A low power fully differential RF receiver front-end for 2.4 GHz wireless sensor networks

In this paper, a novel merged LNA-mixer denoted as LNMA is proposed. The proposed LNMA consisting of a folded cascode LNA using improved derivative superposition technique and folded double-balanced subthreshold mixer using capacitor cross-coupled common-gate transconductor and it is integrated with on-chip LC voltage controlled oscillator (LC-VCO). In LNMA, a diode and power clamp based on-chip ESD protection circuit is used to tolerate ESD current of human-body-model specifications. To evaluate its performance, it is implemented in 0.18-µm MMRF CMOS process with 1-V supply, studied through post layout simulation and compared the results with other reported works. It achieves higher conversion gain of 27 dB, lower noise figure of 9.5 dB, lower input return loss (S11) of − 20 dB, higher third-order input intercept point (IIP₃) of – 16 dBm and higher IIP₂ of + 29.9 dBm compared to the works reported in the literature. The on-chip oscillator has the lower phase noise of – 114 dBc/Hz. The proposed LNMA and the LC-VCO achieves the power consumptions of 1.6 and 1.72 mW, respectively at 1-V power supply.

     

Parameterization of positively stabilizing feedbacks for single-input positive systems

This paper provides parameterizations of all positively stabilizing feedbacks for a particular class of finite-dimensional single-input positive systems, a method to yield these parameterizations by means of tools of linear programming and a convergence analysis which allows to extend the results to a particular infinite-dimensional system described by a parabolic partial differential equation. It also provides an academic standard example – the pure diffusion equation – to support the theoretical results.     

Adaptive EWMA procedures for monitoring processes subject to linear drifts

The conventional Statistical Process Control (SPC) techniques have been focused mostly on the detection of step changes in process means. However, there are often settings for monitoring linear drifts in process means, e.g., the gradual change due to tool wear or similar causes. The adaptive exponentially weighted moving average (AEWMA) procedures proposed by Yashchin (1995) have received a great deal of attention mainly for estimating and monitoring step mean shifts. This paper analyzes the performance of AEWMA schemes in signaling linear drifts. A numerical procedure based on the integral equation approach is presented for computing the average run length (ARL) of AEWMA charts under linear drifts in the mean. The comparison results favor the AEWMA chart under linear drifts. Some guidelines for designing AEWMA charts for detecting linear drifts are presented.     

Temporal dynamics of the impact of land use on modal disparity in commuting efficiency

Urban land use is known to affect commuting efficiency according to the excess commuting framework. However, most studies do not include temporal dynamics, and those that do, focus on decadal, yearly, or daily temporal resolutions. However, commuting is not a stationary spatial process. Since people leave home and start their jobs at different times of the day and since traffic congestion varies throughout the day, neglecting hourly dynamics can misestimate commuting efficiency in a region and lead to erroneous policy implications. Another important issue often overlooked in the past is the modal disparity in commuting efficiency and how it evolves during the day. To overcome these limitations, this research examines the commuting efficiency variation by car and public transport by six one-hour periods between 5 AM and 11 AM in Warsaw, Poland, using travel survey data and travel times generated from GPS-based big data for cars and from GTFS for public transport. We develop four different groups of modeling scenarios: no disaggregation, disaggregation by time, disaggregation by mode, and disaggregation by time and mode. Therefore, excess commuting and modal disparity metrics are applied for a total of 21 specific time and mode combinations. The results suggest that commuting efficiency is worst during the 8–9 AM period for both modes, and that public transport users are more efficient after 7 AM. Hourly variations in the excess commuting metrics imply that policy makers should examine ways to encourage flexible work hours to distribute work starts and to increase public transport frequencies in the off-peak.     

Direction coding using a tactile chair

This laboratory study examined the possibility of using a car seat instrumented with a tactile display to communicate directional information to a driver. A car seat fitted with an 8 × 8 matrix of vibrators embedded in the seat pan was used to code eight different directions. Localization response time and angular accuracy were examined as a function of stimulus direction, presence of a tactile attention cue, temporal pattern, stimulus layout, age, and gender. The mean absolute angular error was 23°, and both localization accuracy and response times were superior for the back left, backward, and back right directions. Of the various temporal pattern/attention cue combinations examined, results favored the relatively fast patterns consisting of vibration bursts of 125 or 250 ms without a centrally located attention cue over 500 ms bursts that were preceded by an attention cue. Observed age and gender effects were relatively modest, suggesting that using tactile cueing to communicate direction is effective across a wide range of users. In addition, the tactile stimulus was detected by more than 90% of the participants under surprise trial conditions. Overall, these results indicate that the tactile chair provides a promising and robust method of providing directional information.     

State-of-charge estimation for lead–acid batteries via embeddings and observers

In this paper, an approach is proposed to estimate the open-circuit voltage of a battery – and consequently the battery State-of-Charge during normal operation of electric vehicles – by only measuring the charge/discharge current and the voltage on the load. The result is achieved, without any knowledge of the characteristic values of the battery model, by combining a system embedding with a high-gain observer design strategy. Interestingly, the method is based on genuinely nonlinear estimation strategies, hence it does not suffer the typical drawbacks of linear approaches, including the requirement for persistence of excitation of the charge/discharge current.     

Predictive seam tracking with iteratively learned feedforward compensation for high-precision robotic laser welding

In this paper, a novel architecture for robotic seam tracking using an industrial robot and off-the-shelf sensors is proposed to compensate the residual errors that are commonly observed in high-precision robotic laser welding due to the nonlinearity of a seam and the fast path drifts along a robot path. Our experiments demonstrate that the robot system can track both linear and nonlinear long seams at a high speed of 100 mm/s with TCP offset-error within ±0.1 mm using the proposed method.     

Investigation of wear resistance and lifetime of diamond-like carbon (DLC) coated glass disk in flying height measurement process

Flying height has been greatly reduced to less than 10 nm to achieve high-density magnetic storage. This leads to significant disk wear especially, glass disks used in flying height measurement process. This paper reports the utilization of diamond-like carbon (DLC) overcoat to increase the wear resistance and lifetime of commercial glass disks in a flying height tester. Wear resistance of the DLC coated glass disks was investigated in wear test using a triboindentor. The results showed significant wear resistance improvement of the coated disk where the wear depth reduced from 62.2 nm on an uncoated disk to 5–7 nm on 15-nm thick DLC coated disks. Furthermore, lifetime measurement of the coated disk has been performed in a flying height tester. As a result, lifetime of the coated disk has been drastically improved by more than 30 times in comparison to an uncoated disk.     

LAI and fAPAR CYCLOPES global products derived from VEGETATION. Part 2: validation and comparison with MODIS collection 4 products

The main objective of this paper is the validation of CYCLOPES version 3.1 LAI and fAPAR products. It is achieved by the comparison with MODIS collection 4 and 4.1 products and ECOCLIMAP LAI climatology over the BELMANIP representative set of sites, and with ground measurements over a limited set of sites. Great attention is paid to the consistency of the comparison: for the spatial dimension, product PSF appears to be the main aspect governing the spatial resolution at which the comparison has to be achieved. For CYCLOPES, a minimal size of the sites should be 3 km × 3 km², while the optimal one is 10 km × 10 km²; regarding the temporal sampling interval and resolution, the problem is much easier to solve when assuming a relatively smooth time course of vegetation characteristics (8-16 days). Great care was also paid to the departure of products from the nominal definition, particularly for LAI where different scales of clumping have to be considered.Results showed that CYCLOPES and MODIS products have generally consistent seasonality, CYCLOPES being however characterized by a smoother temporal evolution as expected. Differences are mainly concentrated on the magnitude of products values, CYCLOPES achieving better performances both for LAI (RMSE = 0.73) and fAPAR (RMSE = 0.10) over the limited number of sites where ground measurements were available. This study also sets a framework to the validation exercise that could be used to evaluate other products or future versions of the same products and contribute to associate quantitative uncertainties as required by the user community.     

基于模糊模型的CMP过程智能R2R预测控制方法

针对化学机械研磨(CMP)过程非线性、时变和产品质量不易在线测量的特性,提出了一种基于T-S模糊模型的CMP过程智能run-to-run(R2R)预测控制器FIPR2R;通过G-K聚类算法和最小二乘法对CMP过程的T-S模糊预测模型离线辨识,解决了复杂CMP过程难以建立精确数学模型的难题和提高了模型预测精度;通过双指数加权移动平均(dEWMA)中对过程扰动及漂移进行估计的方法实现反馈校正和基于克隆选择算法的滚动优化求取最优控制律,提高了控制精度;性能分析结果表明,FIPR2R控制器的控制性能优于dEWMA方法,有效抑制了过程扰动和漂移的影响。     

Downscaling AVHRR land surface temperatures for improved surface urban heat island intensity estimation

Surface urban heat island (SUHI) is a phenomenon of both high spatial and temporal variability. In this context, studying and monitoring the SUHIs of urban areas through the satellite remote sensing technology, requires land surface temperature (LST) image data from satellite-borne thermal sensors of high spatial resolution as well as temporal resolution. However, due to technical constrains, satellite-borne thermal sensors yield a trade-off between their spatial and temporal resolution; a high spatial resolution is associated with a low temporal resolution and vice versa. To resolve this drawback, we applied in this study four downscaling techniques using different scaling factors to downscale 1-km LST image data provided by the Advanced Very High Resolution Radiometer (AVHRR) sensor, given that AVHRR can offer the highest temporal resolution currently available. The city of Athens in Greece was used as the application site. Downscaled 120-m AVHRR LSTs simulated by the downscaling techniques, were then used for SUHI intensity estimation based on LST differences observed between the main urban land covers of Athens and the city's rural background. For the needs of the study, land cover information for Athens was obtained from the Corine Land Cover (CLC) 2000 database for Greece. Validation of the downscaled 120-m AVHRR LSTs as well of the retrieved SUHI intensities was performed by comparative analysis with time-coincident observations of 120-m LST and SUHI intensities generated from the band 6 of the Thermal Mapper (TM) sensor onboard the Landsat 5 platform. The spatial pattern of the downscaled AVHRR LST was found to be visually improved when compared to that of the original AVHRR LST and to resemble more that of TM6 LST. Statistical results indicated that, when compared to 120-m TM6 LST, the root mean square error (RMSE) in 120-m AVHRR LST generated by the downscaling techniques ranged from 4.9 to 5.3 °C. However, the accuracy in SUHI intensity was found to have significantly improved, with a RMSE value decreasing from 2.4 °C when the original AVHRR LST was utilized, down to 0.94 °C in case that downscaling was applied.     

Characteristic patterns of QuikScat-based wind stress and turbulent heat flux in the tropical Indian Ocean

Using QuikScat-based vector wind data for 1999-2003, surface wind stress and turbulent heat (Q) have been mapped for the tropical Indian Ocean (IO) to understand their seasonal variability. During July wind stress is enhanced by ∼ 70% in the Arabian Sea compared to that during January. The Arabian Sea experiences a large Q loss (150-200 W/m²) during the summer and winter monsoons, which is nearly 1.3 times of that in the Bay of Bengal. The southeasterlies are strengthened during the southern hemisphere winter. Empirical Orthogonal Function analysis captures different phases of monsoon-induced variability in wind stress and Q, ranging from seasonal to high-frequency perturbations. Coherency between time coefficients of EOF-1 for wind stress and Q suggests that former leads the latter with a temporal lag of 20-40 days for period > 322 days. At high frequencies (< 21 days) Q leads wind stress with a temporal lag of 2 days. Possible explanation for wind stress leading Q over an annual time scale is offered based on the marine atmospheric boundary layer physics and pre-conditioned ocean surface, while on shorter time scales (21 days) ocean thermodynamics through mixed layer processes cause Q to lead wind stress.     

A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS

Investigating the temporal and spatial pattern of landscape disturbances is an important requirement for modeling ecosystem characteristics, including understanding changes in the terrestrial carbon cycle or mapping the quality and abundance of wildlife habitats. Data from the Landsat series of satellites have been successfully applied to map a range of biophysical vegetation parameters at a 30 m spatial resolution; the Landsat 16 day revisit cycle, however, which is often extended due to cloud cover, can be a major obstacle for monitoring short term disturbances and changes in vegetation characteristics through time.The development of data fusion techniques has helped to improve the temporal resolution of fine spatial resolution data by blending observations from sensors with differing spatial and temporal characteristics. This study introduces a new data fusion model for producing synthetic imagery and the detection of changes termed Spatial Temporal Adaptive Algorithm for mapping Reflectance Change (STAARCH). The algorithm is designed to detect changes in reflectance, denoting disturbance, using Tasseled Cap transformations of both Landsat TM/ETM and MODIS reflectance data. The algorithm has been tested over a 185 × 185 km study area in west-central Alberta, Canada. Results show that STAARCH was able to identify spatial and temporal changes in the landscape with a high level of detail. The spatial accuracy of the disturbed area was 93% when compared to the validation data set, while temporal changes in the landscape were correctly estimated for 87% to 89% of instances for the total disturbed area. The change sequence derived from STAARCH was also used to produce synthetic Landsat images for the study period for each available date of MODIS imagery. Comparison to existing Landsat observations showed that the change sequence derived from STAARCH helped to improve the prediction results when compared to previously published data fusion techniques.     

一种基于双层窗口的概念漂移数据流分类算法

数据流中概念漂移问题的研究已成为近年来流数据挖掘领域的研究热点之一. 已有的研究工作多依据单窗口中错误率的变化来检测概念漂移,难以适应不同类型的漂移. 为此, 本文提出一种新的基于双层窗口机制的数据流分类算法(Double-windows-based classification algorithm for concept drifting data streams, DWCDS),该算法采用随机决策树模型构建集成分类器, 利用双层窗口机制周期性地检测滑动窗口中流数据分布的变化,并动态地更新模型以适应概念漂移. 分析与实验结果表明: 该算法可以快速有效地跟踪检测含噪数据流中的概念漂移,且抗噪性能与分类精度显著提高.     

Technology of microthermoforming of complex three-dimensional parts with multiscale features

Thermoforming parts with micro-scale design features require use of thin polymer films. Low heat capacity and fragility of thin (<100 μm) polymer films requires new technical developments for precise heating and form pressure application. This paper will present results of an improved process based on a new replication machine. Temperature stability and pressure distribution is highly improved, even at reduced cycle times. With an upgraded temperature range microthermoforming of high temperature polymers is possible. This technology is well suited for the replication of three-dimensional micro parts with multiscale features. Replication of hollow parts with multiscale features is also possible. Outer dimension in macroscopic length scale and functional design features in microscopic length scale are combined with nanoscale surface structures in an affordable technology.     

Remote sensing of water clarity in Tampa Bay

We examined the spatial and temporal variability of the Secchi Disk Depth (SDD) within Tampa Bay, Florida, using the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) satellite imagery collected from September 1997 to December 2005. SDD was computed using a two-step process, first estimating the diffuse light attenuation coefficient at 490 nm, K_d(490), using a semi-analytical algorithm and then SDD using an empirical relationship with K_d(490). The empirical SDD algorithm (SDD = 1.04 × K_d(490)^− 0.82, 0.9 < SDD < 8.0 m, r² = 0.67, n = 80) is based on historical SDD observations collected by the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa Bay. SeaWiFS derived SDD showed distinctive seasonal variability, attributed primarily to chlorophyll concentrations and color in the rainy season and to turbidity in the dry season, which are in turn controlled by river runoff and winds or wind-induced sediment resuspension, respectively. The Bay also experienced strong interannual variability, mainly related to river runoff variability. As compared to in situ single measurements, the SeaWiFS data provide improved estimates of the “mean” water clarity conditions in this estuary because of the robust, frequent, and synoptic coverage. Therefore we recommend incorporation of this technique for routine monitoring of water quality in coastal and large estuarine waters like Tampa Bay.     

Ultrafast measurement of transient electroosmotic flow in microfluidics

We present a non-intrusive molecular dye based method, i.e., laser-induced fluorescence photobleaching anemometer (LIFPA), to significantly increase temporal resolution (TR) for velocity measurement of fast transient electrokinetic flows. To our knowledge, the TR has been for the first time achieved to 5–10 μs, about 100 times better than that published from state-of-the-art micro particle image velocimetry (μPIV), which is currently the most widely used velocimetry in the microfluidics community. The new method provides us with new opportunities to study experimentally the fundamental phenomena of unsteady electrokinetics (EK) and to validate relevant theoretical models. One application of the new method is demonstrated by measuring the rise time of DC electroosmotic flows (EOFs) in a microcapillary of 10 μm in diameter.     

Scaling laws of spatial visitation frequency: Applications for trip frequency prediction

The relationship of the built environment to human travel is one of the mainstream themes in urban studies. It provides a foundation for transport prediction. The existing literature is limited in accuracy when predicting spatial temporal travels from built environment. Understanding the scaling laws of spatial visitation frequency sheds new light on the issue. The scaling laws connect travel and the built environment by ordered-rankings, which make it possible to predict the number of arrivals from environmental variables. This research analyses the scaling laws of dynamic spatial visitation frequency using taxis' global positioning system (GPS) records, and proposes a model to predict spatial temporal arrivals from points of interest (POIs). The results show that: (i) the scaling law of spatial visitation frequency is exponential; (ii) the exponential scaling law is explained by the linear preferential attachment effect and a logarithmic travel growth process; (iii) the exponential scaling law is not sensitive to time; (iv) the proposed model predicts spatial temporal arrivals with high accuracy (R² > 0.6).     

A traffic cellular automata model based on road network grids and its spatial and temporal resolution’s influences on simulation

Microscopic Traffic Simulation Model based on Cellular Automata (CA) has become more and more popular since it was firstly introduced by Creamer and Ludwig in 1986. Cellular automata are simpler to implement on computers, provide a simple physical picture of the system and can be easily modified to deal with different aspects of traffic. However, in a traditional traffic CA model, the spatial resolution of CA and temporal resolution of simulation are low. Take TRANSIMS for example. The size of cellular automata is 7.5 m and the time step equals 1 s. In such a case, if a vehicle drives at a speed of 4 cells per s, the speed difference between 95 km/h (3.5 1 7.5 m/s) and 121 km/h (4.4999 1 7.5 m/s) will not be distinguished by simulation models. And the temporal resolution of 1 s makes the system hard to model different drivers’ reaction time, which plays a very important role in vehicular movement models. In this paper, a microscopic traffic cellular automata model based on road network grids is proposed to overcome the low spatial and temporal resolutions of traditional traffic CA models. In our model, spatial resolution can be changed by setting different grid size for lanes and intersections before or during simulation and temporal resolution can be defined according to simulation needs to model different drivers’ reaction time, whereas the vehicular movement models are still traditional CA models. By doing so, the low spatial and temporal resolution of CA model can be overcome and the advantages of using CA to simulate traffic are preserved. The paper also presents analyses of the influences on simulation of different 1D lane grid size, 2D intersection grid size and different combinations of temporal resolution and mean drivers’ reaction time. The analysis results prove the existence of spatial and temporal resolution thresholds in traffic CA models. They also reveal that the size of grids, the combinations of different temporal resolutions and mean drivers’ reaction time do pose influences on the speed of vehicles and lane/intersection occupancy, but do not affect the volume of traffic greatly.