded system designs
As modern embedded systems become more integrated and complex, it is crucial to be able to represent systems at multiple levels of abstraction, so that the design space can be effectively explored by successive refinements and abstractions. We present a formal verification methodology and case studies for property verification of designs represented at different abstraction levels. Utilizing Metropolis meta-model (MMM), Y-chart Application Programmer's Interface (YAPI), an automatic translator, and the model checker SPIN, we verify properties for both system level representations and refined representations.
11415872
On the largest eigenvalues of trees
An upper bound for the largest eigenvalues of all but a few families of trees is given in this paper. This upper bound depends only on the vertex number of trees under consideration.
62212743
Resampling for face detection by self-adaptive genetic algorithm
Over the past ten years, face detection has been thoroughly studied in computer vision research for its interesting applications. However, all of the state-of-the-art statistical methods suffer from the data collection for training a classifier. This paper presents a self-adaptive genetic algorithm (GA)-based method to swell face database through re-sampling from the existing faces. The basic idea is that a face is composed of a limited components set, and the GA can simulate the procedure of heredity. This simulation can also cover the variations of faces in different lighting conditions, poses, accessories, and quality conditions. To verify the generalization capability of the proposed method, we also use the expanded database to train an Adaboost-based face detector and test it on the MIT+CMU frontal face test set. The experimental results show that the data collection can be efficiently speeded up by the proposed methods.
3822993
Learning by Examples: Identifying Key Concepts from Text Using Pre-Defined Inputs
761547
Finite Element Surface Fitting for Bridge Management
We propose a new finite element surface fitting method which can handle very large databases. This method uses finite element discretization to find an approximation of a smooth function which minimizes a sum of data residuals and second derivatives under some constraints on data. The finite element discretization derives a large scale constrained quadratic program, which can be reformulated as a system of piecewise linear equations. We develop a preconditioned Newton method to solve the system efficiently. We apply this method to form surfaces over Aomori Region in Japan by geographic databases, such that every bridge became associated with environmental information.
62599943
Finding nuggets in documents: A machine learning approach
Document keyphrases provide a concise summary of a document's content, offering semantic metadata summarizing a document. They can be used in many applications related to knowledge management and text mining, such as automatic text summarization, development of search engines, document clustering, document classification, thesaurus construction, and browsing interfaces. Because only a small portion of documents have keyphrases assigned by authors, and it is time-consuming and costly to manually assign keyphrases to documents, it is necessary to develop an algorithm to automatically generate keyphrases for documents. This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified phrases to assign weights to the candidate keyphrases. The logic of our algorithm is: The more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. KIP's learning function can enrich the glossary database by automatically adding new identified keyphrases to the database. KIP's personalization feature will let the user build a glossary database specifically suitable for the area of hissher interest. The evaluation results show that KIP's performance is better than the systems we compared to and that the learning function is effective. © 2006 Wiley Periodicals, Inc.