High-fidelity Recognition of Organotrifluoroborate Anions (R−BF3−) as Designer Guest Molecules

The recognition of boron compounds is well developed as boronic acids but untapped as organotrifluoroborate anions (R−BF₃⁻). We are exploring the development of these and other designer anions as anion-recognition motifs by considering them as substituted versions of the parent inorganic ion. To this end, we demonstrate strong and reliable binding of organic trifluoroborates, R−BF₃⁻, by cyanostar macrocycles that are size-complementary to the inorganic BF₄⁻ progenitors. We find that recognition is modulated by the substituent's sterics and that the affinities are retained using the common K⁺ salts of R−BF₃⁻ anions.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

A DNA Switch for Detecting Single Nucleotide Polymorphism within a Long DNA Sequence Under Denaturing Conditions

DNA detection is usually conducted under nondenaturing conditions to favor the formation of Watson–Crick base-paring interactions. However, although such a setting is excellent for distinguishing a single-nucleotide polymorphism (SNP) within short DNA sequences (15–25 nucleotides), it does not offer a good solution to SNP detection within much longer sequences. Here we report on a new detection method capable of detecting SNP in a DNA sequence containing 35–90 nucleotides. This is achieved through incorporating into the recognition DNA sequence a previously discovered DNA molecule that forms a stable G-quadruplex in the presence of 7 molar urea, a known condition for denaturing DNA structures. The systems are configured to produce both colorimetric and fluorescent signals upon target binding.     

指纹考勤管理软件的研究与实现

针对企、事业单位原有的考勤系统，如打卡钟、磁卡、IC卡等考勤方式存在代打卡、卡丢失等不足和缺陷的实际，结合指纹识别技术，建立一套考勤、薪资、人事管理于一体的软件系统。给出了系统的体系结构和功能实现，能使企业考勤管理更加简便快捷、客观公正。并提出了进一步的发展方向和展望。     

一种高性能的新结构IGBT

提出了一种低功率损耗的新结构IGBT.该新结构的创新点在于其复合耐压层结构,该耐压层包括深扩散形成的n型缓冲层和硼注入形成的透明背发射区两部分.虽然在正常工作条件下,该新结构IGBT工作于穿通状态,但器件仍具有非穿通IGBT(NPT-IGBT)的优良特性.该新结构IGBT具有比NPT-IGBT更薄的芯片厚度,从而可以获得更好的通态压降和关断功耗之间的折衷.实验结果表明:与NPT-IGBT相比较,新结构IGBT的功率损耗降低了40%.     

人工神经网络理论及其应用

简要介绍了人工神经网络的发展过程和基本理论，从神经网络具有自学习功能、联想存储功能和高速寻找优化解的能力三个方面论述了其特点和优越性，详细阐述了在模式识别、信号处理、自动控制、人工智能、自适应的人机接口、优化计算、通信以及其它方面的应用，探讨和分析了其发展前景。     

灰色信息及其运算研究

本文提出了全真信息、信息的亲善性等概念,讨论了信息的有关性质及运算的关系,得到了信息的运算与普通集合运算之间存在着差异的结论,说明了引起该差异的原因.同时,以认知模式为基础,定义了信息函数,并得到了有关的命题及运算.     

Real time estimation of CO2 laser weld quality for automotive industry

Laser welding is one of the most precise welding processes in joining sheet metals. In laser welding, performing real time evaluation of the welding quality is very important to enhance the efficiency of the welding process. In this study, the plasma and spatter, which are generated during laser welding, are measured using UV and IR photodiodes. The factors that influence weld quality are classified into five categories; optimal heat input, slightly low heat input, low heat input, partial joining due to gap mismatch, and nozzle deviation. The data number deviated from reference signals and their standard deviations were also considered to evaluate the qualities. A system was also formulated to perform real time evaluations of the weld quality using a fuzzy multi-feature pattern recognition with the measured signals.     

数字散斑干涉技术及应用

介绍了数字散斑干涉技术在位移、应变、振动和医学诊断等领域中的应用和国内外发展状况。提出了一种新的应用领域—数字散斑干涉技术在语音识别中的应用,并对该方法作了介绍,讨论了它的特点。