974 resultados para Clifford Algebra


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Green energy is one of the key factors, driving down electricity bill and zero carbon emission generating electricity to green building. However, the climate change and environmental policies are accelerating people to use renewable energy instead of coal-fired (convention type) energy for green building that energy is not environmental friendly. Therefore, solar energy is one of the clean energy solving environmental impact and paying less in electricity fee. The method of solar energy is collecting sun from solar array and saves in battery from which provides necessary electricity to whole house with zero carbon emission. However, in the market a lot of solar arrays suppliers, the aims of this paper attempted to use superiority and inferiority multi-criteria ranking (SIR) method with 13 constraints establishing I-flows and S-flows matrices to evaluate four alternatives solar energies and determining which alternative is the best, providing power to sustainable building. Furthermore, SIR is well-known structured approach of multi-criteria decision support tools and gradually used in construction and building. The outcome of this paper significantly gives an indication to user selecting solar energy.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

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Although mental health literacy has been proposed as a factor that may facilitate help-seeking, few studies have examined this relation. This pilot study aimed to investigate the relation between mental health literacy and help-seeking intentions, and to explore which components of mental health literacy may be best able to predict help-seeking intentions. An online questionnaire was completed by a convenience sample of 150 university students enrolled in a psychology unit, aged between 17 and 26 years. A simultaneous multiple regression indicated that higher levels of mental health literacy were able to predict greater intentions to seek help from professional sources. A number of mental health literacy components made a unique and significant contribution to the prediction of help-seeking intentions. The findings of this pilot study indicate that the role of mental health literacy in facilitating help-seeking is a promising area of research.

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We derive an explicit method of computing the composition step in Cantor’s algorithm for group operations on Jacobians of hyperelliptic curves. Our technique is inspired by the geometric description of the group law and applies to hyperelliptic curves of arbitrary genus. While Cantor’s general composition involves arithmetic in the polynomial ring F_q[x], the algorithm we propose solves a linear system over the base field which can be written down directly from the Mumford coordinates of the group elements. We apply this method to give more efficient formulas for group operations in both affine and projective coordinates for cryptographic systems based on Jacobians of genus 2 hyperelliptic curves in general form.

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PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

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Sandwich shells have recently emerged as aesthetically pleasing, efficient and economical structural systems, with a number of applications. They combine the advantages of sandwich layer technology together with those of shell action. With different materials and thicknesses used in the sandwich layers, their performance characteristics largely remain un-quantified and there are no guidelines at present for their design. This research paper provides verification, through finite element modeling and testing, for the application of this technology to dome styled dwellings with research currently being conducted into the further application to roofing and floor structures.

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Quantifying spatial and/or temporal trends in environmental modelling data requires that measurements be taken at multiple sites. The number of sites and duration of measurement at each site must be balanced against costs of equipment and availability of trained staff. The split panel design comprises short measurement campaigns at multiple locations and continuous monitoring at reference sites [2]. Here we present a modelling approach for a spatio-temporal model of ultrafine particle number concentration (PNC) recorded according to a split panel design. The model describes the temporal trends and background levels at each site. The data were measured as part of the “Ultrafine Particles from Transport Emissions and Child Health” (UPTECH) project which aims to link air quality measurements, child health outcomes and a questionnaire on the child’s history and demographics. The UPTECH project involves measuring aerosol and particle counts and local meteorology at each of 25 primary schools for two weeks and at three long term monitoring stations, and health outcomes for a cohort of students at each school [3].

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The use of symbols and abbreviations adds uniqueness and complexity to the mathematical language register. In this article, the reader’s attention is drawn to the multitude of symbols and abbreviations which are used in mathematics. The conventions which underpin the use of the symbols and abbreviations and the linguistic difficulties which learners of mathematics may encounter due to the inclusion of the symbolic language are discussed. 2010 NAPLAN numeracy tests are used to illustrate examples of the complexities of the symbolic language of mathematics.

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Proving security of cryptographic schemes, which normally are short algorithms, has been known to be time-consuming and easy to get wrong. Using computers to analyse their security can help to solve the problem. This thesis focuses on methods of using computers to verify security of such schemes in cryptographic models. The contributions of this thesis to automated security proofs of cryptographic schemes can be divided into two groups: indirect and direct techniques. Regarding indirect ones, we propose a technique to verify the security of public-key-based key exchange protocols. Security of such protocols has been able to be proved automatically using an existing tool, but in a noncryptographic model. We show that under some conditions, security in that non-cryptographic model implies security in a common cryptographic one, the Bellare-Rogaway model [11]. The implication enables one to use that existing tool, which was designed to work with a different type of model, in order to achieve security proofs of public-key-based key exchange protocols in a cryptographic model. For direct techniques, we have two contributions. The first is a tool to verify Diffie-Hellmanbased key exchange protocols. In that work, we design a simple programming language for specifying Diffie-Hellman-based key exchange algorithms. The language has a semantics based on a cryptographic model, the Bellare-Rogaway model [11]. From the semantics, we build a Hoare-style logic which allows us to reason about the security of a key exchange algorithm, specified as a pair of initiator and responder programs. The other contribution to the direct technique line is on automated proofs for computational indistinguishability. Unlike the two other contributions, this one does not treat a fixed class of protocols. We construct a generic formalism which allows one to model the security problem of a variety of classes of cryptographic schemes as the indistinguishability between two pieces of information. We also design and implement an algorithm for solving indistinguishability problems. Compared to the two other works, this one covers significantly more types of schemes, but consequently, it can verify only weaker forms of security.

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The aim of this research was to develop and assess the psychometric properties of the Coach Motivation Questionnaire (CMQ). Study 1 focused on the compilation and pilot testing of potential questionnaire items. Consistent with self-determination theory, items were devised to tap into six forms of motivation: amotivation, external regulation, introjected regulation, identified regulation, integrated regulation, and intrinsic motivation. The purpose of the second study (N = 556) was to empirically examine the psychometric properties of the CMQ. Items were subjected to confirmatory factor analyses to determine the fit of the a priori model. In addition, the validity of the questionnaire was assessed through links with the theoretically related concepts of intrinsic need satisfaction, well-being, and goal orientation. Together with test–retest reliability (Study 3), these results showed preliminary support for the psychometric properties of the CMQ. Finally, using an independent sample (N = 254), the fourth study confirmed the factor structure and supports the use of the CMQ in future coaching research.

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The need for pre-service teachers to be proficient in the use of information and communication technologies (ICT) in the classroom once they graduate is essential, though this process is not a straightforward process (Zhang, 2008) and needs to go beyond pre-service teachers just being able to use ICT. Research suggests that for teachers to successfully use ICT in their classrooms they need to be specifically trained to do so (Markauskaite, 2007; Batane, 2004; Jacobsen, Clifford & Friesen, 2002). Pre-service teachers must also be able to embrace and use new and emerging ICT’s, often referred to as digital technologies, within their pedagogical approaches to teaching and learning. According to UNESCO, these “new technologies require new teacher roles, new pedagogies, and new approaches to teacher training” (2008, p.9). However, new approaches to teacher training have moved very slowly in many areas and preparing pre-service teachers to develop proficiency in embracing a digital pedagogy within their own classrooms can be a challenge for teacher training institutes. This paper reports on a case study of first year education students (N=667) and their experiences during their first semester of pre-service teacher education in a core ICT unit. It will report on the background ICT knowledge and skills that these students bring to the course as well as their expectations of the unit and ICT in their future teaching. The paper will then draw on the research results to identify challenges facing teacher training of pre-service teachers in using digital technologies in their future classrooms.

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This article considers the implications of the decision in Paroz v Clifford Gouldson Lawyers [2012] QDC 151, which examined provisions of the Legal Profession Act 2007 (Qld) dealing with costs disclosure and assessment, and also considered associated provisions of the Uniform Civil Procedure Rules 1999 (Qld).

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In 1980 Alltop produced a family of cubic phase sequences that nearly meet the Welch bound for maximum non-peak correlation magnitude. This family of sequences were shown by Wooters and Fields to be useful for quantum state tomography. Alltop’s construction used a function that is not planar, but whose difference function is planar. In this paper we show that Alltop type functions cannot exist in fields of characteristic 3 and that for a known class of planar functions, x^3 is the only Alltop type function.

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Mutually unbiased bases (MUBs) have been used in several cryptographic and communications applications. There has been much speculation regarding connections between MUBs and finite geometries. Most of which has focused on a connection with projective and affine planes. We propose a connection with higher dimensional projective geometries and projective Hjelmslev geometries. We show that this proposed geometric structure is present in several constructions of MUBs.