Evaluation of physiological workload assessment methods using heart rate and accelerometry for a smart wearable system

Work metabolism (WM) can be accurately estimated by oxygen consumption (VO₂), which is commonly assessed by heart rate (HR) in field studies. However, the VO₂–HR relationship is influenced by individual capacity and activity characteristics. The purpose of this study was to evaluate three models for estimating WM compared with indirect calorimetry, during simulated work activities. The techniques were: the HR-Flex model; HR branched model, combining HR with hip-worn accelerometers (ACC); and HR?+?arm-leg ACC model, combining HR with wrist- and thigh-worn ACC. Twelve participants performed five simulated work activities and three submaximal tests. The HR?+?arm-leg ACC model had the overall best performance with limits of agreement (LoA) of ?3.94 and 2.00?mL/min/kg, while the HR-Flex model had ?5.01 and 5.36?mL/min/kg and the branched model, ?6.71 and 1.52?mL/min/kg. In conclusion, the HR?+?arm-leg ACC model should, when feasible, be preferred in wearable systems for WM estimation.

Practitioner Summary: Work with high energy demand can impair employees’ health and life quality. Three models were evaluated for estimating work metabolism during simulated tasks. The model combining heart rate, wrist- and thigh-worn accelerometers showed the best accuracy. This is, when feasible, suggested for wearable systems to assess work metabolism.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.     

Kalman filter based production control of a failure-prone single-machine single-product manufacturing system with imprecise demand and inventory information

An adaptive production control structure for failure-prone manufacturing systems under inventory and demand uncertainty is proposed. It contains estimation and forecasting modules incorporated into a control loop. The customer demand is unknown and its rate is composed of ramp-type, seasonal and random components. Information available to decision maker consists of imprecise inventory records, and the Kalman filter technique is used for estimating the inventory level and demand rate online from noisy inventory measurements. Estimates obtained are shown to converge to the actual values in stochastic sense. They are subsequently used for demand component forecasting, once the estimation errors become sufficiently small. A forecasting algorithm allows estimating ramp-type and seasonal demand components, together with their potential errors. Obtained estimates are incorporated into production control procedures, recently developed for manufacturing systems under variable and uncertain demand. Optimality conditions in the form of Hamilton-Jacobi-Bellman equations are obtained. A constructive numerical method for computing sub-optimal production policies is proposed and validated through numerical simulations.     

基于微流控的人卵母细胞特性检测

人的卵母细胞特性的研究对于临床医学具有重要意义,可以通过卵母细胞的大小对其活性进行研究。采用微流控平台与MATLAB算法相结合的方法,利用微流控器件的沟道对卵母细胞进行挤压,由于卵母细胞的活性不同对于挤压的反应也不同,活性越好的卵母细胞通过沟道时变形性越好,经检测卵母细胞有很好的活性;拍摄卵母细胞发生形变与卵母细胞通过沟道的视频,利用MATLAB程序进行图像处理得到卵母细胞的大小,测得卵母细胞的直径约为170μm。这种方法有别于传统方法,在一定程度上使用了算法识别,提高了卵母细胞分析统计的准确度,提升了工作效率。由于人的卵母细胞比较珍贵,只进行了初期实验研究,证明此方法确实可行。     

Clustering biomedical and gene expression datasets with kernel density and unique neighborhood set based vein detection

It is a crucial need for a clustering technique to produce high-quality clusters from biomedical and gene expression datasets without requiring any user inputs. Therefore, in this paper we present a clustering technique called KUVClust that produces high-quality clusters when applied on biomedical and gene expression datasets without requiring any user inputs. The KUVClust algorithm uses three concepts namely multivariate kernel density estimation, unique closest neighborhood set and vein-based clustering. Although these concepts are known in the literature, KUVClust combines the concepts in a novel manner to achieve high-quality clustering results. The performance of KUVClust is compared with established clustering techniques on real-world biomedical and gene expression datasets. The comparisons were evaluated in terms of three criteria (purity, entropy, and sum of squared error (SSE)). Experimental results demonstrated the superiority of the proposed technique over the existing techniques for clustering both the low dimensional biomedical and high dimensional gene expressions datasets used in the experiments.     

Enhancement of resistance to galvanic corrosion of ZE41 Mg alloy by equal channel angular pressing

The galvanic corrosion behavior of as-received and ECAPed ZE41 Mg alloy coupled with Al7075 alloy is investigated using zero resistance ammeter in three different corrosive environments, 0, 0.1, and 1 M NaCl, to mimic the conditions experienced in engineering applications. The mechanism of galvanic corrosion for the ZE41 Mg–Al7075 aluminum alloy is explained. It is observed that a robust surface film containing a composite layer of oxide/hydroxide of magnesium and aluminum is established in deionized water (0 M). However, only a single layer of magnesium oxide/hydroxide is detected in chloride-containing environments. Equal channel angular pressing (ECAP) improved the resistance to galvanic corrosion by 58% and 54% when compared with the as-cast counterparts in 0 and 1 M NaCl solution, respectively. In contrast, galvanic corrosion resistance decreased by 26% in 0.1 M NaCl after ECAP while the as-received samples evinced pits unfavorable to be used in engineering applications. ECAP is a promising method to combat galvanic corrosion encountered by ZE41 magnesium alloy used in automobiles and components of military vehicles.     

宽带数字接收机IQ不平衡估计与自适应补偿算法

针对宽带调制解调技术中广泛存在的IQ不平衡问题,在IQ不平衡模型及补偿原理的分析基础上提出了一种宽带数字接收机IQ不平衡估计与自适应补偿算法。首先利用解调数据对IQ不平衡参数进行实时估计,然后利用估计参数对接收信号进行自适应补偿。实验结果表明,所提算法可以有效解决宽带调制解调系统中普遍存在的IQ不平衡问题,提升系统误码性能。     

Modeling and analysis of multiple access channel capacity based on hybrid energy storage and energy harvesting

Energy harvesting (EH) has been considered as a promising technology to solve the constrained energy problem in the devices of IoT with its advantages of flexible deployment and sustainable energy supply.For multiple access channel with energy harvesting,a hybrid energy storage structure model composed by super capacitor and battery was proposed for the devices of IoT.According to the peculiarities of medium access channel and energy harvesting system,an optimized energy allocation strategy with exponential-type decline (ETD) was presented,the upper and lower bounds of the average throughput were deduced,in particular,the gap of two bounds was derived to be a constant.The channel capacity was further obtained by utilizing the relationship between the average throughput and the channel capacity.In the simulations,the effect of harvested energy,storage capacity and the number of nodes on the channel capacity were analyzed respectively.Experiment results show that compared with the conventional wireless node with single battery storage,the proposed hybrid energy storage structure can improve the harvested energy value and increase the multiple access channel capacity by using adaptive modulation scheme when transmitting the signals.     

Temporal information based GoP adaptation for linear video delivery schemes

An original wireless video transmission scheme called SoftCast has been recently proposed to deal with the issues encountered in conventional wireless video broadcasting systems (e.g. cliff effect). In this paper, we evaluate and optimize the performance of the SoftCast scheme according to the transmitted video content. Precisely, an adaptive coding mechanism based on GoP-size adaptation, which takes into account the temporal information fluctuations of the video, is proposed. This extension denoted Adaptive GoP-size mechanism based on Content and Cut detection for SoftCast (AGCC-SoftCast) significantly improves the performance of the SoftCast scheme. It consists in modifying the GoP-size according to the shot changes and the spatio-temporal characteristics of the transmitted video. When hardware capacities, such as buffer or processor performance are limited, an alternative method based only on the shot changes detection (AGCut-SoftCast) is also proposed. Improvements up to 16 dB for the PSNR and up to 0.55 for the SSIM are observed with the proposed solutions at the cut boundaries. In addition, temporal visual quality fluctuations are reduced under 1dB in average, showing the effectiveness of the proposed methods.     

Fabrication of improved flexural strength C/SiC composites via LA-CVI method using optimized spacing of mass transfer channels

The traditional chemical vapor infiltration (CVI) method still faces massive challenge in improving the densification owing to its unavoidable bottleneck effect. Herein, laser assisted-chemical vapor infiltration (LA-CVI) was introduced to fabricate C/SiC composites with mass transfer channels. As a result, the densities of the C/SiC composites were improved due to the dense band formed during the LA-CVI process. Also, with different spacing of mass transfer channels, C/SiC composites exhibited enhanced degree of densification varying from 2.10 to 2.23 g/cm³. When the spacing of channels was 3 mm, the maximum value of flexural strength reached 528 ± 12 MPa. Additionally, micro-CT and finite element analysis were empolyed to investigate dense band and density gradient in detail. The results show that C/SiC composites prepared via LA-CVI method with suitable spacing of channels had improved density and great flexural strength. The proposed method provides a novel route for the preparation of ceramic matrix composites with high density.