A formal metamodeling approach to a transformation between the UML state machine and object-z

A significant problem with currently suggested approaches for transforming between models in different languages is that the transformation is often described imprecisely, with the result that the overall transformation task may be imprecise, incomplete and inconsistent. This paper presents a formal metamodeling approach for transforming between UML and Object-Z. In the paper, the two languages are defined in terms of their formal metamodels, and a systematic transformation between the models is provided at the meta-level in terms of formal mapping functions. As a consequence, we can provide a precise, consistent and complete transformation between them.

Critical feature analysis of a radiotherapy machine

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An `assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code.

Blood type classification using computer vision and machine learning

In emergency situations, where time for blood transfusion is reduced, the O negative blood type (the universal donor) is administrated. However, sometimes even the universal donor can cause transfusion reactions that can be fatal to the patient. As commercial systems do not allow fast results and are not suitable for emergency situations, this paper presents the steps considered for the development and validation of a prototype, able to determine blood type compatibilities, even in emergency situations. Thus it is possible, using the developed system, to administer a compatible blood type, since the first blood unit transfused. In order to increase the system’s reliability, this prototype uses different approaches to classify blood types, the first of which is based on Decision Trees and the second one based on support vector machines. The features used to evaluate these classifiers are the standard deviation values, histogram, Histogram of Oriented Gradients and fast Fourier transform, computed on different regions of interest. The main characteristics of the presented prototype are small size, lightweight, easy transportation, ease of use, fast results, high reliability and low cost. These features are perfectly suited for emergency scenarios, where the prototype is expected to be used.

Noisy fitness evaluation in genetic algorithms and the dynamics of learning

A theoretical model is presented which describes selection in a genetic algorithm (GA) under a stochastic fitness measure and correctly accounts for finite population effects. Although this model describes a number of selection schemes, we only consider Boltzmann selection in detail here as results for this form of selection are particularly transparent when fitness is corrupted by additive Gaussian noise. Finite population effects are shown to be of fundamental importance in this case, as the noise has no effect in the infinite population limit. In the limit of weak selection we show how the effects of any Gaussian noise can be removed by increasing the population size appropriately. The theory is tested on two closely related problems: the one-max problem corrupted by Gaussian noise and generalization in a perceptron with binary weights. The averaged dynamics can be accurately modelled for both problems using a formalism which describes the dynamics of the GA using methods from statistical mechanics. The second problem is a simple example of a learning problem and by considering this problem we show how the accurate characterization of noise in the fitness evaluation may be relevant in machine learning. The training error (negative fitness) is the number of misclassified training examples in a batch and can be considered as a noisy version of the generalization error if an independent batch is used for each evaluation. The noise is due to the finite batch size and in the limit of large problem size and weak selection we show how the effect of this noise can be removed by increasing the population size. This allows the optimal batch size to be determined, which minimizes computation time as well as the total number of training examples required.

Technology valuation within the context of transfer collaborations with Chinese machine tool companies

The point of departure for this study was a recognition of the differences in suppliers' and acquirers' judgements of the value of technology when transferred between the two, and the significant impacts of technology valuation on the establishment of technology partnerships and effectiveness of technology collaborations. The perceptions, transfer strategies and objectives, perceived benefits and assessed technology contributions as well as associated costs and risks of both suppliers and acquirers were seen to be the core to these differences. This study hypothesised that the capability embodied in technology to yield future returns makes technology valuation distinct from the process of valuing manufacturing products. The study hence has gone beyond the dimensions of cost calculation and price determination that have been discussed in the existing literature, by taking a broader view of how to achieve and share future added value from transferred technology. The core of technology valuation was argued as the evaluation of the 'quality' of the capability (technology) in generating future value and the effectiveness of the transfer arrangement for best use of such a capability. A dynamic approach comprising future value generation and realisation within the context of specific forms of collaboration was therefore adopted. The research investigations focused on the UK and China machine tool industries, where there are many technology transfer activities and the value issue has already been recognised in practice. Data were gathered from three groups: machine tool manufacturing technology suppliers in the UK and acquirers in China, and machine tool users in China. Data collecting methods included questionnaire surveys and case studies within all the three groups. The study has focused on identifying and examining the major factors affecting value as well as their interactive effects on technology valuation from both the supplier's and acquirer's point of view. The survey results showed the perceptions and the assessments of the owner's value and transfer value from the supplier's and acquirer's point of view respectively. Benefits, costs and risks related to the technology transfer were the major factors affecting the value of technology. The impacts of transfer payment on the value of technology by the sharing of financial benefits, costs and risks between partners were assessed. The close relationship between technology valuation and transfer arrangements was established by which technical requirements and strategic implications were considered. The case studies reflected the research propositions and revealed that benefits, costs and risks in the financial, technical and strategic dimensions interacted in the process of technology valuation within the context of technology collaboration. Further to the assessment of factors affecting value, a technology valuation framework was developed which suggests that technology attributes for the enhancement of contributory factors and their contributions to the realisation of transfer objectives need to be measured and compared with the associated costs and risks. The study concluded that technology valuation is a dynamic process including the generation and sharing of future value and the interactions between financial, technical and strategic achievements.

International technology transfer and collaborative new product development:evidence and a case from the machine tool industry

In recent years, it has become increasingly common for companies to improve their competitiveness and find new markets by extending their operations through international new product development collaborations involving technology transfer. Technology development, cost reduction and market penetration are seen as the foci in such collaborative operations with the aim being to improve the competitive position of both partners. In this paper, the case of technology transfer through collaborative new product development in the machine tool sector is used to provide a typical example of such partnerships. The paper outlines the links between the operational aspects of collaborations and their strategic objectives. It is based on empirical data collected from the machine tool industries in the UK and China. The evidence includes longitudinal case studies and questionnaire surveys of machine tool manufacturers in both countries. The specific case of BSA Tools Ltd and its Chinese partner the Changcheng Machine Tool Works is used to provide an in-depth example of the operational development of a successful collaboration. The paper concludes that a phased coordination of commercial, technical and strategic interactions between the two partners is essential for such collaborations to work.

A heuristic approach for component scheduling on a high-speed PCB assembly machine

The collect-and-place machine is one of the most widely used placement machines for assembling electronic components on the printed circuit boards (PCBs). Nevertheless, the number of researches concerning the optimisation of the machine performance is very few. This motivates us to study the component scheduling problem for this type of machine with the objective of minimising the total assembly time. The component scheduling problem is an integration of the component sequencing problem, that is, the sequencing of component placements; and the feeder arrangement problem, that is, the assignment of component types to feeders. To solve the component scheduling problem efficiently, a hybrid genetic algorithm is developed in this paper. A numerical example is used to compare the performance of the algorithm with different component grouping approaches and different population sizes.

Reliability management of machine tool technology: a case study of current practice

Considerable attention has been given in the literature to identifying and describing the effective elements which positively affect the improvement of product reliability. These have been perceived by many as the 'state of the art' in the manufacturing industry. The applicability, diffusion and effectiveness of such methods and philosophies, as a means of systematically improving the reliability of a product, come in the main from case studies and single and infra-industry empirical studies. These studies have both been carried out within the wider context of quality assurance and management, and taking reliability as a discipline in its own right. However, it is somewhat of a surprise that there are no recently published findings or research studies on the adoption of these methods by the machine tool industry. This may lead one to construct several hypothesised paradigms: (a) that machine tool manufacturers compared to other industries, are slow to respond to propositions given in the literature by theorists or (b) this may indicate that a large proportion of the manufacturers make little use of the reliability improvement techniques as described in the literature, with the overall perception that they will not lead to any significant improvements? On the other hand, it is evident that hypothetical verification of the operational and engineering methods of reliability achievement and improvement adopted in the machine tool industry is less widely researched. Therefore, research into this area is needed in order to explore the 'state of the art' practice in the machine tool industry. This is in terms of the status, structure and activities of the operation of the reliability function. This paper outlines a research programme being conducted with the co-operation of a leading machine tool manufacturer, whose UK manufacturing plant produces in the main Vertical Machining Centres (VMCs) and is continuously undergoing incremental transitions in product reliability improvement.