978 resultados para Computing device mechanism
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CORBA (Common Object Request Broker Architecture) on laajalle levinnyt ja teollisuudessa yleisesti käytetty hajautetun tietojenkäsittelyn arkkitehtuuri. CORBA skaalautuu eri kokoisiin tarpeisiin ja sitä voidaan hyödynntää myös sulautetuissa langattomissa laitteissa. Oleellista sulautetussa ympäristössä on rakentaa rajapinnat kevytrakenteisiksi, pysyviksi ja helposti laajennettaviksi ilman että yhteensopivuus aikaisempiin rajapintoihin olisi vaarassa. Langattomissa laitteissa resurssit, kuten muistin määrä ja prosessointiteho, ovat hyvin rajalliset, joten rajapinta tulee suunnitella ja toteuttaa optimaalisesti. Palveluiden tulee ottaa huomioon myös langattomuuden rajoitukset, kuten hitaat tiedonsiirtonopeudet ja tiedonsiirron yhteydettömän luonteen. Työssä suunniteltiin ja toteutettiin CORBA-rajapinta GSM-päätelaitteeseen, jonka on todettu täyttävän sille asetetut tavoitteet. Rajapinta tarjoaa kaikki yleisimmät GSM-terminaalin ominaisuudet ja on laajennettavissa tulevia tuotteita ja verkkotekniikoita varten. Laajennettavuutta saavutetaan esimerkiksi kuvaamalla terminaalin ominaisuudet yleisellä kuvauskielellä, kuten XML:lla (Extensible Markup Language).
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El projecte que es presenta a continuació és el resultat fruit de la detecció d’un problema de comunicació entre les escoles (sobretot de primària) i el pares dels alumnes que hi cursen els estudis, i la necessitat de trobar-hi una solució. Amb aquesta premissa, i tenint en compte que la tecnologia cada vegada ens ofereix més i millors eines per gestionar les nostres necessitats, es porta a terme la construcció d’un servei al núvol (Saas) capaç de cobrir aquestes necessitats i de fer-ho de la manera més senzilla i eficient possible. La plataforma Aula és un servei on tant professors com pares dels alumnes poden comunicar-se i consultar la informació referent als seus alumnes (en el cas del professors), i dels seus fills (en el cas dels pares/tutors). La solució adoptada ha de ser capaç de funcionar sobre qualsevol aparell (ordinador, tablet o mòbil) i en qualsevol lloc on hi hagi connexió a Internet. No s’ha de realitzar cap tipus d’instal·lació un cop el sistema estigui funcionant, i s’hi podran registrar tants centres com siguin necessaris, així com professionals i pares dels alumnes. També s’ha valorat el manteniment mínim del sistema i la seva escalabilitat, per poder fer front a diferents volums de dades. Així doncs, el projecte Aula es presenta com una solució per gestionar el dia a dia dels professors i alumnes, però que no pretén ser substitut de cap altre sistema de gestió que pugui tenir el centre.
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Memristive computing refers to the utilization of the memristor, the fourth fundamental passive circuit element, in computational tasks. The existence of the memristor was theoretically predicted in 1971 by Leon O. Chua, but experimentally validated only in 2008 by HP Labs. A memristor is essentially a nonvolatile nanoscale programmable resistor — indeed, memory resistor — whose resistance, or memristance to be precise, is changed by applying a voltage across, or current through, the device. Memristive computing is a new area of research, and many of its fundamental questions still remain open. For example, it is yet unclear which applications would benefit the most from the inherent nonlinear dynamics of memristors. In any case, these dynamics should be exploited to allow memristors to perform computation in a natural way instead of attempting to emulate existing technologies such as CMOS logic. Examples of such methods of computation presented in this thesis are memristive stateful logic operations, memristive multiplication based on the translinear principle, and the exploitation of nonlinear dynamics to construct chaotic memristive circuits. This thesis considers memristive computing at various levels of abstraction. The first part of the thesis analyses the physical properties and the current-voltage behaviour of a single device. The middle part presents memristor programming methods, and describes microcircuits for logic and analog operations. The final chapters discuss memristive computing in largescale applications. In particular, cellular neural networks, and associative memory architectures are proposed as applications that significantly benefit from memristive implementation. The work presents several new results on memristor modeling and programming, memristive logic, analog arithmetic operations on memristors, and applications of memristors. The main conclusion of this thesis is that memristive computing will be advantageous in large-scale, highly parallel mixed-mode processing architectures. This can be justified by the following two arguments. First, since processing can be performed directly within memristive memory architectures, the required circuitry, processing time, and possibly also power consumption can be reduced compared to a conventional CMOS implementation. Second, intrachip communication can be naturally implemented by a memristive crossbar structure.
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Cobalt nanotubes (CoNTs) with very high longitudinal coercivity were prepared by electrodeposition of cobalt acetate for the first time by using anodized alumina (AAO) template. They were then characterized with X-ray diffraction (XRD), a field emission scanning electron microscope (FESEM), and a transmission electron microscope (TEM). Formation of a highly ordered hexagonal cobalt phase is observed. Room temperature SQUID (superconducting quantum interference device) magnetometer measurements indicate that the easy axis of magnetization is parallel to the nanotube axis. These CoNTs exhibit very high longitudinal coercivity of ∼820 Oe. A very high intertubular interaction resulting from magnetostatic dipolar interaction between nanotubes is observed. Thick-walled nanotubes were also fabricated by using cobalt acetate tetrahydrate precursors. A plausible mechanism for the formation of CoNTs based on mobility assisted growth is proposed. The role of the hydration layer and the mobility of metal ions are elucidated in the case of the growth mechanism of one-dimensional geometry
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Magnetism and magnetic materials have been playing a lead role in improving the quality of life. They are increasingly being used in a wide variety of applications ranging from compasses to modern technological devices. Metallic glasses occupy an important position among magnetic materials. They assume importance both from a scientific and an application point of view since they represent an amorphous form of condensed matter with significant deviation from thermodynamic equilibrium. Metallic glasses having good soft magnetic properties are widely used in tape recorder heads, cores of high-power transformers and metallic shields. Superconducting metallic glasses are being used to produce high magnetic fields and magnetic levitation effect. Upon heat treatment, they undergo structural relaxation leading to subtle rearrangements of constituent atoms. This leads to densification of amorphous phase and subsequent nanocrystallisation. The short-range structural relaxation phenomenon gives rise to significant variations in physical, mechanical and magnetic properties. Magnetic amorphous alloys of Co-Fe exhibit excellent soft magnetic properties which make them promising candidates for applications as transformer cores, sensors, and actuators. With the advent of microminiaturization and nanotechnology, thin film forms of these alloys are sought after for soft under layers for perpendicular recording media. The thin film forms of these alloys can also be used for fabrication of magnetic micro electro mechanical systems (magnetic MEMS). In bulk, they are drawn in the form of ribbons, often by melt spinning. The main constituents of these alloys are Co, Fe, Ni, Si, Mo and B. Mo acts as the grain growth inhibitor and Si and B facilitate the amorphous nature in the alloy structure. The ferromagnetic phases such as Co-Fe and Fe-Ni in the alloy composition determine the soft magnetic properties. The grain correlation length, a measure of the grain size, often determines the soft magnetic properties of these alloys. Amorphous alloys could be restructured in to their nanocrystalline counterparts by different techniques. The structure of nanocrystalline material consists of nanosized ferromagnetic crystallites embedded in an amorphous matrix. When the amorphous phase is ferromagnetic, they facilitate exchange coupling between nanocrystallites. This exchange coupling results in the vanishing of magnetocrystalline anisotropy which improves the soft magnetic properties. From a fundamental perspective, exchange correlation length and grain size are the deciding factors that determine the magnetic properties of these nanocrystalline materials. In thin films, surfaces and interfaces predominantly decides the bulk property and hence tailoring the surface roughness and morphology of the film could result in modified magnetic properties. Surface modifications can be achieved by thermal annealing at various temperatures. Ion irradiation is an alternative tool to modify the surface/structural properties. The surface evolution of a thin film under swift heavy ion (SHI) irradiation is an outcome of different competing mechanism. It could be sputtering induced by SHI followed by surface roughening process and the material transport induced smoothening process. The impingement of ions with different fluence on the alloy is bound to produce systematic microstructural changes and this could effectively be used for tailoring magnetic parameters namely coercivity, saturation magnetization, magnetic permeability and remanence of these materials. Swift heavy ion irradiation is a novel and an ingenious tool for surface modification which eventually will lead to changes in the bulk as well as surface magnetic property. SHI has been widely used as a method for the creation of latent tracks in thin films. The bombardment of SHI modifies the surfaces or interfaces or creates defects, which induces strain in the film. These changes will have profound influence on the magnetic anisotropy and the magnetisation of the specimen. Thus inducing structural and morphological changes by thermal annealing and swift heavy ion irradiation, which in turn induce changes in the magnetic properties of these alloys, is one of the motivation of this study. Multiferroic and magneto-electrics is a class of functional materials with wide application potential and are of great interest to material scientists and engineers. Magnetoelectric materials combine both magnetic as well as ferroelectric properties in a single specimen. The dielectric properties of such materials can be controlled by the application of an external magnetic field and the magnetic properties by an electric field. Composites with magnetic and piezo/ferroelectric individual phases are found to have strong magnetoelectric (ME) response at room temperature and hence are preferred to single phasic multiferroic materials. Currently research in this class of materials is towards optimization of the ME coupling by tailoring the piezoelectric and magnetostrictive properties of the two individual components of ME composites. The magnetoelectric coupling constant (MECC) (_ ME) is the parameter that decides the extent of interdependence of magnetic and electric response of the composite structure. Extensive investigates have been carried out in bulk composites possessing on giant ME coupling. These materials are fabricated by either gluing the individual components to each other or mixing the magnetic material to a piezoelectric matrix. The most extensively investigated material combinations are Lead Zirconate Titanate (PZT) or Lead Magnesium Niobate-Lead Titanate (PMNPT) as the piezoelectric, and Terfenol-D as the magnetostrictive phase and the coupling is measured in different configurations like transverse, longitudinal and inplane longitudinal. Fabrication of a lead free multiferroic composite with a strong ME response is the need of the hour from a device application point of view. The multilayer structure is expected to be far superior to bulk composites in terms of ME coupling since the piezoelectric (PE) layer can easily be poled electrically to enhance the piezoelectricity and hence the ME effect. The giant magnetostriction reported in the Co-Fe thin films makes it an ideal candidate for the ferromagnetic component and BaTiO3 which is a well known ferroelectric material with improved piezoelectric properties as the ferroelectric component. The multilayer structure of BaTiO3- CoFe- BaTiO3 is an ideal system to understand the underlying fundamental physics behind the ME coupling mechanism. Giant magnetoelectric coupling coefficient is anticipated for these multilayer structures of BaTiO3-CoFe-BaTiO3. This makes it an ideal candidate for cantilever applications in magnetic MEMS/NEMS devices. SrTiO3 is an incipient ferroelectric material which is paraelectric up to 0K in its pure unstressed form. Recently few studies showed that ferroelectricity can be induced by application of stress or by chemical / isotopic substitution. The search for room temperature magnetoelectric coupling in SrTiO3-CoFe-SrTiO3 multilayer structures is of fundamental interest. Yet another motivation of the present work is to fabricate multilayer structures consisting of CoFe/ BaTiO3 and CoFe/ SrTiO3 for possible giant ME coupling coefficient (MECC) values. These are lead free and hence promising candidates for MEMS applications. The elucidation of mechanism for the giant MECC also will be the part of the objective of this investigation.
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Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.
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A world of ubiquitous computing, full of networked mobile and embedded technologies, is approaching. The benefits of this technology are numerous, and act as the major driving force behind its development. These benefits are brought about, in part, by ubiquitous monitoring (UM): the continuous and wide spread collection of ?significant amounts of data about users
The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions
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Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The aim of this work is to propose a simple and efficient mechanism to deal with the problem of executing sequential code in a pure dataflow machine. Our results is obtained with a simulator of Wolf [4] architecture. The implemented mechanism improved the architecture performance when executing sequential code and we expect that this improvement could be better if we use some heuristics to deal with some special groups of instructions such as branch operations. Further research will show us if this is true.
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Research on Blindsight, Neglect/Extinction and Phantom limb syndromes, as well as electrical measurements of mammalian brain activity, have suggested the dependence of vivid perception on both incoming sensory information at primary sensory cortex and reentrant information from associative cortex. Coherence between incoming and reentrant signals seems to be a necessary condition for (conscious) perception. General reticular activating system and local electrical synchronization are some of the tools used by the brain to establish coarse coherence at the sensory cortex, upon which biochemical processes are coordinated. Besides electrical synchrony and chemical modulation at the synapse, a central mechanism supporting such a coherence is the N-methyl-D-aspartate channel, working as a 'coincidence detector' for an incoming signal causing the depolarization necessary to remove Mg 2+, and reentrant information releasing the glutamate that finally prompts Ca 2+ entry. We propose that a signal transduction pathway activated by Ca 2+ entry into cortical neurons is in charge of triggering a quantum computational process that accelerates inter-neuronal communication, thus solving systemic conflict and supporting the unity of consciousness. © 2001 Elsevier Science Ltd.
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The problem of shock generated vibration is very common in practice and difficult to isolate due to the high levels of excitation involved and its transient nature. If not properly isolated it could lead to large transmitted forces and displacements. Typically, classical shock isolation relies on the use of passive stiffness elements to absorb energy by deformation and some damping mechanism to dissipate residual vibration. The approach of using nonlinear stiffness elements is explored in this paper, focusing in providing an isolation system with low dynamic stiffness. The possibilities of using such a configuration for a shock mount are studied experimentally following previous theoretical models. The model studied considers electromagnets and permanent magnets in order to obtain nonlinear stiffness forces using different voltage configurations. It is found that the stiffness nonlinearities could be advantageous in improving shock isolation in terms of absolute displacement and acceleration response when compared with linear elastic elements. Copyright (C) 2015 Elsevier Ltd. All rights reserved
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As the area of nanotechnology continues to grow, the development of new nanomaterials with interesting physical and electronic properties and improved characterization techniques are several areas of research that will be remain vital for continued improvement of devices and the understanding in nanoscale phenomenon. In this dissertation, the chemical vapor deposition synthesis of rare earth (RE) compounds is described in detail. In general, the procedure involves the vaporization of a REClx (RE = Y, La, Ce, Pr, Nd, Sm, Gd, Tb, Dy, Ho) in the presence of hydride phase precursors such as decaborane and ammonia at high temperatures and low pressures. The vapor-liquid-solid mechanism was used in combination with the chemical vapor deposition process to synthesize single crystalline rare earth hexaboride nanostructures. The crystallographic orientation of as-synthesized rare earth hexaboride nanostructures and gadolinium nitride thin films was controlled by judicious choice of specific growth substrates and modeled by analyzing x-ray diffraction powder patterns and crystallographic models. The rare earth hexaboride nanostructures were then implemented into two existing technologies to enhance their characterization capabilities. First, the rare earth hexaboride nanowires were used as a test material for the development of a TEM based local electrode atom probe tomography (LEAP) technique. This technique provided some of the first quantitative compositional information of the rare earth hexaboride systems. Second, due to the rigidity and excellent conductivity of the rare earth hexaborides, nanostructures were grown onto tungsten wires for the development of robust, oxidation resistant nanomanipulator electronic probes for semiconductor device failure analysis.
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Light-emitting electrochemical cells (LECs) made of electroluminescent polymers were studied by d.c. and transient current-voltage and luminance-voltage measurements to elucidate the operation mechanisms of this kind of device. The time and external voltage necessary to form electrical double layers (EDLs) at the electrode interfaces could be determined from the results. In the low-and intermediate-voltage ranges (below 1.1 V), the ionic transport and the electronic diffusion dominate the current, being the device operation better described by an electrodynamic model. For higher voltages, electrochemical doping occurs, giving rise to the formation of a p-i-n junction, according to an electrochemical doping model. Copyright (C) EPLA, 2012
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Some phase space transport properties for a conservative bouncer model are studied. The dynamics of the model is described by using a two-dimensional measure preserving mapping for the variables' velocity and time. The system is characterized by a control parameter epsilon and experiences a transition from integrable (epsilon = 0) to nonintegrable (epsilon not equal 0). For small values of epsilon, the phase space shows a mixed structure where periodic islands, chaotic seas, and invariant tori coexist. As the parameter epsilon increases and reaches a critical value epsilon(c), all invariant tori are destroyed and the chaotic sea spreads over the phase space, leading the particle to diffuse in velocity and experience Fermi acceleration (unlimited energy growth). During the dynamics the particle can be temporarily trapped near periodic and stable regions. We use the finite time Lyapunov exponent to visualize this effect. The survival probability was used to obtain some of the transport properties in the phase space. For large epsilon, the survival probability decays exponentially when it turns into a slower decay as the control parameter epsilon is reduced. The slower decay is related to trapping dynamics, slowing the Fermi Acceleration, i.e., unbounded growth of the velocity.