Using RGB colour combination in coloured quick response (QR) code algorithm to enhance QR code capacity

A Quick Response (QR) Code is a two-dimensional barcode that stores characters and can be read by any smartphone camera. The QR code has the capability to encode various data formats and languages; nevertheless, existing black and white QR code offers limited data storage. Even though there exist research on coloured QR Code to increase the storage capacity, requirement for larger data capacity by end user keep increasing. Hence, this thesis proposes a coloured QR Code algorithm which utilizes RGB colour combination to allow a larger data storage. The proposed algorithm integrates the use of compression, multiplexing, and multilayer techniques in encoding and decoding the QR code. Furthermore, it also introduces a partial encoding/decoding algorithm that allows the stored data to be manipulated. The algorithm that includes encoding and decoding processes is based on the red, green, and blue (RGB) colour techniques, which are used to create high capacity coloured QR code. This is realised in the experiments that store American Standard Code for Information Interchange (ASCII) characters. The ASCII text characters are used as an input and performance is measured by the number of characters that can be stored in a single black and white QR code version 40 (i.e. the benchmark) and also the coloured QR code. Other experiment metrics include percentage of missing characters, number of produced QR code, and elapsed time to create the QR code. Simulation results indicate that the proposed algorithm stores 29 times more characters than the black and white QR code and 9 times more than other coloured QR code. Hence, this shows that the coloured QR Code has the potential of becoming a useful mini-data storage as it does not rely on internet connection

Evaluating Sensor Data in the Context of Mobile Crowdsensing

With the recent rise of the Internet of Things the prevalence of mobile sensors in our daily life experienced a huge surge. Mobile crowdsensing (MCS) is a new emerging paradigm that realizes the utility and ubiquity of smartphones and more precisely their incorporated smart sensors. By using the mobile phones and data of ordinary citizens, many problems have to be solved when designing an MCS-application. What data is needed in order to obtain the wanted results? Should the calculations be executed locally or on a server? How can the quality of data be improved? How can the data best be evaluated? These problems are addressed by the design of a streamlined approach of how to create an MCS-application while having all these problems in mind. In order to design this approach, an exhaustive literature research on existing MCS-applications was done and to validate this approach a new application was designed with its help. The procedure of designing and implementing this application went smoothly and thus shows the applicability of the approach

Visualizing the data flow in virtual reality for training developers

The visual aids are powerful tools in learning, understanding, and retaining data, especially in the industrial sector. However, visualizing data for complex systems is an essential challenge as they need to address a discrete and large amount of data. When novice programmers develop these complex systems, they typically require further training on the data flow in order to understand the hidden meaningful patterns. The visualization of invisible data in virtual reality (VR) helps to explore these patterns and direct new avenues to develop a system in the real world. Thus, the presentation of complex data in a 3D visual form is crucial and effective. To accomplish this, this research study considers a case scenario of Indoor Air Quality (IAQ) system based on Internet of Things (IoT). By definition, IoT is a multifarious connection of devices and data over the internet and thus, needs visualization. A better understanding of how visualization in 3D space can assist programmers to learn IoT concepts. In turn, this poses profound questions in the areas of virtual reality and human-computer interaction. Consequently, the aim of this study was to visualize IoT sensor data in a virtual environment and produce guidelines for programmers in order to help them better comprehend the data flow. Subsequent to this, the level of immersion required for an effective VR experience was also investigated. Overall, this study involved background research and an empirical study. The semi-structured interviews were conducted with the programmers and were handled as empirical evidence. This evidence was further analyzed qualitatively. As a result, the static visuals of IoT sensor data values helped the users to understand its flow. The visual clues both from abstract and skeuomorphic designs furthered the users understanding of the concepts. Accompanied by the text, necessary information about the concept was revealed to the end user. The analysis clearly highlights that visualizing in virtual reality enhances the experience by improving user awareness and user engagement level. In addition, this provides a more intuitive understanding of data flow and better recall of the observed relationships

A Modular and Open-Source Framework for Virtual Reality Visualisation and Interaction in Bioimaging

Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data from analysis of such data or simulations. The advent of new imaging technologies, such as lightsheet microscopy, has resulted in the users being confronted with an ever-growing amount of data, with even terabytes of imaging data created within a day. With the possibility of gentler and more high-performance imaging, the spatiotemporal complexity of the model systems or processes of interest is increasing as well. Visualisation is often the first step in making sense of this data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualisations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we present scenery, a modular and extensible visualisation framework for the Java VM that can handle mesh and large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms, and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features, and discuss its use with VR/AR hardware and in distributed rendering. In addition to the visualisation framework, we present a series of case studies, where scenery can provide tangible benefit in developmental and systems biology: With Bionic Tracking, we demonstrate a new technique for tracking cells in 4D volumetric datasets via tracking eye gaze in a virtual reality headset, with the potential to speed up manual tracking tasks by an order of magnitude. We further introduce ideas to move towards virtual reality-based laser ablation and perform a user study in order to gain insight into performance, acceptance and issues when performing ablation tasks with virtual reality hardware in fast developing specimen. To tame the amount of data originating from state-of-the-art volumetric microscopes, we present ideas how to render the highly-efficient Adaptive Particle Representation, and finally, we present sciview, an ImageJ2/Fiji plugin making the features of scenery available to a wider audience.:Abstract Foreword and Acknowledgements Overview and Contributions Part 1 - Introduction 1 Fluorescence Microscopy 2 Introduction to Visual Processing 3 A Short Introduction to Cross Reality 4 Eye Tracking and Gaze-based Interaction Part 2 - VR and AR for System Biology 5 scenery — VR/AR for Systems Biology 6 Rendering 7 Input Handling and Integration of External Hardware 8 Distributed Rendering 9 Miscellaneous Subsystems 10 Future Development Directions Part III - Case Studies C A S E S T U D I E S 11 Bionic Tracking: Using Eye Tracking for Cell Tracking 12 Towards Interactive Virtual Reality Laser Ablation 13 Rendering the Adaptive Particle Representation 14 sciview — Integrating scenery into ImageJ2 & Fiji Part IV - Conclusion 15 Conclusions and Outlook Backmatter & Appendices A Questionnaire for VR Ablation User Study B Full Correlations in VR Ablation Questionnaire C Questionnaire for Bionic Tracking User Study List of Tables List of Figures Bibliography Selbstständigkeitserklärun

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Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Security and health: Biopolitical health surveillance in China’s digital response to COVID-19

Why is health a security issue now? An emerging paradigm that links epidemics and security concerns has influenced how we think about health and the preparedness of health surveillance. As the ongoing COVID-19 pandemic has swept the world with its tremendous threats to public health and societies, innovative digital health surveillance technologies have been (and continue to be) developed for pandemic surveillance. With a special focus on China’s Health Code system and its implementation in Wuhan since the Wuhan lockdown, this thesis aims to examine the surveillance dynamics of such technological artefacts. In doing so, this thesis applies institutional ethnography (IE) to illustrate how the ruling relations embedded in such assemblages coordinate and organize citizens’ everyday lives. The primary findings of this thesis suggest that Health Code as a health security practice is a flexible and dynamic surveillance assemblage embedded with political classifications and decisions to define and mediate risk in everyday settings, located in a larger network of power relations. The insecurities and anxieties brought by the normalized use of Health Code exacerbate the fear of being classified as sick, as the threat of illness leads people to embrace the current situation and cooperate with the existing surveillance system through the rationalization of collective norms and the valorization and stabilization of data-driven knowledge

Optical Communication

Optical communication is very much useful in telecommunication systems, data processing and networking. It consists of a transmitter that encodes a message into an optical signal, a channel that carries the signal to its desired destination, and a receiver that reproduces the message from the received optical signal. It presents up to date results on communication systems, along with the explanations of their relevance, from leading researchers in this field. The chapters cover general concepts of optical communication, components, systems, networks, signal processing and MIMO systems. In recent years, optical components and other enhanced signal processing functions are also considered in depth for optical communications systems. The researcher has also concentrated on optical devices, networking, signal processing, and MIMO systems and other enhanced functions for optical communication. This book is targeted at research, development and design engineers from the teams in manufacturing industry, academia and telecommunication industries