Thermal building simulation using the UKCP09 probabilistic climate projections

This article investigates how to use UK probabilistic climate-change projections (UKCP09) in rigorous building energy analysis. Two office buildings (deep plan and shallow plan) are used as case studies to demonstrate the application of UKCP09. Three different methods for reducing the computational demands are explored: statistical reduction (Finkelstein-Schafer [F-S] statistics), simplification using degree-day theory and the use of metamodels. The first method, which is based on an established technique, can be used as reference because it provides the most accurate information. However, it is necessary to automatically choose weather files based on F-S statistic by using computer programming language because thousands of weather files created from UKCP09 weather generator need to be processed. A combination of the second (degree-day theory) and third method (metamodels) requires only a relatively small number of simulation runs, but still provides valuable information to further implement the uncertainty and sensitivity analyses. The article also demonstrates how grid computing can be used to speed up the calculation for many independent EnergyPlus models by harnessing the processing power of idle desktop computers. © 2011 International Building Performance Simulation Association (IBPSA).

Discriminative Orthogonal Neighborhood-Preserving Projections for Classification

Orthogonal neighborhood-preserving projection (ONPP) is a recently developed orthogonal linear algorithm for overcoming the out-of-sample problem existing in the well-known manifold learning algorithm, i.e., locally linear embedding. It has been shown that ONPP is a strong analyzer of high-dimensional data. However, when applied to classification problems in a supervised setting, ONPP only focuses on the intraclass geometrical information while ignores the interaction of samples from different classes. To enhance the performance of ONPP in classification, a new algorithm termed discriminative ONPP (DONPP) is proposed in this paper. DONPP 1) takes into account both intraclass and interclass geometries; 2) considers the neighborhood information of interclass relationships; and 3) follows the orthogonality property of ONPP. Furthermore, DONPP is extended to the semisupervised case, i.e., semisupervised DONPP (SDONPP). This uses unlabeled samples to improve the classification accuracy of the original DONPP. Empirical studies demonstrate the effectiveness of both DONPP and SDONPP.

On The Uniqueness of Correspondence Under Orthographic and Perspective Projections

The task of shape recovery from a motion sequence requires the establishment of correspondence between image points. The two processes, the matching process and the shape recovery one, are traditionally viewed as independent. Yet, information obtained during the process of shape recovery can be used to guide the matching process. This paper discusses the mutual relationship between the two processes. The paper is divided into two parts. In the first part we review the constraints imposed on the correspondence by rigid transformations and extend them to objects that undergo general affine (non rigid) transformation (including stretch and shear), as well as to rigid objects with smooth surfaces. In all these cases corresponding points lie along epipolar lines, and these lines can be recovered from a small set of corresponding points. In the second part of the paper we discuss the potential use of epipolar lines in the matching process. We present an algorithm that recovers the correspondence from three contour images. The algorithm was implemented and used to construct object models for recognition. In addition we discuss how epipolar lines can be used to solve the aperture problem.

Object Recognition By Alignment Using Invariant Projections of Planar Surfaces

In order to recognize an object in an image, we must determine the best transformation from object model to the image. In this paper, we show that for features from coplanar surfaces which undergo linear transformations in space, there exist projections invariant to the surface motions up to rotations in the image field. To use this property, we propose a new alignment approach to object recognition based on centroid alignment of corresponding feature groups. This method uses only a single pair of 2D model and data. Experimental results show the robustness of the proposed method against perturbations of feature positions.

Active Hidden Models for Tracking with Kernel Projections

We introduce Active Hidden Models (AHM) that utilize kernel methods traditionally associated with classification. We use AHMs to track deformable objects in video sequences by leveraging kernel projections. We introduce the "subset projection" method which improves the efficiency of our tracking approach by a factor of ten. We successfully tested our method on facial tracking with extreme head movements (including full 180-degree head rotation), facial expressions, and deformable objects. Given a kernel and a set of training observations, we derive unbiased estimates of the accuracy of the AHM tracker. Kernels are generally used in classification methods to make training data linearly separable. We prove that the optimal (minimum variance) tracking kernels are those that make the training observations linearly dependent.

Technology on screen: projections, paranoia and discursive practice

This paper explores the extent to which film can be viewed as a discursive practice and as such the extent to which it can be seen as an element central to the essence of technology more universally defined. Our analysis of recurring visual and narrative motifs and metaphors around the representation of technology in specific films will consider how these representations are part of wider discursive practices around conceptualising technology.

Vulnerability of coastal ecosystems to changes in harmful algal bloom distribution in response to climate change: projections based on model analysis

Harmful algal blooms (HABs), those proliferations of algae that can cause fish kills, contaminate seafood with toxins, form unsightly scums, or detrimentally alter ecosystem function have been increasing in frequency, magnitude, and duration worldwide. Here, using a global modeling approach, we show, for three regions of the globe, the potential effects of nutrient loading and climate change for two HAB genera, pelagic Prorocentrum and Karenia, each with differing physiological characteristics for growth. The projections (end of century, 2090-2100) are based on climate change resulting from the A1B scenario of the Intergovernmental Panel on Climate Change Institut Pierre Simon Laplace Climate Model (IPCC, IPSL-CM4), applied in a coupled oceanographic-biogeochemical model, combined with a suite of assumed physiological 'rules' for genera-specific bloom development. Based on these models, an expansion in area and/or number of months annually conducive to development of these HABs along the NW European Shelf-Baltic Sea system and NE Asia was projected for both HAB genera, but no expansion (Prorocentrum spp.), or actual contraction in area and months conducive for blooms (Karenia spp.), was projected in the SE Asian domain. The implications of these projections, especially for Northern Europe, are shifts in vulnerability of coastal systems to HAB events, increased regional HAB impacts to aquaculture, increased risks to human health and ecosystems, and economic consequences of these events due to losses to fisheries and ecosystem services.

Performance projections and design optimization of planar double gate SOI MOSFETs for logic technology applications

In this paper, by investigating the influence of source/drain extension region engineering (also known as gate-source/drain underlap) in nanoscale planar double gate (DG) SOI MOSFETs, we offer new insights into the design of future nanoscale gate-underlap DG devices to achieve ITRS projections for high performance (HP), low standby power (LSTP) and low operating power (LOP) logic technologies. The impact of high-kappa gate dielectric, silicon film thickness, together with parameters associated with the lateral source/drain doping profile, is investigated in detail. The results show that spacer width along with lateral straggle can not only effectively control short-channel effects, thus presenting low off-current in a gate underlap device, but can also be optimized to achieve lower intrinsic delay and higher on-off current ratio (I-on/I-off). Based on the investigation of on-current (I-on), off-current (I-off), I-on/I-off, intrinsic delay (tau), energy delay product and static power dissipation, we present design guidelines to select key device parameters to achieve ITRS projections. Using nominal gate lengths for different technologies, as recommended from ITRS specification, optimally designed gate-underlap DG MOSFETs with a spacer-to-straggle (s/sigma) ratio of 2.3 for HP/LOP and 3.2 for LSTP logic technologies will meet ITRS projection. However, a relatively narrow range of lateral straggle lying between 7 to 8 nm is recommended. A sensitivity analysis of intrinsic delay, on-current and off-current to important parameters allows a comparative analysis of the various design options and shows that gate workfunction appears to be the most crucial parameter in the design of DG devices for all three technologies. The impact of back gate misalignment on I-on, I-off and tau is also investigated for optimized underlap devices.

Ranges of bimodule projections and reflexivity

We develop a general framework for reflexivity in dual Banach
spaces, motivated by the question of when the weak* closed linear
span of two reflexive masa-bimodules is automatically reflexive. We
establish an affirmative answer to this question in a number of
cases by examining two new classes of masa-bimodules, defined in
terms of ranges of masa-bimodule projections. We give a number of
corollaries of our results concerning operator and spectral
synthesis, and show that the classes of masa-bimodules we study are
operator synthetic if and only if they are strong operator Ditkin.

Characterizing changes in the excitability of corticospinal projections to proximal muscles of the upper limb

Background: There has been an explosion of interest in methods of exogenous brain stimulation that induce changes in the excitability of human cerebral cortex. The expectation is that these methods may promote recovery of function following brain injury. To assess their effects on motor output, it is typical to assess the state of corticospinal projections from primary motor cortex to muscles of the hand, via electromyographic responses to transcranial magnetic stimulation. If a range of stimulation intensities is employed, the recruitment curves (RCs) obtained can, at least for intrinsic hand muscles, be fitted by a sigmoid function.

Objective/hypothesis: To establish whether sigmoid fits provide a reliable basis upon which to characterize the input–output properties of the corticospinal pathway for muscles proximal to the hand, and to assess as an alternative the area under the (recruitment) curve (AURC).

Methods: A comparison of the reliability of these measures, using RCs obtained for muscles that are frequently the targets of rehabilitation.

Results: The AURC is an extremely reliable measure of the state of corticospinal projections to hand and forearm muscles, which has both face and concurrent validity. Construct validity is demonstrated by detection of widely distributed (across muscles) changes in corticospinal excitability induced by paired associative stimulation (PAS).

Conclusion(s): The parameters derived from sigmoid fits are unlikely to provide an adequate means to assess the effectiveness of therapeutic regimes. The AURC can be employed to characterize corticospinal projections to a range of muscles, and gauge the efficacy of longitudinal interventions in clinical rehabilitation.

Paired associative transcranial alternating current stimulation increases the excitability of corticospinal projections in humans

Many types of non-invasive brain stimulation alter corticospinal excitability (CSE). Paired associative stimulation (PAS) has attracted particular attention as its effects ostensibly adhere to Hebbian principles of neural plasticity. In prototypical form, a single electrical stimulus is directed to a peripheral nerve in close temporal contiguity with transcranial magnetic stimulation delivered to the contralateral primary motor cortex (M1). Repeated pairing of the two discrete stimulus events (i.e. association) over an extended period either increases or decreases the excitability of corticospinal projections from M1, contingent on the interstimulus interval. We studied a novel form of associative stimulation, consisting of brief trains of peripheral afferent stimulation paired with short bursts of high frequency (≥80 Hz) transcranial alternating current stimulation (tACS) over contralateral M1. Elevations in the excitability of corticospinal projections to the forearm were observed for a range of tACS frequency (80, 140 and 250 Hz), current (1, 2 and 3 mA) and duration (500 and 1000 ms) parameters. The effects were at least as reliable as those brought about by PAS or transcranial direct current stimulation. When paired with tACS, muscle tendon vibration also induced elevations of CSE. No such changes were brought about by the tACS or peripheral afferent stimulation alone. In demonstrating that associative effects are expressed when the timing of the peripheral and cortical events is not precisely circumscribed, these findings suggest that multiple cellular pathways may contribute to a long term potentiation-type response. Their relative contributions will differ depending on the nature of the induction protocol that is used.