Food futures: Three provocations to challenge HCI interventions

Our contemporary concerns about food range from food security to agricultural sustainability to getting dinner on the table for family and friends. This book investigates food issues as they intersect with participatory Internet culture--blogs, wikis, online photo- and video-sharing platforms, and social networks in efforts to bring about a healthy, socially inclusive, and sustainable food future. Focusing on our urban environments provisioned with digital and network capacities, and drawing on such "bottom-up" sociotechnical trends as DIY and open source, the chapters describe engagements with food and technology that engender (re-)creative interactions.

Integrated decoupling and matching network incorporated in the ground plane of a compact monopole array

Compact arrays enable various applications such as antenna beam-forming and multi-input, multi-output (MIMO) schemes on limited-size platforms. The reduced element spacing in compact arrays introduces high levels of mutual coupling which can affect the performance of the adaptive array. This coupling causes a mismatch at the input ports, which disturbs the performance of the individual elements in the array and affects the implementation of beam steering. In this article, a reactive decoupling network for a 3-element monopole array is used to establish port isolation while simultaneously matching input impedance at each port to the system impendence. The integrated decoupling and matching network is incorporated in the ground plane of the monopole array, providing further development scope for beamforming using phase shifters and power splitters in double-layered circuits.

The security and privacy of usage policies and provenance logs in an Information Accountability Framework

The potential benefits of shared eHealth records systems are promising for the future of improved healthcare. However, the uptake of such systems is hindered by concerns over the security and privacy of patient information. The use of Information Accountability and so called Accountable-eHealth (AeH) systems has been proposed to balance the privacy concerns of patients with the information needs of healthcare professionals. However, a number of challenges remain before AeH systems can become a reality. Among these is the need to protect the information stored in the usage policies and provenance logs used by AeH systems to define appropriate use of information and hold users accountable for their actions. In this paper, we discuss the privacy and security issues surrounding these accountability mechanisms, define valid access to the information they contain, discuss solutions to protect them, and verify and model an implementation of the access requirements as part of an Information Accountability Framework.

The doomsday vault: Seed banks, food security, and climate change

"It could easily provide the back-drop for a James Bond movie. Deep inside a mountain near the North Pole, down a fortified tunnel, and behind airlocked doors in a vault frozen to -18 degrees Celsius, scientists are squirreling away millions of seed samples. The samples constitute the very foundation of agriculture, the biological diversity needed so the world's major food crops can adapt to the next pest or disease, or to climate change. It's little wonder that the Svalbard Global Seed Vault has captured the public's imagination more than almost any agricultural topic in recent years. Popular press reports about the ‘Doomsday Vault,’ however, typically mask the complexity of the endeavor and, if anything, underestimate its practical utility." Cary Fowler This chapter considers the use of seed banks to address concerns about intellectual property, climate change and food security. It has a number of themes. First of all, it is interested in the use of ‘Big Science’ projects to address pressing global scientific concerns and Millennium Development Goals. Second, it highlights the increasing use of banks as a means of managing both property and intellectual property across a wide range of fields of agriculture and biotechnology. Third, it considers the linkage of intellectual property, access to genetic resources and benefit sharing. There are a variety of positions in this debate. Some see requirements in respect of access to genetic resources and benefit sharing as an inconvenient burden for science and commerce. Others defend access to genetic resources and benefit sharing as meaningful and productive. Those inclined to somewhat more conspiratorial views suggest that access to genetic resources and benefit sharing are a ruse to facilitate biopiracy. This chapter has a number of components. Section I focuses upon the Consultative Group on International Agricultural Research (CGIAR) network – often raised as a model for Climate Innovation Centres. Section II considers the Svalbard Global Seed Vault – the so-called Doomsday Vault. After a consideration of the World Summit on Food Security in 2009, it is concluded in this chapter that any future international agreement on climate change needs to address intellectual property, plant genetic resources and food security.

Intellectual property and biofuels: The energy crisis, food security, and climate change

In light of larger public policy debates over intellectual property and climate change, this article considers patent practice, law, and policy in respect of biofuels. This debate has significant implications for public policy discussions in respect of energy independence, food security, and climate change. The first section of the paper provides a network analysis of patents in respect of biofuels across the three generations. It provides empirical research in respect of patent subject matter, ownership, and strategy in respect of biofuels. The second section provides a case study of significant patent litigation over biofuels. There is an examination of the biofuels patent litigation between the Danish company Novozymes, and Danisco and DuPont. The third section examines flexibilities in respect of patent law and clean technologies in the context of the case study of biofuels. In particular, it explores the debate over substantive doctrinal matters in respect of biofuels – such as patentable subject matter, technology transfer, patent pools, compulsory licensing, and disclosure requirements. The conclusion explores the relevance of the debate over patent law and biofuels to the larger public policy discussions over energy independence, food security, and climate change.

On food security and alternative food networks: Understanding and performing food security in the context of urban bias

This paper offers one explanation for the institutional basis of food insecurity in Australia, and argues that while alternative food networks and the food sovereignty movement perform a valuable function in building forms of social solidarity between urban consumers and rural producers, they currently make only a minor contribution to Australia’s food and nutrition security. The paper begins by identifying two key drivers of food security: household incomes (on the demand side) and nutrition-sensitive, ‘fair food’ agriculture (on the supply side). We focus on this second driver and argue that healthy populations require an agricultural sector that delivers dietary diversity via a fair and sustainable food system. In order to understand why nutrition-sensitive, fair food agriculture is not flourishing in Australia we introduce the development economics theory of urban bias. According to this theory, governments support capital intensive rather than labour intensive agriculture in order to deliver cheap food alongside the transfer of public revenues gained from rural agriculture to urban infrastructure, where the majority of the voting public resides. We chart the unfolding of the Urban Bias across the twentieth century and its consolidation through neo-liberal orthodoxy, and argue that agricultural policies do little to sustain, let alone revitalize, rural and regional Australia. We conclude that by observing food system dynamics through a re-spatialized lens, Urban Bias Theory is valuable in highlighting rural–urban socio-economic and political economy tensions, particularly regarding food system sustainability. It also sheds light on the cultural economy tensions for alternative food networks as they move beyond niche markets to simultaneously support urban food security and sustainable rural livelihoods.

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Creating heterogeneity: Evolving use of groupware in a network of freelancers

This contribution is a long-term study of the evolving use of the organization-wide groupware in a service network. We are describing the practices related to organization-wide groupware in conjunction with local groupware-related practices and how they have proceeded since the organization was established. In the discussion of these practices we are focussing on issues such as: 1. tendencies for proliferation and integration, 2. local appropriations of a variety of systems, 3. creative appropriations, including the creation of a unique heterogeneous groupware fabric, 4. the design strategy of multiple parallel experimental use an; 5. the relation between disparate local meanings and successful computer supported cooperative practice. As an overarching theme we are exploring the explanatory value of the concepts of objectification and appropriation as compared to the concepts of design vs. use.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Building instance knowledge network for word sense disambiguation

In this paper, a new high precision focused word sense disambiguation (WSD) approach is proposed, which not only attempts to identify the proper sense for a word but also provides the probabilistic evaluation for the identification confidence at the same time. A novel Instance Knowledge Network (IKN) is built to generate and maintain semantic knowledge at the word, type synonym set and instance levels. Related algorithms based on graph matching are developed to train IKN with probabilistic knowledge and to use IKN for probabilistic word sense disambiguation. Based on the Senseval-3 all-words task, we run extensive experiments to show the performance enhancements in different precision ranges and the rationality of probabilistic based automatic confidence evaluation of disambiguation. We combine our WSD algorithm with five best WSD algorithms in senseval-3 all words tasks. The results show that the combined algorithms all outperform the corresponding algorithms.

An information accountability perspective to eHealth security and privacy

Rigid security boundaries hinder the proliferation of eHealth. Through active audit logs, accountable-eHealth systems alleviate privacy concerns and enhance information availability.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Protection of a Static Frequency Converter fed traction network, a case study

Aurizon, Australia's largest rail freight operator, is introducing the Static Frequency Converter (SFC) technology into its electric railway network as part of the Bauhinia Electrification Project. The introduction of SFCs has significant implications on the protection systems of the 50kV traction network. The traditional distance protection calculation method does not work in this configuration because of the effect that the SFC in combination with the remote grid has on the apparent impedance, and was substantially reviewed. The standard overcurrent (OC) protection scheme is not suitable due to the minimum fault level being below the maximum load level and was revised to incorporate directionality and under-voltage inhibit. Delta protection was reviewed to improve sensitivity. A new protection function was introduced to prevent back-feeding faults in the transmission network through the grid connection. Protection inter-tripping was included to ensure selectivity between the SFC protection and the system downstream.