Place making facilitators of knowledge and innovation spaces: Insights from European best practices

Knowledge economy seeks its nourishment from diversity and dissemination of ideas and creativity of its talent base. This has led to the acknowledgement of place making as a major strategy to attract and retain the knowledge base into the emerging knowledge and innovation spaces. The study seeks to explore the adoption of place making in this context. Literature and practice provide information to understand the evolution of various spatial typologies and the specialised role of place making in such locations. This helps in determining the key facilitators of place making. The paper takes an interdisciplinary approach and develops an integrated conceptual framework considering dimensions and facilitators of place making. Through the lens of the framework, best practices across Europe—i.e., Cambridge Science Park (UK), 22@Barcelona (Spain), Arabianranta (Finland), Strijp-S (Netherlands), and Digital Hub (Ireland)—are scrutinised to highlight various approaches to place making. The findings provide insights and a discussion into the interplay of form, function, image and underlying processes in globally emerging spatial typologies of contemporary knowledge and innovation spaces.

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.

Pathophysiology team teaching: Bioscientist contribution to knowledge integration in a nursing subject

Bioscience content within undergraduate nursing degrees provides foundational knowledge of pathophysiology, anatomy, physiology, microbiology and pharmacology. However, nursing students often find studying the bioscience components of undergraduate nursing program daunting (Friedel & Treagust 2005, Craft et al. 2013). This is related to factors such as the volume of content, degree of difficulty and insufficient linkage between bioscience concepts and nurses' clinical practice. Students who are unable to conceptualise the relevance of bioscience with nursing subjects and subsequent nursing practice may not appreciate the broader importance of bioscience, and hence may adopt a surface approach to learning (Craft et al. 2013). The aim of this study was to develop a model within Nursing Practice in the Context theory subject, to include a bioscientist lecturing to complement the nursing lecturer, in order to explicitly demonstrate links between physiology, pathophysiology and nursing practice.

Advancing practice in critical care: A model of knowledge integration

It could be argued that advancing practice in critical care has been superseded by the advanced practice agenda. Some would suggest that advancing practice is focused on the core attributes of an individuals practice progressing onto advanced practice status. However, advancing practice is more of a process than identifiable skills and as such is often negated when viewing the development of practitioners to the advanced practice level. For example practice development initiatives can be seen as advancing practice for the masses which ensures that practitioners are following the same level of practice. The question here is; are they developing individually.

Automated topometric graph generation from floor plan analysis

The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.

Improving Knowledge and Practices in Mango Supply Chains

Mangoes consigned to domestic markets suffered from fruit quality problems from 1997 to 2000. A high incidence of disease breakdown and green-ripe fruit resulted in loss of confidence by marketers, and reduced profits for everyone from grower to retailer. The ‘Better Mangoes’ project was initiated to identify where, and why quality was being lost, and to use this information to improve the knowledge and practices of supply chain businesses.

Advancing practice in critical care : A model of knowledge integration: A Singaporean context

It could be argued that advancing practice in critical care has been superseded by the advanced practice agenda. Some would suggest that advancing practice is focused on the core attributes of an individuals practice progressing onto advanced practice status. However, advancing practice is more of a process than identifiable skills and as such is often negated when viewing the development of practitioners to the advanced practice level. For example practice development initiatives can be seen as advancing practice for the masses which ensures that practitioners are following the same level of practice. The question here is; are they developing individually. To discuss the potential development of a conceptual model of knowledge integration pertinent to critical care nursing practice. In an attempt to explore the development of leading edge critical care thinking and practice, a new model for advancing practice in critical care is proposed. This paper suggests that reflection may not be the best model for advancing practice unless the individual practitioner has a sound knowledge base both theoretically and experientially. Drawing on the contemporary literature and recent doctoral research, the knowledge integration model presented here uses multiple learning strategies that are focused in practise to develop practice, for example the use of work-based learning and clinical supervision. Ongoing knowledge acquisition and its relationship with previously held theory and experience will enable individual practitioners to advance their own practice as well as being a resource for others.

Advancing practice in critical care: A model of knowledge integration

Explore and describe a conceptual model of knowledge integration pertinent to the development of individual practitioners in critical care. Discussion of how multiple learning strategies that are embedded in practice can be beneficial in developing knowledge.

Transparency and ‘uncomfortable knowledge’ in child protection

Australia's child protection systems and the provision of out-of-home care, in particular, have been subject to sustained criticism for decades from dozens of official inquiries and reviews. It is now well established that many children in state care are treated significantly less well than required by relevant legal frameworks and community standards. Much attention and significant resources have been directed toward trying to ameliorate this ‘wicked problem’ and yet it continues. This article focuses on one reason the problems persists, namely the secrecy and closed cultures that characterize relevant organizations which reinforce strategies of denial that avoid acknowledging or dealing with ‘uncomfortable knowledge’. It is a situation many people in child protection systems confront. It is, for example, when we know abuse is taking place, or when they see or are ourselves party to corrupt or negligent practices. It is knowing that important ethical principles are being abrogated. We draw on recent official reports and inquiries noting the repeated calls for greater transparency and independent oversight. An argument is made for a default position of total transparency subject to caveats that protect privacy and any investigation underway. An account of what this can look like is offered.

Improving knowledge and practices in fresh produce chains

A successful supply chain must delivery the right product, value and satisfaction to the end customer, and profitability for its participants. Critical to getting the product right is the practices used to produce and maintain product quality through the supply chain from production to sale to the end customer. This paper describes the approach used by a R&D team to add value to supply chains through improving knowledge and practices. The desired outcome is better produce quality for consumers and more control and less wastage for chain participants. The team worked with specific supply chains to identify areas for improvement and to develop, test and implement improved practices. The knowledge gained was communicated to the industry to gain wider adoption of results. Three conditions were identified as critical for practice change - motivation, knowledge, and capacity for change. For improvement in practices to occur, a business must be motivated and have the knowledge and capacity to improve. Two case studies of working with Australian supply chains (mango and melons) are presented to illustrate our participatory methodology. A key activity is monitoring produce quality and handling practices and conditions to demonstrate to participants the points where quality deterioration occurs in the supply chain. This participatory approach is successful because working with supply chain participants generates knowledge and solutions to real problems. It enables the participants to observe the effect of handling practices and conditions on produce quality, gain knowledge and assess the benefits of improvements. Where existing knowledge is not present, research is conducted to fill the knowledge gaps. IV International Conference on Managing Quality in Chains - The Integrated View on Fruits and Vegetables Quality

Trapping to monitor tephritid movement: Results, best practice, and assessment of alternatives

Movement of tephritid flies underpins their survival, reproduction, and ability to establish in new areas and is thus of importance when designing effective management strategies. Much of the knowledge currently available on tephritid movement throughout landscapes comes from the use of direct or indirect methods that rely on the trapping of individuals. Here, we review published experimental designs and methods from mark-release-recapture (MRR) studies, as well as other methods, that have been used to estimate movement of the four major tephritid pest genera (Bactrocera, Ceratitis, Anastrepha, and Rhagoletis). In doing so, we aim to illustrate the theoretical and practical considerations needed to study tephritid movement. MRR studies make use of traps to directly estimate the distance that tephritid species can move within a generation and to evaluate the ecological and physiological factors that influence dispersal patterns. MRR studies, however, require careful planning to ensure that the results obtained are not biased by the methods employed, including marking methods, trap properties, trap spacing, and spatial extent of the trapping array. Despite these obstacles, MRR remains a powerful tool for determining tephritid movement, with data particularly required for understudied species that affect developing countries. To ensure that future MRR studies are successful, we suggest that site selection be carefully considered and sufficient resources be allocated to achieve optimal spacing and placement of traps in line with the stated aims of each study. An alternative to MRR is to make use of indirect methods for determining movement, or more correctly, gene flow, which have become widely available with the development of molecular tools. Key to these methods is the trapping and sequencing of a suitable number of individuals to represent the genetic diversity of the sampled population and investigate population structuring using nuclear genomic markers or non-recombinant mitochondrial DNA markers. Microsatellites are currently the preferred marker for detecting recent population displacement and provide genetic information that may be used in assignment tests for the direct determination of contemporary movement. Neither MRR nor molecular methods, however, are able to monitor fine-scale movements of individual flies. Recent developments in the miniaturization of electronics offer the tantalising possibility to track individual movements of insects using harmonic radar. Computer vision and radio frequency identification tags may also permit the tracking of fine-scale movements by tephritid flies by automated resampling, although these methods come with the same problems as traditional traps used in MRR studies. Although all methods described in this chapter have limitations, a better understanding of tephritid movement far outweighs the drawbacks of the individual methods because of the need for this information to manage tephritid populations.

A generic design environment for the rural industry knowledge acquisition

This paper describes a new knowledge acquisition method using a generic design environment where context-sensitive knowledge is used to build specific DSS for rural business. Although standard knowledge acquisition methods have been applied in rural business applications, uptake remains low and familiar weaknesses such as obsolescence and brittleness apply. We describe a decision support system (DSS) building environment where contextual factors relevant to the end users are directly taken into consideration. This "end user enabled design environment" (EUEDE) engages both domain experts in creating an expert knowledge base and business operators/end users (such as farmers) in using this knowledge for building their specific DSS. We document the knowledge organisation for the problem domain, namely a dairy industry application. This development involved a case-study research approach used to explore dairy operational knowledge. In this system end users can tailor their decision-making requirements using their own judgement to build specific DSSs. In a specific end user's farming context, each specific DSS provides expert suggestions to assist farmers in improving their farming practice. The paper also shows the environment's generic capability.

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Actionable climate knowledge: From analysis to synthesis

The traditional reductionist approach to science has a tendency to create 'islands of knowledge in a sea of ignorance', with a much stronger focus on analysis of scientific inputs rather than synthesis of socially relevant outcomes. This might be the principal reason why intended end users of climate information generally fail to embrace what the climate science community has to offer. The translation of climate information into real-life action requires 3 essential components: salience (the perceived relevance of the information), credibility (the perceived technical quality of the information) and legitimacy (the perceived objectivity of the process by which the information is shared). We explore each of these components using 3 case studies focused on dryland cropping in Australia, India and Brazil. In regards to 'salience' we discuss the challenge for climate science to be 'policy-relevant', using Australian drought policy as an example. In a village in southern India 'credibility' was gained through engagement between scientists and risk managers with the aim of building social capital, achieved only at high cost to science institutions. Finally, in Brazil we found that 'legitimacy' is a fragile, yet renewable resource that needs to be part of the package for successful climate applications; legitimacy can be easily eroded but is difficult to recover. We conclude that climate risk management requires holistic solutions derived from cross-disciplinary and participatory, user-oriented research. Approaches that combine climate, agroecological and socioeconomic models provide the scientific capabilities for establishment of 'borderless' institutions without disciplinary constraints. Such institutions could provide the necessary support and flexibility to deliver the social benefits of climate science across diverse contexts. Our case studies show that this type of solution is already being applied, and suggest that the climate science community attempt to address existing institutional constraints, which still impede climate risk management.