Miracle-dz/UniFAR-FTUs huggingface dataset:
A 195 mW, 9.1 MVertices/s Fully Programmable 3-D Graphics Processor for Low-Power Mobile Devices

A 195 mW, 9.1 Mvertices/s fully programmable 3-D graphics processor is designed and implemented for mobile devices. The mobile unified shader provides programmable per-vertex operations and per-pixel operations in a single hardware and thus, it achieves 35% area and 28% power reduction compared with previous architecture. The pixel-vertex multi-threading enhances the 3-D graphics performance by enabling to compute the per-vertex operations and the per-pixel operations at the same time. By adopting the pixel-vertex multi-threading, 94% of the per-vertex operations are interleaved into the per-pixel operations and enhances 3-D graphics performance in real applications. The logarithmic lighting engine and specialized lighting instruction improve the vertex throughput including transform and OpenGL lighting up to 9.1 Mvertices/s, which is 2.5 times higher performance compared with previous works. The proposed 3-D graphics processor is implemented in 3.3 mmtimes3.0 mm using 0.13 mum CMOS process and it was successfully demonstrated on the system evaluation board.
Dietary accumulation of PCBs from a contaminated sediment source by a demersal fish species (Leiostomus xanthurus)

Destroy this report when no longer needed. Do not return it to the originator. The findings in this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. The contents of this report are not to be used for advertising, publication, or promotronal purposes.
Persistence-based branch misprediction bounds for WCET analysis

Branch prediction is an important feature of pipelined processors to achieve high performance. However, it can lead to overly pessimistic worst-case execution time (WCET) bounds when being modeled too conservatively. This paper presents bounds on the number of branch mispredictions for local dynamic branch predictors. To handle interferences between branch instructions we use the notion of persistence, a concept that is also found in cache analyses. The bounds apply to branches in general, not only to branches that close a loop. Furthermore, the bounds can be easily integrated into integer linear programming formulations of the WCET problem. An evaluation on a number of benchmarks shows that with these bounds, dynamic branch prediction does not necessarily lead to higher WCET bounds than static prediction schemes.
Investigating plant root effects on soil electrical conductivity: An integrated field monitoring and statistical modelling approach

Plants have been shown to affect soil water content and temperature. Previous studies were conducted mainly in forestry and agricultural soils, where conditions of soil and vegetation are different from those in an urban landscape. In an urban landscape, the influence of plant roots on electrical conductivity, soil water content and temperature is still not clear. This study aims to investigate the effects of soil water content and temperature on electrical conductivity in vegetated soils through an integrated field monitoring and computational modelling approach. A new relationship between soil electrical conductivity and water content as well as temperature is proposed. Field monitoring was conducted in both vegetated (tree species) and bare soils. The monitoring included measurements of soil water content, soil temperature and soil electrical conductivity. This was followed by response surface regression modelling. Measured results show that soil temperature at shallow depths was lower in vegetated soil than that in the bare soil. This observation was also consistent with the higher soil water content and hence, higher electrical conductivity under tree canopy. The model developed could predict nonlinear relationships between electrical conductivity and soil temperature and water content. Uncertainty analysis indicated normal distribution for electrical conductivity under variation of soil temperature and water content. © 2018 John Wiley & Sons, Ltd.
UAS as tools for rapid detection of storm-induced morphodynamic changes at Camposoto beach, SW Spain

ABSTRACT The increasing pressures and hazards derived from human action and climate change make the implementation of coastal monitoring plans a requirement for assessing coastal responses and evolution. For this reason, this work aims to use unmanned aerial systems (UAS) in combination with Structure from Motion algorithms for detecting morphodynamic changes caused by a storm in Camposoto beach (SW Spain). This approach provided pre- and post-storm digital elevation models of the study area with root mean square vertical errors of 6.89 and 5.54 cm, respectively, that allowed the identification of storm-induced gain and loss of sediment using Geomorphic Change Detection software. Furthermore, it also captured the response of the system against the action of specific marine processes such as storm-induced swash, collision, and overwash. The results obtained highlight the importance of an optimum flight plan design (e.g. the use of 85–75% front and side image overlap, respectively) and enhance the suitability of the UAS technology to satisfy the demands and needs in coastal monitoring studies in comparison with the traditional techniques, namely aerial photogrammetry, satellite imagery, and/or light detection and ranging.
Ice decay at the base of a supra-ice melt pond.

ICE DECAY AT THE BASE OF A SUPRA-ICE MELT POND During the melt season, water accumulates in depressions on sea, lake and river ice, and on glaciers to form ponds. In 1990, a météorologie and hydrologie study was conducted on two typical supra-ice melt ponds near Resolute, N.W. T. , Canada. Field measurements showed that most of the water was isothermal in the convective layer, with temperatures less than 2.6 °C. At the ice-water interface, there was a large temperature gradient and the water was effectively still. The energy balance was dominated by the fluxes of net radiation and sensible heat and consumed almost entirely by melt. The effective thermal diffusivity was found to vary with wind speed and water depth. The heat flux from the water to the ice surface was similar to the results of Lunardini et al. (1986) and could be used to predict melt. The results of this study can be applied to any fresh-water melt pond on ice to predict melt, but because of salinity effects, sea ice ponds may behave somewhat differently.
Fast precise GPS positioning in the presence of ionospheric delays

In many geodetic (surveying) applications positions of points in the terrain need to be determined with high precision (cm-accuracy or even better). The Global Positioning System (GPS) is very suitable for this purpose. High positioning accuracy is in principle feasible when a relative measurement setup is used and in the processing procedure certain systematic errors in the GPS observations are properly taken into account. The largest of these errors is due to the propagation of the GPS signals through the ionosphere, the part of the atmosphere from about 80 km altitude. When the distance between the GPS receivers in the relative measurement setup is sufficiently short (e.g. a few km) it is known that these errors almost cancel, such that the positioning can be conducted using only a short time span of measurements, which is very favorable from an economical point of view. For longer distances the necessary time span increases enormously since unknown parameters for among others the ionospheric errors need to be estimated in the processing. In this thesis a procedure is outlined for the processing of relative GPS observations over medium distances (max. 50 km), while at the same time it should allow a user a short time span of measurements. An important requirement to this procedure is the availability of a permanent network of GPS reference stations. From the observations this permanent network collects, it is possible to generate information about the ionospheric delays, which a user can consequently apply to correct his own GPS observations. Much attention in the thesis is paid to the mathematical modelling aspects of this procedure.
Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses

ABSTRACT Scatterometer surface wind speed and direction observations in combination with radiometer wind speeds allow to generate surface wind analyses with high space and time resolutions over global as well as at regional scales. Regarding scatterometer sampling schemes and physics, the resulting surface wind analyses suffer from lack of accuracy in areas near coasts. The use of the synthetic aperture radar (SAR) onboard the Sentinel-1A satellite attempts to address the enhancement of surface wind analyses issues. In this study, SAR wind speeds and directions retrieved from backscatter coefficients acquired in interferometric wide (IW) swath mode are used. Their accuracy is determined through comprehensive comparisons with moored buoy wind measurements. SAR and buoy winds agree well at offshore and nearshore locations. The statistics characterizing the comparison of SAR and buoy wind speeds and directions are of the same order as those obtained from scatterometer (Advanced SCATterometer (ASCAT) and RapidScat) and buoy wind comparisons. The main discrepancy between SAR and buoy data are found for high wind speeds. SAR wind speeds exceeding 10 m s–1 tend to be underestimated. A similar conclusion is drawn from SAR and scatterometer wind speed comparisons. It is based on the underestimation of SAR backscatter coefficient (σ°) with respect to σ° estimated from scatterometer winds and the geophysical model function (GMF) named CMOD-IFR2 (Ifremer C band MODel). New SAR wind speeds are retrieved using CMOD-IFR2. The corrected SAR retrievals allow better determination of the spatial characteristics of surface wind speeds and of the related wind components in near-coast areas. They are used for enhancing the determination of the spatial structure function required for the estimation of wind fields gridded in space and time at the regional scale. The resulting wind fields are only determined from scatterometer wind observations in combination with radiometer retrievals. Their qualities are determined through comparisons with SAR wind speeds and directions, and through their application for determination of wind power off Brittany coasts.
An embedded camera lens distortion correction method for mobile computing applications

This paper describes a lens geometric and photometric distortion correction method to obtain a high quality image with low cost digital cameras. Lens geometric distortion coefficient of a digital camera is estimated using a simplified camera calibration technique, which is extended to calibration-free estimation method. Based on the estimate of the lens geometric distortion coefficient, image warping adapted for DSP architecture is applied. Photometric distortion, on the other hand, is corrected by a nonlinear model fitting of a proposed photometric distortion model function. Light intensity profile distribution is obtained without precisely controlled illumination and memory requirement is considerably reduced compared with traditional lookup table (LUT) methods.
Input : Stereo Images IMU Measurements Triangulate New 3 D Information Gravity Alignment Direct Pose Estimation Propagate 3 D Map To Current View Feature Detection ( Lines / Points ) Keyframe Output : Camera Pose

We propose a novel stereo visual odometry approach, which is especially suited for poorly textured environments. We introduce a novel, fast line segment detector and matcher, which detects vertical lines supported by an IMU. The patches around lines are then used to directly estimate the pose of consecutive cameras by minimizing the photometric error. Our algorithm outperforms state-of-the-art approaches in challenging environments. Our implementation runs in real-time and is therefore well suited for various robotics and augmented reality applications.
Mesozoic resource potential in the Southern Permian Basin area: the geological key to exploiting remaining hydrocarbons whilst unlocking geothermal potential

It is generally accepted that hydrocarbon exploration in northern Europe has reached a mature stage. A basin’s maturity is defined by the underlying number of new discoveries and the declining production rate of mature fields (SPE 2015). For geoscientists, a mature basin has well-defined characteristics in terms of, for example, reservoir presence or trap formation (e.g. Byrne 2012). It is interesting, therefore, to note how much is still unknown about certain stratigraphic intervals in northern Europe. The Mesozoic overburden of the Southern Permian Basin (sensu Maystrenko et al. 2008; Doornenbal & Stevenson 2010) continues to provide fresh insights into the geological history of an area where, as the name suggests, historical hydrocarbon exploration has focused on the Paleozoic. The aim of this Special Publication is to increase knowledge of the Mesozoic overburden as a driver for further hydrocarbon exploration/production and the development of new geothermal energy sources. The succeeding chapters are introduced by tectonic framework overviews that give a context for the papers that follow. The remaining articles are organized in approximate stratigraphic order, from old to young, and include a variety of examples from semi-regional to localized field or sub-basin studies. An overview of the study area for all the following chapters is given in Figure 1. It is recognized that the overprinting Mesozoic systems have different naming conventions across the study area (e.g. the Central European Basin System sensu Littke et al. 2008; Maystrenko et al. 2008). Here we use the title ‘Southern Permian Basin area’ to emphasize the resource opportunities associated with a region that has, at least in large part, been associated with hydrocarbon exploration, and very large gas fields, in the Permian Rotliegend. For our purposes, this includes part of the Polish Trough, the highs surrounding the basin (e.g. the Ringkobing-Fyn High), and analogous elements of the Danish and Norwegian offshore. In this introduction, an overview of the geological history and resource base of the area is presented as a framework for the chapters that follow. A description of further prospective resources is then offered (oil and gas plus geothermal potential).
Nutrient Leaching in Soil Affected by Fertilizer Application and Frozen Ground

Preferential flow is prevalent in clay soil under both frozen and thawed conditions. Preferential flow dominates the infiltration regime under frozen soil conditions in silt loam. Subsurface placement of fertilizer can limit subsurface nutrient leaching. Subsurface placement is particularly effective in soil with abundant preferential flow. Subsurface placement is recommended for fall fertilizer application.
FACTORS INFLUENCING CONSUMER’S BEHAVIOR TOWARDS THE USAGE OF INTERNET BANKING

The purpose of the present study is to understand the factors influencing adoption of internet banking in Malaysia. A model has been proposed based on the technology acceptance model (TAM). The proposed model is referred to as extended TAM and is better suited to identify and quantify the important factors that influence adoption of internet banking (IB) technology in the country. Data were collected from 487 individuals who are either current or prospective internet banking users. Partial Least Squared (PLS) was used to identify the important factors affecting technological adoption. It is found that perceived usefulness (PU) and familiarity have a significant relationship towards the behavior of users to use IB. Perceived ease of usefulness (PEU), awareness and opportuneness on the other hand, have been identified as not having significant relationship towards the behavior of consumers to use IB in the tested mediated model. This study enables IB service providers in Malaysia to design new service offerings or modify current service offerings to achieve higher adoption rates in IB.
Bayesian estimation of NOEM models: identification and inference in small samples

This paper studies the (potential) weak identification of these relationships in the context of a fully specified structural model using Bayesian estimation techniques. We trace the problems to sample size, rather than misspecification bias. We conclude that standard macroeconomic time series with a coverage of less than forty years are subject to potentially serious identification issues, and also to model selection errors. We recommend estimation with simulated data prior to bringing the model to the actual data as a way of detecting parameters that are susceptible to weak identification in short samples.
LSU Digital

The Additive Increase Multiplicative Decrease (AIMD) algorithm of the Transport Control Protocol (TCP) had worked remarkably well over low speed networks and had guaranteed fairness to the users all over these years, but at present, the demands for transferring large quantities of data over very high-speed networks are increasing at a tremendous rate. Because of its AIMD algorithm to control its window growth function accompanied by a slow response function which is inadequate over high-speed links, TCP has been proven to underutilize the available network bandwidth and leave a considerable amount of unused bandwidth. To overcome this limitation of TCP, the network research community came up with a number of TCP variants: HSTCP, STCP, BIC TCP, CUBIC, HTCP, and FAST TCP. All these protocols differ in the window growth policy to utilize the available bandwidth over a high-speed link. Various tests have shown that these protocols successfully utilize the link but at the same time they are not able to guarantee fairness to the other flows in the network. In this work, we aim to explore the following research questions:
An Empirical Tropical Instability Wave-induced Wind Stress Model in the Equatorial Pacific and its Incorporation into the Ocean Model

Abstract Satellite observations revealed that there is a close relationship between perturbations of sea surface temperature (SST) and wind stress (τ) induced by tropical instability waves (TIWs; SSTTIW and τ TIW). Using the empirical relationship observed between TIW-induced wind stress divergence (curl) and downwind (crosswind) SST gradients, this study establishes a TIW-induced wind stress field perturbation model τ TIW = F(SST). This empirical model solves τ TIW from the TIW-induced wind stress divergence and curl, which are estimated from the downwind and crosswind SST gradients. This empirical τ TIW = F(SST) model can be incorporated into the ocean model to take into account the effect of τ TIW. By comparing two experiments with and without the τ TIW effect, this study demonstrates that τ TIW has a substantial effect on the equatorial Pacific heat budget and induces the long-term mean SST to exhibit a 0.2°C difference, which is consistent with previous studies.
A simple assessment approach for winter wheat loss risk impacted by water stress

Abstract In this study, an empirical assessment approach for the risk of crop loss due to water stress was developed and used to evaluate the risk of winter wheat loss in China, the United States, Germany, France and the United Kingdom. We combined statistical and remote sensing data on crop yields with climate data and cropland distribution to model the effect of water stress from 1982 to 2011. The average value of winter wheat loss due to water stress for the three European countries was about −931 kg/ha, which was higher than that in China (−570 kg/ha) and the United States (−367 kg/ha). Our study has important implications for the operational assessment of crop loss risk at a country or regional scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapotranspiration to estimate water stress, improving the method for downscaling of statistical crop yield data and establishing more sophisticated zoning methods.
Improving peanut (Arachis hypogaea L.) production strategies through use of cover crops and organic management

Cover crops are commonly used in peanut production and could potentially provide some nutrient benefits to peanut as cover crop residues decompose. Therefore, the objective of this experiment was to evaluate the rate of decomposition and nutrient cycling potential of crimson clover, rye, and wheat cover crops grown in either conventional or strip-tillage and their impacts on a subsequent peanut crop. Field trials were conducted in Tifton, GA from 20082010. Crimson clover, rye, wheat, and no cover treatments were established in the fall preceding each year of the trial in conventional and strip-tillage. Soil and plant tissue samples from cover crop residues and peanut plants were collected at various points throughout the growing season and analyzed for nutrient concentration and biomass. Wheat residues displayed the sharpest decline in conventional-tillage both years, though not different from rye in 2010. Conventionaltillage resulted in sharper cover crop biomass decline than strip-tillage in 2009. Despite the sharper decline of wheat residues in 2009, crimson clover in conventional-tillage released the greatest amounts of N, P, K, Ca, Mg, B, and Zn that year. Soil nutrient levels varied little among cover crops and tillage at all sample dates, but levels did tend to increase within the first 60-90 days after cover crop burndown, as residues began to decompose. Cover crops did little to improve nutrient content in peanut vegetation and actually reduced uptake of K, Mn, and Zn compared to no cover in conventional-tillage in 2009 (P ≤ 0.05). However, strip-tillage increased total N, K, Mg, S, Mn, and Zn content in peanut pods under drought-like conditions in 2010 (P ≤ 0.05). There were almost no differences among treatments in vegetative peanut production, yield, or grade. These results indicate that cover crops have some impact on nutrient uptake of peanut, but have little impact on overall productivity. Tillage has some impact on nutrient uptake in pods, but was not consistent in both years of this experiment.
Regular Articles : A Monte Carlo Comparison of Robust MANOVA Test Statistics

Multivariate Analysis of Variance (MANOVA) is a popular statistical tool in the social sciences, allowing for the comparison of mean vectors across groups. MANOVA rests on three primary assumptions regarding the population: (a) multivariate normality, (b) equality of group population covariance matrices and (c) independence of errors. When these assumptions are violated, MANOVA does not perform well with respect to Type I error and power. There are several alternative test statistics that can be considered including robust statistics and the use of the structural equation modeling (SEM) framework. This simulation study focused on comparing the performance of the P test statistics with fifteen other test statistics across seven manipulated factors. These statistics were evaluated across 12,076 different conditions in terms of Type I error and power. Results suggest that when assumptions were met, the standard MANOVA test functioned well. However, when assumptions were violated, it performed poorly, whereas several of the alternatives performed better. Discussion focuses on advice for selecting alternatives in practice. This study's focus on all these in one simulation and the 3 group case should be helpful to the practitioner making methodological sections.