scholarly journals On Phase-I Monitoring of Process Location Parameter with Auxiliary Information-Based Median Control Charts

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 706 ◽  
Author(s):  
Shahid Hussain ◽  
Sun Mei ◽  
Muhammad Riaz ◽  
Saddam Akber Abbasi
Keyword(s):  
Phase I ◽  
Control Chart ◽  
Phase Ii ◽  
Control Charts ◽  
Auxiliary Information ◽  
Location Parameter ◽  
Attractive Alternative ◽  
Location Parameters ◽  
The Mean ◽  
Two Phases

A control chart is often used to monitor the industrial or services processes to improve the quality of the products. Mostly, the monitoring of location parameters, both in Phase I and Phase II, is done using a mean control chart with the assumption that the process is free from outliers or the estimators are correctly estimated from in-control samples. Generally, there are question marks about such kind of narratives. The performance of the mean chart is highly affected in the presence of outliers. Therefore, the median chart is an attractive alternative to the mean chart in this situation. The control charts are usually implemented in two phases: Phase I (retrospective) and Phase II (prospective/monitoring). The efficiency of any control chart in Phase II depends on the accuracy of control limits obtained from Phase I. The current study focuses on the Phase I analysis of location parameters using median control charts. We examined the performance of different auxiliary information-based median control charts and compared the results with the usual median chart. Standardized variance and relative efficacy are used as performance measures to evaluate the efficiency of median estimators. Moreover, the probability to signal measure is used to evaluate the performance of proposed control charts to detect any potential changes in the process. The results revealed that the proposed auxiliary information based median control charts perform better in Phase I analysis. In addition, a practical illustration of an industrial scenario demonstrated the significance of the proposed control charts, in which the monitoring of concrete compressive strength is emphasized.

Robust approaches for monitoring logistic regression profiles under outliers

2017 ◽  
Vol 34 (4) ◽  
pp. 494-507 ◽  
Author(s):  
Ahmad Hakimi ◽  
Amirhossein Amiri ◽  
Reza Kamranrad
Keyword(s):  
Logistic Regression ◽  
Robust Control ◽  
Phase I ◽  
Control Chart ◽  
Phase Ii ◽  
Control Charts ◽  
Likelihood Estimation ◽  
Estimation Of Parameters ◽  
Content Type ◽  
Practical Applications

Purpose The purpose of this paper is to develop some robust approaches to estimate the logistic regression profile parameters in order to decrease the effects of outliers on the performance of T2 control chart. In addition, the performance of the non-robust and the proposed robust control charts is evaluated in Phase II. Design/methodology/approach In this paper some, robust approaches including weighted maximum likelihood estimation, redescending M-estimator and a combination of these two approaches (WRM) are used to decrease the effects of outliers on estimating the logistic regression parameters as well as the performance of the T2 control chart. Findings The results of the simulation studies in both Phases I and II show the better performance of the proposed robust control charts rather than the non-robust control chart for estimating the logistic regression profile parameters and monitoring the logistic regression profiles. Practical implications In many practical applications, there are outliers in processes which may affect the estimation of parameters in Phase I and as a result of deteriorate the statistical performance of control charts in Phase II. The methods developed in this paper are effective for decreasing the effect of outliers in both Phases I and II. Originality/value This paper considers monitoring the logistic regression profile in Phase I under the presence of outliers. Also, three robust approaches are developed to decrease the effects of outliers on the parameter estimation and monitoring the logistic regression profiles in both Phases I and II.

Guidelines for automating Phase I of control charts by considering effects on Phase-II performance of individuals control chart

2019 ◽  
Vol 32 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Murat Atalay ◽  
Murat Caner Testik ◽  
Serhan Duran ◽  
Christian H. Weiß
Keyword(s):  
Phase I ◽  
Control Chart ◽  
Phase Ii ◽  
Control Charts

Improving Phase I Monitoring of Dirichlet Regression Profiles

2018 ◽  
Vol 25 (06) ◽  
pp. 1850030 ◽  
Author(s):  
Hourieh Foroutan ◽  
Amirhossein Amiri ◽  
Reza Kamranrad
Keyword(s):  
Phase I ◽  
Control Chart ◽  
Control Charts ◽  
Compositional Data ◽  
Ratio Test ◽  
Statistical Process ◽  
Explanatory Variables ◽  
Monitoring Procedure ◽  
Multivariate Control

In most statistical process control (SPC) applications, quality of a process or product is monitored by univariate or multivariate control charts. However, sometimes a functional relationship between a response variable and one or more explanatory variables is established and monitored over time. This relationship is called “profile” in SPC literature. In this paper, we specifically consider processes with compositional data responses, including multivariate positive observations summing to one. The relationship between compositional data responses and explanatory variables is modeled by a Dirichlet regression profile. We develop a monitoring procedure based on likelihood ratio test (lrt) for Phase I monitoring of Dirichlet regression profiles. Then, we compare the performance of the proposed method with the best method in the literature in terms of probability of signal. The results of simulation studies show that the proposed control chart has better performance in Phase I monitoring than the competing control chart. Moreover, the proposed method is able to estimate the real time of a change as well. The performance of this feature is also investigated through simulation runs which show the satisfactory performance. Finally, the application of the proposed method is illustrated based on a real case in comparison with the existing method.

scholarly journals COVID-19 and radiation oncology: the experience of a two-phase plan within a single institution in central Italy

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Luciana Caravatta ◽  
Consuelo Rosa ◽  
Maria Bernadette Di Sciascio ◽  
Andrea Tavella Scaringi ◽  
Angelo Di Pilla ◽  
...  
Keyword(s):  
Phase I ◽  
Phase Ii ◽  
Central Italy ◽  
Significant Risk ◽  
Tumor Board ◽  
Radiotherapy Planning ◽  
Two Phase ◽  
Hospital Environments ◽  
Two Phases

Abstract Background COVID-19 in Italy has led to the need to reorganize hospital protocols with a significant risk of interruption to cancer treatment programs. In this report, we will focus on a management model covering the two phases of the COVID-19 emergency, namely lockdown-phase I and post-lockdown-phase II. Methods The following steps were taken in the two phases: workload during visits and radiotherapy planning, use of dedicated routes, measures for triage areas, management of suspected and positive COVID-19 cases, personal protective equipment, hospital environments and intra-institutional meetings and tumor board management. Due to the guidelines set out by the Ministry of Health, oncological follow-up visits were interrupted during the lockdown-phase I; consequently, we set about contacting patients by telephone, with laboratory and instrumental exams being viewed via telematics. During the post-lockdown-phase II, the oncological follow-up clinic reopened, with two shifts operating daily. Results By comparing our radiotherapy activity from March 9 to May 4 2019 with the same period in 2020 during full phase I of the COVID-19 emergency, similar results were achieved. First radiotherapy visits, Simulation Computed Tomography and Linear Accelerator treatments amounted to 123, 137 and 151 in 2019 compared with 121, 135 and 170 in 2020 respectively. There were no cases of COVID-19 positivity recorded either in patients or in healthcare professionals, who were all negative to the swab tests performed. Conclusion During both phases of the COVID-19 emergency, the planned model used in our own experience guaranteed both continuity in radiotherapy treatments whilst neither reducing workload nor interrupting treatment and, as such, it ensured the safety of cancer patients, hospital environments and staff.

scholarly journals A pareto ensemble based spectral clustering framework

2020 ◽  
Author(s):  
Juanjuan Luo ◽  
Huadong Ma ◽  
Dongqing Zhou
Keyword(s):  
Phase I ◽  
Phase Ii ◽  
Spectral Clustering ◽  
Clustering Algorithms ◽  
Divide And Conquer ◽  
Nonzero Entry ◽  
Similarity Matrix ◽  
Diversity Preservation ◽  
Two Phases ◽  
Matrix Construction

Abstract Similarity matrix has a significant effect on the performance of the spectral clustering, and how to determine the neighborhood in the similarity matrix effectively is one of its main difficulties. In this paper, a “divide and conquer” strategy is proposed to model the similarity matrix construction task by adopting Multiobjective evolutionary algorithm (MOEA). The whole procedure is divided into two phases, phase I aims to determine the nonzero entries of the similarity matrix, and Phase II aims to determine the value of the nonzero entries of the similarity matrix. In phase I, the main contribution is that we model the task as a biobjective dynamic optimization problem, which optimizes the diversity and the similarity at the same time. It makes each individual determine one nonzero entry for each sample, and the encoding length decreases to O(N) in contrast with the non-ensemble multiobjective spectral clustering. In addition, a specific initialization operator and diversity preservation strategy are proposed during this phase. In phase II, three ensemble strategies are designed to determine the value of the nonzero value of the similarity matrix. Furthermore, this Pareto ensemble framework is extended to semi-supervised clustering by transforming the semi-supervised information to constraints. In contrast with the previous multiobjective evolutionary-based spectral clustering algorithms, the proposed Pareto ensemble-based framework makes a balance between time cost and the clustering accuracy, which is demonstrated in the experiments section.

scholarly journals How do palliative care doctors recognise imminently dying patients? A judgement analysis

BMJ Open ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. e024996 ◽  
Author(s):  
Nicola White ◽  
Priscilla Harries ◽  
Adam JL Harris ◽  
Victoria Vickerstaff ◽  
Philip Lodge ◽  
...  
Keyword(s):  
Palliative Care ◽  
Observational Study ◽  
Phase I ◽  
Phase Ii ◽  
Prospective Observational Study ◽  
Clinical Signs ◽  
Brier Score ◽  
Prognostic Test ◽  
Probability Of Death ◽  
The Mean

ObjectivesTo identify a group of palliative care doctors who perform well on a prognostic test and to understand how they make their survival predictions.DesignProspective observational study and two cross-sectional online studies.SettingPhase I: an online prognostic test, developed from a prospective observational study of patients referred to palliative care. Phase II: an online judgement task consisting of 50 hypothetical vignettes.ParticipantsAll members of the Association of Palliative Medicine (APM) were eligible (n=~1100). 99 doctors completed the prognostic test and were included in the phase I analysis. The top 20% were invited to participate in phase II; 14/19 doctors completed the judgement task and were included in the phase II analysis.MeasuresPhase I: participants were asked to give a probability of death within 72 hours (0%–100%) for all 20 cases. Accuracy on the prognostic test was measured with the Brier score which was used to identify the ‘expert’ group (scale range: 0 (expert)–1 (non-expert)). Phase II: participants gave a probability of death within 72 hours (0%–100%). A mixed model regression analysis was completed using the percentage estimate as the outcome and the patient information included in the vignettes as the predictors.ResultsThe mean Brier score of all participants was 0.237 (95% CI 0.235 to 0.239). The mean Brier score of the ‘experts’ was 0.184 (95% CI 0.176 to 0.192). Six of the seven prognostic variables included in the hypothetical vignettes were significantly associated with clinician predictions of death. The Palliative Performance Score was identified as being the most influential in the doctors’ prognostic decision making (β=0.48, p<0.001).ConclusionsThis study identified six clinical signs and symptoms which influenced the judgement policies of palliative care doctors. These results may be used to teach novice doctors how to improve their prognostic skills.

scholarly journals Involvement of NO in Antinociception of NSAIDS in Murine Formalin Hind Paw Assay

Drug Research ◽  
2020 ◽  
Vol 70 (04) ◽  
pp. 145-150 ◽  
Author(s):  
Viviana Noriega ◽  
Hugo F. Miranda ◽  
Juan Carlos Prieto ◽  
Ramón Sotomayor-Zárate ◽  
Fernando Sierralta
Keyword(s):  
Phase I ◽  
Phase Ii ◽  
Dose Response ◽  
Rank Order ◽  
Linear Regression Analysis ◽  
Second Phase ◽  
Response Curves ◽  
Before And After ◽  
Two Phases ◽  
Phase Phase

AbstractThere are different animal models to evaluate pain among them the formalin hind paw assay which is widely used since some of its events appear to be similar to the clinical pain of humans. The assay in which a dilute solution of formalin is injected into the dorsal hindpaw of a murine produces two ‘phases’ of pain behavior separated by a inactive period. The early phase (Phase I) is probably due to direct activation of nociceptors and the second phase (Phase II) is due to ongoing inflammatory input and central sensitization. Mice were used to determine the potency antinociceptive of piroxicam (1,3,10,and 30 mg/kg), parecoxib (0.3, 1,3,10 and 30 mg/kg), dexketoprofen (3,10,30 and 100 mg/kg) and ketoprofen (3,10,30 and 100 mg/kg). Dose-response for each NSAIDs were created before and after 5 mg/kg of L-NAME i.p. or 5 mg/kg i.p. of 7-nitroindazole. A least-squares linear regression analysis of the log dose–response curves allowed the calculation of the dose that produced 50% of antinociception (ED50) for each drug. The ED50 demonstrated the following rank order of potency, in the phase I: piroxicam > dexketoprofen > ketoprofen > parecoxib and in the phase II: piroxicam > ketoprofen > parecoxib > dexketoprofen. Pretreatment of the mice with L-NAME or 7-nitroindazol induced a significant increase of the analgesic power of the NSAIDs, with a significant reduction of the ED50. It is suggested that NO may be involved in both phases of the trial, which means that nitric oxide regulates the bioactivity of NSAIDs.

Identifying Criteria for Continuous Evaluation of Software Engineers for Reward and Recognition

2016 ◽  
Vol 7 (4) ◽  
pp. 61-78 ◽  
Author(s):  
Sreejith S. S. ◽  
Muthu Mathirajan
Keyword(s):  
Phase I ◽  
Phase Ii ◽  
Employee Performance ◽  
Exploratory Research ◽  
Structured Interviews ◽  
Continuous Evaluation ◽  
Software Engineers ◽  
Two Phases ◽  
R Process ◽  
Reward And Recognition

Reward and Recognition (R&R) should be given to employees in a timely manner, based on continuous evaluation of their performance. Success of an R&R process lies in clear and well defined criteria for continuous evaluation of employee performance. Often such criteria are decided by the organization with no input from the employees. The purpose of this paper is to use qualitative research methods to explore and identify the criteria to be used for continuous employee performance evaluation for R&R in Information Technology organizations, from the perspectives of software engineers (SEs) and project managers (PMs). Exploratory research was conducted in two phases. In Phase I, unstructured interviews are used to elicit information from 7 SEs. Caselets are prepared based on these interviews and 19 criteria are identified. In Phase II, the criteria identified in Phase I are confirmed using content analysis of semi-structured interviews, conducted on relatively larger group of SEs (in stage 1) and PMs (in stage 2). Additionally, 12 criteria are also identified in Phase II. Collectively 31 criteria are identified. The proposed criteria set is expected to comprehensively cover the SE performance on a continuous basis in various dimensions to award R&R.

Assessing Hospital Disaster Readiness Over Time at the US Department of Veterans Affairs

2016 ◽  
Vol 32 (1) ◽  
pp. 46-57 ◽  
Author(s):  
Claudia Der-Martirosian ◽  
Tiffany A. Radcliff ◽  
Alicia R. Gable ◽  
Deborah Riopelle ◽  
Farhad A. Hagigi ◽  
...  
Keyword(s):  
Phase I ◽  
Emergency Management ◽  
Phase Ii ◽  
Veterans Affairs ◽  
Assessment Tools ◽  
Department Of Veterans Affairs ◽  
The Us ◽  
Two Phases ◽  
Hospital Readiness ◽  
Over Time

AbstractIntroductionThere have been numerous initiatives by government and private organizations to help hospitals become better prepared for major disasters and public health emergencies. This study reports on efforts by the US Department of Veterans Affairs (VA), Veterans Health Administration, Office of Emergency Management’s (OEM) Comprehensive Emergency Management Program (CEMP) to assess the readiness of VA Medical Centers (VAMCs) across the nation.Hypothesis/ProblemThis study conducts descriptive analyses of preparedness assessments of VAMCs and examines change in hospital readiness over time.MethodsTo assess change, quantitative analyses of data from two phases of preparedness assessments (Phase I: 2008-2010; Phase II: 2011-2013) at 137 VAMCs were conducted using 61 unique capabilities assessed during the two phases. The initial five-point Likert-like scale used to rate each capability was collapsed into a dichotomous variable: “not-developed=0” versus “developed=1.” To describe changes in preparedness over time, four new categories were created from the Phase I and Phase II dichotomous variables: (1) rated developed in both phases; (2) rated not-developed in Phase I but rated developed in Phase II; (3) rated not-developed in both phases; and (4) rated developed in Phase I but rated not- developed in Phase II.ResultsFrom a total of 61 unique emergency preparedness capabilities, 33 items achieved the desired outcome – they were rated either “developed in both phases” or “became developed” in Phase II for at least 80% of VAMCs. For 14 items, 70%-80% of VAMCs achieved the desired outcome. The remaining 14 items were identified as “low-performing” capabilities, defined as less than 70% of VAMCs achieved the desired outcome.Conclusion:Measuring emergency management capabilities is a necessary first step to improving those capabilities. Furthermore, assessing hospital readiness over time and creating robust hospital readiness assessment tools can help hospitals make informed decisions regarding allocation of resources to ensure patient safety, provide timely access to high-quality patient care, and identify best practices in emergency management during and after disasters. Moreover, with some minor modifications, this comprehensive, all-hazards-based, hospital preparedness assessment tool could be adapted for use beyond the VA.Der-MartirosianC, RadcliffTA, GableAR, RiopelleD, HagigiFA, BrewsterP, DobalianA. Assessing hospital disaster readiness over time at the US Department of Veterans Affairs. Prehsop Disaster Med. 2017;32(1):46–57.

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