Arcot Sowmya

Bridge over troubled wrappers:automated interface synthesis

System-on-Chip (SoC) design methodologies rely heavily on reuse of intellectual property (IP) blocks. IP reuse is a labour intensive and time consuming process as IP blocks often have different communication interfaces. We present an algorithm which automates the generation of provably correct HDL descriptions of interfaces between mismatched IP communication protocols. We significantly improve and extend existing work by providing a solution which addresses data mismatches, pipelining and differences in clock speeds. These ideas have been implemented and the tool has been used to synthesise wrappers and bridges for many SoC protocols.

Extending statecharts with temporal logic

The task of designing large real-time reactive systems, which interact continuously with their environment and exhibit concurrency properties, is a challenging one. The authors explore the utility of a combination of behavior and function specification languages in specifying such systems and verifying their properties. An existing specification language, statecharts, is used to specify the behavior of real-time reactive systems, while a new logic-based language called FNLOG (based on first-order predicate calculus and temporal logic) is designed to express the system functions over real time. Two types of system properties, intrinsic and structural, are proposed. It is shown that both types of system properties are expressible in FNLOG and may be verified by logical deduction, and also hold for the corresponding behavior specification.

Modelling and representation issues in automated feature extraction from aerial and satellite images

New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.

Synchronous protocol automata: a framework for modelling and verification of SoC communication architectures

Plug-n-Play style Intellectual Property (IP) reuse in System on Chip (SoC) design is facilitated by the use of an on-chip bus architecture. We present a synchronous, Finite State Machine based framework for modelling communication aspects of such architectures. This formalism has been developed via interaction with designers and the industry and is intuitive and lightweight. We have developed cycle accurate methods to formally specify protocol compatibility and component composition and show how our model can be used for compatibility verification, interface synthesis and model checking with automated specification. We demonstrate the utility of our framework by modelling the AMBA bus architecture including details such as pipelined operation, burst and split transfers, the AHB-APB bridge and arbitration features.

An Underwater Color Image Quality Evaluation Metric

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

Multi-level classification of emphysema in HRCT lung images

Emphysema is a common chronic respiratory disorder characterised by the destruction of lung tissue. It is a progressive disease where the early stages are characterised by a diffuse appearance of small air spaces, and later stages exhibit large air spaces called bullae. A bullous region is a sharply demarcated region of emphysema. In this paper, it is shown that an automated texture-based system based on co-training is capable of achieving multiple levels of emphysema extraction in high-resolution computed tomography (HRCT) images. Co-training is a semi-supervised technique used to improve classifiers that are trained with very few labelled examples using a large pool of unseen examples over two disjoint feature sets called views. It is also shown that examples labelled by experts can be incorporated within the system in an incremental manner. The results are also compared against “density mask”, currently a standard approach used for emphysema detection in medical image analysis and other computerized techniques used for classification of emphysema in the literature. The new system can classify diffuse regions of emphysema starting from a bullous setting. The classifiers built at different iterations also appear to show an interesting correlation with different levels of emphysema, which deserves more exploration.

The anisotropic Gaussian kernel for SVM classification of HRCT images of the lung

High-resolution computed tomography (HRCT) produces lung images with a high level of detail which makes it suitable for diagnosis of diffuse lung diseases. Segmentation of abnormal lung patterns is a necessary stage in the construction of a computer-aided diagnosis system. We interpret lung patterns as textures and develop a texture classification technique for segmentation of lung patterns. The wavelet transform is used to extract texture features and then the support vector machines (SVM) machine learning algorithm is applied to texture classification. The parameters of the SVM play a crucial role in the performance of the algorithm. We apply gradient-based optimization of the radius/margin bound of a generalization error to tune parameters of the SVM algorithm. We compare the performance of isotropic and anisotropic Gaussian kernels and study the applicability of the radius/margin bound to tuning parameters of the SVM algorithm on the problem of lung pattern classification.

Forecasting the onset of genocide and politicide: Annual out-of-sample forecasts on a global dataset, 1988–2003

We present what is, to the best of our knowledge, the first published set of annual out-of-sample forecasts of genocide and politicide based on a global dataset. Our goal is to produce a prototype for a real-time model capable of forecasting one year into the future. Building on the current literature, we take several important steps forward. We implement an unconditional two-stage model encompassing both instability and genocide, allowing our sample to be the available global data, rather than using conditional case selection or a case-control approach. We explore factors exhibiting considerable variance over time to improve yearly forecasting performance. And we produce annual lists of at-risk states in a format that should be of use to policymakers seeking to prevent such mass atrocities. Our out-of-sample forecasts for 1988–2003 predict 90.9% of genocide onsets correctly while also predicting 79.2% of non-onset years correctly, an improvement over a previous study using a case-control in-sample approach. We produce 16 annual forecasts based only on previous years’ data, which identify six of 11 cases of genocide/politicide onset within the top 5% of at-risk countries per year. We believe this represents substantial progress towards useful real-time forecasting of such rare events. We conclude by suggesting ways to further enhance predictive performance.

A formal approach to the protocol converter problem

In the absence of a single module interface standard, integration of pre-designed modules in System-on-Chip design often requires the use of protocol converters. Existing approaches to automatic synthesis of protocol converters mostly lack formal foundations and either employ abstractions that ignore crucial low level behaviors, or grossly simplify the structure of the protocols considered. We present a state-machine based formal model for bus based communication protocols, and precisely define protocol compatibility, and correct protocol conversion. Our model is expressive enough to capture features of commercial protocols such as bursts, pipelined transfers, wait state insertion, and data persistence, in cycle accurate detail. We show that the most general, correct converter for a pair of protocols, can be described as the greatest fixed point of a function for updating buffer states. This characterization yields a natural algorithm for automatic synthesis of a provably correct converter by iterative computation of the fixed point. We report our experience with automatic converter synthesis between widely used commercial bus protocols, such as AMBA AHB, ASB, APB, and OCP, considering features which are beyond the scope of current techniques.

Provably correct on-chip communication: A formal approach to automatic protocol converter synthesis

Hardware module reuse is a standard solution to the problems of increasing complexity of chip architectures and pressure to reduce time to market. In the absence of a single module interface standard, predesigned modules for “plug-and-play” usually require a converter between incompatible interface protocols. Current approaches to automatic synthesis of protocol converters mostly lack formal foundations and either employ abstractions far removed from the HDL implementation level or grossly simplify the structure of the protocols considered. This work presents a state-machine-based formalism for modeling bus-based communication protocols and a notion of protocol compatibility and of correct conversion between incompatible protocols. This formalism is used to derive algorithms for checking protocol compatibility and for provably correct, automatic converter synthesis. Experiments with automatic converter synthesis between different configurations of widely used commercial bus protocols, such as AMBA AHB, ASB APB, and the Open Core Protocol (OCP) are discussed. The work here is unique in its combination of a completely formal approach and the use of a low abstraction level that enables precise modeling of protocol characteristics that is also close to HDL.