Standardisation and benchmarking for improving translator training

The worldwide growth of the translation industry requires qualified professional translators. During the last decade, we have seen an enormous increase in translator training programmes offered by universities, mainly at postgraduate level. A challenge for such university programmes is to make sure that they prepare graduates who are qualified for the needs of the diverse profession in the rapidly changing market. This means that programmes need to be developed with the market needs in mind and that they need to ensure a good match between graduates' competences and employers' requirements. This paper addresses the following questions: How can universities adapt translator training programmes to the rapidly changing industry and the accompanying changes in professional profiles? How can we reconcile the requests of the industry for graduates who have practical and professional skills with the requests of the universities for graduates who have in-depth academic knowledge and intellectual skills? What standards and benchmarks are in place to assure quality of translator training programmes? Some such developments in respect of benchmarking are illustrated at first for the United Kingdom, followed by information on the European Master’s in Translation (EMT) project, an initiative at the European level. Finally, the paper reflects on the challenges which the EMT translator competence profile poses for university programmes.

Municipal benchmarking:organisational learning and network performance in the public sector

The main purpose of this dissertation is to assess the relation between municipal benchmarking and organisational learning with a specific emphasis on benchlearning and performance within municipalities and between groups of municipalities in the building and housing sector in the Netherlands. The first and main conclusion is that this relation exists, but that the relative success of different approaches to dimensions of change and organisational learning are a key explanatory factor for differences in the success of benchlearning. Seven other important conclusions could be derived from the empirical research. First, a combination of interpretative approaches at the group level with a mixture of hierarchical and network strategies, positively influences benchlearning. Second, interaction among professionals at the inter-organisational level strengthens benchlearning. Third, stimulating supporting factors can be seen as a more important strategy to strengthen benchlearning than pulling down barriers. Fourth, in order to facilitate benchlearning, intrinsic motivation and communication skills matter, and are supported by a high level of cooperation (i.e., team work), a flat organisational structure and interactions between individuals. Fifth, benchlearning is facilitated by a strategy that is based on a balanced use of episodic (emergent) and systemic (deliberate) forms of power. Sixth, high levels of benchlearning will be facilitated by an analyser or prospector strategic stance. Prospectors and analysers reach a different learning outcome than defenders and reactors. Whereas analysers and prospectors are willing to change policies when it is perceived as necessary, the strategic stances of defenders and reactors result in narrow process improvements (i.e., single-loop learning). Seventh, performance improvement is influenced by functional perceptions towards performance, and these perceptions ultimately influence the elements adopted. This research shows that efforts aimed at benchlearning and ultimately improved service delivery, should be directed to a multi-level and multi-dimensional approach addressing the context, content and process of dimensions of change and organisational learning.

A socio-economic approach to online vision graph generation and handover in distributed smart camera networks

In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.

Green operations initiatives in the automotive industry:an environmental reports analysis and benchmarking study

Purpose: The purpose of this paper is to focus on investigating and benchmarking green operations initiatives in the automotive industry documented in the environmental reports of selected companies. The investigation roadmaps the main environmental initiatives taken by the world's three major car manufacturers and benchmarks them against each other. The categorisation of green operations initiatives that is provided in the paper can also help companies in other sectors to evaluate their green practices. Design/methodology/approach: The first part of the paper is based on existing literature on the topic of green and sustainable operations and the "unsustainable" context of automotive production. The second part relates to the roadmap and benchmarking of green operations initiatives based on an analysis of secondary data from the automotive industry. Findings: The findings show that the world's three major car manufacturers are pursuing various environmental initiatives involving the following green operations practices: green buildings, eco-design, green supply chains, green manufacturing, reverse logistics and innovation. Research limitations/implications: The limitations of this paper start from its selection of the companies, which was made using production volume and country of origin as the principal criteria. There is ample evidence that other, smaller, companies are pursuing more sophisticated and original environmental initiatives. Also, there might be a gap between what companies say they do in their environmental reports and what they actually do. Practical implications: This paper helps practitioners in the automotive industry to benchmark themselves against the major volume manufacturers in three different continents. Practitioners from other industries will also find it valuable to discover how the automotive industry is pursuing environmental initiatives beyond manufacturing, apart from the green operations practices covering broadly all the activities of operations function. Originality/value: The originality of the paper is in its up-to-date analysis of environmental reports of automotive companies. The paper offers value for researchers and practitioners due to its contribution to the green operations literature. For instance, the inclusion of green buildings as part of green operations practices has so far been neglected by most researchers and authors in the field of green and sustainable operations. © Emerald Group Publishing Limited.

Self-assessment benchmarking as a quality management tool in primary healthcare

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Innovation and performance:benchmarking Australian firms

This article empirically analyses the link between innovation and performance using a sample of large Australian firms, with a specific aim of developing benchmarking tools. Innovation is measured by firms' investment in R&D and applications for patents, trademarks and designs. An innovation index is constructed to provide one method of benchmarking. The index incorporates a firm's innovative activities into a single figure after accounting for firm size. The index provides a ranking of the most innovative firms in Australia. A second method of benchmarking uses a stochastic production frontier. This type of analysis identifies the firms which are located closest to a ‘best practice innovation frontier’.

Socio-economic vision graph generation and handover in distributed smart camera networks

In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras.

Outlier-resisting graph embedding

Graph embedding is a general framework for subspace learning. However, because of the well-known outlier-sensitiveness disadvantage of the L2-norm, conventional graph embedding is not robust to outliers which occur in many practical applications. In this paper, an improved graph embedding algorithm (termed LPP-L1) is proposed by replacing L2-norm with L1-norm. In addition to its robustness property, LPP-L1 avoids small sample size problem. Experimental results on both synthetic and real-world data demonstrate these advantages. © 2009 Elsevier B.V. All rights reserved.

The Role of DBMS in Analytical Processes of the Logistic of Stock Reserves

One of main problems of corporate information systems is the precise evaluation of speed of transactions and the speed of making reports. The core of the problem is based on the DBMS that is used. Most DBMS which are oriented for high performance and reliability of transactions do not give fast access to analytical and summarized data and vice versa. It is quite difficult to estimate which class of database to use. The author of the article gives a concise observation of the problem and a possible way to be solved.

How to Use a Desktop Version of a DBMS for Client-Server Applications

DBMS (Data base management systems) still have a very high price for small and middle enterprises in Bulgaria. Desktop versions are free but they cannot function in multi-user environment. We will try to make an application server which will make a Desktop version of a DBMS open to many users. Thus, this approach will be appropriate for client-server applications. The author of the article gives a concise observation of the problem and a possible way of solution.

On Graph-Based Cryptography and Symbolic Computations

We have been investigating the cryptographical properties of in nite families of simple graphs of large girth with the special colouring of vertices during the last 10 years. Such families can be used for the development of cryptographical algorithms (on symmetric or public key modes) and turbocodes in error correction theory. Only few families of simple graphs of large unbounded girth and arbitrarily large degree are known. The paper is devoted to the more general theory of directed graphs of large girth and their cryptographical applications. It contains new explicit algebraic constructions of in finite families of such graphs. We show that they can be used for the implementation of secure and very fast symmetric encryption algorithms. The symbolic computations technique allow us to create a public key mode for the encryption scheme based on algebraic graphs.

An improved memory management scheme for large scale graph computing engine GraphChi

GraphChi is the first reported disk-based graph engine that can handle billion-scale graphs on a single PC efficiently. GraphChi is able to execute several advanced data mining, graph mining and machine learning algorithms on very large graphs. With the novel technique of parallel sliding windows (PSW) to load subgraph from disk to memory for vertices and edges updating, it can achieve data processing performance close to and even better than those of mainstream distributed graph engines. GraphChi mentioned that its memory is not effectively utilized with large dataset, which leads to suboptimal computation performances. In this paper we are motivated by the concepts of 'pin ' from TurboGraph and 'ghost' from GraphLab to propose a new memory utilization mode for GraphChi, which is called Part-in-memory mode, to improve the GraphChi algorithm performance. The main idea is to pin a fixed part of data inside the memory during the whole computing process. Part-in-memory mode is successfully implemented with only about 40 additional lines of code to the original GraphChi engine. Extensive experiments are performed with large real datasets (including Twitter graph with 1.4 billion edges). The preliminary results show that Part-in-memory mode memory management approach effectively reduces the GraphChi running time by up to 60% in PageRank algorithm. Interestingly it is found that a larger portion of data pinned in memory does not always lead to better performance in the case that the whole dataset cannot be fitted in memory. There exists an optimal portion of data which should be kept in the memory to achieve the best computational performance.

The Application of Graph Model for Automation of the User Interface Construction

The ability of automatic graphic user interface construction is described. It is based on the building of user interface as reflection of the data domain logical definition. The submitted approach to development of the information system user interface enables dynamic adaptation of the system during their operation. This approach is used for creation of information systems based on CASE-system METAS.