科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数...科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数据干扰等不足。文章以多源大数据支持的指标体系为基础,构建熵权-随机森林耦合的地下空间需求评价模型。该模型基于熵权法确定负样本,将总样本和指标因子导入随机森林算法中,挖掘社会经济指标与现有地下设施间的复杂非线性关系。研究表明,经过网格搜索调优后的模型AUC(area under curve)精度达到0.979,其中77.45%的现有设施落入评价的高需求区内,证明所采用模型有较强的准确性和可靠性,其精细化评价结果可为今后地下建设选址提供更符合实际的借鉴。展开更多
近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧...近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧化硫、氮氧化物以及颗粒物)的排放特征及其成因.结果表明:各污染物的区域性分布明显,污染物浓度变化的总体趋势北方高于南方,SO2、NO2、PM10年平均浓度北方分别高于南方108.15%、7.60%、48.36%;从大气污染组分来看,颗粒物的增长速度最快,石家庄2007—2016年PM10增速为28.10%;而SO2的污染物浓度在下降,乌鲁木齐的降速为84.10%.展开更多
Background Combinations of coronary heart disease(CHD) and other chronic conditions complicate clinical management and increase healthcare costs. The aim of this study was to evaluate gender-specific relationships bet...Background Combinations of coronary heart disease(CHD) and other chronic conditions complicate clinical management and increase healthcare costs. The aim of this study was to evaluate gender-specific relationships between CHD and other comorbidities. Methods We analyzed data from the German Health Interview and Examination Survey(DEGS1), a national survey of 8152 adults aged 18-79 years. Female and male participants with self-reported CHD were compared for 23 chronic medical conditions. Regression models were applied to determine potential associations between CHD and these 23 conditions. Results The prevalence of CHD was 9%(547 participants): 34%(185) were female CHD participants and 66%(362) male. In women, CHD was associated with hypertension(OR = 3.28(1.81-5.9)), lipid disorders(OR = 2.40(1.50-3.83)), diabetes mellitus(OR = 2.08(1.24-3.50)), kidney disease(OR = 2.66(1.101-6.99)), thyroid disease(OR = 1.81(1.18-2.79)), gout/high uric acid levels(OR = 2.08(1.22-3.56)) and osteoporosis(OR = 1.69(1.01-2.84)). In men, CHD patients were more likely to have hypertension(OR = 2.80(1.94-4.04)), diabetes mellitus(OR = 1.87(1.29-2.71)), lipid disorder(OR = 1.82(1.34-2.47)), and chronic kidney disease(OR = 3.28(1.81-5.9)). Conclusion Our analysis revealed two sets of chronic conditions associated with CHD. The first set occurred in both women and men, and comprised known risk factors: hypertension, lipid disorders, kidney disease, and diabetes mellitus. The second set appeared unique to women: thyroid disease, osteoporosis, and gout/high uric acid. Identification of shared and unique gender-related associations between CHD and other conditions provides potential to tailor screening, preventive, and therapeutic options.展开更多
Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical ...Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical methods for anomalous cell detection cannot adapt to the evolution of networks, and data mining becomes the mainstream. In this paper, we propose a novel kernel density-based local outlier factor(KLOF) to assign a degree of being an outlier to each object. Firstly, the notion of KLOF is introduced, which captures exactly the relative degree of isolation. Then, by analyzing its properties, including the tightness of upper and lower bounds, sensitivity of density perturbation, we find that KLOF is much greater than 1 for outliers. Lastly, KLOFis applied on a real-world dataset to detect anomalous cells with abnormal key performance indicators(KPIs) to verify its reliability. The experiment shows that KLOF can find outliers efficiently. It can be a guideline for the operators to perform faster and more efficient trouble shooting.展开更多
文摘科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数据干扰等不足。文章以多源大数据支持的指标体系为基础,构建熵权-随机森林耦合的地下空间需求评价模型。该模型基于熵权法确定负样本,将总样本和指标因子导入随机森林算法中,挖掘社会经济指标与现有地下设施间的复杂非线性关系。研究表明,经过网格搜索调优后的模型AUC(area under curve)精度达到0.979,其中77.45%的现有设施落入评价的高需求区内,证明所采用模型有较强的准确性和可靠性,其精细化评价结果可为今后地下建设选址提供更符合实际的借鉴。
文摘近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧化硫、氮氧化物以及颗粒物)的排放特征及其成因.结果表明:各污染物的区域性分布明显,污染物浓度变化的总体趋势北方高于南方,SO2、NO2、PM10年平均浓度北方分别高于南方108.15%、7.60%、48.36%;从大气污染组分来看,颗粒物的增长速度最快,石家庄2007—2016年PM10增速为28.10%;而SO2的污染物浓度在下降,乌鲁木齐的降速为84.10%.
文摘Background Combinations of coronary heart disease(CHD) and other chronic conditions complicate clinical management and increase healthcare costs. The aim of this study was to evaluate gender-specific relationships between CHD and other comorbidities. Methods We analyzed data from the German Health Interview and Examination Survey(DEGS1), a national survey of 8152 adults aged 18-79 years. Female and male participants with self-reported CHD were compared for 23 chronic medical conditions. Regression models were applied to determine potential associations between CHD and these 23 conditions. Results The prevalence of CHD was 9%(547 participants): 34%(185) were female CHD participants and 66%(362) male. In women, CHD was associated with hypertension(OR = 3.28(1.81-5.9)), lipid disorders(OR = 2.40(1.50-3.83)), diabetes mellitus(OR = 2.08(1.24-3.50)), kidney disease(OR = 2.66(1.101-6.99)), thyroid disease(OR = 1.81(1.18-2.79)), gout/high uric acid levels(OR = 2.08(1.22-3.56)) and osteoporosis(OR = 1.69(1.01-2.84)). In men, CHD patients were more likely to have hypertension(OR = 2.80(1.94-4.04)), diabetes mellitus(OR = 1.87(1.29-2.71)), lipid disorder(OR = 1.82(1.34-2.47)), and chronic kidney disease(OR = 3.28(1.81-5.9)). Conclusion Our analysis revealed two sets of chronic conditions associated with CHD. The first set occurred in both women and men, and comprised known risk factors: hypertension, lipid disorders, kidney disease, and diabetes mellitus. The second set appeared unique to women: thyroid disease, osteoporosis, and gout/high uric acid. Identification of shared and unique gender-related associations between CHD and other conditions provides potential to tailor screening, preventive, and therapeutic options.
基金supported by the National Basic Research Program of China (973 Program: 2013CB329004)
文摘Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical methods for anomalous cell detection cannot adapt to the evolution of networks, and data mining becomes the mainstream. In this paper, we propose a novel kernel density-based local outlier factor(KLOF) to assign a degree of being an outlier to each object. Firstly, the notion of KLOF is introduced, which captures exactly the relative degree of isolation. Then, by analyzing its properties, including the tightness of upper and lower bounds, sensitivity of density perturbation, we find that KLOF is much greater than 1 for outliers. Lastly, KLOFis applied on a real-world dataset to detect anomalous cells with abnormal key performance indicators(KPIs) to verify its reliability. The experiment shows that KLOF can find outliers efficiently. It can be a guideline for the operators to perform faster and more efficient trouble shooting.
