687 research outputs found

    FPGAs in Industrial Control Applications

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    The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs

    3D PRINTING, OPEN-SOURCE TECHNOLOGY AND THEIR APPLICATIONS IN RESEARCH

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    Open-source software received tremendous success as it drives down the cost of software and expand the distribution. Open-source hardware, as part of the open-source movement, has just risen into public attention for its potential to further drive down the cost of all kinds of manufacturing goods and reshape the manufacture chain. In this report we explores the history, development and the future of open-source hardware project, summarizing the opportunities, challenges and possible solutions. 3D printing is demonstrated as a booster to assist open-source hardware’s development. Low-cost 3D printer enables at-home and in-time fabrication, the download-print-use-improve-distribute cycle is established to encourage more to make and in turn to benefit more. Researchers, teachers and scientists are the first to receive the benefit since they are often lack of budget to purchase much expensive research tools with only limited function. To demonstrate the power of open-source 3D printing in driving down research cost. A library of 3D printable optics components are designed, printed and tested. The study shows significantly reduced research cost – more than 97% equipment investment is saved with some of the optical parts representing only 1% of the cost of its commercial version. Cost reduction stimulates a much broader participants that can further help in modifying, improving the project or even developing new project, this is how open-source hardware innovation chain is established. In the end it is summarized as the technology advances, printers suitable for all kinds of material such as metals, bio-materials, semiconductors are become feasible, the open-source paradigm has the potential to replace the tradition manufacture and activate the new future

    Vertical Optimizations of Convolutional Neural Networks for Embedded Systems

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Advances in SCA and RF-DNA Fingerprinting Through Enhanced Linear Regression Attacks and Application of Random Forest Classifiers

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    Radio Frequency (RF) emissions from electronic devices expose security vulnerabilities that can be used by an attacker to extract otherwise unobtainable information. Two realms of study were investigated here, including the exploitation of 1) unintentional RF emissions in the field of Side Channel Analysis (SCA), and 2) intentional RF emissions from physical devices in the field of RF-Distinct Native Attribute (RF-DNA) fingerprinting. Statistical analysis on the linear model fit to measured SCA data in Linear Regression Attacks (LRA) improved performance, achieving 98% success rate for AES key-byte identification from unintentional emissions. However, the presence of non-Gaussian noise required the use of a non-parametric classifier to further improve key guessing attacks. RndF based profiling attacks were successful in very high dimensional data sets, correctly guessing all 16 bytes of the AES key with a 50,000 variable dataset. With variable reduction, Random Forest still outperformed Template Attack for this data set, requiring fewer traces and achieving higher success rates with lower misclassification rate. Finally, the use of a RndF classifier is examined for intentional RF emissions from ZigBee devices to enhance security using RF-DNA fingerprinting. RndF outperformed parametric MDA/ML and non-parametric GRLVQI classifiers, providing up to GS =18.0 dB improvement (reduction in required SNR). Network penetration, measured using rogue ZigBee devices, show that the RndF method improved rogue rejection in noisier environments - gains of up to GS =18.0 dB are realized over previous methods

    Design and development of auxiliary components for a new two-stroke, stratified-charge, lean-burn gasoline engine

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    A unique stepped-piston engine was developed by a group of research engineers at Universiti Teknologi Malaysia (UTM), from 2003 to 2005. The development work undertaken by them engulfs design, prototyping and evaluation over a predetermined period of time which was iterative and challenging in nature. The main objective of the program is to demonstrate local R&D capabilities on small engine work that is able to produce mobile powerhouse of comparable output, having low-fuel consumption and acceptable emission than its crankcase counterpart of similar displacement. A two-stroke engine work was selected as it posses a number of technological challenges, increase in its thermal efficiency, which upon successful undertakings will be useful in assisting the group in future powertrain undertakings in UTM. In its carbureted version, the single-cylinder aircooled engine incorporates a three-port transfer system and a dedicated crankcase breather. These features will enable the prototype to have high induction efficiency and to behave very much a two-stroke engine but equipped with a four-stroke crankcase lubrication system. After a series of analytical work the engine was subjected to a series of laboratory trials. It was also tested on a small watercraft platform with promising indication of its flexibility of use as a prime mover in mobile platform. In an effort to further enhance its technology features, the researchers have also embarked on the development of an add-on auxiliary system. The system comprises of an engine control unit (ECU), a directinjector unit, a dedicated lubricant dispenser unit and an embedded common rail fuel unit. This support system was incorporated onto the engine to demonstrate the finer points of environmental-friendly and fuel economy features. The outcome of this complete package is described in the report, covering the methodology and the final characteristics of the mobile power plant

    Communications subsystem hardware and software development for the ESTCube-2 nanosatellite

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    One of the most crucial components of satellites is their communications subsystem. Without a functioning radio link, it would be challenging to receive telemetry and payload data from the satellite and send telecommands to it from the ground. ESTCube-2 is a 3U CubeSat from the Estonian Student Satellite Foundation that is expectedto launch in 2022. The mission of ESTCube-2 is to test various payloads inLEO. The primary payload being the plasma brake, similar to the Electric Solar Wind Sail (E-Sail) experiment on ESTCube-1. Due to the critical nature of the satellite communications system, it is essential to start with thorough testing early to reach high reliability by the launch. The goals for this master thesis are to test ESTCube-2 communications subsystem hardware and software, and to create an engineering model, to resolve any issues discovered

    Innovative intelligent sensors to objectively understand exercise interventions for older adults

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    The population of most western countries is ageing and, therefore, the ageing issue now matters more than ever. According to the reports of the United Nations in 2017, there were a total of 15.8 million (26.9%) people over 60 years of age in the United Kindom, and the numbers are projected to reach 23.5 million (31.5%) by 2050. Spending on medical treatment and healthcare for older adults accounts for two-fifths of the UK National Health Service (NHS) budget. Keeping older people healthy is a challenge. In general, exercise is believed to benefit both mental and physical health. Specifically, resistance band exercises are proven by many studies that they have potentially positive effects on both mental and physical health. However, treatment using resistance band exercise is usually done in unmonitored environments, such as at home or in a rehabilitation centre; therefore, the exercise cannot be measured and/or quantified accurately. Despite many years of research, the true effectiveness of resistance band exercises remains unclear. [Continues.]</div

    Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

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    Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques

    Design Techniques for High Performance Wireline Communication and Security Systems

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    As the amount of data traffic grows exponentially on the internet, towards thousands of exabytes by 2020, high performance and high efficiency communication and security solutions are constantly in high demand, calling for innovative solutions. Within server communication dominates todays network data transfer, outweighing between-server and server-to-user data transfer by an order of magnitude. Solutions for within-server communication tend to be very wideband, i.e. on the order of tens of gigahertz, equalizers are widely deployed to provide extended bandwidth at reasonable cost. However, using equalizers typically costs the available signal-to-noise ratio (SNR) at the receiver side. What is worse is that the SNR available at the channel becomes worse as data rate increases, making it harder to meet the tight constraint on error rate, delay, and power consumption. In this thesis, two equalization solutions that address optimal equalizer implementations are discussed. One is a low-power high-speed maximum likelihood sequence detection (MLSD) that achieves record energy efficiency, below 10 pico-Joule per bit. The other one is a phase-shaping equalizer design that suppresses inter-symbol interference at almost zero cost of SNR. The growing amount of communication use also challenges the design of security subsystems, and the emerging need for post-quantum security adds to the difficulties. Most of currently deployed cryptographic primitives rely on the hardness of discrete logarithms that could potentially be solved efficiently with a powerful enough quantum computer. Efficient post-quantum encryption solutions have become of substantial value. In this thesis a fast and efficient lattice encryption application-specific integrated circuit is presented that surpasses the energy efficiency of embedded processors by 4 orders of magnitude.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146092/1/shisong_1.pd
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