Parameter Sensitive Detectors

Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and then train separate classifiers for each portion. However, with continuous spaces the partitions tend to be arbitrary since there are no natural boundaries (for example, consider the continuous range of human body poses). In this paper, a new formulation is proposed, where the detectors themselves are associated with continuous parameters, and reside in a parameterized function space. There are two advantages of this strategy. First, a-priori partitioning of the parameter space is not needed; the detectors themselves are in a parameterized space. Second, the underlying parameters for object variations can be learned from training data in an unsupervised manner. In profile face detection experiments, at a fixed false alarm number of 90, our method attains a detection rate of 75% vs. 70% for the method of Viola-Jones. In hand shape detection, at a false positive rate of 0.1%, our method achieves a detection rate of 99.5% vs. 98% for partition based methods. In pedestrian detection, our method reduces the miss detection rate by a factor of three at a false positive rate of 1%, compared with the method of Dalal-Triggs.

Hazard and early warning analysis based on domain specific modeling technologies

An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

Early warning sign attributes for the safety of drinking water treatment works

A proactive risk management strategy seeks to prevent accidents from taking place and maintain the safety of a system. In this context, the task of identifying and disseminating early warning signs and signals is among the most important. The problem is that warning signs that are present before an accident takes place are often being overlooked and not picked up or identified as warning signs. If these warning signs were responded to, then an accident may be averted. Accidents occuring in the critical domain of a drinking water treatments works can have serious implications for the public health of consumers of the water supplied. Realising and comprehending early warning signs is a major challenge for the domain of systems safety and especially in the domain of a water treatment works. The approaches that are typically used to enhance the realisation, comprehension and dissemination of early warning signs in the water treatment domain in Ireland mainly involves the creation of accident scenarios, the use of monitoring data and procedures for the dissemination of warnings. While all of these approaches are all useful to inform the mental or process models of possible accident scenarios, nevertheless, accidents are still occurring in this domain. Therefore, a new approach to enhance the comprehension of and effective dissemination of early warning signs is required in order to improve safety and proactive risk management strategies. The contributions of this thesis is the provision of a set of attributes associated with the early warning sign concept that provides meaningful data on the early warning signs and allows recipients to better comprehend them. The values of these attributes were customised for application in the water treatment domain. This research proves that early warning signs at a water treatment works received with information on their attributes are comprehended and communicated more effectively and efficiently than the usual pragmatic approach and thereby improves the safety and proactive risk management strategies.

The ecology of the Irish stoat

The Irish stoat, Mustela erminea hibernica (Thomas and Barrett-Hamilton), has been regarded as an intermediate between the British stoat and the weasel. In this study Irish stoats, mainly from road casualties, were collected and studied. A small number were also live-trapped and radio-tracked. Thus information was gathered on the stoat’s ecology, in particular its form (size and coat colours), reproduction, food habits, parasites, habitat utilisation mortality and predation. The Irish stoats studied were clearly not intermediate in size between British stoats and weasels. They showed considerable size overlap with British stoats, and marked size variation within Ireland. It is argued that size of stoats is determined by food supply early in life. The ventral coat pattern of Irish stoats is apparently unique in the Palaearctic, being similar to that of some stoats found on the west coast of North America. It is argued that this is an example of parallel evolution resulting from adaptation to similar climatic conditions. The stoats were reproductively active in spring and summer. Food consisted mainly of rabbits, but rats, birds, shrews mice and voles were also consumed. Mites were the most numerous ectoparasites, followed by lice, ticks and fleas. Damage by the parasitic nematode Skrjabingylus nasicola was found more frequently in female stoat skulls. Stoats were frequently found in a variety of habitats, both open and wooded. Some of the radio-tracked stoats climbed trees. Dens used were often rat holes. Only one home range, that of a breeding female, was considered to have been accurately measured. It was 22 ha. in size. Mortality is known to have been caused by road accidents and domestic carnivores. It is argued that predation by raptorial birds is important to stoat populations. Results of this study are compared with information available from elsewhere.

Study on street children in four selected towns of Ethiopia

The child is the most precious asset and the focal point of development for any country. However, unless children are brought up in a stimulating and conducive environment getting the best possible care and protection, their physical, mental, emotional and social development is susceptible to permanent damage. Ethiopia, being one of the least developed countries of the world due to interrelated and complex socio-economic factors including man-made and natural calamities, a large portion of our population - especially children - are victimized by social evils like famine, disease, poverty, mass displacement, lack of education and family instability. Owing to the fact that children are the most vulnerable group among the whole society and also because they constitute half of the population it is evident that a considerable number of Ethiopian children are living under difficult circumstances. Therefore, as in a number of other third world countries there are many poor, displaced, unaccompanied and orphaned children in our country. A considerable proportion of these children work on the street with some even totally living on the street without any adult care and protection. These children are forced to the streets in their tight for survival. They supplement their parents meagre income or support themselves with the small incomes they earn doing menial jobs. In doing this, street children face the danger of getting into accidents and violence, they get exploited and abused, many are forced to drop out of school or never get the chance to be enroled at all and some drift into begging or petty crime. This study is undertaken mainly for updating the findings of previous studies, monitoring changing trends, examining new facts of the problem and getting a better understanding of the phenomenon in the country by covering at least some of the major centres where the problem is acute. Thus, the outcome of this research can be useful in the formation of the social welfare programme of the country. Finally, in recognition of the urgency of the problem and the limited resources available, the Ministry of Labour and Social Affairs expresses appreciation to all agencies engaged in the rehabilitation of street children and prevention of the problem. The Ministry also calls for more co-operation and support between concerned governmental and non-governmental organizations in their efforts for improving the situation of street children and in curbing the overwhelming nature of the problem.

Road Traffic Injury Prevention Initiatives: A Systematic Review and Metasummary of Effectiveness in Low and Middle Income Countries.

BACKGROUND: Road traffic injuries (RTIs) are a growing but neglected global health crisis, requiring effective prevention to promote sustainable safety. Low- and middle-income countries (LMICs) share a disproportionately high burden with 90% of the world's road traffic deaths, and where RTIs are escalating due to rapid urbanization and motorization. Although several studies have assessed the effectiveness of a specific intervention, no systematic reviews have been conducted summarizing the effectiveness of RTI prevention initiatives specifically performed in LMIC settings; this study will help fill this gap. METHODS: In accordance with PRISMA guidelines we searched the electronic databases MEDLINE, EMBASE, Scopus, Web of Science, TRID, Lilacs, Scielo and Global Health. Articles were eligible if they considered RTI prevention in LMICs by evaluating a prevention-related intervention with outcome measures of crash, RTI, or death. In addition, a reference and citation analysis was conducted as well as a data quality assessment. A qualitative metasummary approach was used for data analysis and effect sizes were calculated to quantify the magnitude of emerging themes. RESULTS: Of the 8560 articles from the literature search, 18 articles from 11 LMICs fit the eligibility and inclusion criteria. Of these studies, four were from Sub-Saharan Africa, ten from Latin America and the Caribbean, one from the Middle East, and three from Asia. Half of the studies focused specifically on legislation, while the others focused on speed control measures, educational interventions, enforcement, road improvement, community programs, or a multifaceted intervention. CONCLUSION: Legislation was the most common intervention evaluated with the best outcomes when combined with strong enforcement initiatives or as part of a multifaceted approach. Because speed control is crucial to crash and injury prevention, road improvement interventions in LMIC settings should carefully consider how the impact of improvements will affect speed and traffic flow. Further road traffic injury prevention interventions should be performed in LMICs with patient-centered outcomes in order to guide injury prevention in these complex settings.

Accidentes en trabajadores ganaderos en Santa Fe, Argentina

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Numerical optimisation of water curtain barriers design

The interactions between water curtain protective barriers and impinging cold gas clouds released during industrial accidents are simulated by a 2D finite difference code using a PSI-cell of the heat, mass and momentum transfer processes between the phases. A consistent derivation of the continuous phase source terms is presented. The results of early simulations of an existing 1:10 experimental model of a water curtain impacted by a cold gas cloud are presented for two typical curtain configurations.

AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

Estimating the flow rate capacity of an overturned rail carriage end exit in the presence of smoke

While incidents requiring the rapid egress of passengers from trains are infrequent, perhaps the most challenging scenario for passengers involves the evacuation from an overturned carriage subjected to fire. In this paper we attempt to estimate the flow rate capacity of an overturned rail carriage end exit. This was achieved through two full-scale evacuation experiments, in one of which the participants were subjected to non-toxic smoke. The experiments were conducted as part of a pilot study into evacuation from rail carriages. In reviewing the experimental results, it should be noted that only a single run of each trial was undertaken with a limited — though varied — population. As a result it is not possible to test the statistical significance of the evacuation times quoted and so the results should be treated as indicative rather than definitive. The carriage used in the experiments was a standard class Mark IID which, while an old carriage design, shares many features with those carriages commonly found on the British rail network. In the evacuation involving smoke, the carriage end exit was found to achieve an average flow rate capacity of approximately 5.0 persons/min. The average flow rate capacity of the exit without smoke was found to be approximately 9.2 persons/min. It was noted that the presence of smoke tended to reduce significantly the exit flow rate. Due to the nature of the experimental conditions, these flow rates are considered optimistic. Finally, the authors make several recommendations for improving survivability in rail accidents. Copyright © 2000 John Wiley & Sons, Ltd.

An analysis of human behaviour during aircraft evacuation situations using the AASK v3.0 database

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.