Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection

T.Boongoen and Q. Shen. Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection. Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09), pp. 288-293, 2009. Sponsorship: EPSRC

Cultivating creative learners in higher education: Engaging students in anatomy through art

Introduction
Nursing and midwifery students often struggle to engage with bioscience modules because they lack confidence in their ability to study science (Fell et al., 2012). Consequently many have difficulty applying anatomical and physiological information, essential to providing safe and effective patient care (Rogers, 2014; Rogers and Sterling, 2012); therefore a need exists for nurse educators to explore different methods of delivery of these important topics to enhance current curricula (Johnston, 2010). Inspired by the reported success of creative methods to enhance the teaching and learning of anatomy in medical education (Noel, 2013; Finn and McLachlan, 2010), this pilot study engaged nursing students in anatomy through the art of felt. The project was underpinned by the principles of good practice in undergraduate education, staff-student engagement, cooperation among students, active learning, prompt feedback, time on task, high expectations and respect for diverse learning styles (Chickering and Gamson, 1987).

Method
Undergraduate student nurses from Queen’s University, Belfast, enrolled in the year one ‘Health and Wellbeing’ model were invited to participate in the project. Over a six week period the student volunteers worked in partnership with teaching staff to construct individual, unique, three dimensional felt models of the upper body. Students researched the agreed topic for each week in terms of anatomical structure, location, tissue composition and vascular access. Creativity was encouraged in relation to the colour and texture of materials used. The evaluation of the project was based on the four level model detailed by Kirkpatrick and Kirkpatrick (2006) and included both quantitative and qualitative analysis:• pre and post knowledge scores• self-rated confidence• student reflections on the application of learning to practice.

Results
At the end of the project students had created felt pieces reflective of their learning throughout the project and ‘memorable’ three dimensional mental maps of the human anatomy. Evaluation revealed not only acquisition of anatomical knowledge, but the wider benefits of actively engaging in creative learning with other students and faculty teaching staff.

The project has enabled nurse educators to assess the impact of innovative methods for delivery of these important topics.

Evaluation of the matabolic response of osteosarcoma cells to conventional and new anticancer drugs by NMR metabolomics

The main scope of this work was to evaluate the metabolic effects of anticancer agents (three conventional and one new) in osteosarcoma (OS) cells and osteoblasts, by measuring alterations in the metabolic profile of cells by nuclear magnetic resonance (NMR) spectroscopy metabolomics. Chapter 1 gives a theoretical framework of this work, beginning with the main metabolic characteristics that globally describe cancer as well as the families and mechanisms of action of drugs used in chemotherapy. The drugs used nowadays to treat OS are also presented, together with the Palladium(II) complex with spermine, Pd2Spm, potentially active against cancer. Then, the global strategy for cell metabolomics is explained and the state of the art of metabolomic studies that analyze the effect of anticancer agents in cells is presented. In Chapter 2, the fundamentals of the analytical techniques used in this work, namely for biological assays, NMR spectroscopy and multivariate and statistical analysis of the results are described. A detailed description of the experimental procedures adopted throughout this work is given in Chapter 3. The biological and analytical reproducibility of the metabolic profile of MG-63 cells by high resolution magic angle spinning (HRMAS) NMR is evaluated in Chapter 4. The metabolic impact of several factors (cellular integrity, spinning rate, temperature, time and acquisition parameters) on the 1H HRMAS NMR spectral profile and quality is analysed, enabling the definition of the best acquisition parameters for further experiments. The metabolic consequences of increasing number of passages in MG-63 cells as well as the duration of storage are also investigated. Chapter 5 describes the metabolic impact of drugs conventionally used in OS chemotherapy, through NMR metabolomics studies of lysed cells and aqueous extracts analysis. The results show that MG-63 cells treated with cisplatin (cDDP) undergo a strong up-regulation of lipid contents, alterations in phospholipid constituents (choline compounds) and biomarkers of DNA degradation, all associated with cell death by apoptosis. Cells exposed to doxorubicin (DOX) or methotrexate (MTX) showed much slighter metabolic changes, without any relevant alteration in lipid contents. However, metabolic changes associated with altered Krebs cycle, oxidative stress and nucleotides metabolism were detected and were tentatively interpreted at the light of the known mechanisms of action of these drugs. The metabolic impact of the exposure of MG-63 cells and osteoblasts to cDDP and the Pd2Spm complex is described in Chapter 6. Results show that, despite the ability of the two agents to bind DNA, the metabolic consequences that arise from exposure to them are distinct, namely in what concerns to variation in lipid contents (absent for Pd2Spm). Apoptosis detection assays showed that, differently from what was seen for MG-63 cells treated with cDDP, the decreased number of living cells upon exposure to Pd2Spm was not due to cell death by apoptosis or necrosis. Moreover, the latter agent induces more marked alterations in osteoblasts than in cancer cells, while the opposite seemed to occur upon cDDP exposure. Nevertheless, the results from MG-63 cells exposure to combination regimens with cDDP- or Pd2Spm-based cocktails, described in Chapter 7, revealed that, in combination, the two agents induce similar metabolic responses, arising from synergy mechanisms between the tested drugs. Finally, the main conclusions of this thesis are summarized in Chapter 8, and future perspectives in the light of this work are presented.

Most Significant Change in conflict settings: staff development through monitoring and evaluation

Capoeira4Refugees is an NGO that uses the Afro-Brazilian art-form of Capoeira to promote psychosocial well-being in children affected by conflict and occupation. Capoeira4Refugees introduced the Most Significant Change (MSC) methodology to monitor and evaluate project implementation and impact across two locations in the Middle East. Analysis of interviews conducted with five field staff revealed that in line with, and building on previous research, MSC became an empowering tool that led to staff development. The potential for MSC to build staff reflexivity, independence and leadership has implications for other organisations working in conflict areas, particularly in situations of remote management.

Evaluation and Potential Cost-Effectiveness of Active Surveillance Pharmacovigilance for First-Line HAART in Namibia

Thesis (Ph.D.)--University of Washington, 2016-02

Design and evaluation of multi-band RF energy harvesting circuits and antennas for WSNs

Radio frequency (RF) energy harvesting is an emerging technology that will enable to drive the next generation of wireless sensor networks (WSNs) without the need of using batteries. In this paper, we present RF energy harvesting circuits specifically developed for GSM bands (900/1800) and a wearable dual-band antenna suitable for possible implementation within clothes for body worn applications. Besides, we address the development and experimental characterization of three different prototypes of a five-stage Dickson voltage multiplier (with match impedance circuit) responsible for harvesting the RF energy. Different printed circuit board (PCB) fabrication techniques to produce the prototypes result in different values of conversion efficiency. Therefore, we conclude that if the PCB fabrication is achieved by means of a rigorous control in the photo-positive method and chemical bath procedure applied to the PCB it allows for attaining better values for the conversion efficiency. All three prototypes (1, 2 and 3) can power supply the IRIS sensor node for RF received powers of -4 dBm, -6 dBm and -5 dBm, and conversion efficiencies of 20, 32 and 26%, respectively. © 2014 IEEE.

A director’s approach to art and religion : o quadro, um musical da Paixão segundo o sr. João (The masterpiece, a musical of The passion according to John): trabalho de projecto

Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Encenação.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Developmental patterns of individiuals within a sensory-based learning environment in art education : insights emerging from a case study /

My research permitted me to reexamine my recent evaluations of the Leaf Project given to the Foundation Year students during the fall semester of 1997. My personal description of the drawing curriculum formed part of the matrix of the Foundation Core Studies at the Ontario College of Art and Design. Research was based on the random selection of 1 8 students distributed over six of my teaching groups. The entire process included a representation of all grade levels. The intent of the research was to provide a pattern of alternative insights that could provide a more meaningful method of evaluation for visual learners in an art education setting. Visual methods of learning are indeed complex and involve the interplay of many sensory modalities of input. Using a qualitative method of research analysis, a series of queries were proposed into a structured matrix grid for seeking out possible and emerging patterns of learning. The grid provided for interrelated visual and linguistic analysis with emphasis in reflection and interconnectedness. Sensory-based modes of learning are currently being studied and discussed amongst educators as alternative approaches to learning. As patterns emerged from the research, it became apparent that a paradigm for evaluation would have to be a progressive profile of the learning that would take into account many of the different and evolving learning processes of the individual. A broader review of the student's entire development within the Foundation Year Program would have to have a shared evaluation through a cross section of representative faculty in the program. The results from the research were never intended to be conclusive. We realized from the start that sensory-based learning is a difficult process to evaluate from traditional standards used in education. The potential of such a process of inquiry permits the researcher to ask for a set of queries that might provide for a deeper form of evaluation unique to the students and their related learning environment. Only in this context can qualitative methods be used to profile their learning experiences in an expressive and meaningful manner.

Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Evaluation of five guidelines for option development in multiple-choice item-writing. 'Evaluaci??n de cinco directrices para la construcci??n de opciones en ??tems de elecci??n m??ltiple'

Resumen tomado de la publicaci??n

Evaluaci??n de las medidas de atenci??n a la diversidad de la educaci??n primaria en Galicia : impacto escolar. 'Evaluation of the measures of attention to the diversity in the primary education in Galicia : school impact'

Resumen tomado de la publicaci??n. Con el apoyo econ??mico del departamento MIDE de la UNED

Learning objects management and evaluation in an e-learning environment. 'Objetos de gesti??n de aprendizaje y evaluaci??n en un entorno de e-learning'

Monogr??fico con el t??tulo: 'Estado actual de los sistemas e-learning'. Resumen basado en el de la publicaci??n

Evaluation of the cognitive-behavioral model of generalized and problematic Internet use in Spanish adolescents

Resumen tomado de la publicaci??n

Evaluation of satisfaction in an extracurricular enrichment program for high-intellectual ability participants

Resumen tomado de la publicaci??n