725 resultados para Graph-based Learning


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Румен В. Николов - Статията анализира необходимостта от институционални промени в училищата и университетите с цел да се адаптират към съвременните изисквания на обществото на знанието. Паралелно се анализират феноменът на електронното обучение, глобалната образователна реформа и необходимостта от разработването и прилагането на нови педагогически модели. В статията е поставен акцент върху Уеб 2.0 технологиите и електронните инфраструктури, както и върху тяхното влияние върху образованието и научните изледвания в училищата и университетите. Професионална квалификация на учителите, която да е проектирана така, че да отговаря на новите предизвикателства, се разглежда като ключов фактор за успешното навлизане на новите технологии в училище. Важно е да се отбележи необходимостта от разработка на стратегия за обучение на учителите през целия живот, която да отчита съвременните научни постижения в технологично- обогатеното обучение и новите теории за ученето. Препоръчва се изграждането на социални умения и компетенции, които са подходящи за работа в една Уеб 2.0 базирана учебна среда и с глобалния социален софтуер, да се включи в учебните планове и програми както на учениците, така и в курсовете за подготовка на учители.

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Иво Й. Дамянов - Манипулирането на булеви функции е основнo за теоретичната информатика, в това число логическата оптимизация, валидирането и синтеза на схеми. В тази статия се разглеждат някои първоначални резултати относно връзката между граф-базираното представяне на булевите функции и свойствата на техните променливи.

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Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2012

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

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

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Well–prepared, adaptive and sustainably developing specialists are an important competitive advantage, but also one of the main challenges for businesses. One option of the education system for creation and development of staff adequate to the needs is the development of pro jects with topics from real economy ("Practical Projects"). The objective assessment is an essential driver and motivator, and is based on a system of well-chosen, well-defined and specific criteria and indicators. An approach to a more objective evaluation of practical projects is finding more objective weights of the criteria. A natural and reasonable approach is the accumulation of opinions of proven experts and subsequent bringing out the weights from the accumulated data. The preparation and conduction of a survey among recognized experts in the field of project-based learning in mathematics, informatics and information technologies is described. The processing of the data accumulated by applying AHP, allowed us to objectively determine weights of evaluation criteria and hence to achieve the desired objectiveness. ACM Computing Classification System (1998): K.3.2.

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The UK Government and large employers have recognised the skills gap between learners leaving the education system and the requirements of employers. The current system is seen to be failing significant numbers of learners and has been accused of schooling but not educating our young people. University-led technical colleges are one part of the solution being developed to provide outstanding engineering education. This paper focusses on the learning experience that the Aston University Engineering Academy, the first University-led University Technical College (UTC), has created for entrants to the Engineering Academy in September 2012, when it opens in brand new buildings next to the University. The overall aim is to produce technically literate young people that have business and enterprise skills as well as insight into the diverse range of opportunities in Engineering and Technical disciplines. The project has brought University staff and students together with employers and Academy staff to optimise the engineering education that they will receive. The innovative model presented has drawn on research from across the world in the implementation of this new type of school, as well as educational practices from the USA and the Scandinavian countries. The resulting curriculum is authentic and exciting and expands the University model of problem-based learning and placements into the secondary school environment. The benefits of this close partnership for University staff and students, the employers and the Academy staff are expanded on and the paper concludes with a prediction of progression routes from the Academy.

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Student engagement is vital in enhancing the student experience and encouraging deeper learning. Involving students in the design of assessment criteria is one way in which to increase student engagement. In 2011, a marking matrix was used at Aston University (UK) for logbook assessment (Group One) in a project-based learning module. The next cohort of students in 2012 (Group Two) were asked to collaboratively redesign the matrix and were given a questionnaire about the exercise. Group Two initially scored a lower average logbook mark than Group One. However, Group Two showed the greatest improvement between assessments, and the quality of, and commitment to, logbooks was noticeably improved. Student input resulted in a more defined, tougher mark scheme. However, this provided an improved feedback system that gave more scope for self-improvement. The majority of students found the exercise incorporated their ideas, enhanced their understanding, and was useful in itself.

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In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area. © 2011 Springer-Verlag Berlin Heidelberg.

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This paper explores engineering students' perceptions of developing practical competencies as experienced in their industrial placements. In addition, it discusses the criticisms in the literature on Problem Based Learning, Project Based Learning and Conceive-Design-Implement-Operate in relation to the evaluation of effective learning and teaching during placements. The paper goes on to discuss a study which examines how undergraduate engineering students develop practical competencies during their industrial placements. A phenomenological research approach is adopted using in-depth interviews and document analysis. The research findings from this PhD study will contribute to the knowledge, theory and practice for the students, the industries and the institutions of higher education as students' practical competencies are developed and graduate employability rises. In conclusion, this study explores students' experiences of developing practical competencies during industrial placements. Hence, the study should be able to contribute to a set of evidence-based guidelines for higher education institutions and industry.

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It is important to help researchers find valuable papers from a large literature collection. To this end, many graph-based ranking algorithms have been proposed. However, most of these algorithms suffer from the problem of ranking bias. Ranking bias hurts the usefulness of a ranking algorithm because it returns a ranking list with an undesirable time distribution. This paper is a focused study on how to alleviate ranking bias by leveraging the heterogeneous network structure of the literature collection. We propose a new graph-based ranking algorithm, MutualRank, that integrates mutual reinforcement relationships among networks of papers, researchers, and venues to achieve a more synthetic, accurate, and less-biased ranking than previous methods. MutualRank provides a unified model that involves both intra- and inter-network information for ranking papers, researchers, and venues simultaneously. We use the ACL Anthology Network as the benchmark data set and construct the gold standard from computer linguistics course websites of well-known universities and two well-known textbooks. The experimental results show that MutualRank greatly outperforms the state-of-the-art competitors, including PageRank, HITS, CoRank, Future Rank, and P-Rank, in ranking papers in both improving ranking effectiveness and alleviating ranking bias. Rankings of researchers and venues by MutualRank are also quite reasonable.

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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.

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Healthy brain functioning depends on efficient communication of information between brain regions, forming complex networks. By quantifying synchronisation between brain regions, a functionally connected brain network can be articulated. In neurodevelopmental disorders, where diagnosis is based on measures of behaviour and tasks, a measure of the underlying biological mechanisms holds promise as a potential clinical tool. Graph theory provides a tool for investigating the neural correlates of neuropsychiatric disorders, where there is disruption of efficient communication within and between brain networks. This research aimed to use recent conceptualisation of graph theory, along with measures of behaviour and cognitive functioning, to increase understanding of the neurobiological risk factors of atypical development. Using magnetoencephalography to investigate frequency-specific temporal dynamics at rest, the research aimed to identify potential biological markers derived from sensor-level whole-brain functional connectivity. Whilst graph theory has proved valuable for insight into network efficiency, its application is hampered by two limitations. First, its measures have hardly been validated in MEG studies, and second, graph measures have been shown to depend on methodological assumptions that restrict direct network comparisons. The first experimental study (Chapter 3) addressed the first limitation by examining the reproducibility of graph-based functional connectivity and network parameters in healthy adult volunteers. Subsequent chapters addressed the second limitation through adapted minimum spanning tree (a network analysis approach that allows for unbiased group comparisons) along with graph network tools that had been shown in Chapter 3 to be highly reproducible. Network topologies were modelled in healthy development (Chapter 4), and atypical neurodevelopment (Chapters 5 and 6). The results provided support to the proposition that measures of network organisation, derived from sensor-space MEG data, offer insights helping to unravel the biological basis of typical brain maturation and neurodevelopmental conditions, with the possibility of future clinical utility.

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In the discussion - Industry Education: The Merger Continues - by Rob Heiman Assistant Professor Hospitality Food Service Management at Kent State University, the author originally declares, “Integrating the process of an on-going catering and banquet function with that of selected behavioral academic objectives leads to an effective, practical course of instruction in catering and banquet management. Through an illustrated model, this article highlights such a merger while addressing a variety of related problems and concerns to the discipline of hospitality food service management education.” The article stresses the importance of blending the theoretical; curriculum based learning process with that of a hands-on approach, in essence combining an in-reality working program, with academics, to develop a well rounded hospitality student. “How many programs are enjoying the luxury of excessive demand for students from industry [?],” the author asks in proxy for, and to highlight the immense need for qualified personnel in the hospitality industry. As the author describes it, “An ideal education program concerns itself with the integration of theory and simulation with hands-on experience to teach the cognitive as well as the technical skills required to achieve the pre-determined hospitality education objectives.” In food service one way to achieve this integrated learning curve is to have the students prepare foods and then consume them. Heiman suggests this will quickly illustrate to students the rights and wrongs of food preparation. Another way is to have students integrating the academic program with feeding the university population. Your author offers more illustrations on similar principles. Heiman takes special care in characterizing the banquet and catering portions of the food service industry, and he offers empirical data to support the descriptions. It is in these areas, banquet and catering, that Heiman says special attention is needed to produce qualified students to those fields. This is the real focus of the discussion, and it is in this venue that the remainder of the article is devoted. “Based on the perception that quality education is aided by implementing project assignments through the course of study in food service education, a model description can be implemented for a course in Catering and Banquet Management and Operations. This project model first considers the prioritized objectives of education and industry and then illustrates the successful merging of resources for mutual benefits,” Heiman sketches. The model referred to above is also the one aforementioned in the thesis statement at the beginning of the article. This model is divided into six major components; Heiman lists and details them. “The model has been tested through two semesters involving 29 students,” says Heiman. “Reaction by all participants has been extremely positive. Recent graduates of this type of program have received a sound theoretical framework and demonstrated their creative interpretation of this theory in practical application,” Heiman says in summation.

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Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^