Classification of areas through quantifiable spatial attributes

This paper presents a comparative analysis of three areas within London based on measurable attributes of each city block, to assess the degree to which characteristic differences between the neighborhoods are evident and quantifiable. Both morphological measures of buildings and Space Syntax measures of streets are used. Results indicate that neighbourhoods are clearly distinguishable, however, the types of measures which best capture that distinction vary depending on the distinction being made. In the cases studied, building morphology alone distinguishes the residential neighbourhoods from mixed use, but the distinction between two residential neighbourhoods requires a combination of building and street measures

The Structure of Spatial Networks and Communities in Bicycle Sharing Systems

Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models

Big Data and Workplace Micro-Behaviours: A closer inspection of the social behaviour of eating and interacting

Evidence-based design aims to understand human behaviour so that strategic decisions are well-informed when creating a new space. Workplace research to date has provided interesting insights, but has mostly done so on a case-by-case basis. This approach does not yield generalisable patterns, making results problematic to use in an evidence-based design context. This paper builds upon previous large-scale analysis done by the authors and focuses on two aspects of workplace behaviour – eating and interacting. We aim to understand the nuances of these behaviours, thus we explore them as independent phenomena, separate them into subcategories and set out to understand the reasons behind these observations. The examined dataset includes 23 organisations in the UK, with a wide variety of sizes, numbers of floors and buildings. It consists of human activity data collected through direct observation, Visibility Graph Analysis and organisational parameters such as industry and flexibility of desk occupancy. The first behaviour we focus on – interaction – has already been explored in previous research and has been found to happen primarily in workspace and meeting rooms. In this instance we initially classify interactions according to the activity of the members and the type of space they occur in. The analysis of the second behaviour – eating – revolves around the activities and locations of people at lunchtime. We aim to discover where people choose to eat and how this is affected by the characteristics and availability of eating spaces. For the two behaviours studied, we examine how each activity relates to the space it is happening in, taking into account a set of spatial and organisational factors. In the first case we test each interaction against proximity to circulation and local visibility of the space, while in the second we examine the popularity of different types of spaces, for example canteens and breakout spaces, against their proximity to workspace and what possibilities of inter-visibility they offer. This paper provides detailed insights into the phenomena of interacting and eating, and reflects on limitations of traditional statistical analysis. It will also highlight further opportunities for handling these types of big datasets using different techniques such as Principal Component Analysis and machine learning

Beyond academia – interrogating research impact in the Research Excellence Framework

Big changes to the way in which research funding is allocated to UK universities were brought about in the Research Excellence Framework (REF), overseen by the Higher Education Funding Council, England. Replacing the earlier Research Assessment Exercise, the purpose of the REF was to assess the quality and reach of research in UK universities – and allocate funding accordingly. For the first time, this included an assessment of research ‘impact’, accounting for 20% of the funding allocation. In this article we use a text mining technique to investigate the interpretations of impact put forward via impact case studies in the REF process. We find that institutions have developed a diverse interpretation of impact, ranging from commercial applications to public and cultural engagement activities. These interpretations of impact vary from discipline to discipline and between institutions, with more broad-based institutions depicting a greater variety of impacts. Comparing the interpretations with the score given by REF, we found no evidence of one particular interpretation being more highly rewarded than another. Importantly, we also found a positive correlation between impact score and [overall research] quality score, suggesting that impact is not being achieved at the expense of research excellence

Spatial databases: Generating new insights on office design and human behaviours in the workplace

Space Syntax research has shown how human behaviours in the workplace are shaped by spatial configuration; in turn, evidence-based design practices have highlighted ways in which this data can be used to inform tailor-made solutions in office design. Yet, existing research focuses on either single case studies or comparisons of a few cases on a small scale. Also, each study uses its own methods and metrics which makes it difficult to establish wider patterns beyond single datasets. This paper presents a larger than usual data set on workplaces, which has been collected by Spacelab, a design and consultancy practice based in London. This dataset includes spatial and space usage information such as syntactic analysis and desk occupancy on client companies. It resides in a spatial relational database, allowing for systematic combination of the collected data, useful for doing either deeper analysis, or generating benchmarks and baselines. These insights are not only highly relevant to clients but also give rise to opportunities to generate new insights on office design and human behaviours in the workplace from a research perspective Two main research questions relating to the size of samples are discussed: Firstly, whether large samples are necessary to fully understand phenomena, and secondly, whether behavioural patterns vary across cases. Observation data and syntactic analysis are combined to understand in which areas of an office different activities take place. Observation data is also brought together with the functional allocations of space in order to ask whether activities follow the programme introduced by functions such as meeting rooms, kitchens, workspaces, etc. It is shown that observation data only becomes robust and reliable with longer periods of observations than previously recommended. Three to four full days seems to produce reasonably stable results for desk occupancy, while five full days seemed required for percentages of people walking and interacting. Some surprising findings were revealed regarding the distribution of activities in space, for instance dispelling the myth that interactions happen in corridors and highlighting that interactions tend to occur in rather segregated spaces. While it is argued that predictive power of the analysis varies, first steps towards establishing generic patterns have clearly been taken

Understanding the Impact of E-commerce on Last-Mile Light Goods Vehicle Activity in Urban Areas: The Case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels

Measuring Interaction in Workplaces

Interactions in the workplace have long been studied by the architectural research community, however, in the past, the majority of those contributions focused on single case studies. Drawing on a much larger empirical sample of 27 offices, this chapter aims at establishing a baseline of understanding how the physical structure of office buildings shapes human behaviours of interaction. This may form a foundation for the Human-Computer Interaction (HCI) community to investigate the impact of embedded computer technology on human behaviours inside buildings. Methods of data collection included an analysis of floor plans with Space Syntax techniques and direct observations of space usage patterns. Exploring this data, different patterns emerged: interactions appeared unevenly distributed in space; interaction rates as well as preferences for locations varied by industry; spatial configuration appeared to create affordances for interaction, since unplanned interactions outside of meeting rooms tended to cluster in more visually connected areas of the office; in addition, seven different micro-behaviours of interaction were identified, each of them driven by affordances in both the built environment and the presence of other people; last but not least, locations for interactions showed clear time-space routines. The chapter closes with interpretations of the results, reflecting on the problem of predictability and how these insights could be useful for evidence-based design, but also the HCI community. It also gives an outlook on future developments regarding the constant logging of human behaviours in offices with emerging technologies

Monitoring collagen gelling by elastic scattering spectroscopy (ESS)

Collagen is being used extensively in tissue engineering and on a larger scale in the field of cosmetic surgery. It is either used as a gel or plastically compressed sheet. The fundamental science behind collagen gelling has been studied but little is known about the precise timing of gelling and the variables that affect gelling in the first 30 minutes. Critically, before collagen can be engineered as a predictable functional material we must be able to control fibril aggregation and gel formation. Here we report on the use of elastic scattering spectroscopy (ESS) to detect changes in scattering in rat tail and GMP bovine skin collagen during gelling. Effect of cell seeding on gelling is also reported

Проблеми вищої освіти в Україні в сучасних умовах

Most experts agree that it is too early to say how quantum computers will eventually be built, and several nanoscale solid-state schemes are being implemented in a range of materials. Nanofabricated quantum dots can be made in designer configurations, with established technology for controlling interactions and for reading out results. Epitaxial quantum dots can be grown in vertical arrays in semiconductors, and ultrafast optical techniques are available for controlling and measuring their excitations. Single-walled carbon nanotubes can be used for molecular self-assembly of endohedral fullerenes, which can embody quantum information in the electron spin. The challenges of individual addressing in such tiny structures could rapidly become intractable with increasing numbers of qubits, but these schemes are amenable to global addressing methods for computation

Enabling the freight traffic controller for collaborative multi-drop urban logistics: practical and theoretical challenges

There is increasing interest in how horizontal collaboration between parcel carriers might help alleviate problems associated with last-mile logistics in congested urban centers. Through a detailed review of the literature on parcel logistics pertaining to collaboration, along with practical insights from carriers operating in the United Kingdom, this paper examines the challenges that will be faced in optimizing multicarrier, multidrop collection, and delivery schedules. A “freight traffic controller” (FTC) concept is proposed. The FTC would be a trusted third party, assigned to equitably manage the work allocation between collaborating carriers and the passage of vehicles over the last mile when joint benefits to the parties could be achieved. Creating this FTC concept required a combinatorial optimization approach for evaluation of the many combinations of hub locations, network configuration, and routing options for vehicle or walking to find the true value of each potential collaboration. At the same time, the traffic, social, and environmental impacts of these activities had to be considered. Cooperative game theory is a way to investigate the formation of collaborations (or coalitions), and the analysis used in this study identified a significant shortfall in current applications of this theory to last-mile parcel logistics. Application of theory to urban freight logistics has, thus far, failed to account for critical concerns including (a) the mismatch of vehicle parking locations relative to actual delivery addresses; (b) the combination of deliveries with collections, requests for the latter often being received in real time during the round; and (c) the variability in travel times and route options attributable to traffic and road network conditions