841 resultados para Computer aided network analysis
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In all segments, the companies are looking for the highest productivity with the lowest possible cost, and in the construction industry, the thinking is the same. Over time, techniques that generate more productivity supplanted previous techniques; an example is the CAD technology that replaced free drawings in projects execution. However, the Computer Aided Design (CAD) technology does not deal with certain factors that permeate the entire project. It is required the use of other techniques to supply this need in traditional projects. For example, a software for schedule management, another for assets management and a person who makes calculations for estimates and budgets. The BIM (Building Information Modeling) technology aims to integrate all this information, facilitating the communication among members of a work team and reducing the time required to carry out the project. This work is a applied research, a descriptive research, carried out through modeling and simulation, processes inherent in the use of BIM, a survey was also used only to contextualization. BIM was used for a soccer stadium roof project, in order to verify the feasibility of such use through the analysis of: BIM tools, difficulties encountered and implications of BIM use, and comparison of traditional methods and the use of BIM. To aid the contextualization, a survey was conducted to verify the use of BIM in medium and small companies
Resumo:
In all segments, the companies are looking for the highest productivity with the lowest possible cost, and in the construction industry, the thinking is the same. Over time, techniques that generate more productivity supplanted previous techniques; an example is the CAD technology that replaced free drawings in projects execution. However, the Computer Aided Design (CAD) technology does not deal with certain factors that permeate the entire project. It is required the use of other techniques to supply this need in traditional projects. For example, a software for schedule management, another for assets management and a person who makes calculations for estimates and budgets. The BIM (Building Information Modeling) technology aims to integrate all this information, facilitating the communication among members of a work team and reducing the time required to carry out the project. This work is a applied research, a descriptive research, carried out through modeling and simulation, processes inherent in the use of BIM, a survey was also used only to contextualization. BIM was used for a soccer stadium roof project, in order to verify the feasibility of such use through the analysis of: BIM tools, difficulties encountered and implications of BIM use, and comparison of traditional methods and the use of BIM. To aid the contextualization, a survey was conducted to verify the use of BIM in medium and small companies
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Objectives-The purpose of this study was to predict perinatal outcomes using fetal total lung volumes assessed by 3-dimensional ultrasonography (3DUS) in primary pleural effusion. Methods-Between July 2005 and July 2010, total lung volumes were prospectively estimated in fetuses with primary pleural effusion by 3DUS using virtual organ computer-aided analysis software. The first and last US examinations were considered in the analysis. The observed/expected total lung volumes were calculated. Main outcomes were perinatal death (up to 28 days of life) and respiratory morbidity (orotracheal intubation with mechanical respiratory support >48 hours). Results-Twelve of 19 fetuses (63.2%) survived. Among the survivors, 7 (58.3%) had severe respiratory morbidity. The observed/expected total lung volume at the last US examination before birth was significantly associated with perinatal death (P < .01) and respiratory morbidity (P < .01) as well as fetal hydrops (P < .01) and bilateral effusion (P = .01). Conclusions-Fetal total lung volumes may be useful for the prediction of perinatal outcomes in primary pleural effusion.
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Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.
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Background: Although the molecular pathogenesis of pituitary adenomas has been assessed by several different techniques, it still remains partially unclear. Ribosomal proteins (RPs) have been recently related to human tumorigenesis, but they have not yet been evaluated in pituitary tumorigenesis. Objective: The aim of this study was to introduce serial analysis of gene expression (SAGE), a high-throughput method, in pituitary research in order to compare differential gene expression. Methods: Two SAGE cDNA libraries were constructed, one using a pool of mRNA obtained from five GH-secreting pituitary tumors and another from three normal pituitaries. Genes differentially expressed between the libraries were further validated by real-time PCR in 22 GH-secreting pituitary tumors and in 15 normal pituitaries. Results: Computer-generated genomic analysis tools identified 13 722 and 14 993 exclusive genes in normal and adenoma libraries respectively. Both shared 6497 genes, 2188 were underexpressed and 4309 overexpressed in tumoral library. In adenoma library, 33 genes encoding RPs were underexpressed. Among these, RPSA, RPS3, RPS14, and RPS29 were validated by real-time PCR. Conclusion: We report the first SAGE library from normal pituitary tissue and GH-secreting pituitary tumor, which provide quantitative assessment of cellular transcriptome. We also validated some downregulated genes encoding RPs. Altogether, the present data suggest that the underexpression of the studied RP genes possibly collaborates directly or indirectly with other genes to modify cell cycle arrest, DNA repair, and apoptosis, leading to an environment that might have a putative role in the tumorigenesis, introducing new perspectives for further studies on molecular genesis of somatotrophinomas.
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OBJETIVO: Comparar do débito cardíaco (DC) e a fração de ejeção (FE) do coração de fetos masculinos e femininos obtidos por meio da ultrassonografia tridimensional, utilizando o spatio-temporal image correlation (STIC). MÉTODOS: Realizou-se um estudo de corte transversal com 216 fetos normais, entre 20 a 34 semanas de gestação, sendo 108 masculinos e 108 femininos. Os volumes ventriculares no final da sístole e diástole foram obtidos por meio do STIC, sendo as avaliações volumétricas realizadas pelo virtual organ computer-aided analysis (VOCAL) com rotação de 30º. Para o cálculo do DC utilizou-se a fórmula: DC= volume sistólico/frequência cardíaca fetal, enquanto que para a FE utilizou-se a fórmula: FE= volume sistólico/volume diastólico final. O DC (combinado, feminino e masculino) e a FE (masculina e feminina) foram comparadas utilizando-se o teste t não pareado e ANCOVA. Foram criados gráficos de dispersão com os percentis 5, 50 e 95. RESULTADOS: A média do DC combinado, DC direito, DC esquerdo, FE direita e FE esquerda, para feminino e masculino, foram 240,07 mL/min; 122,67 mL/min; 123,40 mL/min; 72,84%; 67,22%; 270,56 mL/min; 139,22 mL/min; 131,34 mL/min; 70,73% e 64,76%, respectivamente; sem diferença estatística (P> 0,05). CONCLUSÕES: O DC e a FE fetal obtidos por meio da ultrassonografia tridimensional (STIC) não apresentaram diferença significativa em relação ao gênero.
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Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.
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To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.
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L'indagine condotta, avvalendosi del paradigma della social network analysis, offre una descrizione delle reti di supporto personale e del capitale sociale di un campione di 80 italiani ex post un trattamento terapeutico residenziale di lungo termine per problemi di tossicodipendenza. Dopo aver identificato i profili delle reti di supporto sociale degli intervistati, si è proceduto, in primis, alla misurazione e comparazione delle ego-centered support networks tra soggetti drug free e ricaduti e, successivamente, all'investigazione delle caratteristiche delle reti e delle forme di capitale sociale – closure e brokerage – che contribuiscono al mantenimento dell'astinenza o al rischio di ricaduta nel post-trattamento. Fattori soggettivi, come la discriminazione pubblica percepita e l'attitudine al lavoro, sono stati inoltre esplorati al fine di investigare la loro correlazione con la condotta di reiterazione nell'uso di sostanze. Dai risultati dello studio emerge che un più basso rischio di ricaduta è positivamente associato ad una maggiore attitudine al lavoro, ad una minore percezione di discriminazione da parte della società, all'avere membri di supporto con un più alto status socio-economico e che mobilitano risorse reputazionali e, infine, all'avere reti più eterogenee nell'occupazione e caratterizzate da più elevati livelli di reciprocità. Inoltre, il capitale sociale di tipo brokerage contribuisce al mantenimento dell'astinenza in quanto garantisce l'accesso del soggetto ad informazioni meno omogenee e la sua esposizione a opportunità più numerose e differenziate. I risultati dello studio, pertanto, dimostrano l'importante ruolo delle personal support networks nel prevenire o ridurre il rischio di ricaduta nel post-trattamento, in linea con precedenti ricerche che suggeriscono la loro incorporazione nei programmi terapeutici per tossicodipendenti.
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Il tumore al seno si colloca al primo posto per livello di mortalità tra le patologie tumorali che colpiscono la popolazione femminile mondiale. Diversi studi clinici hanno dimostrato come la diagnosi da parte del radiologo possa essere aiutata e migliorata dai sistemi di Computer Aided Detection (CAD). A causa della grande variabilità di forma e dimensioni delle masse tumorali e della somiglianza di queste con i tessuti che le ospitano, la loro ricerca automatizzata è un problema estremamente complicato. Un sistema di CAD è generalmente composto da due livelli di classificazione: la detection, responsabile dell’individuazione delle regioni sospette presenti sul mammogramma (ROI) e quindi dell’eliminazione preventiva delle zone non a rischio; la classificazione vera e propria (classification) delle ROI in masse e tessuto sano. Lo scopo principale di questa tesi è lo studio di nuove metodologie di detection che possano migliorare le prestazioni ottenute con le tecniche tradizionali. Si considera la detection come un problema di apprendimento supervisionato e lo si affronta mediante le Convolutional Neural Networks (CNN), un algoritmo appartenente al deep learning, nuova branca del machine learning. Le CNN si ispirano alle scoperte di Hubel e Wiesel riguardanti due tipi base di cellule identificate nella corteccia visiva dei gatti: le cellule semplici (S), che rispondono a stimoli simili ai bordi, e le cellule complesse (C) che sono localmente invarianti all’esatta posizione dello stimolo. In analogia con la corteccia visiva, le CNN utilizzano un’architettura profonda caratterizzata da strati che eseguono sulle immagini, alternativamente, operazioni di convoluzione e subsampling. Le CNN, che hanno un input bidimensionale, vengono solitamente usate per problemi di classificazione e riconoscimento automatico di immagini quali oggetti, facce e loghi o per l’analisi di documenti.
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Schon seit einigen Jahrzehnten wird die Sportwissenschaft durch computergestützte Methoden in ihrer Arbeit unterstützt. Mit der stetigen Weiterentwicklung der Technik kann seit einigen Jahren auch zunehmend die Sportpraxis von deren Einsatz profitieren. Mathematische und informatische Modelle sowie Algorithmen werden zur Leistungsoptimierung sowohl im Mannschafts- als auch im Individualsport genutzt. In der vorliegenden Arbeit wird das von Prof. Perl im Jahr 2000 entwickelte Metamodell PerPot an den ausdauerorientierten Laufsport angepasst. Die Änderungen betreffen sowohl die interne Modellstruktur als auch die Art der Ermittlung der Modellparameter. Damit das Modell in der Sportpraxis eingesetzt werden kann, wurde ein Kalibrierungs-Test entwickelt, mit dem die spezifischen Modellparameter an den jeweiligen Sportler individuell angepasst werden. Mit dem angepassten Modell ist es möglich, aus gegebenen Geschwindigkeitsprofilen die korrespondierenden Herzfrequenzverläufe abzubilden. Mit dem auf den Athleten eingestellten Modell können anschliessend Simulationen von Läufen durch die Eingabe von Geschwindigkeitsprofilen durchgeführt werden. Die Simulationen können in der Praxis zur Optimierung des Trainings und der Wettkämpfe verwendet werden. Das Training kann durch die Ermittlung einer simulativ bestimmten individuellen anaeroben Schwellenherzfrequenz optimal gesteuert werden. Die statistische Auswertung der PerPot-Schwelle zeigt signifikante Übereinstimmungen mit den in der Sportpraxis üblichen invasiv bestimmten Laktatschwellen. Die Wettkämpfe können durch die Ermittlung eines optimalen Geschwindigkeitsprofils durch verschiedene simulationsbasierte Optimierungsverfahren unterstützt werden. Bei der neuesten Methode erhält der Athlet sogar im Laufe des Wettkampfs aktuelle Prognosen, die auf den Geschwindigkeits- und Herzfrequenzdaten basieren, die während des Wettkampfs gemessen werden. Die mit PerPot optimierten Wettkampfzielzeiten für die Athleten zeigen eine hohe Prognosegüte im Vergleich zu den tatsächlich erreichten Zielzeiten.
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Over the time, Twitter has become a fundamental source of information for news. As a one step forward, researchers have tried to analyse if the tweets contain predictive power. In the past, in financial field, a lot of research has been done to propose a function which takes as input all the tweets for a particular stock or index s, analyse them and predict the stock or index price of s. In this work, we take an alternative approach: using the stock price and tweet information, we investigate following questions. 1. Is there any relation between the amount of tweets being generated and the stocks being exchanged? 2. Is there any relation between the sentiment of the tweets and stock prices? 3. What is the structure of the graph that describes the relationships between users?
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Oncological liver surgery and interventions aim for removal of tumor tissue while preserving a sufficient amount of functional tissue to ensure organ regeneration. This requires detailed understanding of the patient-specific internal organ anatomy (blood vessel system, bile ducts, tumor location). The introduction of computer support in the surgical process enhances anatomical orientation through patient-specific 3D visualization and enables precise reproduction of planned surgical strategies though stereotactic navigation technology. This article provides clinical background information on indications and techniques for the treatment of liver tumors, reviews the technological contributions addressing the problem of organ motion during navigated surgery on a deforming organ, and finally presents an overview of the clinical experience in computer-assisted liver surgery and interventions. The review concludes that several clinically applicable solutions for computer aided liver surgery are available and small-scale clinical trials have been performed. Further developments will be required more accurate and faster handling of organ deformation and large clinical studies will be required for demonstrating the benefits of computer aided liver surgery.
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BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.