Structure and luminescent properties of YAG : Eu, Bi synthesized by sol-gel method

(Y1-xEux)(3)Al5O12 and (Y1-x-yEuxBiy)(3)Al5O12 were prepared by so-gel method. Their structures of the luminophor are similar to that of YAG, which is recorded on the ASTM card and belongs to a cubic system. The luminescent properties show that the reaction temperature of the current sol-gel method is in the range of 400-500 degrees C, which is lower than that of the conventional solid state reaction. The luminophors have the strongest emission intensity when the values of x and y are 0.06 and 0.013, respectively.

酚酞型聚芳醚砜(Ⅶ):K_2C0_3存在下PP/DCDPS体系聚合反应机理的研究

利用~(13)C-NMR方法研究了弱碱K_2CO_3存在下酚酞成盐反应及其与活性双卤砜亲核缩聚反应过程中的结构特征。对一系列碱性条件下酚酞(PP)与4,4'-二氯二苯砜(DCDPS)的缩聚反应的研究表明任何影响内酯结构酚酞盐生成的因素都会严重阻碍聚合反应的进行。对模型化合物存在下K_2CO_3在极性非质子溶剂中的溶解/解离行为的研究结果表明酚酞类Card。双酚与固体K_2CO_3之间可能存在着一种特殊的络合作用。基于我们系列研究结果,本文中总结提出了弱碱K_2CO_3存在下酚酞的反应机理。

基于DSP的CANopen通讯协议的实现

CANopen是一种开放的应用层协议,其应用可以进一步提高系统的可靠性、通讯效率及灵活性,而且可以使产品具有很好的兼容性。本文采用CANopen通讯协议实现了CAN总线DSP系统与上位机CAN卡之间的通讯,并通过测试实验验证了信息传递的可靠性,保证了全数字网络化伺服驱动系统中对电机控制的准确性和实时性。

基于C8051的运动控制卡研制和应用

本文针对排爆机器人手臂多关节联动控制的需要,开发了一种具有高集成度的基于C8051单片机和CAN总线的运动控制卡。介绍了运动控制卡的原理及实施方案,同时给出了运动控制卡在机器人平台的应用实例。在排爆机器人平台上的应用表明该运动控制卡具有较高的精度及很好的可靠性和实时性。

仿人机器人腰机构控制及分析实验平台研究

介绍了一种新型的仿人机器人两自由度腰部结构,给出了该机构两个伺服电机的PID控制策略,建立了基于PC机CAN卡的网络控制平台,该平台可实现腰部机构的实时控制及实时机构控制响应特性分析,该平台还具有扩展性强、成本低的特点。

卷烟条盒包装质量检测机器视觉系统设计

为了避免人眼对产品外观质量检测时,人眼视觉疲劳所产生的产品错检、漏检,提出了基于机器视觉的烟支条盒包装质量检测系统的设计。该系统由光源、相机、图像采集卡和工业控制计算机组成视觉系统处理单元,应用定位配准、边缘检测和斑点分析等图像处理算法完成对产品缺陷的检测。该视觉检测系统已经在烟厂得到了实际应用,对今后开发类似的基于机器视觉的产品外观质量检测系统具有一定的参考价值和指导意义。

车道收费系统中USB接口通信卡的设计

带USB接口的设备使用方便,发展迅速,文章结合高速公路车道收费系统中的实际问题,详细介绍了设计一个USB接口通信卡的过程,包括电路设计、器件选择、固件设计、驱动程序及其应用程序设计。

基于DSRC的多功能不停车收费系统

DSRC标准是ISO/TC204制定的智能交通系统(ITS)中车—路信息通讯的协议。采用双片式ETC电子标签结合双界面IC卡的储值卡方案形成的多功能不停车收费系统,充分兼容了当前国内普遍应用的IC卡半自动收费方式,集中了IC卡收费系统和ETC收费系统的优点,方便、快捷、通行能力强,并解决了收费口的交通拥挤现象。

云南兰坪金顶超大型铅锌矿区镉的环境地球化学研究

矿产资源开采利用过程中导致的重金属环境污染问题日益严重。我国铅锌矿资源丰富，其开采利用过程中镉的环境污染也日益突出。本文通过对云南兰坪金顶Pb-Zn矿区矿床开采利用过程中镉等重金属元素的环境地球化学行为及矿区生态环境的研究，得出如下主要结论。 1. 矿石淋滤实验表明矿区部分氧化铅锌矿石可以很快被再次氧化或者被溶解并释放出大量镉等有害元素，滤出元素可以迅速发生沉淀或被沉淀物包裹，其释放能力表现为Zn>Pb>Cd。铅锌氧化矿石中菱锌矿组分含量是影响镉淋失的主要因素。在开放体系的水-岩作用下，矿区岩石、矿物的自然风化极易造成当地水系统中镉污染。 2. 矿区不同岩（矿）石中镉含量分布差异比较大，围岩中镉含量为50-650 ppm，平均310 ppm，原生矿中镉含量为14-2800 ppm，平均767 ppm，氧化矿中镉含量为110-8200 ppm，平均1661 ppm，其平均值最高。Zn、Cd地球化学性质的差异导致了二者在原生矿和氧化矿中的不同地球化学分配特点，原生矿Zn/Cd高于氧化矿Zn/Cd，表明氧化环境中镉更容易在氧化矿中富集，而锌更容易被氧化析出到环境中。氧化矿中Cd与Ca呈负相关，这表明Cd的富集和Ca的氧化淋失是同时进行的，并且还可能有Cd对Ca的类质同像代替存在。 3. 矿区上游对照区土壤中的高含量Cd浓度是因土壤母质层重金属高背景值造成的，而非人为污染。矿区中心区土壤受到严重Cd污染，可能与选厂、采场废石堆、尾矿库和露采矿山大范围暴露有关。矿区沿沘江下游两岸土壤中Cd含量远远超出上游土壤背景值和金顶全区土壤背景值，这可能是与污水灌溉有关。通过加权综合污染指数评价法发现矿区土壤污染的主要因子是Cd，其次是Zn和Pb，矿区土壤重金属污染贡献顺序为：Cd>Zn>Pb。矿区土壤污染主要表现为：矿区土壤污染有从中心区向沘江下游扩散区土壤中蔓延的趋势。 4. 矿区水体中出现较高含量的镉，高出天然河流中镉含量的50-100倍。矿区架崖山、北厂和跑马坪等采矿区水体中镉浓度范围在15-30 µg/L之间。矿区水体中镉含量水平表现为：矿山浅层地下水>矿山溪流水>沘江河水。研究结果表明，矿区沘江下游河段水体明显受镉污染，其中水体中镉的平均含量为15.7 µg/L，悬浮物中镉含量为49.3 mg/kg，沉积物中镉含量为203.7 mg/kg。矿区载镉岩石和矿物的自然风化是造成矿区水环境中镉污染的直接原因。 5. 跑马坪采场的废弃石具有较低的Cd含量，而北厂、架崖山采场的废弃石具有较高的Cd浓度，可能与废弃矿石类型本身差异有关。尾矿剖面中的Cd含量，在表层中随剖面深度呈递减趋势，在中层随剖面深度变化不明显，而在底层中明显富集。尾矿库表层尾矿样品中弱酸提取态和可还原态Cd高于底层尾矿样品，相比之下，表层尾矿中Cd等重金属元素易于释放到环境中，对环境的潜在危害大。老尾矿库尾矿砂中Cd金属总量高于新尾矿库尾矿砂，可能还是因为选矿工艺、技术的差异造成的。 6. 矿区污染段水体中硫同位素值较低，远远低于上游非污染区硫同位素值。矿区水体中δ34S值保持了金顶铅锌矿山源区矿山物质硫同位素的特征，显示了矿山来源物质的影响。根据水体硫酸盐中硫同位素稀释原理，研究发现沘江下游水体SO42-中85 %的硫来源于矿山物质。 7. 从矿区筛选出Cd、Zn、Pb的超富集植物共有4种：其中Cd超富集植物有2种，分别是本地生条裂萎陵菜（Potentilla lancinata Card. In Lecomte）和辣子草（Galinsoga parviflora Cav.）；Zn超富集植物仅发现有1种植物，为节节草（Equisetum ramosissmum Desf.）；Pb超富集植物发现了1种植物，为毛莲菜（Picris hieracioides L.）。这些植物均具备了超富集植物的基本特征，在污染土壤治理与修复方面具有一定的实践意义。 8. 建立了金顶铅锌矿山（床）地质环境模型。Cd的释放、迁移扩散模式为：雨水淋滤时，矿山固体废弃物产生富Cd的酸性或弱酸性矿山排水，通过下渗淋滤发生测向和垂向迁移，进入周边水体和土壤，然后被水系沉积物中针铁矿、方解石等吸附，并在沉降物中沉淀富集，导致矿区主要河流沘江水体的自净能力下降，加速水体的进一步恶化，破坏生物生存环境。矿区受污染水体、土壤和大气中的有害物质通过生物链进入动植物体内，进而危害人类健康。

海洛因成瘾者决策障碍及其行为机制的研究----短视行为及冲动、强迫和药物在决策中的作用

Addiction can be investigated from the perspective of decision making. Addicts usually make incorrect decisions when facing drug-related cues or they are driven to drugs, resulting in repeated drug seeking and taking. The present study adopted temporal discounting as behavioral task and on the basis of the fact that heroin addicts discounted more steeply than health participants (addicts preferred to choose immediate but smaller reward, regarded as myopia) which was consistent with previous research, three questions was raised and being concentrated on in this study. The first question was whether the character of myopia would be revealed in a somewhat complicated task? We designed a card game in which the participants were tested whether they would play the trump card in order to win a trick but not the whole game. Addicts played the trump card significantly earlier than controls did, indicating they focused on immediate single trick but not the game. Moreover, the performance in the card game and temporal discounting correlated significantly, suggesting addicts would display myopic decision not only in simply task like temporal discounting but also in task more complicated and similar to daily-life decision. Secondly, the present study adopted various kinds of temporal discounting tasks. In previous research, temporal discounting gain task was usually adopted. In the present study, we also adopted temporal discounting loss task. In either gain or loss task, there are two delayed amounts. Results showed in each decision condition addicts made poorer performance compared with control but in larger amount condition, addicts actually improved their decision performance. Meanwhile, addicts did not show loss aversion due to their close discount rates in gain and loss task while for controls, the discount rates were much lower in loss task than those in gain task. Thus we demonstrated that addicts were insensitive to negative outcomes by the method of temporal discounting. Finally, we investigated three mechanisms which exerted impacts on decision making. We adopted Go/NoGo task to test impulsivity and found addicts commits more errors (higher impulsivity) than controls did. We also designed a behavioral task which could be used to test drug-related compulsive behavior on human participants. Results showed addicts produced stereotyped key-pressing behavior when presented with drug-related cues. Furthermore, it was found participants with higher impulsivity displayed poorer performance in decision making but addicts with higher compulsivity only made poorer performance in smaller amount decision and the correlation between compulsivity and decision making was relative weak. In order to investigate the role of susceptibility and effect of drugs, we adopted years of abusing heroin as the indictor and discovered addicts with longer history of heroin abusing made poorer performance in smaller amount condition than addicts with shorter history. Also, the earlier the addicts began to use drug, the worse they would do in the smaller amount decision. The results here indicated drug itself could exert impact on decision making in certain condition. The present study revealed three characters of heroin addicts from the aspect of decision making: (1) focusing upon current benefit due to they preferred to choose immediate gain and delayed loss; (2) showed no loss aversion compared with healthy participants (3) inability to inhibit inappropriate response particularly when facing drug-related cue. These characters contribute to the facts that addicts seek and take drugs repeatedly while ignoring the negative consequences caused by abusing drugs.

NHS Wales e-library portal evaluation (For Informing Healthcare Strategy implementation programme)

Thomas, R. & Urquhart, C. NHS Wales e-library portal evaluation. (For Informing Healthcare Strategy implementation programme). Aberystwyth: Department of Information Studies, University of Wales Aberystwyth Follow-on to NHS Wales User Needs study Sponsorship: Informing Healthcare, NHS Wales

Strategies that students use to trace code: an analysis based in grounded theory

Fitzgerald, S., Simon, B., and Thomas, L. 2005. Strategies that students use to trace code: an analysis based in grounded theory. In Proceedings of the First international Workshop on Computing Education Research (Seattle, WA, USA, October 01 - 02, 2005). ICER '05. ACM, New York, NY, 69-80

Modelo de Aceitação da Tecnologia adaptado às compras online

Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos de obtenção do grau de Mestre em Ciências da Comunicação, ramo de Marketing e Publicidade

Energy harvesting system design and optimization for wireless sensor networks

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.

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency.