Pico Cell Integration to Operator’s Incident Management Process

Mobile network coverage is traditionally provided by outdoor macro base stations, which have a long range and serve several of customers. Due to modern passive houses and tightening construction legislation, mobile network service is deteriorated in many indoor locations. Typically, solutions for indoor coverage problem are expensive and demand actions from the mobile operator. Due to these, superior solutions are constantly researched. The solution presented in this thesis is based on Small Cell technology. Small Cells are low power access nodes designed to provide voice and data services.. This thesis concentrates on a specific Small Cell solution, which is called a Pico Cell. The problem regarding Pico Cells and Small Cells in general is that they are a new technological solution for the mobile operator, and the possible problem sources and incidents are not properly mapped. The purpose of this thesis is to figure out the possible problems in the Pico Cell deployment and how they could be solved within the operator’s incident management process. The research in the thesis is carried out with a literature research and a case study. The possible problems are investigated through lab testing. Pico Cell automated deployment process was tested in the lab environment and its proper functionality is confirmed. The related network elements were also tested and examined, and the emerged problems are resolvable. Operators existing incident management process can be used for Pico Cell troubleshooting with minor updates. Certain pre-requirements have to be met before Pico Cell deployment can be considered. The main contribution of this thesis is the Pico Cell integrated incident management process. The presented solution works in theory and solves the problems found during the lab testing. The limitations in the customer service level were solved by adding the necessary tools and by designing a working question pattern. Process structures for automated network discovery and pico specific radio parameter planning were also added for the mobile network management layer..

Policy analysis of disaster health management in China

Humankind has been dealing with all kinds of disasters since the dawn of time. The risk and impact of disasters producing mass casualties worldwide is increasing, due partly to global warming as well as to increased population growth, increased density and the aging population. China, as a country with a large population, vast territory, and complex climatic and geographical conditions, has been plagued by all kinds of disasters. Disaster health management has traditionally been a relatively arcane discipline within public health. However, SARS, Avian Influenza, and earthquakes and floods, along with the need to be better prepared for the Olympic Games in China has brought disasters, their management and their potential for large scale health consequences on populations to the attention of the public, the government and the international community alike. As a result significant improvements were made to the disaster management policy framework, as well as changes to systems and structures to incorporate an improved disaster management focus. This involved the upgrade of the Centres for Disease Control and Prevention (CDC) throughout China to monitor and better control the health consequences particularly of infectious disease outbreaks. However, as can be seen in the Southern China Snow Storm and Wenchuan Earthquake in 2008, there remains a lack of integrated disaster management and efficient medical rescue, which has been costly in terms of economics and health for China. In the context of a very large and complex country, there is a need to better understand whether these changes have resulted in effective management of the health impacts of such incidents. To date, the health consequences of disasters, particularly in China, have not been a major focus of study. The main aim of this study is to analyse and evaluate disaster health management policy in China and in particular, its ability to effectively manage the health consequences of disasters. Flood has been selected for this study as it is a common and significant disaster type in China and throughout the world. This information will then be used to guide conceptual understanding of the health consequences of floods. A secondary aim of the study is to compare disaster health management in China and Australia as these countries differ in their length of experience in having a formalised policy response. The final aim of the study is to determine the extent to which Walt and Gilson’s (1994) model of policy explains how disaster management policy in China was developed and implemented after SARS in 2003 to the present day. This study has utilised a case study methodology. A document analysis and literature search of Chinese and English sources was undertaken to analyse and produce a chronology of disaster health management policy in China. Additionally, three detailed case studies of flood health management in China were undertaken along with three case studies in Australia in order to examine the policy response and any health consequences stemming from the floods. A total of 30 key international disaster health management experts were surveyed to identify fundamental elements and principles of a successful policy framework for disaster health management. Key policy ingredients were identified from the literature, the case-studies and the survey of experts. Walt and Gilson (1994)’s policy model that focuses on the actors, content, context and process of policy was found to be a useful model for analysing disaster health management policy development and implementation in China. This thesis is divided into four parts. Part 1 is a brief overview of the issues and context to set the scene. Part 2 examines the conceptual and operational context including the international literature, government documents and the operational environment for disaster health management in China. Part 3 examines primary sources of information to inform the analysis. This involves two key studies: • A comparative analysis of the management of floods in China and Australia • A survey of international experts in the field of disaster management so as to inform the evaluation of the policy framework in existence in China and the criteria upon which the expression of that policy could be evaluated Part 4 describes the key outcomes of this research which include: • A conceptual framework for describing the health consequences of floods • A conceptual framework for disaster health management • An evaluation of the disaster health management policy and its implementation in China. The research outcomes clearly identified that the most significant improvements are to be derived from improvements in the generic management of disasters, rather than the health aspects alone. Thus, the key findings and recommendations tend to focus on generic issues. The key findings of this research include the following: • The health consequences of floods may be described in terms of time as ‘immediate’, ‘medium term’ and ‘long term’ and also in relation to causation as ‘direct’ and ‘indirect’ consequences of the flood. These two aspects form a matrix which in turn guides management responses. • Disaster health management in China requires a more comprehensive response throughout the cycle of prevention, preparedness, response and recovery but it also requires a more concentrated effort on policy implementation to ensure the translation of the policy framework into effective incident management. • The policy framework in China is largely of international standard with a sound legislative base. In addition the development of the Centres for Disease Control and Prevention has provided the basis for a systematic approach to health consequence management. However, the key weaknesses in the current system include: o The lack of a key central structure to provide the infrastructure with vital support for policy development, implementation and evaluation. o The lack of well-prepared local response teams similar to local government based volunteer groups in Australia. • The system lacks structures to coordinate government action at the local level. The result of this is a poorly coordinated local response and lack of clarity regarding the point at which escalation of the response to higher levels of government is advisable. These result in higher levels of risk and negative health impacts. The key recommendations arising from this study are: 1. Disaster health management policy in China should be enhanced by incorporating disaster management considerations into policy development, and by requiring a disaster management risk analysis and disaster management impact statement for development proposals. 2. China should transform existing organizations to establish a central organisation similar to the Federal Emergency Management Agency (FEMA) in the USA or the Emergency Management Australia (EMA) in Australia. This organization would be responsible for leading nationwide preparedness through planning, standards development, education and incident evaluation and to provide operational support to the national and local government bodies in the event of a major incident. 3. China should review national and local plans to reflect consistency in planning, and to emphasize the advantages of the integrated planning process. 4. Enhance community resilience through community education and the development of a local volunteer organization. China should develop a national strategy which sets direction and standards in regard to education and training, and requires system testing through exercises. Other initiatives may include the development of a local volunteer capability with appropriate training to assist professional response agencies such as police and fire services in a major incident. An existing organisation such as the Communist Party may be an appropriate structure to provide this response in a cost effective manner. 5. Continue development of professional emergency services, particularly ambulance, to ensure an effective infrastructure is in place to support the emergency response in disasters. 6. Funding for disaster health management should be enhanced, not only from government, but also from other sources such as donations and insurance. It is necessary to provide a more transparent mechanism to ensure the funding is disseminated according to the needs of the people affected. 7. Emphasis should be placed on prevention and preparedness, especially on effective disaster warnings. 8. China should develop local disaster health management infrastructure utilising existing resources wherever possible. Strategies for enhancing local infrastructure could include the identification of local resources (including military resources) which could be made available to support disaster responses. It should develop operational procedures to access those resources. Implementation of these recommendations should better position China to reduce the significant health consequences experienced each year from major incidents such as floods and to provide an increased level of confidence to the community about the country’s capacity to manage such events.

Hazard based models for freeway traffic incident duration

Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

Traffic incident clearance time and arrival time prediction based on hazard models

Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

Medication incident reporting in residential aged care facilities: Limitations and risks to residents' safety

Background Medication incident reporting (MIR) is a key safety critical care process in residential aged care facilities (RACFs). Retrospective studies of medication incident reports in aged care have identified the inability of existing MIR processes to generate information that can be used to enhance residents’ safety. However, there is little existing research that investigates the limitations of the existing information exchange process that underpins MIR, despite the considerable resources that RACFs’ devote to the MIR process. The aim of this study was to undertake an in-depth exploration of the information exchange process involved in MIR and identify factors that inhibit the collection of meaningful information in RACFs. Methods The study was undertaken in three RACFs (part of a large non-profit organisation) in NSW, Australia. A total of 23 semi-structured interviews and 62 hours of observation sessions were conducted between May to July 2011. The qualitative data was iteratively analysed using a grounded theory approach. Results The findings highlight significant gaps in the design of the MIR artefacts as well as information exchange issues in MIR process execution. Study results emphasized the need to: a) design MIR artefacts that facilitate identification of the root causes of medication incidents, b) integrate the MIR process within existing information systems to overcome key gaps in information exchange execution, and c) support exchange of information that can facilitate a multi-disciplinary approach to medication incident management in RACFs. Conclusions This study highlights the advantages of viewing MIR process holistically rather than as segregated tasks, as a means to identify gaps in information exchange that need to be addressed in practice to improve safety critical processes.

The European Flood Alert System and the communication, perception, and use of ensemble predictions for operational flood risk management

Although ensemble prediction systems (EPS) are increasingly promoted as the scientific state-of-the-art for operational flood forecasting, the communication, perception, and use of the resulting alerts have received much less attention. Using a variety of qualitative research methods, including direct user feedback at training workshops, participant observation during site visits to 25 forecasting centres across Europe, and in-depth interviews with 69 forecasters, civil protection officials, and policy makers involved in operational flood risk management in 17 European countries, this article discusses the perception, communication, and use of European Flood Alert System (EFAS) alerts in operational flood management. In particular, this article describes how the design of EFAS alerts has evolved in response to user feedback and desires for a hydrographic-like way of visualizing EFAS outputs. It also documents a variety of forecaster perceptions about the value and skill of EFAS forecasts and the best way of using them to inform operational decision making. EFAS flood alerts were generally welcomed by flood forecasters as a sort of ‘pre-alert’ to spur greater internal vigilance. In most cases, however, they did not lead, by themselves, to further preparatory action or to earlier warnings to the public or emergency services. Their hesitancy to act in response to medium-term, probabilistic alerts highlights some wider institutional obstacles to the hopes in the research community that EPS will be readily embraced by operational forecasters and lead to immediate improvements in flood incident management. The EFAS experience offers lessons for other hydrological services seeking to implement EPS operationally for flood forecasting and warning. Copyright © 2012 John Wiley & Sons, Ltd.

Emergency management in the highways of the future. A performance-based multilayered ITS architecture design proposal

Emergency management is one of the key aspects within the day-to-day operation procedures in a highway. Efficiency in the overall response in case of an incident is paramount in reducing the consequences of any incident. However, the approach of highway operators to the issue of incident management is still usually far from a systematic, standardized way. This paper attempts to address the issue and provide several hints on why this happens, and a proposal on how the situation could be overcome. An introduction to a performance based approach to a general system specification will be described, and then applied to a particular road emergency management task. A real testbed has been implemented to show the validity of the proposed approach. Ad-hoc sensors (one camera and one laser scanner) were efficiently deployed to acquire data, and advanced fusion techniques applied at the processing stage to reach the specific user requirements in terms of functionality, flexibility and accuracy.

Simplified guide to the incident command system for transportation professionals /

"February 2006."

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

COSMOS - Congestion management strategies and methods in urban sites.

The paper describes the strategies for Congestion and Incident Management (CIM) on the basis of Automatic Congestion and Incident Detection (ACID) that COSMOS will develop, implement in SCOOT, UTOPIA and MOTION, and validate and demonstrate in London, Piraeus and Torino. Four levels of operation were defined for CIM: strategies, tactics, tools and realisation. The strategies for CIM form the top level of this hierarchy. They have to reflect the strategic requirements of the system operators. The tactics are the means that can be employed by the strategies to achieve particular goals in particular situations. The tools that are used by the tactics relate to the elements of the signal plan and the ways in which they can be modified. Strategies, tactics and tools are generally common to all three systems, while the realisation of individual strategies and tactical decisions, through the use of particular common sets of tools, will generally be system specific. For the covering abstract, see IRRD 490001.

Managing hostile environments : journalists and media workers : learning to survive the world's difficult, remote and hostile environments

The aim of this research is to examine the changing nature of risks that face journalists and media workers in the world's difficult, remote and hostile environments, and consider the 'adequacy' of managing hostile environment safety courses that some media organizations require prior to foreign assignments. The study utilizes several creative works and contributions to this area of analysis, which includes a documentary film production, course contributions, an emergency reference handbook, security and incident management reviews and a template for evacuation and contingency planning. The research acknowledges that employers have a 'duty of care' to personnel working in these environments, identifies the necessity for pre-deployment training and support, and provides a solution for organizations that wish to initiate a comprehensive framework to advise, monitor, protect and respond to incidents. Finally, it explores the possible development of a unique and holistic service to facilitate proactive and responsive support, in the form of a new profession of 'Editorial Logistics Officer' or 'Editorial Safety Officer' within media organizations. This area of research is vitally important to the profession, and the intended contribution is to introduce a simple and cost-efficient framework for media organizations that desire to implement pre-deployment training and field-support – as these programs save lives. The complete proactive and responsive services may be several years from implementation. However, this study demonstrates that the facilitation of Managing Hostile Environment (MHE) courses should be the minimum professional standard. These courses have saved lives in the past and they provide journalists with the tools to "cover the story, and not become the story."

Motorway crash duration and its determinants: Do durations vary across motorways?

Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard-based models to develop in-depth insights into how the crash-specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, have been compared to random parameter AFT structures in terms of goodness of fit to the duration data and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway exhibits durations that are on average 19% shorter compared to the durations on motorway. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that, looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.