Developing and maintaining software is a difficult task, and finding effective methods of understanding software is more necessary now than ever with the last few decades seeing a dramatic climb in the scale of software. Appropriate visualisations may enable greater understanding of the datasets we deal with in software engineering. As an aid for sense-making, visualisation is widely used in daily life (through graphics such as weather maps and road signs), as well as in other research domains, and is thought to be exceedingly beneficial. Unfortunately, there has not been widespread use of the multitude of techniques which have proposed for the software engineering domain. Tag clouds are a simple, text-based visualisation commonly found on the internet. Typically, implementations of tag clouds have not included rich interactive features which are necessary for data exploration. In this thesis, I introduce design considerations and a task set for enabling interaction in a tag cloud visualisation system. These considerations are based on an analysis of challenges in visualising software engineering data, and the perceptive influences of visual properties available in tag clouds. The design and implementation of interactive system Taggle based on these considerations is also presented, along with its broad-based evaluation. Evaluation approaches were informed by a systematic mapping study of previous tag cloud evaluation, providing an overview of existing research in the domain. The design of Taggle was improved following a heuristic evaluation by domain experts. Subsequent evaluations were divided into two parts - experiments focused on the tag cloud visualisation technique itself, and a task-based approach focused on the whole interactive system. As evidenced in the series of evaluative studies, the enhanced tag cloud features incorporated into Taggle enabled faster visual search response time, and the system could be used with minimal training to discover relevant information about an unknown software engineering dataset.

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

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Magistro kvalifikaciniame darbe analizuojama „Debesų“ technologija sukurta verslo valdymo sistema „NetSkaita“. Darbo tikslas yra ištirti “Debesų” technologijos pritaikomumą versle. Tyrimui buvo pasirinkta SSGG (angl. SWOT) ir PEST analizės. Tyrimo metu gauti rezultatai atskleidė produkto „NetSkaita“ silpnąsias ir stipriąsias savybęs, galimybes ir grėsmes. Taip pat buvo pateiktas grėsmių ir silpnybių planas įmonei UAB“Prototechnika“, kuriuo vadovajantis, įmonė galėtų sustiprinti savo „NetSkaita“ produktą. Išorinės aplinkos vertinimui atlikta PEST analizė, kuri parodė makroaplinkos įtaką produktui. Magistro darbas turi išliekamąją praktinę vertę. Panaudojant tyrimo medžiagą, UAB „Prototechnika“ galės numatyti produkto grėsmes ir silpnybes, o pasinaudojus stiprybėmis ir galimybėmis, sustiprinti verslo valdymo sistemos, paremtos „Debesų“ technologija konkureciją rinkoje, išlikti joje ir sėkmingai konkuruoti su kitomis įmonėmis. / In this Master Thesis is analysed „Clouds“ technology, which was created to a business management system „NetSkaita“. The main purpose of this work is to investigate „Clouds“ technology adaptability to a business management systems. In the research two methods were chosen, such as SWOT and PEST analysis. The results of research revealed the strongest and weakness parts also opportunities and threats of product „NetSkaita“. A Plan of possible threats and possible weakness was suggested to organisation “Prototechnika“, which could help in product „NetSkaita“ consolidation in the market. In Outside environment‘s estimation PEST analysis was chosen to apply, which helped to reveal macroenvironment‘s influence to a product. This Master Thesis has a survival practical value. Using research material, organisation „Prototechnika“ will have opportunity to foresee the main weakness and threats of their product and with using opportunities and strongest parts - to strenghten, business management system, supported with „Clouds“ technology competition in the marked and be competitive with other organisations.

Microphysical and dynamical interactions between aerosols and clouds are associated with some of the largest uncertainties in projections of future climate. Many possible aerosol effects on clouds have been suggested, but large uncertainties remain. In order to improve model projections of future climate, it is essential that we improve our quantitative understanding of anthropogenic aerosol effects. Several studies investigating interactions between satellite-observed aerosol and cloud properties have been published in recent years. However, the observed relationships are not necessarily due to aerosol effects on clouds. They may be due to cloud and precipitation effects on aerosol, meteorological covariation, observational data errors or methodological errors. An analysis of methodological errors arising through climatological spatial gradients is performed. For region sizes larger than 4°×4°, commonly used in the literature, spurious spatial variations in retrieved cloud and aerosol properties are found to introduce widespread significant errors to calculations of aerosol-cloud relationships. Small scale analysis prior to error-weighted aggregation to larger region sizes is recommended. Appropriate ways of quantifying relationships between aerosol optical depth (τ) and cloud properties are considered, and results are presented for three satellite datasets. There is much disagreement in observed relationships between τ and liquid cloud droplet number concentration and between τ and liquid cloud droplet effective radius, particularly over land. However, all three satellite datasets are in agreement about strong positive relationships between τ and cloud top height and between τ and cloud fraction (f_c). Using reanalysis τ data, which are less affected by retrieval artifacts, it is suggested that a large part of the observed f_c-τ signal may be due to cloud contamination of τ. General circulation model simulations further demonstrate that positive f_c-τ relationships may primarily arise due to covariation with relative humidity, and that negative f_c-τ relationships may arise due to scavenging of aerosol by precipitation. A new method of investigating the contribution of meteorological covariation to the observed relationships is introduced. Extratropical cyclone storm-centric composites of retrieved aerosol and cloud properties are investigated. A storm-centric description of the synoptics is found to be capable of explaining spurious f_c-τ relationships, although the spurious relationships explained are considerably smaller than observed relationships.

The next generation of ground-based optical/infrared (IR) telescopes will have primary mirrors of up to 42 m. To take advantage of the large potential increase in angular resolution, adaptive optics will be essential to overcome the resolution limits set by atmospheric turbulence. Novel techniques such as Multi-Conjugate Adaptive Optics (MCAO) and Multi-Object Adaptive Optics (MOAO) are being developed to achieve near diffraction-limited images over large fields-of-view. This thesis concerns the development of MCAO and MOAO pathfinders. Specifically, the construction of CANARY, aMOAO demonstrator, and the on-sky performance and scientific exploitation of the Multi-conjugate Adaptive optics Demonstrator (MAD). CANARY is under construction for the William Herschel Telescope (WHT) in La Palma and contains a telescope simulator to allow testing of the set-up in the laboratory. The simulator contains a natural guide star emulator, turbulence phase screens, and telescope relay optics. The work presented here concerns the integration of the various components in relation to numerical models and the CANARY specifications. MAD was a near-IR imager on the Very Large Telescope (VLT) in Chile. Science demonstration observations were taken of R136, the young, massive cluster situated in the 30 Doradus star-forming region in the Large Magellanic Cloud. These data were used here to determine the MCAO performance across the ~1’x1’ field-of-view, for different pointings with respect to the guide stars, finding high Strehl ratios and relatively uniform corrections across the fields. The MAD data are then used to construct radial surface brightness profiles for R136, providing new insights into intriguing past results from the Hubble Space Telescope. The MAD data reveal that the profile is strongly asymmetric, removing the need for dramatic dynamical evolution of the cluster in the recent past, and highlighting the importance of considering asymmetries when analysing clusters further afield. The MAD data, combined with other near-IR imaging from the VLT, are then used to investigate the nature of candidate young stellar objects from recent observations with the Spitzer Space Telescope.

We present spectral line mapping observations towards four massive star-forming regions Cepheus A, DR21S, S76E and G34.26+0.15 - with the IRAM 30-m telescope at the 2 and 3 mm bands. In total, 396 spectral lines from 51 molecules, one helium recombination line, 10 hydrogen recombination lines and 16 unidentified lines were detected in these four sources. An emission line of nitrosyl cyanide (ONCN, 14(0), 14-13(0), (13)) was detected in G34.26+0.15, as the first detection in massive star-forming regions. We found that c-C3H2 and NH2D show enhancement in shocked regions, as suggested by the evidence of SiO and/or SO emission. The column density and rotational temperature of CH3CN were estimated with the rotational diagram method for all four sources. Isotope abundance ratios of C-12/C-13 were derived using HC3N and its C-13 isotopologue, which were around 40 in all four massive star-forming regions and slightly lower than the local interstellar value (similar to 65). The N-14/N-15 and O-16/O-18 abundance ratios in these sources were also derived using the double isotopic method, which were slightly lower than in the local interstellar medium. Except for Cep A, the S-33/S-34 ratios in the other three targets were derived, which were similar to that in the local interstellar medium. The column density ratios of N(DCN)/N(HCN) and N( DCO+)/N(HCO+) in these sources were more than two orders of magnitude higher than the elemental [D]/[H] ratio, which is 1.5 x 10(-5). Our results show that the later stage sources, G34.26+0.15 in particular, present more molecular species than earlier stage sources. Evidence of shock activity is seen in all stages studied.

Approved for public release, distribution is unlimited / An analysis of in-situ aircraft observations collected in the parent cloud of a waterspout is presented. Previous waterspout studies were confined mainly to photometric and model simulated data, no in-situ observations were made internal to the parent cloud. On 27 June 2002 the Cooperative Institute for Remotely Piloted Aircraft Studies (CIRPAS) UV-18A Twin Otter aircraft collected observations in a cloud that had developed in a cloud line, located approximately 15km south of Key West, and that formed a waterspout. This study attempts to analyze the waterspout formation process using these data and through a series of scale interactions, from the synoptic scale down to the individual cloud scale. Based upon the analyzed data a hypothetical formation process is developed. The background synoptic scale flow is shown to establish the necessary ambient shear as a key factor in the waterspout formation. The orientation of mesoscale convergent boundaries and thermodynamic processes, internal to the cloud, proved to be an essential factor in developing the vertical motion patterns necessary for formation of an organized circulation in the shear region and to provide the tipping and stretching of the resultant vortex necessary to account for the waterspout formation. This is consistent with conclusions derived from previous studies. / Captain, United States Air Force

Aerosole dienen als Kondensationskerne (CCN) und verändern die Wolkentropfenkonzentration (Nd) und weitere Wolkeneigenschaften. Nd ist daher ein Schlüsselparameter von Aerosol-Wolken-Wechselwirkungen (ACI). ACI sind bezüglich ihrer Klimarelevanz nur unzureichend bestimmt. ACI wurden auf verschiedenen Skalen und mit unterschiedlichen Methoden von unterschiedlichen Perspektiven aus untersucht, was zu einer großen Variabilität von ACI Metriken in der Literatur führt. Für eine genauere Quantifizierung von ACI, wurden in dieser Arbeit damit verbundene, entscheidende Unsicherheiten diskutiert, u.a. das Einmischen trockener Luft, Unsicherheiten von Retrieval-Methoden und die Konsistenz von Schlüsselparametern auf verschiedenen Skalen. Um Nd und weitere Wolkeneigenschaften aus passiven Satellitenbeobachtungen für Flüssigwasserwolken abzuleiten, wird oft das adiabatische Modell herangezogen. Es wurde untersucht, inwiefern dieses Modell reale Bedingungen wiedergibt. Es wurde gezeigt, dass Wolken typischerweise subadiabatisch sind, mit stark reduziertem Flüssigwassergehalt nahe der Wolkenoberkante. Der Einmischprozess variiert zeitlich stark und erschwert die Quantizierung von ACI. Für unterschiedliche Cloudnet-Stationen variieren die Medianwerte des subadiabatischen Faktors von 0.35+/-0.12 bis 0.48+/-0.22. Dieser hängt stark von der geometrischen Wolkendicke ab, wobei dickere Wolken subadiabatischer sind. Die Ableitung von Nd aus bodenbasierten Radar-Radiometer-Beobachtungen ist sehr sensitiv gegenüber a-priori Annahmen. Um zusätzliche Beobachtungen und Unsicherheiten berücksichtigen zu können, wurde ein neuartiges Optimal Estimation (OE) Retrieval entwickelt und mittels synthetischer Wolkenprofile evaluiert. Mittels einer Sensitivitätsstudie konnte die Verbesserung der Retrieval-Genauigkeit für die OE Methode gezeigt werden, wenn die Beobachtungen der optischen Dicke mit berücksichtigt werden. Die Annahme einer typischen Breite der Tropfengrößenverteilung ist dabei eine der größten Unsicherheiten von Nd (Unsicherheit für die OE Methode etwa 150%, für die Radar-Radiometer-Methode etwa 200%). Desweiteren wurden aus unterschiedlichen Perspektiven abgeleitete wolkenmikrophysikalische Größen hinsichtlich ihrer Konsistenz untersucht. Beim Vergleich von Nd und des Effektivradius (re) vom bodengebundenen Retrieval mit in-situ Beobachtungen für einen Falltag wurde eine gute Übereinstimmung gefunden. Beim Vergleich der von SEVIRI und Bodenstationen abgeleiteten Wolkeneigenschaften haben sich mittlere quadratische Abweichungen des Flüssigwasserpfads und der optischen Dicke von jeweils 65 gm2 und 14 ohne signifikanten Bias gezeigt. Damit zeigt sich SEVIRI für großskalige, statistische ACI-Untersuchungen repräsentativ zur Bodenperspektive. Für individuelle Falltage traten jedoch teils größere Unterschiede auf, welche durch Inhomogenitäten und Auflösungseffekte erklärt werden können. Mit SEVIRI Beobachtungen und aus der MACC Reanalyse abgeleiteten CCN Konzentrationen wurde eine Quantifizierung von ACI für das Jahr 2012 durchgeführt. Dabei wurde für Europa ein deutlicher, mikrophysikalischer Effekt gefunden, d.h. eine Abnahme von re und eine Zunahme von Nd mit zunehmender CCN Konzentration. Im Gegensatz dazu wurde für die Wolkenalbedo kein eindeutiger Anstieg mit der CCN-Konzentration gefunden. Verwendet man die Aerosol-optische Dicke (AOD) anstelle der CCN-Konzentration, sind die Werte der ACI Metrik nur halb so groß. Dieses Ergebnis deutet darauf hin, dass die AOD kein optimaler CCN-Proxy ist.

No description available.