Error correction in second language writing : teachers’ beliefs, practices, and students’ preferences

Error correction is perhaps the most widely used method for responding to student writing. While various studies have investigated the effectiveness of providing error correction, there has been relatively little research incorporating teachers' beliefs, practices, and students' preferences in written error correction. The current study adopted features of an ethnographic research design in order to explore the beliefs and practices of ESL teachers, and investigate the preferences of L2 students regarding written error correction in the context of a language institute situated in the Brisbane metropolitan district. In this study, two ESL teachers and two groups of adult intermediate L2 students were interviewed and observed. The beliefs and practices of the teachers were elicited through interviews and classroom observations. The preferences of L2 students were elicited through focus group interviews. Responses of the participants were encoded and analysed. Results of the teacher interviews showed that teachers believe that providing written error correction has advantages and disadvantages. Teachers believe that providing written error correction helps students improve their proof-reading skills in order to revise their writing more efficiently. However, results also indicate that providing written error correction is very time consuming. Furthermore, teachers prefer to provide explicit written feedback strategies during the early stages of the language course, and move to a more implicit strategy of providing written error correction in order to facilitate language learning. On the other hand, results of the focus group interviews suggest that students regard their teachers' practice of written error correction as important in helping them locate their errors and revise their writing. However, students also feel that the process of providing written error correction is time consuming. Nevertheless, students want and expect their teachers to provide written feedback because they believe that the benefits they gain from receiving feedback on their writing outweigh the apparent disadvantages of their teachers' written error correction strategies.

Time dependency of molecular rate estimates and systematic overestimation of recent divergence times

Studies of molecular evolutionary rates have yielded a wide range of rate estimates for various genes and taxa. Recent studies based on population-level and pedigree data have produced remarkably high estimates of mutation rate, which strongly contrast with substitution rates inferred in phylogenetic (species-level) studies. Using Bayesian analysis with a relaxed-clock model, we estimated rates for three groups of mitochondrial data: avian protein-coding genes, primate protein-coding genes, and primate d-loop sequences. In all three cases, we found a measurable transition between the high, short-term (<1–2 Myr) mutation rate and the low, long-term substitution rate. The relationship between the age of the calibration and the rate of change can be described by a vertically translated exponential decay curve, which may be used for correcting molecular date estimates. The phylogenetic substitution rates in mitochondria are approximately 0.5% per million years for avian protein-coding sequences and 1.5% per million years for primate protein-coding and d-loop sequences. Further analyses showed that purifying selection offers the most convincing explanation for the observed relationship between the estimated rate and the depth of the calibration. We rule out the possibility that it is a spurious result arising from sequence errors, and find it unlikely that the apparent decline in rates over time is caused by mutational saturation. Using a rate curve estimated from the d-loop data, several dates for last common ancestors were calculated: modern humans and Neandertals (354 ka; 222–705 ka), Neandertals (108 ka; 70–156 ka), and modern humans (76 ka; 47–110 ka). If the rate curve for a particular taxonomic group can be accurately estimated, it can be a useful tool for correcting divergence date estimates by taking the rate decay into account. Our results show that it is invalid to extrapolate molecular rates of change across different evolutionary timescales, which has important consequences for studies of populations, domestication, conservation genetics, and human evolution.

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.

Risky driving behavior among university students and staff in the Sultanate of Oman

Background: There is a well developed literature on research investigating the relationship between various driving behaviours and road crash involvement. However, this research has predominantly been conducted in developed economies dominated by western types of cultural environments. To date no research has been published that has empirically investigated this relationship within the context of the emerging economies such as Oman. Objective: The present study aims to investigate driving behaviour as indexed in the Driving Behaviour Questionnaire (DBQ) among a group of Omani university students and staff. Methods: A convenience non-probability self- selection sampling approach was utilized with Omani university students and staff. Results: A total of 1003 Omani students (n= 632) and staff (n=371) participated in the survey. Factor analysis of the BDQ revealed four main factors that were errors, speeding violation, lapses and aggressive violation. In the multivariate logistic backward regression analysis, the following factors were identified as significant predictors of being involved in causing at least one crash: driving experience, history of offences and two DBQ components i.e. errors and aggressive violation. Conclusion: This study indicates that errors and aggressive violation of the traffic regulations as well as history of having traffic offences are major risk factors for road traffic crashes among the sample. While previous international research has demonstrated that speeding is a primary cause of crashing, in the current context, the results indicate that an array of factors is associated with crashes. Further research using more rigorous methodology is warranted to inform the development of road safety countermeasures in Oman that improves overall traffic safety culture.

Verification of patient position and delivery of IMRT by electronic Portal Imaging

We have taken a new method of calibrating portal images of IMRT beams and used this to measure patient set-up accuracy and delivery errors, such as leaf errors and segment intensity errors during treatment. A calibration technique was used to remove the intensity modulations from the images leaving equivalent open field images that show patient anatomy that can be used for verification of the patient position. The images of the treatment beam can also be used to verify the delivery of the beam in terms of multileaf collimator leaf position and dosimetric errors. A series of controlled experiments delivering an IMRT anterior beam to the head and neck of a humanoid phantom were undertaken. A 2mm translation in the position of the phantom could be detected. With intentional introduction of delivery errors into the beam this method allowed us to detect leaf positioning errors of 2mm and variation in monitor units of 1%. The method was then applied to the case of a patient who received IMRT treatment to the larynx and cervical nodes. The anterior IMRT beam was imaged during four fractions and the images calibrated and investigated for the characteristic signs of patient position error and delivery error that were shown in the control experiments. No significant errors were seen. The method of imaging the IMRT beam and calibrating the images to remove the intensity modulations can be a useful tool in verifying both the patient position and the delivery of the beam.

New graduate occupational therapists' perceptions of near-misses and mistakes in the workplace

Purpose - The purpose of this paper is to explore the perceptions of near-misses and mistakes among new graduate occupational therapists from Australia and Aotearoa/New Zealand (NZ), and their knowledge of current incident reporting systems. Design/methodology/approach - New graduate occupational therapists in Australia and Aotearoa/NZ in their first year of practice (n=228) participated in an online electronic survey that examined five areas of work preparedness. Near-misses and mistakes was one focus area. Findings - The occurrence and disclosure of practice errors among new graduate occupational therapists are similar between Australian and Aotearoa/NZ participants. Rural location, structured supervision and registration status significantly influenced the perceptions and reporting of practice errors. Structured supervision significantly impacted on reporting procedure knowledge. Current registration status was strongly correlated with perceptions that the workplace encouraged event reporting. Research limitations/ implications - Areas for further investigation include investigating the perceptions and knowledge of practice errors within a broader profession and the need to explore definitional aspects and contextual factors of adverse events that occur in allied health settings. Selection bias may be a factor in this study. Practical implications - Findings have implications for university and workplace structures, such as clinical management, supervision, training about practice errors and reporting mechanisms in allied health. Originality/value - Findings may enable the development of better strategies for detecting, managing and preventing practice errors in the allied health professions.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Human errors in computer related abuses

The term “Human error” can simply be defined as an error which made by a human. In fact, Human error is an explanation of malfunctions, unintended consequents from operating a system. There are many factors that cause a person to have an error due to the unwanted error of human. The aim of this paper is to investigate the relationship of human error as one of the factors to computer related abuses. The paper beings by computer-relating to human errors and followed by mechanism mitigate these errors through social and technical perspectives. We present the 25 techniques of computer crime prevention, as a heuristic device that assists. A last section discussing the ways of improving the adoption of security, and conclusion.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

An application of the Driver Behaviour Questionnaire in a large Australian organisational fleeting setting : can it predict crashes and demerit point loss?

This study reports on the utilisation of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours of a large sample of Australian fleet drivers (N = 3414). Surveys were completed by employees before they commenced a one day safety workshop intervention. Factor analysis techniques identified a three factor solution similar to previous research, which was comprised of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Two items traditionally related with highway-code violations were found to be associated with aggressive driving behaviours among the current sample. Multivariate analyses revealed that exposure to the road, errors and self-reported offences predicted crashes at work in the last 12 months, while gender, highway violations and crashes predicted offences incurred while at work. Importantly, those who received more fines at work were at an increased risk of crashing the work vehicle. However, overall, the DBQ demonstrated limited efficacy at predicting these two outcomes. This paper outlines the major findings of the study in regards to identifying and predicting aberrant driving behaviours and also highlights implications regarding the future utilisation of the DBQ within fleet settings.

Contrast transfer function correction applied to cryo-electron tomography and sub-tomogram averaging

Cryo-electron tomography together with averaging of sub-tomograms containing identical particles can reveal the structure of proteins or protein complexes in their native environment. The resolution of this technique is limited by the contrast transfer function (CTF) of the microscope. The CTF is not routinely corrected in cryo-electron tomography because of difficulties including CTF detection, due to the low signal to noise ratio, and CTF correction, since images are characterised by a spatially variant CTF. Here we simulate the effects of the CTF on the resolution of the final reconstruction, before and after CTF correction, and consider the effect of errors and approximations in defocus determination. We show that errors in defocus determination are well tolerated when correcting a series of tomograms collected at a range of defocus values. We apply methods for determining the CTF parameters in low signal to noise images of tilted specimens, for monitoring defocus changes using observed magnification changes, and for correcting the CTF prior to reconstruction. Using bacteriophage PRDI as a test sample, we demonstrate that this approach gives an improvement in the structure obtained by sub-tomogram averaging from cryo-electron tomograms.

Sensitivity of an Elekta iView GT a-Si EPID model to delivery errors for pre-treatment verification of IMRT fields

A Monte Carlo model of an Elekta iViewGT amorphous silicon electronic portal imaging device (a-Si EPID) has been validated for pre-treatment verification of clinical IMRT treatment plans. The simulations involved the use of the BEAMnrc and DOSXYZnrc Monte Carlo codes to predict the response of the iViewGT a-Si EPID model. The predicted EPID images were compared to the measured images obtained from the experiment. The measured EPID images were obtained by delivering a photon beam from an Elekta Synergy linac to the Elekta iViewGT a-Si EPID. The a-Si EPID was used with no additional build-up material. Frame averaged EPID images were acquired and processed using in-house software. The agreement between the predicted and measured images was analyzed using the gamma analysis technique with acceptance criteria of 3% / 3 mm. The results show that the predicted EPID images for four clinical IMRT treatment plans have a good agreement with the measured EPID signal. Three prostate IMRT plans were found to have an average gamma pass rate of more than 95.0 % and a spinal IMRT plan has the average gamma pass rate of 94.3 %. During the period of performing this work a routine MLC calibration was performed and one of the IMRT treatments re-measured with the EPID. A change in the gamma pass rate for one field was observed. This was the motivation for a series of experiments to investigate the sensitivity of the method by introducing delivery errors, MLC position and dosimetric overshoot, into the simulated EPID images. The method was found to be sensitive to 1 mm leaf position errors and 10% overshoot errors.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

CBCT image guidance in head and neck irradiation: The impact of daily and weekly imaging protocols

Purpose This study evaluated the impact of a daily and weekly image-guided radiotherapy protocols in reducing setup errors and setting of appropriate margins in head and neck cancer patients. Materials and methods Interfraction and systematic shifts for the hypothetical day 1–3 plus weekly imaging were extrapolated from daily imaging data from 31 patients (964 cone beam computed tomography (CBCT) scans). In addition, residual setup errors were calculated by taking the average shifts in each direction for each patient based on the first three shifts and were presumed to represent systematic setup error. The clinical target volume (CTV) to planning target volume (PTV) margins were calculated using van Herk formula and analysed for each protocol. Results The mean interfraction shifts for daily imaging were 0·8, 0·3 and 0·5 mm in the S-I (superior-inferior), L-R (left-right) and A-P (anterior-posterior) direction, respectively. On the other hand the mean shifts for day 1–3 plus weekly imaging were 0·9, 1·8 and 0·5 mm in the S-I, L-R and A-P direction, respectively. The mean day 1–3 residual shifts were 1·5, 2·1 and 0·7 mm in the S-I, L-R and A-P direction, respectively. No significant difference was found in the mean setup error for the daily and hypothetical day 1–3 plus weekly protocol. However, the calculated CTV to PTV margins for the daily interfraction imaging data were 1·6, 3·8 and 1·4 mm in the S-I, L-R and A-P directions, respectively. Hypothetical day 1–3 plus weekly resulted in CTV–PTV margins of 5, 4·2 and 5 mm in the S-I, L-R and A-P direction. Conclusions The results of this study show that a daily CBCT protocol reduces setup errors and allows setup margin reduction in head and neck radiotherapy compared to a weekly imaging protocol.

Towards an understanding of the information dynamics of the handover process in aged care settings: A prerequisite for the safe and effective use of ICT

Background Poor clinical handover has been associated with inaccurate clinical assessment and diagnosis, delays in diagnosis and test ordering, medication errors and decreased patient satisfaction in the acute care setting. Research on the handover process in the residential aged care sector is very limited. Purpose The aims of this study were to: (i) Develop an in-depth understanding of the handover process in aged care by mapping all the key activities and their information dynamics, (ii) Identify gaps in information exchange in the handover process and analyze implications for resident safety, (iii) Develop practical recommendations on how information communication technology (ICT) can improve the process and resident safety. Methods The study was undertaken at a large metropolitan facility in NSW with more than 300 residents and a staff including 55 registered nurses (RNs) and 146 assistants in nursing (AINs). A total of 3 focus groups, 12 interviews and 3 observation sessions were conducted over a period from July to October 2010. Process mapping was undertaken by translating the qualitative data via a five-category code book that was developed prior to the analysis. Results Three major sub-processes were identified and mapped. The three major stages are Handover process (HOP) I “Information gathering by RN”, HOP II “Preparation of preliminary handover sheet” and HOP III “Execution of handover meeting”. Inefficient processes were identified in relation to the handover including duplication of information, utilization of multiple communication modes and information sources, and lack of standardization. Conclusion By providing a robust process model of handover this study has made two critical contributions to research in aged care: (i) a means to identify important, possibly suboptimal practices; and (ii) valuable evidence to plan and improve ICT implementation in residential aged care. The mapping of this process enabled analysis of gaps in information flow and potential impacts on resident safety. In addition it offers the basis for further studies into a process that, despite its importance for securing resident safety and continuity of care, lacks research.