845 resultados para Design Technology


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Hybrid MIMO Phased-Array Radar (HMPAR) is an emerging technology that combines MIMO (multiple-in, multiple-out) radar technology with phased-array radar technology. The new technology is in its infancy, but much of the theoretical work for this specific project has already been completed and is explored in great depth in [1]. A brief overview of phased-array radar systems, MIMO radar systems, and the HMPAR paradigm are explored in this paper. This report is the culmination of an effort to support research in MIMO and HMPAR utilizing a concept called intrapulse beamscan. Using intrapulse beamscan, arbitrary spatial coverage can be achieved within one MIMO beam pulse. Therefore, this report focuses on designing waveforms for MIMO radar systems with arbitrary spatial coverage using that phenomenon. With intrapulse beamscan, scanning is done through phase-modulated signal design within one pulse rather than phase-shifters in the phased array over multiple pulses. In addition to using this idea, continuous phase modulation (CPM) signals are considered for their desirable peak-to-average ratio property as well as their low spectral leakage. These MIMO waveforms are designed with three goals in mind. The first goal is to achieve flexible spatial coverage while utilizing intrapulse beamscan. As with almost any radar system, we wish to have flexibility in where we send our signal energy. The second goal is to maintain a peak-to-average ratio close to 1 on the envelope of these waveforms, ensuring a signal that is close to constant modulus. It is desired to have a radar system transmit at the highest available power; not doing so would further diminish the already very small return signals. The third goal is to ensure low spectral leakage using various techniques to limit the bandwidth of the designed signals. Spectral containment is important to avoid interference with systems that utilize nearby frequencies in the electromagnetic spectrum. These three goals are realized allowing for limitations of real radar systems. In addition to flexible spatial coverage, the report examines the spectral properties of utilizing various space-filling techniques for desired spatial areas. The space-filling techniques examined include Hilbert/Peano curves and standard raster scans.

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High concentrations of fluoride naturally occurring in the ground water in the Arusha region of Tanzania cause dental, skeletal and non-skeletal fluorosis in up to 90% of the region’s population [1]. Symptoms of this incurable but completely preventable disease include brittle, discolored teeth, malformed bones and stiff and swollen joints. The consumption of high fluoride water has also been proven to cause headaches and insomnia [2] and adversely affect the development of children’s intelligence [3, 4]. Despite the fact that this array of symptoms may significantly impact a society’s development and the citizens’ ability to perform work and enjoy a reasonable quality of life, little is offered in the Arusha region in the form of solutions for the poor, those hardest hit by the problem. Multiple defluoridation technologies do exist, yet none are successfully reaching the Tanzanian public. This report takes a closer look at the efforts of one local organization, the Defluoridation Technology Project (DTP), to address the region’s fluorosis problem through the production and dissemination of bone char defluoridation filters, an appropriate technology solution that is proven to work. The goal of this research is to improve the sustainability of DTP’s operations and help them reach a wider range of clients so that they may reduce the occurrence of fluorosis more effectively. This was done first through laboratory testing of current products. Results of this testing show a wide range in uptake capacity across batches of bone char emphasizing the need to modify kiln design in order to produce a more consistent and high quality product. The issue of filter dissemination was addressed through the development of a multi-level, customerfunded business model promoting the availability of filters to Tanzanians of all socioeconomic levels. Central to this model is the recommendation to focus on community managed, institutional sized filters in order to make fluoride free water available to lower income clients and to increase Tanzanian involvement at the management level.

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A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

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Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lies in developing a brain-inspired architecture that can emulate human brain and can work for real time applications. In this report a flexible neural architecture is presented which consists of 128 X 128 SRAM crossbar memory and 128 spiking neurons. For Neuron, digital integrate and fire model is used. All components are designed in 45nm technology node. The core can be configured for certain Neuron parameters, Axon types and synapses states and are fully digitally implemented. Learning for this architecture is done offline. To train this circuit a well-known algorithm Restricted Boltzmann Machine (RBM) is used and linear classifiers are trained at the output of RBM. Finally, circuit was tested for handwritten digit recognition application. Future prospects for this architecture are also discussed.

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The demand for consumer goods in the developing world continues to rise as populations and economies grow. As designers, manufacturers, and consumers look for ways to address this growing demand, many are considering the possibilities of 3D printing. Due to 3D printing’s flexibility and relative mobility, it is speculated that 3D printing could help to meet the growing demands of the developing world. While the merits and challenges of distributed manufacturing with 3D printing have been presented, little work has been done to determine the types of products that would be appropriate for such manufacturing. Inspired by the author’s two years of Peace Corps service in the Tanzania and the need for specialty equipment for various projects during that time, an in-depth literature search is undertaken to better understand and summarize the process and capabilities of 3D printing. Human-centered design considerations are developed to focus on the product desirability, the technical feasibility, and the financial viability of using 3D printing within Tanzania. Beginning with concerns of what Tanzanian consumers desire, many concerns later arise in regards to the feasibility of creating products that would be sufficient in strength and quality for the demands of developing world consumers. It is only after these concerns are addressed that the viability of products can be evaluated from an economic perspective. The larger impacts of a product beyond its use are vital in determining how it will affect the social, economic, and environmental well-being of a developing nation such as Tanzania. Thus technology specific criteria are necessary for assessing and quantifying the broader impacts that a 3D-printed product can have within its ecosystem, and appropriate criteria are developed for this purpose. Both sets of criteria are then demonstrated and tested while evaluating the desirability, feasibility, viability, and sustainability of printing a piece of equipment required for the author’s Peace Corps service: a set of Vernier calipers. Required for science educators throughout the country, specialty equipment such as calipers initially appear to be an ideal candidate for 3D printing, though ultimately the printing of calipers is not recommended due to current restrictions in the technology. By examining more specific challenges and opportunities of the products 3D printing can produce, it can be better determined what place 3D printing will have in manufacturing for the developing world. Furthermore, the considerations outlined in this paper could be adapted for other manufacturing technologies and regions of the world, as human centered design and sustainability will be critical in determining how to supply the developing world with the consumer goods it demands.

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MT Hard Water of Montana Tech of the University of Montana submits Task 3: Treatment Technology Validation for Water Softening Technology as an entry into the 2012 WERC Environmental Design Contest. Currently, there are several commercially available technologies that treat water hardness. The objective of this project is to develop a strategy to evaluate and validate different water hardness treatment technologies. MT Hard Water (MTHW) has studied several technologies including: electromagnetic water treatment, ion exchange, and reverse osmosis. For validation purposes, an electromagnetic water treatment system (ScaleRID) was selected according to the WERC task description.

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SWISSspine is a so-called pragmatic trial for assessment of safety and efficiency of total disc arthroplasty (TDA). It follows the new health technology assessment (HTA) principle of "coverage with evidence development". It is the first mandatory HTA registry of its kind in the history of Swiss orthopaedic surgery. Its goal is the generation of evidence for a decision by the Swiss federal office of health about reimbursement of the concerned technologies and treatments by the basic health insurance of Switzerland. During the time between March 2005 and 2008, 427 interventions with implantation of 497 lumbar total disc arthroplasties have been documented. Data was collected in a prospective, observational multicenter mode. The preliminary timeframe for the registry was 3 years and has already been extended. Data collection happens pre- and perioperatively, at the 3 months and 1-year follow-up and annually thereafter. Surgery, implant and follow-up case report forms are administered by spinal surgeons. Comorbidity questionnaires, NASS and EQ-5D forms are completed by the patients. Significant and clinically relevant reduction of low back pain VAS (70.3-29.4 points preop to 1-year postop, p < 0.0001) leg pain VAS (55.5-19.1 points preop to 1-year postop, p < 0.001), improvement of quality of life (EQ-5D, 0.32-0.73 points preop to 1-year postop, p < 0.001) and reduction of pain killer consumption was revealed at the 1-year follow-up. There were 14 (3.9%) complications and 7 (2.0%) revisions within the same hospitalization reported for monosegmental TDA; there were 6 (8.6%) complications and 8 (11.4%) revisions for bisegmental surgery. There were 35 patients (9.8%) with complications during followup in monosegmental and 9 (12.9%) in bisegmental surgery and 11 (3.1%) revisions with 1 [corrected] new hospitalization in monosegmental and 1 (1.4%) in bisegmental surgery. Regression analysis suggested a preoperative VAS "threshold value" of about 44 points for increased likelihood of a minimum clinically relevant back pain improvement. In a short-term perspective, lumbar TDA appears as a relatively safe and efficient procedure concerning pain reduction and improvement of quality of life. Nevertheless, no prediction about the long-term goals of TDA can be made yet. The SWISSspine registry proofs to be an excellent tool for collection of observational data in a nationwide framework whereby advantages and deficits of its design must be considered. It can act as a model for similar projects in other health-care domains.

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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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The article introduces the E-learning Circle, a tool developed to assure the quality of the software design process of e-learning systems, considering pedagogical principles as well as technology. The E-learning Circle consists of a number of concentric circles which are divided into three sectors. The content of the inner circles is based on pedagogical principles, while the outer circle specifies how the pedagogical principles may be implemented with technology. The circle’s centre is dedicated to the subject taught, ensuring focus on the specific subject’s properties. The three sectors represent the student, the teacher and the learning objectives. The strengths of the E-learning Circle are the compact presentation combined with the overview it provides, as well as the usefulness of a design tool dealing with complexity, providing a common language and embedding best practice. The E-learning Circle is not a prescriptive method, but is useful in several design models and processes. The article presents two projects where the E-learning Circle was used as a design tool.

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ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

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Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.

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OBJECTIVES Optical scanners combined with computer-aided design and computer-aided manufacturing (CAD/CAM) technology provide high accuracy in the fabrication of titanium (TIT) and zirconium dioxide (ZrO) bars. The aim of this study was to compare the precision of fit of CAD/CAM TIT bars produced with a photogrammetric and a laser scanner. METHODS Twenty rigid CAD/CAM bars were fabricated on one single edentulous master cast with 6 implants in the positions of the second premolars, canines and central incisors. A photogrammetric scanner (P) provided digitized data for TIT-P (n=5) while a laser scanner (L) was used for TIT-L (n=5). The control groups consisted of soldered gold bars (gold, n=5) and ZrO-P with similar bar design. Median vertical distance between implant and bar platforms from non-tightened implants (one-screw test) was calculated from mesial, buccal and distal scanning electron microscope measurements. RESULTS Vertical microgaps were not significantly different between TIT-P (median 16μm; 95% CI 10-27μm) and TIT-L (25μm; 13-32μm). Gold (49μm; 12-69μm) had higher values than TIT-P (p=0.001) and TIT-L (p=0.008), while ZrO-P (35μm; 17-55μm) exhibited higher values than TIT-P (p=0.023). Misfit values increased in all groups from implant position 23 (3 units) to 15 (10 units), while in gold and TIT-P values decreased from implant 11 toward the most distal implant 15. SIGNIFICANCE CAD/CAM titanium bars showed high precision of fit using photogrammetric and laser scanners. In comparison, the misfit of ZrO bars (CAM/CAM, photogrammetric scanner) and soldered gold bars was statistically higher but values were clinically acceptable.