R2D2: A scalable deep learning toolkit for medical imaging segmentation

Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures.     

一种基于深度森林的恶意代码分类方法

针对当前恶意代码静态分析方法精度不足的问题，将恶意代码映射为无压缩的灰度图像，然后根据图像变换方法将图像变换为恒定大小的图像，使用方向梯度直方图提取图像的特征，最后提出一种基于深度森林的恶意代码分类方法.实验中选择不同家族的多个恶意代码样本进行分类，验证了该方法的有效性，并且实验结果优于近期提出的SPAM-GIST方法.     

Performance of near-infrared dyes as effective contrast agents for breast cancer detection through simulation of photoacoustic imaging

ABSTRACT

Targeted photoacoustic imaging using exogenous contrast agents can potentially improve early detection of breast cancer, even at significant depths inside the breast. In this study, computer simulations were performed to compare the photoacoustic performance of 11 different near-infrared (NIR) dyes for detecting tumours deep inside the breast tissue. It was observed that the three high performing NIR dyes produced at least two-fold contrast enhancement of a spherical breast tumour embedded at 4?cm depth inside the breast than those of the corresponding endogenous contrast agents. These three selected dyes were employed to visualize small blood vessels deep inside the breast tissue. Although methylene blue provided the best contrast in visualizing tumour blood vessels at depths beyond 3?cm, considering other factors such as availability of suitable targeting agent, indocyanine green at 800?nm may be preferred over all other dyes for deep breast imaging applications.     

既有居住建筑附属地下换热站降噪研究

为了降低既有建筑附属用房产生的噪声对居民生活的影响、改善居住建筑声环境,对既有居住建筑附属用房地下换热站的噪声源以及噪声传播途径进行了分析;以既有居住建筑地下换热站室内噪声实测数据为基础,对室内环境的声学特征进行分析。在综合考虑居民的健康和舒适的基础上,提出了针对该附属用房的降噪处理改造设计方案。经过改造后的空间噪声明显降低,空间声环境指标达到标准要求,有效地改善了居住建筑的声环境。文中提出的改造设计方案为制定民用建筑附属用房声学设计标准提供了技术支撑。     

滚动轴承振动加速度信号积分测试技术研究

滚动轴承出厂时需要根据国家标准进行振动检测。对滚动轴承的振动进行测量的方法主要是采用速度型测振和加速度型测振。由于速度型测振仪和加速度型测振仪所采用的传感器不同,两者的测量结果有相关性,但测量结果并不一致。传统的轴承测振仪采用模拟电路,对加速度信号进行准确积分,难度较大;随着计算机测量技术的迅速发展,运用数字量测试和积分技术,可以采用对加速度信号进行积分得到速度的方法进行测试。通过对轴承的加速度信号进行积分,进行振动速度测量,可以在同样的测试条件下对轴承的振动加速度和振动速度进行比较,具有实际应用价值。本文采用数字量测试技术,以深沟球轴承为研究对象,对加速度积分算法进行研究,利用MATLAB和Lab VIEW软件编写了数字滤波器和时域积分算法,减去了时域积分产生的趋势项,降低了趋势项误差。通过实际测量实验,所得结果与轴承行业所用的标准精密模拟积分器所得结果具有较好的一致性,可以满足轴承振动速度测量的需要。     

实验室设备和标准物质的控制

为了保证实验室检定、检测、校准数据准确可靠,应配备满足规程、规范、规则所要求的仪器设备和标准物质,并对所使用的仪器设备和标准物质实施有效的控制。     

煤炭地下气化过程中温度场及其传热特征研究进展

煤炭地下气化(UCG)技术作为一种环境友好的采煤方法,可被用来开发深部煤层与矿井遗留的煤炭资源。当地下气化时,随着气化时间的推移,煤炭在煤层内部"燃烧"逐渐形成气化炉,炉内温度最高可达1 200℃。从UCG过程中的放热反应出发,综述了热量来源、温度场的变化及其传热特征等,总结了研究温度场的重要手段。分析认为,UCG是一个复杂的温热动态变化过程,在此过程中氧化还原反应、吸热和放热的可逆反应同时进行,导致了气化炉的温度场及其传热机制的复杂性。研究气化过程传热机制的方法主要有物理模拟、试验监测、理论计算和数值模拟4种,各自具有不同的适应性。其中,物理模拟的可操控性强,但是难以解决地层接触关系导致的接触热阻误差;试验监测能真实反映温度场等的变化情况,但是实际操作的经济性差;理论计算通过对气化过程的拆分,从理论角度定性定量了UCG的温度场特征,但理论计算难以考虑到温度渗流等对温度的影响;数值模拟借助计算机进行温度场的多场耦合,综合考虑了渗流、变形、温度等对传热的影响,但多场的物理耦合计算难度较大,且煤层及岩石的热物理性质随温度变化会产生较大的差异,导致数值建模的计算难度增加,制约了数值模拟方法的...