A global perspective on psycho-educational assessment

For psychologists in less developed countries, psycho-educational assessment is often challenging due to a lack of specialist training and a scarcity of appropriate, psychometrically robust instruments. This paper focuses on school psychology and psycho-educational assessment in three countries: Bangladesh, China and Iran. Despite differences in demographic and cultural features, these countries share similar issues that restrict the practice of psycho-educational assessment. We conclude that it is important for psychologists in western countries to support professional training and testing practices in less developed countries.

A market assessment and evaluation of structural roundwood products from hardwood pulp plantations.

Roundwood structures have always been used for temporary and low cost shelters and other fleeting structures. Novel concepts for the use of plantation hardwoods in roundwood form in construction were developed and circulated along with an electronic questionnaire to stakeholders representing growers, designers and users of hardwood. Responses indicate that there is a high level of interest in developing products from the emerging small roundwood resource and a detailed program of research was supported and recommended by the majority of participants in the survey. These results indicate a high level of support for further investigation into the use of plantation hardwood for roundwood components. Respondents representing a wide range of stakeholders have indicated that to gain benefit from a detailed project they would require solutions for connection systems and protection from pests and weathering, indications of cost and assurance of ongoing supply for niche applications, data for strength, acoustic dampening and thermal insulation properties, acceptance by regulatory authorities and training for on-site construction.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

An ANN based approach for voltage stability assessment

Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Interdisciplinary experience in the Teacher Training College of Vitoria-Gasteiz: teaching profession module

[EN] The higher education regulation process in Europe, known as the Bologna Process, has involved many changes, mainly in relation to methodology and assessment. The paper given below relates to implementing the new EU study plans into the Teacher Training College of Vitoria-Gasteiz; it is the first interdisciplinary paper written involving teaching staff and related to the Teaching Profession module, the first contained in the structure of the new plans. The coordination of teaching staff is one of the main lines of work in the Bologna Process, which is also essential to develop the right skills and maximise the role of students as an active learning component. The use of active, interdisciplinary methodologies has opened up a new dimension in universities, requiring the elimination of the once componential, individual structure, making us look for new areas of exchange that make it possible for students' training to be developed jointly.

Implementation of a nursing competency assessment system in public hospitals

Numerous problems are frequently observed when nursing competency assessment systems (NCAS) are implemented. How to effectively implement a nursing competency assessment system, according to academic and practical contributions, is poorly reported in the literature. The purpose of this paper is to present a set of recommendations for public hospitals and nursing management in order to facilitate the implementation of a NCAS. To achieve this objective we have revised the existing literature and conducted a Delphi study with nursing managers and human resource managers of the public hospitals of the Basque Health Service. The results are that the implementation of a NCAS requires a well-planned strategy that managers must consider before implementing any NCAS. This strategy must include, at minimum, the following aspects: communication, training, leadership, and content where the NCAS is concerned. The context of the organisations and the cultural dimensions may also influence the results of the application of the system.

Integrated treatment of first episode psychosis with online training (e-learning): study protocol for a randomised controlled trial

Background: The integrated treatment of first episode psychosis has been shown to improve functionality and negative symptoms in previous studies. In this paper, we describe a study of integrated treatment (individual psychoeducation complementary to pharmacotherapy) versus treatment as usual, comparing results at baseline with those at 6-month re-assessment (at the end of the study) for these patients, and online training of professionals to provide this complementary treatment, with the following objectives: 1) to compare the efficacy of individual psychoeducation as add-on treatment versus treatment as usual in improving psychotic and mood symptoms; 2) to compare adherence to medication, functioning, insight, social response, quality of life, and brain-derived neurotrophic factor, between both groups; and 3) to analyse the efficacy of online training of psychotherapists. Methods/design: This is a single-blind randomised clinical trial including patients with first episode psychosis from hospitals across Spain, randomly assigned to either a control group with pharmacotherapy and regular sessions with their psychiatrist (treatment as usual) or an intervention group with integrated care including treatment as usual plus a psychoeducational intervention (14 sessions). Training for professionals involved at each participating centre was provided by the coordinating centre (University Hospital of Alava) through video conferences. Patients are evaluated with an extensive battery of tests assessing clinical and sociodemographic characteristics (Positive and Negative Syndrome Scale, State-Trait Anxiety Inventory, Liebowitz Social Anxiety Scale, Hamilton Rating Scale for Depression, Scale to Assess Unawareness of Mental Disorders, Strauss and Carpenter Prognostic Scale, Global Assessment of Functioning Scale, Morisky Green Adherence Scale, Functioning Assessment Short Test, World Health Organization Quality of Life instrument WHOQOL-BREF (an abbreviated version of the WHOQOL-100), and EuroQoL questionnaire), and brain-derived neurotrophic factor levels are measured in peripheral blood at baseline and at 6 months. The statistical analysis, including bivariate analysis, linear and logistic regression models, will be performed using SPSS. Discussion: This is an innovative study that includes the assessment of an integrated intervention for patients with first episode psychosis provided by professionals who are trained online, potentially making it possible to offer the intervention to more patients.

Training in fisheries planning and management: the case of the Southern African Development Community nations

This paper presents an evaluation of the 15-week course on Training in Fisheries Planning and Management being offered at the University of Namibia since 1991. This course includes instruction in fisheries technology, fisheries biology, fisheries law and law of the sea, fisheries economics, fisheries sociology, environment impact assessment, planning and management, the logical framework approach to planning and computer literacy. The participats in the course have rated the various elements in a range of 2.9 to 4.7 out of a maximum of 5 points.

Report of the procedures and methods for continuing assessment of the status of the Hilsa resources

The Bangladesh Fisheries Research Institute (BFRI) sampled length frequency data, reviewed historical catch and effort data and sampled water quality to asses the status of hilsa (Tenualosa ilisha) resources. BFRI conducted a training course for BOBLME members. They also prepared awareness building materials for use in workshops for hilsa fishers.

Report of the essential EAFM training course, Chittagong, Bangladesh, 12-20 November, 2014

Participants were exposed to concepts and information about Ecosystem Approach to Fisheries Management (EAFM) using a structured, participatory method of delivery. The learning strategy involved specifically designed exercises, using real examples, to consolidate learning. Daily monitoring and reviews were conducted together with pre-and post-course assessment.

Report of the training programme on Essential Ecosystem Approach to Fisheries Management (EAFM): developing capacity in the EAFM, Chennai, India, 11-16 August, 2014

Participants were exposed to concepts and information about EAFM using a structured, participatory method of delivery. The learning strategy involved specifically designed exercises, using real examples, to consolidate learning. Daily monitoring and reviews were conducted together with pre-and post-course assessment.

Multi-parametric metabolic assessment of cells under stress conditions

Glycolysis, glutaminolysis, the Krebs cycle and oxidative phosphorylation are the main metabolic pathways. Exposing cells to key metabolic substrates (glucose, glutamine and pyruvate); investigation of the contribution of substrates in stress conditions such as uncoupling and hypoxia was conducted. Glycolysis, O2 consumption, O2 and ATP levels and hypoxia inducible factor (HIF) signalling in PC12 cells were investigated. Upon uncoupling with FCCP mitochondria were depolarised similarly in all cases, but a strong increase in respiration was only seen in the cells fed on glutamine with either glucose or pyruvate. Inhibition of glutaminolysis reversed the glutamine dependant effect. Differential regulation of the respiratory response to FCCP by metabolic environment suggests mitochondrial uncoupling has a potential for substrate-specific inhibition of cell function. At reduced O2 availability (4 % and 0 % O2), cell bioenergetics and local oxygenation varied depending on the substrate composition. Results indicate that both supply and utilisation of key metabolic substrates can affect the pattern of HIF-1/2α accumulation by differentially regulating iO2¬, ATP levels and Akt/Erk/AMPK pathways. Inhibition of key metabolic pathways can modulate HIF regulatory pathways, metabolic responses and survival of cancer cells in hypoxia. Hypoxia leads to transcriptional activation, by HIF, of pyruvate dehydrogenase (PDH) kinase which phosphorylates and inhibits PDH, a mitochondrial enzyme that converts pyruvate into acetyl-CoA. The levels of PDH (total and phosphorylated), PDH kinase and HIF-1α were analysed in HCT116 and HCT116 SCO2-/- (deficient in complex IV of the respiratory chain) grown under 20.9 % and 3 % O2. Data indicate that regulation of PDH can occur in a manner independent of the HIF-1/PDH kinase 1 axis, mitochondrial respiration and the demand for acetyl-CoA. Collectively these results can be applied to many diseases; reduced nutrient supply and O2 during ischemia/stroke, hypoglycaemia in diabetes mellitus and cancer associated changes in uncoupling protein expression levels.