A new synergy decision method for radar and infrared search and track (IRST) data fusion is proposed, to solve such problems as how to decrease opportunities for radar suffering from being locked on by adverse electr...A new synergy decision method for radar and infrared search and track (IRST) data fusion is proposed, to solve such problems as how to decrease opportunities for radar suffering from being locked on by adverse electronic support measures (ESM), how to retrieve range information of the target during radar off, and how to detect the maneuver of the target. Firstly, polynomials used to predict target motion states are constructed. Secondly, a set of discriminants for detecting target maneuver are established by comparing the predicted values with the observations from IRST. Thirdly, a set of decisions are presented. Lastly, simulation is performed on the given scenario to test the validity of the method.展开更多
Spectrum sensing is one of the core technologies for cognitive radios （CR）, where reliable detection of the signals of primary users （PUs） is precondition for implementing the CR systems. A cooperative spectrum se...Spectrum sensing is one of the core technologies for cognitive radios （CR）, where reliable detection of the signals of primary users （PUs） is precondition for implementing the CR systems. A cooperative spectrum sensing scheme based on an adaptive decision fusion algorithm for spectrum sensing in CR is proposed in this paper. This scheme can estimate the PU prior probability and the miss detection and false alarm probabilities of various secondary users （SU）, and make the local decision with the Chair-Varshney rule so that the decisions fusion can be done for the global decision. Simulation results show that the false alarm and miss detection probabilities resulted from the proposed algorithm are significantly lower than those of the single SU, and the performance of the scheme outperforms that of the cooperative detection by using the conventional decision fusion algorithms.展开更多
目的构建预测后路腰椎椎间融合患者术中低体温发生风险的决策树模型。方法2022年6-9月,采用便利抽样法选取于某医院行后路腰椎椎间融合术的102例患者为研究对象,根据是否发生术中低体温将其分为低体温组(n=77)和非低体温组(n=25),使用...目的构建预测后路腰椎椎间融合患者术中低体温发生风险的决策树模型。方法2022年6-9月,采用便利抽样法选取于某医院行后路腰椎椎间融合术的102例患者为研究对象,根据是否发生术中低体温将其分为低体温组(n=77)和非低体温组(n=25),使用单因素和多因素Logistic回归分析发生术中低体温的危险因素,并建立相关决策树预测模型。结果体质量指数(body mass index,BMI)较低、美国麻醉医生协会(American Society of Aneshesiologists,ASA)评分较高、入室体温较低、手术时间较长和出血量较多是后路腰椎椎间融合术患者术中低体温的独立危险因素(均P<0.05);基于上述因素建立了预测后路腰椎椎间融合术患者术中低体温发生风险的决策树模型,模型验证结果显示,曲线下面积(area under curve,AUC)为0.821(95%CI:0.798~0.844)。结论基于影响因素构建的决策树模型,对后路腰椎椎间融合术患者术中低体温的发生风险具有良好的预测能力。展开更多
文摘A new synergy decision method for radar and infrared search and track (IRST) data fusion is proposed, to solve such problems as how to decrease opportunities for radar suffering from being locked on by adverse electronic support measures (ESM), how to retrieve range information of the target during radar off, and how to detect the maneuver of the target. Firstly, polynomials used to predict target motion states are constructed. Secondly, a set of discriminants for detecting target maneuver are established by comparing the predicted values with the observations from IRST. Thirdly, a set of decisions are presented. Lastly, simulation is performed on the given scenario to test the validity of the method.
文摘Spectrum sensing is one of the core technologies for cognitive radios （CR）, where reliable detection of the signals of primary users （PUs） is precondition for implementing the CR systems. A cooperative spectrum sensing scheme based on an adaptive decision fusion algorithm for spectrum sensing in CR is proposed in this paper. This scheme can estimate the PU prior probability and the miss detection and false alarm probabilities of various secondary users （SU）, and make the local decision with the Chair-Varshney rule so that the decisions fusion can be done for the global decision. Simulation results show that the false alarm and miss detection probabilities resulted from the proposed algorithm are significantly lower than those of the single SU, and the performance of the scheme outperforms that of the cooperative detection by using the conventional decision fusion algorithms.
文摘目的构建预测后路腰椎椎间融合患者术中低体温发生风险的决策树模型。方法2022年6-9月,采用便利抽样法选取于某医院行后路腰椎椎间融合术的102例患者为研究对象,根据是否发生术中低体温将其分为低体温组(n=77)和非低体温组(n=25),使用单因素和多因素Logistic回归分析发生术中低体温的危险因素,并建立相关决策树预测模型。结果体质量指数(body mass index,BMI)较低、美国麻醉医生协会(American Society of Aneshesiologists,ASA)评分较高、入室体温较低、手术时间较长和出血量较多是后路腰椎椎间融合术患者术中低体温的独立危险因素(均P<0.05);基于上述因素建立了预测后路腰椎椎间融合术患者术中低体温发生风险的决策树模型,模型验证结果显示,曲线下面积(area under curve,AUC)为0.821(95%CI:0.798~0.844)。结论基于影响因素构建的决策树模型,对后路腰椎椎间融合术患者术中低体温的发生风险具有良好的预测能力。
