A Model of a Diagnostic Test for Controlling the Results of a Computer Based Education in Applied Mathematics at the University of Ruse

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

Assessing the motivation of MDs to use computer-based support at the point-of-care in the emergency department

A significant body of research investigates the acceptance of computer-based support (including devices and applications ranging from e-mail to specialized clinical systems, like PACS) among clinicians. Much of this research has focused on measuring the usability of systems using characteristics related to the clarity of interactions and ease of use. We propose that an important attribute of any clinical computer-based support tool is the intrinsic motivation of the end-user (i.e. a clinician) to use the system in practice. In this paper we present the results of a study that investigated factors motivating medical doctors (MDs) to use computer-based support. Our results demonstrate that MDs value computer-based support, find it useful and easy to use, however, uptake is hindered by perceived incompetence, and pressure and tension associated with using technology.

A computer based approach to improve the dietary and physical activity patterns of a diverse group of adolescents

Diet and physical activity patterns have been implicated as major factors in the increasing prevalence of childhood and adolescent obesity. It is estimated that between 16 and 33 percent of children and adolescents in the United States are overweight (CDC, 2000). Moreover, the CDC estimates that less than 50% of adolescents are physically active on a regular basis (CDC, 2003). Interventions must be focused to modify these behaviors. Facilitating the understanding of proper nutrition and need for physical activity among adolescents is the first step in preventing overweight and obesity and delaying the development of chronic diseases later in life (Dwyer, 2000). The purpose of this study was to compare the outcomes of students receiving one of two forms of education (both emphasizing diet and physical activity), to determine whether a computer based intervention (CBI) program using an interactive, animated CD-ROM would elicit a greater behavior change in comparison to a traditional didactic intervention (TDI) program. A convenience sample of 254 high school students aged 14-19 participated in the 6-month program. A pre-test post-test design was used, with follow-up measures taken at three months post-intervention. ^ No change was noted in total fat, saturated fat, fruit/vegetables, or fiber intake for any of the groups. There was also no change in perceived self-efficacy or perceived social support. Results did, however, indicate an increase in nutrition knowledge for both intervention groups (p<0.001). In addition, the CBI group demonstrated more positive and sustained behavior changes throughout the course of the study. These changes included a decrease in BMI (ppre/post<0.001, ppost/follow-up<0.001), number of meals skipped (ppre/post<0.001), and soda consumption (ppre/post=0.003, ppost/follow-up=0.03) and an increase in nutrition knowledge (ppre/post<0.001, ppre/follow-up <0.001), physical activity (ppre/post<0.05, p pre/follow-up<0.01), frequency of label reading (ppre/follow-up <0.0l) and in dairy consumption (ppre/post=0.03). The TDI group did show positive gains in some areas post intervention, however a return to baseline behavior was shown at follow-up. Findings of this study suggest that compared to traditional didactic teaching, computer-based nutrition and health education has greater potential to elicit change in knowledge and behavior as well as promote maintenance of the behavior change over time. ^

The effect of different instructional groupings on student achievement and attitudes from a computer-based interactive videodisk biology unit

The purpose of this research study was to determine the effect of two different instructional groupings (cooperative and traditional whole-class) on student achievement and attitudes using a computer-based interactive videodisc biology unit. The subjects were 64 high school biology students assigned to two heterogeneous experimental groups, randomly selected from two preassigned summer school biology classes, one honors, the other regular. A two-group, posttest-only, control group experimental research design was utilized. Achievement at three cognitive levels and attitudes towards science laserdisc instruction were measured at the conclusion of the study. The cooperative group consistently outperformed the traditional group in achievement posttest scores. Factorial ANOVA on total (overall) achievement scores indicated that subjects in cooperative groups significantly outperformed those in the traditional group, and also that the instructional group, class level, and gender interacted in an ordinal fashion to make a significant difference in how female and male subjects were affected by the treatments depending on their class (aptitude) level. Regular level females and honors level males performed much better when in cooperative groups, whereas group membership did not appear to make a difference for either honors level females or regular level males. A t-test comparing honors level males revealed that cooperative groups were close to being significantly better in total achievement posttest scores than their traditional group counterparts. Factorial MANOVA comparing the instructional groups at three cognitive levels found no significant difference. Analysis on the attitudes posttest data also revealed that subjects in cooperative groups demonstrated more positive attitudes towards science laserdisc instruction; however these differences were not found to be significant. Significant interactions in attitudes of females and males from different class levels had the opposite effect as achievement: honors level females and regular level males demonstrated more positive attitudes towards science laserdisc instruction when in cooperative groups, whereas group membership did not appear to make a difference for honors level males, and regular level females demonstrated the lowest attitudes ratings of any group when involved in cooperative groups. This contrast between achievement and attitudinal results suggests cross-gender interaction in traditionally defined gender roles.

The impact of income and social status on population health: a scenario based simulation for nursing students

The development of critical thinking and communication skills is an essential part of Baccalaureate and Practical Nursing education. Scenario-based simulation, a form of experiential learning, directly engages students in the learning process. This teaching learning method has been shown to increase students’ understanding of the influence of their personal beliefs and values when working with clients and to improve therapeutic communication and critical thinking skills. Students in both the BN (Collaborative) and PN Programs at the Centre for Nursing Studies demonstrate a strong theoretical understanding of the impact of income and social status on population health but often experience difficulty applying this knowledge to the clinical situations involving clients and families. The purpose of the project was to develop a scenario-based simulation activity to provide nursing students with first-hand experiences of the impact of income and social status on health service accessibility. A literature review and stakeholder consultations were conducted to inform the project. The findings of these initiatives and Kolb’s Experiential Learning Theory were used to guide all aspects of the project. This report is an account of how the income and social status simulation and its accompanying materials were developed. This project provided an excellent learning opportunity that demonstrated the use of advanced nursing competencies.

Development and Evaluation of a Computer-Based, Self-Management Tool for People Recently Diagnosed with Type 2 Diabetes

Aim. The purpose of this study was to develop and evaluate a computer-based, dietary, and physical activity self-management program for people recently diagnosed with type 2 diabetes. 
Methods. The computer-based program was developed in conjunction with the target group and evaluated in a 12-week randomised controlled trial (RCT). Participants were randomised to the intervention (computer-program) or control group (usual care). Primary outcomes were diabetes knowledge and goal setting (ADKnowl questionnaire, Diabetes Obstacles Questionnaire (DOQ)) measured at baseline and week 12. User feedback on the program was obtained via a questionnaire and focus groups. Results. Seventy participants completed the 12-week RCT (32 intervention, 38 control, mean age 59 (SD) years). After completion there was a significant between-group difference in the “knowledge and beliefs scale” of the DOQ. Two-thirds of the intervention group rated the program as either good or very good, 92% would recommend the program to others, and 96% agreed that the information within the program was clear and easy to understand. 
Conclusions. The computer-program resulted in a small but statistically significant improvement in diet-related knowledge and user satisfaction was high. With some further development, this computer-based educational tool may be a useful adjunct to diabetes self-management.

A randomized controlled trial of an early-intervention, computer-based literacy program to boost phonological skills in 4- to 6-year-old children

Background: Many school-based interventions are being delivered in the absence of evidence of effectiveness (Snowling & Hulme, 2011, Br. J. Educ. Psychol., 81, 1).Aim: This study sought to address this oversight by evaluating the effectiveness of the commonly used the Lexia Reading Core5 intervention, with 4- to 6-year-old pupils in Northern Ireland.Sample: A total of 126 primary school pupils in year 1 and year 2 were screened on the Phonological Assessment Battery 2nd Edition (PhAB-2). Children were recruited from the equivalent year groups to Reception and Year 1 in England and Wales, and Pre-kindergarten and Kindergarten in North America.
Methods: A total of 98 below-average pupils were randomized (T0) to either an 8-week block (inline image = 647.51 min, SD = 158.21) of daily access to Lexia Reading Core5 (n = 49) or a waiting-list control group (n = 49). Assessment of phonological skills was completed at post-intervention (T1) and at 2-month follow-up (T2) for the intervention group only.
Results: Analysis of covariance which controlled for baseline scores found that the Lexia Reading Core5 intervention group made significantly greater gains in blending, F(1, 95) = 6.50, p = .012, partial η2 = .064 (small effect size) and non-word reading, F(1, 95) = 7.20, p = .009, partial η2 = .070 (small effect size). Analysis of the 2-month follow-up of the intervention group found that all group treatment gains were maintained. However, improvements were not uniform among the intervention group with 35% failing to make progress despite access to support. Post-hoc analysis revealed that higher T0 phonological working memory scores predicted improvements made in phonological skills.
Conclusions: An early-intervention, computer-based literacy program can be effective in boosting the phonological skills of 4- to 6-year-olds, particularly if these literacy difficulties are not linked to phonological working memory deficits.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

Computer-based tools for assessing micro-longitudinal patterns of cognitive function in older adults

Patterns of cognitive change over micro-longitudinal timescales (i.e., ranging from hours to days) are associated with a wide range of age-related health and functional outcomes. However, practical issues with conducting high-frequency assessments make investigations of micro-longitudinal cognition costly and burdensome to run. One way of addressing this is to develop cognitive assessments that can be performed by older adults, in their own homes, without a researcher being present. Here, we address the question of whether reliable and valid cognitive data can be collected over micro-longitudinal timescales using unsupervised cognitive tests.In study 1, 48 older adults completed two touchscreen cognitive tests, on three occasions, in controlled conditions, alongside a battery of standard tests of cognitive functions. In study 2, 40 older adults completed the same two computerized tasks on multiple occasions, over three separate week-long periods, in their own homes, without a researcher present. Here, the tasks were incorporated into a wider touchscreen system (Novel Assessment of Nutrition and Ageing (NANA)) developed to assess multiple domains of health and behavior. Standard tests of cognitive function were also administered prior to participants using the NANA system.Performance on the two “NANA” cognitive tasks showed convergent validity with, and similar levels of reliability to, the standard cognitive battery in both studies. Completion and accuracy rates were also very high. These results show that reliable and valid cognitive data can be collected from older adults using unsupervised computerized tests, thus affording new opportunities for the investigation of cognitive function.

Some parameters that affect CDMA capacity analysis. Results using GIS based simulation

In previous papers we describe a model for capacity analysis in CDMA systems using DC-Cell, a GIS based planning tool developed at Universidad Politecnica de Valencia, and MATLAB. We show some initial results of that model, and now, we are exploring different parameters like cell size, proximity between cells, number of cells in the system and “clustering” CDMA in order to improve the planning process for third generation systems. In this paper we show the results for variations of some of these parameters, specifically the cell size and number of cells. In CDMA systems is quite common to suppose only one carrier frequency for capacity estimation, and it is intuitive to think that for more base stations, mean more users. However the multiple access interference problem in CDMA systems could establish a limit for that supposition in a similar way that occurs in FDMA and TDMA systems.

Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study

This study is about the comparison of simulation techniques between Discrete Event Simulation (DES) and Agent Based Simulation (ABS). DES is one of the best-known types of simulation techniques in Operational Research. Recently, there has been an emergence of another technique, namely ABS. One of the qualities of ABS is that it helps to gain a better understanding of complex systems that involve the interaction of people with their environment as it allows to model concepts like autonomy and pro-activeness which are important attributes to consider. Although there is a lot of literature relating to DES and ABS, we have found none that focuses on exploring the capability of both in tackling the human behaviour issues which relates to queuing time and customer satisfaction in the retail sector. Therefore, the objective of this study is to identify empirically the differences between these simulation techniques by stimulating the potential economic benefits of introducing new policies in a department store. To apply the new strategy, the behaviour of consumers in a retail store will be modelled using the DES and ABS approach and the results will be compared. We aim to understand which simulation technique is better suited to human behaviour modelling by investigating the capability of both techniques in predicting the best solution for an organisation in using management practices. Our main concern is to maximise customer satisfaction, for example by minimising their waiting times for the different services provided.

Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

Investigating output accuracy for a discrete event simulation model and an agent based simulation model

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store’s fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Comparison of Computer-Based and Optical Face Recognition Paradigms

The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB © software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers an acceptable error rate, easy calculation, and a reasonable speed. Finally, in detection and recognition, the performance of the digital model is better than the performance of the optical model.

Computer-based monitoring platform for renewable energy systems: Four experimental application cases using NI LabVIEW

Sustainability and responsible environmental behaviour constitute a vital premise in the development of the humankind. In fact, during last decades, the global energetic scenario is evolving towards a scheme with increasing relevance of Renewable Energy Sources (RES) like photovoltaic, wind, biomass and hydrogen. Furthermore, hydrogen is an energy carrier which constitutes a mean for long-term energy storage. The integration of hydrogen with local RES contributes to distributed power generation and early introduction of hydrogen economy. Intermittent nature of many of RES, for instance solar and wind sources, impose the development of a management and control strategy to overcome this drawback. This strategy is responsible of providing a reliable, stable and efficient operation of the system. To implement such strategy, a monitoring system is required.The present paper aims to contribute to experimentally validate LabVIEW as valuable tool to develop monitoring platforms in the field of RES-based facilities. To this aim, a set of real systems successfully monitored is exposed.