含噪混合盲扰信分离中联合降噪技术研究

针对盲扰信分离技术在含噪混合条件下分离效果差的问题,文章采用经验模态分解和小波变换联合的降噪技术进行分离前的消噪预处理,研究了联合降噪的三种模式,分别对其降噪效果进行了仿真分析,得到了一种较好的联合降噪模式。将该模式与无噪环境下的盲分离算法相结合,弥补了经典盲源分离算法处理含噪混合盲扰信分离的不足。仿真结果表明该算法在一定范围的低信噪比条件下,能够从含噪的混合信号中恢复出通信信号源。     

Revenue management: A real options approach

Revenue management is the process of actively managing inventory or capacity to maximize revenues. The active management typically occurs through managerial levers such as price, promotion, or availability. We present a novel real options approach to revenue management that is specifically suited to the car rental business. We illustrate the concept with actual car rental data. The model produces minimally acceptable prices and inventory release quantities (number of cars available for rent at a given price) as a function of remaining time and available inventory. The pricing and inventory release recommendations of the developed model confirm earlier empirical analysis that suggested current practises discount too deeply early in the booking cycle. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

极化域—空域联合谱估计

首次提出极化域-空域联合谱的概念,拓广了电磁波特征参量的谱描述方法.结合具体的极化敏感阵列定义了极化域-空域联合谱,用MUSIC方法得到联合谱函数表达式.研究了联合谱的估计的重要性能指标估计精度和分辨力,估计精度用克拉美劳限CRB(cramer-Rao Bound)来具体度量,分辨力由极化域-空域模糊函数以及模糊图来描述.最后仿真结果验证了该方法的有效性和理论分析的正确性.     

基于模态分析的挠性接头角刚度测量研究

挠性接头是动力调谐陀螺的关键元件,刚度是其重要指标。针对挠性接头角刚度的测量,提出了一种基于模态分析的动态角刚度测量方法。该方法采用阶跃激励,利用高精度传感器和数据采集卡测量挠性接头的振动并采集数据,然后对采集数据进行数字滤波、FFT变换和频谱细化,计算出挠性接头的动态角刚度,同时相应地求出了角阻尼比系数。该方法解决了长期以来采用静态测试法测量挠性接头角刚度所带来的问题,具有测量精度高、操作方便、测试效率高、重复性好等特点。     

夺占小型岛屿作战综合登陆舰编队展开点选择优化模型

针对综合登陆舰编队夺占小型岛屿作战中的威胁特点,确定了岸基航空兵对综合登陆舰的有效掩护区,建立了综合登陆舰展开点选择的优化模型,并给出了简单方便的图上作业法,为合理确定综合登陆舰的展开点提供了方法和依据。     

含万向铰偏斜轴系的过渡过程横扭耦合振动特性

为提供船艇推进、火炮、航空动力及传动装置机械设计的理论分析基础,建立了加速度冲击下含万向铰偏斜轴系横扭耦合振动模型,揭示了轴系的过渡过程横扭耦合振动特性。将从动轴视为弯曲刚性、扭转柔性的轴,用投影平面上动态偏斜角表示轴系横向振动,用拉格朗日方程推导了万向铰轴系过渡过程横扭耦合三自由度振动微分方程,结合振动响应仿真给出了加速度和系统参数对轴系过渡过程横扭耦合振动特性的影响规律。结果表明:负载转矩增大和刚度不对称性减小导致耦合振动系统颤振失稳区增大;在超谐共振区内,加速度增大对过渡过程系统振动起稳定作用,转矩、刚度和偏斜角增大导致过渡过程系统振动失稳区域变大。     

一体化联合作战对装备保障系统的影响及要求

装备保障信息建设要适应一体化联合作战的需求,就必须弄清一体化联合作战对装备保障系统的影响。运用系统方法,着眼环境对系统的影响,从分析一体化联合作战本质入手,阐述了一体化联合作战对装备保障系统功能、结构、运行和组成等要素的影响及要求,并为未来我军装备保障信息化建设提出了几点应对策略。     

空降作战中空降兵电子对抗力量运用浅析

在科技引领的现代战争中,空降作战面临着高精度、杀伤力大的制导武器的威胁。电子对抗力量作为电子战中的武装力量,为空降兵提供了重要的安全保障。本文研究了空降作战在复杂的电磁环境中面临的电子武器威胁,分析了空降兵电子对抗力量在空降作战中的地位作用,结合空降作战的特点探索空降兵电子对抗力量的运用模式,如通过电子侦察、电子佯动、压制干扰、综合防护等手段为空降作战快速占据进攻优势奠定良好的电磁环境基础。此外,为完善空降兵电子对抗力量的作战结构,本研究提出空降作战中电子对抗作战运用的要求,以充分发挥电子对抗在空降作战中的能力,确保空降作战中制电磁权的优势,提高空降作战的制胜效能。     

Heart analytics: Analytical modeling of cardiovascular care

Cardiovascular diseases (CVDs) are the leading cause of death and disability both in the United States and worldwide. Despite high morbidity, mortality, and cost in the United States and global healthcare systems, cardiovascular care has been understudied in the healthcare operations management literature. In this paper, we identify research opportunities for healthcare operations management scholars to aid in improving cardiovascular care. We focus on three burdensome conditions, including (1) coronary artery disease, (2) stroke, and (3) heart failure, which, collectively, lead to the vast majority of CVD‐caused mortality and disability. For each condition, we characterize a typical patient's journey in receiving cardiovascular care, elucidating key challenges in improving care and outlining research questions for healthcare operations management scholars. We close with a reference to new research opportunities that emerge as artificial intelligence is likely to transform much of cardiovascular care.     

Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.