Developing a forest data portal to support multi-scale decision making

Forests play a pivotal role in timber production, maintenance and development of biodiversity and in carbon sequestration and storage in the context of the Kyoto Protocol. Policy makers and forest experts therefore require reliable information on forest extent, type and change for management, planning and modeling purposes. It is becoming increasingly clear that such forest information is frequently inconsistent and unharmonised between countries and continents. This research paper presents a forest information portal that has been developed in line with the GEOSS and INSPIRE frameworks. The web portal provides access to forest resources data at a variety of spatial scales, from global through to regional and local, as well as providing analytical capabilities for monitoring and validating forest change. The system also allows for the utilisation of forest data and processing services within other thematic areas. The web portal has been developed using open standards to facilitate accessibility, interoperability and data transfer.

Multimodal field data entry:performance and usability issues

Mobile technologies have yet to be widely adopted by the Architectural, Engineering, and Construction (AEC) industry despite being one of the major growth areas in computing in recent years. This lack of uptake in the AEC industry is likely due, in large part, to the combination of small screen size and inappropriate interaction demands of current mobile technologies. This paper discusses the scope for multimodal interaction design with a specific focus on speech-based interaction to enhance the suitability of mobile technology use within the AEC industry by broadening the field data input capabilities of such technologies. To investigate the appropriateness of using multimodal technology for field data collection in the AEC industry, we have developed a prototype Multimodal Field Data Entry (MFDE) application. This application, which allows concrete testing technicians to record quality control data in the field, has been designed to support two different modalities of data input speech-based data entry and stylus-based data entry. To compare the effectiveness or usability of, and user preference for, the different input options, we have designed a comprehensive lab-based evaluation of the application. To appropriately reflect the anticipated context of use within the study design, careful consideration had to be given to the key elements of a construction site that would potentially influence a test technician's ability to use the input techniques. These considerations and the resultant evaluation design are discussed in detail in this paper.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Information geometric measurements of generalisation

Neural networks can be regarded as statistical models, and can be analysed in a Bayesian framework. Generalisation is measured by the performance on independent test data drawn from the same distribution as the training data. Such performance can be quantified by the posterior average of the information divergence between the true and the model distributions. Averaging over the Bayesian posterior guarantees internal coherence; Using information divergence guarantees invariance with respect to representation. The theory generalises the least mean squares theory for linear Gaussian models to general problems of statistical estimation. The main results are: (1)~the ideal optimal estimate is always given by average over the posterior; (2)~the optimal estimate within a computational model is given by the projection of the ideal estimate to the model. This incidentally shows some currently popular methods dealing with hyperpriors are in general unnecessary and misleading. The extension of information divergence to positive normalisable measures reveals a remarkable relation between the dlt dual affine geometry of statistical manifolds and the geometry of the dual pair of Banach spaces Ld and Ldd. It therefore offers conceptual simplification to information geometry. The general conclusion on the issue of evaluating neural network learning rules and other statistical inference methods is that such evaluations are only meaningful under three assumptions: The prior P(p), describing the environment of all the problems; the divergence Dd, specifying the requirement of the task; and the model Q, specifying available computing resources.

International technology transfer:perceptions and reality of quality and reliability

Impressions about product quality and reliability can depend as much on perceptions about brands and country of origin as on data regarding performance and failure. This has implications for companies in developing countries that need to compete with importers. For manufacturers in industrialised countries it has implications for the value of transferred technologies. This article considers the issue of quality and reliability when technology is transferred between countries with different levels of development. It is based on UK and Chinese company case studies and questionnaire surveys undertaken among three company groups: UK manufacturers; Chinese manufacturers; Chinese users. Results show that all three groups recognise quality and reliability as important and support the premise that foreign technology based machines made in China carry a price premium over Chinese machines based on local technology. Closer examination reveals a number of important differences concerning the perceptions and reality of quality and reliability between the groups.

Why organizational and community diversity matter:the emergence of incivility and organizational outcomes

Integrating sociological and psychological perspectives, this research considers the value of organizational ethnic diversity as a function of community diversity. Employee and patient surveys, census data, and performance indexes relevant to 142 hospitals in the United Kingdom suggest that intraorganizational ethnic diversity is associated with reduced civility toward patients. However, the degree to which organizational demography was representative of community demography was positively related to civility experienced by patients and ultimately enhanced organizational performance. These findings underscore the understudied effects of community context and imply that intergroup biases manifested in incivility toward out-group members hinder organizational performance.

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.

Data envelopment analysis and performance management

4th International Symposium of DEA, 5th-6th September 2004, Birmingham (UK)

Performance data indicate summation for pictorial depth-cues in slanted surfaces

Over recent years much has been learned about the way in which depth cues are combined (e.g. Landy et al., 1995). The majority of this work has used subjective measures, a rating scale or a point of subjective equality, to deduce the relative contributions of different cues to perception. We have adopted a very different approach by using two interval forced-choice (2IFC) performance measures and a signal processing framework. We performed summation experiments for depth cue increment thresholds between pairs of pictorial depth cues in displays depicting slanted planar surfaces made from arrays of circular 'contrast' elements. Summation was found to be ideal when size-gradient was paired with contrast-gradient for a wide range of depth-gradient magnitudes in the null stimulus. For a pairing of size-gradient and linear perspective, substantial summation (> 1.5 dB) was found only when the null stimulus had intermediate depth gradients; when flat or steeply inclined surfaces were depicted, summation was diminished or abolished. Summation was also abolished when one of the target cues was (i) not a depth cue, or (ii) added in conflict. We conclude that vision has a depth mechanism for the constructive combination of pictorial depth cues and suggest two generic models of summation to describe the results. Using similar psychophysical methods, Bradshaw and Rogers (1996) revealed a mechanism for the depth cues of motion parallax and binocular disparity. Whether this is the same or a different mechanism from the one reported here awaits elaboration.

Can production subsidies explain China's export performance? Evidence from firm-level data

This paper analyses the relationship between production subsidies and firms’ export performance using a very comprehensive and recent firm-level database and controlling for the endogeneity of subsidies. It documents robust evidence that production subsidies stimulate export activity at the intensive margin, although this effect is conditional on firm characteristics. In particular, the positive relationship between subsidies and the intensive margin of exports is strongest among profit-making firms, firms in capital-intensive industries, and those located in non-coastal regions. Compared to firm characteristics, the extent of heterogeneity across ownership structure (SOEs, collectives, and privately owned firms) proves to be relatively less important.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

General and multiplicative non-parametric corporate performance models with interval ratio data

The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios. © 2011 Elsevier Inc.

Handbook of research on strategic performance management and measurement using data envelopment analysis

Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors. All rights reserved.

Guiding schools to improved performance using data envelopment analysis:an illustration with data from a local education authority

The educational process is characterised by multiple outcomes such as the achievement of academic results of various standards and non-academic achievements. This paper shows how data envelopment analysis (DEA) can be used to guide secondary schools to improved performance through role-model identification and target setting in a way which recognises the multi-outcome nature of the education process and reflects the relative desirability of improving individual outcomes. The approach presented in the paper draws from a DEA-based assessment of the schools of a local education authority carried out by the authors. Data from that assessment are used to illustrate the approach presented in the paper. (Key words: Data envelopment analysis, education, target setting.)