Formal verification of ASM designs using the MDG tool

In this paper, we present a formal hardware verification framework linking ASM with MDG. ASM (Abstract State Machine) is a state based language for describing transition systems. MDG (Multiway Decision Graphs) provides symbolic representation of transition systems with support of abstract sorts and functions. We implemented a transformation tool that automatically generates MDG models from ASM specifications, then formal verification techniques provided by the MDG tool, such as model checking or equivalence checking, can be applied on the generated models. We support this work with a case study of an Island Tunnel Controller, which behavior and structure were specified in ASM then using our ASM-MDG tool successfully verified within the MDG tool.

Compositional verification for object-Z

This paper presents a framework for compositional verification of Object-Z specifications. Its key feature is a proof rule based on decomposition of hierarchical Object-Z models. For each component in the hierarchy local properties are proven in a single proof step. However, we do not consider components in isolation. Instead, components are envisaged in the context of the referencing super-component and proof steps involve assumptions on properties of the sub-components. The framework is defined for Linear Temporal Logic (LTL)

Off-line signature verification and forgery detection system based on fuzzy modeling

This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.

Verification of floating point programs

In this thesis we present an approach to automated verification of floating point programs. Existing techniques for automated generation of correctness theorems are extended to produce proof obligations for accuracy guarantees and absence of floating point exceptions. A prototype automated real number theorem prover is presented, demonstrating a novel application of function interval arithmetic in the context of subdivision-based numerical theorem proving. The prototype is tested on correctness theorems for two simple yet nontrivial programs, proving exception freedom and tight accuracy guarantees automatically. The prover demonstrates a novel application of function interval arithmetic in the context of subdivision-based numerical theorem proving. The experiments show how function intervals can be used to combat the information loss problems that limit the applicability of traditional interval arithmetic in the context of hard real number theorem proving.

Cascaded Bayesian processes: an account of bias in orientation perception

Following adaptation to an oriented (1-d) signal in central vision, the orientation of subsequently viewed test signals may appear repelled away from or attracted towards the adapting orientation. Small angular differences between the adaptor and test yield 'repulsive' shifts, while large angular differences yield 'attractive' shifts. In peripheral vision, however, both small and large angular differences yield repulsive shifts. To account for these tilt after-effects (TAEs), a cascaded model of orientation estimation that is optimized using hierarchical Bayesian methods is proposed. The model accounts for orientation bias through adaptation-induced losses in information that arise because of signal uncertainties and neural constraints placed upon the propagation of visual information. Repulsive (direct) TAEs arise at early stages of visual processing from adaptation of orientation-selective units with peak sensitivity at the orientation of the adaptor (theta). Attractive (indirect) TAEs result from adaptation of second-stage units with peak sensitivity at theta and theta+90 degrees , which arise from an efficient stage of linear compression that pools across the responses of the first-stage orientation-selective units. A spatial orientation vector is estimated from the transformed oriented unit responses. The change from attractive to repulsive TAEs in peripheral vision can be explained by the differing harmonic biases resulting from constraints on signal power (in central vision) versus signal uncertainties in orientation (in peripheral vision). The proposed model is consistent with recent work by computational neuroscientists in supposing that visual bias reflects the adjustment of a rational system in the light of uncertain signals and system constraints.

A formal methodology for the verification of concurrent systems

There is an increasing emphasis on the use of software to control safety critical plants for a wide area of applications. The importance of ensuring the correct operation of such potentially hazardous systems points to an emphasis on the verification of the system relative to a suitably secure specification. However, the process of verification is often made more complex by the concurrency and real-time considerations which are inherent in many applications. A response to this is the use of formal methods for the specification and verification of safety critical control systems. These provide a mathematical representation of a system which permits reasoning about its properties. This thesis investigates the use of the formal method Communicating Sequential Processes (CSP) for the verification of a safety critical control application. CSP is a discrete event based process algebra which has a compositional axiomatic semantics that supports verification by formal proof. The application is an industrial case study which concerns the concurrent control of a real-time high speed mechanism. It is seen from the case study that the axiomatic verification method employed is complex. It requires the user to have a relatively comprehensive understanding of the nature of the proof system and the application. By making a series of observations the thesis notes that CSP possesses the scope to support a more procedural approach to verification in the form of testing. This thesis investigates the technique of testing and proposes the method of Ideal Test Sets. By exploiting the underlying structure of the CSP semantic model it is shown that for certain processes and specifications the obligation of verification can be reduced to that of testing the specification over a finite subset of the behaviours of the process.

A new randomization assay reveals Unexpected elements of sequence bias in model 'randomized' gene libraries:Implications for biopanning

Although techniques such as biopanning rely heavily upon the screening of randomized gene libraries, there is surprisingly little information available on the construction of those libraries. In general, it is based on the cloning of 'randomized' synthetic oligonucleotides, in which given position(s) contain an equal mixture of all four bases. Yet, many supposedly 'randomized' libraries contain significant elements of bias and/or omission. Here, we report the development and validation of a new, PCR-based assay that enables rapid examination of library composition both prior to and after cloning. By using our assay to analyse model libraries, we demonstrate that the cloning of a given distribution of sequences does not necessarily result in a similarly composed library of clones. Thus, while bias in randomized synthetic oligonucleotide mixtures can be virtually eliminated by using unequal ratios of the four phosphoramidites, the use of such mixtures does not ensure retrieval of a truly randomized library. We propose that in the absence of a technique to control cloning frequencies, the ability to analyse the composition of libraries after cloning will enhance significantly the quality of information derived from those libraries. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

Optic flow in human vision: MEG reveals a foveo-fugal bias in V1, specialization for spiral space in hMSTs, and global motion sensitivity in the IPS

Abstract We recorded MEG responses from 17 participants viewing random-dot patterns simulating global optic flow components (expansion, contraction, rotation, deformation, and translation) and a random motion control condition. Theta-band (3–7 Hz), MEG signal power was greater for expansion than the other optic flow components in a region concentrated along the calcarine sulcus, indicating an ecologically valid, foveo-fugal bias for unidirectional motion sensors in V1. When the responses to the optic flow components were combined, a decrease in MEG beta-band (17–23 Hz) power was found in regions extending beyond the calcarine sulcus to the posterior parietal lobe (inferior to IPS), indicating the importance of structured motion in this region. However, only one cortical area, within or near the V5/hMT+ complex, responded to all three spiral-space components (expansion, contraction, and rotation) and showed no selectivity for global translation or deformation: we term this area hMSTs. This is the first demonstration of an exclusive region for spiral space in the human brain and suggests a functional role better suited to preliminary analysis of ego-motion than surface pose, which would involve deformation. We also observed that the rotation condition activated the cerebellum, suggesting its involvement in visually mediated control of postural adjustment.

Morphology in autism spectrum disorders:local processing bias and language

We conducted a detailed study of a case of linguistic talent in the context of autism spectrum disorder, specifically Asperger syndrome. I.A. displays language strengths at the level of morphology and syntax. Yet, despite this grammar advantage, processing of figurative language and inferencing based on context presents a problem for him. The morphology advantage for I.A. is consistent with the weak central coherence (WCC) account of autism. From this account, the presence of a local processing bias is evident in the ways in which autistic individuals solve common problems, such as assessing similarities between objects and finding common patterns, and may therefore provide an advantage in some cognitive tasks compared to typical individuals. We extend the WCC account to language and provide evidence for a connection between the local processing bias and the acquisition of morphology and grammar.