Making smart decisions : key steps towards a typology for emergency communication during natural hazards

Governments, authorities, and organisations dedicate significant resources to encourage communities to prepare for and respond to natural hazards such as cyclones, earthquakes, floods, and bushfires. However, recent events, media attention, and ongoing academic research continue to highlight cases of non-compliance including swift water rescues. Individuals who fail to comply with instructions issued during natural hazards significantly impede the emergency response because they divert resources to compliance-enforcement and risk the lives of emergency service workers who may be required to assist them. An initial investigation of the field suggests several assumptions or practices that influence emergency management policy, communication strategy, and community behaviours during natural hazards: 1) that community members will comply with instructions issued by governments and agencies that represent the most authoritative voice, 2) that communication campaigns are shaped by intuition rather than evidence-based approaches (Wood et al., 2012), and 3) that emergency communication is linear and directional. This extended abstract represents the first stage of a collaborative research project that integrates industry and cross-disciplinary perspectives to provide evidence-based approaches for emergency and risk communication during the response and recovery phases of a natural hazard. Specifically, this abstract focuses on the approach taken and key elements that will form the development of a typology of compliance-gaining messages during the response phase of natural hazards, which will be the focus of the conference presentation.

A CCG virtual system for big data application communication costs analysis

Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

Two-way communication costs and the boundaries of the firm

Casson and Wadeson (International Journal of the Economics of Business, 1998, 5, pp. 5-27) have modelled the dialogue, or conversation, which customers have with their suppliers in order to convey their requirements, while taking production implications into account. They showed that this has important implications for the positioning of the boundaries of the firm. Unfortunately, their model has the restriction that communication is only costly in the direction of customer to supplier. This paper extends their model by introducing two-way communication costs. It shows that the level of communication cost in the direction of supplier to customer is a key additional factor in determining the nature of the dialogue that takes place. It also shows that this has important additional implications for the positioning of the boundaries of the firm. Custom computer software development is used as an example of an application of the theory.

Communication costs and the boundaries of the firm

Much has been written about where the boundaries of the firm are drawn, but little about what occurs at the boundaries themselves. When a firm subcontracts, does it inform its suppliers fully of what it requires, or is it willing to accept what they have available? In practice firms often engage in a dialogue, or conversation, with their suppliers, in which at first they set out their general requirements, and only when the supplier reports back on how these can be met are their more specific requirements set out. This paper models such conversations as a rational response to communication costs. The model is used to examine the impact of new information technology, such as CAD/CAM, on the conduct of subcontracting. It can also be used to examine its impact on the marketing activities of firms. The technique of analysis, which is based on the economic theory of teams, has more general applications too. It can be used to model all the forms of dialogue involved in the processes of coordination both within and between firms.

Status of legislation concerning 911: the emergency telephone number, with a suggested 911 Emergency Telephone Number Act with supporting analysis.

Mode of access: Internet.

Power line carrier equipment for relaying, telemetering, load control, remote trip and emergency communication ...

Mode of access: Internet.

Governmental social media use for emergency communication

The possibility of crowdsourced information, multi-geographical and multi-organisational information flows during emergencies and crises provided by web 2.0 tools are providing emergency management centres with new communication challenges and opportunities. Building on the existing emergency management and social media literature, this article explores how institutions are using and adopting social media for emergency communication. By examining the drivers and barriers of social media adoption in two European governmental agencies dealing with emergencies, the paper aims to establish a framework to examine whether and how institutional resilience could be improved.

Social media and its impact on crisis communication: Case studies of Twitter use in emergency management in Australia and New Zealand

There is a growing awareness worldwide of the significance of social media to communication in times of both natural and human-created disasters and crises. While the media have long been used as a means of broadcasting messages to communities in times of crisis – bushfires, floods, earthquakes etc. – the significance of social media in enabling many-to-many communication through ubiquitous networked computing and mobile media devices is becoming increasingly important in the fields of disaster and emergency management. This paper undertakes an analysis of the uses made of social media during two recent natural disasters: the January 2011 floods in Brisbane and South-East Queensland in Australia, and the February 2011 earthquake in Christchurch, New Zealand. It is part of a wider project being undertaken by a research team based at the Queensland University of Technology in Brisbane, Australia, that is working with the Queensland Department of Community Safety (DCS) and the EIDOS Institute, and funded by the Australian Research Council (ARC) through its Linkages program. The project combines large-scale, quantitative social media tracking and analysis techniques with qualitative cultural analysis of communication efforts by citizens and officials, to enable both emergency management authorities and news media organisations to develop, implement, and evaluate new social media strategies for emergency communication.

Effective emergency messaging during natural disasters: An application of message compliance theories

Study/Objective This research examines the types of emergency messages used in Australia during the response and early recovery phases of a natural disaster. The aim of the research is to develop theory-driven emergency messages that increase individual behavioural compliance during a disaster. Background There is growing evidence of non-compliant behaviour in Australia, such as refusing to evacuate and travelling through hazardous areas. This can result in personal injury, loss of life, and damage to (or loss of) property. Moreover, non-compliance can place emergency services personnel in life-threatening situations when trying to save non-compliant individuals. Drawing on message compliance research in psychology and sociology, a taxonomy of message types was developed to ascertain how emergency messaging can be improved to produce compliant behaviour. Method A review of message compliance literature was conducted to develop the taxonomy of message types previously found to achieve compliance. Seven categories were identified: direct-rational, manipulation, negative phrasing, positive phrasing, exchange appeals, normative appeals, and appeals to self. A content analysis was then conducted to assess the emergency messages evident in the Australian emergency management context. The existing messages were aligned with the literature to identify opportunities to improve emergency messaging. Results & Conclusion The results suggest there is an opportunity to improve the effectiveness of emergency messaging to increase compliance during the response and early recovery phases of a natural disaster. While some message types cannot legally or ethically be used in emergency communication (e.g. manipulative messaging), there is an opportunity to create more persuasive messages (e.g. appeals to self) that personalise the individual’s perception of risk, triggering them to comply with the message.

Communication between nodes for autonomic and distributed management

Over the last decade, the most widespread approaches for traditional management were based on the Simple Network Management Protocol (SNMP) or Common Management Information Protocol (CMIP). However, they both have several problems in terms of scalability, due to their centralization characteristics. Although the distributed management approaches exhibit better performance in terms of scalability, they still underperform regarding communication costs, autonomy, extensibility, exibility, robustness, and cooperation between network nodes. The cooperation between network nodes normally requires excessive overheads for synchronization and dissemination of management information in the network. For emerging dynamic and large-scale networking environments, as envisioned in Next Generation Networks (NGNs), exponential growth in the number of network devices and mobile communications and application demands is expected. Thus, a high degree of management automation is an important requirement, along with new mechanisms that promote it optimally and e ciently, taking into account the need for high cooperation between the nodes. Current approaches for self and autonomic management allow the network administrator to manage large areas, performing fast reaction and e ciently facing unexpected problems. The management functionalities should be delegated to a self-organized plane operating within the network, that decrease the network complexity and the control information ow, as opposed to centralized or external servers. This Thesis aims to propose and develop a communication framework for distributed network management which integrates a set of mechanisms for initial communication, exchange of management information, network (re) organization and data dissemination, attempting to meet the autonomic and distributed management requirements posed by NGNs. The mechanisms are lightweight and portable, and they can operate in di erent hardware architectures and include all the requirements to maintain the basis for an e cient communication between nodes in order to ensure autonomic network management. Moreover, those mechanisms were explored in diverse network conditions and events, such as device and link errors, di erent tra c/network loads and requirements. The results obtained through simulation and real experimentation show that the proposed mechanisms provide a lower convergence time, smaller overhead impact in the network, faster dissemination of management information, increase stability and quality of the nodes associations, and enable the support for e cient data information delivery in comparison to the base mechanisms analyzed. Finally, all mechanisms for communication between nodes proposed in this Thesis, that support and distribute the management information and network control functionalities, were devised and developed to operate in completely decentralized scenarios.

Non-uniform data distribution for communication-efficient parallel clustering

Global communicationrequirements andloadimbalanceof someparalleldataminingalgorithms arethe major obstacles to exploitthe computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication costin parallel data mining algorithms and, in particular, in the k-means algorithm for cluster analysis. In the straightforward parallel formulation of the k-means algorithm, data and computation loads are uniformly distributed over the processing nodes. This approach has excellent load balancing characteristics that may suggest it could scale up to large and extreme-scale parallel computing systems. However, at each iteration step the algorithm requires a global reduction operationwhichhinders thescalabilityoftheapproach.Thisworkstudiesadifferentparallelformulation of the algorithm where the requirement of global communication is removed, while maintaining the same deterministic nature ofthe centralised algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real-world distributed applications or can be induced by means ofmulti-dimensional binary searchtrees. The approachcanalso be extended to accommodate an approximation error which allows a further reduction ofthe communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing element

Dynamic group communication for large-scale parallel data mining

Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

Efficient group communication for large-scale parallel clustering

Global communication requirements and load imbalance of some parallel data mining algorithms are the major obstacles to exploit the computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication cost in iterative parallel data mining algorithms. In particular, the analysis focuses on one of the most influential and popular data mining methods, the k-means algorithm for cluster analysis. The straightforward parallel formulation of the k-means algorithm requires a global reduction operation at each iteration step, which hinders its scalability. This work studies a different parallel formulation of the algorithm where the requirement of global communication can be relaxed while still providing the exact solution of the centralised k-means algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real world distributed applications or can be induced by means of multi-dimensional binary search trees. The approach can also be extended to accommodate an approximation error which allows a further reduction of the communication costs.

Do international flights promote FDI? : the role of face-to-face communication

Air transportation facilitates face-to-face interactions across borders for the spatial expansion of manufacturing production. I investigate the impact of international flights on FDI entry by Japanese firms. I find that FDI entry significantly increases with the weekly frequency of flights from Japan, and the positive impact increases with a proxy for an intensity of face-to-face communication between the parent firm and foreign affiliate. The results are robust to estimation methods, additional control variables, and definitions of face-to-face communication. Thus, the results suggest that flights encourage FDI entry through a reduction in face-to-face communication costs.

9-1-1 emergency ... status report /

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