Experience-Based Cognition for Driving Behavioral Fingerprint Extraction

Abstract

With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and safer car controls. In this paper, we propose a novel approach to extract the driver’s driving behavioral fingerprints based on our conceptual framework Experience-Oriented Intelligent Things (EOIT). EOIT is a learning system that has the potential to enable Internet of Cognitive Things (IoCT) where knowledge can be extracted from experience, stored, evolved, shared, and reused aiming for cognition and thus intelligent functionality of things. By catching driving data, this approach helps cars to collect the driver’s pedal and steering operations and store them as experience; eventually, it uses obtained experience for the driver’s driving behavioral fingerprint extraction. The initial experimental implementation is presented in the paper to demonstrate our idea, and the test results show that it outperforms the Deep Learning approaches (i.e., deep fully connected neural networks and recurrent neural networks/Long Short-Term Memory networks).     

基于差动共焦显微技术的微区拉曼光学系统构建与实验研究

研制了一种基于差动共焦显微技术的微区拉曼光学系统装置,对无机样品进行微区拉曼光谱探测。传统显微共焦拉曼光谱技术没有强调系统的定焦能力,而所研制的光学系统装置利用差动共焦曲线过零点与焦点位置精确对应的特性,采用反馈控制技术,具有长时间定焦功能。在微区拉曼散射信号收集时,采用多模光纤空间耦合技术,以光纤代替传统物理探测针孔,提高了环境抗干扰能力,优化了系统结构和装调性能。实验结果表明:该装置具有较高稳定性,可有效探测单壁碳纳米管在1581.510 cm^-1,2708.065 cm^-1特征峰处的拉曼频移及纯物质硫在153.113 cm^-1,219.917 cm^-1,473.322 cm^-1特征峰处的拉曼频移并且实现碳管的单线检测,满足了光谱探测系统装置设计需求。     

基于自回归谱外推的全聚焦成像分辨力提升

针对相邻缺陷全聚焦超声成像混叠问题，结合低阶、宽有效频带自回归谱外推方法，压缩超声波时域脉冲宽度，实现亚波长级全聚焦（Total focusing method，TFM）成像分辨力。建立碳钢试块模型，设置两个中心间距1.8 mm，直径1.3 mm圆孔，选用中心频率2.25 MHz，32阵元相控阵探头采集全矩阵数据。针对全矩阵数据，选择自回归阶数为2，信号频谱最大幅值下降14 dB为有效频带，建立自回归模型并外推有效频带外的高频与低频成分，随后对全矩阵数据进行延迟叠加处理和TFM成像。仿真结果表明，低阶、宽有效频带自回归谱外推处理方法具有较高的鲁棒性和准确性，TFM成像后可有效分离中心间距0.7λ（λ为超声波长）圆孔，保留缺陷横向位置信息的同时，定位误差不超过0.73%。对碳钢试块中相同位置及尺寸的圆孔进行试验验证，定位误差不超过1.06%，有效地提高TFM成像分辨力。     

Hybrid fully convolutional networks-based skin lesion segmentation and melanoma detection using deep feature

Fully convolutional networks (FCNs) take the input of arbitrary size and produce correspondingly sized output with efficient inference and learning. The automatic diagnosis of melanoma is very essential for reducing the mortality rate by identifying the disease in earlier stages. A two-stage framework is used for implementing the melanoma detection, segmentation of skin lesion, and identification of melanoma lesions. Two FCNs based on VGG-16 and GoogLeNet are incorporated for improving the segmentation accuracy. A hybrid framework is used for incorporating these two FCNs. The classification is done by extracting the feature from segmented lesion by using deep residual network and a hand-crafted feature. Classification is done by support vector machine. The performance analysis of our framework gives a promising accuracy, that is, 0.8892 for classification in ISBI 2016 dataset and 0.853 for ISIC 2017 dataset.     

雷达发射机浮动板调制器与故障检测电路的设计

提出了一种改进的浮动板调制器和对正负偏电压的故障检测电路,利用MOSFET寄生电容特性,通过固定脉宽窄脉冲控制调制脉宽,通过增加负偏MOSFET提高输出负偏电压。对故障检测电路进行仿真实验,通过模拟故障,验证故障检测报警信号发生时间均在微秒级别。完成样机的搭建,利用多重方式解决高压绝缘问题,并对其加电进行试验验证,分析实验波形,证明此电路满足设计要求并且具有可行性。     

Emerging functional nanomaterials for the detection of food contaminants

Along with the progress in nanoscience, a variety of advanced functional nanomaterials were constructed to develop effective and innovative analytical techniques for food safety surveillance. In this review, we summarized the advanced analytical methods that have been developed based upon advanced functional nanomaterials, including plasmonic nanomaterial-based colorimetric methods, fluorescent nanomaterial-based fluorescent methods, advanced functional material-based molecular imprinting technology, advanced functional material-based chromatographic methods, plasmonic nanomaterial-based surface enhanced Raman scattering technology, and advanced functional material-based electrochemical methods. This review provides a progressive roadmap for further development of portable, rapid, and in situ detection technology to promote food safety surveillance from bench to market and eventually reduce the gap between research in the laboratory and industrial applications.     

A Colorimetric Artificial Olfactory System for Airborne Improvised Explosive Identification

The detection of ultralow or nonvolatile target analytes remains a significant challenge for artificial olfactory systems even after decades of development, which severely limits their widespread application. To overcome this challenge, an artificial olfactory system based on a colorimetric hydrogel array is constructed for the first time as a universal representative. As an effective extension of conventional artificial olfactory systems that integrates the merits of its predecessors, the proposed system accurately mimics olfactory mucosa and specific odorant binding proteins using hydrogels endowed with specific colorimetric reagents for the detection of hypochlorite, chlorate, perchlorate, urea, and nitrate. Therefore, the proposed system is capable of detecting and discriminating between these five airborne improvised explosive microparticulates with a detection limit as low as 39.4 pg. Additionally, the system demonstrates good reusability over ten cycles, rapid response time of ≈0.2 s, and excellent discrimination properties, despite significant variation. This proof-of-concept study on colorimetric artificial olfactory systems yields a novel strategy for the direct and discriminative detection of nonvolatile airborne microparticulates.     

煤矿薄煤层定向钻孔水害探查技术研究

从保德煤矿水文地质条件出发，研究了矿区奥灰水突水危险性，计算了8号煤层底板安全隔水层厚度和突水系数。采用薄煤层定向钻探工艺对保德煤矿81312工作面胶带运输巷道和81313工作面辅助运输巷道底板以下岩层及10号煤层进行水害及隐伏构造探查，探明了8号煤层底板岩层地质构造及富水性，形成了区域薄煤层定向钻孔水害探查方法。研究表明，利用定向钻孔的一孔多用功能超前预抽10号煤层瓦斯，可为矿区安全开采提供保障。     

Metallic Nanoparticle-Enabled Sensing of a Drug-of-Abuse: An Attempt at Forensic Application

γ-Hydroxybutyric acid (GHB) functions as a depressant on the central nerve system and serves as a pharmaceutical agent in the treatment of narcolepsy and alcohol withdraw. In recent years, GHB has been misused as a recreational drug due to its ability to induce euphoric feelings. Moreover, it has gained increasing attention as a popular drug of abuse that is frequently related to drug-facilitated sexual assaults. At the moment, detection methods based on chromatography exhibit extraordinary sensitivity for GHB sensing. However, such techniques require complicated sample treatment prior to analysis. Optical sensors provide an alternative approach for rapid and simple analysis of GHB samples. Unfortunately, currently reported probes are mostly based on hydrogen bonding to recognize GHB, and this raises concerns about, for example, the lack of specificity. In this work, we report a bioinspired strategy for selective sensing of GHB. The method is based on specific enzyme recognition to allow highly selective detection of GHB with minimum interference, even in a complex sample matrix (e. g., simulated urine). In addition, the result can be obtained by either quantitative spectroscopy analysis or colorimetric change observed by the naked-eye, thus demonstrating its potential application in drug screening and forensic analysis.