Acceptability-based Brand Color Tolerance, A Case Study

The Pantone R Formula Guide (or Guide), printed using specially-formulated inks on specified substrates, has been used widely by brands to specify brand color aims. While the Guide is silent on brand color tolerance, there are two competing criteria that influence the brand color tolerance, i.e., perceptibility and acceptability. Perceptibility-based color tolerance focuses on “Can I see the difference?” and the permissive difference is in the just-noticeable difference (JND) region. Acceptability-based color tolerance, focusing on “Can I accept the outcome?”, requires fit-for-use cases to identify what the just-acceptable difference (JAD) is. Instead of conducting psychometric tests, this research uses the 2019 Pantone R Formula (Coated) Guide, consisting of 2140 CIELAB colors, and data analyses of the “neighboring color difference” to investigate what is the acceptability-based color tolerance. The result shows that the acceptability-based color tolerance (3 1E00) has more margin than the perceptibility-based color tolerance (2 1E00

On fields inspired with the polar HSV - RGB theory of Colour

This paper was supported by Grant VEGA 2/0178/14 and by the Slovak-Ukrainian joint research project "Vector valued measures and integration in polarized vector spaces

Unfolded Adinkra Properties of Supermultiplets (I)

Adinkra networks arise in the Carroll limit of supersymmetric QFT. Extensions of adinkras that are infinite dimensional graphs have never previously been discussed in the literature. We call these "infinite unfolded'' adinkras and study the properties of their realization on familiar 4D, $\cal N$ = 1 supermultiplets. A new feature in "unfolded'' adinkras is the appearance of quantities whose actions resemble BRST operators within Verma-like modules. New "net-centric" quantities ${\widetilde \chi}_{(1)}$ and ${\widetilde \chi}_{(2)}$ are introduced, which along with quantity $\chi_{\rm o}$, describe distinctions between familiar supermultiplets in 4D, $\cal N$ = 1 theories. A previously unobserved property in all adinkras that we call "adinkra vorticity" is noted.Comment: LaTex twice, 52 pages, 19 figures, and 4 tabl

Exploiting Social Networks for Recommendation in Online Image Sharing Systems

This thesis aims to demonstrate the distinct and so far little explored value of knowledge derived from social interaction data within large web-scale image sharing systems like Flickr, Picasa Web, Facebook and others for image recommendation. I have shown how such systems can be significantly improved through personalisation that takes into account the social context of users by modelling their interactions by mining data, building and evaluating systems that incorporate this information. These improvements allow users to search and browse large online image collections more quickly and to find results that more accurately match their personal information needs when compared to existing methods. Traditional information retrieval and recommendation datasets are contrived to provide stable baselines for researchers to compare against but they rarely accurately reflect the media systems users tend to encounter online. The online photo sharing site Flickr provides rich and varied data that can be used by researchers to analyse and understand users’ interactions with images and with each other. I analyse such data by modelling the connections between users as multigraphs and exploiting the resultant topologies to produce features that can be used to train recommender systems based on machine learnt classifiers. The core contributions of this work include insight into the nature of very large-scale on- line photo collections and the communities that form around them, as well as the dynamic nature of the interactions users have with their media. I do this through the rigorous evaluation of both a probabilistic tag recommendation system and a machine learnt classifier trained to mimic user decisions regarding image preference. These implementations focus on treating the user as both a unique individual and as a member of potentially many explicit and implicit communities. I also explore the validity of the Flickr ‘Favourite’ feedback label as proxy for user preference, which is particularly important when considering other analogous media systems to which my findings transfer. My conclusions highlight how vital both social context information and the understanding of user behaviour are for online image sharing systems. In the field of information retrieval the diverse nature of users is often forgotten in the hunt for increases in esoteric performance metrics. This thesis places them back at the centre of the problem of multimedia information retrieval and shows how their variety and uniqueness are valuable traits that can be exploited to augment and improve the experience of browsing and searching shared online image collections

Instrument design and optimization of interferometric reflectance imaging sensors for in vitro diagnostics

Thesis (Ph.D.)--Boston UniversityIn the field of drug discovery and disease diagnostics, protein microarrays have generated much enthusiasm for their high-throughput monitoring of biomarkers; however, this technology has yet to translate from research laboratories to commercialization. The hindrance is the considerable uncertainty and skepticism regarding data obtained. The disparity in results from different laboratories performing identical tests is attributed to a lack of assay quality control. Unlike DNA microarrays, protein microarrays have a higher level of bioreceptor immobilization variability and non-specific binding because of the more complex molecular structure and broader physiochemical properties. Traditional assay detection modalities, such as fluorescence microscopy and surface plasmon resonance, are unable to overcome both of these sources of variation. This dissertation describes the hardware and software design and biological validation of three complementary platforms that overcome bioreceptor variability and non-specific binding for diagnostics. In order to quantify the bioreceptor quality, a label-free, nondestructive, low cost, and high-throughput interferometric sensor has been developed as a quality control tool. The quality control tool was combined with a wide-field fluorescence imaging system to improve fluorescence experimental repeatability. Lastly, a novel high-throughput and label-free platform for quality control and specific protein microarray detection is described. This platform overcomes the additional complexities and time required with labeled assays by discriminating between specific and nonspecific detection by including sizing of individual binding events. Protein microarrays may one day emerge as routine clinical laboratory tests; however, it is important that the proper quality control procedures are in place to minimize erroneous results. These platforms provide reliable and repeatable protein microarray measurements for new advancements in disease diagnostics with the potential for drug discovery

A Symmetric Interaction Model for Bimanual Input

People use both their hands together cooperatively in many everyday activities. The modern computer interface fails to take advantage of this basic human ability, with the exception of the keyboard. However, the keyboard is limited in that it does not afford continuous spatial input. The computer mouse is perfectly suited for the point and click tasks that are the major method of manipulation within graphical user interfaces, but standard computers have a single mouse. A single mouse does not afford spatial coordination between the two hands within the graphical user interface. Although the advent of the Universal Serial Bus has made it possible to easily plug in many peripheral devices, including a second mouse, modern operating systems work on the assumption of a single spatial input stream. Thus, if a second mouse is plugged into a Macintosh computer, a Windows computer or a UNIX computer, the two mice control the same cursor. Previous work in two-handed or bimanual interaction techniques has often followed the asymmetric interaction guidelines set out by Yves Guiard's Kinematic Chain Model. In asymmetric interaction, the hands are assigned different tasks, based on hand dominance. I show that there is an interesting class of desktop user interface tasks which can be classified as symmetric. A symmetric task is one in which the two hands contribute equally to the completion of a unified task. I show that dual-mouse symmetric interaction techniques outperform traditional single-mouse techniques as well as dual-mouse asymmetric techniques for these symmetric tasks. I also show that users prefer the symmetric interaction techniques for these naturally symmetric tasks

Dynamic characterization of multi-scale analytes by real time interferometric imaging

In the past decade, the field of biosensing has experienced an incredible pace of development, due to the compelling need for accurate and reliable tools for characterization of biomolecular kinetics. Specifically, label-free kinetic measurements are the most direct method for studying molecular binding, for example to establish the efficacy of drug-receptor interactions. For this reason, researchers in the pharmaceutical industry rely heavily on label-free detection for drug and antibody screening. Meanwhile, in the biosafety industry and healthcare, there is great demand for screening tools that can target biothreats, in order to accurately recognize the presence of toxins and pathogens with high sensitivity in diverse samples, such as bodily fluids, food and drinking water. This research topic has become particularly relevant during the recent pandemic, where vaccine development was carried out side by side with quantification and characterization of single viral particles. Here, we introduce a versatile biosensing platform capable of characterizing virtually any type of target compound, down to the single molecule level. For this work, we have improved the Interferometric Reflectance Imaging Sensor (IRIS) to perform accurate measurements of the binding kinetics of analytes ranging in molecular weight from less than 1kDa (small molecules) to more than 1MDa (biological nanoparticles). For the first time, we demonstrate multiplexed kinetic binding characterization of small molecules to surface immobilized antibody probes, as well as detection and phenotyping of large and complex analytes, on the same platform. The IRIS platform utilizes the optical interference signal produced by thinly layered substrates in order to precisely measure the thickness of a transparent film atop a silicon chip. In the context of this work, dynamic characterization of a wide range of biomolecular and nanoparticle targets was made possible by a multidimensional optimization, in order to improve both the sensitivity and the dynamic range of the instrument. Analysis of low molecular weight compounds required a significant increase in signal to noise ratio, which was achieved through averaging, as well as complete elimination of background solution effects ('bulk effect’). Additionally, the best surface chemistry for each application was identified by a new technique which consists of immobilizing capture probes on a multiplexed array of active polymers functionalized on the same sensor surface, allowing for simultaneous side-by-side comparison of their performance. Surface chemistry plays a huge role in kinetic measurements, in terms of probe functionality, steric hindrance, charge distribution and diffusion effects. Finally, imaging optics, illumination wavelength, and thickness of the silicon dioxide film were optimized to perform detection and phenotyping of large analytes, such as extracellular vesicles (EVs) and antibody-conjugated gold nanoparticles (mAb-GNPs). Results obtained from numerical simulations allowed for selection of the best experimental parameters for each application. Experimentally, mAb-GNPs were utilized to produce a real-time sandwich lateral flow assay. In this context, we demonstrated how the improved IRIS platform can bridge the gap between single-particle detection ('digital’ configuration) and bulk reflectance measurements ('analog’ configuration), creating a new 'hybrid' system (h-IRIS), which only requires minimal hardware adjustments to easily switch from one modality to the other. This brought a substantial improvement in sensitivity, improving the limit of detection by three orders of magnitude and enabling single-molecule level measurements. Finally, future system optimization ideas are presented to achieve even higher accuracy and further extend the range of target analytes

Algorithms for colour image processing based on neurological models

373 p. : il., gráf., fot., tablasColour image processing is nowadays mostly achieved through the extrapolation of algorithms developed for images in grey levels into three colour planes, either RGB or some transformed planes, such as HSI, CIELAB... These techniques provide reliable solutions only in simple situations. As colour is a perception and not a characteristic inherent to objects, this thesis has developed new bioinspired algorithms for colour image processing. The work of this thesis has joined elements in colour theory and processing undertaken in the human visual system. A new functional model of the retina has been developed where each cell type has been characterised according to its connections, distribution and size. A retina architecture has been created which provides detailed information about its cell elements and organisation. This has allowed the creation of a retina model that generates a set of parallel output channels as happens in the human retina. The level of detail provided in the model has allowed the characterisation of each of the pathways with a precision that is not present in existing models described in scientific publications. The development of a colour processing model requires the combination of a functional retina model with colour appearance models. This union has achieved a new algorithm for colour image processing that provides colour attributes, such as: hue, lightness, brightness, saturation, chroma, colourfulness as well as edge detection components both in chromatic as well as achromatic components. The results provided by this model have been compared with CIECAM02 model's ones and have obtained noticeably better results in the "ab" plane and in the attributes calculated on Munsell colour samples. The colour processing model is backed by its results and has allowed identifying output channels of the retina that make up the usual "a", "b" and "A" channels in colour appearance models. This model entails a step forward on colour processing techniques that shall be of great use for image segmentation, characterisation and object identification. Key Words Colour image processing, neuroinspired models, computational modelling, colour appearance models. Colour image processing is nowadays mostly achieved through the extrapolation of algorithms developed for images in grey levels into three colour planes, either RGB or some transformed planes, such as HSI, CIELAB... These techniques provide reliable solutions only in simple situations. As colour is a perception and not a characteristic inherent to objects, this thesis has developed new bioinspired algorithms for colour image processing. The work of this thesis has joined elements in colour theory and processing undertaken in the human visual system. A new functional model of the retina has been developed where each cell type has been characterised according to its connections, distribution and size. A retina architecture has been created which provides detailed information about its cell elements and organisation. This has allowed the creation of a retina model that generates a set of parallel output channels as happens in the human retina. The level of detail provided in the model has allowed the characterisation of each of the pathways with a precision that is not present in existing models described in scientific publications. The development of a colour processing model requires the combination of a functional retina model with colour appearance models. This union has achieved a new algorithm for colour image processing that provides colour attributes, such as: hue, lightness, brightness, saturation, chroma, colourfulness as well as edge detection components both in chromatic as well as achromatic components. The results provided by this model have been compared with CIECAM02 model's ones and have obtained noticeably better results in the "ab" plane and in the attributes calculated on Munsell colour samples. The colour processing model is backed by its results and has allowed identifying output channels of the retina that make up the usual "a", "b" and "A" channels in colour appearance models. This model entails a step forward on colour processing techniques that shall be of great use for image segmentation, characterisation and object identification. Key Words - Colour image processing, neuroinspired models, computational modelling, colour appearance models.El Gobierno Vasco ha proporcionado apoyo financiero a través del programa ETORTEK, para las estancias en el Instituto Técnico de Massachusetts (MIT) y en la Universidad de Cambridge

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII