Integrated Optimal Power Flow for Distribution Networks in Local and Urban Scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

A statistical analysis of person–to–vehicle communications channels in an urban environment at 5.8 GHz

In recent years, the embracement of smart devices carried or worn by people have transformed how society interact with one another. This trend has also been observed in the advancement of vehicular networks. Here, developments in wireless technologies for vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications are leading to a new generation of vehicular networks. A natural extension of both types of networks will be their eventual wireless integration. Both people and vehicles will undoubtedly form integral parts of future mobile networks of people and things. Central to this will be the person-to-vehicle (P2V) communications channel. As the P2V channel will be subject to different signal propagation characteristics than either type of communication system considered in isolation, it is imperative the characteristics of the wireless channel must first be fully understood. To the best of the author's knowledge, this is a topic which has not yet been addressed in the open literature. In this paper we will present our most recent research on the statistical characterization of the 5.8 GHz person-to-vehicle channel in an urban environment.

Comparing the experiences of rural and urban family caregivers of the terminally ill

Introduction: There are many challenges in delivering rural health services; this is particularly true for the delivery of palliative care. Previous work has identified consistent themes around end-of-life care, including caregiver burden in providing care, the importance of informal care networks and barriers imposed by geography. Despite these well-known barriers, few studies have explored the experience of palliative care in rural settings. The purpose of the present study was to compare the experiences of rural family caregivers actively providing end-of-life care to the experiences of their urban counterparts. Methods: Caregivers' perceived health status, the experience of burden in caregiving, assessment of social supports and the pattern of formal care used by the terminally ill were explored using a consistent and standardized measurement approach. A cross-sectional survey study was conducted with 100 informal caregivers (44 rural, 56 urban) actively providing care to a terminally ill patient recruited from a publicly funded community agency located in northeastern Ontario, Canada. The telephone-based survey included questions assessing: (i) caregiver perceived burden (14-item instrument based on the Caregiver's Burden Scale in End-of-Life Care [CBS-EOLC]); (ii) perceived social support (modified version of the Multidimensional Scale of Perceived Social Support [MSPSS] consisting of 12 items); and (iii) functional status of the care recipient (assessed using the Eastern Collaborative Oncology Group performance scale). Results: Rural and urban caregivers were providing care to recipients with similar functional status; the majority of care recipients were either capable of all self-care or experiencing some limitation in self-care. No group differences were observed for caregiver perceived burden: both rural and urban caregivers reported low levels of burden (CBS-EOLC score of 26.5 [SD=8.1] and 25.0 [SD=9.2], respectively; p=0.41). Urban and rural caregivers also reported similarly high levels of social support (mean MSPSS total score of 4.3 [SD=0.7] and 4.1 [SD=0.8], respectively; p=0.40). Although caregivers across both settings reported using a comparable number of services (rural 4.8 [SD=1.9] vs urban 4.5 [SD=1.8]; p=0.39), the types of services used differed. Rural caregivers reported greater use of family physicians (65.1% vs 40.7%; p=0.02), emergency room visits (31.8% vs 13.0%; p=0.02) and pharmacy services (95.3% vs 70.4%; p=0.002), while urban caregivers reported greater use of caregiver respite services (29.6% vs 11.6%; p=0.03). Conclusion: Through the use of standardized tools, this study explored the experiences of rural informal family caregivers providing palliative care in contrast to the experiences of their urban counterparts. The results of the present study suggest that while there are commonalities to the caregiving experience regardless of setting, key differences also exist. Thus, location is a factor to be considered when implementing palliative care programs and services. © K Brazil, S Kaasalainen, A Williams, C Rodriguez, 2013.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.