An algorithm for the inclusion of RC compact models of packages into board level thermal simulation tools

International audience

A distributed, compact routing protocol for the Internet

The Internet has grown in size at rapid rates since BGP records began, and continues to do so. This has raised concerns about the scalability of the current BGP routing system, as the routing state at each router in a shortest-path routing protocol will grow at a supra-linearly rate as the network grows. The concerns are that the memory capacity of routers will not be able to keep up with demands, and that the growth of the Internet will become ever more cramped as more and more of the world seeks the benefits of being connected. Compact routing schemes, where the routing state grows only sub-linearly relative to the growth of the network, could solve this problem and ensure that router memory would not be a bottleneck to Internet growth. These schemes trade away shortest-path routing for scalable memory state, by allowing some paths to have a certain amount of bounded ���stretch���. The most promising such scheme is Cowen Routing, which can provide scalable, compact routing state for Internet routing, while still providing shortest-path routing to nearly all other nodes, with only slightly stretched paths to a very small subset of the network. Currently, there is no fully distributed form of Cowen Routing that would be practical for the Internet. This dissertation describes a fully distributed and compact protocol for Cowen routing, using the k-core graph decomposition. Previous compact routing work showed the k-core graph decomposition is useful for Cowen Routing on the Internet, but no distributed form existed. This dissertation gives a distributed k-core algorithm optimised to be efficient on dynamic graphs, along with with proofs of its correctness. The performance and efficiency of this distributed k-core algorithm is evaluated on large, Internet AS graphs, with excellent results. This dissertation then goes on to describe a fully distributed and compact Cowen Routing protocol. This protocol being comprised of a landmark selection process for Cowen Routing using the k-core algorithm, with mechanisms to ensure compact state at all times, including at bootstrap; a local cluster routing process, with mechanisms for policy application and control of cluster sizes, ensuring again that state can remain compact at all times; and a landmark routing process is described with a prioritisation mechanism for announcements that ensures compact state at all times.

Subject categories used in Nuclear science abstracts, 1967-1975 /

"TID-26500/R1. Distribution category: UC-2."

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

Real-time alert correlation with type graphs

The premise of automated alert correlation is to accept that false alerts from a low level intrusion detection system are inevitable and use attack models to explain the output in an understandable way. Several algorithms exist for this purpose which use attack graphs to model the ways in which attacks can be combined. These algorithms can be classified in to two broad categories namely scenario-graph approaches, which create an attack model starting from a vulnerability assessment and type-graph approaches which rely on an abstract model of the relations between attack types. Some research in to improving the efficiency of type-graph correlation has been carried out but this research has ignored the hypothesizing of missing alerts. Our work is to present a novel type-graph algorithm which unifies correlation and hypothesizing in to a single operation. Our experimental results indicate that the approach is extremely efficient in the face of intensive alerts and produces compact output graphs comparable to other techniques.

Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at ���s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

<p>In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy ���s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb^-1.</p> <p>In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at ���s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.</p> <p>The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.</p> <p>We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 &#177; 0.28, which observation has a p-value of 10^-3 and a local significance of 3.35&#963;. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5&#963; deviation from the Standard Model hypothesis over a broader range of the razor plane.</p> <p>In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.</p>

A Thermal Management Solution for Compact Power Converters

Regulated Transformer Rectifier Units contain several power electronic boards to facilitate AC to DC power conversion. As these units become smaller, the number of devices on each board increases while their distance from each other decreases, making active cooling essential to maintaining reliable operation. Although it is widely accepted that liquid is a far superior heat transfer medium to air, the latter is still capable of yielding low device operating temperatures with proper heat sink and airflow design. The purpose of this study is to describe the models and methods used to design and build the thermal management system for one of the power electronic boards in a compact, high power regulated transformer rectifier unit. Maximum device temperature, available pressure drop and manufacturability were assessed when selecting the final design for testing. Once constructed, the thermal management system���s performance was experimentally verified at three different power levels.

Compact discs as versatile cost-effective substrates for releasable nanopatterned aluminium films

We demonstrate that standard polycarbonate compact disk surfaces can provide unique adhesion to Al films that is both strong enough to permit Al film nanopatterning and weak enough to allow easy nanopatterned Al film detachment using Scotch tape. Transferred Al nanohole arrays on Scotch tape exhibit excellent optical and plasmonic performance.

Desarrollo de los modelos de responsabilidad social corporativa de las empresas transnacionales en El Salvador a partir del establecimiento de los objetivos del global compact de Naciones unidas, 1999-2015

G��nesis y evoluci��n de la responsabilidad social corporativa ��� Global compact y foros de discusi��n auspiciados desde Naciones Unidas en torno a la responsabilidad social corporativa ��� Estudio de pr��cticas de RSC por las empresas transnacionales adheridas al global compact establecidas en El Salvador (TIGO, la Constancia, Grupo Roble y Telef��nica) comportamiento de los modelos de RSC aplicados.

Desarrollo de los modelos de responsabilidad social corporativa de las empresas transnacionales en El Salvador a partir del establecimiento de los objetivos del global compact de Naciones unidas, 1999-2015

G��nesis y evoluci��n de la responsabilidad social corporativa ��� Global compact y foros de discusi��n auspiciados desde Naciones Unidas en torno a la responsabilidad social corporativa ��� Estudio de pr��cticas de RSC por las empresas transnacionales adheridas al global compact establecidas en El Salvador (TIGO, la Constancia, Grupo Roble y Telef��nica) comportamiento de los modelos de RSC aplicados

Solderjet bumping technique used to manufacture a compact and robust green solid-state laser

Solder-joining using metallic solder alloys is an alternative to adhesive bonding. Laser-based soldering processes are especially well suited for the joining of optical components made of fragile and brittle materials such as glasses, ceramics and optical crystals due to a localized and minimized input of thermal energy. The Solderjet Bumping technique is used to assemble a miniaturized laser resonator in order to obtain higher robustness, wider thermal conductivity performance, higher vacuum and radiation compatibility, and better heat and long term stability compared with identical glued devices. The resulting assembled compact and robust green diode-pumped solid-state laser is part of the future Raman Laser Spectrometer designed for the Exomars European Space Agency (ESA) space mission 2018.

Sub-kiloparsec alma imaging of compact star-forming galaxies at z ~ 2.5: revealing the formation of dense galactic cores in the progenitors of compact quiescent galaxies

We present spatially resolved Atacama Large Millimeter/submillimeter Array (ALMA) 870 ��m dust continuum maps of six massive, compact, dusty star-forming galaxies at z ~ 2.5. These galaxies are selected for their small rest-frame optical sizes (r_e,F160W ~ 1.6 kpc) and high stellar mass densities that suggest that they are direct progenitors of compact quiescent galaxies at z ~ 2. The deep observations yield high far-infrared (FIR) luminosities of L_IR = 10^12.3-12.8 L_��� and star formation rates (SFRs) of SFR = 200���700 M_��� yr^���1, consistent with those of typical star-forming "main sequence" galaxies. The high spatial resolution (FWHM ~ 0 12���0 18) ALMA and Hubble Space Telescope photometry are combined to construct deconvolved, mean radial profiles of their stellar mass and (UV+IR) SFR. We find that the dusty, nuclear IR���SFR overwhelmingly dominates the bolometric SFR up to r ~ 5 kpc, by a factor of over 100�� from the unobscured UV���SFR. Furthermore, the effective radius of the mean SFR profile (r_e,SFR ~ 1 kpc) is ~30% smaller than that of the stellar mass profile. The implied structural evolution, if such nuclear starburst last for the estimated gas depletion time of ��t = ��100 Myr, is a 4��increase of the stellar mass density within the central 1 kpc and a 1.6�� decrease of the half-mass���radius. This structural evolution fully supports dissipation-driven, formation scenarios in which strong nuclear starbursts transform larger, star-forming progenitors into compact quiescent galaxies.

2008 Greenhouse Gas Emissions from Selected Iowa Source Categories

This report is the second inventory of point source-specific greenhouse gas emissions conducted by the Department of Natural Resources, covering more industrial sectors and greenhouse gas pollutants than the previous year. This report is required by Iowa Code 455B.851 to be submitted annually to the Iowa General Assembly and the Governor,

2009 Greenhouse Gas Emissions from Selected Iowa Source Categories

This objective report is the third inventory of point source-specific greenhouse gas emissions conducted by the Department of Natural Resources. This report is required by Iowa Code 455B.851

Essays on Atypicality: A narrative perspective to illuminate how atypical actors can counter the disciplining effect of categories

Using Big Data and Natural Language Processing (NLP) tools, this dissertation investigates the narrative strategies that atypical actors can leverage to deal with the adverse reactions they often elicit. Extensive research shows that atypical actors, those who fail to abide by established contextual standards and norms, are subject to skepticism and face a higher risk of rejection. Indeed, atypical actors combine features and behaviors in unconventional ways, thereby generating confusion in the audience and instilling doubts about their propositions' legitimacy. However, the same atypicality is often cited as the precursor to socio-cultural innovation and a strategic act to expand the capacity for delivering valued goods and services. Contextualizing the conditions under which atypicality is celebrated or punished has been a significant theoretical challenge for scholars interested in reconciling this tension. Nevertheless, prior work has focused on audience side factors or on actor-side characteristics that are only scantily under an actor's control (e.g., status and reputation). This dissertation demonstrates that atypical actors can use strategically crafted narratives to mitigate against the audience���s negative response. In particular, when atypical actors evoke conventional features in their story, they are more likely to overcome the illegitimacy discount usually applied to them. Moreover, narratives become successful navigational devices for atypicality when atypical actors use a more abstract language. This simplifies classification and provides the audience with more flexibility to interpret and understand them.