791 resultados para Multicriteria Collaborative Filtering


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This dissertation presents a case study of collaborative research through design with Floracaching, a gamified mobile application for citizen science biodiversity data collection. One contribution of this study is the articulation of collaborative research through design (CRtD), an approach that blends cooperative design approaches with the research through design methodology (RtD). Collaborative research through design is thus defined as an iterative process of cooperative design, where the collaborative vision of an ideal state is embedded in a design. Applying collaborative research through design with Floracaching illustrates how a number of cooperative techniques—especially contextual inquiry, prototyping, and focus groups—may be applied in a research through design setting. Four suggestions for collaborative research through design (recruit from a range of relevant backgrounds; take flexibility as a goal; enable independence and agency; and, choose techniques that support agreement or consensus) are offered to help others who wish to experiment with this new approach. Applying collaborative research through design to Floracaching yielded a new prototype of the application, accompanied by design annotations in the form of framing constructs for designing to support mobile, place-based citizen science activities. The prototype and framing constructs, which may inform other designers of similar citizen science technologies, are a second contribution of this research.

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The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whilst communication between spines is mediated by the cable equation. In this paper we develop a computational framework that allows the study of multiple spiking events in a network of such spines embedded on a simple one-dimensional cable. In the first instance this system is shown to support saltatory waves with the same qualitative features as those observed in a model with Hodgkin-Huxley kinetics in the spine-head. Moreover, there is excellent agreement with the analytically calculated speed for a solitary saltatory pulse. Upon driving the system with time varying external input we find that the distribution of spines can play a crucial role in determining spatio-temporal filtering properties. In particular, the SDS model in response to periodic pulse train shows a positive correlation between spine density and low-pass temporal filtering that is consistent with the experimental results of Rose and Fortune [1999, Mechanisms for generating temporal filters in the electrosensory system. The Journal of Experimental Biology 202, 1281-1289]. Further, we demonstrate the robustness of observed wave properties to natural sources of noise that arise both in the cable and the spine-head, and highlight the possibility of purely noise induced waves and coherent oscillations.

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One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

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Chamber music with piano comprises some of the greatest masterpieces in the Western canon. The works range from duo sonatas with various instruments through septets. In regard to duo sonatas, the violin is the instrument most frequently paired with the piano. Of all the chamber works for larger ensembles, the most popular is the quintet. In this dissertation, I will be exploring the similarities and differences between the duo sonatas and quintets of a given composer. I will be surveying Robert Schumann’s Piano Quintet in E-flat Major, Op. 44 along with his Violin and Piano Sonata in A Minor, Op. 105. The next pairing will be Johannes Brahms’ Piano Quintet in F Minor, Op. 34 and his Piano and Violin Sonata in D Minor, Op. 108. Dmitri Shostakovich’s Piano Quintet in G Minor, Op. 57 and his Cello and Piano Sonata in D Minor, Op. 40 will be the last two works examined in this dissertation. This dissertation project consisted of three recitals, presented in the Gildenhorn Recital Hall at the Clarice Smith Performing Arts Center of the University of Maryland. The recitals featured works by Johannes Brahms, Robert Schumann and Dmitri Shostakovich and took place on March 14, 2014, February 13, 2015 and November 22, 2015. All three recitals were recorded on compact discs, which can be accessed at the Digital Repository at the University of Maryland (DRUM) and at the University of Maryland Hornbake Library.

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The Multicriteria decision analysis is a tool to support decision-making in the identification of areas with the utmost beekeeping potential. This paper design a GIS multicriteria approach to assess the beekeeping potential. The development of a conceptual model structure requires the participation of stakeholders and experts in that process. The spatial Multicriteria Decision Analysis (MCDA) allowed defining the potential beekeeping map. The resulting maps can be used by the beekeepers associations to easily select the more suitable areas for the apiaries location or relocation and avoid prohibited areas by legal requirements.

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Sergei Rachmaninoff and Nikolai Medtner occupy a special place in the history of Russian music. Both composers were exceptional pianists and left us some of the greatest works in the piano repertoire. Although these composers shared many similarities, and were often compared, their musical languages and views on composition were very different. Unfortunately, Medtner’s music, which Rachmaninoff admired greatly, has remained neglected for several generations of performers and listeners. In my dissertation I will explore the similarities and contrasts in Rachmaninoff’s and Medtner’s music. Through these performances, I hope to encourage other musicians to discover the imaginative power of Medtner’s music. Of course, no such encouragement is needed for Rachmaninoff’s extremely popular music; however, the technical and musical challenges of performing that repertoire are an invaluable part of every pianist’s education. This dissertation project was presented in three recitals which were performed in Gildenhorn Recital Hall at the Clarice Smith Performing Arts Center of the University of Maryland on May 8, 2014, December 5, 2014 and March 21, 2016. The following pieces comprised the survey of Rachmaninoff music: Vocalise Op. 34, Variations on a Theme of Corelli Op. 42, Piano Concerto No 2 Op. 18, Selected Songs Opp. 4 and 8, and two Moments Musicaux Op. 16 - Nos 3 and 4. The following pieces were included to represent Medtner: Sonata for Violin and Piano Op. 57 in E minor “Epica”, Fairy Tales for solo piano Op. 20 No 1, Op. 26 No 3 and Op. 51 No 1, and Selected Songs Op. 6 and 15. My partners in this project were Lilly Ahn, soprano, Jennifer Lee, violin and Nadezhda Christova, piano. All three recitals can be found in the Digital Repository at the University of Maryland (DRUM).

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Recent research on affective processing has suggested that low spatial frequency information of fearful faces provide rapid emotional cues to the amygdala, whereas high spatial frequencies convey fine-grained information to the fusiform gyrus, regardless of emotional expression. In the present experiment, we examined the effects of low (LSF, <15 cycles/image width) and high spatial frequency filtering (HSF, >25 cycles/image width) on brain processing of complex pictures depicting pleasant, unpleasant, and neutral scenes. Event-related potentials (ERP), percentage of recognized stimuli and response times were recorded in 19 healthy volunteers. Behavioral results indicated faster reaction times in response to unpleasant LSF than to unpleasant HSF pictures. Unpleasant LSF pictures and pleasant unfiltered pictures also elicited significant enhancements of P1 amplitudes at occipital electrodes as compared to neutral LSF and unfiltered pictures, respectively; whereas no significant effects of affective modulation were found for HSF pictures. Moreover, mean ERP amplitudes in the time between 200 and 500ms post-stimulus were significantly greater for affective (pleasant and unpleasant) than for neutral unfiltered pictures; whereas no significant affective modulation was found for HSF or LSF pictures at those latencies. The fact that affective LSF pictures elicited an enhancement of brain responses at early, but not at later latencies, suggests the existence of a rapid and preattentive neural mechanism for the processing of motivationally relevant stimuli, which could be driven by LSF cues. Our findings confirm thus previous results showing differences on brain processing of affective LSF and HSF faces, and extend these results to more complex and social affective pictures.

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Writing instruction in Canadian universities takes a variety of forms. While there are few formal departments for writing studies, many institutions do have a writing centre – a place that offers writing instruction to varying degrees. The writing centre may be housed within a department, a library, or within a student services unit. Its position within a university may indicate the degree to which writing is valued by the administrative body. The goal of our paper is to share insights into the ways that writing professionals perceive, work in, and adapt to current demands for writing instruction in higher education. Using a collaborative ethnographic approach, three scholars at different career stages explore their experiences with writing centre work. Using data consisting of individually written reflections, our analysis revealed four major themes: (a) initial experience with writing centres, (b) community, (c) frustrations and tensions at work, and (d) mentorship. In this paper, we discuss our findings within the framework of positioning theory in order to understand how we position ourselves as scholars, mentors, and educators, and how we are positioned by others within the fields of writing studies and higher education. This study raises awareness about the value of writing centre professionals’ contributions, the place of mentorship within higher education, and the support required for continued writing centre work.

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Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

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Students often receive instruction from specialists, professionals other than their general educators, such as special educators, reading specialists, and ESOL (English Speakers of Other Languages) teachers. The purpose of this study was to examine how general educators and specialists develop collaborative relationships over time within the context of receiving professional development. While collaboration is considered essential to increasing student achievement, improving teachers’ practice, and creating comprehensive school reform, collaborative partnerships take time to develop and require multiple sources of support. Additionally, both practitioners and researchers often conflate collaboration with structural reforms such as co-teaching. This study used a retrospective single case study with a grounded theory approach to analysis. Data were collected through semi-structured interviews with thirteen teachers and an administrator after three workshops were conducted throughout the school year. The theory, Cultivating Interprofessional Collaboration, describes how interprofessional relationships grow as teachers engage in a cycle of learning, constructing partnership, and reflecting. As relationships deepen some partners experience a seamless dimension to their work. A variety of intrapersonal, interpersonal, and external factors work in concert to promote this growth, which is strengthened through professional development. In this theory, professional development provides a common ground for strengthening relationships, knowledge about the collaborative process, and a reflective space to create new collaborative practices. Effective collaborative practice can lead to aligned instruction and teachers’ own professional growth. This study has implications for school interventions, professional development, and future research on collaboration in schools.