Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterisation of powders using microwave cavity perturbation

The contribution in this thesis is a novel application of microwave cavity perturbation in the characterisation of the fundamental properties of powders. This thesis shows that microwave cavity perturbation is very good at characterising the magnetite to maghemite phase change through dielectric and magnetic measurements. This is very important in material science since conventional techniques, though powerful and are able to verify the change, use complex methods. Quantifying di�erent forms of magnetite and maghemite is important for magnetic drug delivery and EMI absorbers. This thesis shows that microwave cavity perturbation can be used to measure the impurities of nanodiamonds through simple dielectric measurements. This is important because other methods again may involve complex systems, while microwave cavity perturbation can provide a fast, sensitive �gure of merit. Nanodiamonds are used in drug delivery and bio-labelling which requires accurate surface characterisation. This thesis shows that microwave cavity perturbation can measure in-situ temperature dependent and photocatalytic responses in materials such as titania using a novel correction procedure. Microwave cavity perturbation has not been used with this correction procedure before which simpli�es the system when monitoring systematic errors. This work is important as it shows how simple microwave cavity perturbation systems can provide insight to thermally activated processes and veri�cation of some photocatalytic mechanisms in powders for use in pigmentation and light induced drug delivery.
Determination of the Mechanical Properties of Composite Materials by Tensile Tests. Part II: Strength Properties

A new data evaluation scheme is presented for the measurement of tensile strengths at different angles. The method is applicable for all composite materials that follow the Tsai-Wu failure criterion. It is general in the sense that it can be used for both tri-clinic and monoclinic or higher symmetry materials. With this method, tensile strength data at different angles can be made consistent. It is also shown that the shear strength can be determined by tensile tests if in addition a biaxial test and two or three compression tests (for respectively monoclinic or higher symmetry and triclinic materials) are performed. As an example, the method is applied to a glass/epoxy woven fabric composite and two types of knitted fabric composites. The best test angles to determine the strength parameters for these materials happen to be the same angles that were optimal for the determination of the elastic properties.
Relationship between hours spent on the Internet and Web 2.0 in Higher Education

This article analyses the relationship between the number of hours spent by university students on the Internet and their attitude, training, use, impact and perception of difficulties in Web 2.0 integration, as well as their knowledge and use of Web 2.0 tools in Higher Education. To this end, we used a Likert scale applied to a sample of 403 students from the University of Huelva (UHU), Spain. To test the hypothesis, we conducted a one-way ANOVA with post hoc comparisons. The results obtained partially confirmed the general hypothesis. The greatest differences were found in the factors of impact and use of Web 2.0 tools, whereas the least differences were found in the factors of attitude, training, difficulties and knowledge of Web 2.0 tools.ResumenEl presente artículo analiza la relación existente entre el número de horas diarias que el alumnado universitario dedica a internet y la actitud, formación, uso, impacto, perceptción de dificultades de la integración de la web 2.0, así como el conocimiento y uso de herramientas de la web 2.0 en educación universitaria. Para ello hemos usado una escala tipo Likert aplicada a una muestra de 403 alumnos de la Universidad de Huelva. Para contrastar la hipótesis realizamos una ANOVA de un factor con comparaciones post hoc. Los resultados obtenidos permiten confirmar parcialmente la hipótesis general. Las diferencias mayores se observan en los factores de impacto y uso de herramientas de la web 2.0, mientras que las diferencias menores se observan en los factores de actitud, formation, dificultades y conocimiento de herramientas de la web 2.0.
LOCALIZATION OF GHRELIN IN THE EPITHELIAL CELLS OF THE DUODENUM IN THE RAT

Ghrelin is a hormone discovered relatively recently, the effect of which is associated with the normal activity of the digestive tract. It is the most abundant in the gastric mucosa, but also occurs in other parts of the digestive system, sexual organs and some glands. Many authors associate the action of ghrelin with appetite and weight gain or weight loss. The purpose of this study was by immunohistochemical methods to localize grelin-pozitive cells in the duodenal mucosa and comparatively to determine their amount. We use Ghrelin (H-40) antibody (Santa Cruz-USA), and for the visualization of the results - detection system EnVisionTM FLEX Mini Kit, High Ph (DAKO - k8024 HRP). Histomorphometric study performed by Michael Vinther Image Analyzer, Version 1.33 (Mee Soft, Germany).
Symmetric Language-Aware Aspects for Modular Code Generators

Model-driven engineering, especially using domain-specific languages, allows constructing software from abstractions that are more closely fitted to the problem domain and that better hide technical details of the solution space. Code generation is used to produce executable code from these abstractions, which may result in individual concerns being scattered and tangled throughout the generated code. The challenge, then, becomes how to modularise the code-generator templates to avoid scattering and tangling of concerns within the templates themselves. This paper shows how symmetric, language-aware approaches to aspect orientation can be applied to code generation and how this improves modularisation support, in particular reducing dependencies between code-generation templates, over previously proposed asymmetric aspect-oriented approaches.
Extracting Cognition out of Images for the Purpose of Autonomous Driving

Autonomous driving is a broadly recognized solution to serious traffic problems such as accidents and congestions. It is a very broad topic that extends across cognition, artificial intelligence, and control. While this thesis primarily focuses on the cognition aspect, others are also considered. Here, the thesis proposes several computer vision algorithms for autonomous driving, encompassing three major parts: In part one, experiments on motion-based object recognition are presented. The proposed method differentiates objects according to their speed. In part two, the artificial intelligence aspect of autonomous driving is considered. Research on training an autonomous driving AI agent through reinforcement learning is introduced. In part three, the key part of the thesis, a direct perception approach is proposed to drive a car in a highway environment. In this approach, an input image is mapped to a small number of key perception indicators that directly relate to the affordance of a road/traffic state for driving. This representation provides a set of compact yet complete descriptions of the scene to enable a simple controller to drive autonomously on highways. Using synthetic images from a virtual environment, a deep convolutional neural network (ConvNet) is trained for direct perception. Experiments show that the model can effectively drive a car in a very diverse set of virtual environments, and it provides good estimation of affordance indicators from real driving images. To further improve the performance of the direct perception-based system, the issue of temporal information is considered by studying the Long Short Term Memory (LSTM) unit and its influence on the affordance indicator estimation. Quantitative results show that adding the LSTM unit does help to improve the system’s performance. Finally, as object detection is closely related to autonomous driving, in Appendix A a deep learning-based small object detection approach is proposed. The applicability of the state-of-the-art object detection algorithms to the small object detection task is studied. iii
Method for inspection of frame digital aerial photographic quality

At present,the aerial photographic quality inspection still uses the traditional method to check the digital frame images' quality,which prints the digital images on paper first and then checks them manually. The method greatly limits the advantages of digital aerial photography. This paper presents a fully digital aerial photographic quality inspection method,whose whole process is fully completed on computer. Firstly,index images are used to complete the image quality inspection,Then the aerial photography flight quality inspection software and airborne POS( position and orientation system) data are employed to check such quality factors as overlap,swing angle,strip deformation,and flying height,Finally,relevant documentation is collated and prepared according to the results. In order to verify the reliability and scientificalness of this method,the authors selected the manual quality inspection results of Hengyang area in Hunan Province to make comparison and analysis. The results show that this method can actually reflect the flight quality of aerial photography,is in good consistency with manual results,and has some other advantages such as simple operation,high efficiency and low cost.
Latin American university students’ perceptions of social networks and group work

In recent years, the Internet and Web 2.0 tools have played a fairly pivotal role in university education. Social software tools have stood out in particular, with social networks attracting the most attention. In the field of education, social networks have gradually become a highly valuable didactic resource because the students who populate today’s university classrooms also live out a large part of their lives on those networks. Student group work is a cornerstone of the constructivist view of teaching, which can draw on resources of this type because, among other things, they foster socialisation, information searching, the attainment of a common goal, etc. But, for all of this to happen, students must have positive attitudes towards group work. This article presents the results of a study on university students’ level of knowledge of social networks and their perceptions of group work. It was conducted on a sample of students from Argentina, Spain, the Dominican Republic and Venezuela. The findings particularly show that the students held high perceptions of group work and of the opportunity to work online with fellow students from different geographical areas.ResumenEn los últimos tiempos la formación universitaria ha estado bastante centrada en el entorno de internet y de las herramientas de la web 2.0. Destacan dentro de este entramado las clasificadas como software social, siendo las redes sociales las que más atención despiertan. En el ámbito educativo las redes sociales se han ido dibujando como un recurso de gran valor didáctico, dado que los estudiantes que hoy habitan las aulas universitarias viven inmersos en ellas. La visión constructivista de la enseñanza, apoyada fundamentalmente en el trabajo en grupo de los estudiantes, puede alimentarse a través de este tipo de recursos, debido a que potencia, entre otros aspectos, la socialización, la búsqueda de información, el logro de una meta común, etc.; pero para ello el alumno debe tener actitudes positivas para trabajar en grupo. En este trabajo, realizado con estudiantes de Argentina, España, República Dominicana y Venezuela, exponemos los resultados obtenidos en un estudio sobre el grado de conocimiento que tiene el alumnado respecto a las redes sociales y sus percepciones para trabajar en grupo. Entre los hallazgos encontrados destaca que los estudiantes tienen una elevada percepción respecto al trabajo en grupo, junto con la posibilidad de trabajar online con compañeros que no están en su misma zona geográfica
Adaptive sequential feature selection in visual perception and pattern recognition

In the human visual system, one of the most prominent functions of the extensive feedback from the higher brain areas within and outside of the visual cortex is attentional modulation. The feedback helps the brain to concentrate its resources on visual features that are relevant for recognition, i. e. it iteratively selects certain aspects of the visual scene for refined processing by the lower areas until the inference process in the higher areas converges to a single hypothesis about this scene.
The Numb er of Proportional Analogies between Marker-based Chunks in 11 European Languages

An example-based machine translation (EBMT) system based on proportional analogies requires numerous proportional analogies between linguistic units to work properly. Consequently, long sentences cannot be handled directly in such a framework. Cutting sentences into chunks would be a solution. Using different markers, we count the number of proportional analogies between chunks in 11 European languages. As expected, the number of proportional analogies between chunks is very high. Whereas samples of thousand English sentences from the Europarl corpus do not lead to any analogy between sentences, we obtain several tens of thousands of analogies between the chunks extracted from these sentences using 10 markers. These results are very promising for the EBMT system that we intend to build.
Compact, Adaptive and Discriminative Spatial Pyramid for Improved Scene and Object Classification

The release of challenging datasets with a vast number of images, requires the development of efficient image representations and algorithms which are able to manipulate these largescale datasets efficiently. Nowadays the Bag-of-Words (BoW) based image representation is the most successful approach in the context of object and scene classification tasks. However, its main drawback is the absence of the important spatial information. Spatial pyramids (SP) have been successfully applied to incorporate spatial information into BoW-based image representation. The main SP approach, works by repeatedly sub-dividing the image into increasingly finer sub-regions by doubling the number of divisions on each axis direction, and further computing histograms of features over the resulting sub-regions. Observing the remarkable performance of spatial pyramids, their growing number of applications to a broad range of vision problems, and finally its geometry inclusion, a question can be asked what are the limits of spatial pyramids. Within the SP framework, the optimal way for obtaining an image spatial representation which is able to cope with it’s most foremost shortcomings, concretely, it’s high dimensionality and the rigidity of the resulting image representation still remains an active research domain. In summary, the main concern of this thesis is to search for the limits of spatial pyramids and try to figure out solutions for them. This thesis explores the problem of obtaining compact, adaptive, yet informative spatial image representations in the context of object and scene classification tasks. In the first part of this thesis, we first analyze the implications of directly applying the state-of-the-art compression techniques for obtaining compact BoW-based image representation within the context of spatial pyramids. We then introduce a novel SP compression technique that works on two levels; (i) compressing the least informative spatial pyramid features, followed by, (ii) compressing the least informative SP regions for the purpose of obtaining compact, and adaptable SP. We then introduce a new texture descriptor that represents local image texture and its spatial layout. Texture is represented as a compact vector descriptor suitable for use in standard learning algorithms with kernels. Experimental results show that texture information has similar classification performances and sometimes outperforms those methods using only shape or appearance information. The resulting spatial pyramid representation demonstrates signif-
Phonology And Morphology Of The Ciyao Verb

Thank you very much for downloading phonology and morphology of the ciyao verb. As you may know, people have search hundreds times for their chosen readings like this phonology and morphology of the ciyao verb, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some malicious bugs inside their desktop computer. phonology and morphology of the ciyao verb is available in our digital library an online access to it is set as public so you can download it instantly. Our book servers hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the phonology and morphology of the ciyao verb is universally compatible with any devices to read.
Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model

Deep neural network (DNN) based natural language processing models rely on a word embedding matrix to transform raw words into vectors. Recently, a deep structured semantic model (DSSM) has been proposed to project raw text to a continuously-valued vector for Web Search. In this technical report, we propose learning word embedding using DSSM. We show that the DSSM trained on large body of text can produce meaningful word embedding vectors as demonstrated on semantic word clustering and semantic word analogy tasks.
Survey and classification of network-on-chip

Formal description of NoC architectures and applications were provided,then enumerated several related re-search problems and clarified the relationship between them.They are classified as four categories: application modeling and optimizing,communication pattern,communication infrastructure,solution evaluation and verification.Problem de-scription,proposed approaches and open problems of major issues are discussed.Finally,summarized the whole work and presented the perfect of the future.
On the Composition of Academic Work in Digital Times

Over the last two decades, a sense of awareness has arisen that universities are facing important challenges. This article focuses on the challenge that could be broadly termed as ‘the digitisation of academic work’, yet without assuming that this digitisation would be an explanatory factor clarifying the precise nature of contemporary academic work. On the contrary, and adopting a relational actor-network theory (ANT) approach, this article stresses the concrete composition of academic work without making any general presumptions regarding how the university looks at present. Furthermore, by introducing a specific interview technique as methodological approach and different visualisations as (qualitative) analytical approach, this article offers a threefold exploratory textual and visual analysis of academic practice in the making. The article concludes, firstly, that it makes not much sense any more to talk about academic practice in terms of humans or non-humans, material or digital, etc. Instead, perhaps it makes more sense to speak of actors in academic practice as being humandigital. Secondly, the article concludes that sociomaterial approaches might constitute a fruitful addition to more traditional research about the university that is inclined to focus on epochal changes that are suggested or expected to alter the position of academics and the university.
The use of massively multiplayer online role-playing games in CALL: an analysis of research

ABSTRACT Contemporary CALL research reflects renewed interest in digital games. One aspect of this phenomenon namely, use of massively multiplayer online role-playing games (MMORPGs), has expanded significantly, highlighting the need for a review. This paper analyzes findings from 10 learner-based studies that draw on accounts of SLA informed by cognitive and sociocultural theories. Analysis reveals that research conducted from the sociocultural perspective provides evidence of constructs identified as playing a central role in SLA. Analysis indicates that playing MMORPGs elicits target language dialogue involving collaboration, assistance and co-construction. Data show that MMORPGs provide access to conditions conducive to the operation of zones of proximal development. Findings show that this type of game provides access to both in-game and extramural communities of practice that facilitate language socialization. Research undertaken from a cognitive perspective shows that participation in MMORPG-based gaming facilitates production of the target language. However, this work does not provide conclusive evidence that game play elicits forms of interaction such as negotiation, that are hypothesized as playing a central role in learning in the cognitive account of SLA. Studies conducted from both perspectives draw attention to positive learner attitudes indicating high levels of motivation. The analysis reveals that although studies are subject to limitations, they have produced promising results. This suggests that further theory-led work in this area is justified, as it offers the prospect of making a significant contribution to the research base. As work continues, areas of potential interest in praxis, theory and future research are identified.
Preparing student teachers to integrate web 2.0 technology in their T&L through meaningful learning

Web 2.0 technology is gaining its reputation in the education context and seen as an important approach for teaching and learning in the 21st century.Teachers in the developed countries such as UK and US have been using Web 2.0 in their teaching and learning practice for nearly a decade.Yet, in Malaysia, the integration of Web 2.0 technology is still in its infancy.Teachers and students are using Web 2.0 tools in their daily life such as Facebook, Twitter and Instagram, but it is more for social networking. Considering these issues, it is crucial to prepare our student teachers with the necessary technology and pedagogical skills to successfully integrate Web 2.0 tools in their future teaching practice. Through the Scholarship of Teaching and Learning (SoTL), underpinned by meaningful learning theory, this paper shares on student teachers’ reflection towards their exploration and experience with Web 2.0 technology.
Information Retrieval from Digital Libraries: Assessing the Potential Utility of Thesauri in Supporting Users' Search Behaviour in an Interdisciplinary Domain

The objective of this research was to investigate the extent to which thesauri have the potential to support the search behaviour of nanoscience and technology researchers while interacting with an electronic book digital library. Transaction log data was obtained from a nanoscience and technology digital library to investigate the nature, type and characteristics of users' queries and search terms. The specific objectives was to assess the extent to which users' search terms matched with those found in two well-established thesauri attached o the INSPEC and Compendex databases.
Support vector machines for pattern recognition

An overview of the basic ideas underlying Support Vector Machine (SVM) for pattern recognition was given. New methods such as ν - SVM, LS- SVM, weighted SVM and direct SVM, training algorithms including chunking method and decomposition method for the sake of fast computational speed and ease of implementation, model selection approaches minimizing the generalization error, and multiclass classification methods such as one- against- the- rest method, one- against- one method, M- ary classification were concentrated. Finally, an example of multiclass classification for monitoring operation status of wastewater treatment processes was given. As a direct implementation of the structure risk minimization (SRM) inductive principle, SVM provides good performances such as global optimization and good generalization ability.