CHARACTERIZATION OF THE MICRO-SITE CONDITIONS FROM RESTORED AREAS WITH DIFFERENT AGES

Regeneration microsites are characterized by diverse combinations of attributes which assure the best conditions for seed germination and seedling establishment. By understanding these attributes, we can contribute to determining better management methodologies for reestablishing ecological process in sites under restoration. Thus, we sought to characterize and differentiate the micro-site conditions of restoration plantings to indentify likely physical-chemical limitations for the establishment of native tree species in the forest understory. This study was carried out in reforestation plantings with different ages (10, 22 and 55 years). The physical-chemical characterization of the micro-site of regeneration of the study areas was carried out by evaluating the soil compression level, porosity, humidity, organic matter and nutrients content and granulometry, as well as litter dry mass and canopy cover. An increase on the canopy cover and soil porosity, humidity, clay and organic matter content were observed in the oldest restored areas, as well as a decrease in soil compression. Thus, these findings demonstrated that the evaluated microsite properties are in process of restoration. Therefore, microsite conditions for seedling establishment become even more similar to reference ecosystems as restoration planting evolve.

Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Safe construction through design: perspectives from the site team

How does the work of designers impact on the safety of operatives at the construction site? Safety research and policy emphasize the importance of designing for safe construction, yet the interface between design and construction is poorly understood: accidents have multiple causes making it hard to establish causal links between design choices and safety outcomes. An in-depth case study of a major station project examines how professionals on the construction site perceive and manage the safety challenges of a building design. Analyses reveal understandings that, on the project studied, design has an impact on safety because of: (1) the timing of design work, where the volume of late design changes increased the difficulty of planning safe procedures, e.g. for working at height, lifting heavy items, refurbishing and demolishing old buildings; and (2) inputs from design stakeholders with insufficient practical knowledge of construction and operation required unplanned work-arounds, e.g. to coordinate different sub-systems, provide maintenance access, and manage loads during construction. These findings suggest that safety suffers where projects are under-designed, and that alongside regulation, there is a need for robust management attention to the contractual structures, incentives, processes and tools that enable clients and designers to understand material practices of construction and operation.

Outdoor worker sun protection project : a comprehensive applied research project to demonstrate the effectiveness of sun protection measures which influence high risk outdoor workers in Queensland to adopt sun safe behaviour practices 2010 – 2013

The QUT Outdoor Worker Sun Protection (OWSP) project undertook a comprehensive applied health promotion project to demonstrate the effectiveness of sun protection measures which influence high risk outdoor workers in Queensland to adopt sun safe behaviours. The three year project (2010-2013) was driven by two key concepts: 1) The hierarchy of control, which is used to address risks in the workplace, advocates for six control measures that need to be considered in order of priority (refer to Section 3.4.2); and 2) the Ottawa Charter which recommends five action means to achieve health promotion (refer to Section 2.1). The project framework was underpinned by a participatory action research approach that valued peoples’ input, took advantage of existing skills and resources, and stimulated innovation (refer to Section 4.2). Fourteen workplaces (small and large) with a majority outdoor workforce were recruited across regional Queensland (Darling Downs, Northwest, Mackay and Cairns) from four industries types: 1) building and construction, 2) rural and farming, 3) local government, and 4) public sector. A workplace champion was identified at each workplace and was supported (through resource provision, regular contact and site visits) over a 14 to 18 month intervention period to make sun safety a priority in their workplace. Employees and employers were independently assessed for pre- and postintervention sun protection behaviours. As part of the intervention, an individualised sun safety action plan was developed in conjunction with each workplace to guide changes across six key strategy areas including: 1) Policy (e.g., adopt sun safety practices during all company events); 2) Structural and environmental (e.g., shade on worksites; eliminate or minimise reflective surfaces); 3) Personal protective equipment (PPE) (e.g., trial different types of sunscreens, or wide-brimmed hats); 4) Education and awareness (e.g., include sun safety in inductions and toolbox talks; send reminder emails or text messages to workers);5) Role modelling (e.g., by managers, supervisors, workplace champions and mentors); and 6) Skin examinations (e.g., allow time off work for skin checks). The participatory action process revealed that there was no “one size fits all” approach to sun safety in the workplace; a comprehensive, tailored approach was fundamental. This included providing workplaces with information, resources, skills, know how, incentives and practical help. For example, workplaces engaged in farming complete differing seasonal tasks across the year and needed to prepare for optimal sun safety of their workers during less labour intensive times. In some construction workplaces, long pants were considered a trip hazard and could not be used as part of a PPE strategy. Culture change was difficult to achieve and workplace champions needed guidance on the steps to facilitate this (e.g., influencing leaders through peer support, mentoring and role modelling). With the assistance of the project team the majority of workplaces were able to successfully implement the sun safety strategies contained within their action plans, up skilling them in the evidence for sun safety, how to overcome barriers, how to negotiate with all relevant parties and assess success. The most important enablers to the implementation of a successful action plan were a pro-active workplace champion, strong employee engagement, supportive management, the use of highly visual educational resources, and external support (provided by the project team through regular contact either directly through phone calls or indirectly through emails and e-newsletters). Identified barriers included a lack of time, the multiple roles of workplace champions, (especially among smaller workplaces), competing issues leading to a lack of priority for sun safety, the culture of outdoor workers, and costs or budgeting constraints. The level of sun safety awareness, knowledge, and sun protective behaviours reported by the workers increased between pre-and post-intervention. Of the nine sun protective behaviours that were assessed, the largest changes reported included a 26% increase in workers who “usually or always” wore a broad-brimmed hat, a 20% increase in the use of natural shade, a 19% increase in workers wearing long-sleeved collared shirts, and a 16% increase in workers wearing long trousers.

Enabling aircraft emergency landings using active visual site detection

The ability to automate forced landings in an emergency such as engine failure is an essential ability to improve the safety of Unmanned Aerial Vehicles operating in General Aviation airspace. By using active vision to detect safe landing zones below the aircraft, the reliability and safety of such systems is vastly improved by gathering up-to-the-minute information about the ground environment. This paper presents the Site Detection System, a methodology utilising a downward facing camera to analyse the ground environment in both 2D and 3D, detect safe landing sites and characterise them according to size, shape, slope and nearby obstacles. A methodology is presented showing the fusion of landing site detection from 2D imagery with a coarse Digital Elevation Map and dense 3D reconstructions using INS-aided Structure-from-Motion to improve accuracy. Results are presented from an experimental flight showing the precision/recall of landing sites in comparison to a hand-classified ground truth, and improved performance with the integration of 3D analysis from visual Structure-from-Motion.

A dynamic Web agent for verifying the security and integrity of a Web site's contents

To harness safe operation of Web-based systems in Web environments, we propose an SSPA (Server-based SHA-1 Page-digest Algorithm) to verify the integrity of Web contents before the server issues an HTTP response to a user request. In addition to standard security measures, our Java implementation of the SSPA, which is called the Dynamic Security Surveillance Agent (DSSA), provides further security in terms of content integrity to Web-based systems. Its function is to prevent the display of Web contents that have been altered through the malicious acts of attackers and intruders on client machines. This is to protect the reputation of organisations from cyber-attacks and to ensure the safe operation of Web systems by dynamically monitoring the integrity of a Web site's content on demand. We discuss our findings in terms of the applicability and practicality of the proposed system. We also discuss its time metrics, specifically in relation to its computational overhead at the Web server, as well as the overall latency from the clients' point of view, using different Internet access methods. The SSPA, our DSSA implementation, some experimental results and related work are all discussed

Proactive training system for safe and efficient precast installation

The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system – the Proactive Construction Management System (PCMS) – to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Cluster randomised-control trial for an Australian child protection education program: Study protocol for the Learn to be safe with Emmy and friends™

Background Child maltreatment has severe short-and long-term consequences for children’s health, development, and wellbeing. Despite the provision of child protection education programs in many countries, few have been rigorously evaluated to determine their effectiveness. We describe the design of a multi-site gold standard evaluation of an Australian school-based child protection education program. The intervention has been developed by a not-for-profit agency and comprises 5 1-h sessions delivered to first grade students (aged 5–6 years) in their regular classrooms. It incorporates common attributes of effective programs identified in the literature, and aligns with the Australian education curriculum. Methods/Design A three-site cluster randomised controlled trial (RCT) of Learn to be safe with Emmy and friends™ will be conducted with children in approximately 72 first grade classrooms in 24 Queensland primary (elementary) schools from three state regions, over a period of 2 years. Entire schools will be randomised, using a computer generated list of random numbers, to intervention and wait-list control conditions, to prevent contamination effects across students and classes. Data will be collected at baseline (pre-assessment), immediately after the intervention (post-assessment), and at 6-, 12-, and 18-months (follow-up assessments). Outcome assessors will be blinded to group membership. Primary outcomes assessed are children’s knowledge of program concepts; intentions to use program knowledge, skills, and help-seeking strategies; actual use of program material in a simulated situation; and anxiety arising from program participation. Secondary outcomes include a parent discussion monitor, parent observations of their children’s use of program materials, satisfaction with the program, and parental stress. A process evaluation will be conducted concurrently to assess program performance. Discussion This RCT addresses shortcomings in previous studies and methodologically extends research in this area by randomising at school-level to prevent cross-learning between conditions; providing longer-term outcome assessment than any previous study; examining the degree to which parents/guardians discuss intervention content with children at home; assessing potential moderating/mediating effects of family and child demographic variables; testing an in-vivo measure to assess children’s ability to discriminate safe/unsafe situations and disclose to trusted adults; and testing enhancements to existing measures to establish greater internal consistency.

Estimation of design basis earthquake using region-specific M-max, for the NPP site at Kalpakkam, Tamil Nadu, India

The objective of the paper is to estimate Safe Shutdown Earthquake (SSE) and Operating/Design Basis Earthquake (OBE/DBE) for the Nuclear Power Plant (NPP) site located at Kalpakkam, Tamil Nadu, India. The NPP is located at 12.558 degrees N, 80.175 degrees E and a 500 km circular area around NPP site is considered as `seismic study area' based on past regional earthquake damage distribution. The geology, seismicity and seismotectonics of the study area are studied and the seismotectonic map is prepared showing the seismic sources and the past earthquakes. Earthquake data gathered from many literatures are homogenized and declustered to form a complete earthquake catalogue for the seismic study area. The conventional maximum magnitude of each source is estimated considering the maximum observed magnitude (M-max(obs)) and/or the addition of 0.3 to 0.5 to M-max(obs). In this study maximum earthquake magnitude has been estimated by establishing a region's rupture character based on source length and associated M-max(obs). A final source-specific M-max is selected from the three M-max values by following the logical criteria. To estimate hazard at the NPP site, ten Ground-Motion Prediction Equations (GMPEs) valid for the study area are considered. These GMPEs are ranked based on Log-Likelihood (LLH) values. Top five GMPEs are considered to estimate the peak ground acceleration (PGA) for the site. Maximum PGA is obtained from three faults and named as vulnerable sources to decide the magnitudes of OBE and SSE. The average and normalized site specific response spectrum is prepared considering three vulnerable sources and further used to establish site-specific design spectrum at NPP site.

Confined Site Construction: Issues Regarding Implementation of Health and Safety

The objective of this paper is to identify the various managerial constraints, difficulties and issues encountered and resulting strategies adopted, to aid in the management of the various and often complex health and safety concerns, which occur within a confined construction site. This is achieved through classifying the various managerial burdens encountered with the numerous strategies adopted, to ensure the successful management of such confined environments within the realm of health and safety. Through an extensive literature review and detailed interviews, a comprehensive insight into the health and safety concerns within a confined construction site environment is portrayed. The leading managerial strategies to the management of health and safety on confined construction sites may be listed as follows; (1) Traffic Management Plan, (2) Effective Resource Management Plan, (3) Temporary Facilities Management Plan, (4) Safe System of Work Plan, (5) Site Safety Plan, (6) Design Site Layout, (7) Space Management Plan, (8) Effective Program Management, and (9) Space Scheduling. Based on the research, it can be concluded, that through effective management of these issues identified coupled with implementing the various strategies highlighted; successful management of health and safety within a confined construction site environment is attainable.