Cloud-induced effects on monthly averaged scintillation amplitude along millimeter-wave slant paths

A physical-statistical analysis of cloud-induced effects on millimeter-wave amplitude scintillation along Earth-satellite slant paths is presented. Using numerical simulations derived from a cloud radiative model, a dual-channel nonlinear retrieval algorithm is set up to estimate simultaneously cloud columnar water vapor and liquid water contents from measured ground-based brightness temperatures. The latter are related in cloudy conditions to surface meteorological variables and columnar water vapor and liquid water contents. ITALSAT ground-station data consisting of time series of beacon scintillation at 18.7, 39.6, and 49.5 GHz, surface meteorological data and radiometric observations at 13.0, 23.8, and 31.6 GHz, are used for an experimental analysis of cloud-induced scintillation by selecting a period of six years from 1994 to 1999. The results show a significant correlation between amplitude scintillation variances and cloud columnar contents on a monthly basis (i.e., averaged on-time intervals of one month). Considerations about possible impact of this analysis on the development of scintillation prediction models are finally illustrated.     

Ice depolarization at 11.7 and 19 GHZ on slant paths in Virginia,USA

Measurements of attenuation and cross-polarization on slant paths from the Cts and Comstar D2 satellites to Blacksburg, VA, have been in progress for three years. The data for 1977 and 1978 have been analyzed to determine the extent of severe ice depolarization on these paths, and a number of events have been identified. The behaviour of the observed cross-polarization at 11.7 and 19 GHz in two events has been compared with current theory for ice depolarization.     

A new prediction method for tropospheric scintillation onEarth-space paths

A method of predicting scintillation fading occurring on Earth-space paths is proposed that is based on the data obtained from a low-elevation 14/11 GHz wave propagation experiment at Yamaguchi, Japan. This model includes parameters representing meteorological conditions that have not been covered in existing models and can be applied to broad regions with varying climates. The prediction accuracy of the method is evaluated using experimental data collected at four sites in the western part of Japan, as well as data reported thus far on a worldwide basis. Although data used for evaluation are limited, the model shows good prediction accuracy for frequencies from 7 to 14 GHz and elevation angles from 4° to 30°     

Prediction model for the diurnal behavior of the troposphericscintillation variance

Tropospheric scintillation is caused by variations of the refractive index due to turbulence. The only meteorological input parameter for two common current scintillation models by Karasawa et al. (1988) and by the ITU-R is the monthly average of the wet part of the refractivity N_wet at ground level, which is not directly associated with turbulence. The diurnal correlation between N_wet and scintillation variance is very weak. Because clouds and cloud formation are closely associated with the turbulence, quantitative cloud parameters were looked for. Cloud type information based on edited synoptic cloud reports are available from the common database of CDIAC and NCAR. Both diurnal and seasonal variations between scintillation variance and average amount of Cumulus type clouds are well correlated. Using this cloud information together with N_wet, a new method for tropospheric scintillation variance predicting also the diurnal variations is introduced. This model is derived and tested using scintillation measurements at four sites in different climates in Finland, United Kingdom, Japan, and Texas     

Improved SAP based on adaptive directional prediction for HEVC lossless intra prediction

In HEVC (High Efficiency Video Coding), linear interpolation of the boundary pixels is used as the predictor and pixels within the same PU (Prediction Unit) are in the same prediction direction. When the PU block is large and in high complexity, the prediction performance would worsen. Although many algorithms use the pixel-based weighted averaging or interpolation operations to perform the prediction which improves the performance of bitrate saving notably, there is still space for further improvement. This paper proposed an improved SAP (Sample-based Angular Prediction) algorithm based on adaptive directional prediction (ADSAP). The innovation of this paper lies in two aspects: it puts forward a new method to estimate the best prediction direction of current pixel and it introduces the concept of “frame-level pretreatment” which could greatly improve the encoding speed. Experimental results show that it could save the output bitrate by about 9.4158% when compared with the HEVC lossless intra prediction algorithm, which is better than other typical algorithms. Besides, the encoding and decoding time are reduced by about 11%. Moreover, when the minimum PU size gets larger, the increase of output bitrate of ADSAP is much less than that of HEVC and the conventional SAP algorithm, which makes the proposed algorithm quite suitable for the compression of high resolution videos.     

A systematic comparison of rain attenuation prediction methods for terrestrial paths

The available rain attenuation prediction methods have been tested and compared, and the sensitivity to various input parameters regarding both the rain structure and the rainfall intensity measuring and processing techniques has been examined, on the basis of rain data collected in the northern and central parts of Italy. Starting from the same data, some considerations about the relationship between worst month/yearly cumulative rain attenuation distributions, and the diurnal influence on them are also given.     

Differential propagation constants on slant paths through snow and ice crystals as measured by 16.5 GHz polarization-diversity radar

Radar determinations of differential propagation constants at a wavelength of 1.82 cm on slant paths through heavy snow and ice crystals are reported. Also reported are measurements of differential propagation effects in the melting layer. The slant path results indicate an increase of differential phase shift with height, to a value at 2000 m which may exceed 1.3 deg/ km, being typically several times that at the surface. This effect is attributed to a change in the hydrometeors, as they precipitate, from ice crystals to snow aggregates. Differential propagation effects in the melting layer are small.     

Analytical models for cross-polarization on earth-space radio paths for frequency range 9–30 GHz

Depolarization and attenuation of radiowaves along earth-space paths due to rain storms are characterised. Frequency-dependent expressions for specific attenuation and phase shift at (PC and 20°C and for Laws-Parsons raindrop size distribution are given. Using small amplitude and phase approximations, a simple relation for cross-polar discrimination due to rain in terms of co-polar attenuation, frequency, angle of elevation and polarization angle is derived. Expressions for depolarization due to ice crystals are given, treating them as Rayleigh scatterers of spheroidal shape. For both rain and ice the relationship between linear and circular crosspolar ratio can be shown to be simply sin 2 θ, where θ is the polarization angle.     

Nonlinear prediction for Gaussian mixture image models

Prediction is an essential operation in many image processing applications, such as object detection and image and video compression. When the images are modeled as Gaussian, the optimal predictor is linear and easy to obtain. However, image texture and clutter are often non-Gaussian, and, in such cases, optimal predictors are difficult to obtain. In this paper, we derive an optimal predictor for an important class of non-Gaussian image models, the block-based multivariate Gaussian mixture model. This predictor has a special nonlinear structure: it is a linear combination of the neighboring pixels, but the combination coefficients are also functions of the neighboring pixels, not constants. The efficacy of this predictor is demonstrated in object detection experiments where the prediction error image is used to identify "hidden" objects. Experimental results indicate that when the background texture is nonlinear, i.e., with fast-switching gray-level patches, it performs significantly better than the optimal linear predictor.     

基于路径分解的关键路径求解方法

提出了一种求解关键路径的新方法,该方法基于路径分解的思想,对AOE网所有的路径进行分解,并利用多头单尾链表结构实现关键路径的求解。通过实例验证了算法的正确性。     

Propagation prediction models for wireless communication systems

A comprehensive review of the propagation prediction models for terrestrial wireless communication systems is presented in this paper. The classic empirical models are briefly described and the focus is placed on the application of ray-tracing techniques to the development of deterministic propagation models. Schemes to increase the computational efficiency and accuracy are discussed. Traditional statistical models are also briefly reviewed for completeness. New challenges to the propagation prediction are described and some new approaches for meeting these challenges are presented     

Comparison of multiple-diffraction models for digital broadcastingcoverage prediction

This paper investigates and compares the efficiency and accuracy of existing multiple diffraction prediction techniques in real outdoor environments. Extensive comparisons are presented, including more than 20 000 path profiles. It is believed that this study will enable broadcasters to design and maintain broadcast networks with an accuracy commensurate with the highly demanding requirements for new and more efficient digital services. The comparisons involve the most well-known deterministic approaches (Deygout (1966), Causebrook (1971), Giovaneli (1984), Vogler (1982)) whose key feature is either the high accuracy of their predictions or their low computation times. However, a new slope-UTD based deterministic approach, developed recently by the authors, is found to provide the best compromise between computation speed and prediction accuracy     

Remarks on models for prediction of radiated fields in electricaldischarge events

Ambiguities have appeared in the literature on the role of the arc in the electromagnetic radiation associated with electrostatic discharges. The authors discuss the contribution of the arc channel to the total emission and present experimental evidence that this contribution is negligible compared to that of the rest of the circuit     

ECG compression using long-term prediction

A new algorithm for ECG signal compression is introduced. The compression system is based on the subautoregression (SAR) model, known also as the long-term prediction (LTP) model. The periodicity of the ECG signal is employed in order to further reduce redundancy, thus yielding high compression ratios. The suggested algorithm was evaluated using an in-house database. Very low bit rates on the order of 70 b/s are achieved with a relatively low reconstruction error (percent RMS difference-PRD) of less than 10%. The algorithm was compared, using the same database, with the conventional linear prediction (short-term prediction-STP) method, and was found superior at any bit rate. The suggested algorithm can be considered a generalization of the recently published average beat subtraction method     

A new framework for part failure-rate prediction models

This paper presents a framework for developing part failure-rate models. It is a partial result of an effort sponsored by the US Air Force for the development of reliability prediction models for military avionics. Published data show that the existing reliability prediction methods fall far short of providing the required accuracy. One of the problems in the existing methods is the exclusion of critical factors. The new framework is based on the premise that essentially all failures are caused by the interactions of built-in flaws, failure mechanisms, and stresses. These three ingredients contribute to form the failure distribution which are functions of stress application duration (eg, aging time), number of thermal cycles, and vibration duration. The Weibull distribution has been selected as the general distribution. The distribution is then modified by the critical factors such as flaw quantities, effects of environmental stress screening, calendar-time reliability improvements, and vendor quality differences, to provide the part failure-rate functions. To provide credibility for the framework, only well published data and information have been used     

激光雷达观测斜程能见度反演方法

目前基于激光雷达测量能见度的反演算法可以较为准确地反演均匀大气条件下的水平能见度,对云雨雾等非均匀大气条件下斜程能见度的准确反演较为困难。为了准确探测复杂大气条件下的斜程能见度,分析了激光雷达探测大气能见度的反演算法,重点针对非均匀大气条件下能见度难以准确反演的问题,提出了一种将Collis斜率法与Klett后向法相结合的能见度反演迭代算法,适用于不同天气条件下不同倾角路径平均能见度的反演。利用车载式激光雷达系统对能见度进行了实际测量,实验表明:在均匀大气条件下,该迭代算法与广泛使用的Collis斜率法和Klett后向法完全吻合;对于非均匀大气条件,该迭代算法也可克服Collis斜率法和Klett后向法的局限,更为快速稳定准确地反演出需要的大气能见度信息。     

Improved prediction methods for scalable predictive animated mesh compression

Animated meshes represented as sequences of static meshes sharing the same connectivity require efficient compression. Among the compression techniques, layered predictive coding methods efficiently encode the animated meshes in a structured way such that the successive reconstruction with an adaptable quality can be performed. The decoding quality heavily depends on how well the prediction is performed in the encoder. Due to this fact, in this paper, three novel prediction structures are proposed and integrated into a state of the art layered predictive coder. The proposed structures are based on weighted spatial prediction with its weighted refinement and angular relations of triangles between current and previous frames. The experimental results show that compared to the state of the art scalable predictive coder, up to 30% bitrate reductions can be achieved with the combination of proposed prediction schemes depending on the content and quantization level.     

Improved physical models for advanced silicon device processing

We review atomistic modeling approaches for issues related to ion implantation and annealing in advanced device processing. We describe how models have been upgraded to capture physical mechanisms in more detail as a response to the accuracy demanded in modern process and device modeling. Implantation and damage models based on the binary collision approximation have been improved to describe the direct formation of amorphous pockets for heavy or molecular ions. The use of amorphizing implants followed by solid phase epitaxial regrowth has motivated the development of detailed models that account for amorphization and recrystallization, considering the influence of crystal orientation and stress conditions. We apply simulations to describe the role of implant parameters to minimize residual damage, and we address doping issues that arise in non-planar structures such as FinFETs.     

Improved three-dimensional ray tracing technique for microcellularpropagation models

An improved three-dimensional ray tracing technique based in multiple-image and ray launching concepts is presented. The technique yields large improvements in terms of accuracy, computing efficiency and memory requirements compared with the conventional `brute force' ray tracing method