石英管增强拉曼光纤探头粉末样品探测

拉曼光谱技术以其多组分同时探测、分子指纹特性等优点被广泛应用于多个领域,但其较低探测灵敏度严重限制了此技术的进一步发展。为了提高拉曼光谱技术粉末样品原位分析能力,提出了一种基于石英管增强的高灵敏度拉曼光纤探头。探头采取内镀金属空芯光纤用于光信号的传输,有效减小了背景信号对拉曼光谱的影响;探头底端采用石英管设计,增大采样体积和收集效率,提高了拉曼光谱的探测灵敏度。理论分析了石英管拉曼光谱技术可提高粉末样品的探测灵敏度,详细介绍了探头的设计和实现,进一步评估探头的性能,结果表明:相较于球透镜拉曼探头,拉曼信号强度（NaHCO₃）增强2.92倍。为模拟实际应用场景,采用光纤拉曼探头成功获得了容器中不同深度粉末样品（Na₂SO₄和NaHCO₃）的拉曼光谱信息。文中设计的石英管增强拉曼探头具有外径尺寸小（外径仅为2 mm）、灵敏度高等优点,可对深层次粉末样品进行探测,为现场粉末样品原位分析提供了一种新途径。     

An efficient inverse scattering algorithm for the design ofnonuniform fiber Bragg gratings

Presents an efficient method for the design of complex fiber Bragg gratings. The method relies on the synthesis of the impulse response of the grating by means of a differential layer-peeling algorithm. The algorithm developed takes into account all the multiple reflections inside the grating, giving an exact solution to the inverse scattering problem. Its low algorithmic complexity enables the synthesis of long fiber gratings. The method is illustrated by designing several filters with interest for optical fiber communication systems: dispersionless bandpass filters and second- and third order dispersion compensators     

近红外光谱光纤探头的创新设计用于骨关节炎的原位检测

创新设计了一款操作灵活、方便、适于生物医学原位检测的反射式近红外（NIR）光纤探头,通过将自聚焦透镜耦合到NIR光纤探头的顶端,并对探头结构、光纤排布进行全新设计,使光纤探头具有更高的测量精度和收集效率。通过耦合傅里叶变换近红外光谱仪对蔗糖样本进行NIR光谱采集,发现该反射式NIR光纤探头具有高效便捷的特点以及较高的光谱重复性和信噪比。采用该光纤探头对犬膝关节股骨端关节软骨进行NIR光谱离体原位检测,这些光谱数据经一阶导数2次多项式21点Savitzky-Golay平滑预处理后再进行主成分分析和Fisher判别分析。模型初始案例和交互验证案例正确识别率分别为97.62%、90.47%,样本预测集的识别率达96.43%,证明了采用该NIR光纤探头进行NIR光谱原位检测的有效性及骨关节炎识别的可行性,可为骨关节炎的临床诊断奠定实验基础。     

An efficient local search heuristics for asynchronous multiuser detection

This letter considers the application of k-opt local search to the detection of data transmitted through the additive white Gaussian noise channel by K asynchronous users using direct-sequence code-division multiple access. The algorithm is based on a general approach to heuristics that is highly efficient in solving large combinatorial optimization problems. It is shown that the algorithm manages to produce optimum solutions with high frequency, in running time that grows about O(n/sup 2/).     

一种用于光纤周界安防系统的端点检测方法

为了提高光纤周界安防系统中扰动信号端点检测的 性能,提出一种新型端点检测方法。首先通过计算信号 的短时能量和过零率分布分别找出信号中短时能量比和过零率满足一定门限的信号点,通过 对这两信号点 进行一定的加权确定扰动信号的端点位置。与离散小波提取起始点信号相比,本文方法由于 综合了短时能量 和过零率法的优势,能够适应更多的扰动事件类型,通过加权极大提高了端点检测的精度 ,并且运算时 间大幅降低,提高了系统的实时性。实验结果表明,本文算法在10M Hz的采样速度和采集0. 3s数据情况下,93.47%的数据定位误差低于10m,计算时间少于0.3s。     

受纳米结构损伤限制的光纤拉曼探头SERS探测灵敏度

利用光线追迹法,研究了典型光纤拉曼探头在纳米结构损伤限制下收集到的SERS功率与样品位置之间关系,结果表明,对于不同焦距构成的同轴等光程光纤拉曼探头,在给定的纳米结构损伤阈值激发光功率密度下,样品偏离焦平面反而会使探头收集到的SERS功率增加,相比于样品远离探头方向偏离焦平面,靠近探头方向偏离焦平面时收集到的SERS功率更高。此外,收集光纤芯径越大,探头所收集的SERS功率越大。     

An efficient system for anomaly detection using deep learning classifier

In this paper, a deep learning-based anomaly detection (DLAD) system is proposed to improve the recognition problem in video processing. Our system achieves complete detection of abnormal events by involving the following significant proposed modules a Background Estimation (BE) Module, an Object Segmentation (OS) Module, a Feature Extraction (FE) Module, and an Activity Recognition (AR) Module. At first, we have presented a BE (Background Estimation) module that generated an accurate background in which two-phase model is generated to compute the background estimation. After a high-quality background is generated, the OS model is developed to extract the object from videos, and then, object tracking process is used to track the object through the overlapping detection scheme. From the tracked objects, the FE module is extracted for some useful features such as shape, wavelet, and histogram to the abnormal event detection. For the final step, the proposed AR module is classified as abnormal or normal event using the deep learning classifier. Experiments are performed on the USCD benchmark dataset of abnormal activities, and comparisons with the state-of-the-art methods validate the advantages of our algorithm. We can see that the proposed activity recognition system has outperformed by achieving better EER of 0.75 % when compared with the existing systems (20 %). Also, it shows that the proposed method achieves 85 % precision rate in the frame-level performance.     

An efficient approximate maximum likelihood signal detection for MIMO systems

This paper proposes an efficient approximate Maximum Likelihood （ML） detection method for Multiple-Input Multiple-Output （MIMO） systems, which searches local area instead of exhaustive search and Selects valid search points in each transmit antenna signal constellation instead of all hyperplane. Both of the selection and search complexity can be reduced significantly. The method performs the tradeoff between computational complexity and system performance by adjusting the neighborhood size to select the valid search points. Simulation results show that the performance is comparable to that of the ML detection while the complexity is only as the small fraction of ML.     

An optical fiber probe based on multi-optical well particle capture

In this paper, a new method of constructing single-fiber optical tweezers is proposed, which can achieve multi-optical well non-contact capture on the same optical fiber, so as to reduce the difficulty of making single-fiber optical tweezers and enhance the operation function of single-fiber optical tweezers. We use the 650 nm laser source to excite high purity LP11 mode in 980 nm single-mode fiber, which can achieve the multi-optical trap capture effect around the fiber port after simple micro-staggered core fusion treatment for common single-core fiber. Optical fiber ports are fabricated using thermal method to construct special tip structures. Simulation and experimental results show the feasibility of the structure. The excitation and utilization of multi-mode beams in single fiber constitute a new development of single fiber optical trap, enrich the function of single fiber optical tweezers, and make more practical applications in biomedical research possible.     

基于量子点荧光淬灭技术的痕量Cu2+检测传感器研究

本文设计了一种可用于现场检测的痕量Cu2+传感器,运用自行研制的光学感知与信号处理模块实现痕量Cu2+的快速检测,达到了检测仪器的低成本、小型化的目的.实验结果表明,在Cu2+浓度50-1000nmol/L范围内传感器检测结果具有较好的线性关系,拟合后的直线方程为Y=0.11869* X+ 14.47268,线性度为0.99358,标准方差为4.63099,传感器响应时间为50秒,检测的可重复性较好,该传感器可以满足痕量Cu2+现场检测的需求.     

紫外激光增强电离光谱方法进行火焰中痕量元素的灵敏检测

一、实验装置激光增强电离光谱的实验装置由紫外可调谐激光光源、原子化器和信号处理与检测系统等三部分组成. 激光光源是用 Quanta Ray脉冲调 QYAG倍频激光器泵浦的可调谐染料激光器,用KDP晶体倍频,采用角度位相匹配,自动跟踪调谐.脉冲重复率为10次加/s,脉宽为5ns,调谐扫描速度为0.02urn/S,线宽小于0.4Ccm~(-1)单次脉冲能量为1mJ/脉冲.激光应有恰当的强度,使原子达到饱和激发程度,以消     

An efficient blind multiuser detection for improper DS/CDMA signals

This paper proposes a new linear blind multiuser detection based on widely linear (WL) signal processing. The received signal and its complex conjugate are separately filtered and the results are linearly combined. The WL maximum/minimum (max/min) mean-output-energy (MOE) receiver is derived by applying the modified cost function. It is shown that a performance gain can be attained for the improper direct-sequence code division multiple access (DS/CDMA) signal, due to the additional information contained in pseudocovariance matrix of observations. The adaptive implementation with acceptable complexity is also developed. Computer-simulation results show that a significant performance gain is obtained over the other classical methods.     

Design optimization for efficient erbium-doped fiber amplifiers

The gain and pumping efficiency of aluminosilicate erbium-doped fiber amplifiers (EDFAs) are analyzed as a function of guiding parameters and Er-doping profile for two pump wavelengths of λ _p=980 nm and λ_p=1.47 μm. Three designs of fiber-amplifier waveguides are considered: one with the same mode size as standard 1.5-μm communication fibers (type 1); one with the same mode size as standard 1.5-μm dispersion-shifted fibers (type 2); and one with mode size smaller than those of communication fibers (type 3). For the 1.47-μm pump, fundamental LP₀₁ mode excitation is assumed, while for the λ_p=980-nm pump, concurrent excitation of LP₁₁ modes is considered. It is shown that excitation of higher-order pump modes at 980 nm does not significantly affect the amplifier gain performance. The effect of concentrating the Er³⁺ doping near the center of the fiber core is shown to increase the amplifier gain coefficients by a factor of 1.5 to 2     

An efficient approach for the detection of link failures in WBAN system for health care applications

Wireless body area network (WBAN) plays an important role in patient health care. The performance of this WBAN system is affected by link failures due to the presence of malicious sensor nodes. Hence, the detection and mitigation of this link failure is important for improving the efficiency of the WBAN system. This paper proposes a methodology for link failure detection using weight metric approach. The performance of the proposed methodology is analyzed in terms of packet delivery ratio (PDR), link failure detection latency, and link failure detection rate.     

An efficient detection technique for synchronous CDMA communicationsystems based on the expectation maximization algorithm

Maximum likelihood detection of superimposed signals in code-division multiple access (CDMA) communication systems has a computational complexity that is exponential in the number of users, and its implementation is practically prohibitive even for a moderate number of users. Applying the expectation maximization algorithm to this problem, we decompose the multiuser detection problem into a series of single-user problems, and thus present an iterative computationally efficient algorithm for detection of superimposed signals in synchronous direct-sequence CDMA communication systems. The resulting structure includes the well-known multistage detector as one of its special cases. With a proper choice of its parameters, the new detector can achieve the advantages of both the multistage and conventional detector and have good performance for both strong and weak users     

An improved and efficient detection scheme for V-BLAST systems with QAM modulation

The paper proposed an improved Ordered Successive Interference Cancellation （OSIC） detection scheme for V-BLAST systems with square/rectangular Quadrature Amplitude Modulation （QAM） modulation. It utilizes an equivalent real-valued vector expression of relationship between transmit signals and received signals, exploits the constellation＇s product-form structure and can eventually make the order, in which components of the transmit signals vector are extracted, more ＂optimal＂ in some sense. Thereby, it can offer an improved error probability as compared to the conventional OSIC detection scheme. In addition, the paper also proposes an efficient projection algorithm to calculate nulling vectors in a simple recursive fashion in order to avoid the vast increase of complexity, which is due to the fact that the original complex N- dimensional data vector and M × N channel matrix are transformed into a real 2N- dimensional data vector and a real 2M × 2N channel matrix respectively. A scrutinous complexity analysis shows that the complexity increases by only 33% as compared to the conventional scheme.     

An efficient two-step approach to integer frequency offset detection for OFDM systems

An efficient preamble structure for OFDM systems is proposed which inserts a short embedded repetition pattern (SERP) into conventional preamble structures allowing a two-step detection of the integer frequency offset (IFO). A coarse estimate of the IFO using the SERP is performed in the time domain prior to performing fine IFO detection in the frequency domain based on the original preamble structure. The complexity of the overall IFO detection procedure can be significantly reduced at a price of slight loss in SNR.     

An efficient forgery detection algorithm for object removal by exemplar-based image inpainting

As a popular image manipulation technique, object removal can be achieved by image-inpainting without any noticeable traces, which poses huge challenges to passive image forensics. The existing detection approach utilizes full search for block matching, resulting in high computational complexity. This paper presents an efficient forgery detection algorithm for object removal by exemplar-based inpainting, which integrates central pixel mapping (CPM), greatest zero-connectivity component labeling (GZCL) and fragment splicing detection (FSD). CPM speeds up suspicious block search by efficiently matching those blocks with similar hash values and then finding the suspicious pairs. To improve the detection precision, GZCL is used to mark the tampered pixels in suspected block pairs. FSD is adopted to distinguish and locate tampered regions from its best-match regions. Experimental results show that the proposed algorithm can reduce up to 90% of the processing time and maintain a detection precision above 85% under different kinds of object-removed images.     

An efficient approach for outlier detection in big sensor data of health care

In recent years, wireless sensor networks are pervasive and are generating tons of data every second. Performing outlier detection to detect faulty sensors from such a large amount of data becomes a challenging task. Most of the existing techniques for outlier detection in wireless sensor networks concentrate only on contents of the data source without considering correlation among different data attributes. Moreover, these methods are not scalable to big data. To address these 2 limitations, this paper proposes an outlier detection approach based on correlation and dynamic SMO (sequential minimal optimization) regression that is scalable to big data. Initially, correlation is used to find out strongly correlated attributes and then the point anomalous nodes are detected using dynamic SMO regression. For fast processing of big data, Hadoop MapReduce framework is used. The experimental analysis demonstrates that the proposed approach efficiently detects the point and contextual anomalies and reduces the number of false alarms. For experiments, real data of sensors used in body sensor networks are taken from Physionet database.