Photophysical investigation of the formation of defect levels in P doped ZnO thin films

Zinc oxide (ZnO) offers a major disadvantage of asymmetry doping in terms of reliability, stability, and reproducibility of p-type doping, which is the main hindrance in realization of optoelectronic devices. The problem is even more complicated due to formation of various native defects in unintentionally doped n-type ZnO. The realization of p-type conductivity in doped ZnO requires an in-depth understanding of the formation of an effective shallow acceptor, as well as donor-acceptor compensation. Photophysical properties such as photoconductivity along with photoluminescence (PL) studies have unprecedentedly and effectively been utilized in this work to monitor the evolution of various in-gap defects. Phosphorus (P) doped ZnO thin films have been grown by RF magnetron sputtering under various Ar to O₂ gas ratios to investigate the effect of O₂ on the donor-acceptor compensation by comprehensive photoconductivity measurements supported by the PL studies. Initial elemental analyses indicate presence of abundant zinc vacancies (V_Zn) in O-rich ambience. The results predict that P sits in the zinc (Zn) site rather than the oxygen (O) site causing the formation of P_Zn–2V_Zn acceptor-like defects, which compensates the donor defects in P doped ZnO films. Photocurrent spectra uniquely reveal presence of more oxygen vacancies (V_O) defects states in lower O₂ flow, which gets compensated with an increase in the O₂ flow. Successive photocurrent transients indicate probable presence of more V_O in the films grown with lower O₂ flow and more V_Zn in higher O₂ flow. Overall the photosensitivity measurements clearly present that O-rich ambience expedites the formation of acceptor defects which are compensated, thereby lowering the dark current and enhancing the ultraviolet photosensitivity.     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

Adaptive GLR-, Rao- and Wald-based CFAR detectors for a subspace signal embedded in structured Gaussian interference

The problem of detecting a subspace signal embedded in subspace Gaussian interference and thermal noise is studied in this paper. In this problem, both the signal-independent and signal-dependent interferences are assumed to be present, therefore the overall interference subspace covers the signal subspace. The approach of this paper extends previous works involving either of those two kinds of interferences. A set of secondary data containing only interference plus noise is employed to estimate the interference covariance matrix and the noise power. Three new detectors are designed via the generalized likelihood ratio (GLR), Rao and Wald tests, respectively. Their probabilities of false alarms (PFAs) and detections are analytically derived. The PFAs show that the new detectors have the constant false alarm rate (CFAR) property against the interference and noise. Numerical results show that the new detectors outperform their counterparts for the studied problem. Furthermore, the new detectors are less sensitive to the secondary data size and to the mismatched subspace signal than some other detectors, such as the GLR detector (GLRD), the adaptive matched filter (AMF), the adaptive subspace detector (ASD), etc.     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

A signal adaptive diffusion filter for video coding: Mathematical framework and complexity reductions

In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished.     

Trajectories of knowledge economy in SSA and MENA countries

In the first critical assessment of knowledge economy dynamic paths in Africa and the Middle East, but for a few exceptions, we find overwhelming support for diminishing cross-country disparities in knowledge-based economy dimensions. The paper employs all the four components of the World Bank's Knowledge Economy Index (KEI): economic incentives, innovation, education, and information infrastructure. The main finding suggests that sub-Saharan African (SSA) and the Middle East and North African (MENA) countries with low levels of KE dynamics and catching-up their counterparts of higher KE levels. We provide the speeds of integration and time necessary to achieve full (100%) integration. Policy implications are also discussed.     

Optimization of waste quail eggshells as biocomposites for polyaniline in ammonia gas detection

A simple, cost-effective, and novel chemical sensor for ammonia (NH₃) gas detection was developed from polyaniline (PANI)/quail eggshell (QES) composites. QES is a natural waste enriched in calcium carbonate. In this work, pure PANI was synthesized from chemical oxidation method and PANI/QES composites were prepared from physical mixing of QES with the synthesized PANI at different mass ratio. A series of complementary techniques including Fourier transform infrared and ultraviolet-visible spectrometers, scanning electron microscope with energy dispersive detection coupled with mapping, thermogravimetric analysis, and X-ray diffractometer were used to characterize the physicochemical and textural properties of the biocomposites. From the results, PANI/QES composite with a mass ratio of 1 exhibited the lowest NH₃ detection limit of 5.24 ppm with a linear correlation coefficient (R²) of close to unity (0.9932) between the signal and NH₃ gas concentration. As a whole, the PANI/QES biocomposites synthesized from this work exhibited excellent selectivity toward NH₃ gas even in the presence of other gas impurities, such as acetone, ethanol, and hexane. For the sensor reusability, the PANI/QES biocomposites can be reused in the application of NH₃ gas detection for at least 4 cycles.     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.