Sleeping at work: not all about location, location, location

Working arrangements in industries that use non-standard hours sometimes necessitate an 'onsite' workforce where workers sleep in accommodation within or adjacent to the workplace. Of particular relevance to these workers is the widely held (and largely anecdotal) assumption that sleep at home is better than sleep away, particularly when away for work. This narrative review explores the idea that sleep outcomes in these unique work situations are the product of an interaction between numerous factors including timing and duration of breaks, commute length, sleeping environment (noise, movement, vibration, light), circadian phase, demographic factors and familiarity with the sleep location. Based on the data presented in this review, it is our contention that the location of sleep, whilst important, is secondary to other factors such as the timing and duration of sleep periods. We suggest that future research should include measures that allow conceptualisation of other critical factors such as familiarity with the sleeping environment.

Incidental physical activity in Melbourne, Australia: health and economic impacts of mode of transport and suburban location.

Using the known health impacts of physical activity (PA), levels of incidental PA in Melbourne were analysed, and after determining key behavioural associations, economic modelling estimated potential long-term health and economic benefits of changes in active transport (AT) patterns.

Re-thinking continuing professional development through changing metaphors and location in professional practices

Many professions have requirements for professional development activities to ensure continuing registration or membership. These commonly focus on participation in a limited range of activities. This paper questions the assumptions behind such approaches and what alternatives might be considered. It explores the suitability of metaphors used for continuing professional education and suggests that continuing professional development might be better conceptualised within practice theory. It identifies what a practice theory view of continuing professional development might involve and discusses the implications, particularly the notion of locating development within the practices of work.

Privacy preserving in location data release: A differential privacy approach

Communication devices with GPS chips allow people to generate large volumes of location data. However, location datasets have been confronted with serious privacy concerns. Recently, several privacy techniques have been proposed but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes a private release algorithm to randomize location datasets in a strict privacy notion, differential privacy. This algorithm includes three privacy-preserving operations: Private Location Clustering shrinks the randomized domain and Cluster Weight Perturbation hides the weights of locations, while Private Location Selection hides the exact locations of a user. Theoretical analysis on utility confirms an improved trade-off between the privacy and utility of released location data. The experimental results further suggest this private release algorithm can successfully retain the utility of the datasets while preserving users’ privacy.

Location privacy preserving for semantic-aware applications

With the increase use of location-based services, location privacy has recently raised serious concerns. To protect a user from being identified, a cloaked spatial region that contains other k-1 nearest neighbors of the user is used to replace the accurate position. In this paper, we consider location-aware applications that services are different among regions. To search nearest neighbors, we define a novel distance measurement that combines the semantic distance and the Euclidean distance to address the privacy preserving issue in the above-mentioned applications. We also propose an algorithm kNNH to implement our proposed method. The experimental results further suggest that the proposed distance metric and the algorithm can successfully retain the utility of the location services while preserving users’ privacy.

Energy efficiency on location based applications in mobile cloud computing: a survey

The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions. © 2013 Springer-Verlag Wien.

Thermal comfort of multiple user groups in indoor aquatic centres

Aquatic centres are popular recreational facilities in Australia and other developed countries. These buildings have experienced exponential demand over the past few decades. The growing desire for better indoor environmental quality in aquatic centres has resulted in a marked increase in energy consumption in this sector. With the existence of multiple user groups, achieving thermal comfort has always been challenging. Even though several thermal comfort studies are conducted in other building types, such studies are very limited with respect to aquatic centres. This paper analyses the thermal comfort conditions of various user groups in seven aquatic centres in Australia. Comfort measurements are performed through monitoring environmental parameters and surveying swimmers, staff and spectators. The results revealed the variation of air temperatures among the buildings, resulting in high level of thermal discomfort for the spectators and staff in some of the buildings. The thermal sensation of the staff and spectators had good correlation with the indoor temperatures and PMVs. Altering temperature settings according to the seasons will help to improve the comfort with respect to the adaptation and expectation of the occupants.

A privacy-preserving location tracking system for smartphones based on cloud storage

With the widespread use of smartphones, the loss of a device is a critical problem, which results both in disrupting daily communications and losing valuable property. As a result, tracking systems have been developed to track mobile devices. Previous tracking systems focus on recovering the device's locations after it goes missing, with security methods implemented on the clients. However, users' locations are stored in untrusted third-party services, which may be attacked or eavesdropped. In this paper, we propose a system, named Android Cloud Tracker, to provide a privacy-preserving tracking client and safe storing of user's locations. We use cloud storage controlled by users themselves as storage facilities, and they do not need to worry about any untrusted third party. We implement Android Cloud Tracker prototype on Android phones, and the evaluation shows that it is both practical and lightweight: it generates a small amount of data flow and its distributed architecture provides strong guarantees of location privacy while preserving the ability to efficiently track missing devices.

A differentially private algorithm for location data release

The rise of mobile technologies in recent years has led to large volumes of location information, which are valuable resources for knowledge discovery such as travel patterns mining and traffic analysis. However, location dataset has been confronted with serious privacy concerns because adversaries may re-identify a user and his/her sensitivity information from these datasets with only a little background knowledge. Recently, several privacy-preserving techniques have been proposed to address the problem, but most of them lack a strict privacy notion and can hardly resist the number of possible attacks. This paper proposes a private release algorithm to randomize location dataset in a strict privacy notion, differential privacy, with the goal of preserving users’ identities and sensitive information. The algorithm aims to mask the exact locations of each user as well as the frequency that the user visits the locations with a given privacy budget. It includes three privacy-preserving operations: private location clustering shrinks the randomized domain and cluster weight perturbation hides the weights of locations, while private location selection hides the exact locations of a user. Theoretical analysis on privacy and utility confirms an improved trade-off between privacy and utility of released location data. Extensive experiments have been carried out on four real-world datasets, GeoLife, Flickr, Div400 and Instagram. The experimental results further suggest that this private release algorithm can successfully retain the utility of the datasets while preserving users’ privacy.

Continuous discovery of co-location contexts from Bluetooth data

The discovery of contexts is important for context-aware applications in pervasive computing. This is a challenging problem because of the stream nature of data, the complexity and changing nature of contexts. We propose a Bayesian nonparametric model for the detection of co-location contexts from Bluetooth signals. By using an Indian buffet process as the prior distribution, the model can discover the number of contexts automatically. We introduce a novel fixed-lag particle filter that processes data incrementally. This sampling scheme is especially suitable for pervasive computing as the computational requirements remain constant in spite of growing data. We examine our model on a synthetic dataset and two real world datasets. To verify the discovered contexts, we compare them to the communities detected by the Louvain method, showing a strong correlation between the results of the two methods. Fixed-lag particle filter is compared with Gibbs sampling in terms of the normalized factorization error that shows a close performance between the two inference methods. As fixed-lag particle filter processes a small chunk of data when it comes and does not need to be restarted, its execution time is significantly shorter than that of Gibbs sampling.

DoSTra: Discovering common behaviors of objects using the duration of staying on each location of trajectories

Since semantic trajectories can discover more semantic meanings of a user's interests without geographic restrictions, research on semantic trajectories has attracted a lot of attentions in recent years. Most existing work discover the similar behavior of moving objects through analysis of their semantic trajectory pattern, that is, sequences of locations. However, this kind of trajectories without considering the duration of staying on a location limits wild applications. For example, Tom and Anne have a common pattern of Home→Restaurant → Company → Restaurant, but they are not similar, since Tom works at Restaurant, sends snack to someone at Company and return to Restaurant while Anne has breakfast at Restaurant, works at Company and has lunch at Restaurant. If we consider duration of staying on each location we can easily to differentiate their behaviors. In this paper, we propose a novel approach for discovering common behaviors by considering the duration of staying on each location of trajectories (DoSTra). Our approach can be used to detect the group that has similar lifestyle, habit or behavior patterns and predict the future locations of moving objects. We evaluate the experiment based on synthetic dataset, which demonstrates the high effectiveness and efficiency of the proposed method.

Estimated Number and Location of Future Moose-Vehicle Collisions (MVC) in Maine

Moose (Alces alces) are a keystone herbivore in Maine. Because of the large number of rural roads in Maine, there is a high rate of moose-vehicle collisions (MVCs), which is increasing. On-road encounters with animals resulted in 231 fatalities in the United States in 1999. Because of the fatality of MVCs, it is important to know where they are most likely to occur. I used GIS analysis to estimate where future MVCs would occur, factoring in the variables of land cover suitability for moose, distance from water bodies, locations of past MVCs, and speed limits on the roads. I ran four different analyses, each one weighting the variables equally. I also ran a regression to determine if increasing road speed was associated with the increase in the number of MVCs per length of road. There was not a strong positive relationship between the number of MVCs per length of road and the speed limit, but it was interesting to note that there were more MVCs per length of road on 35mph and 40mph roads than on 45, 50, 55 or 65mph roads. Future research on MVCs would benefit from the inclusion of include moose population density and road traffic data.

Trade or investment? location decisions under regional integration

This paper studies the production and trade patterns that may arise between two different countries if plant location is introduced as a first step in the producers' decision making. A three-stage game is used: the first deals with location and the next two with capacity and final sales decisions. Demand and cost structures differ by country, and the latter contain specific elements related to the foreign operation. The structure of possible Nash-equilibria is examined and an analysis of the changes in the solution, if the countries engage in an integration process, is made. As in previous models, though global welfare gains may not be very high, single country ones may be considerable, due to changes in the location of the plants. However, even if full integration takes place, global Marshallian welfare may decrease. Conditions which determine a tendency towards multinationalisation are obtained. Assuming a move toward integration, conditions are also provided to characterize when exporting will be preferred to local production. The fact that producers may retain a certain discriminating power, notwithstanding the elimination of barriers to arbitrage, creates a tendency to locate production in the country where prices are higher. This explains why welfare gains may not be obvious. An empirical illustration, with real data from two MERCOSUL countries (Brazil and Argentina) illustrates the possible outcomes.