Design of dual-frequency probe-fed microstrip antennas with genetic optimization algorithm

Cataloged from PDF version of article.Dual-frequency operation of antennas has become a necessity for many applications in recent wireless communication systems, such as GPS, GSM services operating at two different frequency bands, and services of PCS and IMT-2000 applications. Although there are various techniques to achieve dual-band operation from various types of microstrip antennas, there is no efficient design tool that has been incorporated with a suitable optimization algorithm. In this paper, the cavity-model based simulation tool along with the genetic optimization algorithm is presented for the design of dual-band microstrip antennas, using multiple slots in the patch or multiple shorting strips between the patch and the ground plane. Since this approach is based on the cavity model, the multiport approach is efficiently employed to analyze the effects of the slots and shorting strips on the input impedance. Then, the optimization of the positions of slots and shorting strips is performed via a genetic optimization algorithm, to achieve an acceptable antenna operation over the desired frequency bands. The antennas designed by this efficient design procedure were realized experimentally, and the results are compared. In addition, these results are also compared to the results obtained by the commercial electromagnetic simulation tool, the FEM-based software HFSS by ANSOFT

Simulating the Effects of Irrigation over the U.S. in a Land Surface Model Based on Satellite Derived Agricultural Data

A novel method is introduced for integrating satellite derived irrigation data and high-resolution crop type information into a land surface model (LSM). The objective is to improve the simulation of land surface states and fluxes through better representation of agricultural land use. Ultimately, this scheme could enable numerical weather prediction (NWP) models to capture land-atmosphere feedbacks in managed lands more accurately and thus improve forecast skill. Here we show that application of the new irrigation scheme over the continental US significantly influences the surface water and energy balances by modulating the partitioning of water between the surface and the atmosphere. In our experiment, irrigation caused a 12% increase in evapotranspiration (QLE) and an equivalent reduction in the sensible heat flux (QH) averaged over all irrigated areas in the continental US during the 2003 growing season. Local effects were more extreme: irrigation shifted more than 100 W/m from QH to QLE in many locations in California, eastern Idaho, southern Washington, and southern Colorado during peak crop growth. In these cases, the changes in ground heat flux (QG), net radiation (RNET), evapotranspiration (ET), runoff (R), and soil moisture (SM) were more than 3 W/m(sup 2), 20 W/m(sup 2), 5 mm/day, 0.3 mm/day, and 100 mm, respectively. These results are highly relevant to continental- to global-scale water and energy cycle studies that, to date, have struggled to quantify the effects of agricultural management practices such as irrigation. Based on the results presented here, we expect that better representation of managed lands will lead to improved weather and climate forecasting skill when the new irrigation scheme is incorporated into NWP models such as NOAA's Global Forecast System (GFS)

Pressure-tuning of the c-f hybridization in Yb metal detected by infrared spectroscopy up to 18 GPa

It has been known that the elemental Yb, a divalent metal at mbient pressure, becomes a mixed-valent metal under external pressure, with its valence reaching ~2.6 at 30 GPa. In this work, infrared spectroscopy has been used to probe the evolution of microscopic electronic states associated with the valence crossover in Yb at external pressures up to 18 GPa. The measured infrared reflectivity spectrum R(w) of Yb has shown large variations with pressure. In particular, R(w) develops a deep minimum in the mid-infrared, which shifts to lower energy with increasing pressure. The dip is attributed to optical absorption due to a conduction c-f electron hybridization state, similarly to those previously observed for heavy fermion compounds. The red shift of the dip indicates that the $c$-$f$ hybridization decreases with pressure, which is consistent with the increase of valence.Comment: 2 pages, to appear in J. Phys. Soc. Jpn. Supp

A Deeper Look at the New Milky Way Satellites: Sagittarius II, Reticulum II, Phoenix II, and Tucana III

We present deep Magellan/Megacam stellar photometry of four recently discovered faint Milky Way satellites: Sagittarius II (Sgr II), Reticulum II (Ret II), Phoenix II (Phe II), and Tucana III (Tuc III). Our photometry reaches ~2-3 magnitudes deeper than the discovery data, allowing us to revisit the properties of these new objects (e.g., distance, structural properties, luminosity measurements, and signs of tidal disturbance). The satellite color-magnitude diagrams show that they are all old (~13.5 Gyr) and metal-poor ([Fe/H]$\lesssim-2.2$). Sgr II is particularly interesting as it sits in an intermediate position between the loci of dwarf galaxies and globular clusters in the size-luminosity plane. The ensemble of its structural parameters is more consistent with a globular cluster classification, indicating that Sgr II is the most extended globular cluster in its luminosity range. The other three satellites land directly on the locus defined by Milky Way ultra-faint dwarf galaxies of similar luminosity. Ret II is the most elongated nearby dwarf galaxy currently known for its luminosity range. Our structural parameters for Phe II and Tuc III suggest that they are both dwarf galaxies. Tuc III is known to be associated with a stellar stream, which is clearly visible in our matched-filter stellar density map. The other satellites do not show any clear evidence of tidal stripping in the form of extensions or distortions. Finally, we also use archival HI data to place limits on the gas content of each object.Comment: Accepted for publication in ApJ. Minor updates to match accepted versio

Exploiting Inter- and Intra-Memory Asymmetries for Data Mapping in Hybrid Tiered-Memories

Modern computing systems are embracing hybrid memory comprising of DRAM and non-volatile memory (NVM) to combine the best properties of both memory technologies, achieving low latency, high reliability, and high density. A prominent characteristic of DRAM-NVM hybrid memory is that it has NVM access latency much higher than DRAM access latency. We call this inter-memory asymmetry. We observe that parasitic components on a long bitline are a major source of high latency in both DRAM and NVM, and a significant factor contributing to high-voltage operations in NVM, which impact their reliability. We propose an architectural change, where each long bitline in DRAM and NVM is split into two segments by an isolation transistor. One segment can be accessed with lower latency and operating voltage than the other. By introducing tiers, we enable non-uniform accesses within each memory type (which we call intra-memory asymmetry), leading to performance and reliability trade-offs in DRAM-NVM hybrid memory. We extend existing NVM-DRAM OS in three ways. First, we exploit both inter- and intra-memory asymmetries to allocate and migrate memory pages between the tiers in DRAM and NVM. Second, we improve the OS's page allocation decisions by predicting the access intensity of a newly-referenced memory page in a program and placing it to a matching tier during its initial allocation. This minimizes page migrations during program execution, lowering the performance overhead. Third, we propose a solution to migrate pages between the tiers of the same memory without transferring data over the memory channel, minimizing channel occupancy and improving performance. Our overall approach, which we call MNEME, to enable and exploit asymmetries in DRAM-NVM hybrid tiered memory improves both performance and reliability for both single-core and multi-programmed workloads.Comment: 15 pages, 29 figures, accepted at ACM SIGPLAN International Symposium on Memory Managemen

Metamaterial Polarization Converter Analysis: Limits of Performance

In this paper we analyze the theoretical limits of a metamaterial converter that allows for linear-to- elliptical polarization transformation with any desired ellipticity and ellipse orientation. We employ the transmission line approach providing a needed level of the design generalization. Our analysis reveals that the maximal conversion efficiency for transmission through a single metamaterial layer is 50%, while the realistic re ection configuration can give the conversion efficiency up to 90%. We show that a double layer transmission converter and a single layer with a ground plane can have 100% polarization conversion efficiency. We tested our conclusions numerically reaching the designated limits of efficiency using a simple metamaterial design. Our general analysis provides useful guidelines for the metamaterial polarization converter design for virtually any frequency range of the electromagnetic waves.Comment: 10 pages, 11 figures, 2 table

TESS asteroseismology of the known red-giant host stars HD 212771 and HD 203949

International audienc

A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study

Light Detection and Ranging (LiDAR) is a remote sensor able to extract vertical information from sensed objects. LiDAR-derived information is nowadays used to develop environmental models for describing fire behaviour or quantifying biomass stocks in forest areas. A multiple linear regression (MLR) with previous stepwise feature selection is the most common method in the literature to develop LiDAR-derived models. MLR defines the relation between the set of field measurements and the statistics extracted from a LiDAR flight. Machine learning has recently been paid an increasing attention to improve classic MLR results. Unfortunately, few studies have been proposed to compare the quality of the multiple machine learning approaches. This paper presents a comparison between the classic MLR-based methodology and common regression techniques in machine learning (neural networks, regression trees, support vector machines, nearest neighbour, and ensembles such as random forests). The selected techniques are applied to real LiDAR data from two areas in the province of Lugo (Galizia, Spain). The results show that support vector regression statistically outperforms the rest of techniques when feature selection is applied. However, its performance cannot be said statistically different from that of Random Forests when previous feature selection is skipped

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development