基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience

Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration.     

Mining fleet management systems: a review of models and algorithms

The objective of this paper is to review and document the mine fleet management systems’ models and algorithms. The purpose is to understand the algorithms behind the fleet management systems and the proposed academic solutions in this area to identify any gaps in the current literature and to open up opportunities to establish research questions that need to be addressed in an integrated simulation and optimisation operational planning research framework. In this paper, we review industrial fleet management systems and the main academic algorithms behind such systems. The fleet management systems are divided into three subsequently related problems to review: shortest path, production optimisation and real-time dispatching. Finally, the limitations of current algorithms for fleet management systems are documented in terms of mining practice feasibility and optimality of the solution on large-scale problems. The results of this literature review enable us to evaluate the logical links between major components of an integrated simulation and optimisation operational planning framework with current theory of fleet management systems.     

Deformation-Strength Relationships in Short-Term Tension of Heat-Resistant Materials

The analysis of 124 curves obtained in short-term tensile tests demonstrate that they can be described by varying strain hardening and softening characteristics. Different stress–strain curves can be produced at invariable yield strength and ultimate strength and interrelated proportional variations of the above characteristics. To determine some specific stress–strain curve, it is necessary to take account of yield strength and ultimate strength as well as strain corresponding to the latter. The relations between yield strength, ultimate strength and hardening and their practically complete absence between these parameters and softening were statistically established.     

煤矿生产、安全调度LED电子大屏幕显示系统的设计

通过比较煤矿生产、安全调度显示方式的优缺点，提出和分析了适合于煤矿生产安全调度的ＬＥＤ电子大屏幕显示系统配置、功能及特点。     

基于B/S与C/S相结合的闸门自动调度系统

以上海市淀北片河网闸门为例,开发了以基于Web的B/S结构为主、B/S与C/S相结合的河网闸门自动调度系统,介绍了该系统的整体框架和各子系统的功能。经实践检验,基于B/S与C/S相结合的闸门自动调度系统发挥了B/S与C/S各自的优点,提高了防洪决策的及时性和准确性。     

金沙江防洪(库容)规划的探讨

在分析长江灾害洪水特征的基础上，全面深入地研究了全沙江水库的防洪库客、防洪目标、防洪特点和调度原则，并对防洪库容的作用进行了估算和分析。从多方面比较了虎跳峡高坝方案与低坝方案，结果表明：高坝方案的效益明显高于低坝方案，而两者所需付出的代价相差不大。     

Treatment of depressive symptoms during short-term rehabilitation: An attempted replication of the DOUR project.

Objective: To replicate and extend P. A. Lichtenberg and colleagues' (1996) cross-disciplinary intervention to improve physical and mental health among older adults. Participants: 14 depressed older adults (6 treatment, 8 control). Setting: The short-term rehabilitation unit of an urban nursing home. Intervention: Occupational therapists were trained to treat depression using pleasant events and cognitive-behavioral therapies. Outcome Measures: Geriatric Depression Scale, the Short Form-12, and the Multi-Level Assessment Instrument: Activities of Daily Living. Results: No significant group differences were found in physical or mental health. However, more control group members (75%) than treatment group members (33%) were depressed at study completion. Conclusions: The treatment of depressive symptoms can be integrated with a nonmental health treatment modality. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

风电典型机型的闪变严重度分析

风力发电机组的并网运行对当地电网的电能质量有不良影响。为此．根据定速机型、变速机型引起电压波动和闪变的原理及并网风电机组电能质量的国际电工标准IEC61400—21，讨论了测量风电机组输出闪变的方法，给出了两种典型机型的短时闪变严重度与风速的关系实验曲线，并对不同风速段的闪变成因进行了分析。结果表明，变速风电机组在高风速区域综合应用桨叶节距角和变流器控制实现输出功率的稳定能够减小短时闪变严重度，在低风速区域追求最佳风能利用系数将使闪变严重度值增高。