A Golden Age of Hardware Description Languages: Applying Programming Language Techniques to Improve Design Productivity

Leading experts have declared that there is an impending golden age of computer architecture. During this age, the rate at which architects will be able to innovate will be directly tied to the design and implementation of the hardware description languages they use. Thus, the programming languages community stands on the critical path to this new golden age. This implies that we are also on the cusp of a golden age of hardware description languages. In this paper, we discuss the intellectual challenges facing researchers interested in hardware description language design, compilers, and formal methods. The major theme will be identifying opportunities to apply programming language techniques to address issues in hardware design productivity. Then, we present a vision for a multi-language system that provides a framework for developing solutions to these intellectual problems. This vision is based on a meta-programmed host language combined with a core embedded hardware description language that is used as the basis for the research and development of a sea of domain-specific languages. Central to the design of this system is the core language which is based on an abstraction that provides a general mechanism for the composition of hardware components described in any language

Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed

The implementation of a competency based assessment system for applicants for a restrictive licence for cadastral surveying

The Surveyors Board of Queensland has the responsibility for assessing the standards and regulating cadastral surveyors within the state. Recent legislative changes have required the Board to implement a competency based assessment scheme. This paper summarises the legislative framework and the theory of competency based assessment. It goes on to describe the development of competency standards for surveyors and the implementation of an assessment scheme. The move to a competency based assessment system was a substantial task undertaken by the Board and the paper discusses some useful lessons that may be learnt by other jurisdictions considering a similar move

The importance of strategic financial leadership in the UK public sector in a time of financial austerity

Given the severity of financial pressures on public authorities, this report is concerned with how finance managers in public services are coping with the demands placed on them and how they can demonstrate improved value by providing more effective strategic financial leadership. It considers how they are applying managerial approaches and solutions to the challenges of austerity and the role that the public sector finance function can play in this process

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as multilinguality, scalability, and issues which are related to diversity and inconsistency in content of different web pages. Due to the wide range of domains and the dynamic environments that the Semantic Annotation systems must be performed on, the problem of automating annotation process is one of the significant challenges in this domain. To overcome this problem, different machine learning approaches such as supervised learning, unsupervised learning and more recent ones like, semi-supervised learning and active learning have been utilized. In this paper we present an inclusive layered classification of Semantic Annotation challenges and discuss the most important issues in this field. Also, we review and analyze machine learning applications for solving semantic annotation problems. For this goal, the article tries to closely study and categorize related researches for better understanding and to reach a framework that can map machine learning techniques into the Semantic Annotation challenges and requirements

Action learning : co-creating value from collaborative sustainable projects

This article reports on the specific role that action learning plays in the promotion of sustainability and innovation in the Local Government sector. The study focuses on one organisation and the efforts of a senior manager to enact change. The senior manager utilized his participation in an MBA programme to bring the classroom learning into his business. As a consequence of the requirements of the programme and also the desire of the senior manager, he was able to instigate a change programme, which delivered measurable outcomes and had financial and cultural impact. This case study illustrates the favourable advantages of using action learning as an intervention approach by HEI’s in driving sustainable innovation in the Local Government sectorFinal Published versio

Analysis of the need for skilled workers in the construction industry

Includes bibliographical references