该项目致力于开源数据质量和数据准备解决方案。 数据质量包括策略定义的概要分析,过滤,治理,相似性检查,数据充实变更,实时警报,篮子分析,气泡图仓库验证,单个客户视图等。 该工具正在开发高性能的集成数据管理平台,它将无缝地进行数据集成,数据分析,数据质量,数据准备,虚拟数据创建,元数据发现,异常发现,数据清理,报告和分析。 它还具有Hadoop(大数据)支持,可将文件移入Hadoop Grid或从Hadoop Grid移出,创建,加载和配置Hive表。 此项目也称为“ Aggregate Profiler”。此项目的Resful API的构建方式为(测试版)https://sourceforge.net/projects/restful-api-for-osdq/基于apache spark的数据质量正在构建https://sourceforge.net/projects/apache-spark-osdq/
2022-04-13 09:12:23 84.88MB 开源软件
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产品质量目标制定标准流程DOC以持续提高组织业绩为目的,只为给你最适合、最想要产品质量目标制定标准流...该文档为产品质量目标制定标准流程DOC,是一份很不错的参考资料,具有较高参考价值,感兴趣的可以下载看看
2022-04-13 08:52:33 5KB
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图像质量调试工具使用指南,就是HISI的调试工具的使用方法,还是又有用的,可以下载看看,如果你是hisi的客户的话会有技术支持
2022-04-12 21:42:52 11.9MB ISP
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随着电子商务领域的迅速发展,在线商品评价规模日益庞大,评价质量参差不齐,用户难以筛选有用评价信息做出购买决策,因此如何有效识别高质量评价信息成为重要议题。以在线商品评价的有用性投票为基础定义评价质量,使用贝叶斯网络表示在线商品评价的相似性及不确定性,通过对在线商品评价信息进行多维度特征统计,构建在线商品评价质量评估模型,使用概率推理机制对在线商品评价质量进行分类预测,并给出评价质量分类置信度。在真实数据集上验证模型有效性及高效性。
2022-04-12 19:57:46 641KB 论文研究
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During the past two decades, the field of medical imaging has achieved dramatic improvements in imaging system capability with accompanying increases in system complexity. Much of this progress has been fueled by advances in computing technology and the widespread adoption of digital techniques for data acquisition, processing and display. Although every branch of medical imaging has been significantly affected, the most striking examples ofthis revolution are x-ray computed tomography and magnetic resonance imaging. Fortunately, a consensus on quantitative measurement methodology for assessing diagnostic imaging technologies has been gradually emerging. It has grown out of the recognition of common features among imaging modalities that allows their limitations to be understood within the framework of statistical decision analysis.
2022-04-12 17:30:18 8.78MB 图像处理 图像质量
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电压质量评估模型(内含数据与python代码)。 提供给最终用途设备的电力质量取决于公用事业公司提供的电压质量。如果电压在额定频率下具有额定值,则称其具有质量,而没有任何偏差。
2010药品GMP指南-质量控制实验室与物料系统,帮助了解GMP中质量控制实验室与物料系统建立
2022-04-11 00:00:30 18.78MB GMP
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The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a good approximation to perceived image quality. This paper proposes a multi-scale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions. We develop an image synthesis method to calibrate the parameters that define the relative importance of different scales. Experimental comparisons demonstrate the effectiveness of the proposed method.
2022-04-10 22:50:33 464KB 图像质量评价
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22届陕西省高三教学质量检测试题(二)理数试题及答案
2022-04-10 14:00:11 9.02MB 高考数学
2022届陕西省高三教学质量检测试题(二)文数试题及答案
2022-04-10 14:00:10 8.71MB 高考数学