Designing multiple user perspectives and functionality for clinical decision support systems

Clinical Decision Support Systems (CDSSs) need to disseminate expertise in formats that suit different end users and with functionality tuned to the context of assessment. This paper reports research into a method for designing and implementing knowledge structures that facilitate the required flexibility. A psychological model of expertise is represented using a series of formally specified and linked XML trees that capture increasing elements of the model, starting with hierarchical structuring, incorporating reasoning with uncertainty, and ending with delivering the final CDSS. The method was applied to the Galatean Risk and Safety Tool, GRiST, which is a web-based clinical decision support system (www.egrist.org) for assessing mental-health risks. Results of its clinical implementation demonstrate that the method can produce a system that is able to deliver expertise targetted and formatted for specific patient groups, different clinical disciplines, and alternative assessment settings. The approach may be useful for developing other real-world systems using human expertise and is currently being applied to a logistics domain. © 2013 Polish Information Processing Society.

Extent and nature of unlicensed and off-label medicine use in hospitalised children in Palestine

Objective of the study To determine the extent and nature of unlicensed/off-label prescribing patterns in hospitalised children in Palestine. Setting Four paediatric wards in two public health system hospitals in Palestine [Caritas children’s hospital (Medical and neonatal intensive care units) and Rafidia general hospital (Medical and surgical units)]. Method A prospective survey of drugs administered to infants and children <18 years old was carried out over a five-week period in the four paediatric wards. Main outcome measure Drug-licensing status of all prescriptions was determined according to the Palestinian Registered Product List and the Physician’s Desk Reference. Results Overall, 917 drug prescriptions were administered to 387children. Of all drug prescriptions, 528 (57.5%) were licensed for use in children; 65 (7.1%) were unlicensed; and 324 (35.3%) were used off-label. Of all children, 49.6% received off-label prescriptions, 10.1% received unlicensed medications and 8.2% received both. Seventy-two percent of off-label drugs and 66% of unlicensed drugs were prescribed for children <2 years. Multivariate analysis showed that patients who were admitted to the neonatal intensive care unit and infants aged 0–1 years were most likely to receive a greater number of off-label or unlicensed medications (OR 1.80; 95% CI 1.03–3.59 and OR 1.99; 95% CI 0.88–3.73, respectively). Conclusion The present findings confirmed the elevated prevalence of unlicensed and off-label paediatric drugs use in Palestine and strongly support the need to perform well designed clinical studies in children.

Intonation contour realisation for Standard Yorùbá text-to-speech synthesis:a fuzzy computational approach

This paper presents a novel intonation modelling approach and demonstrates its applicability using the Standard Yorùbá language. Our approach is motivated by the theory that abstract and realised forms of intonation and other dimensions of prosody should be modelled within a modular and unified framework. In our model, this framework is implemented using the Relational Tree (R-Tree) technique. The R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. Our R-Tree for an utterance is generated in two steps. First, the abstract structure of the waveform, called the Skeletal Tree (S-Tree), is generated using tone phonological rules for the target language. Second, the numerical values of the perceptually significant peaks and valleys on the S-Tree are computed using a fuzzy logic based model. The resulting points are then joined by applying interpolation techniques. The actual intonation contour is synthesised by Pitch Synchronous Overlap Technique (PSOLA) using the Praat software. We performed both quantitative and qualitative evaluations of our model. The preliminary results suggest that, although the model does not predict the numerical speech data as accurately as contemporary data-driven approaches, it produces synthetic speech with comparable intelligibility and naturalness. Furthermore, our model is easy to implement, interpret and adapt to other tone languages.

The state of the art in fuzzy data envelopment analysis

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years. © 2014 Springer-Verlag Berlin Heidelberg.

Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Logic Based Pattern Recognition - Ontology Content (2)

Logic based Pattern Recognition extends the well known similarity models, where the distance measure is the base instrument for recognition. Initial part (1) of current publication in iTECH-06 reduces the logic based recognition models to the reduced disjunctive normal forms of partially defined Boolean functions. This step appears as a way to alternative pattern recognition instruments through combining metric and logic hypotheses and features, leading to studies of logic forms, hypotheses, hierarchies of hypotheses and effective algorithmic solutions. Current part (2) provides probabilistic conclusions on effective recognition by logic means in a model environment of binary attributes.

Systematic financial resources allocation processes:a model for critical resources mobilization and deployment for nigerian universities

Purpose – The purpose of this research is to study the perceived impact of some factors on the resources allocation processes of the Nigerian universities and to suggest a framework that will help practitioners and academics to understand and improve such processes. Design/methodology/approach – The study adopted the interpretive qualitative approach aimed at an ‘in-depth’ understanding of the resource allocation experiences of key university personnel and their perceived impact of the contextual factors affecting such processes. The analysis of individual narratives from each university established the conditions and factors impacting the resources allocation processes within each institution. Findings – The resources allocation process issues in the Nigerian universities may be categorised into people (core and peripheral units’ challenge, and politics and power); process (resources allocation processes); and resources (critical financial shortage and resources dependence response). The study also provides insight that resourcing efficiency in Nigerian universities appears strongly constrained by the rivalry among the resource managers. The efficient resources allocation process (ERAP) model is proposed to resolve the identified resourcing deficiencies. Research limitations/implications – The research is not focused to provide generalizable observations but ‘in-depth’ perceived factors and their impact on the resources allocation processes in Nigerian universities. The study is limited to the internal resources allocation issues within the universities and excludes the external funding factors. The resource managers’ responses to the identified factors may affect their internal resourcing efficiency. Further research using more empirical samples is required to obtain more widespread results and the implications for all universities. Originality/value – This study contributes a fresh literature framework to resources allocation processes focusing at ‘people’, ‘process’ and ‘resources’. Also a middle range theory triangulation is developed in relation to better understanding of resourcing process management. The study will be of interest to university managers and policy makers.

Educational Model of Computer as a Base for Informatics Learning

It is proposed to use one common model of computer for teaching different parts of the informatics course, connected with both hardware and software subjects. Reasoning of such slant is presented; the most suitable themes of the course, where it is practical, are enumerated. The own author's development (including software support) – the educational model of virtual computer "E97" and compiler from Pascal language for it – are described. It is accented, that the discussed ideas are helpful for any other similar model.

Teaching Strategies and Ontologies for E-Learning

* The work is partially suported by Russian Foundation for Basic Studies (grant 02-01-00466).

Simulation of surface EMG for the analysis of muscle activity during whole body vibratory stimulation

This study aims to reproduce the effect of motor-unit synchronization on surface EMG recordings during vibratory stimulation to highlight vibration evoked muscle activity. The authors intended to evaluate, through numerical simulations, the changes in surface EMG spectrum in muscles undergoing whole body vibration stimulation. In some specific bands, in fact, vibration induced motion artifacts are also typically present. In addition, authors meant to compare the simulated EMGs with respect to real recordings in order to discriminate the effect of synchronization of motor units discharges with vibration frequencies from motion artifacts. Computations were performed using a model derived from previous studies and modified to consider the effect of vibratory stimulus, the motor unit synchronization and the endplates-electrodes relative position on the EMG signal. Results revealed that, in particular conditions, synchronization of MUs' discharge generates visible peaks at stimulation frequency and its harmonics. However, only a part of the total power of surface EMGs might be enclosed within artifacts related bands (±1. Hz centered at the stimulation frequency and its superior harmonics) even in case of strong synchronization of motor units discharges with the vibratory stimulus. © 2013 Elsevier Ireland Ltd.

Motivating students to learn through good and helpful coursework feedback

The 2008 National Student Survey revealed that: 44% of full-time students in England did not think that the feedback on their work had been prompt nor did they agree that the feedback on their work helped them clarify things that they did not understand (HEFCE, 2008). Computer Science and Engineering & Technology have been amongst the poorest performers in this aspect as they ranked in the lower quartile (Surridge, 2007, p.32). Five years since the first NSS survey, assessment and feedback remains the biggest concern. Dissatisfaction in any aspect of studies demotivates students and can lead to disengagement and attrition. As the student number grows, the situation can only get worse if nothing is done about it. We have conducted a survey to investigate views on assessment and feedback from Engineering, Mathematics and Computing students. The survey aims at investigating the core issues of dissatisfaction in assessment and feedback and ways in which UK Engineering students can learn better through helpful feedback. The study focuses on collecting students' experiences with feedback received in their coursework, assignments and quizzes in Computing Science modules. The survey reveals the role of feedback in their learning. The results of the survey help to identify the forms of feedback that are considered to be helpful in learning and the time frame for timely feedback. We report on the findings of the survey. We also explore ways to improve assessment and feedback in a bid to better engage engineering students in their studies.

Computer Mathematics with MuPAD in School Years 6. To 9

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Estimation of computer waste quantities using forecasting techniques

Technology changes rapidly over years providing continuously more options for computer alternatives and making life easier for economic, intra-relation or any other transactions. However, the introduction of new technology “pushes” old Information and Communication Technology (ICT) products to non-use. E-waste is defined as the quantities of ICT products which are not in use and is bivariate function of the sold quantities, and the probability that specific computers quantity will be regarded as obsolete. In this paper, an e-waste generation model is presented, which is applied to the following regions: Western and Eastern Europe, Asia/Pacific, Japan/Australia/New Zealand, North and South America. Furthermore, cumulative computer sales were retrieved for selected countries of the regions so as to compute obsolete computer quantities. In order to provide robust results for the forecasted quantities, a selection of forecasting models, namely (i) Bass, (ii) Gompertz, (iii) Logistic, (iv) Trend model, (v) Level model, (vi) AutoRegressive Moving Average (ARMA), and (vii) Exponential Smoothing were applied, depicting for each country that model which would provide better results in terms of minimum error indices (Mean Absolute Error and Mean Square Error) for the in-sample estimation. As new technology does not diffuse in all the regions of the world with the same speed due to different socio-economic factors, the lifespan distribution, which provides the probability of a certain quantity of computers to be considered as obsolete, is not adequately modeled in the literature. The time horizon for the forecasted quantities is 2014-2030, while the results show a very sharp increase in the USA and United Kingdom, due to the fact of decreasing computer lifespan and increasing sales.

Improving the Quality of Education by Using a System for Development and Generation of Personalized Educational Materials

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

Benchmarking of distributed computing engines spark and GraphLab for big data analytics

In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.