基于近红外特征波长提取与最小二乘支持向量机的白芷掺滑石粉定量研究

中药掺假不仅降低疗效而且严重危害身体健康, 本文利用近红外光谱分析技术对中药白芷中掺入滑石粉的含量进 行定量分析。仪器采用自主研制的近红外光谱仪,光谱范围为900～ 1700 nm,分辨率为4nm,采集181份白芷中掺 入了 滑石粉的样本光谱以及7份白芷中掺入了滑石粉和面粉的样本光谱,进行平滑和一阶求导预 处理的基础上,比较研究了 多种不同算法的建模效果,提出了采用移动窗口法(MW)结合遗传算法(GA)进行特征波长 优选,以最小二乘支持向 量机(LS-SVM)建立定量模型的分析方法,结果表明MW-GA能有效筛选波长,提高预测精 度,还用白芷中同时掺入了 滑石粉和面粉的多成分样本对模型进行了验证。MW-GA-LS-SVM与全光谱-PLS、MW-GA- PLS、全光谱-LS-SVM比较, 其性能最佳,在极大减少建模变量的同时,模型的验证集决定系数R²=0.995,校正均方根误差RMSEC= 0.42%,预测均 方根误差RMSEP=0.48%,表明MW-GA-LS -SVM建立的模型准确度高,为近红外光谱在中药成分快速定量分析应用提供了方法依据。     

基于统计的灰度视频自适应背景建模算法

针对灰度视频的目标检测依赖先验知识、召回率低以及单一算法无法同时兼顾静态与动态背景等问题,提出一种基于统计的背景建模算法。该算法无需先验知识,根据统计信息可以准确区分静态背景和动态背景,并采取不同的检测策略提取目标。对于静态背景,采用改进的三帧差分法自适应设置阈值,可以保证较高的召回率。对于动态背景,采用改进的概率密度估计法可以有效降低虚警率。采用所提算法对光照变化以及阴影进行处理,可以进一步提升算法的性能。在公开数据集与实际采集红外数据进行验证实验。实验结果表明,所提算法在多种场景中处理灰度视频的结果比其他传统算法好,在保证准确率的同时可以极大地提升召回率,并且有效提高目标的完整性。     

Supervised learning and frequency domain averaging-based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.     

Random forest classifier‐based safe and reliable routing for opportunistic IoT networks

Designing a safe and reliable way for communicating the messages among the devices and humans forming the Opportunistic Internet of Things network (OppIoT) has been a challenge since the broadcast mode of message sharing is used. To contribute toward addressing such challenge, this paper proposes a Random Forest Classifier (RFC)‐based safe and reliable routing protocol for OppIoT (called RFCSec) which ensures space efficiency, hash‐based message integrity, and high packet delivery, simultaneously protecting the network against safety threats viz. packet collusion, hypernova, supernova, and wormhole attacks. The proposed RFCSec scheme is composed of two phases. In the first one, the RFC is trained on real data trace, and based on the output of this training, the second phase consists in classifying the encountered nodes of a given node as belonging to one of the output classes of nodes based on their past behavior in the network. This helps in proactively isolating the malicious nodes from participating in the routing process and encourages the participation of the ones with good message forwarding behavior, low packet dropping rate, high buffer availability, and a higher probability of delivering the messages in the past. Simulation results using the ONE simulator show that the proposed RFCSec secure routing scheme is superior to the MLProph, RLProph, and CAML routing protocols, chosen as benchmarks, in terms of legitimate packet delivery, probability of message delivery, count of dropped messages, and latency in packet delivery. The out‐of‐bag error obtained is also minimal     

Tailored and Highly Stretchable Sensor Prepared by Crosslinking an Enhanced 3D Printed UV-Curable Sacrificial Mold

Taking advantage of unlimited geometry design, 3D printed sacrificial mold cast with highly conductive polymer composites is used to prepare a sensor with designed structures. However, the disposal of the mold in a mild condition while the refined structures can be maintained is still a challenge. Herein, a bifunctional monomer hydrolyzable hindered urea acrylate is synthesized to create a cross-linked polymer network, preventing the dissolution of printed parts in the uncured resin. 3D printed scaffolds can be hydrolyzed in hot water, which provides an attractive option for sacrificial molds. Also, a porous flexible strain sensor (PFSS) is fabricated by casting polyurethane/carbon nanotubes composites into the sacrificial molds, which demonstrates a high stretchability (≈510%) and an excellent recoverability. Meantime, the pressure sensitivity (0.111 kPa⁻¹) and a long-term electrical resistance of PFSS is characterized. The resistance response signal remains nearly unchanged after 100 compressive loading cycles at a large strain of 60%. Benefiting from the design freedom of 3D printing, a practical application of the PFSS with a complex and customized structure to monitor human motion is demonstrated. These results prove that the sacrificial molding process has great potential for user-specific stretchable wearable devices.     

Nanowire-Based Soft Wearable Human–Machine Interfaces for Future Virtual and Augmented Reality Applications

A virtual world has now become a reality as augmented reality (AR) and virtual reality (VR) technology become commercially available. Similar to how humans interact with the physical world, AR and VR systems rely on human–machine interface (HMI) sensors to interact with the virtual world. Currently, this is achieved via state of-the-art wearable visual and auditory tools that are rigid, bulky, and burdensome, thereby causing discomfort during practical application. To this end, a skin sensory interface has the potential to serve as the next-generation AR/VR technology because skin-like wearable sensors have advantages in that they can be ultrathin, ultra-soft, conformal, and imperceptible, which provides the ultimate comfort and immersive experience for users. In this progress report, nanowire-based soft wearable HMI sensors including acoustic, strain, pressure sensors, and physiological sensors are reviewed that may be adopted as skin sensory inputs in future AR/VR systems. Further, nanowire-based soft contact lenses, haptic force, and thermal and vibration actuators are covered as potential means of feedback for future AR/VR systems. Considering the possible effects of the virtual world on human health, skin-like wearable artery pulses, glucose, and lactate sensors are also described, which may enable imperceptible health monitoring during future AR/VR practices.     

Wearable Sensors-Enabled Human–Machine Interaction Systems: From Design to Application

In comparison to traditional bulky and rigid electronic devices, the human–machine interaction (HMI) system with flexible and wearable components is an inevitable future trend. To achieve effective, intuitive, and seamless manipulation of high-performance wearable HMI systems, it is important to develop effective strategies for designing material microstructures on flexible sensors and electric devices with excellent mechanical flexibility and stretchability. The real-time acquisition of human physiology and surrounding signals through accurate and flexible sensors is the basis of wearable HMIs. Herein, the construction of a wearable HMI system that utilizes sensors, communication modes, and actuators is reviewed. The mechanisms and strategies for designing various flexible sensors based on different mechanisms are analyzed and discussed. The functional mechanism, material selection, and novel design strategies of each part are summarized in detail. The different communication modes in interactive systems and the manufacturing technology of soft machines are also introduced. Additionally, the most advanced applications of wearable HMI systems in intelligent identification and security, interactive controls for robots, augmented reality, and virtual reality have been highlighted. The review concludes with an overview of the remaining key challenges and several ideas regarding the further improvement of wearable HMI systems.     

Thermoplastic Photoheating Polymer Enables 3D-Printed Self-Healing Light-Propelled Smart Devices

Swimming devices have shown great potential in various fields. Future swimming devices are expected to be capable of facile fabrication, smart on-demand transportation, and self-healing. Here, a swimming device is developed with the aforementioned features based on a newly designed photoheating thermoplastic poly(sebacoyl diglyceride-co-4,4′-azodibenzoyl diglyceride) (PSeDA). PSeDA). PSeDA can be instantly heated by ultraviolet light to modulate its spatiotemporal viscoelasticity. Accordingly, a series of swimming devices are customized via single integrated 3D printing. The micrometer-scale grid structure enables versatile multimode motion and generates a higher propulsive force than that of typical molded analogs based on the photoheat-induced Marangoni effect. The device exhibits smart transportation capabilities, including capture, conveyance, and release, and is also the first of its kind to achieve self-healing. This work provides a design principle for swimming devices in which the key is photoheating thermoplastics. This design principle of material is further demonstrated by synthesizing photoheating thermoplastics responsive to visible and near infrared light and will inspire an exciting field of thermoplastics.     

Ice-Templated,Large-Area Silver Nanowire Pattern for Flexible Transparent Electrode

Flexible transparent electrodes are critically important for the emerging flexible and stretchable electronic and optoelectronic devices. To this end, transparent polymer films coated with silver nanowires (AgNWs) have been intensively studied in the past decade. However, it remains a grand challenge to achieve both high conductivity and transmittance in large-area films, mainly due to the poor alignment of AgNWs and their high junction resistance. Here, the successful attempt to realize large-area AgNW patterns on various substrates by a 2D ice-templating approach is reported. With a relatively low dosage of AgNWs (4 µg·cm⁻²), the resulted flexible electrode simultaneously achieves high optical transmittance (≈91%) and low sheet resistance (20 Ω·sq⁻¹). In addition, the electrode exhibits excellent durability during cyclic bending (≈10 000 times) and stretching (50% strain). The potential applications of the flexible transparent electrode in both touch screen and electronic skin sensor, which can monitor the sliding pressure and direction in real-time, are demonstrated. More importantly, it is believed that the study represents a facile and low-cost approach to assemble various nanomaterials into large-area functional patterns for advanced flexible devices.     

Laser-Empowered Random Metasurfaces for White Light Printed Image Multiplexing

Printed image multiplexing based on the design of metasurfaces has attracted much interest in the past decade. Optical switching between different images displayed directly on the metasurface is performed by altering the parameters of the incident light such as polarization, wavelength, or incidence angle. When using white light, only two-image multiplexing is implemented with polarization switching. Such metasurfaces are made of nanostructures perfectly controlled individually, which provide high-resolution pixels but small images and involve long fabrication processes. Here, it is demonstrated that laser processing of nanocomposites offers a versatile low-cost, high-speed method with large area processing capabilities for controlling the statistical properties of random metasurfaces, allowing up to three-image multiplexing under white light illumination. By independently controlling absorption and interference effects, colors in reflection and transmission can be varied independently yielding two-image multiplexing under white light. Using anisotropy of plasmonic nanoparticles, a third image can be multiplexed and revealed through polarization changes. The design strategy, the fundamental properties, and the versatility of implementation of these laser-empowered random metasurfaces are discussed. The technique, applied on flexible substrate, can find applications in information encryption or functional switchable optical devices, and offers many advantages for visual security and anticounterfeiting.