Добірка наукової літератури з теми "Clutter rate"

Purpose The purpose of this study was to examine the effects of video education about cluttering on students' perceptions of a person who clutters. Method A total of 193 undergraduate students served as participants. Ninety-five students were provided with a written definition of cluttering, while 98 were also provided with video education about cluttering. Students then rated a person who clutters on speech and personality scales. Results Results yielded significant group differences in ratings of intelligibility, speech rate, ease of listening, and competence. Respondents who viewed the educational video rated a person who clutters significantly more negatively along these dimensions than respondents who read a definition only. However, participants who did not view the video reported knowing significantly more people who clutter. Conclusion Findings suggest that this particular form of video education might provide students with “realistic” exposure to cluttering. Further research is needed to assess effects of exposure to and interaction with a person who clutters on perceptions of cluttering. Implications include the impact of prior exposure to those who clutter, as well as potential confusion between cluttering and “fast speech.” These factors might have influenced identification rates of individuals who clutter, which could have affected the results.

The constant false alarm rate (CFAR) process is essential for target detection in radar systems. Although the detection performance of the CFAR process is normally guaranteed in noise-limited environments, it may be dramatically degraded in clutter-limited environments since the probabilistic characteristics for clutter are unknown. Therefore, sophisticated CFAR processes that suppress the effect of clutter can be used in actual applications. However, these methods have the fundamental limitation of detection performance because there is no feedback structure in terms of the probability of false alarm for determining the detection threshold. This paper presents a robust control scheme for adjusting the detection threshold of the CFAR process while estimating the clutter measurement density (CMD) that uses only the measurement sets over a finite time interval in order to adapt to time-varying cluttered environments, and the probability of target existence with finite measurement sets required for estimating CMD is derived. The improved performance of the proposed method was verified by simulation experiments for heterogeneous situations.

Dysfunction of the left ventricle (LV) weakens the cardiac function and affects the physical activity. Echocardiagraphy has been used to visualize the blood flow dynamics and to evaluate the cardiac function. However, the signal processing to suppress the clutter signals should be employed. In this study, we employed the singular value decomposition (SVD) clutter filtering to obtain the cardiac blood speckle images. We also employed the adaptive thresholding metric to determine the proper cutoff values at each phase during the cardiac cycle. Moreover, we employed a depth-dependent SVD clutter filter for more accurate estimation of the cardiac blood echo signals. The 2D blood flow velocity vectors were estimated by applying the block matching method to obtained blood speckle images. The obtained results show that the proposed filter suppressed the clutter signals from left ventricular wall significantly, and the contrast-to-noise ratio (CNR) was improved from -0.5 dB to 13.8 dB by the proposed SVD clutter filtering.

Small target detection is very important for infrared search and track (IRST) problems. Grouped targets are difficult to detect using the conventional constant false alarm rate (CFAR) detection method. In this study, a novel multitarget detection method was developed to identify adjacent or closely spaced small infrared targets. The neighboring targets decrease the signal-to-clutter ratio in hysteresis threshold-based constant false alarm rate (H-CFAR) detection, which leads to poor detection performance in cluttered environments. The proposed adjacent target rejection-based robust background estimation can reduce the effects of the neighboring targets and enhance the small multitarget detection performance in infrared images by increasing the signal-to-clutter ratio. The experimental results of the synthetic and real adjacent target sequences showed that the proposed method produces an upgraded detection rate with the same false alarm rate compared to the recent target detection methods (H-CFAR, Top-hat, and TDLMS).

The detection capabilities in vertical polarized, High-frequency SurfaceWave Radar (HFSWR) are limited by the clutter spikes in first-order sea clutter. The energy, position, and Doppler frequency of first-order sea clutter depend on the sea states, which are non-homogeneous – because of that, using a fixed expression to eliminate sea clutter gives limited results. In this paper, the authors proposed a new adaptive method using a two-stage detector based on the Order Statistic Constant False Alarm Rate (OS-CFAR) principle. The approach shows the capability to eliminate heterogeneous clutter and detect targets in the vicinities of sea clutter in the Range – Doppler map.

The problem that this paper is concerned with is High Frequency Surface Wave Radar (HFSWR) detection of desired targets against a complex interference background consisting of sea clutter, ionosphere clutter, Radio Frequency Interference (RFI) and atmospheric noise. Eliminating unwanted echoes and exploring obscured targets contribute to achieving ideal surveillance of sea surface targets. In this paper, a Self-regulating Multi-clutter Suppression Framework (SMSF) has been proposed for small aperture HFSWR. SMSF can remove many types of clutter or RFI; meanwhile, it mines the targets merged into clutter and tracks the travelling path of the ship. In SMSF, a novel Dynamic Threshold Mapping Recognition (DTMR) method is first proposed to reduce the atmospheric noise and recognize each type of unwanted echo; these recognized echoes are fed into the proposed Adaptive Prophase-current Dictionary Learning (APDL) algorithm. To make a comprehensive evaluation, we also designed three novel assessment parameters: Obscured Targets Detection Rate (OTDR), Clutter Purification Rate (CPR) and Erroneous Suppression Rate (ESR). The experiment data collected from a small aperture HFSWR system confirm that SMSF has precise suppression performance over most of the classical algorithms and concurrently reveals the moving targets, and OTDR of SMSF is usually higher than compared methods.

In this paper, a support vector machine (SVM) based land/sea clutter classification algorithm was proposed. For target location error correction based on passive beacon reference source of over-the-horizon radar (OTHR), the signal model of land/sea clutter is established, the three kinds of multi-features of land/sea clutter are analyzed, and the classification algorithm based on SVM using multi-features is detailed. Simulation experiments were carried out for different clutter-noise- ratios, and the results showed that the proposed algorithm has a higher recognition rate of land/sea clutter than algorithms based on single feature of backscatter amplitude or linear discriminant analysis. This paper could provide theoretical guidance for improving target location accuracy.

A 4D TBD approach is developed here for closely weak extended target tracking and overcoming heterogeneous clutter background and various clutter regions. The 4D measurements in this work are the points containing three positional information in spatial space and corresponding timestamp. The proposed method is mainly designed to address two issues. The first one is the dilemma between the weak target detection and difficult computation originating from the high dimensions of measurement. The second issue is the suppression of inhomogeneous background clutter and various clutter regions. The extension experiment using synthetic data showcases that no false alarm track would be built in the clutter regions, and the detection rate of close targets exceeds 94%. The experiments using real 3D radar also prove that the method works well in tracking closely maneuvering extended targets even if a clutter region exists.

ABSTRACTBackground: Development of a scale to rate the degree and various aspects of uncleanliness will facilitate description and research in cases of severe domestic squalor.Methods: Discussion with representatives of relevant agencies led to selection of various aspects of domestic uncleanliness and clutter to be assessed when describing cases of squalor. Rooms and areas with varying functions (toilet, kitchen, bedroom, etc.) were all to be rated, along with other indicators of squalor (e.g. odor, vermin). Trial use and further discussion resulted in reduction to ten items, each rated on a four-point scale, with succinct descriptions of anchor-points. Two experienced psychogeriatricians then used this new Environmental Cleanliness and Clutter Scale (ECCS) to rate independently 55 dwellings which had been reported by Aged Care staff as cluttered or unclean, and also rated overall degree of squalor. Reliability and indications of validity were analyzed.Results: The inter-rater reliability for the ten items was considered satisfactory (κ 0.48, varying from 0.31 to 0.58). Cronbach's α for the new scale was 0.94, demonstrating high internal consistency. Each author's ratings of degree of squalor (none to severe) matched well with the other's ratings on the scale; a score of >12 usually indicated moderate or severe squalor.Conclusion: The ECCS proved reliable and useful in rating cases where elderly people were living in severe domestic squalor.

In this study, novel methods for high-resolution radar target detection in non-Gaussian clutter environment are proposed. In solution of the problem, two approaches are used: Non-coherent detection that operates on the envelope-detected signal for thresholding and coherent detection that performs clutter suppression, Doppler processing and thresholding at the same time. The proposed non-coherent detectors, which are designed to operate in non-Gaussian and range-heterogeneous clutter, yield higher performance than the conventional methods that were designed either for Gaussian clutter or heterogeneous clutter. The proposed coherent detector exploits the information in all the range cells and pulses and performs the clutter reduction and thresholding simultaneously. The design is performed for uncorrelated, partially correlated and fully correlated clutter among range cells. The performance analysis indicates the superiority of the designed methods over the classical ones, in fully correlated and partially correlated situations. In addition, by design of detectors for multiple targets and making corrections to the conventional methods, the target-masking problem of the classical detectors is alleviated.

Cette thèse présente un ensemble de travaux qui s'inscrivent dans le domaine du génie biomédical pour des applications cliniques. L'objectif principal de ce travail est de fournir aux cliniciens un mode d'imagerie ultrasonore pour extraire simultanément la vitesse du flux et le mouvement de la paroi à des cadences d'imagerie élevées dans les artères. Les pathologies cardiovasculaires sont une cause majeure de décès et d'invalidité dans le monde. Bien que l'origine de ces maladies ne soit pas encore entièrement comprise, il semble que certains marqueurs pathologiques de la paroi et du flux pourraient permettre une détection plus précoce. Parce que les tissus artériels sont sujets à des phénomènes rapides et complexes, une modalité d'imagerie à haute cadence semble très pertinente pour étudier les pathologies du système cardiovasculaire. Malheureusement, aucune technique n'est actuellement utilisée cliniquement ni même approuvée pour l'extraction de marqueurs pathologiques du sang et de la paroi à des cadences d'imagerie élevées. C'est pourquoi, dans cette thèse, je propose de concevoir une séquence et un algorithme ultrasonore permettant d'extraire ces deux aspects, à des cadences d'imagerie élevées sur les artères, pour une application clinique potentielle. Trois contributions scientifiques principales sont présentées cette thèse : i) la conception de la séquence ultrasonore avec un estimateur de mouvement 2D, ii) une nouvelle approche adaptative de filtrage de paroi, et iii) un essai clinique. La séquence d'imagerie ultrasonore est basée sur la transmission d'ondes planes permettant d'obtenir des cadences d'imagerie allant jusqu'à 10 000 Hz sur la carotide. La méthode d'estimation de mouvement est basée sur une approche introduisant une oscillation latérale virtuelle dans les images qui, couplée à un estimateur de phase 2D basé sur des travaux antérieurs de la littérature, permet d'extraire des champs vectoriels de vitesses. Les validations pour l'estimation des vitesses du flux et du mouvement des parois ont été effectuées à l'aide d'un fantôme d'écoulement Doppler commercial et d'un fantôme de carotide réaliste conçu pour les expériences. Une technique de filtrage adaptatif de paroi a été développée et validée sur des volontaires à l'aide des estimations de vitesses tissulaires, ce qui permet d'éliminer précisément le signal du tissu des signaux du sang. Enfin, l'essai clinique a été réalisé à l'hôpital avec un groupe de volontaires et un groupe de patients. La séquence ultrasonore, l'algorithme d'estimation de mouvement et les approches adaptatives de filtrage de paroi ont été validés dans la thèse. La méthode permet d'extraire les vitesses du flux et de la paroi à haute cadence d'imagerie, avec de faibles erreurs et écarts-types. L'approche adaptative du filtrage de paroi permet de mieux extraire le flux par rapport à d'autres approches standard. Cette amélioration est particulièrement perceptible à proximité de la paroi, ce qui permettrait des mesures précises de l'écoulement et des contraintes le long des parois artérielles où les plaques peuvent se former et se développer. Pour conclure, l'essai clinique a démontré la faisabilité de notre approche dans un environnement clinique avec l'extraction des mouvements tissulaires, du flux et de paramètres artériels qui ont montré des différences entre et au sein des groupes. Cette thèse est donc un pas en avant vers l'utilisation clinique de l'imagerie ultrasonore à haute cadence pour la quantification du mouvement tissulaire et du flux pour la détection et le diagnostic des maladies cardiovasculaires
This thesis is focused on biomedical engineering for clinical applications. The main goal of this work is to provide to clinicians an ultrasound mode to simultaneously extract wall motion and flow at high frame rates in arteries. Cardiovascular pathologies are a major cause of death and disability worldwide. Although the formation of such diseases is still not fully understood, it appears that some pathological markers from both wall and flow could allow an earlier detection. Because tissues are subject to fast and complex phenomena in the arteries, a high frame rate imaging modality seems highly relevant to extract as much information as possible on the condition of the cardiovascular system. Unfortunately, no technique is currently clinically used or even approved for the extraction of both flow and wall pathological markers at high frame rates. Therefore, in this thesis, I propose to design an ultrasound sequence and algorithm permitting to extract both aspects, at high frame rates on arteries, for a potential clinical application. There are three main scientific contributions in this thesis: i) the design of the ultrasound sequence with a 2D motion estimator, ii) a new adaptive clutter filtering approach, and iii) a clinical trial. The ultrasound sequence is based on plane wave acquisition permitting to yield frame rates up to 10 000 Hz in the carotid. The pipeline used an approach introducing a virtual lateral oscillation in ultrasound images which, coupled with a 2D phase-based estimator based on previous works from the literature, allows to extract vectorial velocity fields. Validations for both flow and wall motion estimation were performed on a commercial Doppler flow phantom and an in-house realistic carotid phantom was designed for the experiments. An adaptive clutter filtering technique was also developed and validated on volunteers based on tissue estimates, which permit to precisely remove tissue clutter from flow signals. Finally, the clinical trial was performed at the hospital with a group of volunteers and a group of patients. The ultrasound sequence, motion estimation algorithm, and adaptive clutter filtering approaches were well validated in the thesis. The method can provide both wall motion and flow estimates at high frame rates, with low errors and standard deviations. The adaptive clutter filtering approach permits to better extract the flow compared to other standard approaches. This improvement is especially noticeable close to the wall, which would allow accurate flow and stress measurements along arterial walls where plaques can form and develop. To conclude, the clinical trial has demonstrated the feasibility in a clinical environment with the extraction of wall motion, flow, and arterial parameters that showed differences between and within groups. This thesis is then a step toward clinical use of high frame rate ultrasound imaging for quantification of both wall motion and flow for pathological detection of cardiovascular diseases

This thesis focuses on the problem of automated tracking of tiny cellular and sub-cellular structures, known as particles, in the sequences acquired from total internal reflection fluorescence microscopy (TIRFM) imaging technique. Our primary biological motivation is to develop an automated system for tracking the sub-cellular structures involving exocytosis (an intracellular mechanism) which is helpful for studying the possible causes of the defects in diseases such as diabetes and obesity. However, all methods proposed in this thesis are generalized to be applicable for a wide range of particle tracking applications. A reliable multi-particle tracking method should be capable of tracking numerous similar objects in the presence of high levels of noise, high target density and complex motions and interactions. In this thesis, we choose the Bayesian filtering framework as our main approach to deal with this problem. We focus on the approaches that work based on detections. Therefore, in this thesis, we first propose a method that robustly detects the particles in the noisy TIRFM sequences with inhomogeneous and time-varying background. In order to evaluate our detection and tracking methods on the sequences with known and reliable ground truth, we also present a framework for generating realistic synthetic TIRFM data. To propose a reliable multi-particle tracking method for TIRFM sequences, we suggest a framework by combining two robust Bayesian filters, the interacting multiple model and joint probabilistic data association (IMM-JPDA) filters. The performance of our particle tracking method is compared against those of several popular and state-of-the art particle tracking approaches on both synthetic and real sequences. Although our approach performs well in tracking particles, it can be very computationally demanding for the applications with dense targets with poor detections. To propose a computationally cheap, but reliable, multi-particle tracking method, we investigate the performance of a recent multi-target Bayesian filter based on random finite theory, the probability hypothesis density (PHD) filter, on our application. To this end, we propose a general framework for tracking particles using this filter. Moreover, we assess the performance of our proposed PHD filter on both synthetic and real sequences with high level of noise and particle density. We compare its results from both aspects of accuracy and processing time against our IMM-JPDA filter. Finally, we suggest a framework for tracking particles in a challenging problem where the noise characteristic and the background intensity of sequences change during the acquisition process which make detection profile and clutter rate time-variant. To deal with this, we propose a bootstrap filter using another type of the random finite set based Bayesian filters, the cardinalized PHD (CPHD) filter, composed of an estimator and a tracker. The estimator adaptively estimates the required meta parameters for the tracker such as clutter rate and the detection probability while the tracker estimates the state of the targets. We evaluate the performance of our bootstrap on both synthetic and real sequences under these time-varying conditions. Moreover, its performance is compared against those of our other particle trackers as well as the state-of-the art particle tracking approaches.

AbstractAn introduction to acoustic and vibrational communication in animals is presented in this chapter. Starting with the origins of communication and ritualization of vocal and vibrational signals to produce a clear message or broadcast. A summary of communication concepts is presented describing behaviors such as displays. The chapter continues by unraveling some of the complexities of acoustic and vibrational communication such as elephant vibration detection posture and reception of long-range vibrational signal production—or drumming—in Prairie chickens and Kangaroo rats. We discuss the advantages of vibrational and acoustic signal production signals as well as the disadvantages including the influence of environmental factors that may mask or attenuate signals such as wind, water, or structural clutter. Research on the informational content of these signals is progressing. We provide a summary of ground-breaking earlier work, an indication of where we believe the field is now, and a glimpse of where we believe the field could be going in the future. The chapter concludes with a discussion of the characteristics of human language and whether nonhuman animals have such a language with the accompanying mental abilities. It could just be that other animals are most entertained (and threatened!) by our signaling behaviors.

Direct signal, clutter, and multipath echoes are received along with surveillance signal in passive bi-static radars. These signals degrade the target detection capability of the radar processing algorithm and thus require additional processing to achieve a decent performance. Different clutter and multipath cancellation algorithms are devised for removal of unwanted signals. These algorithms require different computational complexity to provide different level of clutter cancellation. This chapter reviews different clutter cancellation techniques and compares their performance based on the computational complexity. This performance comparison allows understanding the computation load put up by different clutter cancellation techniques and ultimately the response rate of the radar system while maintaining decent target detection.

This chapter looks at the growing problem of pollution on Manhattan Island. Since its founding, the city lacked proper sanitation. Garbage piles along the streets—which the public nicknamed “Corporation Pudding”—were supposed to be cleared up by the Department of Street Cleaning. However, the contractors rarely did their job. Because of the clutter, New York's streets proved hard to navigate. Adding to the nastiness was the mass of pigs, cattle and horses—which meant mounds of manure—along with all the rats scurrying around. Not surprisingly, sanitary conditions were thus the main cause of the diseases that permeated all levels of 19th-century New York society. With limited understanding of medicine or a sense of how to combat disease, Yellow Fever and cholera wreaked havoc on the city.

The combination of highly turbulent airflow, flammable fluids, and numerous ignition sources makes aircraft engine nacelles a difficult fire zone to protect. Better understanding of nacelle air flow and how it influences the spread of fires and fire extinguishing agents is needed to improve the efficiency of fire suppression. The principal objective of this study is to analyze the flow field and the dispersion of fire extinguishing agents in the presence of various clutter elements of aircraft engine nacelles. Three dimensional simulations of the transport of liquid droplets in highly turbulent flow past clutter elements are performed in this study. A three dimensional model with 2000 mm length, 915 mm width and 610 mm height was first created. The clutter package consists of 16 cylindrical elements; each element has an outer diameter D of 50.8 mm and assembled to form three separate arrays of 5, 6 and 5 elements. The stream wise spacing between each clutter array is set to twice the diameter (2 D). The three dimensional geometry is similar to the one used in the experimental study at Sandia National Laboratory. This will help to validate the numerical results before performing a parametric study. Water with initial droplet size of 150 to 280 μm, and flow rate of 0.285 Kg/s is used as suppressant agent. The three velocity components, turbulence intensity, and droplet concentrations and trajectories behind the clutter package are obtained in this study. The droplet X-velocity and Y-velocity and the droplet size distribution downstream the clutter elements show a good agreement with the experimental data. The effect of initial turbulence intensity, the air flow velocity at the inlet, and droplet diameter at the injection on the transport and dispersion of fire extinguishing agent in this complex geometry is presented in this paper.