Detecção de interface em tanques de petróleo usando transmissores de nível e controladores Fuzzy

This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs

Detecção de interface em tanques de petróleo usando transmissores de nível e controladores Fuzzy

This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs

Self-healing Techniques for RF and mm-Wave Transmitters and Receivers

With continuing advances in CMOS technology, feature sizes of modern Silicon chip-sets have gone down drastically over the past decade. In addition to desktops and laptop processors, a vast majority of these chips are also being deployed in mobile communication devices like smart-phones and tablets, where multiple radio-frequency integrated circuits (RFICs) must be integrated into one device to cater to a wide variety of applications such as Wi-Fi, Bluetooth, NFC, wireless charging, etc. While a small feature size enables higher integration levels leading to billions of transistors co-existing on a single chip, it also makes these Silicon ICs more susceptible to variations. A part of these variations can be attributed to the manufacturing process itself, particularly due to the stringent dimensional tolerances associated with the lithographic steps in modern processes. Additionally, RF or millimeter-wave communication chip-sets are subject to another type of variation caused by dynamic changes in the operating environment. Another bottleneck in the development of high performance RF/mm-wave Silicon ICs is the lack of accurate analog/high-frequency models in nanometer CMOS processes. This can be primarily attributed to the fact that most cutting edge processes are geared towards digital system implementation and as such there is little model-to-hardware correlation at RF frequencies.

All these issues have significantly degraded yield of high performance mm-wave and RF CMOS systems which often require multiple trial-and-error based Silicon validations, thereby incurring additional production costs. This dissertation proposes a low overhead technique which attempts to counter the detrimental effects of these variations, thereby improving both performance and yield of chips post fabrication in a systematic way. The key idea behind this approach is to dynamically sense the performance of the system, identify when a problem has occurred, and then actuate it back to its desired performance level through an intelligent on-chip optimization algorithm. We term this technique as self-healing drawing inspiration from nature's own way of healing the body against adverse environmental effects. To effectively demonstrate the efficacy of self-healing in CMOS systems, several representative examples are designed, fabricated, and measured against a variety of operating conditions.

We demonstrate a high-power mm-wave segmented power mixer array based transmitter architecture that is capable of generating high-speed and non-constant envelope modulations at higher efficiencies compared to existing conventional designs. We then incorporate several sensors and actuators into the design and demonstrate closed-loop healing against a wide variety of non-ideal operating conditions. We also demonstrate fully-integrated self-healing in the context of another mm-wave power amplifier, where measurements were performed across several chips, showing significant improvements in performance as well as reduced variability in the presence of process variations and load impedance mismatch, as well as catastrophic transistor failure. Finally, on the receiver side, a closed-loop self-healing phase synthesis scheme is demonstrated in conjunction with a wide-band voltage controlled oscillator to generate phase shifter local oscillator (LO) signals for a phased array receiver. The system is shown to heal against non-idealities in the LO signal generation and distribution, significantly reducing phase errors across a wide range of frequencies.

Reconfigurable transmitters for software-defined radios

Flexible radio transmitters based on the Software-Defined Radio (SDR) concept are gaining an increased research importance due to the unparalleled proliferation of new wireless standards operating at different frequencies, using dissimilar coding and modulation schemes, and targeted for different ends. In this new wireless communications paradigm, the physical layer of the radio transmitter must be able to support the simultaneous transmission of multi-band, multi-rate, multi-standard signals, which in practice is very hard or very inefficient to implement using conventional approaches. Nevertheless, the last developments in this field include novel all-digital transmitter architectures where the radio datapath is digital from the baseband up to the RF stage. Such concept has inherent high flexibility and poses an important step towards the development of SDR-based transmitters. However, the truth is that implementing such radio for a real world communications scenario is a challenging task, where a few key limitations are still preventing a wider adoption of this concept. This thesis aims exactly to address some of these limitations by proposing and implementing innovative all-digital transmitter architectures with inherent higher flexibility and integration, and where improving important figures of merit, such as coding efficiency, signal-to-noise ratio, usable bandwidth and in-band and out-of-band noise will also be addressed. In the first part of this thesis, the concept of transmitting RF data using an entirely digital approach based on pulsed modulation is introduced. A comparison between several implementation technologies is also presented, allowing to state that FPGAs provide an interesting compromise between performance, power efficiency and flexibility, thus making them an interesting choice as an enabling technology for pulse-based all-digital transmitters. Following this discussion, the fundamental concepts inherent to pulsed modulators, its key advantages, main limitations and typical enhancements suitable for all-digital transmitters are also presented. The recent advances regarding the two most common classes of pulse modulated transmitters, namely the RF and the baseband-level are introduced, along with several examples of state-of-the-art architectures found on the literature. The core of this dissertation containing the main developments achieved during this PhD work is then presented and discussed. The first key contribution to the state-of-the-art presented here consists in the development of a novel ΣΔ-based all-digital transmitter architecture capable of multiband and multi-standard data transmission in a very flexible and integrated way, where the pulsed RF output operating in the microwave frequency range is generated inside a single FPGA device. A fundamental contribution regarding the simultaneous transmission of multiple RF signals is then introduced by presenting and describing novel all-digital transmitter architectures that take advantage of multi-gigabit data serializers available on current high-end FPGAs in order to transmit in a time-interleaved approach multiple independent RF carriers. Further improvements in this design approach allowed to provide a two-stage up-conversion transmitter architecture enabling the fine frequency tuning of concurrent multichannel multi-standard signals. Finally, further improvements regarding two key limitations inherent to current all-digital transmitter approaches are then addressed, namely the poor coding efficiency and the combined high quality factor and tunability requirements of the RF output filter. The followed design approach based on poliphase multipath circuits allowed to create a new FPGA-embedded agile transmitter architecture that significantly improves important figures of merit, such as coding efficiency and SNR, while maintains the high flexibility that is required for supporting multichannel multimode data transmission.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.