Exploring privacy for ubiquitous computing: Tools, methods and experiments

Ubiquitous computing is about making computers and computerized artefacts a pervasive part of our everyday lifes, bringing more and more activities into the realm of information. The computationalization, informationalization of everyday activities increases not only our reach, efficiency and capabilities but also the amount and kinds of data gathered about us and our activities. In this thesis, I explore how information systems can be constructed so that they handle this personal data in a reasonable manner. The thesis provides two kinds of results: on one hand, tools and methods for both the construction as well as the evaluation of ubiquitous and mobile systems---on the other hand an evaluation of the privacy aspects of a ubiquitous social awareness system. The work emphasises real-world experiments as the most important way to study privacy. Additionally, the state of current information systems as regards data protection is studied. The tools and methods in this thesis consist of three distinct contributions. An algorithm for locationing in cellular networks is proposed that does not require the location information to be revealed beyond the user's terminal. A prototyping platform for the creation of context-aware ubiquitous applications called ContextPhone is described and released as open source. Finally, a set of methodological findings for the use of smartphones in social scientific field research is reported. A central contribution of this thesis are the pragmatic tools that allow other researchers to carry out experiments. The evaluation of the ubiquitous social awareness application ContextContacts covers both the usage of the system in general as well as an analysis of privacy implications. The usage of the system is analyzed in the light of how users make inferences of others based on real-time contextual cues mediated by the system, based on several long-term field studies. The analysis of privacy implications draws together the social psychological theory of self-presentation and research in privacy for ubiquitous computing, deriving a set of design guidelines for such systems. The main findings from these studies can be summarized as follows: The fact that ubiquitous computing systems gather more data about users can be used to not only study the use of such systems in an effort to create better systems but in general to study phenomena previously unstudied, such as the dynamic change of social networks. Systems that let people create new ways of presenting themselves to others can be fun for the users---but the self-presentation requires several thoughtful design decisions that allow the manipulation of the image mediated by the system. Finally, the growing amount of computational resources available to the users can be used to allow them to use the data themselves, rather than just being passive subjects of data gathering.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.

Validating adult and paediatric nutrition screening and assessment tools in Vietnamese language in two acute hospital in Ho Chi Minh City, Vietnam

Despite being commonly prevalent in acute care hospitals worldwide, malnutrition often goes unidentified and untreated due to a lack in the implementation of a nutrition care pathway. The aim of this study was to validate nutrition screening and assessment tools in Vietnamese language. After converting into Vietnamese, Malnutrition Screening Tool (MST) and Subjective Global Assessment (SGA) were used to identify malnutrition in the adult setting; and the Paediatric Nutrition Screening Tool (PNST) and paediatric Subjective Global Nutritional Assessment (SGNA) were used in the paediatric setting in two acute care hospitals in Vietnam. This cross-sectional observational study sampled 123 adults (median age 78 years [39–96 years], 63% males) and 105 children (median age 20 months [2–100 months], 66% males). In adults, nutrition risk and malnutrition were identified in 29% and 45% of the cohort respectively. Nutrition risk and malnutrition were identified in 71% and 43% of the paediatric cohort respectively. The sensitivity and specificity of the screening tools were: 62% and 99% for the MST compared to the SGA; 89% and 42% for the PNST compared to the SGNA. This study provides a stepping stone to the potential use of evidence-based nutrition screening and assessment tools in Vietnamese language within the adult and paediatric Vietnamese acute care setting. Further work is required into integrating a complete nutrition care pathway within the acute care setting in Vietnamese hospitals.

Web 2.0 technology: Social learning tools in higher education in Saudi Arabia

Information and communication technology (ICT) has created opportunities for students' online interaction in higher education throughout the world. Limited research has been done in this area in Saudi Arabia. This study investigated university students' engagement and perceptions of online collaborative learning using Social Learning Tools (SLTs). In addition, it explored the quality of knowledge construction that occurred in this environment. A mixed methods case study approach was adopted, and the data was gathered from undergraduate students (n=43) who were enrolled in a 15-week course at a Saudi university. The results showed that while the students had positive perceptions towards SLTs and their engagement, data gathered from their work also showed little evidence of high levels of knowledge construction.

Tools for compositional data with a total

Compositional data analysis usually deals with relative information between parts where the total (abundances, mass, amount, etc.) is unknown or uninformative. This article addresses the question of what to do when the total is known and is of interest. Tools used in this case are reviewed and analysed, in particular the relationship between the positive orthant of D-dimensional real space, the product space of the real line times the D-part simplex, and their Euclidean space structures. The first alternative corresponds to data analysis taking logarithms on each component, and the second one to treat a log-transformed total jointly with a composition describing the distribution of component amounts. Real data about total abundances of phytoplankton in an Australian river motivated the present study and are used for illustration.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Negative sequence compensation within fundamental positive sequence reference frame for a stiff micro-grid generation in a wind power system using slip ring induction machine

An isolated wind power generation scheme using slip ring induction machine (SRIM) is proposed. The proposed scheme maintains constant load voltage and frequency irrespective of the wind speed or load variation. The power circuit consists of two back-to-back connected inverters with a common dc link, where one inverter is directly connected to the rotor side of SRIM and the other inverter is connected to the stator side of the SRIM through LC filter. Developing a negative sequence compensation method to ensure that, even under the presence of unbalanced load, the generator experiences almost balanced three-phase current and most of the unbalanced current is directed through the stator side converter is the focus here. The SRIM controller varies the speed of the generator with variation in the wind speed to extract maximum power. The difference of the generated power and the load power is either stored in or extracted from a battery bank, which is interfaced to the common dc link through a multiphase bidirectional fly-back dc-dc converter. The SRIM control scheme, maximum power point extraction algorithm and the fly-back converter topology are incorporated from available literature. The proposed scheme is both simulated and experimentally verified.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Mutations as molecular tools : The metabolic-rate dependent molecular clock and DNA barcoding of allied species

Mutation and recombination are the fundamental processes leading to genetic variation in natural populations. This variation forms the raw material for evolution through natural selection and drift. Therefore, studying mutation rates may reveal information about evolutionary histories as well as phylogenetic interrelationships of organisms. In this thesis two molecular tools, DNA barcoding and the molecular clock were examined. In the first part, the efficiency of mutations to delineate closely related species was tested and the implications for conservation practices were assessed. The second part investigated the proposition that a constant mutation rate exists within invertebrates, in form of a metabolic-rate dependent molecular clock, which can be applied to accurately date speciation events. DNA barcoding aspires to be an efficient technique to not only distinguish between species but also reveal population-level variation solely relying on mutations found on a short stretch of a single gene. In this thesis barcoding was applied to discriminate between Hylochares populations from Russian Karelia and new Hylochares findings from the greater Helsinki region in Finland. Although barcoding failed to delineate the two reproductively isolated groups, their distinct morphological features and differing life-history traits led to their classification as two closely related, although separate species. The lack of genetic differentiation appears to be due to a recent divergence event not yet reflected in the beetles molecular make-up. Thus, the Russian Hylochares was described as a new species. The Finnish species, previously considered as locally extinct, was recognized as endangered. Even if, due to their identical genetic make-up, the populations had been regarded as conspecific, conservation strategies based on prior knowledge from Russia would not have guaranteed the survival of the Finnish beetle. Therefore, new conservation actions based on detailed studies of the biology and life-history of the Finnish Hylochares were conducted to protect this endemic rarity in Finland. The idea behind the strict molecular clock is that mutation rates are constant over evolutionary time and may thus be used to infer species divergence dates. However, one of the most recent theories argues that a strict clock does not tick per unit of time but that it has a constant substitution rate per unit of mass-specific metabolic energy. Therefore, according to this hypothesis, molecular clocks have to be recalibrated taking body size and temperature into account. This thesis tested the temperature effect on mutation rates in equally sized invertebrates. For the first dataset (family Eucnemidae, Coleoptera) the phylogenetic interrelationships and evolutionary history of the genus Arrhipis had to be inferred before the influence of temperature on substitution rates could be studied. Further, a second, larger invertebrate dataset (family Syrphidae, Diptera) was employed. Several methodological approaches, a number of genes and multiple molecular clock models revealed that there was no consistent relationship between temperature and mutation rate for the taxa under study. Thus, the body size effect, observed in vertebrates but controversial for invertebrates, rather than temperature may be the underlying driving force behind the metabolic-rate dependent molecular clock. Therefore, the metabolic-rate dependent molecular clock does not hold for the here studied invertebrate groups. This thesis emphasizes that molecular techniques relying on mutation rates have to be applied with caution. Whereas they may work satisfactorily under certain conditions for specific taxa, they may fail for others. The molecular clock as well as DNA barcoding should incorporate all the information and data available to obtain comprehensive estimations of the existing biodiversity and its evolutionary history.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

IASDR 2015 Interplay Exhibition 2-5 NOV 2015

It has been said that we are living in a golden age of innovation. New products, systems and services aimed to enable a better future, have emerged from novel interconnections between design and design research with science, technology and the arts. These intersections are now, more than ever, catalysts that enrich daily activities for health and safety, education, personal computing, entertainment and sustainability, to name a few. Interactive functions made possible by new materials, technology, and emerging manufacturing solutions demonstrate an ongoing interplay between cross-disciplinary knowledge and research. Such interactive interplay bring up questions concerning: (i) how art and design provide a focus for developing design solutions and research in technology; (ii) how theories emerging from the interactions of cross-disciplinary knowledge inform both the practice and research of design and (iii) how research and design work together in a mutually beneficial way. The IASDR2015 INTERPLAY EXHIBITION provides some examples of these interconnections of design research with science, technology and the arts. This is done through the presentation of objects, artefacts and demonstrations that are contextualised into everyday activities across various areas including health, education, safety, furniture, fashion and wearable design. The exhibits provide a setting to explore the various ways in which design research interacts across discipline knowledge and approaches to stimulate innovation. In education, Designing South African Children’s Health Education as Generative Play (A Bennett, F Cassim, M van der Merwe, K van Zijil, and M Ribbens) presents a set of toolkits that resulted from design research entailing generative play. The toolkits are systems that engender pleasure and responsibility, and are aimed at cultivating South African’s youth awareness of nutrition, hygiene, disease awareness and prevention, and social health. In safety, AVAnav: Avalanche Rescue Helmet (Jason Germany) delivers an interactive system as a tool to contribute to reduce the time to locate buried avalanche victims. Helmet-mounted this system responds to the contextual needs of rescuers and has since led to further design research on the interface design of rescuing devices. In apparel design and manufacturing, Shrinking Violets: Fashion design for disassembly (Alice Payne) proposes a design for disassembly through the use of beautiful reversible mono-material garments that interactively responds to the challenges of garment construction in the fashion industry, capturing the metaphor for the interplay between technology and craft in the fashion manufacturing industry. Harvest: A biotextile future (Dean Brough and Alice Payne), explores the interplay of biotechnology, materiality and textile design in the creation of sustainable, biodegradable vegan textile through the process of a symbiotic culture of bacteria and yeast (SCOBY). SCOBY is a pellicle curd that can be harvested, machine washed, dried and cut into a variety of designs and texture combinations. The exploration of smart materials, wearable design and micro-electronics led to creative and aesthetically coherent stimulus-reactive jewellery; Symbiotic Microcosms: Crafting Digital Interaction (K Vones). This creation aims to bridge the gap between craft practitioner and scientific discovery, proposing a move towards the notion of a post-human body, where wearable design is seen as potential ground for new human-computer interactions, affording the development of visually engaging multifunctional enhancements. In furniture design, Smart Assistive chair for older adults (Chao Zhao) demonstrates how cross-disciplinary knowledge interacting with design strategies provide solution that employed new technological developments in older aged care, and the participation of multiple stakeholders: designers, health care system and community based health systems. In health, Molecular diagnosis system for newborns deafness genetic screening (Chao Zhao) presents an ambitious and complex project that includes a medical device aimed at resolving a number of challenges: technical feasibility for city and rural contexts, compatibility with standard laboratory and hospital systems, access to health system, and support the work of different hospital specialists. The interplay between cross-disciplines is evident in this work, demonstrating how design research moves forward through technology developments. These works exemplify the intersection between domains as a means to innovation. Novel design problems are identified as design intersects with the various areas. Research informs this process, and in different ways. We see the background investigation into the contextualising domain (e.g. on-snow studies, garment recycling, South African health concerns, the post human body) to identify gaps in the area and design criteria; the technologies and materials reviews (e.g. AR, biotextiles) to offer plausible technical means to solve these, as well as design criteria. Theoretical reviews can also inform the design (e.g. play, flow). These work together to equip the design practitioner with a robust set of ‘tools’ for design innovation – tools that are based in research. The process identifies innovative opportunity and criteria for design and this, in turn, provides a means for evaluating the success of the design outcomes. Such an approach has the potential to come full circle between research and design – where the design can function as an exemplar, evidencing how the research-articulated problems can be solved. Core to this, however, is the evaluation of the design outcome itself and identifying knowledge outcomes. In some cases, this is fairly straightforward that is, easily measurable. For example the efficacy of Jason Germany’s helmet can be determined by measuring the reduced response time in the rescuer. Similarly the improved ability to recycle Payne’s panel garments can be clearly determined by comparing it to those recycling processes (and her identified criteria of separating textile elements!); while the sustainability and durability of the Brough & Payne’s biotextile can be assessed by documenting the growth and decay processes, or comparative strength studies. There are however situations where knowledge outcomes and insights are not so easily determined. Many of the works here are open-ended in their nature, as they emphasise the holistic experience of one or more designs, in context: “the end result of the art activity that provides the health benefit or outcome but rather, the value lies in the delivery and experience of the activity” (Bennet et al.) Similarly, reconfiguring layers of laser cut silk in Payne’s Shrinking Violets constitutes a customisable, creative process of clothing oneself since it “could be layered to create multiple visual effects”. Symbiotic Microcosms also has room for facilitating experience, as the work is described to facilitate “serendipitous discovery”. These examples show the diverse emphasis of enquiry as on the experience versus the product. Open-ended experiences are ambiguous, multifaceted and differ from person to person and moment to moment (Eco 1962). Determining the success is not always clear or immediately discernible; it may also not be the most useful question to ask. Rather, research that seeks to understand the nature of the experience afforded by the artefact is most useful in these situations. It can inform the design practitioner by helping them with subsequent re-design as well as potentially being generalizable to other designers and design contexts. Bennett et. al exemplify how this may be approached from a theoretical perspective. This work is concerned with facilitating engaging experiences to educate and, ultimately impact on that community. The research is concerned with the nature of that experience as well, and in order to do so the authors have employed theoretical lenses – here these are of flow, pleasure, play. An alternative or complementary approach to using theory, is using qualitative studies such as interviews with users to ask them about what they experienced? Here the user insights become evidence for generalising across, potentially revealing insight into relevant concerns – such as the range of possible ‘playful’ or experiences that may be afforded, or the situation that preceded a ‘serendipitous discovery’. As shown, IASDR2015 INTERPLAY EXHIBITION provides a platform for exploration, discussion and interrogation around the interplay of design research across diverse domains. We look forward with excitement as IASDR continues to bring research and design together, and as our communities of practitioners continue to push the envelope of what is design and how this can be expanded and better understood with research to foster new work and ultimately, stimulate innovation.

Aircraft trajectory clustering techniques using circular statistics

This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

Do inventory management practices affect economic performance? An empirical evaluation of the machine tool SMEs in Bangalore

Inventory management (IM) has a decisive role in the enhancement of manufacturing industry's competitiveness. Therefore, major manufacturing industries are following IM practices with the intention of improving their performance. However, the effort to introduce IM in SMEs is very limited due to lack of initiation, expertise, and financial constraints. This paper aims to provide a guideline for entrepreneurs in enhancing their IM performance, as it presents the results of a survey based study carried out for machine tool Small and Medium Enterprises (SMEs) in Bangalore. Having established the significance of inventory as an input, we probed the relationship between IM performance and economic performance of these SMEs. To the extent possible all the factors of production and performance indicators were deliberately considered in pure economic terms. All economic performance indicators adopted seem to have a positive and significant association with IM performance in SMEs. On the whole, we found that SMEs which are IM efficient are likely to perform better on the economic front also and experience higher returns to scale.