973 resultados para Dies (Metal-working) - Design and construction


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Act2 is a highly concurrent programming language designed to exploit the processing power available from parallel computer architectures. The language supports advanced concepts in software engineering, providing high-level constructs suitable for implementing artificially-intelligent applications. Act2 is based on the Actor model of computation, consisting of virtual computational agents which communicate by message-passing. Act2 serves as a framework in which to integrate an actor language, a description and reasoning system, and a problem-solving and resource management system. This document describes issues in Act2's design and the implementation of an interpreter for the language.

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An iminodiacetic acid (IDA)-type adsorbent is prepared at the one end of a capillary by covalently bonding IDA to the monolithic rods of macroporous poly(glycidyl methacrylate-co-ethylene dimethacrylate). Cu(II) is later introduced to the support via the interaction with IDA. By this means, polymer monolithic immobilized metal affinity chromatography (IMAC) materials are prepared. With such a column, IMAC for on-line concentration and capillary electrophoresis (CE) for the subsequent analysis are hyphenated for the analysis of peptides and proteins. The reproducibility of such a column has been proved good with relative standard deviations (RSDs) of dead time of less than 5% for injection-to-injection and 12% for column-to-column (n = 3). Through application on the analysis of standard peptides and real protein samples, such a technique has shown promising in proteome study.

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Transport and its energetic and environmental impacts affect our daily lives. The transport sector is the backbone of the United Kingdom’s economy with 2.3 million people being employed in this sector. With a high dependency on transport for passengers and freight and with the knowledge that oil reserves are rapidly decreasing a solution has to be identified for conserving fuel. Passenger vehicles account for 61% of the transport fuel consumed in the U.K. and should be seen as a key area to tackle. Despite the introduction and development of electric powered cars, the widespread infrastructure that is required is not in place and has attributed to their slow uptake, as well as the fact that the electric car’s performance is not yet comparable with the conventional internal combustion engine. The benefits of the introduction of kinetic energy recovery systems to be used in conjunction with internal combustion engines and designed such that the system could easily be fitted into future passenger vehicles are examined. In this article, a review of automobile kinetic energy recovery system is presented. It has been argued that the ultracapacitor technology offers a sustainable solution. An optimum design for the urban driving cycle experienced in the city of Edinburgh has been introduced. The potential for fuel savings is also presented

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Malicious software (malware) have significantly increased in terms of number and effectiveness during the past years. Until 2006, such software were mostly used to disrupt network infrastructures or to show coders’ skills. Nowadays, malware constitute a very important source of economical profit, and are very difficult to detect. Thousands of novel variants are released every day, and modern obfuscation techniques are used to ensure that signature-based anti-malware systems are not able to detect such threats. This tendency has also appeared on mobile devices, with Android being the most targeted platform. To counteract this phenomenon, a lot of approaches have been developed by the scientific community that attempt to increase the resilience of anti-malware systems. Most of these approaches rely on machine learning, and have become very popular also in commercial applications. However, attackers are now knowledgeable about these systems, and have started preparing their countermeasures. This has lead to an arms race between attackers and developers. Novel systems are progressively built to tackle the attacks that get more and more sophisticated. For this reason, a necessity grows for the developers to anticipate the attackers’ moves. This means that defense systems should be built proactively, i.e., by introducing some security design principles in their development. The main goal of this work is showing that such proactive approach can be employed on a number of case studies. To do so, I adopted a global methodology that can be divided in two steps. First, understanding what are the vulnerabilities of current state-of-the-art systems (this anticipates the attacker’s moves). Then, developing novel systems that are robust to these attacks, or suggesting research guidelines with which current systems can be improved. This work presents two main case studies, concerning the detection of PDF and Android malware. The idea is showing that a proactive approach can be applied both on the X86 and mobile world. The contributions provided on this two case studies are multifolded. With respect to PDF files, I first develop novel attacks that can empirically and optimally evade current state-of-the-art detectors. Then, I propose possible solutions with which it is possible to increase the robustness of such detectors against known and novel attacks. With respect to the Android case study, I first show how current signature-based tools and academically developed systems are weak against empirical obfuscation attacks, which can be easily employed without particular knowledge of the targeted systems. Then, I examine a possible strategy to build a machine learning detector that is robust against both empirical obfuscation and optimal attacks. Finally, I will show how proactive approaches can be also employed to develop systems that are not aimed at detecting malware, such as mobile fingerprinting systems. In particular, I propose a methodology to build a powerful mobile fingerprinting system, and examine possible attacks with which users might be able to evade it, thus preserving their privacy. To provide the aforementioned contributions, I co-developed (with the cooperation of the researchers at PRALab and Ruhr-Universität Bochum) various systems: a library to perform optimal attacks against machine learning systems (AdversariaLib), a framework for automatically obfuscating Android applications, a system to the robust detection of Javascript malware inside PDF files (LuxOR), a robust machine learning system to the detection of Android malware, and a system to fingerprint mobile devices. I also contributed to develop Android PRAGuard, a dataset containing a lot of empirical obfuscation attacks against the Android platform. Finally, I entirely developed Slayer NEO, an evolution of a previous system to the detection of PDF malware. The results attained by using the aforementioned tools show that it is possible to proactively build systems that predict possible evasion attacks. This suggests that a proactive approach is crucial to build systems that provide concrete security against general and evasion attacks.

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The Activity in GEriatric acute CARe (AGECAR) is a randomised control trial to assess the effectiveness of an intrahospital strength and walk program during short hospital stays for improving functional capacity of patients aged 75 years or older. Patien

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To evaluate the effects of chronic lead exposure on the nervous system in adults, a set of neurobehavioural and electrophysiological tests was administered to 99 lead exposed foundry employees and 61 unexposed workers. Current and past blood lead concentrations were used to estimate the degree of lead absorption; all previous blood lead concentrations had been less than or equal to 90 micrograms/100 ml. Characteristic signs (such as wrist extensor weakness) or symptoms (such as colic) of lead poisoning were not seen. Sensory conduction in the sural nerve was not affected. By contrast, various neurobehavioural functions deteriorated with increasing lead burden. Workers with blood lead concentrations between 40 and 60 micrograms/100 ml showed impaired performance on tests of verbal concept formation, visual/motor performance, memory, and mood. Thus impairment in central nervous system function in lead exposed adults occurred in the absence of peripheral nervous system derangement and increased in severity with increasing lead dose.

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Statistical Rate Monotonic Scheduling (SRMS) is a generalization of the classical RMS results of Liu and Layland [LL73] for periodic tasks with highly variable execution times and statistical QoS requirements. The main tenet of SRMS is that the variability in task resource requirements could be smoothed through aggregation to yield guaranteed QoS. This aggregation is done over time for a given task and across multiple tasks for a given period of time. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. SRMS feasibility test ensures that it is possible for a given periodic task set to share a given resource without violating any of the statistical QoS constraints imposed on each task in the set. The SRMS scheduling algorithm consists of two parts: a job admission controller and a scheduler. The SRMS scheduler is a simple, preemptive, fixed-priority scheduler. The SRMS job admission controller manages the QoS delivered to the various tasks through admit/reject and priority assignment decisions. In particular, it ensures the important property of task isolation, whereby tasks do not infringe on each other. In this paper we present the design and implementation of SRMS within the KURT Linux Operating System [HSPN98, SPH 98, Sri98]. KURT Linux supports conventional tasks as well as real-time tasks. It provides a mechanism for transitioning from normal Linux scheduling to a mixed scheduling of conventional and real-time tasks, and to a focused mode where only real-time tasks are scheduled. We overview the technical issues that we had to overcome in order to integrate SRMS into KURT Linux and present the API we have developed for scheduling periodic real-time tasks using SRMS.

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The flip-chip technology is a high chip density solution to meet the demand for very large scale integration design. For wireless sensor node or some similar RF applications, due to the growing requirements for the wearable and implantable implementations, flip-chip appears to be a leading technology to realize the integration and miniaturization. In this paper, flip-chip is considered as part of the whole system to affect the RF performance. A simulation based design is presented to transfer the surface mount PCB board to the flip-chip die package for the RF applications. Models are built by Q3D Extractor to extract the equivalent circuit based on the parasitic parameters of the interconnections, for both bare die and wire-bonding technologies. All the parameters and the PCB layout and stack-up are then modeled in the essential parts' design of the flip-chip RF circuit. By implementing simulation and optimization, a flip-chip package is re-designed by the parameters given by simulation sweep. Experimental results fit the simulation well for the comparison between pre-optimization and post-optimization of the bare die package's return loss performance. This design method could generally be used to transfer any surface mount PCB to flip-chip package for the RF systems or to predict the RF specifications of a RF system using the flip-chip technology.

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In this paper, the embedded capacitance material (ECM) is fabricated between the power and ground layers of the wireless sensor nodes, forming an integrated capacitance to replace the large amount of decoupling capacitors on the board. The ECM material, whose dielectric constant is 16, has the same size of the wireless sensor nodes of 3cm*3cm, with a thickness of only 14μm. Though the capacitance of a single ECM layer being only around 8nF, there are two reasons the ECM layers can still replace the high frequency decoupling capacitors (100nF in our case) on the board. The first reason is: the parasitic inductance of the ECM layer is much lower than the surface mount capacitors'. A smaller capacitance value of the ECM layer could achieve the same resonant frequency of the surface mount decoupling capacitors. Simulation and measurement fit this assumption well. The second reason is: more than one layer of ECM material are utilized during the design step to get a parallel connection of the several ECM capacitance layers, finally leading to a larger value of the capacitance and smaller value of parasitic. Characterization of the ECM is carried out by the LCR meter. To evaluate the behaviors of the ECM layer, time and frequency domain measurements are performed on the power-bus decoupling of the wireless sensor nodes. Comparison with the measurements of bare PCB board and decoupling capacitors solution are provided to show the improvement of the ECM layer. Measurements show that the implementation of the ECM layer can not only save the space of the surface mount decoupling capacitors, but also provide better power-bus decoupling to the nodes.

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With the proliferation of mobile wireless communication and embedded systems, the energy efficiency becomes a major design constraint. The dissipated energy is often referred as the product of power dissipation and the input-output delay. Most of electronic design automation techniques focus on optimising only one of these parameters either power or delay. Industry standard design flows integrate systematic methods of optimising either area or timing while for power consumption optimisation one often employs heuristics which are characteristic to a specific design. In this work we answer three questions in our quest to provide a systematic approach to joint power and delay Optimisation. The first question of our research is: How to build a design flow which incorporates academic and industry standard design flows for power optimisation? To address this question, we use a reference design flow provided by Synopsys and integrate in this flow academic tools and methodologies. The proposed design flow is used as a platform for analysing some novel algorithms and methodologies for optimisation in the context of digital circuits. The second question we answer is: Is possible to apply a systematic approach for power optimisation in the context of combinational digital circuits? The starting point is a selection of a suitable data structure which can easily incorporate information about delay, power, area and which then allows optimisation algorithms to be applied. In particular we address the implications of a systematic power optimisation methodologies and the potential degradation of other (often conflicting) parameters such as area or the delay of implementation. Finally, the third question which this thesis attempts to answer is: Is there a systematic approach for multi-objective optimisation of delay and power? A delay-driven power and power-driven delay optimisation is proposed in order to have balanced delay and power values. This implies that each power optimisation step is not only constrained by the decrease in power but also the increase in delay. Similarly, each delay optimisation step is not only governed with the decrease in delay but also the increase in power. The goal is to obtain multi-objective optimisation of digital circuits where the two conflicting objectives are power and delay. The logic synthesis and optimisation methodology is based on AND-Inverter Graphs (AIGs) which represent the functionality of the circuit. The switching activities and arrival times of circuit nodes are annotated onto an AND-Inverter Graph under the zero and a non-zero-delay model. We introduce then several reordering rules which are applied on the AIG nodes to minimise switching power or longest path delay of the circuit at the pre-technology mapping level. The academic Electronic Design Automation (EDA) tool ABC is used for the manipulation of AND-Inverter Graphs. We have implemented various combinatorial optimisation algorithms often used in Electronic Design Automation such as Simulated Annealing and Uniform Cost Search Algorithm. Simulated Annealing (SMA) is a probabilistic meta heuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. We used SMA to probabilistically decide between moving from one optimised solution to another such that the dynamic power is optimised under given delay constraints and the delay is optimised under given power constraints. A good approximation to the global optimum solution of energy constraint is obtained. Uniform Cost Search (UCS) is a tree search algorithm used for traversing or searching a weighted tree, tree structure, or graph. We have used Uniform Cost Search Algorithm to search within the AIG network, a specific AIG node order for the reordering rules application. After the reordering rules application, the AIG network is mapped to an AIG netlist using specific library cells. Our approach combines network re-structuring, AIG nodes reordering, dynamic power and longest path delay estimation and optimisation and finally technology mapping to an AIG netlist. A set of MCNC Benchmark circuits and large combinational circuits up to 100,000 gates have been used to validate our methodology. Comparisons for power and delay optimisation are made with the best synthesis scripts used in ABC. Reduction of 23% in power and 15% in delay with minimal overhead is achieved, compared to the best known ABC results. Also, our approach is also implemented on a number of processors with combinational and sequential components and significant savings are achieved.

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Wireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments.

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Drug delivery systems influence the various processes of release, absorption, distribution and elimination of drug. Conventional delivery methods administer drug through the mouth, the skin, transmucosal areas, inhalation or injection. However, one of the current challenges is the lack of effective and targeted oral drug administration. Development of sophisticated strategies, such as micro- and nanotechnology that can integrate the design and synthesis of drug delivery systems in a one-step, scalable process is fundamental in advancing the limitations of conventional processing techniques. Thus, the objective of this thesis is to evaluate novel microencapsulation technologies in the production of size-specific and target-specific drug-loaded particles. The first part of this thesis describes the utility of PDMS and silicon microfluidic flow focusing devices (MFFDs) to produce PLGA-based microparticles. The formation of uniform droplets was dependent on the surface of PDMS remaining hydrophilic. However, the durability of PDMS was limited to no more than 1 hour before wetting of the microchannel walls with dichloromethane and subsequent swelling occurred. Critically, silicon MFFDs revealed very good solvent compatibility and was sufficiently robust to withstand elevated fluid flow rates. Silicon MFFDs facilitated experiments to run over days with continuous use and re-use of the device with a narrower microparticle size distribution, relative to conventional production techniques. The second part of this thesis demonstrates an alternative microencapsulation technology, SmPill® minispheres, to target CsA delivery to the colon. Characterisation of CsA release in vitro and in vivo was performed. By modulating the ethylcellulose:pectin coating thickness, release of CsA in-vivo was more effectively controlled compared to current commercial CsA formulations and demonstrated a linear in-vitro in-vivo relationship. Coated minispheres were shown to limit CsA release in the upper small intestine and enhance localised CsA delivery to the colon.

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The de novo design of membrane proteins remains difficult despite recent advances in understanding the factors that drive membrane protein folding and association. We have designed a membrane protein PRIME (PoRphyrins In MEmbrane) that positions two non-natural iron diphenylporphyrins (Fe(III)DPP's) sufficiently close to provide a multicentered pathway for transmembrane electron transfer. Computational methods previously used for the design of multiporphyrin water-soluble helical proteins were extended to this membrane target. Four helices were arranged in a D(2)-symmetrical bundle to bind two Fe(II/III) diphenylporphyrins in a bis-His geometry further stabilized by second-shell hydrogen bonds. UV-vis absorbance, CD spectroscopy, analytical ultracentrifugation, redox potentiometry, and EPR demonstrate that PRIME binds the cofactor with high affinity and specificity in the expected geometry.