Automated color correction for colorimetric applications using barcodes

[eng] Color-based sensor devices often offer qualitative solutions, where a material change its color from one color to another, and this is change is observed by a user who performs a manual reading. These materials change their color in response to changes in a certain physical or chemical magnitude. Nowadays, we can find colorimetric indicators with several sensing targets, such as: temperature, humidity, environmental gases, etc. The common approach to quantize these sensors is to place ad hoc electronic components, e.g., a reader device. With the rise of smartphone technology, the possibility to automatically acquire a digital image of those sensors and then compute a quantitative measure is near. By leveraging this measuring process to the smartphones, we avoid the use of ad hoc electronic components, thus reducing colorimetric application cost. However, there exists a challenge on how-to acquire the images of the colorimetric applications and how-to do it consistently, with the disparity of external factors affecting the measure, such as ambient light conditions or different camera modules. In this thesis, we tackle the challenges to digitize and quantize colorimetric applications, such as colorimetric indicators. We make a statement to use 2D barcodes, well-known computer vision patterns, as the base technology to overcome those challenges. We focus on four main challenges: (I) to capture barcodes on top of real-world challenging surfaces (bottles, food packages, etc.), which are the usual surface where colorimetric indicators are placed; (II) to define a new 2D barcode to embed colorimetric features in a back-compatible fashion; (III) to achieve image consistency when capturing images with smartphones by reviewing existent methods and proposing a new color correction method, based upon thin-plate splines mappings; and (IV) to demonstrate a specific application use case applied to a colorimetric indicator for sensing CO2 in the range of modified atmosphere packaging, MAP, one of the common food-packaging standards.[cat] Els dispositius de sensat basats en color, normalment ofereixen solucions qualitatives, en aquestes solucions un material canvia el seu color a un altre color, i aquest canvi de color és observat per un usuari que fa una mesura manual. Aquests materials canvien de color en resposta a un canvi en una magnitud física o química. Avui en dia, podem trobar indicadors colorimètrics que amb diferents objectius, per exemple: temperatura, humitat, gasos ambientals, etc. L'opció més comuna per quantitzar aquests sensors és l'ús d'electrònica addicional, és a dir, un lector. Amb l'augment de la tecnologia dels telèfons intel·ligents, la possibilitat d'automatitzar l'adquisició d'imatges digitals d'aquests sensors i després computar una mesura quantitativa és a prop. Desplaçant aquest procés de mesura als telèfons mòbils, evitem l'ús d'aquesta electrònica addicional, i així, es redueix el cost de l'aplicació colorimètrica. Tanmateix, existeixen reptes sobre com adquirir les imatges de les aplicacions colorimètriques i de com fer-ho de forma consistent, a causa de la disparitat de factors externs que afecten la mesura, com per exemple la llum ambient or les diferents càmeres utilitzades. En aquesta tesi, encarem els reptes de digitalitzar i quantitzar aplicacions colorimètriques, com els indicadors colorimètrics. Fem una proposició per utilitzar codis de barres en dues dimensions, que són coneguts patrons de visió per computador, com a base de la nostra tecnologia per superar aquests reptes. Ens focalitzem en quatre reptes principals: (I) capturar codis de barres sobre de superfícies del món real (ampolles, safates de menjar, etc.), que són les superfícies on usualment aquests indicadors colorimètrics estan situats; (II) definir un nou codi de barres en dues dimensions per encastar elements colorimètrics de forma retro-compatible; (III) aconseguir consistència en la captura d'imatges quan es capturen amb telèfons mòbils, revisant mètodes de correcció de color existents i proposant un nou mètode basat en transformacions geomètriques que utilitzen splines; i (IV) demostrar l'ús de la tecnologia en un cas específic aplicat a un indicador colorimètric per detectar CO2 en el rang per envasos amb atmosfera modificada, MAP, un dels estàndards en envasos de menjar.

Mapping the Focal Points of WordPress: A Software and Critical Code Analysis

Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected vulnerabilities. An examination of the influence of digital and computational thinking follows this. The work also explores the intersection of code patching and vulnerability management and how code shapes our sense of control, trust, and empathy, ultimately arguing that a rhetorical-cultural lens can be used to better understand code\u27s controlling influence. Recurring themes throughout these analyses and observations are the connections to power and vulnerability in WordPress\u27 code and how cultural, processual, rhetorical, and ethical implications can be expressed through its code, creating a particular worldview. Code\u27s emergent properties help illustrate how human values and practices (e.g., empathy, aesthetics, language, and trust) become encoded in software design and how people perceive the software through its worldview. These connected analyses reveal cultural, processual, and vulnerability focal points and the influence these entanglements have concerning WordPress as code, software, and platform. WordPress is a complex sociotechnical platform worthy of further study, as is the interdisciplinary merging of theoretical perspectives and disciplines to critically examine code. Ultimately, this project helps further enrich the field by introducing focal points in code, examining sociocultural phenomena within the code, and offering techniques to apply critical code methods

A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization

Inspired by the great success of machine learning (ML), researchers have applied ML techniques to visualizations to achieve a better design, development, and evaluation of visualizations. This branch of studies, known as ML4VIS, is gaining increasing research attention in recent years. To successfully adapt ML techniques for visualizations, a structured understanding of the integration of ML4VISis needed. In this paper, we systematically survey 88 ML4VIS studies, aiming to answer two motivating questions: "what visualization processes can be assisted by ML?" and "how ML techniques can be used to solve visualization problems?" This survey reveals seven main processes where the employment of ML techniques can benefit visualizations:Data Processing4VIS, Data-VIS Mapping, InsightCommunication, Style Imitation, VIS Interaction, VIS Reading, and User Profiling. The seven processes are related to existing visualization theoretical models in an ML4VIS pipeline, aiming to illuminate the role of ML-assisted visualization in general visualizations.Meanwhile, the seven processes are mapped into main learning tasks in ML to align the capabilities of ML with the needs in visualization. Current practices and future opportunities of ML4VIS are discussed in the context of the ML4VIS pipeline and the ML-VIS mapping. While more studies are still needed in the area of ML4VIS, we hope this paper can provide a stepping-stone for future exploration. A web-based interactive browser of this survey is available at https://ml4vis.github.ioComment: 19 pages, 12 figures, 4 table

Development of a secure multi-factor authentication algorithm for mobile money applications

A Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyWith the evolution of industry 4.0, financial technologies have become paramount and mobile money as one of the financial technologies has immensely contributed to improving financial inclusion among the unbanked population. Several mobile money schemes were developed but, they suffered severe authentication security challenges since they implemented two-factor authentication. This study focused on developing a secure multi-factor authentication (MFA) algorithm for mobile money applications. It uses personal identification numbers, one-time passwords, biometric fingerprints, and quick response codes to authenticate and authorize mobile money subscribers. Secure hash algorithm-256, Rivest-Shamir-Adleman encryption, and Fernet encryption were used to secure the authentication factors, confidential financial information and data before transmission to the remote databases. A literature review, survey, evolutionary prototyping model, and heuristic evaluation and usability testing methods were used to identify authentication issues, develop prototypes of native genuine mobile money (G-MoMo) applications, and identify usability issues with the interface designs and ascertain their usability, respectively. The results of the review grouped the threat models into attacks against privacy, authentication, confidentiality, integrity, and availability. The survey identified authentication attacks, identity theft, phishing attacks, and PIN sharing as the key mobile money systems’ security issues. The researcher designed a secure MFA algorithm for mobile money applications and developed three native G-MoMo applications to implement the designed algorithm to prove the feasibility of the algorithm and that it provided robust security. The algorithm was resilient to non-repudiation, ensured strong authentication security, data confidentiality, integrity, privacy, and user anonymity, was highly effective against several attacks but had high communication overhead and computational costs. Nevertheless, the heuristic evaluation results showed that the G-MoMo applications’ interface designs lacked forward navigation buttons, uniformity in the applications’ menu titles, search fields, actions needed for recovery, and help and documentation. Similarly, the usability testing revealed that they were easy to learn, effective, efficient, memorable, with few errors, subscriber satisfaction, easy to use, aesthetic, easy to integrate, and understandable. Implementing a secure mobile money authentication and authorisation by combining multiple factors which are securely stored helps mobile money subscribers and other stakeholders to have trust in the developed native G-MoMo applications