地震平衡技术及其在地震反演中的应用

地震平衡技术是一种在地震反演中改善井震关系的新技术。它通过单井对比、空间分形建模以及平衡处理的手段 ,克服地震反演中子波空变的影响 ,使得经过地震平衡技术处理的地震剖面井震关系得到较好改善 ,从而可以用统一的子波对研究区的地震资料进行反演     

全球宽带电话市场分析

近两年．IP电话又叫网络电话的发展受到全球的关注。随着宽带接入的发展，基于宽带接入提供的网络电话具有了更大的生命力。从宽带电话的经营模式出发，探究这类业务的出现时现有话音业务市场的影响，进而分析这类业务的发展前景。     

从稳态到动态的空气调节

分析传统空调所提供的稳态参数微气候环境不一定能达到人的舒适和健康的要求,提出符合人本身生理习惯的空调送风方式应该是动态空气调节.认为个人可调节和适宜的环境渐变能同时保证舒适和健康两方面需要.     

不同注F剂量与CMOS运放电路辐照损伤的相关性

在不同注F剂量条件下,对P沟和N沟两种不同差分对输入CMOS运放电路的电离辐照响应进行了研究.分析比较了注F和未注F运放电路电离辐照响应之间的差异.结果表明,在栅场介质注入适量的F,可有效抑制辐照感生的氧化物电荷尤其是界面态的增长,从而提高CMOS运放电路的抗辐照特性.     

Gamma-irradiation-induced Ag/SiO2 composite films and their optical absorption properties

Small Ag particles or clusters dispersed mesoporous SiO₂ composite films were prepared by a new method: First the matrix SiO₂ films were prepared by sol-gel process combined with the dip-coating technique, then they were soaked in AgNO₃ solutions followed by irradiation of γ-ray at room temperature and in ambient pressure. The structures of these films were examined by X-ray diffraction (XRD), high-resolution transmission electron microscope (HRTEM), and optical absorption spectroscopy. It has been shown that the Ag particles grown within the porous SiO₂ films are very small, and they are isolated and dispersed from each other with very narrow size distributions. With increasing the soaking concentration and an additional annealing, an opposite peakshift effect of the surface plasmon resonance (SPR) was observed in the optical absorption measurements.     

低温脂肪酶产生菌的筛选、鉴定及其部分酶学性质

从南极乔治王岛冻土来源的76株低温细菌中筛选到13株低温脂肪酶产生菌，对其中的BTsl0022菌株进行鉴定。通过生理生化特征、16s rDNA基因序列的同源性和系统发育分析发现，菌株RTsl0022属于假单胞菌属(Pseudomonas)，但与已定名的假单胞菌有一定的差异，与未定名的Pseudomonas sp．PsB的亲缘关系最接近，故将其暂定名为Pseudomonas sp．BTsl0022。对该菌脂肪酶的酶学性质初步研究表明，酶的最适作用温度为24℃，对热敏感，60℃处理30min仅残留25％酶活性，酶的适宜作用pH范围在7．0～9．0，最适pH为8．0。     

An evaluation of biological and abiotic controls for grapevine powdery mildew. 2. Vineyard trials

Grapevine powdery mildew ( Erysiphe necator) affects grape yield and fruit quality worldwide. Managers of conventional vineyards rely mainly on synthetic fungicides and sulfur to control powdery mildew, while in organic vineyards sulfur is the main control agent, often in rotation with canola-based oils, bicarbonates and biological control agents. The efficacy of those materials has not been evaluated critically under field conditions in Australia. Accordingly, a range of materials showing most promise in previous greenhouse trials (Crisp et al. 2006 Australian Journal of Grape and Wine Research 12 , pp. 192–202) were assessed via field trials in commercial vineyards. Applications of either milk or whey (alone, or mixed with a canola oil-based product), as well as applications of potassium bicarbonate (commercial formulation), all reduced the severity of powdery mildew compared with untreated vines. Eight applications of a 1:10 dilution of milk, 45 g/L whey powder or programs comprising rotations of potassium bicarbonate plus oil and whey, applied at 10–14 day intervals, reduced the severity of powdery mildew to levels not significantly different from that on vines sprayed with sulfur (wettable powder, 3–6 g/L). However, the relative control of powdery mildew by the test materials in field trials was dependent on the susceptibility of the grapevine cultivar and the extent of spray coverage achieved. In vineyards where highly susceptible cultivars were planted, and spray coverage was compromised, the resultant control of powdery mildew was reduced; and sometimes to commercially unacceptable levels.     

Combined RLS-LMS initialization for per tone equalizers in DMT-receivers

In discrete multitone receivers, the classical equalizer structure consists of a (real) time domain equalizer (TEQ) combined with complex one-tap frequency domain equalizers. An alternative receiver is based on a per tone equalization (PTEQ), which optimizes the signal-to-noise ratio (SNR) on each tone separately and, hence, the total bitrate. In this paper, a new initialization scheme for the PTEQ is introduced, based on a combination of least mean squares (LMS) and recursive least squares (RLS) adaptive filtering. It is shown that the proposed method has only slightly slower convergence than full square-root RLS (SR-RLS) while complexity as well as memory cost are reduced considerably. Hence, in terms of complexity and convergence speed, the proposed algorithm is in between LMS and RLS.     

Volumetric Change and Surface Properties of Temperature-Sensitive Polyvinylalcohol (PVA) Hydrogel

Polyvinylalcohol (PVA) polymer gel is a temperature sensitive polymeric gel, with a critical transition temperature (with H₂O) of 310 K. At higher than 310 K, this temperature sensitive polymer gel shrinks because of discharging water, whereas at lower temperatures, the gel swelled because of absorbing water. The reversibility of the gel's volume change was confirmed by temperature swing. The adsorption behavior of an organic compound onto the PVA polymer gel in water was tested at various temperatures. The amount of adsorbed organic compound increased remarkably at temperatures higher than about 310 K. Then, it was confirmed that the organic compound in PVA polymer gel could be reversibly adsorbed and desorbed by a temperature change between 293 and 323 K. The mechanism of adsorption of the organic compound onto the PVA polymer gel could be explained by hydration and dehydration of polymer gel.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.