The future shape of digital cars

Background. Digital information is increasingly becoming available on all aspects of the urban landscape, anywhere and any time. Physical objects (c.f. the Internet of Things) and people (c.f. the Social Web) are increasingly infused with actuators, sensors and tagged with a wealth of digital information. Urban Informatics explores these emerging digital layers of the city. However, very little is known about the challenges and new opportunities that these developments may offer to road users. As we gradually spend more time using our mobile devices as well as our car, the tension between appeasing our craving for connectedness and road safety requirements grow farther apart. Objective. The aims of this paper are to identify (a) new opportunities that Urban Informatics research can offer to our future cars and (b) potential benefits to road safety. Methods. 14 Urban Informatics research experts were grouped into seven teams of two to participate in a guided ideation (idea creation) workshop in a driving simulator. They were immersed into different driving scenarios to brainstorm innovative Urban Informatics applications in different driving contexts. This qualitative study was then evaluated in the context of road safety. Outcomes. There is a lack of articulation between Urban Informatics and Road Safety research. Several Urban Informatics applications (e.g., to enhance social interaction between people in urban environments) may provide benefits, rather than threats, towards road safety, provided they are implemented ergonomically and safely. Conclusions. This research initiates a much-needed dialogue between Urban Informatics and Road Safety disciplines, in the context of Intelligent Transport Systems, before the fast approaching digital wave invades our cars. The dialogue will help to avoid driver distraction issues similar to mobile phones use in cars. As such, it provides valuable information for future regulators and policy makers in charge of shaping our future road transport landscape.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Towards visualising people’s ecology of hybrid personal learning environments

Ambient media architecture can provide place-based collaborative learning experiences and pathways for social interactions that would not be otherwise possible. This paper is concerned with ways of enhancing peer-to-peer learning affordances in library spaces; how can the library facilitate the community of library users to learn from each other? We report on the findings of a study that employed a participatory design method where participants were asked to reflect and draw places, social networks, and activities that they use to work (be creative, productive), play (have fun, socialize, be entertained), and learn (acquire new information, knowledge, or skills). The results illustrate how informal learning – learning outside the formal education system – is facilitated by a personal selection of physical and socio-cultural environments, as well as online tools, platforms, and networks. This paper sheds light on participants’ individually curated ecologies of their work, play, and learning related networks and the hybrid (physical and digital) nature of these places. These insights reveal opportunities for ambient media architecture to increase awareness of and connections between people’s hybrid personal learning environments.

A hybrid approach to combining CART and logistic regression for stock ranking

The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

A hybrid stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints, including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing most invalid matches. The accuracy of matching in the vicinity of edges is also improved.

Optimal planning of electric-vehicle charging stations in distribution systems

With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

An intelligent network control system for plug-in electric vehicles and the associate communication mechanism

The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup

Innovative hybrid composite floor plate system

New materials technology has provided the potential for the development of an innovative Hybrid Composite Floor Plate System (HCFPS) with many desirable properties, such as light weight, easy to construct, economical, demountable, recyclable and reusable. Component materials of HCFPS include a central Polyurethane (PU) core, outer layers of Glass-fibre Reinforced Cement (GRC) and steel laminates at tensile regions. HCFPS is configured such that the positive inherent properties of individual component materials are combined to offset any weakness and achieve optimum performance. Research has been carried out using extensive Finite Element (FE) computer simulations supported by experimental testing. Both the strength and serviceability requirements have been established for this lightweight floor plate system. This paper presents some of the research towards the development of HCFPS along with a parametric study to select suitable span lengths.

A hybrid simulation framework to assess the impact of renewable generators on a distribution network

With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.

Public, private, or hybrid? What the upstream oil and gas industry can learn from other sectors about ‘the cloud’

Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology (IT) infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry’s technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry’s services to be offered through cloud-based “apps.”

Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks

The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.

Multi-area reliability assessment of interconnected generating systems using hybrid approach

This paper present an efficient method using system state sampling technique in Monte Carlo simulation for reliability evaluation of multi-area power systems, at Hierarchical Level One (HLI). System state sampling is one of the common methods used in Monte Carlo simulation. The cpu time and memory requirement can be a problem, using this method. Combination of analytical and Monte Carlo method known as Hybrid method, as presented in this paper, can enhance the efficiency of the solution. Incorporation of load model in this study can be utilised either by sampling or enumeration. Both cases are examined in this paper, by application of the methods on Roy Billinton Test System(RBTS).

Social cars : sensing, gathering, sharing and conveying social cues to road users

Intelligent Transport Systems (ITS) resembles the infrastructure for ubiquitous computing in the car. It encompasses a) all kinds of sensing technologies within vehicles as well as road infrastructure, b) wireless communication protocols for the sensed information to be exchanged between vehicles (V2V) and between vehicles and infrastructure (V2I), and c) appropriate intelligent algorithms and computational technologies that process these real-time streams of information. As such, ITS can be considered a game changer. It provides the fundamental basis of new, innovative concepts and applications, similar to the Internet itself. The information sensed or gathered within or around the vehicle has led to a variety of context-aware in-vehicular technologies within the car. A simple example is the Anti-lock Breaking System (ABS), which releases the breaks when sensors detect that the wheels are locked. We refer to this type of context awareness as vehicle/technology awareness. V2V and V2I communication, often summarized as V2X, enables the exchange and sharing of sensed information amongst cars. As a result, the vehicle/technology awareness horizon of each individual car is expanded beyond its observable surrounding, paving the way to technologically enhance such already advanced systems. In this chapter, we draw attention to those application areas of sensing and V2X technologies, where the human (driver), the human’s behavior and hence the psychological perspective plays a more pivotal role. The focal points of our project are illustrated in Figure 1: In all areas, the vehicle first (1) gathers or senses information about the driver. Rather than to limit the use of such information towards vehicle/technology awareness, we see great potential for applications in which this sensed information is then (2) fed back to the driver for an increased self-awareness. In addition, by using V2V technologies, it can also be (3) passed to surrounding drivers for an increased social awareness, or (4), pushed even further, into the cloud, where it is collected and visualized for an increased, collective urban awareness within the urban community at large, which includes all city dwellers.

Hybrid light-emitting diodes based on ZnO nanowires

ZnO is a wide band-gap semiconductor that has several desirable properties for optoelectronic devices. With its large exciton binding energy of ~60 meV, ZnO is a promising candidate for high stability, room-temperature luminescent and lasing devices [1]. Ultraviolet light-emitting diodes (LEDs) based on ZnO homojunctions had been reported [2,3], while preparing stable p-type ZnO is still a challenge. An alternative way is to use other p-type semiconductors, ether inorganic or organic, to form heterojunctions with the naturally n-type ZnO. The crystal structure of wurtzite ZnO can be described as Zn and O atomic layers alternately stacked along the [0001] direction. Because of the fastest growth rate over the polar (0001) facet, ZnO crystals tend to grow into one-dimensional structures, such as nanowires and nanobelts. Since the first report of ZnO nanobelts in 2001 [4], ZnO nanostructures have been particularly studied for their potential applications in nano-sized devices. Various growth methods have been developed for growing ZnO nanostructures, such as chemical vapor deposition (CVD), Metal-organic CVD (MOCVD), aqueous growth and electrodeposition [5]. Based on the successful synthesis of ZnO nanowires/nanorods, various types of hybrid light-emitting diodes (LEDs) were made. Inorganic p-type semiconductors, such as GaN, Si and SiC, have been used as substrates to grown ZnO nanorods/nanowires for making LEDs. GaN is an ideal material that matches ZnO not only in the crystal structure but also in the energy band levels. However, to prepare Mg-doped p-GaN films via epitaxial growth is still costly. In comparison, the organic semiconductors are inexpensive and have many options to select, for a large variety of p-type polymer or small-molecule semiconductors are now commercially available. The organic semiconductor has the limitation of durability and environmental stability. Many polymer semiconductors are susceptible to damage by humidity or mere exposure to oxygen in the air. Also the carrier mobilities of polymer semiconductors are generally lower than the inorganic semiconductors. However, the combination of polymer semiconductors and ZnO nanostructures opens the way for making flexible LEDs. There are few reports on the hybrid LEDs based on ZnO/polymer heterojunctions, some of them showed the characteristic UV electroluminescence (EL) of ZnO. This chapter reports recent progress of the hybrid LEDs based on ZnO nanowires and other inorganic/organic semiconductors. We provide an overview of the ZnO-nanowire-based hybrid LEDs from the perspectives of the device configuration, growth methods of ZnO nanowires and the selection of p-type semiconductors. Also the device performances and remaining issues are presented.

A hybrid smoothed finite element method (H-SFEM) to solid mechanics problems

In this paper, a hybrid smoothed finite element method (H-SFEM) is developed for solid mechanics problems by combining techniques of finite element method (FEM) and Node-based smoothed finite element method (NS-FEM) using a triangular mesh. A parameter is equipped into H-SFEM, and the strain field is further assumed to be the weighted average between compatible stains from FEM and smoothed strains from NS-FEM. We prove theoretically that the strain energy obtained from the H-SFEM solution lies in between those from the compatible FEM solution and the NS-FEM solution, which guarantees the convergence of H-SFEM. Intensive numerical studies are conducted to verify these theoretical results and show that (1) the upper and lower bound solutions can always be obtained by adjusting ; (2) there exists a preferable at which the H-SFEM can produce the ultrasonic accurate solution.