Online mining abnormal period patterns from multiple medical sensor data streams

With the advanced technology of medical devices and sensors, an abundance of medical data streams are available. However, data analysis techniques are very limited, especially for processing massive multiple physiological streams that may only be understood by medical experts. The state-of-the-art techniques only allow multiple medical devices to independently monitor different physiological parameters for the patient’s status, thus they signal too many false alarms, creating unnecessary noise, especially in the Intensive Care Unit (ICU). An effective solution which has been recently studied is to integrate information from multiple physiologic parameters to reduce alarms. But it is a challenge to detect abnormalities from high frequently changed physiological streams data, since abnormalities occur gradually due to the complex situation of patients. An analysis of ICU physiological data streams shows that many vital physiological parameters are changed periodically (such as heart rate, arterial pressure, and respiratory impedance) and thus abnormalities are generally abnormal period patterns. In this paper, we develop a Mining Abnormal Period Patterns from Multiple Physiological Streams (MAPPMPS) method to detect and rank abnormalities in medical sensor streams. The efficiency and effectiveness of the MAPPMPS method is demonstrated by a real-world massive database of multiple physiological streams sampled in ICU, comprising 250 patients’ streams (each stream involving over 1.3 million data points) with a total size of 28 GB data.     

A revised discrete particle swarm optimization algorithm for permutation flow-shop scheduling problem

This research proposes a revised discrete particle swarm optimization (RDPSO) to solve the permutation flow-shop scheduling problem with the objective of minimizing makespan (PFSP-makespan). The candidate problem is one of the most studied NP-complete scheduling problems. RDPSO proposes new particle swarm learning strategies to thoroughly study how to properly apply the global best solution and the personal best solution to guide the search of RDPSO. A new filtered local search is developed to filter the solution regions that have been reviewed and guide the search to new solution regions in order to keep the search from premature convergence. Computational experiments on Taillard’s benchmark problem sets demonstrate that RDPSO significantly outperforms all the existing PSO algorithms.     

Effect of natural antioxidants in virgin olive oil on oxidative stability of refined,bleached, and deodorized olive oil

The factors influencing the oxidative stability of different commercial olive oils were evaluated. Comparisons were made of (i) the oxidative stability of commercial olive oils with that of a refined, bleached, and deodorized (RBD) olive oil, and (ii) the antioxidant activity of a mixture of phenolic compounds extracted from virgin olive oil with that of pure compounds andα-tocopherol added to RBD olive oil. The progress of oxidation at 60°C was followed by measuring both the formation (peroxide value, PV) and the decomposition (hexanal and volatiles) of hydroperoxides. The trends in antioxidant activity were different according to whether PV or hexanal were measured. Although the virgin olive oils contained higher levels of phenolic compounds than did the refined and RBD oils, their oxidative stability was significantly decreased by their high initial PV. Phenolic compounds extracted from virgin olive oils increased the oxidative stability of RBD olive oil. On the basis of PV, the phenol extract had the best antioxidant activity at 50 ppm, as gallic acid equivalents, but on the basis of hexanal formation, better antioxidant activity was observed at 100 and 200 ppm.α-Tocopherol behaved as a prooxidant at high concentrations (>250 ppm) on the basis of PV, but was more effective than the other antioxidants in inhibiting hexanal formation in RBD olive oil.o-Diphenols (caffeic acid) and, to a lesser extent, substitutedo-diphenols (ferulic and vanillic acids), showed better antioxidant activity than monophenols (p- ando-coumaric), based on both PV and hexanal formation. This study emphasizes the need to measure at least two oxidation parameters to better evaluate antioxidants and the oxidative stability of olive oils. The antioxidant effectiveness of phenolic compounds in virgin olive oils can be significantly diminished in oils if their initial PV are too high.     

变电运行倒闸操作的危险点及预防对策探究

在实际操作中,由于变电运行非常复杂,很容易出现危险,因此,做好相关危险点的分析和预防工作,对保证电力系统运行安全有着非常重要的意义。结合变电运行倒闸操作中的危险点,对其预防对策进行了分析和探讨。     

浅谈煤矿地质构造评价指标系统的建立与优选

煤炭资源是我国社会发展的重要能源之一,在煤炭资源开采过程中,必须对煤矿的地质结构进行认真分析。重点分析了煤矿地质结构与煤矿开采的关系,通过对煤矿地质结构的发展规律进行分析,建立了一套完善的煤矿地质构造评价指标系统,从而为煤矿资源的安全开采提供了保障。     

高职院校工学结合人才培养机制的创新与实践

为了推进工学结合、校企合作的人才培养模式改革,以创建国家示范性高职院校为实践平台,通过创新机制,在一定程度上解决了制约工学结合人才培养模式改革的主要问题。     

高职院校特色专业监控体系建设研究

近年来,高职院校都比较注重特色专业的建设。其中,特色专业建设的监控体系也受到了高职院校的重视,并取得了一定的效果,同时,也给其他院校提供了有价值的参考和借鉴。但由于在认识水平、管理水平和教学水平等方面仍有一些问题,导致在监控过程和措施实施方面还存在许多疏漏,有待完善。     

刍议市政道路养护机械优化配置评价指标体系构建

市政府道路是城市道路的主要组成部分。通过对市政府道路养护的必要性、养护机械配置的问题以及如何构建合理的评价指标体系等进行阐释,为市政府道路养护工作提供相应的参考意见。     

10 kV配电线路接地故障及处理措施

配电线路是电网的基础设施,配电线路接地故障是10 kV配电线路实际运行过程中常见的故障之一.通过阐述10 kV配电线路接地故障的原因,提出了处理措施,以期为相关单位提供参考.     

二次酸水解法从黄姜中提取薯蓣皂甙元的工艺

薯蓣皂甙元是合成甾体激素药物和甾体避孕药物的重要原料,是黄姜中的主要活性物质。采用正交实验的方法,探讨了经过二次酸水解法从黄姜中提取薯蓣皂甙元的工艺条件,结果表明该方法提取的薯蓣皂甙元产率达到了2.41%,比直接水解法(2.20%)提高了9.55%。另外,采用熔点、元素分析法、红外、核磁等一系列的手段对产品进行表征,结果表明该法是可行的,提取的薯蓣皂甙元的质量纯度达到了工业的要求。