Effective prediction and resource allocation method (EPRAM) in fog computing environment for smart healthcare system

Multimedia Tools and Applications - Recently, many concepts in technology has been changed. According to the digital transformation trends, Internet of Things (IoT) represents an interested...     

西藏燕麦主要种植区灌溉定额空间分布及影响因素

燕麦为西藏自治区典型牧草之一,由于种植区地域辽阔,灌溉试验结果受限,西藏燕麦主要种植区的灌溉定额尚不明确。本文在西藏燕麦主要种植区内选取28个典型站点进行资料收集,遵循农业气候相似原则进行区域划分,基于水量平衡法揭示了西藏燕麦主要种植区灌溉定额的空间分布特征,并根据统计学原理分析了其影响因素。研究表明:燕麦主要种植区的灌溉定额呈由西藏中部至东部呈现先递增后递减的趋势,50%水文年下的燕麦灌溉定额在56~265 mm之间变化。降雨量是影响研究区内燕麦灌溉定额的主要因素(R²为0.515),ET₀次之(R²为0.152);其它气象因素中,日照时数对研究区燕麦灌溉定额影响较大(R²为0.462),且呈正相关关系;相对湿度对燕麦灌溉定额影响较小。西藏燕麦主要种植区的灌溉定额及其空间分布可为西藏自治区灌溉用水管理提供支撑。     

Diluted chemical bath deposition of CdZnS as prospective buffer layer in CIGS solar cell

In this study, dilute chemical bath deposition technique has been used to deposit CdZnS thin films on soda-lime glass substrates. The structural, morphological, optoelectronic properties of as-grown films have been investigated as a function of different Zn²⁺ precursor concentrations. The X-ray diffractogram of CdS thin-film reveals a peak corresponding to (002) plane with wurtzite structure, and the peak shift has been observed with the increase of the Zn²⁺ concentration upon formation of CdZnS thin film. From morphological studies, it has been revealed that the diluted chemical bath deposition technique provides homogeneous distribution of film on the substrate even at a lower concentration of Zn²⁺. Optical characterization has shown that the transparency of the film is influenced by Zn²⁺ concentration and when the Zn²⁺ concentration is varied from 0 M to 0.0256 M, bandgap values of resulting films range from 2.42 eV to 3.90 eV while. Furthermore, electrical properties have shown that with increasing zinc concentration the resistivity of the film increases. Finally, numerical simulation validates and suggests that CdZnS buffer layer with composition of 0.0032 M Zn²⁺ concentration would be a promising candidate in CIGS solar cell.     

基于形态特征提取的急性下壁心肌梗死BiLSTM网络辅助诊断算法

急性下壁心肌梗死是一种病发急、进展快、致死率高的心脏疾病,该文提出一种新颖的基于形态特征提取的BiLSTM神经网络分类的急性下壁心肌梗死辅助诊断算法,可大幅度提高医生对急性下壁心肌梗死疾病的诊断效率并有助于及时确诊.算法包括:对胸痛中心数据库心拍信号进行降噪及心拍分割;根据临床心内科医学诊断指南提取了12导联波形距离特征和分导联波形幅值特征;依据提取的特征搭建LSTM与BiLSTM神经网络进行心拍的分类识别;使用PTB公开数据库和胸痛中心数据库多临床中心进行交叉验证.实验结果表明,加入胸痛中心真实临床数据后,基于形态特征提取BiLSTM神经网络的急性下壁心肌梗死辅助诊断算法准确率达到99.72％,精度达到99.53％,灵敏度达到100.00％,同时F1-Score达到99.76.该算法比其他现有算法准确率提高至少1％,该项研究具有非常重要的临床应用价值.     

Modeling of Ignition and Combustion of a Coflowing Hydrogen Jet in a Supersonic Air Flow

Combustion, Explosion, and Shock Waves - Results of a numerical study of mixing, ignition, and combustion of a cold hydrogen jet propagating along the lower wall of a channel parallel to a...     

Low light enhancement algorithm for color images using intuitionistic fuzzy sets with histogram equalization

Multimedia Tools and Applications - In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light color images. A generalization of a fuzzy set known as an...     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

Low Temperature Characteristics of the Metal–Superconductor NIS Tunneling Thermometer

We discuss the temperature dependence of a common low temperature local thermometer, a tunnel junction between a superconductor and a normal metal (NIS junction). Towards the lowest temperatures its characteristics tend to saturate, which is usually attributed to selfheating effects. In this technical note, we reanalyze this saturation and show that the temperature independent subgap current of the junction alone explains in some cases the low temperature behavior quantitatively.

     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.