Study on the winding quality for spiral HTS cable based on AI detection model

The development of high temperature superconducting (HTS) conductors is leading to the diverse structure designs of HTS cable. (RE)Ba2Cu3Ox (REBCO) tapes using spiral geometry has been a popular compact HTS cable structure, which is in the critical stage of engineering production and application. However, the winding quality of REBCO tapes is unstable for spiral HTS cables, because of the different winding methods like manual winding, device-assisted winding, or automatic winding. Although automatic winding will be the first choice for the actual applications by spiral HTS cables, the related winding quality is not monitored effectively yet. In this paper, we first discuss the possible influence of the winding quality on the critical current performance of spiral HTS cables. Then, an artificial intelligence (AI) based method is implemented to realize the detection model for the winding quality. From image data preparation to AI detection and postprocessing, the detection model provides the final results to show the winding intervals as a binary image. Through the intuitive analysis and the evaluation metrics, both error and correct winding conditions obtain acceptable detection results, and the correct one has a better performance. The identification of the winding intervals will help to determine the monitoring strategy for the spiral HTS cable fabrication.

A multimode process monitoring strategy via improved variational inference Gaussian mixture model based on locality preserving projections

For multimode process monitoring, accurate mode information is difficult to be obtained, and each mode is monitored separately, which increases the complexity of the system. This paper proposes a multimode process monitoring strategy via improved variational inference Gaussian mixture model based on locality preserving projections (IVIGMM-LPP). First, the raw data are projected to the feature space where samples still maintain the original neighbor structure. Second, a new discriminant condition is introduced to reduce the influence of the initial category parameter on the iteration results in the VIGMM model. Then, the data are updated utilizing modal information, so that the scales of different modes are adjusted to the same level. Next, the deviation vector is introduced to eliminate the multi-center structure of data. Finally, the statistic is built to monitor the process. IVIGMM-LPP establishes one model for monitoring the premise of knowing the mode information, which reduces the complexity of the monitoring process and improves the fault detection rate. The experimental results of a numerical case and the Tennessee Eastman (TE) process verify the effectiveness of IVIGMM-LPP.

Impact of Fit-for-Purpose Monitoring on EOR Planning

Challenges in the design of efficient EOR field pilots have been discussed and documented in the industry, particularly when it comes to optimization of monitoring plans for technical and economical perspectives. This paper explores the benefits of pilot planning where the monitoring/control strategies are included in the early stages of the design to reduce risk of measurements ambiguity and ensure good quality pilot results evaluation. It addresses the use of new and existing technology in monitoring by highlighting the advantages and challenges of each alternative including potential pairing of complementary options to achieve the pilot objectives including illustration of the use of continuous and sporadic measurements on the evaluation. The proposed approach starts with a review of reservoir performance, heterogeneity and pilot objectives to ascertain the plausible monitoring technologies/strategies to aid during the pilot de-risking, followed by the identification of adequate novel and mature monitoring options, which are specific to EOR type and measurement nature (permanent, time lapse, etc.). Advantages of incorporating the monitoring strategy as integral part of the pilot design, as well as evaluation of the effectiveness/viability in the presence of uncertainty of the selected monitoring alternatives are discussed providing a reference of suitable/plausible EOR specific technologies. The paper illustrates the importance of selecting monitoring alternatives that feed off each other and the importance of using fit-for-purpose evaluation algorithms and a digitally enabled, structured approach to analyze and democratize pilot results and enable actionable decisions in operations.

Implementing a digital human resources management tool in the government health sector in Bangladesh: a policy content analysis

Introduction In Bangladesh, to address the challenges of ensuring adequate human resources for health (HRH), the government began implementing a digital tool for HRH management in 2017. However, evidence suggests institutionalizing such tools in low-and-middle-income countries is impeded by policy aspects like implementation strategy and poor regulatory framework. Therefore, we aimed to explore factors in the current policy landscape that might facilitate and challenge the implementation of the tool in Bangladesh. Methods We conducted a review of policies related to ICT implementation and human resources management in the health sector in Bangladesh using qualitative content analysis method. Ten policies have been identified, and extensive reading was done to ascertain common themes and patterns. A document analysis matrix was developed to synthesize and help interpret the findings. Results Regarding facilitators, strong upstream level commitments were reflected in the content of policies in terms of setting out specific objectives, targets, timelines, and budget allocation. However, the lack of explicit monitoring strategy and extent of stakeholders’ engagement was not well-defined, ultimately creating chances for impeding downstream implementation. In addition, effective coordination among stakeholders and different HRH and ICT policies could be strengthened. Discussion Findings support the current discourse that national commitment plays a vital role in the integration of ICTs in health services. However, well-defined monitoring strategy and inter-ministry and intra-ministry policy coordination are crucial.

The Influence of Monitoring Strategy on Assessment of Ablation Success and Post-ablation Atrial Fibrillation Burden Assessment: Implications for Practice and Clinical Trial Design

Background: Various non-invasive intermittent rhythm monitoring strategies have been used to assess arrhythmia recurrences in trials of atrial fibrillation (AF) ablation. We determined whether a frequency and duration of non-invasive rhythm monitoring could be identified that accurately detects arrhythmia recurrences and approximates the AF burden derived from continuous monitoring using an implantable cardiac monitor (ICM). Methods: The rhythm history of 346 patients enrolled in the CIRCA-DOSE trial was reconstructed. Using computer simulations, we evaluated event-free survival, sensitivity, negative predictive value, and AF burden of a range of non-invasive monitoring strategies, including those used in contemporary AF ablation trials. Results: A total of 126,290 monitoring days were included in the analysis. At 12 months, 164 patients experienced atrial arrhythmia recurrence as documented by the ICM (1-year event-free survival 52.6%). Most non-invasive monitoring strategies used in AF ablation trials had poor sensitivity for detecting arrhythmia recurrence. Sensitivity increased with the intensity of monitoring, with serial (3) short-duration monitors (24-/48-hour ECG monitors) missing a substantial proportion of recurrences (sensitivity 15.8% [95% confidence interval (CI) 8.9-20.7%] and 24.5% [95% CI 16.2-30.6%], respectively). Serial longer-term monitors (14-day ECG monitors) more closely approximated the gold-standard ICM (sensitivity 64.6% [95% CI 53.6-74.3%]). AF burden derived from short-duration monitors significantly over-estimated the true AF burden in patients with recurrences. Increasing monitoring duration resulted in improved correlation and concordance between non-invasive estimates of the invasive AF burden (R2 = 0.85 and interclass correlation coefficient = 0.91 for serial [3] 14-day ECG monitors vs ICM). Conclusions: Detection of arrhythmia recurrence following ablation is highly sensitive to the monitoring strategy employed, between-trial discrepancies in outcomes may reflect different monitoring protocols. Based on measures of agreement, serial long-term (7-14 day) intermittent monitors accumulating at least 28 days of annual monitoring provide estimates of AF burden comparable to ICM. However, ICMs outperform intermittent monitoring for arrhythmia detection, and should be considered the gold standard for clinical trials.