Colour consistency in computer vision : a multiple image dynamic exposure colour classification system : a thesis presented to the Institute of Natural and Mathematical Sciences in fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, Auckland, New Zealand

Colour classification vision systems face difficulty when a scene contains both very bright and dark regions. An indistinguishable colour at one exposure may be distinguishable at another. The use of multiple cameras with varying levels of sensitivity is explored in this thesis, aiding the classification of colours in scenes with high illumination ranges. Titled the Multiple Image Dynamic Exposure Colour Classification (MIDECC) System, pie-slice classifiers are optimised for normalised red/green and cyan/magenta colour spaces. The MIDECC system finds a limited section of hyperspace for each classifier, resulting in a process which requires minimal manual input with the ability to filter background samples without specialised training. In experimental implementation, automatic multiple-camera exposure, data sampling, training and colour space evaluation to recognise 8 target colours across 14 different lighting scenarios is processed in approximately 30 seconds. The system provides computationally effective training and classification, outputting an overall true positive score of 92.4% with an illumination range between bright and dim regions of 880 lux. False positive classifications are minimised to 4.24%, assisted by heuristic background filtering. The limited search space classifiers and layout of the colour spaces ensures the MIDECC system is less likely to classify dissimilar colours, requiring a certain ‘confidence’ level before a match is outputted. Unfortunately the system struggles to classify colours under extremely bright illumination due to the simplistic classification building technique. Results are compared to the common machine learning algorithms Naïve Bayes, Neural Networks, Random Tree and C4.5 Tree Classifiers. These algorithms return greater than 98.5% true positives and less than 1.53% false positives, with Random Tree and Naïve Bayes providing the best and worst comparable algorithms, respectively. Although resulting in a lower classification rate, the MIDECC system trains with minimal user input, ignores background and untrained samples when classifying and trains faster than most of the studied machine learning algorithms.Colour classification vision systems face difficulty when a scene contains both very bright and dark regions. An indistinguishable colour at one exposure may be distinguishable at another. The use of multiple cameras with varying levels of sensitivity is explored in this thesis, aiding the classification of colours in scenes with high illumination ranges. Titled the Multiple Image Dynamic Exposure Colour Classification (MIDECC) System, pie-slice classifiers are optimised for normalised red/green and cyan/magenta colour spaces. The MIDECC system finds a limited section of hyperspace for each classifier, resulting in a process which requires minimal manual input with the ability to filter background samples without specialised training. In experimental implementation, automatic multiple-camera exposure, data sampling, training and colour space evaluation to recognise 8 target colours across 14 different lighting scenarios is processed in approximately 30 seconds. The system provides computationally effective training and classification, outputting an overall true positive score of 92.4% with an illumination range between bright and dim regions of 880 lux. False positive classifications are minimised to 4.24%, assisted by heuristic background filtering. The limited search space classifiers and layout of the colour spaces ensures the MIDECC system is less likely to classify dissimilar colours, requiring a certain ‘confidence’ level before a match is outputted. Unfortunately the system struggles to classify colours under extremely bright illumination due to the simplistic classification building technique. Results are compared to the common machine learning algorithms Naïve Bayes, Neural Networks, Random Tree and C4.5 Tree Classifiers. These algorithms return greater than 98.5% true positives and less than 1.53% false positives, with Random Tree and Naïve Bayes providing the best and worst comparable algorithms, respectively. Although resulting in a lower classification rate, the MIDECC system trains with minimal user input, ignores background and untrained samples when classifying and trains faster than most of the studied machine learning algorithms

Thin plate buckling mitigation and reduction challenges for naval ships

Thin plate buckling or distortion on ship structures is an ongoing issue for shipbuilders. It has been identified that a significant number of factors can be put in place based on prior knowledge and good practice. Additionally, research work aimed at reducing thin plate distortion has been relatively prolific, particularly in the area of simulation modelling. However, the uptake in the research findings by industry has been relatively low. A number of these findings are discussed and their application considered. For any further reductions in thin plate distortion to be generated there is a clear need for better interaction between the research institutes and the industry

Holiday Homework

Clever coeds are dreaming up exciting ways of personalizing every package under the Christmas tree this year

Automating the synthesis of platinum(II) complexes and modifying the pharmacokinetics of platinum(IV) complexes

New complexes proposed for anticancer treatments hope to mitigate these issues by utilising different mechanisms of action. Polyaromatic platinum complexes are an example of a class of promising new complexes that have a different mechanism of action than the traditional platinum drugs. In this work the method for the synthesis of a series of novel platinum(IV) polyaromatic complexes was developed and these complexes were characterised using ESIMS, UV spectroscopy, CD spectroscopy, SRCD spectroscopy, microanalysis, NMR and HPLC. These complexes were synthesised via the coordination of halides Cl, Br and I in the axial positions producing the di-halogenated platinum(IV) complexes desired. The effectiveness of substitution in the axial position by various ligands was assessed, as well as the cytotoxicity of the resulting compounds in cell lines. It was revealed that these compounds allow the development of new synthetic methods which were previously closed to these complexes, allowing the synthesis of targeted complexes that have the potential to improve prognosis. The developed method is much less time consuming than the current oxidation methods, reducing time spent on synthesising intermediates which will maximise outcomes for further synthesis. The GI50’s revealed that these complexes are of comparable cytotoxicity to the platinum(II) complexes and are more cytotoxic than dihydroxido platinum(IV) complexes of the same type. Further development of these complexes was achieved through the linkage of targeting and cytotoxic ligands. These ligands were provided by collaborators and will undergo biological testing in their respective laboratories. DCF, a cytotoxic ligand, was bound in both axial positions through an ethylene diamine linker. The synthesis was confirmed by NMR, providing proof of concept for the attachment of such ligands, further diversifying the skillset of the research group. The PSMA targeting ligand DCL was bound using a succinate linker to one of the axial ligands. This synthesis provided proof of concept for the synthesis of asymmetric compounds with large targeting ligands; whose pharmacokinetics can be further adjusted through derivatisation of the remaining axial ligand. The synthesis of more novel asymmetric complexes was developed, platinum compounds with both a hydroxido and acetardo ligand. The asymmetric design of these compounds will allow further asymmetric derivatisation of the Pt(IV) which may be advantageous in the design and synthesis of multi action drugs

M.L.

APPLE-BLOSSOM shampoo, whipped to creamy-fluffiness, trickled behind Mary Lou\u27s ears, over her face, down her smooth, young body. She bent her head back, letting the water drum on her forehead . . . sweeping her long, black hair into the water-fall that rushed down her back..

The Future of Natural History Museums

Dorfman, E. (ed.) The Future of Natural History Museums, Routledge, paperback, £31.99, pp. 268

The Inadequate Adolescent Soldier

The concept of the "Inadequate Personality" or "Inadequate Adolescent Soldier" is described. Methods of Selection Procedure are discussed in some detail and it is shown that even with an efficient Selection Service the Inadequate Personality, the border-line Psychoneurotic and the occasional near Psychotic, gains access into the Army. As such individuals have soon to be discharged from the Army, with a consequent loss in manpower, the concept of the Inadequate Personality as a clinical entity amenable to treatment is discussed as a possibility. The clinical assessment of the Inadequate Adolescent Soldier is fully described, and some case records are given. Attempts at treatment with Dehydroisoandrosterone are described and, as this did not prove successful, detailed routine Psychoendocrine investigations which were next attempted are given in some detail. Finally, reasons for lack of success in this sphere are discussed and some indication given as to the relative importance of personality, environment and motivation

With This Ring

Third finger, left hand! Something sparkling there is the symbol of dreams come true. Your future shines there on your hand