886 resultados para applications in logistics


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This study was undertaken to examine how instructor use of emerging technologies can contribute to better quality pre-service teacher education. A group of nine Memorial University Faculty of Education instructors attempted to systematically incorporate mobile tablet (iPad) technologies into their on-campus instruction over the period of one academic year (2013-2014). Participants familiarized themselves with their device; evaluated a range of instructional applications (apps) specific to their discipline and/or teaching focus areas; and attempted to intentionally integrate the device into the classroom-learning environment. The research team utilized several focus groups and semi-structured interviews to elicit the representations of participants with respect to their impressions of the value of tablet technologies and their experiences in implementing tablet technology in their instructional practice.

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Gold nanoparticles (Au NPs) with diameters ranging between 5-60 nm have been synthesised in water, and further stabilized with polyethylene glycol-based thiol polymers (mPEG-SH). Successful PEGylation of the Au NPs was confirmed by Dynamic Light scattering (DLS) and Zeta potential measurements. PEG coating of the Au NPs is the key of their colloidal stabilty, and its successful applications. Catalytic efficiency testing of the PEG-AuNPs were carried out on homocoupling of boronic acid. PEG-Au NPs with AuNps diameter < 30 nm were useful as catalyst in water. Finally, the PEG-Au NPs were also shown to be stable in biological fluid and not cytotoxic on B16.F10 cell line, making them attractive for further studies.

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This thesis uses models of firm-heterogeneity to complete empirical analyses in economic history and agricultural economics. In Chapter 2, a theoretical model of firm heterogeneity is used to derive a statistic that summarizes the welfare gains from the introduction of a new technology. The empirical application considers the use of mechanical steam power in the Canadian manufacturing sector during the late nineteenth century. I exploit exogenous variation in geography to estimate several parameters of the model. My results indicate that the use of steam power resulted in a 15.1 percent increase in firm-level productivity and a 3.0-5.2 percent increase in aggregate welfare. Chapter 3 considers various policy alternatives to price ceiling legislation in the market for production quotas in the dairy farming sector in Quebec. I develop a dynamic model of the demand for quotas with farmers that are heterogeneous in their marginal cost of milk production. The econometric analysis uses farm-level data and estimates a parameter of the theoretical model that is required for the counterfactual experiments. The results indicate that the price of quotas could be reduced to the ceiling price through a 4.16 percent expansion of the aggregate supply of quotas, or through moderate trade liberalization of Canadian dairy products. In Chapter 4, I study the relationship between farm-level productivity and participation in the Commercial Export Milk (CEM) program. I use a difference-in-difference research design with inverse propensity weights to test for causality between participation in the CEM program and total factor productivity (TFP). I find a positive correlation between participation in the CEM program and TFP, however I find no statistically significant evidence that the CEM program affected TFP.

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Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

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The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

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The major part of this thesis concerns the development of catalytic methodologies based on palladium nanoparticles immobilized on aminopropyl-functionalized siliceous mesocellular foam (Pd0-AmP-MCF). The catalytic activity of the precursor to the nanocatalyst, PdII-AmP-MCF is also covered by this work. In the first part the application of Pd0-AmP-MCF in Suzuki-Miyaura cross-coupling reactions and transfer hydrogenation of alkenes under microwave irradiation is described. Excellent reactivity was observed and a broad range of substrates were tolerated for both transformations. The Pd0-AmP-MCF exhibited high recyclability as well as low metal leaching in both cases. The aim of the second part was to evaluate the catalytic efficiency of the closely related PdII-AmP-MCF for cycloisomerization of various acetylenic acids. The catalyst was able to promote formation of lactones under mild conditions using catalyst loadings of 0.3 - 0.5 mol% at temperatures of up to 50 oC in the presence of Et3N. By adding 1,4-benzoquinone to the reaction, the catalyst could be recycled four times without any observable decrease in the activity. The selective arylation of indoles at the C-2 position using Pd-AmP-MCF and symmetric diaryliodonium salts is presented in the third part. These studies revealed that Pd0-AmP-MCF was more effective than PdII-AmP-MCF for this transformation. Variously substituted indoles as well as diaryliodonium salts were tolerated, giving arylated indoles in high yields within 15 h at 20 - 50 oC in H2O. Only very small amounts of Pd leaching were observed and in this case the catalyst exhibited moderate recyclability. The final part of the thesis describes the selective hydrogenation of the C=C in different α,β-unsaturated systems. The double bond was efficiently hydrogenated in high yields both under batch and continuous-flow conditions. High recyclability and low metal leaching were observed in both cases.

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Digital Image Processing is a rapidly evolving eld with growing applications in Science and Engineering. It involves changing the nature of an image in order to either improve its pictorial information for human interpretation or render it more suitable for autonomous machine perception. One of the major areas of image processing for human vision applications is image enhancement. The principal goal of image enhancement is to improve visual quality of an image, typically by taking advantage of the response of human visual system. Image enhancement methods are carried out usually in the pixel domain. Transform domain methods can often provide another way to interpret and understand image contents. A suitable transform, thus selected, should have less computational complexity. Sequency ordered arrangement of unique MRT (Mapped Real Transform) coe cients can give rise to an integer-to-integer transform, named Sequency based unique MRT (SMRT), suitable for image processing applications. The development of the SMRT from UMRT (Unique MRT), forward & inverse SMRT algorithms and the basis functions are introduced. A few properties of the SMRT are explored and its scope in lossless text compression is presented.

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Con la crescita in complessità delle infrastrutture IT e la pervasività degli scenari di Internet of Things (IoT) emerge il bisogno di nuovi modelli computazionali basati su entità autonome capaci di portare a termine obiettivi di alto livello interagendo tra loro grazie al supporto di infrastrutture come il Fog Computing, per la vicinanza alle sorgenti dei dati, e del Cloud Computing per offrire servizi analitici complessi di back-end in grado di fornire risultati per milioni di utenti. Questi nuovi scenarii portano a ripensare il modo in cui il software viene progettato e sviluppato in una prospettiva agile. Le attività dei team di sviluppatori (Dev) dovrebbero essere strettamente legate alle attività dei team che supportano il Cloud (Ops) secondo nuove metodologie oggi note come DevOps. Tuttavia, data la mancanza di astrazioni adeguata a livello di linguaggio di programmazione, gli sviluppatori IoT sono spesso indotti a seguire approcci di sviluppo bottom-up che spesso risulta non adeguato ad affrontare la compessità delle applicazione del settore e l'eterogeneità dei compomenti software che le formano. Poichè le applicazioni monolitiche del passato appaiono difficilmente scalabili e gestibili in un ambiente Cloud con molteplici utenti, molti ritengono necessaria l'adozione di un nuovo stile architetturale, in cui un'applicazione dovrebbe essere vista come una composizione di micro-servizi, ciascuno dedicato a uno specifica funzionalità applicativa e ciascuno sotto la responsabilità di un piccolo team di sviluppatori, dall'analisi del problema al deployment e al management. Poichè al momento non si è ancora giunti a una definizione univoca e condivisa dei microservices e di altri concetti che emergono da IoT e dal Cloud, nè tantomento alla definzione di linguaggi sepcializzati per questo settore, la definzione di metamodelli custom associati alla produzione automatica del software di raccordo con le infrastrutture potrebbe aiutare un team di sviluppo ad elevare il livello di astrazione, incapsulando in una software factory aziendale i dettagli implementativi. Grazie a sistemi di produzione del sofware basati sul Model Driven Software Development (MDSD), l'approccio top-down attualmente carente può essere recuperato, permettendo di focalizzare l'attenzione sulla business logic delle applicazioni. Nella tesi viene mostrato un esempio di questo possibile approccio, partendo dall'idea che un'applicazione IoT sia in primo luogo un sistema software distribuito in cui l'interazione tra componenti attivi (modellati come attori) gioca un ruolo fondamentale.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Owing to their capability of merging the properties of metals and conventional polymers, Conducting Polymers (CPs) are a unique class of carbon-based materials capable of conducting electrical current. A conjugated backbone is the hallmark of CPs, which can readily undergo reversible doping to different extents, thus achieving a wide range of electrical conductivities, while maintaining mechanical flexibility, transparency and high thermal stability. Thanks to these inherent versatility and attracting properties, from their discovery CPs have experienced incessant widespread in a great plethora of research fields, ranging from energy storage to healthcare, also encouraging the spring and growth of new scientific areas with highly innovative content. Nowadays, Bioelectronics stands out as one of the most promising research fields, dealing with the mutual interplay between biology and electronics. Among CPs, the polyelectrolyte complex poly (3,4-ethylenedioxythiophene): poly (styrenesulfonate) (PEDOT:PSS), especially in the form of thin films, has been emphasized as ideal platform for bioelectronic applications. Indeed, in the last two decades PEDOT:PSS has played a key role in the sensing of bioanalytes and living cells interfacing and monitoring. In the present work, development and characterization of two kinds of PEDOT:PSS-based devices for applications in Bioelectronics are discussed in detail. In particular, a low-cost amperometric sensor for the selective detection of Dopamine in a ternary mixture was optimized, taking advantage of the electrocatalytic and antifouling properties that render PEDOT:PSS thin films appealing tools for electrochemical sensing of bioanalytes. Moreover, the potentialities of this material to interact with live cells were explored through the fabrication of a microfluidic trapping device for electrical monitoring of 3D spheroids using an impedance-based approach.