Traditional Cultural Districts: An Opportunity for Alaska Tribes to Protect Subsistence Rights and Traditional Lands

Alaska tribes have limited control over their traditional lands and waters. Tribes may increase their influence through a Traditional Cultural District designation under Section 106 of the National Historic Preservation Act. This designation does not stop development, but requires federal agencies to consult with tribes regarding potential development that may impact the district. The consultation right applies regardless of whether a tribe owns or has formally designated the district. In Alaska, where no Traditional Cultural Districts exist as of 2014, there is potential for designating large areas of land or water that correspond to the range of traditionally important species

The economic and accounting content of fixed assets

This book presents a mathematical methodology for image analysis tasks at the edge of current research, including anisotropic diffusion filtering of tensor fields. Instead of specific applications, it explores methodological structures on which they are built.DIPLECS, GARNICS, NACI

Assessing the financial potential of the company

In this position paper, we seek to extend the layered perception-action paradigm for on-line learning such that it includes an explicit symbolic processing capability. By incorporating symbolic processing at the apex of the perception action hierarchy in this way, we ensure that abstract symbol manipulation is fully grounded, without the necessity of specifying an explicit representational framework. In order to carry out this novel interfacing between symbolic and sub-symbolic processing, it is necessary to embed fuzzy rst-order logic theorem proving within a variational framework. The online learning resulting from the corresponding Euler-Lagrange equations establishes an extended adaptability compared to the standard subsumption architecture. We discuss an application of this approach within the eld of advanced driver assistance systems, demonstrating that a closed-form solution to the Euler Lagrange optimization problem is obtainable for simple cases.  DIPLEC

Multiscale optical flow computation from the monogenic signal

National audienceWe have developed an algorithm for the estimation of cardiac motion from medical images. The algorithm exploits monogenic signal theory, recently introduced as an N-dimensional generalization of the analytic signal. The displacement is computed locally by assuming the conservation of the monogenic phase over time. A local affine displacement model replaces the standard translation model to account for more complex motions as contraction/expansion and shear. A coarse-to-fine B-spline scheme allows a robust and effective computation of the models parameters and a pyramidal refinement scheme helps handle large motions. Robustness against noise is increased by replacing the standard pointwise computation of the monogenic orientation with a more robust least-squares orientation estimate. This paper reviews the results obtained on simulated cardiac images from different modalities, namely 2D and 3D cardiac ultrasound and tagged magnetic resonance. We also show how the proposed algorithm represents a valuable alternative to state-of-the-art algorithms in the respective fields

Improving the achievements of non-traditional students on computing courses at one wide access university

This longitudinal study set out to improve the retention and achievements of diverse students on computing courses in one wide access university, firstly by early identification of students at risk of poor performance and secondly by developing and implementing an intervention programme. Qualitative data were obtained using the ASSIST questionnaire, by focus group discussions and an open-ended questionnaire on students’ experiences of the transition to higher education (HE). Quantitative data on student characteristics and module results were obtained from Registry. Statistical analyses were performed using SPSS version 10. The study comprised two phases where phase one sought to enable the early detection of students at risk of poor performance by investigating the data set for patterns that may emerge between student achievement at Level 1 and entrance qualification, feeder institution, approaches to learning, conceptions of learning, course and teaching preferences and motivation. Phase one findings showed a trend of poorer performance by students who entered computing courses in HE with an AVCE entrance qualification. It was also shown that mature students scored more highly on the deep approach scale compared to their younger counterparts. Phase two investigated the data set for patterns that may emerge between student achievement at Level 2 and entrance qualification, approaches to learning, conceptions of learning and course and teaching preferences. Phase two, using action research, also sought to develop an intervention programme from the findings. This intervention programme was designed to improve aspects of information delivery to students; the personal tutor system, assessment régimes, Welcome Week, and teaching and learning. Piloting, evaluation and refinement of the intervention programme brought changes that were seen as positive by both staff and students. These changes included the Welcome Week Challenge which involved students in activities that sought to enhance students’ interactions with peers, personal tutors and the school and university facilities. These findings have shown that, for staff in wide access HE institutions, some knowledge of the previous educational experiences of their students, and the requirements of those students, are vital in providing a smooth transition to HE. A model of the characteristics of a successful student on computing courses in HE and a model for enhanced retention of diverse students on computing courses in HE were developed from the research findings. These models provide a significant contribution to current knowledge of those factors that enhance a smooth transition to HE and the characteristics of a successful student in a wide access university.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Динамика интеграционных процессов ЕАЭС

Проведено исследование динамики интеграционных процессов и факторов, их определяющих. Отмечено, что ключевым моментом интеграции стран ЕАЭС является углубление кооперационных связей и формирование региональных цепочек добавленной стоимости

Математична модель контактного з’єднання метало-пластмасових циліндричних оболонок

We consider alpha scale spaces, a parameterized class (alpha is an element of (0, 1]) of scale space representations beyond the well-established Gaussian scale space, which are generated by the alpha-th power of the minus Laplace operator on a bounded domain using the Neumann boundary condition. The Neumann boundary condition ensures that there is no grey-value flux through the boundary. Thereby no artificial grey-values from outside the image affect the evolution proces, which is the case for the alpha scale spaces on an unbounded domain. Moreover, the connection between the a scale spaces which is not trivial in the unbounded domain case, becomes straightforward: The generator of the Gaussian semigroup extends to a compact, self-adjoint operator on the Hilbert space L-2(Omega) and therefore it has a complete countable set of eigen functions. Taking the alpha-th power of the Gaussian generator simply boils down to taking the alpha-th power of the corresponding eigenvalues. Consequently, all alpha scale spaces have exactly the same eigen-modes and can be implemented simultaneously as scale dependent Fourier series. The only difference between them is the (relative) contribution of each eigen-mode to the evolution proces. By introducing the notion of (non-dimensional) relative scale in each a scale space, we are able to compare the various alpha scale spaces. The case alpha = 0.5, where the generator equals the square root of the minus Laplace operator leads to Poisson scale space, which is at least as interesting as Gaussian scale space and can be extended to a (Clifford) analytic scale space

Некоторые вопросы моделирования центробежных насосов

This work presents a novel object tracking approach, where the motion model is learned from sets of frame-wise detections with unknown associations. We employ a higher-order Markov model on position space instead of a first-order Markov model on a high-dimensional state-space of object dynamics. Compared to the latter, our approach allows the use of marginal rather than joint distributions, which results in a significant reduction of computation complexity. Densities are represented using a grid-based approach, where the rectangular windows are replaced with estimated smooth Parzen windows sampled at the grid points. This method performs as accurately as particle filter methods with the additional advantage that the prediction and update steps can be learned from empirical data. Our method is compared against standard techniques on image sequences obtained from an RC car following scenario. We show that our approach performs best in most of the sequences. Other potential applications are surveillance from cheap or uncalibrated cameras and image sequence analysis.DIPLEC

Defining the essence of innovation how important terms in promoting of transformation processes in Ukraine

Feature hierarchies are essential to many visual object recognition systems and are well motivated by observations in biological systems. The present paper proposes an algorithm to incrementally compute feature hierarchies. The features are represented as estimated densities, using a variant of local soft histograms. The kernel functions used for this estimation in conjunction with their unitary extension establish a tight frame and results from framelet theory apply. Traversing the feature hierarchy requires resampling of the spatial and the feature bins. For the resampling, we derive a multi-resolution scheme for quadratic spline kernels and we derive an optimization algorithm for the upsampling. We complement the theoretic results by some illustrative experiments, consideration of convergence rate and computational efficiency.DIPLECSGARNICSELLII