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This paper proposes a mapping approach of various parameters and utilized an optimized Remote Sensing and GIS strategy. A part of Andhra Pradesh, the Krishna delta of Krishna District is chosen as the study area for the evaluation process. The paper incorporated essential information such as field data, topographic maps, IRS satellite images and other collateral maps as inputs. Significant position factors affecting the availability of surface water in the area were established, and corresponding thematic data layers were developed. These data layers depict the study location's geological, hydrological and topographical conditions. For spatial analysis in GIS software, an objective measurement scheme for the considerations was created. The resulting chart of water flow classifies the region into four distinct zones based on their relative information. The maps were validated by correlating the flow of water with the specified relative variables available. This is consistent with the observed field instability state. The map's usefulness was also demonstrated by the strong statistical significance as determined separately for every map.

This article proposes the variable sampling interval (VSI) exponentially weighted moving average (EWMA) t chart for the process mean using auxiliary information (AI) (denoted as the VSI EWMA t-AI chart). The proposed chart allows different sampling intervals to be adopted based on prior process quality. The average time to signal (ATS) and expected average time to signal (EATS) criteria are used to evaluate the performance of the proposed chart. Numerical analyses are conducted and the results show that the proposed VSI EWMA t-AI chart surpasses the EWMA t-AI chart in the detection of all sizes of shifts in the process mean when there are no changes (or estimation error) in the process standard deviation. Additionally, the proposed VSI EWMA t-AI chart is found to be more robust than the VSI EWMA X ¯ -AI chart when there are changes in the process standard deviation.

Background In Australia, midwives are integral to providing safe and supportive care to women in labour. The administration of intravenous (IV) fluids is a frequent clinical intervention performed by midwives. At present, practices surrounding IV fluid administration to women during labour within Australia are largely undescribed and there is a limited amount of robust evidence available to guide practice. IV fluids do carry a risk of harm. To define and ensure safe IV fluid practices, research into practices surrounding the administration of IV fluids to women in labour is essential. Aims To describe the current practice for registered midwives administering IV fluids to women during labour. Design Retrospective clinical chart review and fluid balance documentation audit. Methods A retrospective clinical chart review and audit of fluid balance documentation for 107 nulliparous women was conducted at a single metropolitan tertiary referral hospital in Sydney, New South Wales between 1 October 2016 and 22 March 2017. A 24-point tool was developed to audit fluid balance charts. Results Eighty-eight percent of the 88 fluid balance charts available scored 50% or less using the 24-point fluid balance chart audit tool. Additionally, there was an estimated 18% completion rate for the NSW IV fluid order chart. Conclusion This study found wide variation in clinical practice and incomplete fluid balance documentation at a single, metropolitan tertiary referral hospital. The findings highlight the difficulty of determining IV fluids practices in the context of incomplete fluid balance documentation. Additionally, there are patient safety and professional regulation concerns when fluid management documentation is missing and/or incomplete. Future research should examine barriers and facilitators for documentation.

Purpose The purpose of this quality improvement project was to improve care of obstructive sleep apnea (OSA) patients through increased staff recognition of OSA in the postanesthesia care unit (PACU). Design Retrospective chart review with implementation of best practice guideline form to front of patient's chart. Methods Baseline data were collected during June 2020. Staff education was provided on current hospital policy of OSA patients. Implementation of a care guideline sheet was added to the front of patient charts for patients meeting inclusion criteria; it consisted of continuous pulse oximetry, 30-degree head of bed elevation, continuous positive airway pressure (CPAP) therapy, 1 hour minimum postoperative observation, nonopioid analgesics, and referral to polysomnography. A retrospective chart review was performed following the OSA guideline intervention. Findings Both pre- (N = 413) and postintervention (N = 420) groups had statistically similar demographics. CPAP use increased from 16 to 22 (t = 0.890; P = .336). The number of patients experiencing dyspnea decreased from 10 to 8 (t = 0.263; P = .608). The number of patients experiencing acute respiratory events (AREs) decreased from 24 to 18 (t = 1.012; P = .314). Conclusion There were no significant statistical findings. However, increased recognition of OSA patients by PACU staff can lead to improved care alterations.

Clinicians are dependent on the electronic health record and electronic workflows to provide clinical care. Downtimes are always a threat, but in a time of cyberattacks, downtimes are no longer transient short-term events involving a broken piece of the network. Downtimes may be crime scenes involving multiple levels of law enforcement and may remain unresolved for days or weeks. Nursing units need to prepare through downtime drills; creation of downtime boxes with paper charts for each patient, paper charts for new admits, and additional necessary forms; and clear instructions for using the business continuity computer.

PURPOSE Efforts have been made to standardize laboratory variant interpretation, but clinicians are ultimately tasked with clinical correlation and application of genetic test results in patient care. This study aimed to explore processes clinicians utilize when reviewing and returning genetic test results, and how they impact patient care. METHODS Medical geneticists, genetic counselors, and nongenetics clinicians from two Midwestern states completed surveys (n = 98) and in-depth interviews (n = 29) on practices of reviewing and returning genetic test results. Retrospective chart review (n = 130) examined discordant interpretations and the impact on care. RESULTS Participants reported variable behaviors in both reviewing and returning results based on factors such as confidence, view of role, practice setting, and relationship with the lab. Providers did not report requesting changes to variant classifications from laboratories, but indicated relaying conflicting classifications to patients in some cases. Chart reviews revealed medically impactful differences in interpretation between laboratories and clinicians in 18 (13.8%) records. CONCLUSION Clinician practices for reviewing and integrating genetic test results into patient care vary within and between specialties and impact patient care. Strategies to better incorporate both laboratory and clinician expertise into interpretation of genetic results could result in improved care across providers and settings.

Background and Objectives At the beginning of human civilization, human being needs to undergo immense physical labor to survive. During those days high-calorie diet was essential. However, the evolution of technology has changed the scenario and much lesser amount of physical labor is required to survive in modern hi-tech days, requiring less amount of calorie. The excess calorie gets deposited in the body in the form of white fat. As a consequence, obesity appears as an epidemic all over the world. Long term obesity causes many diseases like heart attack, stroke, diabetes, and many other ailments. It is tough for people, who honestly want to check their obesity by controlling food habits, to continue a static diet chart with fixed restricted foods for a long time. Most of the time, people give up such restrictions on food. It will be very useful if a system exists, that will generate a dynamic diet chart based on calorie spend by the body. Methods This research describes a system that will generate a dynamic diet chart based on calorie spend by the body and other data like user's BMI, food preferences, etc. In this system, user can tailor his/her diet chart by changing daily physical activities (activities that burn calories). The main contributions of the proposed system are as follows: • A dedicated hardware system to quantify physical labor during walking and running throughout the day from feet pressure changes along with walk cycle detection. • The proposed hardware system can distinguish between walk and run. • A dynamic diet chart preparation system, where the user has the provision to plan his/her diet chart with food affinity. The entire work is divided into two modules; the first one focuses on the hardware design to detect and quantify physical activities during “walking” and “running”. These data are used in the second part. The second part contains calorie calculation along with the preparation of a dynamic diet chart with food affinity. In the hardware design, an Application Specific Integrated Circuit (ASIC) is proposed to measure the physical activity during “walking” and “running”. Result At the time of hardware logic synthesis, VHDL and FPGA are used. Experimental results show that the proposed hardware provides more accurate results than a pedometer. There is no standard metric to measure the performance of the dynamic diet chart generation system. Competency of the dietitian at the time of setting the parameters, honesty of the users at the time of the interactive session, etc. are the main factors that influence heavily the performance of the dynamic diet chart preparation system. The advantage of dynamic diet chart is that users can modify the diet menu as per their wish, and the system generates a diet chart in such a way that calorie intake (through food items) is maintained properly. In addition to this, the user can plan his future meals. Discussion This work is an interdisciplinary work. It is a blending of electronics (FSM), design, and computation for decision making; the computation portion includes software engineering, soft computing, etc. Future plan of this work is to integrate this system with “Cloud” to provide different data analysis related services, like region-wise food habit pattern prediction, health-related statistics, etc.

Investigating the effect of measurement errors on the control chart monitoring the ratio of two normal random variables is an important task to facilitate the use of this kind of control chart in practice. Moreover, a deep insight into the problem can help practitioners to find a way to reduce unexpected impacts of measurement errors on the chart performance. This paper provides a study on the performance of the exponentially weighted moving average control chart monitoring the ratio in the presence of measurement errors. We extend the linear covariate error model applied in previous studies to a more general situation, which makes the study more realistic. The numerical results show that although the precision error and the accuracy error have negative influences on the proposed chart performance when these errors are not large these influences are not significant.

Rockburst is defined as a phenomenon with immediate dynamic instability under excavation unloading conditions of deep or high geostress areas. Inadequate knowledge and lack of characterizing information prevent engineers and experts from achieving appropriate prediction results related to the rockburst behaviour. In this study, a data set including 220 rockburst instances was collected for rockburst classification via the geostatistical method. An update of the 2D graph, the tunnel rockburst classification (TRC) chart, was introduced based on analysing three indicators, namely, elastic energy index (Wet), tangential stress in rock mass (σθ), and uniaxial compressive strength (σc). Distribution and correlation of data were drawn on 2D plot, and the boundaries of rockburst were distinguished according to the achieved interpolate points by kriging method. Hierarchically, the validation phase was performed using an additional set of 28 case histories obtained from several projects around the world. The results showed that the TRC chart with an average error percentage of 3.6% in the prediction of rockburst had a significant and effective implementation in comparison to the exiting heuristic systems. Despite the initial character of the prediction, the described chart may be a helpful tool in the first steps of design and construction.

Objective To translate into Spanish and evaluate the evidence of content validity, construct validity and reliability of the Cancer Worry Chart as a single item measure of worry for cancer. Method The Spanish translation of the Cancer Worry Chart was done with the back-translation procedure. The participants were 165 healthy people with a family history of cancer who responded to the Cancer Worry Chart and the Cancer Worry Scale (CWS). Results Translation back-translation allows a Spanish version of the Cancer Worry Chart whose content is clear, coherent and relevant (V > .70). Evidence of construct validity is reported based on 3 criteria: (a) an adequate adjustment of the one-dimensional model formed by the Cancer Worry Chart and the items of the CWS performed with the structural equations method (χ2S-B = 23.38; df = 14; χ2S-B/df = 1.67; CFI = .988; RMSEA = .064); (b) a significant correlation between the Cancer Worry Chart and the CWS (r = .76 [IC95%: .68–.90]); (c) ascending averages in the CWS score as the groups formed by each response option of the Cancer Worry Chart express a greater degree of worry (F = 55.72; p = .000; ω2 = .57). The reliability of the Cancer Worry Chart is above what is recommended (αsingle item = .84). Conclusion The Spanish version of the Cancer Worry Chart showed satisfactory evidence of content validity, construct validity and reliability to measure, briefly, quickly and generally, the worry for cancer in healthy people with a family history of cancer.

BACKGROUND: In order to achieve rapid recovery total joint arthroplasty, surgeons and their teams are spending more time in the weeks before surgery to prepare patients. This study aims to quantify total knee and hip prearthroplasty work using retrospective electronic medical record (EMR) activity audit log analysis. METHODS: EMR activity in 100 elective knee and 100 elective hip arthroplasty cases was performed using audit logs. Each mouse click and action in the EMR was recorded. The time between mouse clicks was calculated and summed for each member of the clinical team. Descriptive statistics and independent samples t-tests were conducted to quantify and compare total preoperative work (POW) between groups defined by gender, procedure, age, insurance type, or health literacy (P < .05). RESULTS: The mean number of days defined in the prearthroplasty time period was 69.1 days (standard deviation [SD] 42.8; range 8-191). The mean time spent in each patient’s chart in the prearthroplasty period was 76.8 (SD 47.8) minutes. Surgeon’s work in the medical record accounted for 7.9 (SD 7.9) minutes, registered nurses 46.7 minutes (SD 39.1), physician extenders 10.8 minutes (SD 16.9), and licensed practical nurses and patient care technicians 9.8 minutes (SD 13.0). A significant difference was observed when groups were dichotomized based on age

A network of 18 pediatric practice locations serving predominantly commercially insured patients implemented the electronic administration of the Pediatric Symptom Checklist-17 parent-report (PSC-17P) for all 5.50- to 17.99-year-old children seen for well child visits (WCVs) and wrote up the results as a quality improvement project. The current study investigated this screening over 2 years to assess its implementation and risk rates over time.Parents completed the PSC-17P electronically before the visit and the scored data were immediately available in the patient's chart. Using billing and screening data, the study tracked rates of overall and positive screening during the first-year baseline (4 months) and full implementation phases of the project in the first (8 months) and second (12 months) year.A total of 35,237 patients completed a WCV in the first year. There was a significant improvement in PSC-17P screening rates from the first-year baseline (26.3%) to full implementation (89.3%; P.001) phases. In the second year, a total of 40,969 patients completed a WCV and 77.9% (n = 31,901) were screened, including 18,024 patients with screens in both years. PSC-17P screening rates varied significantly across the 18 locations and rates of PSC-17P risk differed significantly by practice, insurance type, sex, and age.The current study demonstrated the feasibility of routine psychosocial screening over 2 years using the electronically administered PSC-17P in a network of pediatric practices. This study also corroborated past reports that PSC-17 risk rates differed significantly by insurance type (Medicaid vs commercial), sex, and age group.

Background Quality improvement in the intensive care unit has transitioned from focusing on mortality to improving care and reducing morbidity. Objective This study prospectively investigated clinical and system drivers of family satisfaction in a large quaternary hospital ICU. Methods A validated tool was distributed to family members and a registry chart analysis was conducted. The aims were to assess associations with high or low family satisfaction to evaluate unit-level satisfaction. Candidate predictors were selected from univariate logistic regressions and finalized in a multivariate model by a stepwise selection approach. Results Overall, 75% (n = 188) of respondents (n = 250) indicated high satisfaction. Respondents with higher satisfaction had a Plan of the Day posted (OR = 3.3, 95% CI: 1.63, 6.89, p = 0.001), and did not live with the patient (OR =0.5, 95% CI: 0.25, 0.96, p = 0.044). Conclusion This study indicates that communication and transparency of plans contributes to family satisfaction with ICU care.

Technical analysts believe that by studying past price action, it is possible to forecast future prices of specific securities. Technical analysts rely on the use of charts, which graphically show the past fluctuations of prices. This study focuses on the chart style known as Japanese candlesticks, which relies on four pieces of information for every session: Open, High, Low and Close prices. It is believed that some candle patterns possess predictive capabilities that can alert investors of imminent price tops, bottoms, or price trend continuations. For this study, we performed a statistical analysis, using historical prices of the S&P 500 index, of the effectiveness of Bullish Engulfing and Bearish Engulfing patterns, which are believed to forecast bottoms and tops respectively. Results indicate that the Bearish Engulfing provide strong short-term forecasting power when using the Open and High criteria but not the Close criterion. Likewise, the Bullish Engulfing offered strong short-term forecasting power when using the Open and Low criteria but not the Close criterion.

The coding chart will abuse the speed up of downloading process skillfully. The customer can set up a single server at once, the server arrangement of different customers needs to be disconnected to ensure the download time is reduced. To achieve disjoint in download systems, a double clash coding chart is proposed. The immovability of the ideal long-haul arrangement, an online calculation using structured double clash charts is being proposed by a system. For example, one record demand for each customer is determined both asymptotic lower and upper limits of the proposed strife free calculation. Recreation results show this proposed calculation displays closer to ideal execution contrasted with the ideal arrangement, and decrease download time when contrasted with the single-server coding plan. In addition, situations relating to input conditions are investigated. A most extreme probabilistic approach is utilized at the server to evaluate the system state, which is then consolidated in our proposed calculation to decrease the download time in hard situations.

Objective The establishment of ongoing audits for first-trimester nuchal translucency (NT) measurements is of paramount importance. The exponentially weighted moving average (EWMA) chart has been published as an efficient tool for NT quality control with the advantages of being suitable for real-time long-term monitoring. This study aimed to assess the efficacy of real-time NT quality control using EWMA charts. Materials and methods This was an ongoing prospective study conducted from January 2011 to December 2017 at the Centre for Fetal Medicine Gennet in Prague. The quality of NT measurements was assessed using the NT retrospective distribution parameters and EWMA charts, and the results were presented to the sonographers during collective meetings. Results Overall, 28,928 NT measurements obtained from six sonographers were eligible for the study. Looking at individual EWMA charts, we observed four main outcomes. First, there was a clear improvement in the performance of sonographers with initially poor performances. Second, the performance of sonographers with an initially satisfactory quality was maintained. Third, there was an observed deterioration of the performance without the audits. Last, the sonographers appreciated an unequivocal and straightforward graphical presentation of EWMA curves. Conclusion EWMA proved to be an efficient and suitable tool for real-time monitoring of NT quality and led to an overall improvement of the sonographers’ performance.

Road infrastructure is an integral part of every individual, whether as a driver of a motor vehicle, a pedestrian or a cyclist. Road safety therefore directly affects life, health, property as well as the environment of society. The intensity of road traffic is growing from year to year, and the analysis of the road network, together with safety issues, is coming to the fore. Traffic accidents are on the rise and therefore providing a high level of road safety is an essential part of road traffic. The article described the issue of accident monitoring of the selected region as a web portal that communicates with the database and displays specific traffic accidents through chart background. The information system allocates data based on predefined access rights of individual users. The analysis and comparison of information systems focused on the mapping of traffic accidents led to the creation of an interactive map of traffic accidents. The main goal is to point out the current situation of road traffic, to provide statistical outputs to police forces and entities ensuring road safety, as well as to bring the safety situation on the road closer to the public.

The present work aims at improving the production line efficiency of a hemming unit by implementing three different line balancing techniques. For real time study, a hemming unit which involves 12 different work stations with manual execution was considered. The average actual cycle time at each station obtained through past data and the takt time for each station were compared using Yamazumi chart, which pertains to a line efficiency of 44% initially. It is found out that implementation of the line balancing techniques such as Kilbridge and Wester Column, Ranked Positional Weight, and Largest Candidate Rule significantly improved the line efficiency to 69%. The methods also established the possibility of reducing the number of work stations from 12 to 8. Out of the three methods, the Ranked Positional Weight method is found to be more effective for the present case, through Arena® simulation.

Bed bathing procedures taught to nursing students are not appropriately or fully implemented in hospitals by both nurses and nursing students. This signifies the need to review the bed bathing procedures used in schools, by either simplifying or conditioning them according to the practice area. This study is an analytical-descriptive research which aims to analyze ineffective movements in the conventional bed bathing procedure using the left-hand and right-hand map and further improvements of the procedure in order to improve work efficiency. The subjects of this study were six nursing students from the Nursing Study Program of Udayana University. This research was conducted by analyzing video-recorded data containing the procedures performed by the subjects using the left-hand and right-hand map. The mapping was carried out on the six students who had been trained to use the bed bathing procedure. The bed bathing procedure was divided into eight movement elements. This study found that the average time for bathing a patient was 12.17 min, excluding the time used for preparation, communication during bathing, tidying up the patient, and evaluation. The effective working time of the left hand was noted to be 6.25 min while that of the right hand was 11.40 min. The total waiting time on the left hand was 2.87 min while that of the right hand was 0.74 min. There were 3.26 min of left-hand holding of body parts such as the patient's hands and feet, which movement was not found on the right hand. Modification was conducted by eliminating ineffective movements based on the economic principles of movement and the left-hand and right-hand map. It was concluded that after modification the average time for bathing a patient was 5.73 min and work efficiency increased by 52.92%. Both hands worked simultaneously and there was no waiting movement.

Munsell soil-colour charts are widely used for soil classification. These charts contain 238 standardised colours in small rectangular chips arranged in seven charts and encoded in the Munsell system. Each chart uses three coordinates well correlated with the visual colour attributes: hue, value and chroma. The colour of a soil sample is commonly estimated by visual comparison between the actual soil colour and the Munsell chips, looking for the closest one and taking its Munsell notation. Consequently, the visual determination of soil colour with Munsell charts is a difficult task due to the subjectivity of the observer to match the colour of a soil sample with a single standard Munsell chip. For this reason, to avoid misclassification caused by subjective coincidence, we propose an intelligent method to provide the closest values of the Munsell chips to an unknown colour of a soil sample by using artificial neural networks and fuzzy logic.

Objective The present study aimed to elucidate opinions regarding comprehensibility of audiometry display formats among otolaryngologists in Japan, and to identify the characteristics of otolaryngologists’ cognitive processes for audiometry. Methods We conducted a cross-sectional nationwide questionnaire-based mail survey regarding the comprehensibility of audiometry display formats among 543 Japanese otolaryngologists. Of 543 otolaryngologists to whom the questionnaires were mailed, 137 replied to the questions. For the analysis, the sample size used was 112 participants. The questionnaire contained questions regarding the otolaryngologists’ occupational characteristics, and assessed their opinions of four comprehensibility aspects of five display formats. Results Otolaryngologists in clinics indicated that the passage of time and changes in thresholds of each frequency in numeric tables were ordinary or incomprehensible. More than 60% of otolaryngologists with extensive experience in using electronic medical records indicated that both, the passage of time and change in the thresholds in overlaid thresholds on a chart were comprehensible. Conclusions Display formats in audiometry influenced the comprehension of pure tone audiometry data. Our results suggest that overlaid thresholds on a chart rather than numeric table or multi-dimensional charts are the primary choice for computerized audiometry display formats in most aspects of audiometry.

Purpose To determine the improvement in patient adherence to topical ocular hypotensive therapy by introducing a personalized illustrated medication reference chart and telereminder. Design Prospective randomized controlled clinical trial. Participants Fifty-nine patients with glaucoma who were using at least 3 or more eye drops were recruited from the ophthalmology clinic at the National University Hospital of Singapore. Methods Participants were randomized into 3 groups: control, reference chart only, and reference chart with telereminder. They completed a survey on demographics, barriers to glaucoma medication adherence, and self-adherence (measured by the Morisky adherence scale) before and 6 weeks after intervention. Logistic regression analysis was performed on the barriers that contribute to nonadherence and paired t tests were conducted for the preimplementation and postimplementation effects of intervention on adherence score. Main Outcome Measures Changes in mean adherence score based on the Morisky adherence scale before and after intervention in participants from all 3 groups. Results In our study, 71% of participants who were nonadherent to medications had multiple barriers to adherence, with lack of self-efficacy and forgetfulness being the most common factors. Only the reference chart with telereminder group showed a statistically significant increase in mean adherence score, from 7.18 to 7.69 (P = 0.047). Conclusions Adherence to medication in chronic diseases like glaucoma is an important healthcare issue to address. Most of these patients have poor adherence because of multiple factors, and hence interventions aimed at improving adherence should be multifaceted to target these barriers.

The accurate estimation of the health (reliability) index is important to estimate probability of failure in the reliability assessment of structures. The conventional first-order reliability methods including the Hasofer-Lind, Rackwitz-Fiessler, and Monte Carlo could lead to unstable, fluctuating, and distorted solutions to nonlinear problems, featuring complicated structural performance functions. The present study aimed to propose a new method by combining the particle swarm optimization and differential evolution algorithms in order to calculate the reliability index. The performance of the proposed method was evaluated by 10 examples from different studies, and the convergence results were compared to the results of studies such as Hasofer-Lind, Rackwitz-Fiessler, Monte Carlo and some other methods. To verify the accuracy of the proposed method, to verify the accuracy of the proposed method, a reliability index chart was applied. The comparisons indicated the high accuracy and speed of the proposed method. Accordingly, in higher order nonlinear problems, the proposed method successfully calculated the reliability index while some failed to solve these problems.

Purpose Peer review during physician chart rounds is a major quality assurance and patient safety step in radiation oncology. However, the effectiveness of chart rounds in detecting problematic treatment plans is unknown. We performed a prospective blinded study of error detection at chart rounds to clarify the effectiveness of this quality assurance step. Methods and Materials Radiation Oncology Incident Learning System publications were queried for problematic plans approved for treatment that would be detectable at chart rounds. A resident physician, physicist, and dosimetrist collaboratively generated 20 treatment plans with simulated errors identical in nature to those reported to the Radiation Oncology Incident Learning System. These were inserted randomly into weekly chart rounds over 9 weeks, with a median of 2 problematic plans presented per chart rounds (range, 1-4). Data were collected on detection, attendance, length, and number of cases presented at chart rounds. Data were analyzed using descriptive statistics and univariable logistic regression with odds ratios. Results The median length of chart rounds over the study period was 60 minutes (range, 42-79); median number of cases presented per chart rounds was 45 (range, 38-50). The overall detection rate was 55% (11 of 20). Detection rates were higher for cases presented earlier in chart rounds: 75% versus 25% of problematic plans were detected within 30 minutes of start of chart rounds versus after 30 minutes (odds ratio, 0.11; 95% confidence interval, 0.01–0.88; P = .037). Detection rates showed a trend toward increase during the study period but this was not significant: 33% in weeks 1 to 5 and 73% during weeks 6 to 9 (5.3; 95% confidence interval, 0.78–36; P = .08). Conclusions The detection of clinically significant problematic plans during chart rounds could be significantly improved. Problematic plans are more frequently detected earlier in chart rounds and inserting such plans into chart rounds may enhance detection; however, larger studies are needed to confirm these findings. A multi-institutional study is planned.

Background Measuring the impact of patient safety interventions is challenging. This article aims to illustrate a “gold standard” model of program evaluation incorporating examples from two patient deterioration programs. Methods Australian nurses were trained in primary responses to emergencies in four hospitals using either face-to-face (F2F) or screen-based simulation versions of a simulation program. Evaluation outcomes were measured using Kirkpatrick's evaluation hierarchy covering participant ‘reaction’, ‘learning’, ‘behaviour’ change and ‘results’—based on 1,564 pre–post intervention vital signs chart reviews. Results Seventy-four nurses participated. Reaction—participant confidence/competence ratings and Learning improved significantly in both modalities (p Conclusions Kirkpatrick's evaluation model enables a suitable template for gold standard education evaluations.

This editorial describes an effort by 9 consultation-liaison (C-L) psychiatry service leaders in the United States to incorporate routine performance measurement into their service workflows. Although C-L psychiatry is an essential clinical service in general hospitals, performance metrics for this service have not been broadly accepted or implemented. Meanwhile, the performance metrics that have been developed rely on an investment in resources and/or new workflows that C-L psychiatry services may not be prepared to make on a widespread level. Our group sought to determine the feasibility of incorporating routine performance measurement into the workflows of a diverse sample of C-L psychiatry services using only existing resources via three collection methods: timestamp review, chart auditing, and survey administration. No methods were broadly successful across the 9 services. We argue that for routine performance measurement to gain wider traction in the field of C-L psychiatry, the ready availability-or automatability-of performance data must be taken into account.

The objective of this paper is to present a view of the geodiversity of the Historical Center of João Pessoa, located in Mata da Aldeia chart (scale 1:25.000), Paraíba State, northern Brazil, in order to insert sites in urban geotouristic routes. For this, a mapping of this geodiversity and its geoheritage was carried out through the inventory of sites with relevant value. Geologically, the chart is part of a sedimentary basin that developed on a faulted crystalline basement, whose Plio-Pleistocene reactivation resulted in a stepped substrate, and the terrain has geotouristic potential from the point of view of its geoheritage. It was necessary a detailed study of the geoscientific and historic literature of the area and a detailed field work, having a look about the physical substrate reflecting the importance of this as a heritage element of space. Tambiá fountain, Trincheiras fossil, Ireres doline, Stone Square, Santo Antônio fountain, Miracles fountain and Sanhauá fault were identified as geotouristic sites. It is therefore pertinent to interconnect this urban heritage to tourism in the area, so that more motivation arouses the interest of tourists, now turned to the bias of the lithosphere and hydrosphere. Keywords: Geoheritage, João Pessoa, Historical center, Mata da Aldeia chart, Paraíba, Geotourism

In this paper we consider a new fault detection approach that merges the benefits of Gaussian process regression (GPR) with a generalized likelihood ratio test (GLRT). The GPR is one of the most well-known machine learning techniques. It is simpler and generally more robust than other methods. To deal with both high computational costs for large data sets and time-varying dynamics of industrial processes, we consider a reduced and online version of the GPR method. The online reduced GPR (ORGPR) aims to select a reduced set of kernel functions to build the GPR model and apply it for online fault detection based on GLRT chart. Compared with the conventional GPR technique, the proposed ORGPR method has the advantages of improving the computational efficiency by decreasing the dimension of the kernel matrix. The developed ORGPR-based GLRT (ORGPR-based GLRT) could improve the fault detection efficiency since it is able to track the time-varying characteristics of the processes. The fault detection performance of the developed ORGPR-based GLRT method is evaluated using a Tennessee Eastman process. The simulation results show that the proposed method outperforms the conventional GPR-based GLRT technique.

This study is aimed at reducing the defective parts during production in plastic injection moulding industries. The study was taken up in a plastic processing industry, in which due to increased defects, PPM (Parts per million) rate of the company was affected. The study turned into a defect reduction analysis due to not fully acceptable lead times. Limitations were set to one specific part for case study and a time frame from January to March 2018. The methodology behind this report and study was Design of Experiment developed by Sir Ronald Fisher. The analysis made in this report was of the quantitative kind with interviews and observations of current setting chart of that part. The findings from this report showed that an optimized setting chart is beneficial to limit errors due to faulty setups and information transfers. The conclusion of this report resulted in a standardized manual/routine for the specific part under consideration, improved productivity, and reduced ppm level.

A proxy measurement of four resilience potentials (respond, monitor, learn, and anticipate) developed by Hollnagel is called the resilience assessment grid (RAG). This study aimed to attain an enhanced understanding of the resilience performance of emergency departments (EDs) in terms of the four potentials across hospitals through the adoption of a custom-made RAG (ED-RAG). The study setting was four hospitals. The ED-RAG questionnaire was used to interview focus groups at the four EDs from February to June 2015. All interviews were led by the lead researcher and the interview transcripts were evaluated using the ED-RAG four-point scoring scale. Four radar charts of individual resilience potentials and a star chart presenting a system’s potential of overall resilience performance for each hospital’s ED were generated. The charts provide visualized results that indicate clear directions for making improvement plans toward resilience in EDs. Overall, all EDs exhibited considerable potential to learn compared with the other three potentials at the time of measurement. Common strengths and weaknesses with respect to developing the four potentials were identified. Besides, no association between potential scores and staffing capacity, and no significant differences of resilience performance between hospital types were found. EDs’ ability to perform in a resilient manner can be critical under considerable uncertainty and economic pressure. The study revealed essential knowledge about the development of resilience potentials in emergence departments among hospitals. The findings could contribute to the promotion of resilient health care.

As the manufacturing industry progresses towards the Internet of Things (IoT) and Cyber-Physical Systems (CPS), current methods of historical data analytics face difficulties in addressing the new challenges which follow Industry 4.0. Industry 4.0 and IoT technologies facilitate the acquisition of ubiquitous data from machine tools and processes. However, these technologies also lead to the generation of a large number of data that are complex to be analyzed. Due to the streaming nature of the IoT systems, however, stream analytics could be used to extract features as the data are generated and published, which can prevent the need to store the data and perform advanced analytics that require high performance computing. This manuscript aims at demonstrating how traditional historical methods can be modified to be used as stream analytics tools for IoT data streams. Since data analytics is a wide domain, this paper has only focused on the two light-weighted methods that have been popular in the industry: Statistical Process Control Chart (SPCC), and Bayesian classification. This paper has defined, tested, and evaluated the accuracy and latency of the novel variation of these methods. It is concluded that by modifying the traditional methods and defining incremental solutions, methods such as Real-Time Dynamic Statistical Process Control Chart (RTDSPCC) and Incremental Gaussian Naive Bayes (IGNB) can be formed that are highly beneficial for IoT applications as they are highly scalable, require minimal storage, and can update the models in real-time.

Exponentially weighted moving average (EWMA) control charts are typically used for faster detection of shifts in the process mean, relative to a Shewhart control chart, when the degree of shift is small. Normal guidelines suggest using a small (large) value of the weighting constant, λ, for detecting smaller (larger) shifts in the process mean. Prior research has suggested that the choice of λ should depend on the observed data and have considered the use of a weighting constant, that varies and adapts as monitoring continues and new data are collected. One such adaptive control chart, called the AEWMA chart, utilizes a rather computationally complex scheme to determine the weighting constant λ and it requires knowledge of the size of the shift, to specify whether it is “small” or “large”. A complex two-phase optimization scheme is then solved to yield “good solutions”. As an alternative, we propose an adaptive EWMA-type control chart that does not require knowledge of the degree of the shift. Further, the computational scheme is easier and completed in one stage. The performance of the proposed chart is studied using simulations, where the degree of the shift in the process mean is varied over a wide range of values. Based on the average run length (ARL), as a performance measure, the proposed chart is demonstrated to perform uniformly better than the traditional EWMA chart with a constant weight. The proposed chart also performs better than the AEWMA chart for moderate to large shifts.

In order to reveal the reasons for the differences in initial water production characteristics of gas wells in different regions of the East China Sea Basin and to screen favorable targets for low-permeability reservoir reconstruction, a calculation method of initial production water–gas ratios at different gas column heights was established by combining gas-water two-phase capillary pressure with J function definition, power function relative permeability model and fractional flow equation. Then based on the experimental data of standard capillary pressure and standard relative permeability in the gas province of the East China Sea, an evaluation chart on initial production water–gas ratio of the East China Sea at different gas column heights was calculated and established. Finally, the evaluation chart was validated by using the data of the tested or commissioned gas wells in the gas reservoirs of the East China Sea, and the physical property conditions suitable for reservoir reconstruction of low-permeability gas reservoirs in the East China Sea were determined according to the evaluation chart. The following research results were obtained. First, the evaluation chart established in this paper reflects that the correlation between the parameters is similar to the actual production law and matches well with the actual data, which verifies the correctness and reliability of the chart establishment method and the key parameter calculation method. Second, with the production water–gas ratio less than 1 m3/104 m3 as the screening condition, for the permeability of the low-permeability gas reservoirs (with gas column height of about 50 m) in the west sub-sag, the central uplift belt and the periphery suitable for reservoir reconstruction shall be greater than 0.65 mD, and that of the large low-permeability gas reservoirs (with a gas column height of more than 100 m) in the north of central uplift belt shall be greater than 0.26 mD. Third, there is no gas–water contact in gas reservoirs under the hydrocarbon accumulation conditions of in-situ reservoirs, so the method and the evaluation chart proposed in this paper are not applicable. It is concluded that the method of establishing the initial water production evaluation chart and the method of calculating the key parameters proposed in this paper can provide meaningful reference for the development and evaluation of other gas fields in China. Keywords: China, East China Sea Basin, Gas reservoir, Capillary pressure, Relative permeability model, Water–gas ratio, Evaluation chart, Reservoir reconstruction, Parameter calculation

In rural areas of India, people face a problem of stable power backup for cell sites. Power failure is a common problem and occurred on frequently basis. Telecom tower companies are dealing with various problems for installation of telecom tower in rural areas like pollution created by diesel generator, reliability of energy source, intermittent power supply etc. Installation of telecom tower is depending upon various criteria like capital expenditure, reliability, pollution etc. In the presented study, an onsite study had been done and all the data related to it had been collected and put into an analysis chart. This study had been done for a rural area in India (Uttar Pradesh). In this study the criteria responsible for installation of telecom tower is found out and the importance of each criterion is evaluated with the help of MCDM based approach known as Analytic Hierarchy Process (AHP).

Process monitoring strategies are an amalgamation of procedures and techniques for monitoring of the manufacturing process for the eventual goal of production of good quality end product. The study delves into the development of a monitoring strategy based on statistical techniques and taking into account the nonlinearity of the data. The case study involving a Steel making Shop has been chosen to showcase the methodology thus developed. The statistical monitoring strategy devised is based on multivariate Hotelling T2 chart and the nonlinearity of the data is addressed via the employment of Neural Network Fitting model. The data consisting of the quality characteristics observations of the steel billets is fed to Neural Network Model for removal of nonlinear pattern. Thereafter the complete or partial linear transformed observations are being tested for the presence of fault(s) by employment of Hotelling T2 Control Chart and upon the detection of fault represented by out-of-control observation appropriate actions ought to be initiated.

Providers at an urban pediatric clinic lacked a standardized protocol for counseling parents and children when addressing the problem of obesity. Providers were trained to implement the 5-4-3-2-1 Go! evidence-based intervention. The electronic medical record was revised for documentation of counseling. Adherence to the protocol was monitored through observation and chart reviews. Providers found the protocol to standardize care and enhance the patient’s ability to set goals and develop plans for change. The rate with which providers recommended follow-up visits for this purpose increased significantly. 5-4-3-2-1 Go! was successfully used to standardize obesity-related follow-up visits.

How does brain system organization evolve during development? Cui et al. (2020) combine big and higher-precision fMRI data to find that maturational processes and cognitive ability track individual differences in the refinement of borders between brain systems.

This study proposes a new control chart for monitoring double bounded processes in the intervals (0,1], [0,1) or [0,1], such as fractions and proportions, which commonly contain zeros and/or ones in practical applications. The proposed chart, called inflated beta control chart, presents the control limits based on the inflated beta probability distribution. This distribution allows the modeling of double bounded processes that assume values in the unit interval containing zeros and/or ones. For control limits determination, we consider two approaches based on the suppositions of known and unknown parameters. When the parameters are unknown, usually in empirical applications, the control limits are determined by maximum likelihood estimators. In this case, the performance of the proposed control chart and of the well-known beta control chart is evaluated by Monte Carlo simulations. The inflated beta control chart outperforms the beta control chart in terms of run length analysis. In addition, three illustrative examples are presented to demonstrate the applicability of the proposed control chart.

The objective of this article is to statistically analyze and apply process control on water consumption in toilet flush devices in a public university building using Shewhart, EWMA and combined Shewhart-EWMA control charts. Data such as water volume, number of activations and flush-time duration were collected utilizing Smart-Meter sensors. A script was developed in R language to perform the appropriate statistical analysis, such as finding control charts control limits and transforming the obtained raw data into key variables: total volume per day, average flush volume, flush duration, and number of flushes per day. During the data gathering period, the regular single-flush equipment was replaced by a dual-flush model. The control charts Phase 1 is based on the collected data before the installation of the dual-flush devices, while Phase 2 is based on after replacement. After installing the new dual-flush devices, all control charts displayed visible changes based on the key variables. The replacement of the flush valves brought about a considerable reduction in water consumption in both male and female restrooms. There was a 21.72% reduction in average water consumption and a 12.09% average reduction in flushing time duration. The equipment replacement resulted in an evaluated Internal Rate of Return of 0.73%. Periodic monitoring of Shewhart Control Charts proved useful for observing large shifts of data, while EWMA control charts were more useful in locating small but constant data shifts. All chart models proved useful in identifying water consumption reduction and events such as leakages and water supply cutoffs occurring during the data gathering period.

This paper proposes a new leak/contaminant detection approach that aims to enhance the monitoring of water distribution network (WDN). The developed method relies on using machine learning (e.g Gaussian process regression (GPR)) as a modeling framework and generalized likelihood ratio (GLRT) for detection purposes. To improve the performances of the developed GPR model even further, multiscale representation of data will be used to develop multiscale extension of these method. Multiscale representation is a powerful data analysis technique that presents efficient separation of deterministic characteristics from random noise. Therefore, the multiscale GPR method, that combines the advantages of the GPR method with those of multiscale representation, will be developed to enhance the WDN modeling performance. We develop a new technique for detecting leak/contaminant in WDN using GLRT. For further enhance, the performance of GLRT, an exponentially weighted moving average (EWMA)-GLRT (EWMA-GLRT) chart is developed. The simulation results show that the MSGPR-based EWMA-GLRT method outperforms MSGPR-based GLRT and that both of them provide clear advantages over the neural networks (NN)- and support vector regression (SVR)- and GPR-based GLRT techniques.

Background Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural language processing (NLP) tools are distinctive in their ability to extract critical information from unstructured text in the electronic health records. As a simple proof-of-concept for the potential application of NLP technology in total hip arthroplasty (THA), we examined its ability to identify periprosthetic femur fractures (PPFFx) followed by more complex Vancouver classification. Methods PPFFx were identified among all THAs performed at a single academic institution between 1998 and 2016. A randomly selected training cohort (1538 THAs with 89 PPFFx cases) was used to develop the prototype NLP algorithm and an additional randomly selected cohort (2982 THAs with 84 PPFFx cases) was used to further validate the algorithm. Keywords to identify, and subsequently classify, Vancouver type PPFFx about THA were defined. The gold standard was confirmed by experienced orthopedic surgeons using chart and radiographic review. The algorithm was applied to consult and operative notes to evaluate language used by surgeons as a means to predict the correct pathology in the absence of a listed, precise diagnosis. Given the variability inherent to fracture descriptions by different surgeons, an iterative process was used to improve the algorithm during the training phase following error identification. Validation statistics were calculated using manual chart review as the gold standard. Results In distinguishing PPFFx, the NLP algorithm demonstrated 100% sensitivity and 99.8% specificity. Among 84 PPFFx test cases, the algorithm demonstrated 78.6% sensitivity and 94.8% specificity in determining the correct Vancouver classification. Conclusion NLP-enabled algorithms are a promising alternative to manual chart review for identifying THA outcomes. NLP algorithms applied to surgeon notes demonstrated excellent accuracy in delineating PPFFx, but accuracy was low for Vancouver classification subtype. This proof-of-concept study supports the use of NLP technology to extract THA-specific data elements from the unstructured text in electronic health records in an expeditious and cost-effective manner. Level of Evidence Level III.

Random causes of variation are part of every process and are harmless to product quality characteristics, while special cause variations appear due to a fault in the process and need special attention. The adaptive exponential weighted moving average (EWMA) control chart based on the cumulative sum (CUSUM) accumulation error is proposed in this study. The aim of this study is detecting imbalanced mixed range (different sizes) shifts (special cause) in process dispersion. The Huber and Tukey bi-square functions are used to enhance the proposed chart efficiency to simultaneously detect these small to large shifts. To check the sensitivity of the proposed chart, numerical results are provided through Monto Carlo simulations. The average run length (ARL) for single shift performance and extra quadratic loss (EQL), relative average run length (RARL) and performance comparison index (PCI) measures are used for overall performance evaluation of the proposed chart. The proposed scheme is compared to existing charts in the literature to determine superiority. For practical purposes, the guidelines are provided using real-life data for their practical implementation.

In this paper, we consider a machine learning approach merged with statistical testing hypothesis for enhanced fault detection performance in photovoltaic (PV) systems. The developed method makes use of a machine learning based Gaussian process regression (GPR) technique as a modeling framework, while a generalized likelihood ratio test (GLRT) chart is applied to detect PV system faults. The developed GPR-based GLRT approach is assessed using simulated and real PV data through monitoring the key PV system variables (current, voltage, and power). The computation time, missed detection rate (MDR), and false alarm rate (FAR) are computed to evaluate the fault detection performance of the proposed approach. 190 405 413

Summary Objectives The purpose of this work was twofold. First, we aimed to develop an exact analytical model for tubes used in semi-occluded vocal tract exercises to gain a quantitative insight into the relationship between flow resistance and the tube's geometric parameters. The second goal was to provide an isometric resistance chart that can be used by clinicians to indicate either the diameter or the length of a tube, so as to provide the same flow resistance of a reference tube. Methods The theory for confined flows based on the Darcy-Weisbach equation was used to derive the analytical model, in which the friction factor was obtained by an explicit approximation with error smaller than 0.4%. The isometric resistance chart was generated with the analytical model, assuming the volume flow to be constant and equal to 0.4 L/s. Results The results obtained from the model agreed very well with both experimental and theoretical results from the literature, particularly for tubes longer than 6 cm and with inner diameters greater than 4.1 mm. In general, the analytical model slightly underestimates the back pressure for shorter and thinner tubes. For these cases, the maximum difference between analytical and experimental results corresponds to ≈5%. Conclusions Analysis of the equation terms indicated that the flow resistance is significantly more sensitive to variations in the inner diameter than to variations on the tube's length, which agrees with experimental results found in the literature. Moreover, the effect of the mouth configuration is negligible for tubes whose length are one order of magnitude greater the the inner diameter. Nevertheless, for short tubes the mouth configuration becomes a significant parameter and can be described by the ratio between the tube's inner diameter and the effective diameter of the patient's oral cavity. The analytical model presented in this work can be applied to the entire set of tube geometries found in clinical practice and constitutes a straightforward tool for designing tubes for semi-occluded vocal tract exercises with specific therapeutic purposes or patient needs.

For on-site renewable energy supply, such as photovoltaic (PV) electricity generation, an important issue is the daily and seasonal matching between on-site supply and demand. The matching potential is frequently expressed using the load matching indicators such as self-sufficiency and self-consumption. This paper presents the Energy matching chart, which is a novel graphical approach to visualize the PV-load matching. The chart uses self-sufficiency and self-consumption to provide information regarding the matching in both size and time. Using the Energy matching chart, the matching between PV production and load presented in previous studies is graphically analyzed and compared. Furthermore, the potentials for the two most common measures for improving the matching, namely energy storage and load shifting, are investigated. The results show that energy storage has, on average, a significantly higher potential for increasing the PV-load matching than load shifting. The second part of the paper, illustrates the benefits of the Energy matching chart by evaluating the Swedish implementation of the EU legislation on nearly Zero Energy Buildings (nZEBs). The assessment is performed for detached houses and evaluates the feasibility to use PV and battery systems for Swedish nZEBs. The results show that on-site PV production can help buildings to meet the nZEB regulations, but there are limitations due to the poor time-dependent matching. With a combined PV-battery system, the potential to meet the regulation is significantly larger. To summarize, the Energy matching chart has the potential to become a useful tool in the assessment of PV system and the evaluation of load matching measures.

Background Paper-based charts remain the principal means of documenting the vital signs of hospitalised pregnant and postnatal women. However, poor chart design may contribute to both incorrect charting of data and clinical responses. We decided to identify design faults that might have an adverse clinical impact. Methods One hundred and twenty obstetric early warning charts and escalation protocols from consultant-led maternity units in the United Kingdom and the Channel Islands were analysed using an objective and systematic approach. We identified design errors that might impede their successful use (e.g. generate confusion regarding vital sign documentation, hamper the recognition of maternal deterioration, cause a failure of the early warning system or of any clinical response). Results We found 30% (n=36/120) of charts contained at least one design error with the potential to confuse staff, render the charts difficult to use or compromise patient safety. Amongst the most common areas were inadequate patient identification, poor use of colour, illogical weighting, poor alignment and labelling of axes, and the opportunity for staff to ‘game’ the escalation. Conclusions We recommend the urgent development of an evidence-based, standardised obstetric observation chart, which integrates ‘human factors’ and user experience. It should have a clear layout and style, appropriate colour scheme, correct language and labelling, and the ability for vital signs to be documented accurately and quickly. It should incorporate a suitable early warning score to guide clinical management.

In this paper, an improved fault detection method is proposed based on kernel partial least squares (KPLS) model and generalized likelihood ratio test (GLRT) detection chart in order to enhance the monitoring abilities of nonlinear chemical processes. To deal with both high computational cost for large data set and time-varying dynamics of industrial processes, the proposed method is used to select a reduced set of kernel functions to build the KPLS model and applies it for online fault detection based on GLRT chart. Comparing with the conventional KPLS technique, the proposed method has the advantages of improving the computation efficiency by decreasing the dimension of kernel matrix. The developed online reduced KPLS-based GLRT (OR-GLRT) could improve the fault detection efficiency since it is able to track the time-varying characteristics of the processes. The fault detection performance of the developed OR-GLRT method is evaluated using a Tennessee Eastman process. The simulation results show that the proposed method outperforms the conventional GLRT technique.

In many industries, statistical process monitoring techniques play a key role in improving processes through variation reduction and defect prevention. Modern large-scale industrial processes require appropriate monitoring techniques that can efficiently address high-dimensional nonlinear processes. Such processes have been successfully monitored with several latent variable-based methods. However, because these monitoring methods use Hotelling’s T 2 statistics in the reduced space, a normality assumption underlies the construction of these tools. This assumption has limited the use of latent variable-based monitoring charts in both nonlinear and nonnormal situations. In this study, we propose a variational autoencoder (VAE) as a monitoring method that can address both nonlinear and nonnormal situations in high-dimensional processes. VAE is appropriate for T 2 charts because it causes the reduced space to follow a multivariate normal distribution. The effectiveness and applicability of the proposed VAE-based chart were demonstrated through experiments on simulated data and real data from a thin-film-transistor liquid-crystal display process.

Fault detection (FD) is essential for monitoring various chemical processes. Many chemical processes can be described by input-output models. Partial least squares (PLS) method is one of the most popular statistical approaches used for modeling and monitoring chemical processes. In many situations, measured process data can exhibit some level of uncertainty. In such cases, expressing the data in interval form can be useful. Therefore, this work addresses the problem of fault detection of uncertain chemical processes using interval input-output PLS-based generalized likelihood ratio test (GLRT). The proposed novel approach helps extend the applicability of GLRT to uncertain processes represented by interval-valued input-output data. In the developed approach, the modeling phase is performed using PLS and then the GLRT chart is applied to the interval residuals for fault detection. To evaluate the fault detection abilities of the proposed PLS-based interval valued GLRT approach, two examples are used: a simulated example and a distillation column example. The performance of the proposed technique is evaluated in terms of the missed detection and false alarms rates.

In the rapidly expanding market of wind energy, sites in cold climates are becoming popular because of their high wind potential. However, several challenges are associated with energy production in those sites. Such challenges not only include low temperature and high winds, but also multiple icing events. To cope with the negative impacts of icing, wind turbine manufacturers nowadays include ice protection systems (IPS) to their products. It has been observed that the performances of those systems can be greatly influenced by the ambient conditions. In many occasions, under harsh conditions, turbines IPS may not able to prevent ice formation on the blades nor to remove ice that is already formed. Multiple numerical analysis were made on the IPS performance but none of them relies on actual field data. In this paper, the relationship between the turbine stoppage time, wind speed and ambient temperature was studied on a wind farm of over 80 turbines in eastern Canada. The test site is subject to harsh weather and long recovery time and can therefore provide interesting data on icing events. A simplified 1-D heat transfer model of the blades during recovery time has been developed and then compared to the field data. The model was used to generate IPS performance envelopes to delimit, on a temperature vs. wind speed chart, the conditions where the IPS are expected to operate successfully. This analysis showed the importance of having an IPS adapted to the conditions encountered in a given site. To help wind turbine manufacturers design their IPS, a set of distributions of the most relevant meteorological parameters is presented. This set of data has been retrieved using a custom made meteorological conditions monitoring station (MCMS) installed on one of the wind turbines' nacelle. Wind turbine designers, developers and operators can greatly benefit from the data presented in this paper.