929 resultados para Hardware and software
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In this paper various techniques in relation to large-scale systems are presented. At first, explanation of large-scale systems and differences from traditional systems are given. Next, possible specifications and requirements on hardware and software are listed. Finally, examples of large-scale systems are presented.
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Augmented Reality (AR) is currently gaining popularity in multiple different fields. However, the technology for AR still requires development in both hardware and software when considering industrial use. In order to create immersive AR applications, more accurate pose estimation techniques to define virtual camera location are required. The algorithms for pose estimation often require a lot of processing power, which makes robust pose estimation a difficult task when using mobile devices or designated AR tools. The difficulties are even larger in outdoor scenarios where the environment can vary a lot and is often unprepared for AR. This thesis aims to research different possibilities for creating AR applications for outdoor environments. Both hardware and software solutions are considered, but the focus is more on software. The majority of the thesis focuses on different visual pose estimation and tracking techniques for natural features. During the thesis, multiple different solutions were tested for outdoor AR. One commercial AR SDK was tested, and three different custom software solutions were developed for an Android tablet. The custom software solutions were an algorithm for combining data from magnetometer and a gyroscope, a natural feature tracker and a tracker based on panorama images. The tracker based on panorama images was implemented based on an existing scientific publication, and the presented tracker was further developed by integrating it to Unity 3D and adding a possibility for augmenting content. This thesis concludes that AR is very close to becoming a usable tool for professional use. The commercial solutions currently available are not yet ready for creating tools for professional use, but especially for different visualization tasks some custom solutions are capable of achieving a required robustness. The panorama tracker implemented in this thesis seems like a promising tool for robust pose estimation in unprepared outdoor environments.
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Force plate or pressure plate analysis came as an innovative tool to biomechanics and sport medicine -- This allows engineers, scientists and doctors to virtually reconstruct the way a person steps while running or walking using a measuring system and a computer -- With this information they can calculate and analyze a whole set of variables and factors that characterize the step -- Then they are able to make corrections and/or optimizations, designing appropriate shoes and insoles for the patient -- The idea is to study and understand all the hardware and software implications of this process and all the components involved, and then propose an alternative solution -- This solution should have at least similar performance to existing systems -- It should increase the accuracy and/or the sampling frequency to obtain better results -- By the end, there should be a working prototype of a pressure measuring system and a mathematical model to govern it -- The costs of the system have to be lower than most of the systems in the market
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Esta tese pretende descrever o desenvolvimento e arquitectura do software que constitui o Miradouro Virtual@, mais especificamente do componente referente à interface. O Miradouro Virtual@ é um dispositivo cujo propósito à semelhança dos tradicionais binóculos turísticos, é observar a paisagem, mas cuja interacção não está limitada à simples observação individual. Recorre à realidade aumentada para sobrepôr imagens geradas por computador a imagens reais, capturadas por um dispositivo para aquisição de imagem real (tipicamente uma câmara de vídeo), e mostra-as num ecrã touchscreen, permitindo deste modo, combinar elementos virtuais e multimédia com a paisagem real. A imagem final, composta, dá ao utilizador uma nova dimensão do espaço envolvente, permitindo-lhe explorar uma nova camada de informação não visível anteriormente. Sendo sensíveis à orientação do Miradouro Virtual@, os elementos virtuais e multimédia adaptam-se de acordo com os movimentos do dispositivo. O Miradouro Virtual@ é um produto composto por diversos elementos de hardware e software. O foco desta tese recai apenas nos componentes de software, mais especificamente na interface. Pretende dar a conhecer as limitações da versão anterior do software e mostrar as soluções encontradas que permitiram ultrapassar algumas dessas limitações. ABSTRACT; This thesis focuses on the design and development of the Virtual Sightseeing™ software, more specifically on the interface component. The Virtual Sightseeing™ is a device similar to the traditional scenic viewers that takes advantage of its generally known and popularity to build an innovative system. It works by using augmented reality to superimpose, in real-time, images generated by a computer onto a live stream captured by a video camera and displaying them on a touchscreen display. It allows adding multimedia elements to the real scenery by composing them in the image that is presented to the user. The multimedia information and virtual elements that are displayed are sensitive to the orientation and position of the device. They change as the user manually changes the orientation of the device. The Virtual Sightseeing™ is comprised of several hardware and software components. The focus of this thesis is on the software part, more specifically on the interface component. It intends to show the known limitations of the previous software version and how they were overcome in this new version.
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El presente trabajo empleó herramientas de hardware y software de licencia libre para el establecimiento de una estación base celular (BTS) de bajo costo y fácil implementación. Partiendo de conceptos técnicos que facilitan la instalación del sistema OpenBTS y empleando el hardware USRP N210 (Universal Software Radio Peripheral) permitieron desplegar una red análoga al estándar de telefonía móvil (GSM). Usando los teléfonos móviles como extensiones SIP (Session Initiation Protocol) desde Asterisk, logrando ejecutar llamadas entre los terminales, mensajes de texto (SMS), llamadas desde un terminal OpenBTS hacia otra operadora móvil, entre otros servicios.
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Dataloggerit ovat tärkeitä mittaustekniikassa käytettäviä mittalaitteita, joiden tarkoituksena on kerätä talteen mittausdataa pitkiltä aikaväleiltä. Dataloggereita voidaan käyttää esimerkiksi teollista prosessia osana olevien toimilaitteiden tai kotitalouden energiajärjestelmän seurannassa. Teollisen luokan dataloggerit ovat yleensä hinnaltaan satojen tai tuhansien eurojen luokkaa. Työssä pyrittiin löytämään teollisen luokan laitteille halpa ja helppokäyttöinen vaihtoehto, joka on kuitenkin riittävän tehokas ja toimiva. Työssä suunniteltiin ja toteutettiin dataloggeri Raspberry Pi-alustalle ja testattiin sitä oikeaa teollista ympäristöä vastaavissa olosuhteissa. Kirjallisuudesta ja internet artikkeleista etsittiin samankaltaisia laite- ja ohjelmistoratkaisuja ja niitä käytettiin dataloggausjärjestelmän pohjana. Raspberry Pi-alustalle koodattiin yksinkertainen Python-kielinen data-loggausohjelma, joka käyttää Modbus-tiedonsiirtoprotokollaa. Testien perusteella voidaan todeta, että toteutettu dataloggeri on toimiva ja kykenee kaupallisten dataloggereiden tasoiseen mittaukseen ainakin pienillä näytteistystaajuuksilla. Toteutettu dataloggeri on myös huomattavasti kaupallisia dataloggereita halvempi. Helppokäyttöisyyden näkökulmasta dataloggerissa havaittiin puutteita, joita käydään läpi jatkokehitysideoiden muodossa.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade Gama, Programa de Pós-Graduação em Engenharia Biomédica, 2015.
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The development of robots has shown itself as a very complex interdisciplinary research field. The predominant procedure for these developments in the last decades is based on the assumption that each robot is a fully personalized project, with the direct embedding of hardware and software technologies in robot parts with no level of abstraction. Although this methodology has brought countless benefits to the robotics research, on the other hand, it has imposed major drawbacks: (i) the difficulty to reuse hardware and software parts in new robots or new versions; (ii) the difficulty to compare performance of different robots parts; and (iii) the difficulty to adapt development needs-in hardware and software levels-to local groups expertise. Large advances might be reached, for example, if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a framework for robots, TORP (The Open Robot Project), that aims to put forward a standardization in all dimensions (electrical, mechanical and computational) of a robot shared development model. This architecture is based on the dissociation between the robot and its parts, and between the robot parts and their technologies. In this paper, the first specification for a TORP family and the first humanoid robot constructed following the TORP specification set are presented, as well as the advances proposed for their improvement.
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Artes, Programa de Pós-Graduação em Arte, 2016.
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Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.
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Abstract: After developing many sensor networks using custom protocols to save energy and minimise code complexity - we have now experimented with standards-based designs. These use IPv6 (6LowPAN), RPL routing, Coap for interfaces and data access and protocol buffers for data encapsulation. Deployments in the Cairngorm mountains have shown the capabilities and limitations of the implementations. This seminar will outline the hardware and software we used and discuss the advantages of the more standards-based approach. At the same time we have been progressing with high quality imaging of cultural heritage using the RTIdomes - so some results and designs will be shown as well. So this seminar will cover peat-bogs to museums, binary-HTTP-like REST to 3500 year old documents written on clay.
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The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.
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Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.
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The project aims to experiment the Cone Beam Breast Computed Tomography technique using a standard digital mammography system. The work is focused on the definition of a protocol of quality measurements for the pre-clinical evaluation of the machine. The paper is developed in two parts. The first is specifically concerned with the methods used to define the image quality and dosimetry aspects specific for digital mammography devices. A complete characterization of the system has been performed according to the applicable IEC standards to assure the performances of the equipment and define the quality levels. Due to the lack of a quality control protocol dedicated to CBBCT mammography scanner, a new equivalent test procedure has been proposed. The second part of the paper is focused on the evaluation, through quantitative and visual analyzes, of the CBCT exam feasibility in the hardware and software conditions currently proposed by IMS Giotto. The prototype was in fact developed differing from the technical choices of competing companies and developed for a different intended use. The main difference with respect to the existing breast CT scanners is the possibility of performing on the same system the CBBCT scanning but also all the mammographic techniques. In this thesis, we aim to assess whether, in the current setup, considering a dosimetric range very close to that used in the clinic, the tests produce results that can be considered acceptable or at least indicative of the feasibility of the entire project from a commercial point of view. For this purpose, the final reconstruction images, obtained by two previously developed software, are analyzed.
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The IoT is growing more and more each year and is becoming so ubiquitous that it includes heterogeneous devices with different hardware and software constraints leading to an highly fragmented ecosystem. Devices are using different protocols with different paradigms and they are not compatible with each other; some devices use request-response protocols like HTTP or CoAP while others use publish-subscribe protocols like MQTT. Integration in IoT is still an open research topic. When handling and testing IoT sensors there are some common task that people may be interested in: reading and visualizing the current value of the sensor; doing some aggregations on a set of values in order to compute statistical features; saving the history of the data to a time-series database; forecasting the future values to react in advance to a future condition; bridging the protocol of the sensor in order to integrate the device with other tools. In this work we will show the working implementation of a low-code and flow-based tool prototype which supports the common operations mentioned above, based on Node-RED and Python. Since this system is just a prototype, it has some issues and limitations that will be discussed in this work.