Effect of packaging materials and storage conditions on bacterial growth,off‐odour,pH and colour in chicken breast fillets

A comparison was made of the effect of different packaging materials on bacterial growth, off‐odour, pH and colour of chicken breast fillets stored at 4°C. For one of the packaging materials, the effects of temperature (4°C and 8°C) and initial oxygen present (0%, 2% and 4%) on bacterial growth, off‐odour, pH and colour in chicken breast fillets were also evaluated. Chicken breast fillets stored in the packaging material with the highest oxygen transmission rate (OTR) measured at actual storage conditions had the highest bacterial growth and the highest degree of off‐odour. Chicken breast fillets stored in packaging material mainly consisting of expanded PET had similar bacterial growth and off‐odour as in the barrier display film (BDF) packages, despite a smaller headspace volume and lower initial concentration of CO₂. No differences in discoloration and pH of the chicken breast fillets, due to storage temperature and amount of initial oxygen present, were found when one of the packaging materials was studied. In the early phase of the storage period, Pseudomonas spp. constituted the majority of the total viable counts, while after about 12 days, lactic acid bacteria dominated. At the end of the storage period, both Pseudomonas spp. and Enterobacteriaceae were present in high numbers. Significant differences in counts of Brochothrix thermosphacta were only obtained with initial presence of oxygen. The storage temperature had greater impact on microbial growth and off‐odour than the initial presence of oxygen in the packages. Copyright © 2004 John Wiley & Sons, Ltd.     

化学模式识别在原产地域产品保护中的应用

介绍了常用的化学模式识别方法,并且对化学模式识别在原产地域产品保护中的应用进行了综述.最后展望了原产地域产品表征和化学模式识别模型优化的发展趋势.     

过程神经网络的训练及其应用

研究过程神经网络的学习算法及其在过程模式识别中的应用。针对权值基展开的过程神经网络讨论了权值基的选取规则和对采样曲线的标准化处理问题,给出了含一个隐层的过程神经网络的误差反传播学习算法。以聚合化学反应和渗流实验两个具体实例验证了算法的有效性,也说明了过程神经网络的广泛应用前景。     

单兵智能头盔在消防救援中的探索与应用

目的 在消防装备于高层建筑、地下建筑、大型商业综合体等复杂救援环境中无法满足信息感知和状态感知需求的背景下,探索和分析智能头盔当前在应急救援、军队作战、采矿安全等领域的应用研究现状,以期解决当前消防救援活动中环境视野差、协同效率低、救援人员健康状态无法保证等问题,提高消防救援装备的功能性和保障性,避免救援活动中可能发生的安全事故。方法 人工智能、多设备协作、多模态感知等概念是智慧消防新的发展结合点,以消防救援装备的智能化、集成化趋势为基础,提出了利用增强现实技术满足视觉增强、信息协同、物体识别等信息感知需求,利用脑电监测技术满足人员健康状态监测、疲劳预警等状态感知需求。结论 在城市快速发展的背景下,单兵智能头盔在消防救援领域的应用具有可靠性高、功能扩展性强、任务辅助效率高等优势,但同时面临功耗大、重量大、设备交互研究不足等挑战;适用于消防救援场景的单兵智能头盔有动态舒适性多目标优化、多通道类人感知和意图协同交互、系统故障诊断及容错控制等方面的设计研究趋势。     

肤色建模和肤色分割的人脸定位研究

为了实现彩色图像中人脸的精确定位,提出了一种基于肤色模型、肤色分割处理的人脸定位算法.通过建立肤色模型计算得到图像的相似度分布图,经自适应阈值的二值化处理后,再进行肤色分割,将非人脸区域去除:最终利用眼睛与嘴巴构成三角形特征结合人脸椭圆模板匹配定位人脸.实验结果表明,该算法对于复杂背景下的彩色图像中的人脸正面定位和人脸转动一定角度后定位都有较好效果.     

Pattern recognition and the choice of the method of monitoring the thermal properties of materials in intelligent data-measuring systems

Methods of pattern recognition are proposed for cases when the data being processed is reliable or belongs to the fuzzy category. An algorithm for choosing the method of monitoring the thermal properties of materials is presented. Translated from Izmeritel’naya Tekhnika, No. 1, pp. 37–40, January, 2009.     

Recognition and classification of single and concurrent unnatural patterns in control charts via neural networks and fitted line of samples

The correct, prompt recognition and analysis of unnatural and significant patterns in Schewhart’s control charts are very important since they remind out-of-control conditions. In fact, pattern extraction increases the sensitivity of charts when identifying out of control conditions. Artificial neural networks have been used to identify unnatural patterns in many research studies due to their high efficiency in pattern recognition. In most of such studies, there is a significant risk of misclassification of highly sensitive patterns. To put it more clearly, the proposed models offered for the recognition of patterns with low parametric coefficients are mistaken. This study, offers a model for the recognition and analysis of basic patterns in process control charts using LVQ and MLP networks along with a fitted line analysis. In this model, not only does risk of misclassification at different levels of sensitivity decrease remarkably, but there will also be the possibility for recognition and analysis when basic pattern occur simultaneously. The efficiency and effectiveness of the model are shown by conducting tests based on simulation.     

图形传播与环境识别系统中的公共信息建设

图形传播是环境识别系统中公共信息建设的重要工具,在图形语系的基本构成要素及递进型作用力下产生了传播活动。图形传播中认知功能与导引功能的的逻辑化设计是确定人与环境关系的关键因素,而载体形态设计与受众感知度的关联分析同样也是识别系统中公共信息建设的重要内容。     

焊接过程声信号在线检测技术现状与展望

基于焊接过程声信号的声学检测技术是一种实时采集和检测缺陷的有效方法,对材料内部结构变化反映明显。概述了常规焊接缺陷无损检测方法的优缺点,对焊接过程声信号的分类和声信号采集系统进行了论述,分析总结了声发射信号和可听声信号的发声机理、检测原理和信号处理方法,并阐述其在焊接质量在线检测领域的研究现状及应用,特别是焊接缺陷、熔滴过渡形式和熔透状态的识别与预测。为了满足在线检测要求,包含声学检测在内的多传感信息融合焊接系统研究是关键,智能传感、信号处理、自动控制与人工智能技术的进一步研究能促进焊接产业的长足发展。     

人脸图像中人眼的检测与定位

利用人脸几何特征和图像分割原理，提出了一种在有背景的灰度和彩色人脸图像中自动检测与定位人眼的新算法。首先，基于人脸器官几何分布先验知识建立人眼位置判定准则；其次对人眼的分割阈值范围进行粗估计；然后采用分割阈值递增法，并结合人眼位置判定准则判定分割图像中双眼黑块是否出现；最后利用二雏相关系数作为对称相似性测度，检验检测到的双眼的真实性。为了避免图像背景对人眼检测的干扰，还运用了肤色分割原理来缩小检测人眼的搜索区域，从而进一步提高人眼定位的准确性。实验验证表明，所提出的人眼检测与定位方法在速度和准确性方面具有良好的性能。     

织物疵点检测与识别的方法研究

将织物图像分成大小相同的局部窗口,选取局部熵最小的窗口为待研究的感兴趣区域,在此区域内分割出疵点图像并用数学形态学中的开运算滤除噪声,计算疵点形状因子等作为识别参数,研究表明此方法因能避免对整幅图像进行复杂运算,在提取特征参数时对图像的全局搜索,具有识别正确率高、检测速度快等优点．     

高效3D密集残差网络及其在人体行为识别中的应用

针对3D-CNN能够较好地提取视频中时空特征但对计算量和内存要求很高的问题,本文设计了高效3D卷积块替换原来计算量大的3×3×3卷积层,进而提出了一种融合3D卷积块的密集残差网络(3D-EDRNs)用于人体行为识别。高效3D卷积块由获取视频空间特征的1×3×3卷积层和获取视频时间特征的3×1×1卷积层组合而成。将高效3D卷积块组合在密集残差网络的多个位置中,不但利用了残差块易于优化和密集连接网络特征复用等优点,而且能够缩短训练时间,提高网络的时空特征提取效率和性能。在经典数据集UCF101、HMDB51和动态多视角复杂3D人体行为数据库(DMV action3D)上验证了结合3D卷积块的3D-EDRNs能够显著降低模型复杂度,有效提高网络的分类性能,同时具有计算资源需求少、参数量小和训练时间短等优点。     

动态环境人-车系统的人体振动特性研究与仿真

 针对动态环境机械系统人-机界面设计的分析需要,应用人体动力学建模与人体振动实验相结合方法进行动态环境人-机系统的人体振动特性研究与仿真分析.依据多体系统动力学原理建立了人-车系统五自由度（5-DOF）坐姿人体全身垂直振动模型,经人体振动实验得到坐姿人体的传递函数曲线,采用参数识别方法获得人体的动力学参数,在此基础上,通过MATLAB/Bode对人体振动模型的模拟分析,得到了人体各部分的振动特性.用ADAMS/Vibration软件系统进行人体振动仿真试验,验证了5-DOF人体振动模型的人体振动特性研究结果的有效性.研究结果对于分析人-车系统的人体动力响应有着重要价值,可为动态环境机械系统的人-机界面设计提供重要参考,对客观评价人体坐姿的舒适性有指导作用.     

铁路卧铺客车人体振动舒适性建模与仿真

铁路卧铺客车乘客在卧姿状态下所承受的全身振动是影响其乘用舒适度的主要因素。研究了卧姿人体垂直振动模型,在铁道车辆二系悬挂动力学模型基础上,考虑卧铺的隔振作用与卧姿人体的垂直振动响应特性,建立了14自由度"人-铺-车辆"振动系统空间垂向耦合动力学模型,研究了在轨道随机不平顺激励下的卧姿人体垂直振动响应。应用卧姿人体全身振动舒适性评价标准,建立了铁路卧铺客车人体振动舒适性仿真流程。通过对人体头-臀二部位加速度均方根值先后进行部位计权和频率计权,得到卧铺客车卧姿人体振动舒适性指标。以M atlab为工具编制了卧铺客车人体振动舒适性仿真软件,交互输入车辆与人体的结构和动力学参数后,自动完成卧姿人体振动舒适性仿真计算,进而为铁路卧铺客车人体振动舒适性分析及车辆悬架参数优化提供了有效分析手段。     

静力试验中C/SiC构件集成式热结构的声发射特性及与材料测试的对比静力试验中C/SiC构件集成式热结构的声发射特性及与材料测试的对比

在对C/SiC复合材料常温拉伸试验的损伤表征和声发射演化特性进行简要分析的基础上,针对构件集成式设计带来的复杂性特点,对某C/SiC热结构在常温静力试验中的声发射特性进行了分析。给出了试验中声发射特征参数的分类特点。根据试验加载中声发射信号规律,给出了结构的损伤演化模式。通过与材料级声发射信号的对比,判断了试验加载与热结构极限破坏载荷之间的裕度。由此将声发射测试从材料级别的研究延伸到大型C/SiC热结构。      

Construction and evaluation of thoracic injury risk curves for a finite element human body model in frontal car crashes

There is a need to improve the protection to the thorax of occupants in frontal car crashes. Finite element human body models are a more detailed representation of humans than anthropomorphic test devices (ATDs). On the other hand, there is no clear consensus on the injury criteria and the thresholds to use with finite element human body models to predict rib fractures. The objective of this study was to establish a set of injury risk curves to predict rib fractures using a modified Total HUman Model for Safety (THUMS). Injury criteria at the global, structural and material levels were computed with a modified THUMS in matched Post Mortem Human Subjects (PMHSs) tests. Finally, the quality of each injury risk curve was determined. For the included PMHS tests and the modified THUMS, DcTHOR and shear stress were the criteria at the global and material levels that reached an acceptable quality. The injury risk curves at the structural level did not reach an acceptable quality.     

Advances in piezoelectric thin films for acoustic biosensors,acoustofluidics and lab-on-chip applications

Recently, piezoelectric thin films including zinc oxide (ZnO) and aluminium nitride (AlN) have found a broad range of lab-on-chip applications such as biosensing, particle/cell concentrating, sorting/patterning, pumping, mixing, nebulisation and jetting. Integrated acoustic wave sensing/microfluidic devices have been fabricated by depositing these piezoelectric films onto a number of substrates such as silicon, ceramics, diamond, quartz, glass, and more recently also polymer, metallic foils and bendable glass/silicon for making flexible devices. Such thin film acoustic wave devices have great potential for implementing integrated, disposable, or bendable/flexible lab-on-a-chip devices into various sensing and actuating applications. This paper discusses the recent development in engineering high performance piezoelectric thin films, and highlights the critical issues such as film deposition, MEMS processing techniques, control of deposition/processing parametres, film texture, doping, dispersion effects, film stress, multilayer design, electrode materials/designs and substrate selections. Finally, advances in using thin film devices for lab-on-chip applications are summarised and future development trends are identified.