Obstructive Sleep Apnea Detection Scheme Based on Manually Generated Features andParallel Heterogeneous Deep Learning Model under IoMT

Obstructive sleep apnea (OSA) syndrome is a common sleep disorder and a key cause of cardiovascular and cerebrovascular diseases that seriously affect the lives and health of people. The development of Internet of Medical Things (IoMT) has enabled the remote diagnosis of OSA. The physiological signals of human sleep are sent to the cloud or medical facilities through Internet of Things, after which diagnostic models are employed for OSA detection. In order to improve the detection accuracy of OSA, in this study, a novel OSA detection system based on manually generated features and utilizing aparallel heterogeneous deep learning model in the context of IoMT is proposed, and the accuracy of the proposed diagnostic model is investigated. The OSA recognition scheme used in our model is based on short-term heart rate variability (HRV) signals extracted from ECG signals. First, the HRV signals and the linear and nonlinear features of HRV are combined into a one-dimensional (1-D) sequence. Simultaneously, a two-dimensional (2-D) HRV time-frequency spectrum image is obtained. The 1-D data sequences and 2-D images are coded in different branches of the proposed deep learning network for OSA diagnosis. To validate the performance of the proposed scheme, the Physionet ApneaECG public database is used. The proposed scheme outperforms the existing methods in terms of accuracy and provides a novel direction for OSA recognition.</p

Friction induced vibration and energy generation study of two-degree-of-freedom piezoelectric coupled system

Friction induced vibration (FIV) and its application for energy generation through two-degree-of-freedom (2-DOF) piezoelectric coupled structure are modelled, described, and studied in this work. The FIV mathematical model of 2-DOF system in the direction of friction is established. A 2-DOF energy generator is designed as a sample structure to transform single direction continuum friction motion to high frequency vibration for energy generation. During the operation of a moving plate compressed and sliding on top of the friction excitation module, varying friction force and contact status (sliding and stick) will lead to the dynamic piezoelectric compression deformation, which can generate continuum electrical power for energy absorbing and harvesting applications. Through numerical simulation and parameter studies, the influences of different stiffness ratios, mass ratios, normal force, velocity, acceleration, structure parameter and friction coefficients on the system power generation are analyzed. Through simple structural design, W level power generation can be obtained with few piezoelectric materials. This work revealed the possibility of transforming low frequency excitation to high frequency vibration of general 2-DOF structure for energy generation.</p

Research on Industrial Software for Equipment Management in Industrial Production Process

当前,自主工业软件已成为中国工业发展的&quot;卡脖子&quot;问题,设备管理软件作为工业软件中不可缺少的典型应用代表,成为国内研究机构及高新技术公司研究创新的重点方向。基于上述背景,本文介绍了一种前后端分离架构的设备智能管理软件,实现对设备基础信息与运行状态的管理,助力企业数字化转型,提高企业设备管理效率,为我国工业软件自主开发的研究与应用工作提供参考案例。</p

On a Nonlinear Non-Autonomous Ratio-Dependent Food Chain Model with Delays and Feedback Controls

该文研究了一类具有时滞和反馈控制的三种群非线性非自治比率依赖的食物链模型.首先,基于时滞微分不等式理论,提出了一些新的分析方法,并构造了一个合适的李亚普诺夫函数.其次,得到了系统正解的持久性和全局吸引性的充分条件.第三,利用理论分析和不动点理论,讨论了相应的周期系统,建立了周期系统正周期解的存在性、唯一性和稳定性的充分条件.另外,给出了一些数值模拟,证明了我们的理论分析是正确的.最后,给出了相应的具有乘法噪声源的随机食物链模型的数值例子,并得到该模型一些新的有趣的解的变化过程.</p

An efficient approach of centroid alignment for spaceflight vehicles considering parameter uncertainties

This paper deals with centroid alignment for the spaceflight vehicles that work on orbit under microgravity environment, due to the unavailability of centroid measurement on ground, which is based on the principle of mass&ndash;radius products in different configurations of static equilibrium. A physical prototype of articulated mechanism for centroid alignment, consisting of three sets of linear modules with moving mass mounted, was developed and experimentally validated. The variational method was adopted to derive the error model for accuracy and sensitivity analysis of the developed articulated mechanism with the consideration of parameter uncertainties, from which it is found that the centroid position of the whole system is much more sensitive to the angular parameter variations than the linear ones. With the developed error model, an iterative approach of centroid alignment to ensure the centroid offset to meet the requirement is proposed, regardless of whether the parameter variations can be ignored, and numerous simulations verify the efficiency of the proposed approach.</p

一种螺旋桨优化设计方法

本发明涉及飞行器领域，具体地说是一种螺旋桨优化设计方法，包括如下步骤，步骤一：以桨叶外形参数为设计变量并建立约束条件，并在变量空间范围内随机生成N个个体构成的种群；步骤二：对桨叶进行空气动力学分析，得到个体的适应度；步骤三：计算种群个体的惯性质量；步骤四：计算每个个体不同方向的受力总和和加速度；步骤五：更新种群位置和速度，并计算新种群个体的适应度；步骤六：终止条件判断，达到最大迭代次数或者最新种群中存在适应度满足要求的个体时，进行步骤七，否则返回步骤三；步骤七：将得到的变量参数作为最终桨叶设计方案。本发明借鉴引力搜索算法并作出改进，解决了其在优化过程中容易陷入局部最优的问题

Learning Cognitive Map Representations for Navigation by Sensory-Motor Integration

How to transform a mixed flow of sensory and motor information into memory state of self-location and to build map representations of the environment are central questions in the navigation research. Studies in neuroscience have shown that place cells in the hippocampus of the rodent brains form dynamic cognitive representations of locations in the environment. We propose a neural-network model called sensory-motor integration network model (SeMINet) to learn cognitive map representations by integrating sensory and motor information while an agent is exploring a virtual environment. This biologically inspired model consists of a deep neural network representing visual features of the environment, a recurrent network of place units encoding spatial information by sensorimotor integration, and a secondary network to decode the locations of the agent from spatial representations. The recurrent connections between the place units sustain an activity bump in the network without the need of sensory inputs, and the asymmetry in the connections propagates the activity bump in the network, forming a dynamic memory state which matches the motion of the agent. A competitive learning process establishes the association between the sensory representations and the memory state of the place units, and is able to correct the cumulative path-integration errors. The simulation results demonstrate that the network forms neural codes that convey location information of the agent independent of its head direction. The decoding network reliably predicts the location even when the movement is subject to noise. The proposed SeMINet thus provides a brain-inspired neural-network model for cognitive map updated by both self-motion cues and visual cues

一种面向大质量大长径比构件的定位工装

本发明涉及定位工装，具体地说是一种面向大质量大长径比构件的定位工装，包括可移动式主体托盘部分、分体式卡箍部分及多个可调节式拉动连杆部分，每个可调节式拉动连杆部分的上端分别与分体式卡箍部分铰接，每个可调节式拉动连杆部分的下端分别铰接于可移动式主体托盘部分，每个可调节式拉动连杆部分的内侧均设有安装于可移动式主体托盘部分上的定位整体座组件。本发明适应产品种类广泛，调节范围广，定位牢固，运动稳定，特点突出，工作可靠

一种用于激光冲击强化吸收层涂覆和去除的装置和工艺

本发明公开了一种用于激光冲击强化吸收层涂覆和去除的装置和工艺，属于激光冲击强化技术领域。该装置包括供胶桶、点胶阀、喷嘴、空气压缩机、三轴位移平台、激光器和激光头；其中：所述激光器通过光纤与激光头连接传输激光；所述空气压缩机通过一根管路与供胶桶连接，通过另一根管路连接点胶阀，所述供胶桶通过管路连接点胶阀，点胶阀和喷嘴连接；空气压缩机提供的压缩空气与供胶桶提供的液体吸收层材料输送到喷嘴中，液体吸收层材料在压缩空气的作用下喷射至工件表面后形成吸收层。本发明与手工粘贴和去除传统激光冲击强化吸收层黑胶带或铝箔相比自动化程度更高，涂覆和去除效率更高，更适用于实际工程中

用于空间站载荷在轨维修的机械臂

本实用新型涉及载人航天空间站科学实验操作设备，特别涉及一种用于空间站载荷在轨维修的机械臂。包括维修箱及倒挂于维修箱内的载荷维修机械臂；载荷维修机械臂具有七自由度，且执行末端设有快锁机构和相机模块，其中快锁机构用于连接维修工具，相机模块用于采集待维修载荷的图像信息。本实用新型能实现尺寸、重量与能耗的最小化设计，满足在空间站上进行载荷维修的功能要求，自主或辅助航天员完成载荷在轨就位维修