Usability of VGI for validation of land cover maps

Volunteered Geographic Information (VGI) represents a growing source of potentially valuable data for many applications, including land cover map validation. It is still an emerging field and many different approaches can be used to take value from VGI, but also many pros and cons are related to its use. Therefore, since it is timely to get an overview of the subject, the aim of this article is to review the use of VGI as reference data for land cover map validation. The main platforms and types of VGI that are used and that are potentially useful are analysed. Since quality is a fundamental issue in map validation, the quality procedures used by the platforms that collect VGI to increase and control data quality are reviewed and a framework for addressing VGI quality assessment is proposed. A review of cases where VGI was used as an additional data source to assist in map validation is made, as well as cases where only VGI was used, indicating the procedures used to assess VGI quality and fitness for use. A discussion and some conclusions are drawn on best practices, future potential and the challenges of the use of VGI for land cover map validation.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

Exchange fairness and employee performance:An examination of the relationship between organizational politics and procedural justice

Data obtained from a manufacturing firm and a newspaper firm in India were used to examine the relationship between organizational politics and procedural justice in three separate studies. Study 1 constructively replicated research on the distinctiveness of the two constructs. Confirmatory factor analyses in which data from the manufacturing firm served as the development sample and data from the newspaper firm served as the validation sample demonstrated the distinctiveness of organizational politics and procedural justice. Study 2 examined the antecedents of the two constructs using data from the manufacturing firm. Structural equation modeling (SEM) results revealed formalization and participation in decision making to be positively related to procedural justice but negatively related to organizational politics. Further, authority hierarchy and spatial distance were positively related to organizational politics but unrelated to procedural justice. Study 3 examined the consequences of the two constructs in terms of task and contextual performance using data from the newspaper firm. Results of SEM analysis revealed procedural justice but not organizational politics to be related to task performance and the contextual performance dimensions of interpersonal facilitation and job dedication. © 2004 Elsevier Inc. All rights reserved.

An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

Validation of the food allergy quality of life:parental burden questionnaire in the UK

Purpose - Food allergy can have a profound effect on quality of life (QoL) of the family. The Food Allergy Quality of Life—Parental Burden Questionnaire (FAQL-PB) was developed on a US sample to assess the QoL of parents with food allergic children. The aim of this study was to examine the reliability and validity of the FAQL-PB in a UK sample and to assess the effect of asking about parental burden in the last week compared with parental burden in general, with no time limit for recall given. Methods - A total of 1,200 parents who had at least one child with food allergy were sent the FAQL-PB and the Child Health Questionnaire (CHQ-PF50); of whom only 63 % responded. Results - Factor analysis of the FAQL-PB revealed two factors: limitations on life and emotional distress. The total scale and the two sub-scales had high internal reliability (all a > 0.85). There were small to moderate but significant correlations between total FAQL-PB scores and health and parental impact measures on the CHQ-PF50 (p < 0.01). Significantly greater parental burden was reported for the no-time limited compared with the time-limited version (p < 0.01). Conclusions - The FAQL-PB is a reliable and valid measure for use in the UK. The scale could be used in clinic to assess the physical and emotional quality of life in addition to the impact on total quality of life.

Microwave properties of an inhomogeneous optically illuminated plasma in a microstrip gap

The optical illumination of a microstrip gap on a thick semiconductor substrate creates an inhomogeneous electron-hole plasma in the gap region. This allows the study of the propagation mechanism through the plasma region. This paper uses a multilayer plasma model to explain the origin of high losses in such structures. Measured results are shown up to 50 GHz and show good agreement with the simulated multilayer model. The model also allows the estimation of certain key parameters of the plasma, such as carrier density and diffusion length, which are difficult to measure by direct means. The detailed model validation performed here will enable the design of more complex microwave structures based on this architecture. While this paper focuses on monocrystalline silicon as the substrate, the model is easily adaptable to other semiconductor materials such as GaAs.

Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

PURPOSE: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.