ASDTIC control and standardized interface circuits applied to buck, parallel and buck-boost dc to dc power converters

Versatile standardized pulse modulation nondissipatively regulated control signal processing circuits were applied to three most commonly used dc to dc power converter configurations: (1) the series switching buck-regulator, (2) the pulse modulated parallel inverter, and (3) the buck-boost converter. The unique control concept and the commonality of control functions for all switching regulators have resulted in improved static and dynamic performance and control circuit standardization. New power-circuit technology was also applied to enhance reliability and to achieve optimum weight and efficiency

Can biological quantum networks solve NP-hard problems?

There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines. During the last decades the question has therefore been raised whether we need to consider quantum effects to explain the imagined cognitive power of a conscious mind. This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness and cognition. The purpose is to be able to identify and evaluate instances where quantum effects might play a significant role in cognitive processes. Not surprisingly, the conclusion is that quantum-enhanced cognition and intelligence are very unlikely to be found in biological brains. Quantum effects may certainly influence the functionality of various components and signalling pathways at the molecular level in the brain network, like ion ports, synapses, sensors, and enzymes. This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. So, the conclusion is that biological quantum networks can only approximately solve small instances of NP-hard problems. On the other hand, artificial intelligence and machine learning implemented in complex dynamical systems based on genuine quantum networks can certainly be expected to show enhanced performance and quantum advantage compared with classical networks. Nevertheless, even quantum networks can only be expected to efficiently solve NP-hard problems approximately. In the end it is a question of precision - Nature is approximate.Comment: 38 page

Distributed Generation and Islanding – Study on Converter Modeling of PV Grid-Connected Systems under Islanding Phenomena

Thailand government has launched a 15-year (2008-2022) strategic plan on new and renewable energy. Possible electricity generated from solar photovoltaic has been estimated with a potential of 50,000 MW, whereas at present the cumulative installed wattage is only 32 MW. Under the Plan, numbers of measures and incentives are provided for participation of private very small power producers (VSPP) generating and selling the electricity into the utilities. Most VSPPs generate electricity from renewable sources such as mini-hydro, biogas and biomass, wind and solar. Examples of measures and incentives are the Renewable Portfolio Standard (RPS) for the generating utility and independent power producers (IPP), a feed in tariff with an extra adder, soft loans and tax reduction. The past decade in Thailand has seen shifts from PV used in the public market through government demonstration projects to the consumer market, installations of PV VSPPs and domestic roof-top grid connected PV units gain momentum. With the government incentive more households will be attracted to produce electricity from solar PV and wind energy. As domestic roof sizes are limited, PV roof-top grid-connected units will be of small capacity, less than 10 kW. It is this possible large expansion of market for thousands of small PV rooftop grid-connected units or wind systems in Thailand, and eastern Asia, that draws our attention to the study of single phase distributed generator grid-connected systems. Our focus will be on the anti-islanding protection, which is of concerns to Thai electrical utilities. In order to know the behavior and the effect of anti-islanding techniques, the converter modeling of PV grid-connected systems under islanding phenomena is studied. The approach of modeling is to model a dc-ac full bridge switching converter PV grid-connected system under islanding phenomena using two mathematical modeling techniques. One corresponds to a state-space averaging technique (no linearization) and the other a piecewise technique. The former technique applies a state-space averaging techniqu

An Analysis of Multiple Layered Networks

Current infrastructure network models of single functionality do not typically account for the interdependent nature of infrastructure networks. Infrastructure networks are generally modeled individually, as an isolated network or with minimal recognition of interactions. This research develops a methodology to model the individual infrastructure network types while explicitly modeling their interconnected effects. The result is a formulation built with two sets of variables (the original set to model infrastructure characteristics and an additional set representing cuts of interdependent elements). This formulation is decomposed by variable type using Benders Partitioning and solved to optimality using a Benders Partitioning algorithm. Current infrastructure network models of single functionality do not typically account for the interdependent nature of infrastructure networks, Infrastructure networks are generally modeled individually, as an isolated network or with minimal recognition of interactions, This research develops a methodology to model the individual infrastructure network types while explicitly modeling their interconnected effects, The result is a formulation built with two sets of variables (the original set to model infrastructure characteristics and an additional set representing cuts of interdependent elements) This formulation is decomposed by variable type using Benders\u27 Partitioning and solved to optimality using a Benders\u27 Partitioning algorithm

Design of a Cost-Efficient Reconfigurable Pipeline ADC

Power budget is very critical in the design of battery-powered implantable biomedical instruments. High speed, high resolution and low power usually cannot be achieved at the same time. Therefore, a tradeoff must be made to compromise every aspect of those features. As the main component of the bioinstrument, high conversion rate, high resolution ADC consumes most of the power. Fortunately, based on the operation modes of the bioinstrument, a reconfigurable ADC can be used to solve this problem. The reconfigurable ADC will operate at 10-bit 40 MSPS for the diagnosis mode and at 8-bit 2.5 MSPS for the monitor mode. The ADC will be completely turned off if no active signal comes from sensors or if an off command is received from the antenna. By turning off the sample hold stage and the first two stages of the pipeline ADC, a significant power saving is achieved. However, the reconfigurable ADC suffers from two drawbacks. First, the leakage signals through the extra off-state switches in the third stage degrade the performance of the data converter. This situation tends to be even worse for high speed and high-resolution applications. An interference elimination technique has been proposed in this work to solve this problem. Simulation results show a significant attenuation of the spurious tones. Moreover, the transistors in the OTA tend to operate in weak inversion region due to the scaling of the bias current. The transistor in subthreshold is very slow due to the small transit frequency. In order to get a better tradeoff between the transconductance efficiency and the transit frequency, reconfigurable OTAs and scalable bias technique are devised to adjust the operating point from weak inversion to moderate inversion. The figure of merit of the reconfigurable ADC is comparable to the previously published conventional pipeline ADCs. For the 10-bit, 40 MSPS mode, the ADC attains a 56.9 dB SNDR for 35.4 mW power consumption. For the 8-bit 2.5 MSPS mode, the ADC attains a 49.2 dB SNDR for 7.9 mW power consumption. The area for the core layout is 1.9 mm2 for a 0.35 micrometer process

Getting Things Done: The Science behind Stress-Free Productivity

Allen (2001) proposed the “Getting Things Done” (GTD) method for personal productivity enhancement, and reduction of the stress caused by information overload. This paper argues that recent insights in psychology and cognitive science support and extend GTD’s recommendations. We first summarize GTD with the help of a flowchart. We then review the theories of situated, embodied and distributed cognition that purport to explain how the brain processes information and plans actions in the real world. The conclusion is that the brain heavily relies on the environment, to function as an external memory, a trigger for actions, and a source of affordances, disturbances and feedback. We then show how these principles are practically implemented in GTD, with its focus on organizing tasks into “actionable” external memories, and on opportunistic, situation-dependent execution. Finally, we propose an extension of GTD to support collaborative work, inspired by the concept of stigmergy