A task and performance analysis of endoscopic submucosal dissection (ESD) surgery

BACKGROUND: ESD is an endoscopic technique for en bloc resection of gastrointestinal lesions. ESD is a widely-used in Japan and throughout Asia, but not as prevalent in Europe or the US. The procedure is technically challenging and has higher adverse events (bleeding, perforation) compared to endoscopic mucosal resection. Inadequate training platforms and lack of established training curricula have restricted its wide acceptance in the US. Thus, we aim to develop a Virtual Endoluminal Surgery Simulator (VESS) for objective ESD training and assessment. In this work, we performed task and performance analysis of ESD surgeries. METHODS: We performed a detailed colorectal ESD task analysis and identified the critical ESD steps for lesion identification, marking, injection, circumferential cutting, dissection, intraprocedural complication management, and post-procedure examination. We constructed a hierarchical task tree that elaborates the order of tasks in these steps. Furthermore, we developed quantitative ESD performance metrics. We measured task times and scores of 16 ESD surgeries performed by four different endoscopic surgeons. RESULTS: The average time of the marking, injection, and circumferential cutting phases are 203.4 (σ: 205.46), 83.5 (σ: 49.92), 908.4 s. (σ: 584.53), respectively. Cutting the submucosal layer takes most of the time of overall ESD procedure time with an average of 1394.7 s (σ: 908.43). We also performed correlation analysis (Pearson's test) among the performance scores of the tasks. There is a moderate positive correlation (R = 0.528, p = 0.0355) between marking scores and total scores, a strong positive correlation (R = 0.7879, p = 0.0003) between circumferential cutting and submucosal dissection and total scores. Similarly, we noted a strong positive correlation (R = 0.7095, p = 0.0021) between circumferential cutting and submucosal dissection and marking scores. CONCLUSIONS: We elaborated ESD tasks and developed quantitative performance metrics used in analysis of actual surgery performance. These ESD metrics will be used in future validation studies of our VESS simulator

Perfectionism and efficiency: Accuracy, response bias, and invested time in proof-reading performance

Investigating problem-solving performance, Ishida, H. (2005: College students’ perfectionism and task-strategy inefficience: Why their efforts go unrewarded? Japanese Journal of Social Psychology, 20, 208–215) found high levels of perfectionism were associated with lower efficiency. Aiming to replicate and further explore this finding, the present study investigated how two dimensions of perfectionism (high standards, discrepancy between expectations and performance) predicted efficiency in proof-reading performance. N = 96 students completed a proof-reading task involving the detection of spelling, grammar, and format errors. When error-detection performance was subjected to signal detection analysis, high standards correlated positively with the number of incorrectly detected errors (false alarms). Moreover, when task-completion time was taken into account, high standards were negatively correlated with efficiency (accuracy/time). In comparison, discrepancy correlated negatively with the number of correctly detected errors (hits) and positively with a conservative response bias. The findings show that perfectionistic standards are associated with reduced efficiency demonstrating the importance of considering invested time, errors, and response bias when investigating the relationship between perfectionism and performance

Timing Analysis for DAG-based and GFP Scheduled Tasks

Modern embedded systems have made the transition from single-core to multi-core architectures, providing performance improvement via parallelism rather than higher clock frequencies. DAGs are considered among the most generic task models in the real-time domain and are well suited to exploit this parallelism. In this paper we provide a schedulability test using response-time analysis exploiting exploring and bounding the self interference of a DAG task. Additionally we bound the interference a high priority task has on lower priority ones

Students’ Perceptions of Their Teachers’ Performance in Teaching Engineering Drawing in Nigerian Tertiary Institutions

There have been concerns about the performance of Nigerian school teachers’ in delivering occupational related courses. However, there are currently limited empirical data on this phenomenon – in particular with respect to the teaching of engineering drawing – to justify further actions from educational managers and policy makers. The aim of this study was to assess teachers’ performance in teaching engineering drawing using students’ perception as indicator of teachers’ performance. The study utilized a cross-sectional research design method with the target population of technical education students drawn from four (4) Federal Colleges of education (Technical) in Northern Nigeria. Stratified proportionate sampling technique was used to arrive at the study sample of 253 technical education students. A specifically designed instrument, the Students’ Perceptions of Teachers’ Performance Scales (SPTPS) was used to gather data on the three performance dimensions namely contextual, task and adaptability performance. The exploratory factor analysis and confirmatory factor analysis methods were conducted to validate the performance constructs. The instrument has a high reliability of 0.90 based on the Cronbach Alpha method. The result of the analysis using estimation method indicates that students perceive their teachers’ performance to be at a slightly above average level (M= 3.51 ± 0.05 at the 95% confidence level). The teachers’ task performance, in particular, is found to be the least developed among the three dimension of performance while their adaptability performance is the highest while still being less than excellent. The data support the conclusion that there are aspects of teachers’ performance in teaching engineering drawing that is less than excellent and in need of further enhancements

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks