979 resultados para Adaptative large neighborhood search


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This research examines the process of placemaking in LeDroit Park, a residential Washington, DC, neighborhood with a historic district at its core. Unpacking the entwined physical and social evolution of the small community within the context of the Nation’s Capital, this analysis provides insight into the role of urban design and development as well as historic designation on shaping collective identity. Initially planned and designed in 1873 as a gated suburb just beyond the formal L’Enfant-designed city boundary, LeDroit Park was intended as a retreat for middle and upper-class European Americans from the growing density and social diversity of the city. With a mixture of large romantic revival mansions and smaller frame cottages set on grassy plots evocative of an idealized rural village, the physical design was intentionally inwardly-focused. This feeling of refuge was underscored with a physical fence that surrounded the development, intended to prevent African Americans from nearby Howard University and the surrounding neighborhood, from using the community’s private streets to access the City of Washington. Within two decades of its founding, LeDroit Park was incorporated into the District of Columbia, the surrounding fence was demolished, and the neighborhood was racially integrated. Due to increasingly stringent segregation laws and customs in the city, this period of integration lasted less than twenty years, and LeDroit Park developed into an elite African American enclave, using the urban design as a bulwark against the indignities of a segregated city. Throughout the 20th century housing infill and construction increased density, yet the neighborhood never lost the feeling of security derived from the neighborhood plan. Highlighting the architecture and street design, neighbors successfully received historic district designation in 1974 in order to halt campus expansion. After a stalemate that lasted two decades, the neighborhood began another period of transformation, both racial and socio-economic, catalyzed by a multi-pronged investment program led by Howard University. Through interviews with long-term and new community members, this investigation asserts that the 140-year development history, including recent physical interventions, is integral to placemaking, shaping the material character as well as the social identity of residents.

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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

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This paper discusses the results and propositions of organizational knowledge management research conducted in the period 2001-2007. This longitudinal study had the unique goal of investigating and analyzing “Knowledge Management” (KM) processes effectively implemented in world class organizations. The main objective was to investigate and analyze the conceptions, motivations, practices, metrics and results of KM processes implemented in different industries. The first set of studies involved 20 world cases related in the literature and served as a basis for a theoretical framework entitled “KM Integrative Conceptual Mapping Proposition”. This theoretical proposal was then tested in a qualitative study in three large organizations in Brazil. The results of the qualitative study validated the mapping proposition and left questions for new research concerning the implementation of a knowledge-based organizational model strategy.

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International audience

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This document introduces the planned new search for the neutron Electric Dipole Moment at the Spallation Neutron Source at the Oak Ridge National Laboratory. A spin precession measurement is to be carried out using Ultracold neutrons diluted in a superfluid Helium bath at T = 0.5 K, where spin polarized 3He atoms act as detector of the neutron spin polarization. This manuscript describes some of the key aspects of the planned experiment with the contributions from Caltech to the development of the project.

Techniques used in the design of magnet coils for Nuclear Magnetic Resonance were adapted to the geometry of the experiment. Described is an initial design approach using a pair of coils tuned to shield outer conductive elements from resistive heat loads, while inducing an oscillating field in the measurement volume. A small prototype was constructed to test the model of the field at room temperature.

A large scale test of the high voltage system was carried out in a collaborative effort at the Los Alamos National Laboratory. The application and amplification of high voltage to polished steel electrodes immersed in a superfluid Helium bath was studied, as well as the electrical breakdown properties of the electrodes at low temperatures. A suite of Monte Carlo simulation software tools to model the interaction of neutrons, 3He atoms, and their spins with the experimental magnetic and electric fields was developed and implemented to further the study of expected systematic effects of the measurement, with particular focus on the false Electric Dipole Moment induced by a Geometric Phase akin to Berry’s phase.

An analysis framework was developed and implemented using unbinned likelihood to fit the time modulated signal expected from the measurement data. A collaborative Monte Carlo data set was used to test the analysis methods.

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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.

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.

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.

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 ± 0.28, which observation has a p-value of 10-3 and a local significance of 3.35σ. 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 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

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.

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This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.

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The Geminga pulsar, one of the brighest gamma-ray sources, is a promising candidate for emission of very-high-energy (VHE > 100 GeV) pulsed gamma rays. Also, detection of a large nebula have been claimed by water Cherenkov instruments. We performed deep observations of Geminga with the MAGIC telescopes, yielding 63 hours of good-quality data, and searched for emission from the pulsar and pulsar wind nebula. We did not find any significant detection, and derived 95% confidence level upper limits. The resulting upper limits of 5.3 × 10^(−13) TeV cm^(−2)s^(−1) for the Geminga pulsar and 3.5 × 10^(−12) TeV cm^(−2)s^(−1) for the surrounding nebula at 50 GeV are the most constraining ones obtained so far at VHE. To complement the VHE observations, we also analyzed 5 years of Fermi-LAT data from Geminga, finding that the sub-exponential cut-off is preferred over the exponential cut-off that has been typically used in the literature. We also find that, above 10 GeV, the gamma-ray spectra from Geminga can be described with a power law with index softer than 5. The extrapolation of the power-law Fermi-LAT pulsed spectra to VHE goes well below the MAGIC upper limits, indicating that the detection of pulsed emission from Geminga with the current generation of Cherenkov telescopes is very difficult.

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This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.

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We present a search for ultrarelativistic magnetic monopoles with the Pierre Auger observatory. Such particles, possibly a relic of phase transitions in the early Universe, would deposit a large amount of energy along their path through the atmosphere, comparable to that of ultrahigh-energy cosmic rays (UHECRs). The air-shower profile of a magnetic monopole can be effectively distinguished by the fluorescence detector from that of standard UHECRs. No candidate was found in the data collected between 2004 and 2012, with an expected background of less than 0.1 event from UHECRs. The corresponding 90% confidence level (C.L.) upper limits on the flux of ultrarelativistic magnetic monopoles range from 10(-1)9 (cm(2) sr s)(-1) for a Lorentz factor gamma = 10(9) to 2.5 x 10(-21) (cm(2) sr s)(-1) for gamma = 10(12). These results-the first obtained with a UHECR detector-improve previously published limits by up to an order of magnitude.

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Die Arbeit geht dem Status quo der unternehmensweiten Suche in österreichischen Großunternehmen nach und beleuchtet Faktoren, die darauf Einfluss haben. Aus der Analyse des Ist-Zustands wird der Bedarf an Enterprise-Search-Software abgeleitet und es werden Rahmenbedingungen für deren erfolgreiche Einführung skizziert. Die Untersuchung stützt sich auf eine im Jahr 2009 durchgeführte Onlinebefragung von 469 österreichischen Großunternehmen (Rücklauf 22 %) und daran anschließende Leitfadeninterviews mit zwölf Teilnehmern der Onlinebefragung. Der theoretische Teil verortet die Arbeit im Kontext des Informations- und Wissensmanagements. Der Fokus liegt auf dem Ansatz der Enterprise Search, ihrer Abgrenzung gegenüber der Suche im Internet und ihrem Leistungsspektrum. Im empirischen Teil wird zunächst aufgezeigt, wie die Unternehmen ihre Informationen organisieren und welche Probleme dabei auftreten. Es folgt eine Analyse des Status quo der Informationssuche im Unternehmen. Abschließend werden Bekanntheit und Einsatz von Enterprise-Search-Software in der Zielgruppe untersucht sowie für die Einführung dieser Software nötige Rahmenbedingungen benannt. Defizite machen die Befragten insbesondere im Hinblick auf die übergreifende Suche im Unternehmen und die Suche nach Kompetenzträgern aus. Hier werden Lücken im Wissensmanagement offenbar. 29 % der Respondenten der Onlinebefragung geben zudem an, dass es in ihren Unternehmen gelegentlich bis häufig zu Fehlentscheidungen infolge defizitärer Informationslagen kommt. Enterprise-Search-Software kommt in 17 % der Unternehmen, die sich an der Onlinebefragung beteiligten, zum Einsatz. Die durch Enterprise-Search-Software bewirkten Veränderungen werden grundsätzlich positiv beurteilt. Alles in allem zeigen die Ergebnisse, dass Enterprise-Search-Strategien nur Erfolg haben können, wenn man sie in umfassende Maßnahmen des Informations- und Wissensmanagements einbettet.

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In this thesis, a search for same-sign top quark pairs produced according to the Standard Model Effective Field Theory (SMEFT) is presented. The analysis is carried out within the ATLAS Collaboration using collision data at a center-of-mass energy of $\sqrt{s} = 13$ TeV, collected by the ATLAS detector during the Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of $140$ fb$^{-1}$. Three SMEFT operators are considered in the analysis, namely $\mathcal{O}_{RR}$, $\mathcal{O}_{LR}^{(1)}$, and $\mathcal{O}_{LR}^{(8)}$. The signal associated to same-sign top pairs is searched in the dilepton channel, with the top quarks decaying via $t \longrightarrow W^+ b \longrightarrow \ell^+ \nu b$, leading to a final state signature composed of a pair of high-transverse momentum same-sign leptons and $b$-jets. Deep Neural Networks are employed in the analysis to enhance sensitivity to the different SMEFT operators and to perform signal-background discrimination. This is the first result of the ATLAS Collaboration concerning the search for same-sign top quark pairs production in proton-proton collision data at $\sqrt{s} = 13$ TeV, in the framework of the SMEFT.

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We report on the shape resonance spectra of phenol-water clusters, as obtained from elastic electron scattering calculations. Our results, along with virtual orbital analysis, indicate that the well-known indirect mechanism for hydrogen elimination in the gas phase is significantly impacted on by microsolvation, due to the competition between vibronic couplings on the solute and solvent molecules. This fact suggests how relevant the solvation effects could be for the electron-driven damage of biomolecules and the biomass delignification [E. M. de Oliveira et al., Phys. Rev. A 86, 020701(R) (2012)]. We also discuss microsolvation signatures in the differential cross sections that could help to identify the solvated complexes and access the composition of gaseous admixtures of these species.

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The aim of this study was to analyze the reasons for missed appointments in dental Family Health Units (FHU) and implement strategies to reduce same through action research. This is a study conducted in 12 FHUs in Piracicaba in the State of São Paulo from January, 1 to December, 31 2010. The sample was composed of 385 users of these health units who were interviewed over the phone and asked about the reasons for missing dental appointments, as well as 12 dentists and 12 nurses. Two workshops were staged with professionals: the first to assess the data collected in interviews and develop strategy, and the second for evaluation after 4 months. The primary cause for missed appointments was the opening hours of the units coinciding with the work schedule of the users. Among the strategies suggested were lectures on oral health, ongoing education in team meetings, training of Community Health Agents, participation in therapeutic groups and partnerships between Oral Health Teams and the social infrastructure of the community. The adoption of the single medical record was the strategy proposed by professionals. The strategies implemented led to a 66.6% reduction in missed appointments by the units and the motivating nature of the workshops elicited critical reflection to redirect health practices.

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Spinocerebellar ataxia type 1 (SCA1), spinocerebellar ataxia type 2 (SCA2) and Machado-Joseph disease or spinocerebellar ataxia type 3 (MJD/SCA3) are three distinctive forms of autosomal dominant spinocerebellar ataxia (SCA) caused by expansions of an unstable CAG repeat localized in the coding region of the causative genes. Another related disease, dentatorubropallidoluysian atrophy (DRPLA) is also caused by an unstable triplet repeat and can present as SCA in late onset patients. We investigated the frequency of the SCA1, SCA2, MJD/SCA3 and DRPLA mutations in 328 Brazilian patients with SCA, belonging to 90 unrelated families with various patterns of inheritance and originating in different geographic regions of Brazil. We found mutations in 35 families (39%), 32 of them with a clear autosomal dominant inheritance. The frequency of the SCA1 mutation was 3% of all patients; and 6 % in the dominantly inherited SCAs. We identified the SCA2 mutation in 6% of all families and in 9% of the families with autosomal dominant inheritance. The MJD/SCA3 mutation was detected in 30 % of all patients; and in the 44% of the dominantly inherited cases. We found no DRPLA mutation. In addition, we observed variability in the frequency of the different mutations according to geographic origin of the patients, which is probably related to the distinct colonization of different parts of Brazil. These results suggest that SCA may be occasionally caused by the SCA1 and SCA2 mutations in the Brazilian population, and that the MJD/SCA3 mutation is the most common cause of dominantly inherited SCA in Brazil.