A 75-81 GHz, 14.3 dBm Peak Output Power, 21 dB Peak Gain, SiGe Power-Combining Amplifier Operating from a Single 3.3 V Supply

A compact differential 4-way power combiner with 2.3 dB loss and high common-mode rejection characteristic for use in mm-wave PAs is presented. A complete circuit comprised of a power splitter, two-stage cascode PA array, and a power combiner was implemented in SiGe technology. Measured small-signal gain of at least 17 dB was obtained from 74.5 GHz to 80.5 GHz with a peak 21 dB at 79 GHz. The prototype delivered 13.2 dBm P1dB and 14.3 dBm Psat when operated from a single 3.3 V supply at 75 GHz.

Anticipatory Planning Reveals Segmentation of Cortical Motor Output During Action Observation

It has been argued that the variation in brain activity that occurs when observing another person reflects a representation of actions that is indivisible, and which plays out in full once the intent of the actor can be discerned. We used transcranial magnetic stimulation to probe the excitability of corticospinal projections to 2 intrinsic hand muscles while motions to reach and grasp an object were observed. A symbolic cue either faithfully indicated the required final orientation of the object and thus the nature of the grasp that was required, or was in conflict with the movement subsequently displayed. When the cue was veridical, modulation of excitability was in accordance with the functional role of the muscles in the action observed. If however the cue had indicated that the alternative grasp would be required, modulation of output to first dorsal interosseus was consistent with the action specified, rather than the action observed-until the terminal phase of the motion sequence during which the object was seen lifted. Modulation of corticospinal output during observation is thus segmented-it progresses initially in accordance with the action anticipated, and if discrepancies are revealed by visual input, coincides thereafter with that of the action seen.

Determination of Power System Response during Small Load Fluctuations

This paper proposes a calculation method to determine power system response during small load perturbations or minor disturbances. The method establishes the initial value of active power transient using traditional reduction technique on admittance matrix, which incorporates voltage variations in the determination. The method examines active power distribution among generators when several loads simultaneously change, and verifies that the superposition principle is applicable for this scenario. The theoretical derivation provided in the paper is validated by numerical simulations using a 3-generator 9-bus benchmark model. The results indicate that the inclusion of voltage variation renders an independent and precise measure of active power response during transient conditions.

The Impact of Wind Farm Power Oscillations on the Irish Power System

The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations has been investigated. The authors introduced data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. Through monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the two systems. The impact of tower shadow on the output power from a wind farm was analysed using data recorded on site. A case study investigates the effect on the system of the removal of a large fixed-speed wind farm. Conclusions are drawn on the impact that conventional generation and the output from fixed-speed wind farms have on the stability of the Irish power system.

Wind Farm Induced Oscillations

The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations was investigated. The authors used data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. By monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the Northern Ireland electricity system and that of the electricity supply board. Analysis was preformed to determine the relationship (if any) between the inter-area oscillation and the observed wind power generation at the corresponding time. Subsequently, regression analysis was introduced to model this relationship between the FFT output and the wind power generation. The effect of conventional generators on the magnitude and frequency of the inter-area oscillation was also considered.

Implementation of phantom-less IMRT delivery verification using Varian DynaLog files and R/V output

This study aims to evaluate the use of Varian radiotherapy dynamic treatment log (DynaLog) files to verify IMRT plan delivery as part of a routine quality assurance procedure. Delivery accuracy in terms of machine performance was quantified by multileaf collimator (MLC) position errors and fluence delivery accuracy for patients receiving intensity modulated radiation therapy (IMRT) treatment. The relationship between machine performance and plan complexity, quantified by the modulation complexity score (MCS) was also investigated. Actual MLC positions and delivered fraction of monitor units (MU), recorded every 50 ms during IMRT delivery, were extracted from the DynaLog files. The planned MLC positions and fractional MU were taken from the record and verify system MLC control file. Planned and delivered beam data were compared to determine leaf position errors with and without the overshoot effect. Analysis was also performed on planned and actual fluence maps reconstructed from the MLC control file and delivered treatment log files respectively. This analysis was performed for all treatment fractions for 5 prostate, 5 prostate and pelvic node (PPN) and 5 head and neck (H&N) IMRT plans, totalling 82 IMRT fields in ∼5500 DynaLog files. The root mean square (RMS) leaf position errors without the overshoot effect were 0.09, 0.26, 0.19 mm for the prostate, PPN and H&N plans respectively, which increased to 0.30, 0.39 and 0.30 mm when the overshoot effect was considered. Average errors were not affected by the overshoot effect and were 0.05, 0.13 and 0.17 mm for prostate, PPN and H&N plans respectively. The percentage of pixels passing fluence map gamma analysis at 3%/3 mm was 99.94 ± 0.25%, which reduced to 91.62 ± 11.39% at 1%/1 mm criterion. Leaf position errors, but not gamma passing rate, were directly related to plan complexity as determined by the MCS. Site specific confidence intervals for average leaf position errors were set at -0.03-0.12 mm for prostate and -0.02-0.28 mm for more complex PPN and H&N plans. For all treatment sites confidence intervals for RMS errors with the overshoot was set at 0-0.50 mm and for the percentage of pixels passing a gamma analysis at 1%/1 mm a confidence interval of 68.83% was set also for all treatment sites. This work demonstrates the successful implementation of treatment log files to validate IMRT deliveries and how dynamic log files can diagnose delivery errors not possible with phantom based QC. Machine performance was found to be directly related to plan complexity but this is not the dominant determinant of delivery accuracy.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Synchronous records of pCO2 and Δ14C suggest rapid, ocean-derived pCO2 fluctuations at the onset of Younger Dryas

Just before the onset of the Younger Dryas (YD) cold event, several stomatal proxy-based pCO2 records have shown a sharp increase in atmospheric CO2 concentration (pCO2) of between ca 50 and 100 ppm, followed by a rapid decrease of similar or even larger magnitude. Here we compare one of these records, a high-resolution pCO2 record from southern Sweden, with the IntCal13 record of radiocarbon (Δ14C). The two records show broadly synchronous fluctuations at the YD onset. Specifically, the IntCal13 record documents decreasing Δ14C just before the YD onset when pCO2 peaks, consistent with a source of “old” CO2 from the deep ocean. We propose that this fluctuation occurred due to a major ocean flushing event. The cause of the flushing event remains speculative but could be related to the hypothesis of the glacial ocean as a thermobaric capacitor. We confirm that the earth system can produce such large multi-decadal timescale fluctuations in pCO2 through simulating an artificial ocean flushing event with the GENIE Earth System Model. We suggest that sharp transitions of pCO2 may have remained undetected so far in ice cores due to inter-firn gas exchange and time-averaging. The stomatal proxy record is a powerful complement to the ice core records for the study of rapid climate change.

Design methodology for low power and arametric robustness through output-quality modulation:Application to color-interpolation filtering

Power dissipation and robustness to process variation have conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor upsizing for parametric-delay variation tolerance can be detrimental for power dissipation. However, for a class of signal-processing systems, effective tradeoff can be achieved between Vdd scaling, variation tolerance, and output quality. In this paper, we develop a novel low-power variation-tolerant algorithm/architecture for color interpolation that allows a graceful degradation in the peak-signal-to-noise ratio (PSNR) under aggressive voltage scaling as well as extreme process variations. This feature is achieved by exploiting the fact that all computations used in interpolating the pixel values do not equally contribute to PSNR improvement. In the presence of Vdd scaling and process variations, the architecture ensures that only the less important computations are affected by delay failures. We also propose a different sliding-window size than the conventional one to improve interpolation performance by a factor of two with negligible overhead. Simulation results show that, even at a scaled voltage of 77% of nominal value, our design provides reasonable image PSNR with 40% power savings. © 2006 IEEE.

Design methodology to trade off power, output quality and error resiliency: Application to color interpolation filtering

Power dissipation and tolerance to process variations pose conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. However, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between Vdd scaling, process tolerance and "output quality". In this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. The proposed architecture supports a graceful degradation in the PSNR (Peak Signal to Noise Ratio) under aggressive voltage scaling as well as extreme process variations in. sub-70nm technologies. This is achieved by exploiting the fact that some computations are more important and contribute more to the PSNR improvement compared to the others. The computations are mapped to the hardware in such a way that only the less important computations are affected by Vdd-scaling and process variations. Simulation results show that even at a scaled voltage of 60% of nominal Vdd value, our design provides reasonable image PSNR with 69% power savings.

DEPENDENCE OF LIGHT OUTPUT FROM NOMINALLY SMOOTH AL-OX-AU TUNNEL-JUNCTIONS ON ELECTRODE MORPHOLOGY

The light output from nominally smooth Al-Ox-Au tunnel junctions is observed to be substantially independent of the deposition rate of the Au film electrode. Films deposited quickly (2 nm s-1) and those deposited slowly (0.16 nm s-1) have similar spectral dependences and intensities. (This is in contrast to roughened films where those deposited quickly give out less light, especially towards the blue end of the spectrum.) The behaviour can be interpreted in terms of the ratio l(ph)/l(em) where l(ph) and l(em) are the mean free paths of surface plasmons between external photon emissions and internal electromagnetic absorptions respectively. Once l(ph)/l(em) exceeds 100, as it does on smooth films, grain size has little further effect on the spectral shape of the light output. In fast-deposited films there are two compensating effects on the output intensity: grain boundary scattering decreases it and greater surface roughness increases it.

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine’s previous operational performance, the DFIG’s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization (PSO)-based surrogate optimization techniques are used in conjunction with the finite element method (FEM) to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.