Region-based Mixture of Gaussians Modelling for Foreground Detection in Dynamic Scenes

One of the most widely used techniques in computer vision for foreground detection is to model each background pixel as a Mixture of Gaussians (MoG). While this is effective for a static camera with a fixed or a slowly varying background, it fails to handle any fast, dynamic movement in the background. In this paper, we propose a generalised framework, called region-based MoG (RMoG), that takes into consideration neighbouring pixels while generating the model of the observed scene. The model equations are derived from Expectation Maximisation theory for batch mode, and stochastic approximation is used for online mode updates. We evaluate our region-based approach against ten sequences containing dynamic backgrounds, and show that the region-based approach provides a performance improvement over the traditional single pixel MoG. For feature and region sizes that are equal, the effect of increasing the learning rate is to reduce both true and false positives. Comparison with four state-of-the art approaches shows that RMoG outperforms the others in reducing false positives whilst still maintaining reasonable foreground definition. Lastly, using the ChangeDetection (CDNet 2014) benchmark, we evaluated RMoG against numerous surveillance scenes and found it to amongst the leading performers for dynamic background scenes, whilst providing comparable performance for other commonly occurring surveillance scenes.

A Game-Theoretic Approach for Threats Detection and Intervention in Surveillance

Threat prevention with limited security resources is a challenging problem. An optimal strategy is to eectively predict attackers' targets (or goals) based on current available information, and use such predictions to prevent (or disrupt) their planned attacks. In this paper, we propose a game-theoretic framework to address this challenge which encompasses the following three elements. First, we design a method to analyze an attacker's types in order to determine the most plausible type of an attacker. Second, we propose an approach to predict possible targets of an attack and the course of actions that the attackers may take even when the attackers' types are ambiguous. Third, a game-theoretic based strategy is developed to determine the best protection actions for defenders (security resources).

GALEX Detection of Shock Breakout in Type IIP Supernova PS1-13arp: Implications for the Progenitor Star Wind

We present the GALEX detection of a UV burst at the time of explosion of an optically normal supernova (SN) IIP (PS1-13arp) from the Pan-STARRS1 survey at z = 0.1665. The temperature and luminosity of the UV burst match the theoretical predictions for shock breakout in a red supergiant (RSG), but with a duration a factor of similar to 50 longer than expected. We compare the NUV light curve of PS1-13arp to previous GALEX detections of SNe IIP and find clear distinctions that indicate that the UV emission is powered by shock breakout, and not by the subsequent cooling envelope emission previously detected in these systems. We interpret the similar to 1 day duration of the UV signal with a shock breakout in the wind of an RSG with a pre-explosion mass-loss rate of similar to 10(-3) M-circle dot yr(-1). This mass-loss rate is enough to prolong the duration of the shock breakout signal, but not enough to produce an excess in the optical plateau light curve or narrow emission lines powered by circumstellar interaction. This detection of nonstandard, potentially episodic high mass loss in an RSG SN progenitor has favorable consequences for the prospects of future wide-field UV surveys to detect shock breakout directly in these systems, and provide a sensitive probe of the pre-explosion conditions of SN progenitors.

Seismic damage detection for a steel braced frame structure

A new approach for global detection of seismic damage in a single-storey steel concentrically braced frame (CBF) structure is presented. The filtered lateral in-plane acceleration response of the CBF structure is integrated twice to provide the lateral in-plane displacement which is used to infer buckling and yielding damage. The level of interstorey drift of the CBF during a seismic excitation allows the yield and buckling of the bracing members to be identified and indirectly detects damage based on exceedance of calculated lateral in-plane displacement limits. A band-pass filter removes noise from the acceleration signal followed by baseline correction being used to reduce the drift in velocity and displacement during numerical integration. This pre-processing results in reliable numerical integration of the frame acceleration that predicts the displacement response accurately when compared to the measured lateral displacement of the CBF structure. Importantly, the structural damage is not assumed through removal of bracing members, rather damage is induced through actual seismic loading. The buckling and yielding displacement threshold limits used to identify damage are demonstrated to accurately identify the initiation of buckling and yielding.

Streaming Elements for FPGA Signal and Image Processing Accelerators

Field programmable gate array devices boast abundant resources with which custom accelerator components for signal, image and data processing may be realised; however, realising high performance, low cost accelerators currently demands manual register transfer level design. Software-programmable ’soft’ processors have been proposed as a way to reduce this design burden but they are unable to support performance and cost comparable to custom circuits. This paper proposes a new soft processing approach for FPGA which promises to overcome this barrier. A high performance, fine-grained streaming processor, known as a Streaming Accelerator Element, is proposed which realises accelerators as large scale custom multicore networks. By adopting a streaming execution approach with advanced program control and memory addressing capabilities, typical program inefficiencies can be almost completely eliminated to enable performance and cost which are unprecedented amongst software-programmable solutions. When used to realise accelerators for fast fourier transform, motion estimation, matrix multiplication and sobel edge detection it is shown how the proposed architecture enables real-time performance and with performance and cost comparable with hand-crafted custom circuit accelerators and up to two orders of magnitude beyond existing soft processors.

FPGA-based Tabu Search for Detection in Large-Scale MIMO Systems

The increasing scale of Multiple-Input Multiple- Output (MIMO) topologies employed in forthcoming wireless communications standards presents a substantial implementation challenge to designers of embedded baseband signal processing architectures for MIMO transceivers. Specifically the increased scale of such systems has a substantial impact on the perfor- mance/cost balance of detection algorithms for these systems. Whilst in small-scale systems Sphere Decoding (SD) algorithms offer the best quasi-ML performance/cost balance, in larger systems heuristic detectors, such Tabu-Search (TS) detectors are superior. This paper addresses a dearth of research in architectures for TS-based MIMO detection, presenting the first known realisations of TS detectors for 4 × 4 and 10 × 10 MIMO systems. To the best of the authors’ knowledge, these are the largest single-chip detectors on record.

Rapid, objective detection of cataract-induced blur using a bull's eye photodetector.

PURPOSE: To determine whether optical aberrations caused by cataract can be detected and quantified objectively using a newly described focus detection system (FDS). SETTING: The Wilmer Opthalmological Institute, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. METHODS: The FDS uses a bull's eye photodetector to measure the double-pass blur produced from a point source of light. To determine the range and level of focus, signals are measured with a series of trial lenses in the light path selected to span the point of best focus to generate focus curves. The best corrected visual acuity (BCVA), refractive error, lens photograph grades, and FDS signals were obtained in 18 patients scheduled to have cataract surgery. The tests were repeated 6 weeks after surgery. RESULTS: The mean FDS outcome measures improved after cataract surgery, with increased peak height (P=.001) and decreased peak width (P=.001). Improvement in signal strength (integral of signal within +/-1.5 diopters of the point of best focus) strongly correlated with improvement in peak height (R(2)=.88, P<.0001) and photographic cataract grade (R(2)=.72, P<.0001). The mean BCVA improved from 20/50 to 20/26 (P<.0001). The improvement in BCVA correlated more closely with FDS signal strength (R(2)=.44, P=.001) than with cataract grade (R(2)=.25, P=.06). CONCLUSIONS: Improvement in FDS outcome measures correlated with cataract severity and improvement in visual acuity. This objective approach may be useful in long-term studies of cataract progression.

First Detection of Gas-phase Methanol in a Protoplanetary Disk

The first detection of gas-phase methanol in a protoplanetary disk (TW Hya) is presented. In addition to being one of the largest molecules detected in disks to date, methanol is also the first disk organic molecule with an unambiguous ice chemistry origin. The stacked methanol emission, as observed with the Atacama Large Millimeter/submillimeter Array, is spectrally resolved and detected across six velocity channels (>3σ), reaching a peak signal-to-noise of 5.5σ, with the kinematic pattern expected for TW Hya. Using an appropriate disk model, a fractional abundance of 3 x 10^-12 – 4 x 10^-11 (with respect to H₂) reproduces the stacked line profile and channel maps, with the favored abundance dependent upon the assumed vertical location (midplane versus molecular layer). The peak emission is offset from the source position, suggesting that the methanol emission has a ring-like morphology: the analysis here suggests it peaks at ≈30 au, reaching a column density ≈3–6 x 10¹² cm⁻². In the case of TW Hya, the larger (up to millimeter-sized) grains, residing in the inner 50 au, may thus host the bulk of the disk ice reservoir. The successful detection of cold gas-phase methanol in a protoplanetary disk implies that the products of ice chemistry can be explored in disks, opening a window into studying complex organic chemistry during planetary system formation.

Phytochelatin signal tranduction and cadmium chelation in plants

As plantas utilizam diversas estratégias de sinalização para reconhecer e responder aos stresses ambientais. A maioria das vias de transdução de sinais partilham um sinal genérico, normalmente a modulação dos níveis intracelulares de Ca2+. Esta por sua vez pode iniciar uma cascata de fosforilação proteica que finalmente afecta as proteínas directamente envolvidas na protecção celular ou culmina em factores de transcrição que vão determinar a resposta fisiológica ao stresse. A percepção destes sinais e a compreensão de como estes podem activar as respostas adaptativas são factores-chave para a tolerância das plantas a stresses abióticos. Um dos principais stresses abóticos que restrigem o crescimento das plantas é a presença de metais pesados. A produção de fitoquelatinas e a subsequente quelação dos metais é o mecanismo mais conhecido de tolerância ao stresse metálico em plantas. Fitoquelatinas (PCs) são péptidos com grupos tiol que são sintetizados através da transpeptidação da glutationa (GSH), pela acção da enzima fitoquelatina sintase (PCS). No entanto, até ao momento, as vias de sinalização que levam à síntese de fitoquelatinas e à percepção do stresse metálico são pouco compreendidas. Dentro deste contexto, o presente trabalho foi elaborado com o intuito de elucidar a via de sinalização através da qual o cádmio é detectado pelas células vegetais e induz a síntese de PCs. Quase todos, os estudos de stresses abióticos em plantas apontam para o facto de a sua sinalização se basear nos mesmos tipos de sinais moleculares, nomeadamente a sinalização por cálcio, a fosforilação proteica e a indução de espécies reactivas de oxigénio (ROS). Trabalhos recentes sugerem que a sinalização de PCs poderá envolver todos estes parâmetros. Assim, uma primeira abordagem foi efectuada para compreender a síntese de PCs na espécie Arabidopsis thaliana, através da monitorizaçção da actividade de enzimas relacionadas, a γ-EC sintetase, GSH sintetase e a PC sintase (PCS), assim como o tempo necessário para o elongamento das PCs e a sua acumulação. Seguidamente, ao longo deste processo foi analisada a expressão de sinais específicos, associados com sinais de cálcio, fosforilação proteica e sinalização por ROS. A importância destes factores na síntese de PCs foi também avaliada através do uso de moduladores farmacológicos de cálcio e fosfatases proteicas e também pela indução de stresse oxidativo. Os resultados demonstraram novos dados sobre o papel do cálcio e da fosforilação proteica na produção de PCs e na síntese de GSH, revelando que a actvidade da PCS é regulada por fosforilação e que a sinalização de cálcio pode mediar a síntese de GSH. O envolvimento da sinalização de ROS na síntese de GSH, atráves de crosstalk com a sinalização de cálcio também foi proposta. Assim, os resultados aqui apresentados descrevem uma possível via de sinalização de cádmio nas plantas e da indução de fitoquelatinas. Este trabalho poderá ser portanto muito útil na implementação de novas metodologias de agricultura sustentável e práticas de fitorremediação em solos contaminados com metais pesados.

Detection of Incipient Thermal Damage Of Carbon Fiber/Epoxy Composites Using Fluorescent Thermal Damage Probes

Thesis (Ph.D.)--University of Washington, 2013

Celiac disease detection using a transglutaminase electrochemical immunosensor fabricated on nanohybrid screen-printed carbon electrodes

Celiac disease is a gluten-induced autoimmune enteropathy characterized by the presence of tissue tranglutaminase (tTG) autoantibodies. A disposable electrochemical immunosensor (EI) for the detection of IgA and IgG type anti-tTG autoantibodies in real patient’s samples is presented. Screen-printed carbon electrodes (SPCE) nanostructurized with carbon nanotubes and gold nanoparticles were used as the transducer surface. This transducer exhibits the excellent characteristics of carbon–metal nanoparticle hybrid conjugation and led to the amplification of the immunological interaction. The immunosensing strategy consisted of the immobilization of tTG on the nanostructured electrode surface followed by the electrochemical detection of the autoantibodies present in the samples using an alkaline phosphatase (AP) labelled anti-human IgA or IgG antibody. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with a commercial ELISA kit indicating that the electrochemical immunosensor is a trustful analytical screening tool.

Detection of ZnS phases in CZTS thin-films by EXAFS

Copper zinc tin sulfide (CZTS) is a promising Earthabundant thin-film solar cell material; it has an appropriate band gap of ~1.45 eV and a high absorption coefficient. The most efficient CZTS cells tend to be slightly Zn-rich and Cu-poor. However, growing Zn-rich CZTS films can sometimes result in phase decomposition of CZTS into ZnS and Cu2SnS3, which is generally deleterious to solar cell performance. Cubic ZnS is difficult to detect by XRD, due to a similar diffraction pattern. We hypothesize that synchrotron-based extended X-ray absorption fine structure (EXAFS), which is sensitive to local chemical environment, may be able to determine the quantity of ZnS phase in CZTS films by detecting differences in the second-nearest neighbor shell of the Zn atoms. Films of varying stoichiometries, from Zn-rich to Cu-rich (Zn-poor) were examined using the EXAFS technique. Differences in the spectra as a function of Cu/Zn ratio are detected. Linear combination analysis suggests increasing ZnS signal as the CZTS films become more Zn-rich. We demonstrate that the sensitive technique of EXAFS could be used to quantify the amount of ZnS present and provide a guide to crystal growth of highly phase pure films.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Design of a CMOS amplifier for breast cancer detection

A transimpedance amplifier (TIA) is used, in radiation detectors like the positron emission tomography(PET), to transform the current pulse produced by a photo-sensitive device into an output voltage pulse with a desired amplitude and shape. The TIA must have the lowest noise possible to maximize the output. To achieve a low noise, a circuit topology is proposed where an auxiliary path is added to the feedback TIA input, In this auxiliary path a differential transconductance block is used to transform the node voltage in to a current, this current is then converted to a voltage pulse by a second feedback TIA complementary to the first one, with the same amplitude but 180º out of phase with the first feedback TIA. With this circuit the input signal of the TIA appears differential at the output, this is used to try an reduced the circuit noise. The circuit is tested with two different devices, the Avalanche photodiodes (APD) and the Silicon photomultiplier (SIPMs). From the simulations we find that when using s SIPM with Rx=20kΩ and Cx=50fF the signal to noise ratio is increased from 59 when using only one feedback TIA to 68.3 when we use an auxiliary path in conjunction with the feedback TIA. This values where achieved with a total power consumption of 4.82mv. While the signal to noise ratio in the case of the SIPM is increased with some penalty in power consumption.

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.