842 resultados para Technology Network


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In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

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The scale down of transistor technology allows microelectronics manufacturers such as Intel and IBM to build always more sophisticated systems on a single microchip. The classical interconnection solutions based on shared buses or direct connections between the modules of the chip are becoming obsolete as they struggle to sustain the increasing tight bandwidth and latency constraints that these systems demand. The most promising solution for the future chip interconnects are the Networks on Chip (NoC). NoCs are network composed by routers and channels used to inter- connect the different components installed on the single microchip. Examples of advanced processors based on NoC interconnects are the IBM Cell processor, composed by eight CPUs that is installed on the Sony Playstation III and the Intel Teraflops pro ject composed by 80 independent (simple) microprocessors. On chip integration is becoming popular not only in the Chip Multi Processor (CMP) research area but also in the wider and more heterogeneous world of Systems on Chip (SoC). SoC comprehend all the electronic devices that surround us such as cell-phones, smart-phones, house embedded systems, automotive systems, set-top boxes etc... SoC manufacturers such as ST Microelectronics , Samsung, Philips and also Universities such as Bologna University, M.I.T., Berkeley and more are all proposing proprietary frameworks based on NoC interconnects. These frameworks help engineers in the switch of design methodology and speed up the development of new NoC-based systems on chip. In this Thesis we propose an introduction of CMP and SoC interconnection networks. Then focusing on SoC systems we propose: • a detailed analysis based on simulation of the Spidergon NoC, a ST Microelectronics solution for SoC interconnects. The Spidergon NoC differs from many classical solutions inherited from the parallel computing world. Here we propose a detailed analysis of this NoC topology and routing algorithms. Furthermore we propose aEqualized a new routing algorithm designed to optimize the use of the resources of the network while also increasing its performance; • a methodology flow based on modified publicly available tools that combined can be used to design, model and analyze any kind of System on Chip; • a detailed analysis of a ST Microelectronics-proprietary transport-level protocol that the author of this Thesis helped developing; • a simulation-based comprehensive comparison of different network interface designs proposed by the author and the researchers at AST lab, in order to integrate shared-memory and message-passing based components on a single System on Chip; • a powerful and flexible solution to address the time closure exception issue in the design of synchronous Networks on Chip. Our solution is based on relay stations repeaters and allows to reduce the power and area demands of NoC interconnects while also reducing its buffer needs; • a solution to simplify the design of the NoC by also increasing their performance and reducing their power and area consumption. We propose to replace complex and slow virtual channel-based routers with multiple and flexible small Multi Plane ones. This solution allows us to reduce the area and power dissipation of any NoC while also increasing its performance especially when the resources are reduced. This Thesis has been written in collaboration with the Advanced System Technology laboratory in Grenoble France, and the Computer Science Department at Columbia University in the city of New York.

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Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

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This dissertation deals with two specific aspects of a potential hydrogen-based energy economy, namely the problems of energy storage and energy conversion. In order to contribute to the solution of these problems, the structural and dynamical properties of two promising materials for hydrogen storage (lithium imide/amide) and proton conduction (poly[vinyl phosphonic acid]) are modeled on an atomistic scale by means of first principles molecular dynamics simulation methods.rnrnrnIn the case of the hydrogen storage system lithium amide/imide (LiNH_2/Li_2NH), the focus was on the interplay of structural features and nuclear quantum effects. For these calculations, Path-Integral Molecular Dynamics (PIMD) simulations were used. The structures of these materials at room temperature were elucidated; in collaboration with an experimental group, a very good agreement between calculated and experimental solid-state 1H-NMR chemical shifts was observed. Specifically, the structure of Li_2NH features a disordered arrangement of the Li lattice, which was not reported in previous studies. In addition, a persistent precession of the NH bonds was observed in our simulations. We provide evidence that this precession is the consequence of a toroid-shaped effective potential, in which the protons in the material are immersed. This potential is essentially flat along the torus azimuthal angle, which might lead to important quantum delocalization effects of the protons over the torus.rnrnOn the energy conversion side, the dynamics of protons in a proton conducting polymer (poly[vinyl phosphonic acid], PVPA) was studied by means of a steered ab-initio Molecular Dynamics approach applied on a simplified polymer model. The focus was put on understanding the microscopic proton transport mechanism in polymer membranes, and on characterizing the relevance of the local environment. This covers particularly the effect of water molecules, which participate in the hydrogen bonding network in the material. The results indicate that these water molecules are essential for the effectiveness of proton conduction. A water-mediated Grotthuss mechanism is identified as the main contributor to proton conduction, which agrees with the experimentally observed decay on conductivity for the same material in the absence of water molecules.rnrnThe gain in understanding the microscopic processes and structures present in this materials can help the development of new materials with improved properties, thus contributing to the solution of problems in the implementation of fuel cells.

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Chapter 1 studies how consumers’ switching costs affect the pricing and profits of firms competing in two-sided markets such as Apple and Google in the smartphone market. When two-sided markets are dynamic – rather than merely static – I show that switching costs lower the first-period price if network externalities are strong, which is in contrast to what has been found in one-sided markets. By contrast, switching costs soften price competition in the initial period if network externalities are weak and consumers are more patient than the platforms. Moreover, an increase in switching costs on one side decreases the first-period price on the other side. Chapter 2 examines firms’ incentives to invest in local and flexible resources when demand is uncertain and correlated. I find that market power of the monopolist providing flexible resources distorts investment incentives, while competition mitigates them. The extent of improvement depends critically on demand correlation and the cost of capacity: under social optimum and monopoly, if the flexible resource is cheap, the relationship between investment and correlation is positive, and if it is costly, the relationship becomes negative; under duopoly, the relationship is positive. The analysis also sheds light on some policy discussions in markets such as cloud computing. Chapter 3 develops a theory of sequential investments in cybersecurity. The regulator can use safety standards and liability rules to increase security. I show that the joint use of an optimal standard and a full liability rule leads to underinvestment ex ante and overinvestment ex post. Instead, switching to a partial liability rule can correct the inefficiencies. This suggests that to improve security, the regulator should encourage not only firms, but also consumers to invest in security.

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Sustainable development is one of the biggest challenges of the twenty fist-century. Various university has begun the debate about the content of this concept and the ways in which to integrate it into their policy, organization and activities. Universities have a special responsibility to take over a leading position by demonstrating best practices that sustain and educate a sustainable society. For that reason universities have the opportunity to create the culture of sustainability for today’s student, and to set their expectations for how the world should be. This thesis aim at analyzing how Delft University of Technology and University of Bologna face the challenge of becoming a sustainable campus. In this context, both universities have been studied and analyzed following the International Sustainable Campus Network (ISCN) methodology that provides a common framework to formalize commitments and goals at campus level. In particular this work has been aimed to highlight which key performance indicators are essential to reach sustainability as a consequence the following aspects has been taken into consideration: energy use, water use, solid waste and recycling, carbon emission. Subsequently, in order to provide a better understanding of the current state of sustainability on University of Bologna and Delft University of Technology, and potential strategies to achieve the stated objective, a SWOT Analysis has been undertaken. Strengths, weaknesses, opportunities and threats have been shown to understand how the two universities can implement a synergy to improve each other. In the direction of framing a “Sustainable SWOT” has been considered the model proposed by People and Planet, so it has been necessary to evaluate important matters as for instance policy, investment, management, education and engagement. Regarding this, it has been fundamental to involve the main sustainability coordinators of the two universities, this has been achieved through a brainstorming session. Partnerships are key to the achievement of sustainability. The creation of a bridge between two universities aims to join forces and to create a new generation of talent. As a result, people can become able to support universities in the exchange of information, ideas, and best practices for achieving sustainable campus operations and integrating sustainability in research and teaching. For this purpose the project "SUCCESS" has been presented, the project aims to create an interactive European campus network that can be considered a strategic key player for sustainable campus innovation in Europe. Specifically, the main key performance indicators have been analyzed and the importance they have for the two universities and their strategic impact have been highlighted. For this reason, a survey was conducted with people who play crucial roles for sustainability within the two universities and they were asked to evaluate the KPIs of the project. This assessment has been relevant because has represented the foundation to develop a strategy to create a true collaboration.

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The 5th generation of mobile networking introduces the concept of “Network slicing”, the network will be “sliced” horizontally, each slice will be compliant with different requirements in terms of network parameters such as bandwidth, latency. This technology is built on logical instead of physical resources, relies on virtual network as main concept to retrieve a logical resource. The Network Function Virtualisation provides the concept of logical resources for a virtual network function, enabling the concept virtual network; it relies on the Software Defined Networking as main technology to realize the virtual network as resource, it also define the concept of virtual network infrastructure with all components needed to enable the network slicing requirements. SDN itself uses cloud computing technology to realize the virtual network infrastructure, NFV uses also the virtual computing resources to enable the deployment of virtual network function instead of having custom hardware and software for each network function. The key of network slicing is the differentiation of slice in terms of Quality of Services parameters, which relies on the possibility to enable QoS management in cloud computing environment. The QoS in cloud computing denotes level of performances, reliability and availability offered. QoS is fundamental for cloud users, who expect providers to deliver the advertised quality characteristics, and for cloud providers, who need to find the right tradeoff between QoS levels that has possible to offer and operational costs. While QoS properties has received constant attention before the advent of cloud computing, performance heterogeneity and resource isolation mechanisms of cloud platforms have significantly complicated QoS analysis and deploying, prediction, and assurance. This is prompting several researchers to investigate automated QoS management methods that can leverage the high programmability of hardware and software resources in the cloud.

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SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

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In 1906, two American industrialists, John Munroe Longyear and Frederick Ayer, formed the Arctic Coal Company to make the first large scale attempt at mining in the high-Arctic location of Spitsbergen, north of the Norwegian mainland. In doing so, they encountered numerous obstacles and built an organization that attempted to overcome them. The Americans sold out in 1916 but others followed, eventually culminating in the transformation of a largely underdeveloped landscape into a mining region. This work uses John Law’s network approach of the Actor Network Theory (ANT) framework to explain how the Arctic Coal Company built a mining network in this environmentally difficult region and why they made the choices they did. It does so by identifying and analyzing the problems the company encountered and the strategies they used to overcome them by focusing on three major components of the operations; the company’s four land claims, its technical system and its main settlement, Longyear City. Extensive comparison between aspects of Longyear City and the company’s choices of technology with other American examples place analysis of the company in a wider context and helps isolate unique aspects of mining in the high-Arctic. American examples dominate comparative sections because Americans dominated the ownership and upper management of the company.

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This thesis attempts to understand why people adopt or reject individual-use renewable energy technologies (IURET). I used factors from Everett Rogers' Diffusion of Innovation Theory to understand how people's perceptions towards the characteristics of a given IURET (such as price, compatibility, complexity, etc.), the characteristics of the individual adopter (such as innovativeness and environmental awareness), and the communication network (inter-personal communications and mass media) can influence adoption. An online questionnaire was sent to 101randomly selected Michigan households (using random digit dialing) to ask people whether or not they had adopted at least one IURET and to assess the above-mentioned factors from Rogers' theory. Data analysis was then conducted in SPSS using Chi-squared and binary logistic regression to determine the relationship between adoption behaviors (the dependent variable) and the factors from Rogers' theory (the independent variables) while controlling for education. The results show that Rogers' factors of price and observability and the control variable of education were all significant in explaining adoption but the other factors of Rogers' theory were not. For example, if individuals perceive the price of IURET to be reasonable or if they observe their neighbors using these technologies, then they are more likely to adopt. These results indicate that, if we want to promote greater adoption of IURET, we should focus our efforts on making the price of IURET more affordable through incentives and other mechanisms. Adopters should also be given some form of reward if they provide free demonstrations of their IURET in use to their neighbors to take advantage of the observability effects.

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This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

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In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

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A decision support system based on a neural network approach is proposed to advise on insulin regime and dose adjustment for type 1 diabetes patients.