990 resultados para Dark objects method
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The paper treats the task for cluster analysis of a given assembly of objects on the basis of the information contained in the description table of these objects. Various methods of cluster analysis are briefly considered. Heuristic method and rules for classification of the given assembly of objects are presented for the cases when their division into classes and the number of classes is not known. The algorithm is checked by a test example and two program products (PP) – learning systems and software for company management. Analysis of the results is presented.
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AMS Subj. Classification: 03C05, 08B20
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It has been proposed that dwarf irregular galaxies can be separated into two classes based on their formation mechanism; that they are the result of the collapse of a primordial gas cloud or that they are the product of condensation of gas in the tidal tails of interacting galaxies. Simulations of galaxy interactions indicate that one can differentiate between these two scenarios by the dark matter content, with a low dark matter content indicating a fossil tidal dwarf. The purpose of this dissertation was to explore the dark matter distribution of two dwarf irregular galaxies using optical and neutral atomic hydrogen data. For DDO 210, the method of mass-modelling was used to determine its dark matter. About 64% of the galaxy mass was calculated to be in the form of dark matter and hence it is unlikely to be a fossil tidal dwarf. The method of mass-modelling could not be used for DDO 169 as the galaxy shows evidence of being tidally disrupted and hence, has a disturbed velocity field. Instead, the suggestion that dark matter might be responsible for a pressure anomaly in DDO 169 was tested to determine its dark matter content. According to this method, a pressure anomaly does exist but without a concrete value for the scale-height, it is unclear whether the anomaly is due to the presence of dark matter. Hence one cannot say how much dark matter might actually be present in DDO 169. A rotation curve would be required to do this. ^
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Weakly electric fish produce a dual function electric signal that makes them ideal models for the study of sensory computation and signal evolution. This signal, the electric organ discharge (EOD), is used for communication and navigation. In some families of gymnotiform electric fish, the EOD is a dynamic signal that increases in amplitude during social interactions. Amplitude increase could facilitate communication by increasing the likelihood of being sensed by others or by impressing prospective mates or rivals. Conversely, by increasing its signal amplitude a fish might increase its sensitivity to objects by lowering its electrolocation detection threshold. To determine how EOD modulations elicited in the social context affect electrolocation, I developed an automated and fast method for measuring electroreception thresholds using a classical conditioning paradigm. This method employs a moving shelter tube, which these fish occupy at rest during the day, paired with an electrical stimulus. A custom built and programmed robotic system presents the electrical stimulus to the fish, slides the shelter tube requiring them to follow, and records video of their movements. I trained the electric fish of the genus Sternopygus was trained to respond to a resistive stimulus on this apparatus in 2 days. The motion detection algorithm correctly identifies the responses 91% of the time, with a false positive rate of only 4%. This system allows for a large number of trials, decreasing the amount of time needed to determine behavioral electroreception thresholds. This novel method enables the evaluation the evolutionary interplay between two conflicting sensory forces, social communication and navigation.
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SmartWater is a chemical taggant used as a crime deterrent. The chemical taggant is a colorless liquid that fluoresces yellow under ultra-violet (UV) light and contains distinctive, identifiable and traceable elemental composition. For instance, upon a break and entry scenario, the burglar is sprayed with a solution that has an elemental signature custom-made to a specific location. The residues of this taggant persist on skin and other objects and can be easily recovered for further analysis. The product has been effectively used in Europe as a crime deterrent and has been recently introduced in South Florida. In 2014, Fourt Lauderdale Police Department reported the use of SmartWater products with a reduction in burglaries of 14% [1]. The International Forensic Research Institute (IFRI) at FIU validated the scientific foundation of the methods of recovery and analysis of these chemical tagging systems using LA-ICP-MS. Analytical figures of merit of the method such as precision, accuracy, limits of detection, linearity and selectivity are reported in this study. Moreover, blind samples were analyzed by LA-ICP-MS to compare the chemical signatures to the company’s database and evaluate error rates and the accuracy of the method. This study demonstrated that LA-ICP-MS could be used to effectively detect these traceable taggants to assist law enforcement agencies in the United States with cases involving transfer of these forensic coding systems.
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Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.
Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.
Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.
Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.
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Supernova (SN) is an explosion of a star at the end of its lifetime. SNe are classified to two types, namely type I and II through the optical spectra. They have been categorised based on their explosion mechanism, to core collapse supernovae (CCSNe) and thermonuclear supernovae. The CCSNe group which includes types IIP, IIn, IIL, IIb, Ib, and Ic are produced when a massive star with initial mass more than 8 M⊙ explodes due to a collapse of its iron core. On the other hand, thermonuclear SNe originate from white dwarfs (WDs) made of carbon and oxygen, in a binary system. Infrared astronomy covers observations of astronomical objects in infrared radiation. The infrared sky is not completely dark and it is variable. Observations of SNe in the infrared give different information than optical observations. Data reduction is required to correct raw data from for example unusable pixels and sky background. In this project, the NOTCam package in the IRAF was used for the data reduction. For measuring magnitudes of SNe, the aperture photometry method with the Gaia program was used. In this Master’s thesis, near-infrared (NIR) observations of three supernovae of type IIn (namely LSQ13zm, SN 2009ip and SN2011jb), one type IIb (SN2012ey), in addition to one type Ic (SN2012ej) and type IIP (SN 2013gd) are studied with emphasis on luminosity and colour evolution. All observations were done with the Nordic Optical Telescope (NOT). Here, we used the classification by Mattila & Meikle (2001) [76], where the SNe are differentiated by the infrared light curves into two groups, namely ’ordinary’ and ’slowly declining’. The light curves and colour evolution of these supernovae were obtained in J, H and Ks bands. In this study, our data, combined with other observations, provide evidence to categorize LSQ13zm, SN 2012ej and SN 2012ey as being part of the ordinary type. We found interesting NIR behaviour of SN 2011jb, which lead it to be classified as a slowly declining type.
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The 'Dark Triad' of socially aversive personality traits (Machiavellianism, Narcissism, and Psychopathy) is typically associated with grandiosity, callousness, and exploitation. Despite this, people with such traits can be very successful in life, especially in the occupational context. This study investigated the characteristics of individuals who enable and abet people high on Dark Triad traits (e.g. through tolerating unpleasant behaviours, not challenging unethical conduct, etc.). High Dark Triad individuals may be able to identify individuals who are susceptible to social manipulation and who are therefore less likely to challenge their behaviours. This study used a 20-item Vulnerability Scale to capture the characteristics of individuals who fall victim to people high on the Dark Triad traits. Cronbach's alpha for the Vulnerability Scale was .80. Pearson's correlation between total vulnerability scores and each of the Big Five personality traits revealed that predictors of vulnerability to social manipulation include low extraversion, low conscientiousness, high neuroticism, and high agreeableness. The vignette method was used to elicit perceptions of Dark Triad behaviours from those who are found to demonstrate signs of social vulnerability. Differences in response styles on Likert-type statements and open-ended questions were found between the high and low vulnerability groups.
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This thesis presents an analysis of the largest catalog to date of infrared spectra of massive young stellar objects in the Large Magellanic Cloud. Evidenced by their very different spectral features, the luminous objects span a range of evolutionary states from those most embedded in their natal molecular material to those that have dissipated and ionized their surroundings to form compact HII regions and photodissociation regions. We quantify the contributions of the various spectral features using the statistical method of principal component analysis. Using this analysis, we classify the YSO spectra into several distinct groups based upon their dominant spectral features: silicate absorption (S Group), silicate absorption and fine-structure line emission (SE), polycyclic aromatic hydrocarbon (PAH) emission (P Group), PAH and fine-structure line emission (PE), and only fine-structure line emission (E). Based upon the relative numbers of sources in each category, we are able to estimate the amount of time massive YSOs spend in each evolutionary stage. We find that approximately 50% of the sources have ionic fine-structure lines, indicating that a compact HII region forms about half-way through the YSO lifetime probed in our study. Of the 277 YSOs we collected spectra for, 41 have ice absorption features, indicating they are surrounded by cold ice-bearing dust particles. We have decomposed the shape of the ice features to probe the composition and thermal history of the ice. We find that most the CO2 ice is embedded a polar ice matrix that has been thermally processed by the embedded YSO. The amount of thermal processing may be correlated with the luminosity of the YSO. Using the Australia Telescope Compact Array, we imaged the dense gas around a subsample of our sources in the HII complexes N44, N105, N113, and N159 using HCO+ and HCN as dense gas tracers. We find that the molecular material in star forming environments is highly clumpy, with clumps that range from subparsec to ~2 parsecs in size and with masses between 10^2 to 10^4 solar masses. We find that there are varying levels of star formation in the clumps, with the lower-mass clumps tending to be without massive YSOs. These YSO-less clumps could either represent an earlier stage of clump to the more massive YSO-bearing ones or clumps that will never form a massive star. Clumps with massive YSOs at their centers have masses larger than those with massive YSOs at their edges, and we suggest that the difference is evolutionary: edge YSO clumps are more advanced than those with YSOs at their centers. Clumps with YSOs at their edges may have had a significant fraction of their mass disrupted or destroyed by the forming massive star. We find that the strength of the silicate absorption seen in YSO IR spectra feature is well-correlated with the on-source HCO+ and HCN flux densities, such that the strength of the feature is indicative of the embeddedness of the YSO. We estimate that ~40% of the entire spectral sample has strong silicate absorption features, implying that the YSOs are embedded in circumstellar material for about 40% of the time probed in our study.
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Entrepreneurship attracts people with high job satisfaction and financial independence. Unfortunately, being deceived by this image, people do not pay attention to side effects of entrepreneurship. This ignorance usually turns into devastating results for entrepreneur’s health and venture performance. Therefore, it is required to seek ways to avoid these situations. The interest of the study lies in understanding of stress influence on international entrepreneurs by considering stress as a negative side effect of international entrepreneurship. To cover the concept of entrepreneurial stress completely, the study was divided into three section presented by following research questions: 1. What are the antecedents of entrepreneurial stress? 2. What are the consequences of entrepreneurial stress? 3. What coping strategies are applied to address entrepreneurial stress? Systematic literature review has been chosen as scientific approach to answer above questions due to the reason that it enables to minimise inconsistencies of both concepts of international entrepreneurship and stress. This method has afforded an opportunity to distinguish such stress causes as role conflict, overload, and ambiguity. Additionally, the study has covered the notion of stress moderators. The author argues that entrepreneurial traits, venture environment, and social support can have influence on degree of stress perception. Further, it has been proven that unaddressed stress could lead to reduction of entrepreneur’s psychological and physiological health. It should be taken into consideration that degree of both job satisfaction and performance would depend on the level of perceived stress. The last part of study emphasises the coping strategies. The author argues that it is important for an international entrepreneur to comprehend his or her and others’ emotions in order to overcome negative consequences of stress. In addition, the author suggests that an international entrepreneur needs to practise job sharing to reduce the amount of work to be completed. Moreover, it is believed that job sharing can help to overcome work-family conflict that prevails among entrepreneurs. The author anticipates that results of study can be beneficial for entrepreneurs who aim to achieve great results.
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A new type of space debris was recently discovered by Schildknecht in near -geosynchronous orbit (GEO). These objects were later identified as exhibiting properties associated with High Area-to-Mass ratio (HAMR) objects. According to their brightness magnitudes (light curve), high rotation rates and composition properties (albedo, amount of specular and diffuse reflection, colour, etc), it is thought that these objects are multilayer insulation (MLI). Observations have shown that this debris type is very sensitive to environmental disturbances, particularly solar radiation pressure, due to the fact that their shapes are easily deformed leading to changes in the Area-to-Mass ratio (AMR) over time. This thesis proposes a simple effective flexible model of the thin, deformable membrane with two different methods. Firstly, this debris is modelled with Finite Element Analysis (FEA) by using Bernoulli-Euler theory called “Bernoulli model”. The Bernoulli model is constructed with beam elements consisting 2 nodes and each node has six degrees of freedom (DoF). The mass of membrane is distributed in beam elements. Secondly, the debris based on multibody dynamics theory call “Multibody model” is modelled as a series of lump masses, connected through flexible joints, representing the flexibility of the membrane itself. The mass of the membrane, albeit low, is taken into account with lump masses in the joints. The dynamic equations for the masses, including the constraints defined by the connecting rigid rod, are derived using fundamental Newtonian mechanics. The physical properties of both flexible models required by the models (membrane density, reflectivity, composition, etc.), are assumed to be those of multilayer insulation. Both flexible membrane models are then propagated together with classical orbital and attitude equations of motion near GEO region to predict the orbital evolution under the perturbations of solar radiation pressure, Earth’s gravity field, luni-solar gravitational fields and self-shadowing effect. These results are then compared to two rigid body models (cannonball and flat rigid plate). In this investigation, when comparing with a rigid model, the evolutions of orbital elements of the flexible models indicate the difference of inclination and secular eccentricity evolutions, rapid irregular attitude motion and unstable cross-section area due to a deformation over time. Then, the Monte Carlo simulations by varying initial attitude dynamics and deformed angle are investigated and compared with rigid models over 100 days. As the results of the simulations, the different initial conditions provide unique orbital motions, which is significantly different in term of orbital motions of both rigid models. Furthermore, this thesis presents a methodology to determine the material dynamic properties of thin membranes and validates the deformation of the multibody model with real MLI materials. Experiments are performed in a high vacuum chamber (10-4 mbar) replicating space environment. A thin membrane is hinged at one end but free at the other. The free motion experiment, the first experiment, is a free vibration test to determine the damping coefficient and natural frequency of the thin membrane. In this test, the membrane is allowed to fall freely in the chamber with the motion tracked and captured through high velocity video frames. A Kalman filter technique is implemented in the tracking algorithm to reduce noise and increase the tracking accuracy of the oscillating motion. The forced motion experiment, the last test, is performed to determine the deformation characteristics of the object. A high power spotlight (500-2000W) is used to illuminate the MLI and the displacements are measured by means of a high resolution laser sensor. Finite Element Analysis (FEA) and multibody dynamics of the experimental setups are used for the validation of the flexible model by comparing with the experimental results of displacements and natural frequencies.
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The marine dinoflagellate genus Dinophysis includes species that are the causative agents of diarrhetic shellfish poisoning (DSP). Recent findings indicate that some Dinophysis species are mixotrophic, i.e. capable of both autotrophic and heterotrophic nutrition. We investigated inorganic (and organic) carbon uptake by several species of Dinophysis in the Light and dark using the 'single-cell C-14 method', and compared uptake rates with those of photosynthetic Ceratium species and heterotrophic dinoflagellates in the genus Protoperidinium. Experiments were conducted with water from the Gullmar Fjord and from the Koster Strait (Swedish west coast). Nutrient-enriched phytoplankton from surface water samples were concentrated (20 to 70 mu m) and incubated at in situ temperature under artificial light conditions with high concentrations of inorganic C-14 (1 mu Ci ml(-1)). Individual cells of each desired species were manually isolated under a microscope and transferred to scintillation vials. C. tripes showed net C-14 uptake only during light periods, whereas both C. lineatum and C. furca showed C-14 uptake in the Light as well as uptake (and sometimes losses) in the dark. Dinophysis species had similar carbon fixation rates in Light compared to Ceratium species. For D. acuminata and D. norvegica, net carbon uptake occurred in both Light and dark periods. D. acuta showed a loss of carbon in the dark in one experiment, but in another, dark C uptake was significantly higher than uptake in Light. When exposed to Light, C. furca, D. norvegica and D. acuta had high specific carbon uptake rates. Growth rates for the different species were calculated from C-14 uptake by the cells during the first hours of incubation in light. D. acuminata and D. norvegica had similar maximum growth rates, 0.59 and 0.63 d(-1) (mu); the maximum growth rate of D. acuta was lower (0.41 d(-1)). The positive dark carbon uptake by Dinophysis may suggest a mixotrophic mode of nutrition. In one experiment, both D. norvegica and D. acuta showed a significantly higher carbon uptake in a dark bottle than in a Light bottle, which would be consistent with uptake of C-14-labeled organic matter by D. norvegica and D. acuta. Demonstration of direct uptake of dissolved and particulate organic matter would provide conclusive evidence of mixotrophy and this will require the development of new protocols for measuring organic matter uptake applicable to Dinophysis in the natural assemblages.
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The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.
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Overrecentdecades,remotesensinghasemergedasaneffectivetoolforimprov- ing agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hierarchically structured, the determination of optimal study scales is mandatory in understanding these processes and their interactions. The concept of multi-scale/multi- resolution inherent to OBIA methodologies allows the scale problem to be dealt with. But for that multi-scale and hierarchical segmentation algorithms are required. The question that remains unsolved is to determine the suitable scale segmentation that allows different objects and phenomena to be characterized in a single image. In this work, an adaptation of the Simple Linear Iterative Clustering (SLIC) algorithm to perform a multi-scale hierarchi- cal segmentation of satellite images is proposed. The selection of the optimal multi-scale segmentation for different regions of the image is carried out by evaluating the intra- variability and inter-heterogeneity of the regions obtained on each scale with respect to the parent-regions defined by the coarsest scale. To achieve this goal, an objective function, that combines weighted variance and the global Moran index, has been used. Two different kinds of experiment have been carried out, generating the number of regions on each scale through linear and dyadic approaches. This methodology has allowed, on the one hand, the detection of objects on different scales and, on the other hand, to represent them all in a sin- gle image. Altogether, the procedure provides the user with a better comprehension of the land cover, the objects on it and the phenomena occurring.
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This dissertation, comprised of three separate studies, focuses on the relationship between remote work adoption and employee job performance, analyzing employee social isolation and job concentration as the main mediators of this relationship. It also examines the impact of concern about COVID-19 and emotional stability as moderators of these relationships. Using a survey-based method in an emergency homeworking context, the first study found that social isolation had a negative effect on remote work productivity and satisfaction, and that COVID-19 concerns affected this relationship differently for individuals with high and low levels of concern. The second study, a diary study analyzing hybrid workers, found a positive correlation between work from home (WFH) adoption and job performance through social isolation and job concentration, with emotional stability serving respectively as a buffer and booster in the relationships between WFH and the mediators. The third study, even in this case a diary study of hybrid workers, confirmed the benefits of work from home on job performance and the importance of job concentration as a mediator, while suggesting that social isolation may not be significant when studying employee job performance, but it is relevant for employee well-being. Although each study provides autonomously a discussion and research and practical implications, this dissertation also presents a general discussion on remote work and its psychological implications, highlighting areas for future research