Measuring exertion time,duty cycle and hand activity level for industrial tasks using computer vision

Abstract

Two computer vision algorithms were developed to automatically estimate exertion time, duty cycle (DC) and hand activity level (HAL) from videos of workers performing 50 industrial tasks. The average DC difference between manual frame-by-frame analysis and the computer vision DC was ?5.8% for the Decision Tree (DT) algorithm, and 1.4% for the Feature Vector Training (FVT) algorithm. The average HAL difference was 0.5 for the DT algorithm and 0.3 for the FVT algorithm. A sensitivity analysis, conducted to examine the influence that deviations in DC have on HAL, found it remained unaffected when DC error was less than 5%. Thus, a DC error less than 10% will impact HAL less than 0.5 HAL, which is negligible. Automatic computer vision HAL estimates were therefore comparable to manual frame-by-frame estimates.

Practitioner Summary: Computer vision was used to automatically estimate exertion time, duty cycle and hand activity level from videos of workers performing industrial tasks.     

铅酸蓄电池极板中活性物质含量的测定

采用碘量法和配位滴定法分别测定铅酸蓄电池正、负极板中活性物质PbO2、PbO的含量,借此判断电池是否合格。此方法步骤简单,易于判断终点。     

化妆品生产中抗性环境菌株的研究

对化妆品生产中的环境菌株进行菌种分离,得到了一株伯克霍尔德属类的环境菌。通过抑菌圈和挑战实验证明,该菌对以双咪唑烷基脲为主要功能成分的防腐体系具有抗性;另外通过去活性物挑战实验,证明活性物对抗性环境菌在产品中爆发性生长起关键作用。通过以上数据,更深入的了解产品微生物污染的来源和机制,对有效预防化妆品生产微生物污染,同时设计更有效的防腐体系提供依据。     

次氯酸钠对德尔卑沙门氏菌生物被膜的抑制作用及机制

目的：为控制德尔卑沙门氏菌（Salmonella Derby）在食品加工过程中的污染，研究不同体积分数次氯酸钠对S. Derby生物被膜的抑制作用及其机制。方法：采用结晶紫染色法和平板菌落计数法观察次氯酸钠对生物被膜的抑制和清除效果，进一步观察不同体积分数次氯酸钠作用下沙门氏菌泳动能力和生物被膜内细胞的代谢活性、胞外聚合物含量和微观形态的变化规律。结果：次氯酸钠的最小抑菌浓度（minimum inhibitory concentration，MIC）为0.08%（体积分数，下同），亚MIC（0.04%、0.02%、0.01%）的次氯酸钠可以抑制S. Derby生物被膜的形成，对成熟生物被膜也有一定的清除效果，且不同亚MIC次氯酸钠的作用效果差异显著（P＜0.05）；不同体积分数次氯酸钠处理能降低生物被膜内细胞代谢活性，抑制胞外多糖的合成，且不同体积分数次氯酸钠的作用效果差异显著（P＜0.05）。激光共聚焦扫描显微镜结果显示，与对照组相比，次氯酸钠处理使得生物被膜厚度减小、活菌数减少、死菌数增多、细菌由聚集状态变为分散状态。结论：不同体积分数次氯酸钠对S. Derby生物被膜的形成有明显的抑制作用，这一作用与干扰细菌生长、生物被膜内细胞代谢活性和胞外多糖的合成有关。     

Bark as feedstock for dual fluidized bed gasifiers—Operability,efficiency, and economics

The demand for biofuels and biochemicals is expected to increase in the future, which will in turn increase the demand for biomass feedstock. Large gasification plants fueled with biomass feedstock are likely to be a key enabling technology in a resource‐efficient, bio‐based economy. Furthermore, the costs for producing biofuels and biochemicals in such plants could potentially be decreased by utilizing inexpensive low‐grade residual biomass as feedstock. This study investigates the usage of shredded tree bark as a feedstock for the production of biomethane in the GoBiGas demonstration plant in Gothenburg, Sweden, based on a 32 MW_th industrial dual fluidized bed gasification unit. The plant was operated with bark feedstock for 12 000 hours during the period 2014 to 2018. Data from the measurement campaign were processed using a stochastic approach to establish the plant's mass and energy balances, which were then compared with operation of the plant with wood pellets. For this comparison, an extrapolation algorithm was developed to predict plant performance using bark dried to the same moisture content as wood pellets, ie, 8%_w.b. Plant operation with bark feedstock was evaluated for operability, efficiency, and feedstock‐related cost. The gas quality achieved during the test period was similar to that obtained for operation with wood pellets. Furthermore, no significant ash sintering or agglomeration problems were observed more than 750 hours of operation. The calculated biomass‐to‐biomethane efficiency is 43% to 47% (lower heating value basis) for operation with wet bark. However, the predicted biomass‐to‐biomethane efficiency can be increased to 55%–65% for operation with bark feedstock dried to 8% moisture content, with corresponding feedstock costs in the range of 24.2 to 32.7 EUR/MWh; ie, a cost reduction of about 40% compared with wood pellets.