The learning curve: implications of a quantitative analysis.

Science.gov (United States)

Gallistel, Charles R; Fairhurst, Stephen; Balsam, Peter

2004-09-07

The negatively accelerated, gradually increasing learning curve is an artifact of group averaging in several commonly used basic learning paradigms (pigeon autoshaping, delay- and trace-eye-blink conditioning in the rabbit and rat, autoshaped hopper entry in the rat, plus maze performance in the rat, and water maze performance in the mouse). The learning curves for individual subjects show an abrupt, often step-like increase from the untrained level of responding to the level seen in the well trained subject. The rise is at least as abrupt as that commonly seen in psychometric functions in stimulus detection experiments. It may indicate that the appearance of conditioned behavior is mediated by an evidence-based decision process, as in stimulus detection experiments. If the appearance of conditioned behavior is taken instead to reflect the increase in an underlying associative strength, then a negligible portion of the function relating associative strength to amount of experience is behaviorally visible. Consequently, rate of learning cannot be estimated from the group-average curve; the best measure is latency to the onset of responding, determined for each subject individually.

The Predictive Value of Ultrasound Learning Curves Across Simulated and Clinical Settings

DEFF Research Database (Denmark)

Madsen, Mette E; Nørgaard, Lone N; Tabor, Ann

2017-01-01

OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation-based tra......OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation......-based training program in transvaginal sonography. The training was conducted on a VR simulator as well as on a physical mannequin. A subgroup of 6 participants underwent subsequent clinical training. During each of the 3 steps, the participants' performance was assessed using instruments with established...... settings. RESULTS: A good correlation was found between time needed to achieve predefined performance levels on the VR simulator and the physical mannequin (Pearson correlation coefficient .78; P VR simulator correlated well to the clinical performance scores (Pearson...

Learning curve for intracranial angioplasty and stenting in single center.

Science.gov (United States)

Cai, Qiankun; Li, Yongkun; Xu, Gelin; Sun, Wen; Xiong, Yunyun; Sun, Wenshan; Bao, Yuanfei; Huang, Xianjun; Zhang, Yao; Zhou, Lulu; Zhu, Wusheng; Liu, Xinfeng

2014-01-01

To identify the specific caseload to overcome learning curve effect based on data from consecutive patients treated with Intracranial Angioplasty and Stenting (IAS) in our center. The Stenting and Aggressive Medical Management for Preventing Recurrent Stroke and Intracranial Stenosis trial was prematurely terminated owing to the high rate of periprocedural complications in the endovascular arm. To date, there are no data available for determining the essential caseload sufficient to overcome the learning effect and perform IAS with an acceptable level of complications. Between March 2004 and May 2012, 188 consecutive patients with 194 lesions who underwent IAS were analyzed retrospectively. The outcome variables used to assess the learning curve were periprocedural complications (included transient ischemic attack, ischemic stroke, vessel rupture, cerebral hyperperfusion syndrome, and vessel perforation). Multivariable logistic regression analysis was employed to illustrate the existence of learning curve effect on IAS. A risk-adjusted cumulative sum chart was performed to identify the specific caseload to overcome learning curve effect. The overall rate of 30-days periprocedural complications was 12.4% (24/194). After adjusting for case-mix, multivariate logistic regression analysis showed that operator experience was an independent predictor for periprocedural complications. The learning curve of IAS to overcome complications in a risk-adjusted manner was 21 cases. Operator's level of experience significantly affected the outcome of IAS. Moreover, we observed that the amount of experience sufficient for performing IAS in our center was 21 cases. Copyright © 2013 Wiley Periodicals, Inc.

Learning curve for radical retropubic prostatectomy

Directory of Open Access Journals (Sweden)

Fernando J. A. Saito

2011-02-01

Full Text Available PURPOSE: The learning curve is a period in which the surgical procedure is performed with difficulty and slowness, leading to a higher risk of complications and reduced effectiveness due the surgeon's inexperience. We sought to analyze the residents' learning curve for open radical prostatectomy (RP in a training program. MATERIALS AND METHODS: We conducted a prospective study from June 2006 to January 2008 in the academic environment of the University of São Paulo. Five residents operated on 184 patients during a four-month rotation in the urologic oncology division, mentored by the same physician assistants. We performed sequential analyses according to the number of surgeries, as follows: = 10, 11 to 19, 20 to 28, and = 29. RESULTS: The residents performed an average of 37 RP each. The average psa was 9.3 ng/mL and clinical stage T1c in 71% of the patients. The pathological stage was pT2 (73%, pT3 (23%, pT4 (4%, and 46% of the patients had a Gleason score 7 or higher. In all surgeries, the average operative time and estimated blood loss was 140 minutes and 488 mL. Overall, 7.2% of patients required blood transfusion, and 23% had positive surgical margins. CONCLUSION: During the initial RP learning curve, we found a significant reduction in the operative time; blood transfusion during the procedures and positive surgical margin rate were stable in our series.

Endoscopic sleeve gastroplasty: the learning curve.

Science.gov (United States)

Hill, Christine; El Zein, Mohamad; Agnihotri, Abhishek; Dunlap, Margo; Chang, Angela; Agrawal, Alison; Barola, Sindhu; Ngamruengphong, Saowanee; Chen, Yen-I; Kalloo, Anthony N; Khashab, Mouen A; Kumbhari, Vivek

2017-09-01

 Endoscopic sleeve gastroplasty (ESG) is gaining traction as a minimally invasive bariatric treatment. Concern that the learning curve may be slow, even among those proficient in endoscopic suturing, is a barrier to widespread implementation of the procedure. Therefore, we aimed to define the learning curve for ESG in a single endoscopist experienced in endoscopic suturing who participated in a 1-day ESG training program.  Consecutive patients who underwent ESG between February 2016 and November 2016 were included. The performing endoscopist, who is proficient in endoscopic suturing for non-ESG procedures, participated in a 1-day ESG training session before offering ESG to patients. The outcome measurements were length of procedure (LOP) and number of plications per procedure. Nonlinear regression was used to determine the learning plateau and calculate the learning rate.  Twenty-one consecutive patients (8 males), with mean age 47.7 ± 11.2 years and mean body mass index 41.8 ± 8.5 kg/m 2 underwent ESG. LOP decreased significantly across consecutive procedures, with a learning plateau at 101.5 minutes and a learning rate of 7 cases ( P  = 0.04). The number of plications per procedure also decreased significantly across consecutive procedures, with a plateau at 8 sutures and a learning rate of 9 cases ( P  < 0.001). Further, the average time per plication decreased significantly with consecutive procedures, reaching a plateau at 9 procedures ( P  < 0.001).  Endoscopists experienced in endoscopic suturing are expected to achieve a reduction in LOP and number of plications per procedure in successive cases, with progress plateauing at 7 and 9 cases, respectively.

Learning curves for mutual information maximization

International Nuclear Information System (INIS)

Urbanczik, R.

2003-01-01

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed [S. Becker and G. Hinton, Nature (London) 355, 161 (1992)]. For a generic data model, I show that in the large sample limit the structure in the data is recognized by mutual information maximization. For a more restricted model, where the networks are similar to perceptrons, I calculate the learning curves for zero-temperature Gibbs learning. These show that convergence can be rather slow, and a way of regularizing the procedure is considered

Robotic Mitral Valve Repair: The Learning Curve.

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Goodman, Avi; Koprivanac, Marijan; Kelava, Marta; Mick, Stephanie L; Gillinov, A Marc; Rajeswaran, Jeevanantham; Brzezinski, Anna; Blackstone, Eugene H; Mihaljevic, Tomislav

Adoption of robotic mitral valve surgery has been slow, likely in part because of its perceived technical complexity and a poorly understood learning curve. We sought to correlate changes in technical performance and outcome with surgeon experience in the "learning curve" part of our series. From 2006 to 2011, two surgeons undertook robotically assisted mitral valve repair in 458 patients (intent-to-treat); 404 procedures were completed entirely robotically (as-treated). Learning curves were constructed by modeling surgical sequence number semiparametrically with flexible penalized spline smoothing best-fit curves. Operative efficiency, reflecting technical performance, improved for (1) operating room time for case 1 to cases 200 (early experience) and 400 (later experience), from 414 to 364 to 321 minutes (12% and 22% decrease, respectively), (2) cardiopulmonary bypass time, from 148 to 102 to 91 minutes (31% and 39% decrease), and (3) myocardial ischemic time, from 119 to 75 to 68 minutes (37% and 43% decrease). Composite postoperative complications, reflecting safety, decreased from 17% to 6% to 2% (63% and 85% decrease). Intensive care unit stay decreased from 32 to 28 to 24 hours (13% and 25% decrease). Postoperative stay fell from 5.2 to 4.5 to 3.8 days (13% and 27% decrease). There were no in-hospital deaths. Predischarge mitral regurgitation of less than 2+, reflecting effectiveness, was achieved in 395 (97.8%), without correlation to experience; return-to-work times did not change substantially with experience. Technical efficiency of robotic mitral valve repair improves with experience and permits its safe and effective conduct.

From Curve Fitting to Machine Learning

CERN Document Server

Zielesny, Achim

2011-01-01

The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers that allowed the execution of highly non-linear and increasingly complex data analysis procedures - methods that were completely unfeasible before. Non-linear curve fitting, clustering and machine learning belong to these modern techniques which are a further step towards computational intelligence. The goal of this book is to provide an interactive and illustrative guide to these topics. It concentrates on the road from two dimensional curve fitting to multidimensional clus

Statistical assessment of the learning curves of health technologies.

Science.gov (United States)

Ramsay, C R; Grant, A M; Wallace, S A; Garthwaite, P H; Monk, A F; Russell, I T

2001-01-01

(1) To describe systematically studies that directly assessed the learning curve effect of health technologies. (2) Systematically to identify 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. (3) To test these statistical techniques in data sets from studies of varying designs to assess health technologies in which learning curve effects are known to exist. METHODS - STUDY SELECTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): For a study to be included, it had to include a formal analysis of the learning curve of a health technology using a graphical, tabular or statistical technique. METHODS - STUDY SELECTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): For a study to be included, it had to include a formal assessment of a learning curve using a statistical technique that had not been identified in the previous search. METHODS - DATA SOURCES: Six clinical and 16 non-clinical biomedical databases were searched. A limited amount of handsearching and scanning of reference lists was also undertaken. METHODS - DATA EXTRACTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): A number of study characteristics were abstracted from the papers such as study design, study size, number of operators and the statistical method used. METHODS - DATA EXTRACTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): The new statistical techniques identified were categorised into four subgroups of increasing complexity: exploratory data analysis; simple series data analysis; complex data structure analysis, generic techniques. METHODS - TESTING OF STATISTICAL METHODS: Some of the statistical methods identified in the systematic searches for single (simple) operator series data and for multiple (complex) operator series data were illustrated and explored using three data sets. The first was a case series of 190 consecutive laparoscopic fundoplication procedures performed by a single surgeon; the second

Hysteroscopic sterilization using a virtual reality simulator: assessment of learning curve.

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Janse, Juliënne A; Goedegebuure, Ruben S A; Veersema, Sebastiaan; Broekmans, Frank J M; Schreuder, Henk W R

2013-01-01

To assess the learning curve using a virtual reality simulator for hysteroscopic sterilization with the Essure method. Prospective multicenter study (Canadian Task Force classification II-2). University and teaching hospital in the Netherlands. Thirty novices (medical students) and five experts (gynecologists who had performed >150 Essure sterilization procedures). All participants performed nine repetitions of bilateral Essure placement on the simulator. Novices returned after 2 weeks and performed a second series of five repetitions to assess retention of skills. Structured observations on performance using the Global Rating Scale and parameters derived from the simulator provided measurements for analysis. The learning curve is represented by improvement per procedure. Two-way repeated-measures analysis of variance was used to analyze learning curves. Effect size (ES) was calculated to express the practical significance of the results (ES ≥ 0.50 indicates a large learning effect). For all parameters, significant improvements were found in novice performance within nine repetitions. Large learning effects were established for six of eight parameters (p learning curve established in this study endorses future implementation of the simulator in curricula on hysteroscopic skill acquisition for clinicians who are interested in learning this sterilization technique. Copyright © 2013 AAGL. Published by Elsevier Inc. All rights reserved.

Learning curves for solid oxide fuel cells

International Nuclear Information System (INIS)

Rivera-Tinoco, Rodrigo; Schoots, Koen; Zwaan, Bob van der

2012-01-01

Highlights: ► We present learning curves for fuel cells based on empirical data. ► We disentangle different cost reduction mechanisms for SOFCs. ► We distinguish between learning-by-doing, R and D, economies-of-scale and automation. - Abstract: In this article we present learning curves for solid oxide fuel cells (SOFCs). With data from fuel cell manufacturers we derive a detailed breakdown of their production costs. We develop a bottom-up model that allows for determining overall SOFC manufacturing costs with their respective cost components, among which material, energy, labor and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the R and D stage of development and diffusion, we find local learning rates between 13% and 17% and we demonstrate that the corresponding cost reductions result essentially from learning-by-searching effects. When considering periods in time that focus on the pilot and early commercial production stages, we find regional learning rates of 27% and 1%, respectively, which we assume derive mainly from genuine learning phenomena. These figures turnout significantly higher, approximately 44% and 12% respectively, if also effects of economies-of-scale and automation are included. When combining all production stages we obtain lr = 35%, which represents a mix of cost reduction phenomena. This high learning rate value and the potential to scale up production suggest that continued efforts in the development of SOFC manufacturing processes, as well as deployment and use of SOFCs, may lead to substantial further cost reductions.

Prospects for PV: a learning curve analysis

International Nuclear Information System (INIS)

Zwaan, Bob van der; Rabi, A.

2003-01-01

This article gives an overview of the current state-of-the-art of photovoltaic electricity technology, and addresses its potential for cost reductions over the first few decades of the 21st century. Current PV production cost ranges are presented, both in terms of capacity installation and electricity generation, of single crystalline silicon, multi-crystalline silicon, amorphous silicon and other thin film technologies. Possible decreases of these costs are assessed, as expected according to the learning-curve methodology. We also estimate how much PV could gain if external costs (due to environmental and health damage) of energy were internalised, for example by an energy tax. Our conclusions are that, (1) mainly due its high costs, PV electricity is unlikely to play a major role in global energy supply and carbon emissions abatement before 2020, (2) extrapolating learning curves observed in the past, one can expect its costs to decrease significantly over the coming years, so that a considerable PV electricity share world-wide could materialise after 2020, (3) niche-market applications, e.g. using stand-alone systems in remote areas, are crucial for continuing 'the ride along the learning curve', (4) damage costs of conventional (fossil) power sources are considerable, and their internalisation would improve the competitiveness of PV, although probably not enough to close the current cost gap. (author)

Learning Curves of Virtual Mastoidectomy in Distributed and Massed Practice

DEFF Research Database (Denmark)

Andersen, Steven Arild Wuyts; Konge, Lars; Cayé-Thomasen, Per

2015-01-01

IMPORTANCE: Repeated and deliberate practice is crucial in surgical skills training, and virtual reality (VR) simulation can provide self-directed training of basic surgical skills to meet the individual needs of the trainee. Assessment of the learning curves of surgical procedures is pivotal...... in understanding skills acquisition and best-practice implementation and organization of training. OBJECTIVE: To explore the learning curves of VR simulation training of mastoidectomy and the effects of different practice sequences with the aim of proposing the optimal organization of training. DESIGN, SETTING...... plateaued on a score of 16.0 (15.3-16.7) at approximately the ninth repetition, but the individual learning curves were highly variable. CONCLUSIONS AND RELEVANCE: Novices can acquire basic mastoidectomy competencies with self-directed VR simulation training. Training should be organized with distributed...

Application of Learning Curves for Didactic Model Evaluation: Case Studies

Directory of Open Access Journals (Sweden)

Felix Mödritscher

2013-01-01

Full Text Available The success of (online courses depends, among other factors, on the underlying didactical models which have always been evaluated with qualitative and quantitative research methods. Several new evaluation techniques have been developed and established in the last years. One of them is ‘learning curves’, which aim at measuring error rates of users when they interact with adaptive educational systems, thereby enabling the underlying models to be evaluated and improved. In this paper, we report how we have applied this new method to two case studies to show that learning curves are useful to evaluate didactical models and their implementation in educational platforms. Results show that the error rates follow a power law distribution with each additional attempt if the didactical model of an instructional unit is valid. Furthermore, the initial error rate, the slope of the curve and the goodness of fit of the curve are valid indicators for the difficulty level of a course and the quality of its didactical model. As a conclusion, the idea of applying learning curves for evaluating didactical model on the basis of usage data is considered to be valuable for supporting teachers and learning content providers in improving their online courses.

Teaching Learning Curves in an Undergraduate Economics or Operations Management Course

Science.gov (United States)

Naidu, Jaideep T.; Sanford, John F.

2012-01-01

Learning Curves has its roots in economics and behavioral psychology. Learning Curves theory has several business applications and is widely used in the industry. As faculty of Operations Management courses, we cover this topic in some depth in the classroom. In this paper, we present some of our teaching methods and material that have helped us…

Training in robotics: The learning curve and contemporary concepts in training.

Science.gov (United States)

Bach, Christian; Miernik, Arkadiusz; Schönthaler, Martin

2014-03-01

To define the learning curve of robot-assisted laparoscopic surgery for prostatectomy (RALP) and upper tract procedures, and show the differences between the classical approach to training and the new concept of parallel learning. This mini-review is based on the results of a Medline search using the keywords 'da Vinci', 'robot-assisted laparoscopic surgery', 'training', 'teaching' and 'learning curve'. For RALP and robot-assisted upper tract surgery, a learning curve of 8-150 procedures is quoted, with most articles proposing that 30-40 cases are needed to carry out the procedure safely. There is no consensus about which endpoints should be measured. In the traditional proctored training model, the surgeon learns the procedure linearly, following the sequential order of the surgical steps. A more recent approach is to specify the relative difficulty of each step and to train the surgeon simultaneously in several steps of equal difficulty. The entire procedure is only performed after all the steps are mastered in a timely manner. Recently, a 'warm-up' before robotic surgery has been shown to be beneficial for successful surgery in the operating room. There is no clear definition of the duration of the effective learning curve for RALP and robotic upper tract surgery. The concept of stepwise, parallel learning has the potential to accelerate the learning process and to make sure that initial cases are not too long. It can also be assumed that a preoperative 'warm up' could help significantly to improve the progress of the trainee.

Learning curves for ultrasound guided lung biopsy in the hands of respiratory physicians

DEFF Research Database (Denmark)

Laursen, Christian; Naur, Therese Maria Henriette; Bodtger, Uffe

2016-01-01

are depicted in figure 1. Six of the physicians had learning curves with a relatively downward or stable projection as a sign of developing competence. Three physicians, however, had learning curves with an upward projection indicating unacceptable competence in performing the procedure......Background: The aim of this study was to determine learning curves for ultrasound guided transthoracic needle biopsies (US-TTNB) performed by respiratory physicians after implementation at three different centers.Methods: During January 2012 to August 2014 patients were included if they had...... a registered US-TTNB procedure at any of the three centers. The US-TTNB was defined as being successful if the result was diagnostic and otherwise as being unsuccessful. Histology or cytology results and clinical follow-up were used as a reference tests. The learning curves for physicians having performed...

Machine Learning Techniques for Stellar Light Curve Classification

Science.gov (United States)

Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel

2018-07-01

We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

Colorectal Stenting in Malignant Large Bowel Obstruction: The Learning Curve

Directory of Open Access Journals (Sweden)

D. Williams

2011-01-01

Full Text Available Aim. Self-expanding metal stents (SEMSs are increasingly used for the palliation of metastatic colorectal cancer and as a bridge to surgery for obstructing tumours. This case series analyses the learning curve and changes in practice of colorectal stenting over a three year period. Methods. A study of 40 patients who underwent placement of SEMS for the management of colorectal cancer. Patients spanned the learning curve of a single surgeon endoscopist. Results. Technical success rates increased from 82% initially, using an average of 1.7 stents per procedure, to a 94% success rate where all patients were stented using a single stent. There has been a change in practice from elective palliative stenting toward emergency preoperative stenting. Conclusion. There is a steep learning curve for the use of SEMS in the management of malignant colorectal bowel obstruction. We suggest that at least 20 cases are required for an operator to be considered experienced.

The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves

DEFF Research Database (Denmark)

Kjems, Ulrik; Hansen, Lars Kai; Anderson, Jon

2002-01-01

Learning curves are presented as an unbiased means for evaluating the performance of models for neuroimaging data analysis. The learning curve measures the predictive performance in terms of the generalization or prediction error as a function of the number of independent examples (e.g., subjects......) used to determine the parameters in the model. Cross-validation resampling is used to obtain unbiased estimates of a generic multivariate Gaussian classifier, for training set sizes from 2 to 16 subjects. We apply the framework to four different activation experiments, in this case \\$\\backslash......\\$[/sup 15/ O]water data sets, although the framework is equally valid for multisubject fMRI studies. We demonstrate how the prediction error can be expressed as the mutual information between the scan and the scan label, measured in units of bits. The mutual information learning curve can be used...

SILC for SILC: Single Institution Learning Curve for Single-Incision Laparoscopic Cholecystectomy

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Chee Wei Tay

2013-01-01

Full Text Available Objectives. We report the single-incision laparoscopic cholecystectomy (SILC learning experience of 2 hepatobiliary surgeons and the factors that could influence the learning curve of SILC. Methods. Patients who underwent SILC by Surgeons A and B were studied retrospectively. Operating time, conversion rate, reason for conversion, identity of first assistants, and their experience with previous laparoscopic cholecystectomy (LC were analysed. CUSUM analysis is used to identify learning curve. Results. Hundred and nineteen SILC cases were performed by Surgeons A and B, respectively. Eight cases required additional port. In CUSUM analysis, most conversion occurred during the first 19 cases. Operating time was significantly lower (62.5 versus 90.6 min, P = 0.04 after the learning curve has been overcome. Operating time decreases as the experience increases, especially Surgeon B. Most conversions are due to adhesion at Calot’s triangle. Acute cholecystitis, patients’ BMI, and previous surgery do not seem to influence conversion rate. Mean operating times of cases assisted by first assistant with and without LC experience were 48 and 74 minutes, respectively (P = 0.004. Conclusion. Nineteen cases are needed to overcome the learning curve of SILC. Team work, assistant with CLC experience, and appropriate equipment and technique are the important factors in performing SILC.

Learning curves for solid oxide fuel cells

Energy Technology Data Exchange (ETDEWEB)

Rivera-Tinoco, R.; Schoots, K. [Energy research Centre of the Netherlands (Netherlands). Policy Studies; Zwaan, B.C.C. van der [Energy research Centre of the Netherlands (Netherlands). Policy Studies; Columbia Univ., New York City, NY (United States). Lenfest Center for Sustainable Energy

2010-07-01

We present learning curves for solid oxide fuel cells (SOFCs) and combined heat and power (CHP) SOFC systems with an electric capacity between 1 and 250 kW. On the basis of the cost breakdown of production cost data from fuel cell manufacturers, we developed a bottom-up model that allows for determining overall manufacturing costs from their respective cost components, among which material, energy, labor, and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the early pilot stage of development, we find for SOFC manufacturing a learning rate between 14% and 17%, and for total SOFC system fabrication between 16% and 19%. We argue that the corresponding cost reductions result largely from learning-by-searching effects (R and D) rather than learning-by-doing. When considering a longer time frame that includes the early commercial production stage, we find learning rates between 14% and 39%, which represent a mix of phenomena such as learning-by-doing, learning-by-searching, economies-of-scale and automation. (orig.)

Climbing the health learning curve together | IDRC - International ...

International Development Research Centre (IDRC) Digital Library (Canada)

2011-01-25

Jan 25, 2011 ... Climbing the health learning curve together ... Many of the projects are creating master's programs at their host universities ... Formerly based in the high Arctic, Atlantis is described by Dr Martin Forde of St George's University ...

LEARNING CURVE IN SINGLE-LEVEL MINIMALLY INVASIVE TLIF: EXPERIENCE OF A NEUROSURGEON

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Samuel Romano-Feinholz

Full Text Available ABSTRACT Objective: To describe the learning curve that shows the progress of a single neurosurgeon when performing single-level MI-TLIF. Methods: We included 99 consecutive patients who underwent single-level MI-TLIF by the same neurosurgeon (JASS. Patient’s demographic characteristics were analyzed. In addition, surgical time, intraoperative blood loss and hospital stay were evaluated. The learning curves were calculated with a piecewise regression model. Results: The mean age was 54.6 years. The learning curves showed an inverse relationship between the surgical experience and the variable analyzed, reaching an inflection point for surgical time in case 43 and for blood loss in case 48. The mean surgical time was 203.3 minutes (interquartile range [IQR] 150-240 minutes, intraoperative bleeding was 97.4ml (IQR 40-100ml and hospital stay of four days (IQR 3-5 days. Conclusions: MI-TLIF is a very frequent surgical procedure due to its effectiveness and safety, which has shown similar results to open procedure. According to this study, the required learning curve is slightly higher than for open procedures, and is reached after about 45 cases.

Learning Curves of Virtual Mastoidectomy in Distributed and Massed Practice.

Science.gov (United States)

Andersen, Steven Arild Wuyts; Konge, Lars; Cayé-Thomasen, Per; Sørensen, Mads Sølvsten

2015-10-01

Repeated and deliberate practice is crucial in surgical skills training, and virtual reality (VR) simulation can provide self-directed training of basic surgical skills to meet the individual needs of the trainee. Assessment of the learning curves of surgical procedures is pivotal in understanding skills acquisition and best-practice implementation and organization of training. To explore the learning curves of VR simulation training of mastoidectomy and the effects of different practice sequences with the aim of proposing the optimal organization of training. A prospective trial with a 2 × 2 design was conducted at an academic teaching hospital. Participants included 43 novice medical students. Of these, 21 students completed time-distributed practice from October 14 to November 29, 2013, and a separate group of 19 students completed massed practice on May 16, 17, or 18, 2014. Data analysis was performed from June 6, 2014, to March 3, 2015. Participants performed 12 repeated virtual mastoidectomies using a temporal bone surgical simulator in either a distributed (practice blocks spaced in time) or massed (all practice in 1 day) training program with randomization for simulator-integrated tutoring during the first 5 sessions. Performance was assessed using a modified Welling Scale for final product analysis by 2 blinded senior otologists. Compared with the 19 students in the massed practice group, the 21 students in the distributed practice group were older (mean age, 25.1 years), more often male (15 [62%]), and had slightly higher mean gaming frequency (2.3 on a 1-5 Likert scale). Learning curves were established and distributed practice was found to be superior to massed practice, reported as mean end score (95% CI) of 15.7 (14.4-17.0) in distributed practice vs. 13.0 (11.9-14.1) with massed practice (P = .002). Simulator-integrated tutoring accelerated the initial performance, with mean score for tutored sessions of 14.6 (13.9-15.2) vs. 13.4 (12.8-14.0) for

Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects

International Nuclear Information System (INIS)

Yu, C.F.; van Sark, W.G.J.H.M.; Alsema, E.A.

2011-01-01

In a large number of energy models, the use of learning curves for estimating technological improvements has become popular. This is based on the assumption that technological development can be monitored by following cost development as a function of market size. However, recent data show that in some stages of photovoltaic technology (PV) production, the market price of PV modules stabilizes even though the cumulative capacity increases. This implies that no technological improvement takes place in these periods: the cost predicted by the learning curve in the PV study is lower than the market one. We propose that this bias results from ignoring the effects of input prices and scale effects, and that incorporating the input prices and scale effects into the learning curve theory is an important issue in making cost predictions more reliable. In this paper, a methodology is described to incorporate the scale and input-prices effect as the additional variables into the one factor learning curve, which leads to the definition of the multi-factor learning curve. This multi-factor learning curve is not only derived from economic theories, but also supported by an empirical study. The results clearly show that input prices and scale effects are to be included, and that, although market prices are stabilizing, learning is still taking place. (author)

LEARNING CURVE IN ENDOSCOPIC TRANSNASAL SELLAR REGION SURGERY

Directory of Open Access Journals (Sweden)

Ananth G

2016-07-01

Full Text Available BACKGROUND The endoscopic endonasal approach for the sellar region lesions is a novel technique and an effective surgical option. The evidence thus far has been conflicting with reports in favour and against a learning curve. We attempt to determine the learning curve associated with this approach. METHODS Retrospective and prospective data of the patients who were surgically treated for sellar region lesions between the year 2013 and 2016 was collected, 32 patients were operated by the endoscopic endonasal approach at Vydehi Institute of Medical Sciences and Research Centre, Bangalore. Age, sex, presenting symptoms, length of hospital stay, surgical approach, type of dissection, duration of surgery, sellar floor repair, intraoperative and postoperative complications were noted. All the procedures were performed by a single neurosurgeon. RESULTS A total of 32 patients were operated amongst which 21 patients were non-functioning pituitary adenomas, 2 were growth hormone secreting functional adenomas, 1 was an invasive pituitary adenoma, 4 were craniopharyngiomas, 2 were meningiomas, 1 was Rathke’s cleft cyst and 1 was a clival chordoma. Headache was the mode of presentation in 12 patients, 12 patients had visual deficits, 6 patients presented with hormonal disturbances amongst which 4 patients presented with features of panhypopituitarism and 2 with acromegaly. Amongst the 4 patients with panhypopituitarism, 2 also had DI, two patients presented with CSF rhinorrhoea. There was a 100% improvement in the patients who presented with visual symptoms. Gross total resection was achieved in all 4 cases of craniopharyngiomas and 13 cases of pituitary adenomas. Postoperative CSF leak was seen in 4 patients who underwent re-exploration and sellar floor repair, 9 patients had postoperative Diabetes Insipidus (DI which was transient, the incidence of DI reduced towards the end of the study. There was a 25% decrease in the operating time towards the end of

Learning curve for laparoendoscopic single-site surgery for an experienced laparoscopic surgeon

OpenAIRE

Pao-Ling Torng; Kuan-Hung Lin; Jing-Shiang Hwang; Hui-Shan Liu; I-Hui Chen; Chi-Ling Chen; Su-Cheng Huang

2013-01-01

Objectives: To assess the learning curve and safety of laparoendoscopic single-site (LESS) surgery of gynecological surgeries. Materials and methods: Sixty-three women who underwent LESS surgery by a single experienced laparoscopic surgeon from February 2011 to August 2011 were included. Commercialized single-incision laparoscopic surgery homemade ports were used, along with conventional straight instruments. The learning curve has been defined as the additional surgical time with respect ...

Training, Simulation, the Learning Curve, and How to Reduce Complications in Urology.

Science.gov (United States)

Brunckhorst, Oliver; Volpe, Alessandro; van der Poel, Henk; Mottrie, Alexander; Ahmed, Kamran

2016-04-01

Urology is at the forefront of minimally invasive surgery to a great extent. These procedures produce additional learning challenges and possess a steep initial learning curve. Training and assessment methods in surgical specialties such as urology are known to lack clear structure and often rely on differing operative flow experienced by individuals and institutions. This article aims to assess current urology training modalities, to identify the role of simulation within urology, to define and identify the learning curves for various urologic procedures, and to discuss ways to decrease complications in the context of training. A narrative review of the literature was conducted through December 2015 using the PubMed/Medline, Embase, and Cochrane Library databases. Evidence of the validity of training methods in urology includes observation of a procedure, mentorship and fellowship, e-learning, and simulation-based training. Learning curves for various urologic procedures have been recommended based on the available literature. The importance of structured training pathways is highlighted, with integration of modular training to ensure patient safety. Valid training pathways are available in urology. The aim in urology training should be to combine all of the available evidence to produce procedure-specific curricula that utilise the vast array of training methods available to ensure that we continue to improve patient outcomes and reduce complications. The current evidence for different training methods available in urology, including simulation-based training, was reviewed, and the learning curves for various urologic procedures were critically analysed. Based on the evidence, future pathways for urology curricula have been suggested to ensure that patient safety is improved. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Industrial Learning Curves Series Production of the LHC Main Superconduting Dipoles

CERN Document Server

Fessia, Paolo; Rossi, Lucio

2007-01-01

By mid August 2006, 1160 of the 1232 of LHC main dipoles have been delivered to CERN by the three suppliers in charge of the production. The training of the staff, mostly hired just for this manufacture, and the improvement of the procedures with the acquired experience, naturally decrease the time necessary for the assembly of a unit. The aim of this paper is to apply methodologies like the cost-based learning curves and the time-based learning curves to the LHC Main Dipole production comparing the estimated learning percentage to the ones experienced in other industries. This type of analysis, already presented on 500 units is here extended to more than 1000 completed units. The work also tries to identify which type of industry presents the learning percentages that are the most similar to our case and to investigate the impact of the production strategy on the process efficiency.

Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

Science.gov (United States)

Hsu, Pi-Shan

2012-01-01

This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

Learning-curve estimation techniques for nuclear industry

Energy Technology Data Exchange (ETDEWEB)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year.

Learning-curve estimation techniques for nuclear industry

International Nuclear Information System (INIS)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Learning curve estimation techniques for nuclear industry

International Nuclear Information System (INIS)

Vaurio, Jussi K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Beyond the learning curve: factors influencing cost reductions in photovoltaics

International Nuclear Information System (INIS)

Nemet, Gregory F.

2006-01-01

The extent and timing of cost-reducing improvements in low-carbon energy systems are important sources of uncertainty in future levels of greenhouse-gas emissions. Models that assess the costs of climate change mitigation policy, and energy policy in general, rely heavily on learning curves to include technology dynamics. Historically, no energy technology has changed more dramatically than photovoltaics (PV), the cost of which has declined by a factor of nearly 100 since the 1950s. Which changes were most important in accounting for the cost reductions that have occurred over the past three decades? Are these results consistent with the notion that learning from experience drove technical change? In this paper, empirical data are assembled to populate a simple model identifying the most important factors affecting the cost of PV. The results indicate that learning from experience, the theoretical mechanism used to explain learning curves, only weakly explains change in the most important factors-plant size, module efficiency, and the cost of silicon. Ways in which the consideration of a broader set of influences, such as technical barriers, industry structure, and characteristics of demand, might be used to inform energy technology policy are discussed

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

Science.gov (United States)

Tabelow, Karsten; König, Reinhard; Polzehl, Jörg

2016-01-01

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis.

Directory of Open Access Journals (Sweden)

Matthias Deliano

Full Text Available Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning.

Impact of the learning curve on outcome after transcatheter mitral valve repair

DEFF Research Database (Denmark)

Ledwoch, Jakob; Franke, Jennifer; Baldus, Stephan

2014-01-01

AIMS: This analysis from the German Mitral Valve Registry investigates the impact of the learning curve with the MitraClip(®) technique on procedural success and complications. METHODS AND RESULTS: Consecutive patients treated since 2009 in centers that performed more than 50 transcatheter mitral...... not decrease over time. CONCLUSION: A learning curve using the MitraClip(®) device does not appear to significantly affect acute MR reduction, hospital and 30-day mortality. Most likely, the proctor system leads to already high initial procedure success and relatively short procedure time....

An exploratory analysis of personality, attitudes, and study skills on the learning curve within a team-based learning environment.

Science.gov (United States)

Persky, Adam M; Henry, Teague; Campbell, Ashley

2015-03-25

To examine factors that determine the interindividual variability of learning within a team-based learning environment. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

Hydrogen technologies and the technology learning curve

International Nuclear Information System (INIS)

Rogner, H.-H.

1998-01-01

On their bumpy road to commercialization, hydrogen production, delivery and conversion technologies not only require dedicated research, development and demonstration efforts, but also protected niche markets and early adopters. While niche markets utilize the unique technological properties of hydrogen, adopters exhibit a willingness to pay a premium for hydrogen fueled energy services. The concept of the technology learning curve is applied to estimate the capital requirements associated with the commercialization process of several hydrogen technologies. (author)

The learning curve associated with the introduction of the subcutaneous implantable defibrillator

NARCIS (Netherlands)

Knops, Reinoud E.; Brouwer, Tom F.; Barr, Craig S.; Theuns, Dominic A.; Boersma, Lucas; Weiss, Raul; Neuzil, Petr; Scholten, Marcoen; Lambiase, Pier D.; Leon, Angel R.; Hood, Margaret; Jones, Paul W.; Wold, Nicholas; Grace, Andrew A.; Olde Nordkamp, Louise R. A.; Burke, Martin C.

2016-01-01

Aims The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD implanters

The learning curve associated with the introduction of the subcutaneous implantable defibrillator

NARCIS (Netherlands)

R.E. Knops (Reinoud); T.F. Brouwer (Tom F.); C.S. Barr (Craig); D.A.M.J. Theuns (Dominic); L. Boersma (Lucas); R. Weiss (Ram); P. Neuzil (Petr); M.F. Scholten (Marcoen); P.D. Lambiase (Pier); A. Leon (Angel); A.M. Hood (Margaret); P. Jones; Wold, N. (Nicholas); Grace, A.A. (Andrew A.); L.R.A. Olde Nordkamp (Louise R.A.); M.C. Burke (Martin)

2016-01-01

textabstractAims: The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD

Carbon Intensities of Economies from the Perspective of Learning Curves

Directory of Open Access Journals (Sweden)

Henrique Pacini

2014-03-01

Full Text Available While some countries have achieved considerable development, many others still lack accessto the goods and services considered standard in the modern society. As CO2 emissions and development are often correlated, this paper employs the theoretical background of the Environmental Kuznets Curve (EKC and the learning curves toolkit to analyze how carbon intensities have changed as countries move towards higher development (and cumulative wealth levels. The EKC concept is then tested with the methodology of learning curves for the period between 1971 and 2010, so as to capture a dynamic picture of emissions trends and development. Results of both analyses reveal that empirical data fails to provide direct evidence of an EKC for emissions and development. The data does show, however, an interesting pattern in the dispersion of emissions levels for countries within the same HDI categories. While data does not show that countries grow more polluting during intermediary development stages, it does provide evidence that countries become more heterogeneous in their emission intensities as they develop, later re-converging to lower emission intensities at higher HDI levels. Learning rates also indicate heterogeneity among developing countries and relative convergence among developed countries. Given the heterogeneity of development paths among countries, the experiences of those which are managing to develop at low carbon intensities can prove valuable examples for ongoing efforts in climate change mitigation, especially in the developing world.

Measuring the surgical 'learning curve': methods, variables and competency.

Science.gov (United States)

Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

2014-03-01

To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

A Primer on the Statistical Modelling of Learning Curves in Health Professions Education

Science.gov (United States)

Pusic, Martin V.; Boutis, Kathy; Pecaric, Martin R.; Savenkov, Oleksander; Beckstead, Jason W.; Jaber, Mohamad Y.

2017-01-01

Learning curves are a useful way of representing the rate of learning over time. Features include an index of baseline performance (y-intercept), the efficiency of learning over time (slope parameter) and the maximal theoretical performance achievable (upper asymptote). Each of these parameters can be statistically modelled on an individual and…

Evaluation of the learning curve for external cephalic version using cumulative sum analysis.

Science.gov (United States)

Kim, So Yun; Han, Jung Yeol; Chang, Eun Hye; Kwak, Dong Wook; Ahn, Hyun Kyung; Ryu, Hyun Mi; Kim, Moon Young

2017-07-01

We evaluated the learning curve for external cephalic version (ECV) using learning curve-cumulative sum (LC-CUSUM) analysis. This was a retrospective study involving 290 consecutive cases between October 2013 and March 2017. We evaluated the learning curve for ECV on nulli and over para 1 group using LC-CUSUM analysis on the assumption that 50% and 70% of ECV procedures succeeded by description a trend-line of quadratic function with reliable R 2 values. The overall success rate for ECV was 64.8% (188/290), while the success rate for nullipara and over para 1 groups was 56.2% (100/178) and 78.6% (88/112), respectively. 'H' value, that the actual failure rate does not differ from the acceptable failure rate, was -3.27 and -1.635 when considering ECV success rates of 50% and 70%, respectively. Consequently, in order to obtain a consistent 50% success rate, we would require 57 nullipara cases, and in order to obtain a consistent 70% success rate, we would require 130 nullipara cases. In contrast, 8 to 10 over para 1 cases would be required for an expected success rate of 50% and 70% on over para 1 group. Even a relatively inexperienced physician can experience success with multipara and after accumulating experience, they will manage nullipara cases. Further research is required for LC-CUSUM involving several practitioners instead of a single practitioner. This will lead to the gradual implementation of standard learning curve guidelines for ECV.

Detection of player learning curve in a car driving game

NARCIS (Netherlands)

Bontchev, Boyan; Vassileva, Dessislava

2018-01-01

Detection of learning curves of player metrics is very important for the serious (or so called applied) games, because it provides an indicator representing how players master the game tasks by acquiring cognitive abilities, knowledge, and necessary skills for solving the game challenges. Real

Learning curve estimation techniques for the nuclear industry

International Nuclear Information System (INIS)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.

Science.gov (United States)

Yamaguchi, Tomohiro; Kinugasa, Yusuke; Shiomi, Akio; Sato, Sumito; Yamakawa, Yushi; Kagawa, Hiroyasu; Tomioka, Hiroyuki; Mori, Keita

2015-07-01

Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single institute. From December 2011 to August 2013, a total of 80 consecutive patients who underwent robotic-assisted surgery for rectal cancer performed by the same surgeon were included in this study. The learning curve was analyzed using the cumulative sum method. This method was used for all 80 cases, taking into account operative time. Operative procedures included anterior resections in 6 patients, low anterior resections in 46 patients, intersphincteric resections in 22 patients, and abdominoperineal resections in 6 patients. Lateral lymph node dissection was performed in 28 patients. Median operative time was 280 min (range 135-683 min), and median blood loss was 17 mL (range 0-690 mL). No postoperative complications of Clavien-Dindo classification Grade III or IV were encountered. We arranged operative times and calculated cumulative sum values, allowing differentiation of three phases: phase I, Cases 1-25; phase II, Cases 26-50; and phase III, Cases 51-80. Our data suggested three phases of the learning curve in robotic-assisted surgery for rectal cancer. The first 25 cases formed the learning phase.

Medical learning curves and the Kantian ideal.

Science.gov (United States)

Le Morvan, P; Stock, B

2005-09-01

A hitherto unexamined problem for the "Kantian ideal" that one should always treat patients as ends in themselves, and never only as a means to other ends, is explored in this paper. The problem consists of a prima facie conflict between this Kantian ideal and the reality of medical practice. This conflict arises because, at least presently, medical practitioners can only acquire certain skills and abilities by practising on live, human patients, and given the inevitability and ubiquity of learning curves, this learning requires some patients to be treated only as a means to this end. A number of ways of attempting to establish the compatibility of the Kantian Ideal with the reality of medical practice are considered. Each attempt is found to be unsuccessful. Accordingly, until a way is found to reconcile them, we conclude that the Kantian ideal is inconsistent with the reality of medical practice.

Robotic partial nephrectomy - Evaluation of the impact of case mix on the procedural learning curve.

Science.gov (United States)

Roman, A; Ahmed, K; Challacombe, B

2016-05-01

Although Robotic partial nephrectomy (RPN) is an emerging technique for the management of small renal masses, this approach is technically demanding. To date, there is limited data on the nature and progression of the learning curve in RPN. To analyse the impact of case mix on the RPN LC and to model the learning curve. The records of the first 100 RPN performed, were analysed at our institution that were carried out by a single surgeon (B.C) (June 2010-December 2013). Cases were split based on their Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score into the following groups: 6-7, 8-9 and >10. Using a split group (20 patients in each group) and incremental analysis, the mean, the curve of best fit and R(2) values were calculated for each group. Of 100 patients (F:28, M:72), the mean age was 56.4 ± 11.9 years. The number of patients in each PADUA score groups: 6-7, 8-9 and >10 were 61, 32 and 7 respectively. An increase in incidence of more complex cases throughout the cohort was evident within the 8-9 group (2010: 1 case, 2013: 16 cases). The learning process did not significantly affect the proxies used to assess surgical proficiency in this study (operative time and warm ischaemia time). Case difficulty is an important parameter that should be considered when evaluating procedural learning curves. There is not one well fitting model that can be used to model the learning curve. With increasing experience, clinicians tend to operate on more difficult cases. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Learning curve for laparoendoscopic single-site surgery for an experienced laparoscopic surgeon

Directory of Open Access Journals (Sweden)

Pao-Ling Torng

2013-11-01

Conclusion: LESS is a safe and feasible alternative to conventional laparoscopic surgery for adnexal and uterine diseases. A learning curve is not required for LESS surgery for experienced laparoscopic surgeons.

Learning curve of thyroid fine-needle aspiration biopsy.

Science.gov (United States)

Penín, Manuel; Martín, M Ángeles; San Millán, Beatriz; García, Juana

2017-12-01

Fine-needle aspiration biopsy (FNAB) is the reference procedure for thyroid nodule evaluation. Its main limitation are inadequate samples, which should be less than 20%. To analyze the learning curve of the procedure by comparing the results of a non-experienced endocrinologist (endocrinologist 2) to those of an experienced one (endocrinologist 1). Sixty FNABs were analyzed from February to June 2016. Each endocrinologist made 2punctures of every nodule in a random order. This order and the professional making every puncture were unknown to the pathologist who examined the samples. Endocrinologist 1 had a higher percentage of diagnoses than endocrinologist 2 (82% vs. 72%, P=.015). In the first 20 FNABs, the difference between both physicians was remarkable and statistically significant (80% vs. 50%, P=.047). In the following 20 FNABs, the difference narrowed and was not statistically significant (90% vs. 65%, P=.058). In the final 20 FNABs, the difference was minimal and not statistically significant (75% vs. 70%, P=.723). The learning curve of ultrasound-guided FNAB may be completed in a suitable environment by performing it at least 60 times. Although the guidelines recommend at least 3punctures per nodule, 2are enough to achieve an accurate percentage of diagnoses. Copyright © 2017 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

Learning curve analysis of mitral valve repair using telemanipulative technology.

Science.gov (United States)

Charland, Patrick J; Robbins, Tom; Rodriguez, Evilio; Nifong, Wiley L; Chitwood, Randolph W

2011-08-01

To determine if the time required to perform mitral valve repairs using telemanipulation technology decreases with experience and how that decrease is influenced by patient and procedure variables. A single-center retrospective review was conducted using perioperative and outcomes data collected contemporaneously on 458 mitral valve repair surgeries using telemanipulative technology. A regression model was constructed to assess learning with this technology and predict total robot time using multiple predictive variables. Statistical analysis was used to determine if models were significantly useful, to rule out correlation between predictor variables, and to identify terms that did not contribute to the prediction of total robot time. We found a statistically significant learning curve (P learning percentage∗ derived from total robot times† for the first 458 recorded cases of mitral valve repair using telemanipulative technology is 95% (R(2) = .40). More than one third of the variability in total robot time can be explained through our model using the following variables: type of repair (chordal procedures, ablations, and leaflet resections), band size, use of clips alone in band implantation, and the presence of a fellow at bedside (P Learning in mitral valve repair surgery using telemanipulative technology occurs at the East Carolina Heart Institute according to a logarithmic curve, with a learning percentage of 95%. From our regression output, we can make an approximate prediction of total robot time using an additive model. These metrics can be used by programs for benchmarking to manage the implementation of this new technology, as well as for capacity planning, scheduling, and capital budget analysis. Copyright © 2011 The American Association for Thoracic Surgery. All rights reserved.

Laparoscopy Instructional Videos : The Effect of Preoperative Compared With Intraoperative Use on Learning Curves

NARCIS (Netherlands)

Broekema, Theo H.; Talsma, Aaldert K.; Wevers, Kevin P.; Pierie, Jean-Pierre E. N.

OBJECTIVE: Previous studies have shown that the use of intraoperative instructional videos has a positive effect on learning laparoscopic procedures. This study investigated the effect of the timing of the instructional videos on learning curves in laparoscopic skills training. DESIGN: After

Non-Constant Learning Rates in Retrospective Experience Curve Analyses and their Correlation to Deployment Programs

Energy Technology Data Exchange (ETDEWEB)

Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-07-16

A key challenge for policy-makers and technology market forecasters is to estimate future technology costs and in particular the rate of cost reduction versus production volume. A related, critical question is what role should state and federal governments have in advancing energy efficient and renewable energy technologies? This work provides retrospective experience curves and learning rates for several energy-related technologies, each of which have a known history of federal and state deployment programs. We derive learning rates for eight technologies including energy efficient lighting technologies, stationary fuel cell systems, and residential solar photovoltaics, and provide an overview and timeline of historical deployment programs such as state and federal standards and state and national incentive programs for each technology. Piecewise linear regimes are observed in a range of technology experience curves, and public investments or deployment programs are found to be strongly correlated to an increase in learning rate across multiple technologies. A downward bend in the experience curve is found in 5 out of the 8 energy-related technologies presented here (electronic ballasts, magnetic ballasts, compact fluorescent lighting, general service fluorescent lighting, and the installed cost of solar PV). In each of the five downward-bending experience curves, we believe that an increase in the learning rate can be linked to deployment programs to some degree. This work sheds light on the endogenous versus exogenous contributions to technological innovation and highlights the impact of exogenous government sponsored deployment programs. This work can inform future policy investment direction and can shed light on market transformation and technology learning behavior.

Learning Curve for Seawater Reverse Osmosis Desalination Plants: Capital Cost Trend of the Past, Present, and Future

Science.gov (United States)

Caldera, Upeksha; Breyer, Christian

2017-12-01

Seawater reverse osmosis (SWRO) desalination is expected to play a pivotal role in helping to secure future global water supply. While the global reliance on SWRO plants for water security increases, there is no consensus on how the capital costs of SWRO plants will vary in the future. The aim of this paper is to analyze the past trends of the SWRO capital expenditures (capex) as the historic global cumulative online SWRO capacity increases, based on the learning curve concept. The SWRO capex learning curve is found based on 4,237 plants that came online from 1977 to 2015. A learning rate of 15% is determined, implying that the SWRO capex reduced by 15% when the cumulative capacity was doubled. Based on SWRO capacity annual growth rates of 10% and 20%, by 2030, the global average capex of SWRO plants is found to fall to 1,580 USD/(m3/d) and 1,340 USD/(m3/d), respectively. A learning curve for SWRO capital costs has not been presented previously. This research highlights the potential for decrease in SWRO capex with the increase in installation of SWRO plants and the value of the learning curve approach to estimate future SWRO capex.

The learning curve of laparoscopic holecystectomy in general surgery resident training: old age of the patient may be a risk factor?

Science.gov (United States)

Ferrarese, Alessia; Gentile, Valentina; Bindi, Marco; Rivelli, Matteo; Cumbo, Jacopo; Solej, Mario; Enrico, Stefano; Martino, Valter

2016-01-01

A well-designed learning curve is essential for the acquisition of laparoscopic skills: but, are there risk factors that can derail the surgical method? From a review of the current literature on the learning curve in laparoscopic surgery, we identified learning curve components in video laparoscopic cholecystectomy; we suggest a learning curve model that can be applied to assess the progress of general surgical residents as they learn and master the stages of video laparoscopic cholecystectomy regardless of type of patient. Electronic databases were interrogated to better define the terms "surgeon", "specialized surgeon", and "specialist surgeon"; we surveyed the literature on surgical residency programs outside Italy to identify learning curve components, influential factors, the importance of tutoring, and the role of reference centers in residency education in surgery. From the definition of acceptable error, self-efficacy, and error classification, we devised a learning curve model that may be applied to training surgical residents in video laparoscopic cholecystectomy. Based on the criteria culled from the literature, the three surgeon categories (general, specialized, and specialist) are distinguished by years of experience, case volume, and error rate; the patients were distinguished for years and characteristics. The training model was constructed as a series of key learning steps in video laparoscopic cholecystectomy. Potential errors were identified and the difficulty of each step was graded using operation-specific characteristics. On completion of each procedure, error checklist scores on procedure-specific performance are tallied to track the learning curve and obtain performance indices of measurement that chart the trainee's progress. The concept of the learning curve in general surgery is disputed. The use of learning steps may enable the resident surgical trainee to acquire video laparoscopic cholecystectomy skills proportional to the instructor

Huang's three-step maneuver shortens the learning curve of laparoscopic spleen-preserving splenic hilar lymphadenectomy.

Science.gov (United States)

Huang, Chang-Ming; Huang, Ze-Ning; Zheng, Chao-Hui; Li, Ping; Xie, Jian-Wei; Wang, Jia-Bin; Lin, Jian-Xian; Jun, Lu; Chen, Qi-Yue; Cao, Long-Long; Lin, Mi; Tu, Ru-Hong

2017-12-01

The goal of this study was to investigate the difference between the learning curves of different maneuvers in laparoscopic spleen-preserving splenic hilar lymphadenectomy for advanced upper gastric cancer. From January 2010 to April 2014, 53 consecutive patients who underwent laparoscopic spleen-preserving splenic hilar lymphadenectomy via the traditional-step maneuver (group A) and 53 consecutive patients via Huang's three-step maneuver (group B) were retrospectively analyzed. No significant difference in patient characteristics were found between the two groups. The learning curves of groups A and B were divided into phase 1 (1-43 cases and 1-30 cases, respectively) and phase 2 (44-53 cases and 31-53 cases, respectively). Compared with group A, the dissection time, bleeding loss and vascular injury were significantly decreased in group B. No significant differences in short-term outcomes were found between the two maneuvers. The multivariate analysis indicated that the body mass index, short gastric vessels, splenic artery type and maneuver were significantly associated with the dissection time in group B. No significant difference in the survival curve was found between the maneuvers. The learning curve of Huang's three-step maneuver was shorter than that of the traditional-step maneuver, and the former represents an ideal maneuver for laparoscopic spleen-preserving splenic hilar lymphadenectomy.To shorten the learning curve at the beginning of laparoscopic spleen-preserving splenic hilar lymphadenectomy, beginners should beneficially use Huang's three-step maneuver and select patients with advanced upper gastric cancer with a body mass index of less than 25 kg/m 2 and the concentrated type of splenic artery. Copyright © 2017. Published by Elsevier Ltd.

A New Proposal for Learning Curve of TEP Inguinal Hernia Repair: Ability to Complete Operation Endoscopically as a First Phase of Learning Curve

Directory of Open Access Journals (Sweden)

Mustafa Hasbahceci

2014-01-01

Full Text Available Background. The exact nature of learning curve of totally extraperitoneal inguinal hernia and the number required to master this technique remain controversial. Patients and Methods. We present a retrospective review of a single surgeon experience on patients who underwent totally extraperitoneal inguinal hernia repair. Results. There were 42 hernias (22 left- and 20 right-sided in 39 patients with a mean age of 48.8±15.1 years. Indirect, direct, and combined hernias were present in 18, 12, and 12 cases, respectively. The mean operative time was 55.1±22.8 minutes. Peritoneal injury occurred in 9 cases (21.4%. Conversion to open surgery was necessitated in 7 cases (16.7%. After grouping of all patients into two groups as cases between 1–21 and 22–42, it was seen that the majority of peritoneal injuries (7 out of 9, 77.8%, P=0.130 and all conversions (P=0.001 occurred in the first 21 cases. Conclusions. Learning curve of totally extraperitoneal inguinal hernia repair can be divided into two consequent steps: immediate and late. At least 20 operations are required for gaining anatomical knowledge and surgical pitfalls based on the ability to perform this operation without conversion during immediate phase.

Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea

International Nuclear Information System (INIS)

Hong, Sungjun; Chung, Yanghon; Woo, Chungwon

2015-01-01

South Korea, as the 9th largest energy consuming in 2013 and the 7th largest greenhouse gas emitting country in 2011, established ‘Low Carbon Green Growth’ as the national vision in 2008, and is announcing various active energy policies that are set to gain the attention of the world. In this paper, we estimated the decrease of photovoltaic power generation cost in Korea based on the learning curve theory. Photovoltaic energy is one of the leading renewable energy sources, and countries all over the world are currently expanding R and D, demonstration and deployment of photovoltaic technology. In order to estimate the learning rate of photovoltaic energy in Korea, both conventional 1FLC (one-factor learning curve), which considers only the cumulative power generation, and 2FLC, which also considers R and D investment were applied. The 1FLC analysis showed that the cost of power generation decreased by 3.1% as the cumulative power generation doubled. The 2FCL analysis presented that the cost decreases by 2.33% every time the cumulative photovoltaic power generation is doubled and by 5.13% every time R and D investment is doubled. Moreover, the effect of R and D investment on photovoltaic technology took after around 3 years, and the depreciation rate of R and D investment was around 20%. - Highlights: • We analyze the learning effects of photovoltaic energy technology in Korea. • In order to calculate the learning rate, we use 1FLC (one-factor learning curve) and 2FLC methods, respectively. • 1FLC method considers only the cumulative power generation. • 2FLC method considers both cumulative power generation and knowledge stock. • We analyze a variety of scenarios by time lag and depreciation rate of R and D investment

Learning Curve Analysis and Surgical Outcomes of Single-port Laparoscopic Myomectomy.

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Lee, Hee Jun; Kim, Ju Yeong; Kim, Seul Ki; Lee, Jung Ryeol; Suh, Chang Suk; Kim, Seok Hyun

2015-01-01

To identify learning curves for single-port laparoscopic myomectomy (SPLM) and evaluate surgical outcomes according to the sequence of operation. A retrospective study. A university-based hospital (Canadian Task Force classification II-2). The medical records from 205 patients who had undergone SPLM from October 2009 to May 2013 were reviewed. Because the myomectomy time was significantly affected by the size and number of myomas removed by SPLM, cases in which 2 or more of the myomas removed were >7 cm in diameter were excluded. Furthermore, cases involving additional operations performed simultaneously (e.g., ovarian or hysteroscopic surgery) were also excluded. A total of 161 cases of SPLM were included. None. We assessed the SPLM learning curve via a graph based on operation time versus sequence of cases. Patients were chronologically arranged according to their surgery dates and were then placed into 1 of 4 groups according to their operation sequence. SPLM was completed successfully in 160 of 161 cases (99.4%). One case was converted to multiport surgery. Basal characteristics of the patients between the 4 groups did not differ. The median operation times for the 4 groups were 112.0, 92.8, 83.7, and 90.0 minutes, respectively. Operation time decreased significantly in the second, third, and fourth groups compared with that in the first group (p learning curve became less steep, was evident after about 45 operations. Results from the current study suggested that proficiency for SPLM was achieved after about 45 operations. Additionally, operation time decreased with experience without an increase in complication rate. Copyright © 2015 AAGL. Published by Elsevier Inc. All rights reserved.

Displays mounted on cutting blocks reduce the learning curve in navigated total knee arthroplasty.

Science.gov (United States)

Schnurr, Christoph; Eysel, Peer; König, Dietmar Pierre

2011-01-01

The use of computer navigation in total knee arthroplasty (TKA) improves the implant alignment but increases the operation time. Studies have shown that the operation time is further prolonged due to the surgeon's learning curve, and longer operation times have been associated with higher morbidity risks. It has been our hypothesis that an improvement in the human-machine interface might reduce the time required during the learning curve. Accordingly, we asked whether the use of navigation devices with a display fixed on the surgical instruments would reduce the operation time in navigated TKAs performed by navigation beginners. Thirty medical students were randomized and used two navigation devices in rotation: these were the Kolibri® device with an external display and the Dash® device with a display that was fixed on the cutting blocks. The time for adjustment of the tibial and femoral cutting blocks on knee models while using these devices was measured. A significant time reduction was demonstration when the Dash® device was used: The time reduction was 21% for the tibial block (p = 0.007), 40% for the femoral block (p learning curve may be diminished.

The learning curve of laparoendoscopic single-site (LESS) cholecystectomy: definable, short, and safe.

Science.gov (United States)

Hernandez, Jonathan; Ross, Sharona; Morton, Connor; McFarlin, Kellie; Dahal, Sujat; Golkar, Farhaad; Albrink, Michael; Rosemurgy, Alexander

2010-11-01

The applications of laparoendoscopic single-site (LESS) surgery, including cholecystectomy, are occurring quickly, although little is generally known about issues associated with the learning curve of this new technique including operative time, conversion rates, and safety. We prospectively followed all patients undergoing LESS cholecystectomy, and compared operations undertaken at our institutions in cohorts of 25 patients with respect to operative times, conversion rates, and complications. One-hundred fifty patients of mean age 46 years underwent LESS cholecystectomy. No significant differences in operative times were demonstrable between any of the 25-patient cohorts operated on at our institution. A significant reduction in operative times (p < 0.001) after completion of 75 LESS procedures was, however, identified with the experience of a single surgeon. No significant reduction in the number of procedures requiring an additional trocar(s) or conversion to open operations was observed after completion of 25 LESS cholecystectomies. Complication rates were low, and not significantly different between any 25-patient cohorts. For surgeons proficient with multi-incision laparoscopic cholecystectomy, the learning curve for LESS cholecystectomy begins near proficiency. Operative complications and conversions were infrequent and unchanged across successive 25-patient cohorts, and were similar to those reported for multi-incision laparoscopic cholecystectomy after the learning curve. Copyright © 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Application of the Learning Curve Analysis to the LHC Main Dipole Production First Assessment

CERN Document Server

Fessia, P; Rossi, L

2006-01-01

About two third of the LHC main dipoles have been delivered by the three suppliers charged of the production. The training of the staff, mostly hired just for this manufacture, and the natural improvement of the procedures with the acquired experience, decrease naturally the time necessary for the assembly of a unit. The aim of this paper is to apply methodologies like the cost-based learning curves and the time-based learning curves to the LHC Main Dipole comparing the estimated learning percentage to the ones experienced in other industries. This type of analysis, still in a preliminary phase and here applied to about 40% of the total production of the LHC magnets that will end by 2006, shows that our production has a relatively high learning percentage and it is similar to aerospace and complex machine tools for new models. Therefore with the LHC project, accelerator magnets seem to have reached industrial maturity and this production can be used as bench mark for other large scientific projects implying s...

Learning Curves and Bootstrap Estimates for Inference with Gaussian Processes: A Statistical Mechanics Study

DEFF Research Database (Denmark)

Malzahn, Dorthe; Opper, Manfred

2003-01-01

We employ the replica method of statistical physics to study the average case performance of learning systems. The new feature of our theory is that general distributions of data can be treated, which enables applications to real data. For a class of Bayesian prediction models which are based...... on Gaussian processes, we discuss Bootstrap estimates for learning curves....

Environmental management by the learning curve

International Nuclear Information System (INIS)

Fehr, M.

2003-01-01

This is a futuristic appreciation of waste management challenges and their solution by means of good management models. A literature review, administrative initiatives, research results, and experiences from practice are combined in this study to render an evolutionary picture of the change in paradigm relative to municipal solid waste possible to occur between 2000 and 2025. The principal stages of progress in the 25 years studied were: the correct characterization of municipal solid waste as a function of geographical location and recycling potential, the divided collection model and its corresponding learning curve, correct opportunity cost accounting tools, and the generally admitted and accepted changeover of municipal solid waste treatment from a technical to a management problem. It is reported that as a result of this progress, the municipal landfill is a species in extinction. Regional landfills with long life spans are the rule in 2025

Defining the learning curve of laparoendoscopic single-site Heller myotomy.

Science.gov (United States)

Ross, Sharona B; Luberice, Kenneth; Kurian, Tony J; Paul, Harold; Rosemurgy, Alexander S

2013-08-01

Initial outcomes suggest laparoendoscopic single-site (LESS) Heller myotomy with anterior fundoplication provides safe, efficacious, and cosmetically superior outcomes relative to conventional laparoscopy. This study was undertaken to define the learning curve of LESS Heller myotomy with anterior fundoplication. One hundred patients underwent LESS Heller myotomy with anterior fundoplication. Symptom frequency and severity were scored using a Likert scale (0 = never/not bothersome to 10 = always/very bothersome). Symptom resolution, additional trocars, and complications were compared among patient quartiles. Median data are presented. Preoperative frequency/severity scores were: dysphagia = 10/8 and regurgitation = 8/7. Additional trocars were placed in 12 patients (10%), of whom all were in the first two quartiles. Esophagotomy/gastrotomy occurred in three patients. Postoperative complications occurred in 9 per cent. No conversions to "open" operations occurred. Length of stay was 1 day. Postoperative frequency/severity scores were: dysphagia = 2/0 and regurgitation = 0/0; scores were less than before myotomy (P Heller myotomy with anterior fundoplication well palliates symptoms of achalasia with no apparent scar. Placement of additional trocars only occurred early in the experience. For surgeons proficient with the conventional laparoscopic approach, the learning curve of LESS Heller myotomy with anterior fundoplication is short and safe, because proficiency is quickly attained.

Laparoscopic colorectal surgery in learning curve: Role of implementation of a standardized technique and recovery protocol. A cohort study

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Gaetano Luglio

2015-06-01

Conclusion: Proper laparoscopic colorectal surgery is safe and leads to excellent results in terms of recovery and short term outcomes, even in a learning curve setting. Key factors for better outcomes and shortening the learning curve seem to be the adoption of a standardized technique and training model along with the strict supervision of an expert colorectal surgeon.

Systematic review of learning curves for minimally invasive abdominal surgery: a review of the methodology of data collection, depiction of outcomes, and statistical analysis.

Science.gov (United States)

Harrysson, Iliana J; Cook, Jonathan; Sirimanna, Pramudith; Feldman, Liane S; Darzi, Ara; Aggarwal, Rajesh

2014-07-01

To determine how minimally invasive surgical learning curves are assessed and define an ideal framework for this assessment. Learning curves have implications for training and adoption of new procedures and devices. In 2000, a review of the learning curve literature was done by Ramsay et al and it called for improved reporting and statistical evaluation of learning curves. Since then, a body of literature is emerging on learning curves but the presentation and analysis vary. A systematic search was performed of MEDLINE, EMBASE, ISI Web of Science, ERIC, and the Cochrane Library from 1985 to August 2012. The inclusion criteria are minimally invasive abdominal surgery formally analyzing the learning curve and English language. 592 (11.1%) of the identified studies met the selection criteria. Time is the most commonly used proxy for the learning curve (508, 86%). Intraoperative outcomes were used in 316 (53%) of the articles, postoperative outcomes in 306 (52%), technical skills in 102 (17%), and patient-oriented outcomes in 38 (6%) articles. Over time, there was evidence of an increase in the relative amount of laparoscopic and robotic studies (P statistical evidence of a change in the complexity of analysis (P = 0.121). Assessment of learning curves is needed to inform surgical training and evaluate new clinical procedures. An ideal analysis would account for the degree of complexity of individual cases and the inherent differences between surgeons. There is no single proxy that best represents the success of surgery, and hence multiple outcomes should be collected.

The learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease.

Science.gov (United States)

Novotný, Tomáš; Dvorák, Martin; Staffa, Robert

2011-02-01

Since the end of the 20th century, robot-assisted surgery has been finding its role among other minimally invasive methods. Vascular surgery seems to be another specialty in which the benefits of this technology can be expected. Our objective was to assess the learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease in a group of 40 patients. Between May 2006 and January 2010, 40 patients (32 men, 8 women), who were a median age of 58 years (range, 48-75 years), underwent 40 robot-assisted laparoscopic aortofemoral reconstructions. Learning curve estimations were used for anastomosis, clamping, and operative time assessment. For conversion rate evaluation, the cumulative summation (CUSUM) technique was used. Statistical analysis comparing the first and second half of our group, and unilateral-to-bilateral reconstructions were performed. We created 21 aortofemoral and 19 aortobifemoral bypasses. The median proximal anastomosis time was 23 minutes (range, 18-50 minutes), median clamping time was 60 minutes (range, 40-95 minutes), and median operative time was 295 minutes (range, 180-475 minutes). The 30-day mortality rate was 0%, and no graft or wound infection or cardiopulmonary or hepatorenal complications were observed. During the median 18-month follow-up (range, 2-48 months), three early graft occlusions occurred (7%). After reoperations, the secondary patency of reconstructions was 100%. Data showed a typical short learning curve for robotic proximal anastomosis creation with anastomosis and clamping time reduction. The operative time learning curve was flat, confirming the procedure's complexity. There were two conversions to open surgery. CUSUM analysis confirmed that an acceptable conversion rate set at 5% was achieved. Comparing the first and second half of our group, all recorded times showed statistically significant improvements. Differences between unilateral and bilateral reconstructions were not

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis

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Igor I. Stepanov

2012-01-01

Full Text Available The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1–5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males. A group of MS patients included 365 patients (266 females and 99 males with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients 3 and 4 of our mathematical model 3∗exp(−2∗(−1+4∗(1−exp(−2∗(−1 because discriminant functions, calculated separately for 3 and 4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both.

Does my high blood pressure improve your survival? Overall and subgroup learning curves in health.

Science.gov (United States)

Van Gestel, Raf; Müller, Tobias; Bosmans, Johan

2017-09-01

Learning curves in health are of interest for a wide range of medical disciplines, healthcare providers, and policy makers. In this paper, we distinguish between three types of learning when identifying overall learning curves: economies of scale, learning from cumulative experience, and human capital depreciation. In addition, we approach the question of how treating more patients with specific characteristics predicts provider performance. To soften collinearity problems, we explore the use of least absolute shrinkage and selection operator regression as a variable selection method and Theil-Goldberger mixed estimation to augment the available information. We use data from the Belgian Transcatheter Aorta Valve Implantation (TAVI) registry, containing information on the first 860 TAVI procedures in Belgium. We find that treating an additional TAVI patient is associated with an increase in the probability of 2-year survival by about 0.16%-points. For adverse events like renal failure and stroke, we find that an extra day between procedures is associated with an increase in the probability for these events by 0.12%-points and 0.07%-points, respectively. Furthermore, we find evidence for positive learning effects from physicians' experience with defibrillation, treating patients with hypertension, and the use of certain types of replacement valves during the TAVI procedure. Copyright © 2017 John Wiley & Sons, Ltd.

Why the Kantian ideal survives medical learning curves, and why it matters.

Science.gov (United States)

Brecher, B

2006-09-01

The "Kantian ideal" is often misunderstood as invoking individual autonomy rather than rational self legislation. Le Morvan and Stock's otherwise insightful discussion of "Medical learning curves and the Kantian ideal"--for example--draws the mistaken inference that that ideal is inconsistent with the realities of medical practice. But it is not. Rationally to be a patient entails accepting its necessary conditions.

Preliminary Results and Learning Curve of the Minimally Invasive Chevron Akin Operation for Hallux Valgus.

Science.gov (United States)

Jowett, Charlie R J; Bedi, Harvinder S

Minimally invasive surgery is increasing in popularity. It is relevant in hallux valgus surgery owing to the potential for reduced disruption of the soft tissues and improved wound healing. We present our results and assess the learning curve of the minimally invasive Chevron Akin operation for hallux valgus. A total of 120 consecutive feet underwent minimally invasive Chevron Akin for symptomatic hallux valgus, of which 14 were excluded. They were followed up for a mean of 25 (range 18 to 38) months. The patients were clinically assessed using the American Orthopaedic Foot and Ankle Society score. Complications and patient satisfaction were recorded. The radiographs were analyzed and measurements recorded for hallux valgus and intermetatarsal angle correction. The mean age of the patients undergoing surgery was 55 (range 25 to 81) years. Of the 78 patients, 76 (97.4%) were female and 2 (2.6%) were male; 28 (35.9%) cases were bilateral. The mean American Orthopaedic Foot and Ankle Society score improved from 56 (range 23 to 76) preoperatively to 87 (range 50 to 100) postoperatively (p technique. They display a steep associated learning curve. However, the results are promising, and the learning curve is comparable to that for open hallux valgus surgery. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis

Science.gov (United States)

Stepanov, Igor I.; Abramson, Charles I.; Hoogs, Marietta; Benedict, Ralph H. B.

2012-01-01

The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1–5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(−B2  ∗  (X − 1)) + B4  ∗  (1 − exp(−B2  ∗  (X − 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both. PMID:22745911

Analysis of the learning curve for peroral endoscopic myotomy for esophageal achalasia: Single-center, two-operator experience.

Science.gov (United States)

Lv, Houning; Zhao, Ningning; Zheng, Zhongqing; Wang, Tao; Yang, Fang; Jiang, Xihui; Lin, Lin; Sun, Chao; Wang, Bangmao

2017-05-01

Peroral endoscopic myotomy (POEM) has emerged as an advanced technique for the treatment of achalasia, and defining the learning curve is mandatory. From August 2011 to June 2014, two operators in our institution (A&B) carried out POEM on 35 and 33 consecutive patients, respectively. Moving average and cumulative sum (CUSUM) methods were used to analyze the POEM learning curve for corrected operative time (cOT), referring to duration of per centimeter myotomy. Additionally, perioperative outcomes were compared among distinct learning curve phases. Using the moving average method, cOT reached a plateau at the 29th case and at the 24th case for operators A and B, respectively. CUSUM analysis identified three phases: initial learning period (Phase 1), efficiency period (Phase 2) and mastery period (Phase 3). The relatively smooth state in the CUSUM graph occurred at the 26th case and at the 24th case for operators A and B, respectively. Mean cOT of distinct phases for operator A were 8.32, 5.20 and 3.97 min, whereas they were 5.99, 3.06 and 3.75 min for operator B, respectively. Eckardt score and lower esophageal sphincter pressure significantly decreased during the 1-year follow-up period. Data were comparable regarding patient characteristics and perioperative outcomes. This single-center study demonstrated that expert endoscopists with experience in esophageal endoscopic submucosal dissection reached a plateau in learning of POEM after approximately 25 cases. © 2016 Japan Gastroenterological Endoscopy Society.

Yield curve and Recession Forecasting in a Machine Learning Framework

OpenAIRE

Theophilos Papadimitriou; Periklis Gogas; Maria Matthaiou; Efthymia Chrysanthidou

2014-01-01

In this paper, we investigate the forecasting ability of the yield curve in terms of the U.S. real GDP cycle. More specifically, within a Machine Learning (ML) framework, we use data from a variety of short (treasury bills) and long term interest rates (bonds) for the period from 1976:Q3 to 2011:Q4 in conjunction with the real GDP for the same period, to create a model that can successfully forecast output fluctuations (inflation and output gaps) around its long-run trend. We focus our attent...

Does Prior Laparoscopic and Open Surgery Experience Have Any Impact on Learning Curve in Transition to Robotic Surgery?

Directory of Open Access Journals (Sweden)

Cüneyt Adayener

2016-12-01

Full Text Available It has been 15 years since the Food And Drug Administration approved the Da Vinci® robotic surgery system. Robotic applications are being used extensively in urology, particularly in radical prostatectomy. Like all high-tech products, this system also has a high cost and a steep learning curve, therefore, preventing it from becoming widespread. There are various studies on the effect of open surgery or laparoscopy experience on the learning curve of robotic surgery. Analyzing these interactions well will provide valuable information on making the training period of robotic system more efficient.

Learning curve of hysteroscopic placement of tubal sterilization microinserts in 15 gynecologists in the Netherlands.

Science.gov (United States)

Janse, Juliënne A; Pattij, Thyrza O S; Eijkemans, Marinus J C; Broekmans, Frank J; Veersema, Sebastiaan; Schreuder, Henk W R

2013-09-01

To evaluate the learning curve of hysteroscopic placement of tubal sterilization microinserts by gynecologists in the Netherlands. Prospective multicenter study (Canadian Task Force II-2). Ten community (teaching) hospitals in the Netherlands. A total of 631 women who underwent permanent sterilization by tubal microinserts. Hysteroscopic placement of tubal sterilization microinserts performed by 15 gynecologists experienced in performing operative hysteroscopy, starting from their very first placement. Effect of increasing experience in time on procedure time, pain score, successful bilateral placement, and complications. Bilateral successful placement with confirmation of adequate positioning at follow-up evaluation was achieved in 480 (76.1%) patients at first attempt and in 44 (7.0%) at second attempt. Median procedure time was 8.0 minutes (range: 3-40), and 31 (4.9%) patients were lost to follow-up evaluation. Gravidity showed to be a confounding factor and was consequently adjusted for. A learning curve was seen in a statistically significant decrease of procedure time with increasing experience. The decrease in procedure time extended to 11 to 15 cases and was followed by a plateau phase of the subsequent 60 cases. In contrast, pain scores, successful placement, and complication rate appeared not to improve with increasing experience. A learning curve for hysteroscopic tubal sterilization was seen for procedure time, but successful placement, pain score, and complication rate were not clearly influenced by increasing experience. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Automated Blazar Light Curves Using Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Johnson, Spencer James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-07-27

This presentation describes a problem and methodology pertaining to automated blazar light curves. Namely, optical variability patterns for blazars require the construction of light curves and in order to generate the light curves, data must be filtered before processing to ensure quality.

[Evaluation of the learning curve of residents in localizing a phantom target with ultrasonography].

Science.gov (United States)

Dessieux, T; Estebe, J-P; Bloc, S; Mercadal, L; Ecoffey, C

2008-10-01

Few information are available regarding the learning curve in ultrasonography and even less for ultrasound-guided regional anesthesia. This study aimed to evaluate in a training program the learning curve on a phantom of 12 residents novice in ultrasonography. Twelve trainees inexperienced in ultrasonography were given introductory training consisting of didactic formation on the various components of the portable ultrasound machine (i.e. on/off button, gain, depth, resolution, and image storage). Then, students performed three trials, in two sets of increased difficulty, at executing these predefined tasks: adjustments of the machine, then localization of a small plastic piece introduced into roasting pork (3 cm below the surface). At the end of the evaluation, the residents were asked to insert a 22 G needle into an exact predetermined target (i.e. point of fascia intersection). The progression of the needle was continuously controlled by ultrasound visualization using injection of a small volume of water (needle perpendicular to the longitudinal plane of the ultrasound beam). Two groups of two different examiners evaluated for each three trials the skill of the residents (quality, time to perform the machine adjustments, to localize the plastic target, and to hydrolocalize, and volume used for hydrolocalization). After each trial, residents evaluated their performance using a difficulty scale (0: easy to 10: difficult). All residents performed the adjustments from the last trial of each set, with a learning curve observed in terms of duration. Localization of the plastic piece was achieved by all residents at the 6th trial, with a shorter duration of localization. Hydrolocalization was achieved after the 4th trial by all subjects. Difficulty scale was correlated to the number of trials. All these results were independent of the experience of residents in regional anesthesia. Four trials were necessary to adjust correctly the machine, to localize a target, and to

Utility of Interobserver Agreement Statistics in Establishing Radiology Resident Learning Curves During Self-directed Radiologic Anatomy Training.

Science.gov (United States)

Tureli, Derya; Altas, Hilal; Cengic, Ismet; Ekinci, Gazanfer; Baltacioglu, Feyyaz

2015-10-01

The aim of the study was to ascertain the learning curves for the radiology residents when first introduced to an anatomic structure in magnetic resonance images (MRI) to which they have not been previously exposed to. The iliolumbar ligament is a good marker for testing learning curves of radiology residents because the ligament is not part of a routine lumbar MRI reporting and has high variability in detection. Four radiologists, three residents without previous training and one mentor, studied standard axial T1- and T2-weighted images of routine lumbar MRI examinations. Radiologists had to define iliolumbar ligament while blinded to each other's findings. Interobserver agreement analyses, namely Cohen and Fleiss κ statistics, were performed for groups of 20 cases to evaluate the self-learning curve of radiology residents. Mean κ values of resident-mentor pairs were 0.431, 0.608, 0.604, 0.826, and 0.963 in the analysis of successive groups (P 0.8). Therefore, a junior radiology resident can obtain enough experience in identifying a rather ambiguous anatomic structure in routine MRI after a brief instruction of a few minutes by a mentor and studying approximately 80 cases by oneself. Implementing this methodology will help radiology educators obtain more concrete ideas on the optimal time and effort required for supported self-directed visual learning processes in resident education. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Optimizing area under the ROC curve using semi-supervised learning.

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Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Learning from uncertain curves

DEFF Research Database (Denmark)

Mallasto, Anton; Feragen, Aasa

2017-01-01

We introduce a novel framework for statistical analysis of populations of nondegenerate Gaussian processes (GPs), which are natural representations of uncertain curves. This allows inherent variation or uncertainty in function-valued data to be properly incorporated in the population analysis. Us...

Learning Curve Characteristics for Caesarean Section Among Associate Clinicians : A Prospective Study from Sierra Leone

NARCIS (Netherlands)

Waalewijn, B.P.; van Duinen, A.; Koroma, A. P.; Rijken, M. J.; Elhassein, M.; Bolkan, H. A.

2017-01-01

Background: In response to the high maternal mortality ratio, Sierra Leone has adopted an associate clinician postgraduate surgical task-sharing training programme. Little is known about learning curve characteristics for caesarean sections among associate clinicians. The aim of this study is to

Virtual reality cataract surgery training: learning curves and concurrent validity.

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Selvander, Madeleine; Åsman, Peter

2012-08-01

To investigate initial learning curves on a virtual reality (VR) eye surgery simulator and whether achieved skills are transferable between tasks. Thirty-five medical students were randomized to complete ten iterations on either the VR Caspulorhexis module (group A) or the Cataract navigation training module (group B) and then two iterations on the other module. Learning curves were compared between groups. The second Capsulorhexis video was saved and evaluated with the performance rating tool Objective Structured Assessment of Cataract Surgical Skill (OSACSS). The students' stereoacuity was examined. Both groups demonstrated significant improvements in performance over the 10 iterations: group A for all parameters analysed including score (p < 0.0001), time (p < 0.0001) and corneal damage (p = 0.0003), group B for time (p < 0.0001), corneal damage (p < 0.0001) but not for score (p = 0.752). Training on one module did not improve performance on the other. Capsulorhexis score correlated significantly with evaluation of the videos using the OSACSS performance rating tool. For stereoacuity < and ≥120 seconds of arc, sum of both modules' second iteration score was 73.5 and 41.0, respectively (p = 0.062). An initial rapid improvement in performance on a simulator with repeated practice was shown. For capsulorhexis, 10 iterations with only simulator feedback are not enough to reach a plateau for overall score. Skills transfer between modules was not found suggesting benefits from training on both modules. Stereoacuity may be of importance in the recruitment and training of new cataract surgeons. Additional studies are needed to investigate this further. Concurrent validity was found for Capsulorhexis module. © 2010 The Authors. Acta Ophthalmologica © 2010 Acta Ophthalmologica Scandinavica Foundation.

Learning curves of theta/beta neurofeedback in children with ADHD.

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Janssen, Tieme W P; Bink, Marleen; Weeda, Wouter D; Geladé, Katleen; van Mourik, Rosa; Maras, Athanasios; Oosterlaan, Jaap

2017-05-01

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and specificity of this intervention. A total of 38 children (aged between 7 and 13 years) with a DSM-IV-TR diagnosis of ADHD, completed on average 29 sessions of theta (4-8 Hz)/beta (13-20 Hz) neurofeedback training. Dependent variables included training-related measures as well as theta and beta power during baseline and training runs for each session. Learning effects were analyzed both within and between sessions. To further specify findings, individual learning curves were explored and correlated with behavioral changes in ADHD symptoms. Over the course of the training, there was a linear increase in participants' mean training level, highest obtained training level and the number of earned credits (range b = 0.059, -0.750, p neurofeedback, although a lack of behavioral correlates may indicate insufficient transfer to daily functioning, or to confounding reinforcement of electromyographic activity. This trial is registered at the US National Institutes of Health (ClinicalTrials.gov, ref. no: NCT01363544); https://clinicaltrials.gov/show/NCT01363544 .

Descemet Membrane Endothelial Keratoplasty Learning Curve for Graft Preparation in an Eye Bank Using 645 Donor Corneas.

Science.gov (United States)

Parekh, Mohit; Ruzza, Alessandro; Romano, Vito; Favaro, Elisa; Baruzzo, Mattia; Salvalaio, Gianni; Grassetto, Andrea; Ferrari, Stefano; Ponzin, Diego

2018-03-01

To investigate the learning curve of Descemet membrane endothelial keratoplasty (DMEK) graft preparation in an eye bank. Four operators prepared 645 DMEK grafts using the stripping technique between 2014 and 2017 at the Veneto Eye Bank Foundation, Italy. Endothelial cell loss (ECL) and tissue wastage were recorded retrospectively after DMEK preparation and correlated with the number of tissues prepared each year by each operator. On average, our operators performed 1 donor preparation a week over the course of this study. Only donors older than 60 years were used in this study, and approximately 10% of donors had diabetes. The Wilcoxon test for paired data and 1-way ANOVA were used for checking statistical significance with the Tukey test as post hoc analysis. P 0.05). There is a learning curve for DMEK graft preparation. ECL and tissue wastage can be reduced with practice and skills. However, each operator may be limited to his or her own learning capability.

Innovation and learning curves. Report on knowledge questions of the Working Group Energy and Climate

International Nuclear Information System (INIS)

Schoots, K.

2010-05-01

This report has been written on account of knowledge questions formulated by the Working Group Energy and Climate. This Working Group has been established in the framework of the Broad Reconsideration of Dutch government policy caused by the economic crisis of 2008-2009. Its task is to investigate the possibilities for a structural reduction of government spending by 20% on sustainable energy, energy saving and fiscal advantages carrying non-sustainable incentives. Apart from that, spending on policies aimed at mitigating climate change are scrutinized. In connection with this task, the working group has formulated knowledge questions which refer to cost effectiveness and possibilities for target achievement, possibilities within the European Renewables Directive and learning curves and innovation. This report addresses the latter two themes: learning curves and innovation. The selection of technologies assessed is not all-embracing, but based on the technologies within the SDE regulation (Dutch regulation on support for sustainable energy) supplemented by some promising innovations. [nl

Transforaminal Lumbar Interbody Fusion with Rigid Interspinous Process Fixation: A Learning Curve Analysis of a Surgeon Team's First 74 Cases.

Science.gov (United States)

Doherty, Patrick; Welch, Arthur; Tharpe, Jason; Moore, Camille; Ferry, Chris

2017-05-30

Studies have shown that a significant learning curve may be associated with adopting minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) with bilateral pedicle screw fixation (BPSF). Accordingly, several hybrid TLIF techniques have been proposed as surrogates to the accepted BPSF technique, asserting that less/fewer fixation(s) or less disruptive fixation may decrease the learning curve while still maintaining the minimally disruptive benefits. TLIF with interspinous process fixation (ISPF) is one such surrogate procedure. However, despite perceived ease of adaptability given the favorable proximity of the spinous processes, no evidence exists demonstrating whether or not the technique may possess its own inherent learning curve. The purpose of this study was to determine whether an intraoperative learning curve for one- and two-level TLIF + ISPF may exist for a single lead surgeon. Seventy-four consecutive patients who received one- or two-Level TLIF with rigid ISPF by a single lead surgeon were retrospectively reviewed. It was the first TLIF + ISPF case series for the lead surgeon. Intraoperative blood loss (EBL), hospitalization length-of-stay (LOS), fluoroscopy time, and postoperative complications were collected. EBL, LOS, and fluoroscopy time were modeled as a function of case number using multiple linear regression methods. A change point was included in each model to allow the trajectory of the outcomes to change during the duration of the case series. These change points were determined using profile likelihood methods. Models were fit using the maximum likelihood estimates for the change points. Age, sex, body mass index (BMI), and the number of treated levels were included as covariates. EBL, LOS, and fluoroscopy time did not significantly differ by age, sex, or BMI (p ≥ 0.12). Only EBL differed significantly by the number of levels (p = 0.026). The case number was not a significant predictor of EBL, LOS, or fluoroscopy time (p ≥ 0

Learning curves and long-term outcome of simulation-based thoracentesis training for medical students

Science.gov (United States)

2011-01-01

Background Simulation-based medical education has been widely used in medical skills training; however, the effectiveness and long-term outcome of simulation-based training in thoracentesis requires further investigation. The purpose of this study was to assess the learning curve of simulation-based thoracentesis training, study skills retention and transfer of knowledge to a clinical setting following simulation-based education intervention in thoracentesis procedures. Methods Fifty-two medical students were enrolled in this study. Each participant performed five supervised trials on the simulator. Participant's performance was assessed by performance score (PS), procedure time (PT), and participant's confidence (PC). Learning curves for each variable were generated. Long-term outcome of the training was measured by the retesting and clinical performance evaluation 6 months and 1 year, respectively, after initial training on the simulator. Results Significant improvements in PS, PT, and PC were noted among the first 3 to 4 test trials (p 0.05). Clinical competency in thoracentesis was improved in participants who received simulation training relative to that of first year medical residents without such experience (p simulation-based thoracentesis training can significantly improve an individual's performance. The saturation of learning from the simulator can be achieved after four practice sessions. Simulation-based training can assist in long-term retention of skills and can be partially transferred to clinical practice. PMID:21696584

Retrospective analysis of the learning curve associated with laparoscopic ovariectomy in dogs and associated perioperative complication rates.

Science.gov (United States)

Pope, Juliet Frances Anne; Knowles, Toby Grahame

2014-08-01

To assess the learning curve associated with laparoscopic ovariectomy (LOE) in 618 dogs and to report perioperative complication rates. Case series. Dogs (n = 618). Data retrieved from the medical records of bitches admitted for LOE over 42 months included date of surgery, breed, weight (kg), age (months), surgeon, suture material used, intraoperative complications and postoperative complications. Each LOE was defined as "successful" or "unsuccessful" by the absence or presence of an intraoperative complication and "failure" rate described using a CUSUM technique. Follow-up time ranged from 152 to 1,435 days (median, 737 days). Intraoperative complications occurred in 10 dogs (1.6%) and included: splenic laceration (6 dogs; 1%), urinary bladder perforation (3 dogs; 0.5%), and subcutaneous emphysema (1 dog; 0.2%). Postoperative complications occurred in 99 dogs (16%) and included: incisional inflammation treated with antibiotics (87 dogs [14%]; 96/1,854 incisions; 5.1%), incisional seroma (5 dogs [0.8%]; 5/1,854 incisions, 0.3%), incisional hernia (4 dogs [0.6%]; 4/1,854 incisions, 0.2%), and ovarian remnant syndrome (3 dogs; 0.5%). CUSUM charts indicated an initial "learning curve" of ∼80 LOE. LOE is a technique with an initial learning curve but once surgical proficiency is reached after ∼80 procedures then intraoperative complication rates associated with the procedure can be low. © Copyright 2014 by The American College of Veterinary Surgeons.

Enucleation ratio efficacy might be a better predictor to assess learning curve of holmium laser enucleation of the prostate

Directory of Open Access Journals (Sweden)

Chang Wook Jeong

2012-06-01

Full Text Available PURPOSE: To appraise the evaluation methods for learning curve and to analyze the non-mentor-aided learning curve and early complications following the holmium laser enucleation of the prostate. MATERIALS AND METHODS:One-hundred and forty (n=140 consecutive patients who underwent HoLEP from July 2008 to July 2010 by a single surgeon (SJO were enrolled. Perioperative clinical variables, including enucleation time, morcellation time, enucleation ratio (enucleation weight/transitional zone volume, enucleation efficacy (enucleated weight/enucleation time, enucleation ratio efficacy (enucleation ratio/enucleation time, and early complication rate were analyzed. RESULTS: Mean prostate volume was 62.7 mL (range 21-162 and preoperative International Prostate Symptom Score (IPSS was 19.0 (4-35. Mean enucleation time and morcellation time were 49.9±23.8 (S.D. min and 11.0±9.7 min, respectively. Median duration of postoperative indwelling catheter was 1 (1-7 day and median hospital stay was 1 (1-6 day. There were a total of 31 surgery-related complications in 27 patients (19.3%, and all were manageable. There was an increasing trend of enucleation efficacy in the first 50 cases. However, enucleation efficacy was linearly correlated with the prostate size (correlation coefficients, R=0.701, p<0.001. But, enucleation ratio efficacy could eliminate the confounding effect of the prostate size (R=-0.101, p=0.233. The plateau of enucleation ratio efficacy was reached around the twenty-fifth case. CONCLUSIONS: Our results demonstrated that the operative learning curve plateau is reached after about 25 cases. We propose that a more appropriate parameter for estimating the operative learning curve is enucleation ratio efficacy, rather than enucleation efficacy.

[Individual learning curve for radical robot-assisted prostatectomy based on the example of three professionals working in one clinic].

Science.gov (United States)

Rasner, P I; Pushkar', D Iu; Kolontarev, K B; Kotenkov, D V

2014-01-01

The appearance of new surgical technique always requires evaluation of its effectiveness and ease of acquisition. A comparative study of the results of the first three series of successive robot-assisted radical prostatectomy (RARP) performed on at time by three surgeons, was conducted. The series consisted of 40 procedures, and were divided into 4 groups of 10 operations for the analysis. When comparing data, statistically significant improvement of intra- and postoperative performance in each series was revealed, with increase in the number of operations performed, and in each subsequent series compared with the preceding one. We recommend to perform the planned conversion at the first operation. In our study, previous laparoscopic experience did not provide any significant advantages in the acquisition of robot-assisted technology. To characterize the individual learning curve, we recommend the use of the number of operations that the surgeon looked in the life-surgery regimen and/or in which he participated as an assistant before his own surgical activity, as well as the indicator "technical defect". In addition to the term "individual learning curve", we propose to introduce the terms "surgeon's individual training phase", and "clinic's learning curve".

Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling

International Nuclear Information System (INIS)

Kahouli, Sondes

2011-01-01

This paper studies the effects of returns to scale, technological learning, i.e. learning-by-doing and learning-by-searching, and uranium price on the prospects of nuclear cost decrease. We use an extended learning curve specification, named multiple factors learning curve (MFLC). In a first stage, we estimate a single MFLC. In a second stage, we estimate the MFLC under the framework of simultaneous system of equations which takes into account the uranium supply and demand. This permits not only to enhance the reliability of the estimation by incorporating the uranium price formation mechanisms in the MFLC via the price variable, but also to give preliminary insights about uranium supply and demand behaviors and the associated effects on the nuclear expansion. Results point out that the nuclear cost has important prospects for decrease via capacity expansion, i.e. learning-by-doing effects. In contrast, they show that the learning-by-searching as well as the scale effects have a limited effect on the cost decrease prospects. Conversely, results also show that uranium price exerts a positive and significant effect on nuclear cost, implying that when the uranium price increases, the nuclear power generation cost decreases. Since uranium is characterized by important physical availability, and since it represents only a minor part in the total nuclear cost, we consider that in a context of increasing demand for nuclear energy the latter result can be explained by the fact that the positive learning effects on the cost of nuclear act in a way to dissipate the negative ones that an increase in uranium price may exert. Further, results give evidence of important inertia in the supply and demand sides as well as evidence of slow correlation between the uranium market and oil market which may limit the inter-fuels substituability effects, that is, nuclear capacity expansion and associated learning-by-doing benefits. - Highlights: → We study the prospects of nuclear cost

Provincial carbon intensity abatement potential estimation in China: A PSO–GA-optimized multi-factor environmental learning curve method

International Nuclear Information System (INIS)

Yu, Shiwei; Zhang, Junjie; Zheng, Shuhong; Sun, Han

2015-01-01

This study aims to estimate carbon intensity abatement potential in China at the regional level by proposing a particle swarm optimization–genetic algorithm (PSO–GA) multivariate environmental learning curve estimation method. The model uses two independent variables, namely, per capita gross domestic product (GDP) and the proportion of the tertiary industry in GDP, to construct carbon intensity learning curves (CILCs), i.e., CO 2 emissions per unit of GDP, of 30 provinces in China. Instead of the traditional ordinary least squares (OLS) method, a PSO–GA intelligent optimization algorithm is used to optimize the coefficients of a learning curve. The carbon intensity abatement potentials of the 30 Chinese provinces are estimated via PSO–GA under the business-as-usual scenario. The estimation reveals the following results. (1) For most provinces, the abatement potentials from improving a unit of the proportion of the tertiary industry in GDP are higher than the potentials from raising a unit of per capita GDP. (2) The average potential of the 30 provinces in 2020 will be 37.6% based on the emission's level of 2005. The potentials of Jiangsu, Tianjin, Shandong, Beijing, and Heilongjiang are over 60%. Ningxia is the only province without intensity abatement potential. (3) The total carbon intensity in China weighted by the GDP shares of the 30 provinces will decline by 39.4% in 2020 compared with that in 2005. This intensity cannot achieve the 40%–45% carbon intensity reduction target set by the Chinese government. Additional mitigation policies should be developed to uncover the potentials of Ningxia and Inner Mongolia. In addition, the simulation accuracy of the CILCs optimized by PSO–GA is higher than that of the CILCs optimized by the traditional OLS method. - Highlights: • A PSO–GA-optimized multi-factor environmental learning curve method is proposed. • The carbon intensity abatement potentials of the 30 Chinese provinces are estimated by

Simultaneous development of laparoscopy and robotics provides acceptable perioperative outcomes and shows robotics to have a faster learning curve and to be overall faster in rectal cancer surgery: analysis of novice MIS surgeon learning curves.

Science.gov (United States)

Melich, George; Hong, Young Ki; Kim, Jieun; Hur, Hyuk; Baik, Seung Hyuk; Kim, Nam Kyu; Sender Liberman, A; Min, Byung Soh

2015-03-01

Laparoscopy offers some evidence of benefit compared to open rectal surgery. Robotic rectal surgery is evolving into an accepted approach. The objective was to analyze and compare laparoscopic and robotic rectal surgery learning curves with respect to operative times and perioperative outcomes for a novice minimally invasive colorectal surgeon. One hundred and six laparoscopic and 92 robotic LAR rectal surgery cases were analyzed. All surgeries were performed by a surgeon who was primarily trained in open rectal surgery. Patient characteristics and perioperative outcomes were analyzed. Operative time and CUSUM plots were used for evaluating the learning curve for laparoscopic versus robotic LAR. Laparoscopic versus robotic LAR outcomes feature initial group operative times of 308 (291-325) min versus 397 (373-420) min and last group times of 220 (212-229) min versus 204 (196-211) min-reversed in favor of robotics; major complications of 4.7 versus 6.5 % (NS), resection margin involvement of 2.8 versus 4.4 % (NS), conversion rate of 3.8 versus 1.1 (NS), lymph node harvest of 16.3 versus 17.2 (NS), and estimated blood loss of 231 versus 201 cc (NS). Due to faster learning curves for extracorporeal phase and total mesorectal excision phase, the robotic surgery was observed to be faster than laparoscopic surgery after the initial 41 cases. CUSUM plots demonstrate acceptable perioperative surgical outcomes from the beginning of the study. Initial robotic operative times improved with practice rapidly and eventually became faster than those for laparoscopy. Developing both laparoscopic and robotic skills simultaneously can provide acceptable perioperative outcomes in rectal surgery. It might be suggested that in the current milieu of clashing interests between evolving technology and economic constrains, there might be advantages in embracing both approaches.

Assessing the impact of windfarms - the learning curve in Cornwall

International Nuclear Information System (INIS)

Hull, A.

1998-01-01

This paper uses windfarm application decisions in Cornwall between 1989 and 1995 to illustrate the learning curve of planners in assessing appropriate windfarm locations, and in particular how the process of knowledge construction is constantly reviewed and modified in the light of experience and circumstance. One of the accepted purposes of Environmental Impact Assessment is to predict the possible effects, both beneficial and adverse, of the development on the environment. In practice what is beneficial and what is adverse can be a matter of dispute. The paper draws out the role of the planning system in assessing what is problematic or benign, and the practical strategies and procedures used to assess and control the environmental impacts of wind energy schemes. (Author)

Total hip arthroplasty by the direct anterior approach using a neck-preserving stem: Safety, efficacy and learning curve

Directory of Open Access Journals (Sweden)

Aditya Khemka

2018-01-01

Full Text Available Background: The concept of femoral neck preservation in total hip replacement (THR was introduced in 1993. It is postulated that retaining cortical bone of the femoral neck offers triplanar stability, uniform stress distribution, and accommodates physiological anteversion. However, data on safety, efficacy and learning curve are lacking. Materials and Methods: We prospectively assessed all patients who were operated for a THR with a short neck preserving stem (MiniHip between 2012 and 2014. The safety and learning curve were assessed by recording operative time; stem size; and adverse events including periprosthetic fracture; paresthesia; and limb length discrepancy (LLD. The cohort was divided into equal groups to assess the learning curve effect, and the cumulative sums (CUSUM test was performed to monitor intraoperative neck fractures. For assessment of efficacy, Oxford Hip Score (OHS and Short Form-36 (SF-36 scores were compared preoperatively and postoperatively. Results: 138 patients with median age 62 years (range 35–82 years were included with a median followup of 42 months (range 30–56 months. The minimum followup was 2.5 years. The OHS, SF-36 (physical and mental component scores improved by a mean score of 26, 28, and 27 points, respectively. All patients had LLD of <10 mm (1.9 mm ± 1.3. Adverse events included intraoperative neck fracture (n = 6, subsidence (n = 1, periprosthetic fracture (n = 1, paresthesia (n = 12, and trochanteric bursitis (n = 2. After early modification of the technique to use a smaller finishing broach, the CUSUM test demonstrated acceptable intraoperative neck fracture risk. The second surgery group had a reduced risk of intraoperative neck fracture (5/69 vs. 1/69 P = 0.2, reduced operative time (66 vs. 61 min, P = 0.06, and increased stem size (5 vs. 6, P = 0.09 although these differences were not statistically significant. Conclusions: The MiniHip stem is safe alternative to standard THR with good

Using a high-fidelity patient simulator with first-year medical students to facilitate learning of cardiovascular function curves.

Science.gov (United States)

Harris, David M; Ryan, Kathleen; Rabuck, Cynthia

2012-09-01

Students are relying on technology for learning more than ever, and educators need to adapt to facilitate student learning. High-fidelity patient simulators (HFPS) are usually reserved for the clinical years of medical education and are geared to improve clinical decision skills, teamwork, and patient safety. Finding ways to incorporate HFPS into preclinical medical education represents more of a challenge, and there is limited literature regarding its implementation. The main objective of this study was to implement a HFPS activity into a problem-based curriculum to enhance the learning of basic sciences. More specifically, the focus was to aid in student learning of cardiovascular function curves and help students develop heart failure treatment strategies based on basic cardiovascular physiology concepts. Pretests and posttests, along with student surveys, were used to determine student knowledge and perception of learning in two first-year medical school classes. There was an increase of 21% and 22% in the percentage of students achieving correct answers on a posttest compared with their pretest score. The median number of correct questions increased from pretest scores of 2 and 2.5 to posttest scores of 4 and 5 of a possible total of 6 in each respective year. Student survey data showed agreement that the activity aided in learning. This study suggests that a HFPS activity can be implemented during the preclinical years of medical education to address basic science concepts. Additionally, it suggests that student learning of cardiovascular function curves and heart failure strategies are facilitated.

Education Isn’t Education: The Creativity Response or How to Improve the Learning Curve in Our Society

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Stefan Brunnhuber

2017-06-01

Full Text Available Despite rising expenditure and general enrolment rates on a global level, educational output is stagnating, if not declining. There is increasing empirical evidence that we need a completely different approach to enhancing the learning curve; this holds true for early childhood, primary education, secondary education and higher education. Most existing educational programs do not tap into the full creative potential of our minds and our brains and often lead to suboptimal outcomes both for the individual and for society as a whole. Findings in clinical psychology, neurobiology and social psychology are not sufficiently considered when setting up appropriate educational programs. It is not the cognitive part of the curriculum that makes a difference, but rather the non-cognitive features (including stress management, impulse control, self-regulation, emotional attachment etc. that improve creativity. A ‘six-pack’ of features, including exercise, nutrition, social contact, mindfulness-based practices, sleeping well, and multi-sensory learning, is introduced as part of a ‘creativity response’. They are simple, affordable, evidence-based and efficient strategies that can be implemented promptly without additional costs, increasing our learning curve.

Balloon dilation of the eustachian tube in a cadaver model: technical considerations, learning curve, and potential barriers.

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McCoul, Edward D; Singh, Ameet; Anand, Vijay K; Tabaee, Abtin

2012-04-01

The surgical management options for eustachian tube dysfunction have historically been limited. The goal of the current study was to evaluate the technical considerations, learning curve, and potential barriers for balloon dilation of the eustachian tube (BDET) as an alternative treatment modality. Prospective preclinical trial of BDET in a cadaver model. A novel balloon catheter device was used for eustachian tube dilation. Twenty-four BDET procedures were performed by three independent rhinologists with no prior experience with the procedure (eight procedures per surgeon). The duration and number of attempts of the individual steps and overall procedure were recorded. Endoscopic examination of the eustachian tube was performed after each procedure, and the surgeon was asked to rate the subjective difficulty on a five-point scale. Successful completion of the procedure occurred in each case. The overall mean duration of the procedure was 284 seconds, and a mean number of 1.15 attempts were necessary to perform the individual steps. The mean subjective procedure difficulty was noted as somewhat easy. Statistically shorter duration and subjectively easier procedure were noted in the second compared to the first half of the series, indicating a favorable learning curve. Linear fissuring within the eustachian tube lumen without submucosal disruption (nine procedures, 37%) and with submucosal disruption (five procedures, 21%) were noted. The significance of these physical findings is unclear. Preclinical testing of BDET is associated with favorable duration, learning curve, and overall ease of completion. Clinical trials are necessary to evaluate safety and efficacy. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

LHC Run 2 – reaching the top of the learning curve

CERN Multimedia

2015-01-01

As the LHC Physics conference gets underway in St Petersburg, it’s a good time to take stock of where things stand with Run 2.    For all those involved with operating the LHC and its experiments in this new energy and intensity regime, 2015 was always going to be a learning curve. And learning we most certainly are. The main objective for this year has always been to set up the machine and experiments for production running at high energy and high intensity in 2016, 17 and 18.  That said, the experiments have all been able to collect quality data at 13 TeV, with the first Run 2 papers and conference presentations being written and delivered this summer. It would be unfair of me, however, to give the impression that it’s all been plain sailing. As well as the highs: smooth recommissioning of the machine, physics getting underway, and a successful transition to 25-nanosecond bunch spacing, we’ve also had our fair share of lows. There have been no sho...

Uniportal video-assisted thoracoscopic surgery: safety, efficacy and learning curve during the first 250 cases in Quebec, Canada.

Science.gov (United States)

Drevet, Gabrielle; Ugalde Figueroa, Paula

2016-03-01

Video-assisted thoracoscopic surgery (VATS) using a single incision (uniportal) may result in better pain control, earlier mobilization and shorter hospital stays. Here, we review the safety and efficiency of our initial experience with uniportal VATS and evaluate our learning curve. We conducted a retrospective review of uniportal VATS using a prospectively maintained departmental database and analyzed patients who had undergone a lung anatomic resection separately from patients who underwent other resections. To assess the learning curve, we compared the first 10 months of the study period with the second 10 months. From January 2014 to August 2015, 250 patients underwent intended uniportal VATS, including 180 lung anatomic resections (72%) and 70 other resections (28%). Lung anatomic resection was successfully completed using uniportal VATS in 153 patients (85%), which comprised all the anatomic segmentectomies (29 patients), 80% (4 of 5) of the pneumonectomies and 82% (120 of 146) of the lobectomies attempted. The majority of lung anatomic resections that required conversion to thoracotomy occurred in the first half of our study period. Seventy patients underwent other uniportal VATS resections. Wedge resections were the most common of these procedures (25 patients, 35.7%). Although 24 of the 70 patients (34%) required the placement of additional ports, none required conversion to thoracotomy. Uniportal VATS was safe and feasible for both standard and complex pulmonary resections. However, when used for pulmonary anatomic resections, uniportal VATS entails a steep learning curve.

Single-centre experience of retroperitoneoscopic approach in urology with tips to overcome the steep learning curve

Directory of Open Access Journals (Sweden)

Aneesh Srivastava

2016-01-01

Full Text Available Context: The retroperitoneoscopic or retroperitoneal (RP surgical approach has not become as popular as the transperitoneal (TP one due to the steeper learning curve. Aims: Our single-institution experience focuses on the feasibility, advantages and complications of retroperitoneoscopic surgeries (RS performed over the past 10 years. Tips and tricks have been discussed to overcome the steep learning curve and these are emphasised. Settings and Design: This study made a retrospective analysis of computerised hospital data of patients who underwent RP urological procedures from 2003 to 2013 at a tertiary care centre. Patients and Methods: Between 2003 and 2013, 314 cases of RS were performed for various urological procedures. We analysed the operative time, peri-operative complications, time to return of bowel sound, length of hospital stay, and advantages and difficulties involved. Post-operative complications were stratified into five grades using modified Clavien classification (MCC. Results: RS were successfully completed in 95.5% of patients, with 4% of the procedures electively performed by the combined approach (both RP and TP; 3.2% required open conversion and 1.3% were converted to the TP approach. The most common cause for conversion was bleeding. Mean hospital stay was 3.2 ± 1.2 days and the mean time for returning of bowel sounds was 16.5 ± 5.4 h. Of the patients, 1.4% required peri-operative blood transfusion. A total of 16 patients (5% had post-operative complications and the majority were grades I and II as per MCC. The rates of intra-operative and post-operative complications depended on the difficulty of the procedure, but the complications diminished over the years with the increasing experience of surgeons. Conclusion: Retroperitoneoscopy has proven an excellent approach, with certain advantages. The tips and tricks that have been provided and emphasised should definitely help to minimise the steep learning curve.

The learning curve for narrow-band imaging in the diagnosis of precancerous gastric lesions by using Web-based video.

Science.gov (United States)

Dias-Silva, Diogo; Pimentel-Nunes, Pedro; Magalhães, Joana; Magalhães, Ricardo; Veloso, Nuno; Ferreira, Carlos; Figueiredo, Pedro; Moutinho, Pedro; Dinis-Ribeiro, Mário

2014-06-01

A simplified narrow-band imaging (NBI) endoscopy classification of gastric precancerous and cancerous lesions was derived and validated in a multicenter study. This classification comes with the need for dissemination through adequate training. To address the learning curve of this classification by endoscopists with differing expertise and to assess the feasibility of a YouTube-based learning program to disseminate it. Prospective study. Five centers. Six gastroenterologists (3 trainees, 3 fully trained endoscopists [FTs]). Twenty tests provided through a Web-based program containing 10 randomly ordered NBI videos of gastric mucosa were taken. Feedback was sent 7 days after every test submission. Measures of accuracy of the NBI classification throughout the time. From the first to the last 50 videos, a learning curve was observed with a 10% increase in global accuracy, for both trainees (from 64% to 74%) and FTs (from 56% to 65%). After 200 videos, sensitivity and specificity of 80% and higher for intestinal metaplasia were observed in half the participants, and a specificity for dysplasia greater than 95%, along with a relevant likelihood ratio for a positive result of 7 to 28 and likelihood ratio for a negative result of 0.21 to 0.82, were achieved by all of the participants. No constant learning curve was observed for the identification of Helicobacter pylori gastritis and sensitivity to dysplasia. The trainees had better results in all of the parameters, except specificity for dysplasia, compared with the FTs. Globally, participants agreed that the program's structure was adequate, except on the feedback, which should have consisted of a more detailed explanation of each answer. No formal sample size estimate. A Web-based learning program could be used to teach and disseminate classifications in the endoscopy field. In this study, an NBI classification for gastric mucosal features seems to be easily learned for the identification of gastric preneoplastic

Using learning curves on energy-efficient technologies to estimate future energy savings and emission reduction potentials in the U.S. iron and steel industry

Energy Technology Data Exchange (ETDEWEB)

Karali, Nihan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Park, Won Young [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McNeil, Michael A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-06-18

Increasing concerns on non-sustainable energy use and climate change spur a growing research interest in energy efficiency potentials in various critical areas such as industrial production. This paper focuses on learning curve aspects of energy efficiency measures in the U.S iron and steel sector. A number of early-stage efficient technologies (i.e., emerging or demonstration technologies) are technically feasible and have the potential to make a significant contribution to energy saving and CO₂ emissions reduction, but fall short economically to be included. However, they may also have the cost effective potential for significant cost reduction and/or performance improvement in the future under learning effects such as ‘learning-by-doing’. The investigation is carried out using ISEEM, a technology oriented, linear optimization model. We investigated how steel demand is balanced with/without the availability learning curve, compared to a Reference scenario. The retrofit (or investment in some cases) costs of energy efficient technologies decline in the scenario where learning curve is applied. The analysis also addresses market penetration of energy efficient technologies, energy saving, and CO₂ emissions in the U.S. iron and steel sector with/without learning impact. Accordingly, the study helps those who use energy models better manage the price barriers preventing unrealistic diffusion of energy-efficiency technologies, better understand the market and learning system involved, predict future achievable learning rates more accurately, and project future savings via energy-efficiency technologies with presence of learning. We conclude from our analysis that, most of the existing energy efficiency technologies that are currently used in the U.S. iron and steel sector are cost effective. Penetration levels increases through the years, even though there is no price reduction. However, demonstration technologies are not economically

Training anesthesiology residents in providing anesthesia for awake craniotomy: learning curves and estimate of needed case load.

Science.gov (United States)

Bilotta, Federico; Titi, Luca; Lanni, Fabiana; Stazi, Elisabetta; Rosa, Giovanni

2013-08-01

To measure the learning curves of residents in anesthesiology in providing anesthesia for awake craniotomy, and to estimate the case load needed to achieve a "good-excellent" level of competence. Prospective study. Operating room of a university hospital. 7 volunteer residents in anesthesiology. Residents underwent a dedicated training program of clinical characteristics of anesthesia for awake craniotomy. The program was divided into three tasks: local anesthesia, sedation-analgesia, and intraoperative hemodynamic management. The learning curve for each resident for each task was recorded over 10 procedures. Quantitative assessment of the individual's ability was based on the resident's self-assessment score and the attending anesthesiologist's judgment, and rated by modified 12 mm Likert scale, reported ability score visual analog scale (VAS). This ability VAS score ranged from 1 to 12 (ie, very poor, mild, moderate, sufficient, good, excellent). The number of requests for advice also was recorded (ie, resident requests for practical help and theoretical notions to accomplish the procedures). Each task had a specific learning rate; the number of procedures necessary to achieve "good-excellent" ability with confidence, as determined by the recorded results, were 10 procedures for local anesthesia, 15 to 25 procedures for sedation-analgesia, and 20 to 30 procedures for intraoperative hemodynamic management. Awake craniotomy is an approach used increasingly in neuroanesthesia. A dedicated training program based on learning specific tasks and building confidence with essential features provides "good-excellent" ability. © 2013 Elsevier Inc. All rights reserved.

Colorectal endoscopic submucosal dissection (ESD) in the West - when can satisfactory results be obtained? A single-operator learning curve analysis.

Science.gov (United States)

Spychalski, Michał; Skulimowski, Aleksander; Dziki, Adam; Saito, Yutaka

2017-12-01

Up to date we lack a detailed description of the colorectal endoscopic submucosal dissection (ESD) learning curve, that would represent the experience of the Western center. The aim of this study was to define the critical points of the learning curve and to draw up lesions qualification guidelines tailored to the endoscopists experience. We have carried out a single center prospective study. Between June 2013 and December 2016, 228 primary colorectal lesions were managed by ESD procedure. In order to create a learning curve model and to carry out the analysis the cases were divided into six periods, each consisting of 38 cases. The overall en bloc resection rate was 79.39%. The lowest en bloc resection rate (52.36%) was observed in the first period. After completing 76 procedures, the resection rate surged to 86% and it was accompanied by the significant increase in the mean procedure speed of ≥9 cm 2 /h. Lesions localization and diameter had a signification impact on the outcomes. After 76 procedures, en bloc resection rate of 90.9 and 90.67% were achieved for the left side of colon and rectum, respectively. In the right side of colon statistically significant lower resection rate of 67.57% was observed. We have proved that in the setting of the Western center, colorectal ESD can yield excellent results. It seems that the key to the success during the learning period is 'tailoring' lesions qualification guidelines to the experience of the endoscopist, as lesions diameter and localization highly influence the outcomes.

Laparoscopy Instructional Videos: The Effect of Preoperative Compared With Intraoperative Use on Learning Curves.

Science.gov (United States)

Broekema, Theo H; Talsma, Aaldert K; Wevers, Kevin P; Pierie, Jean-Pierre E N

Previous studies have shown that the use of intraoperative instructional videos has a positive effect on learning laparoscopic procedures. This study investigated the effect of the timing of the instructional videos on learning curves in laparoscopic skills training. After completing a basic skills course on a virtual reality simulator, medical students and residents with less than 1 hour experience using laparoscopic instruments were randomized into 2 groups. Using an instructional video either preoperatively or intraoperatively, both groups then performed 4 repetitions of a standardized task on the TrEndo augmented reality. With the TrEndo, 9 motion analysis parameters (MAPs) were recorded for each session (4 MAPs for each hand and time). These were the primary outcome measurements for performance. The time spent watching the instructional video was also recorded. Improvement in performance was studied within and between groups. Medical Center Leeuwarden, a secondary care hospital located in Leeuwarden, The Netherlands. Right-hand dominant medical student and residents with more than 1 hour experience operating any kind of laparoscopic instruments were participated. A total of 23 persons entered the study, of which 21 completed the study course. In both groups, at least 5 of 9 MAPs showed significant improvements between repetition 1 and 4. When both groups were compared after completion of repetition 4, no significant differences in improvement were detected. The intraoperative group showed significant improvement in 3 MAPs of the left-nondominant-hand, compared with one MAP for the preoperative group. No significant differences in learning curves could be detected between the subjects who used intraoperative instructional videos and those who used preoperative instructional videos. Intraoperative video instruction may result in improved dexterity of the nondominant hand. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc

Adolescent Idiopathic Scoliosis Surgery by a Neurosurgeon: Learning Curve for Neurosurgeons.

Science.gov (United States)

Hyun, Seung-Jae; Han, Sanghyun; Kim, Ki-Jeong; Jahng, Tae-Ahn; Kim, Yongjung J; Rhim, Seung-Chul; Kim, Hyun-Jib

2018-02-01

To determine a neurosurgeon's learning curve of surgical treatment for adolescent idiopathic scoliosis (AIS) patients. This study is a retrospective analysis. Forty-six patients were treated by a single neurosurgeon between 2011 and 2017 using posterior segmental instrumentation and fusion. According to the time period, the former and latter 23 patients were divided into group 1 and group 2, respectively. Patients' demographic data, curve magnitude, number of levels treated, amount of correction achieved, radiographic/clinical outcomes, and complications were compared between the groups. The majority were females (34 vs. 12) with average ages of 15.0 versus 15.6, respectively. The mean follow-up period was 24.6 months. The average number of fusion levels was similar with 10.3 and 11.5 vertebral bodies in groups 1 and 2, respectively. The average Cobb angle of major curvature was 59.8° and 58.5° in groups 1 and 2, respectively. There observed significant reductions of operative time (324.4 vs. 224.7 minutes, P = 0.007) and estimated blood loss (648.3 vs. 438.0 mL, P = 0.027) in group 2. The correction rate of the major structural curve was greater in group 2 (70.7% vs. 81.0%, P = 0.001). There was no case of neurologic deficit, infection, and revision for screw malposition. One patient of group 1 underwent fusion extension surgery for shoulder asymmetry. Radiographic and clinical outcomes of AIS patients treated by a neurosurgeon were acceptable. AIS surgery may be performed with an acceptable rate of complications after about 20 surgeries. With acquisition of surgical experiences, neurosurgeons could perform deformity surgery for AIS effectively and safely. Copyright © 2017 Elsevier Inc. All rights reserved.

Deep-learnt classification of light curves

DEFF Research Database (Denmark)

Mahabal, Ashish; Gieseke, Fabian; Pai, Akshay Sadananda Uppinakudru

2017-01-01

is to derive statistical features from the time series and to use machine learning methods, generally supervised, to separate objects into a few of the standard classes. In this work, we transform the time series to two-dimensional light curve representations in order to classify them using modern deep......Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and techniques to classify light curves. A common approach...... learning techniques. In particular, we show that convolutional neural networks based classifiers work well for broad characterization and classification. We use labeled datasets of periodic variables from CRTS survey and show how this opens doors for a quick classification of diverse classes with several...

PV experience curves for the Netherlands

International Nuclear Information System (INIS)

Gerwig, R.

2005-01-01

Experience curves are one of several tools used by policy makers to take a look at market development. Numerous curves have been constructed for PV but none specific to the Netherlands. The objective of this report is to take a look at the price development of grid-connected PV systems in the Netherlands using the experience curve theory. After a literature and internet search and attempts to acquire information from PV companies information on 51% of the totally installed capacity was found. Curves for the period 1991-2001 were constructed based on system price, BOS (balance-of-system) price and inverter price. The progress ratio of the locally learning BOS was similar to the globally learning module market. This indicates that the pace of development of the Dutch PV market is similar to the globally followed pace. Improvement of the detail of the data might help to get a better idea of which BOS components have declined most. The similar progress ratio also shows the importance of investing both in module and system research as is the case in the Netherlands

Diffusion of robotics into clinical practice in the United States: process, patient safety, learning curves, and the public health.

Science.gov (United States)

Mirheydar, Hossein S; Parsons, J Kellogg

2013-06-01

Robotic technology disseminated into urological practice without robust comparative effectiveness data. To review the diffusion of robotic surgery into urological practice. We performed a comprehensive literature review focusing on diffusion patterns, patient safety, learning curves, and comparative costs for robotic radical prostatectomy, partial nephrectomy, and radical cystectomy. Robotic urologic surgery diffused in patterns typical of novel technology spreading among practicing surgeons. Robust evidence-based data comparing outcomes of robotic to open surgery were sparse. Although initial Level 3 evidence for robotic prostatectomy observed complication outcomes similar to open prostatectomy, subsequent population-based Level 2 evidence noted an increased prevalence of adverse patient safety events and genitourinary complications among robotic patients during the early years of diffusion. Level 2 evidence indicated comparable to improved patient safety outcomes for robotic compared to open partial nephrectomy and cystectomy. Learning curve recommendations for robotic urologic surgery have drawn exclusively on Level 4 evidence and subjective, non-validated metrics. The minimum number of cases required to achieve competency for robotic prostatectomy has increased to unrealistically high levels. Most comparative cost-analyses have demonstrated that robotic surgery is significantly more expensive than open or laparoscopic surgery. Evidence-based data are limited but suggest an increased prevalence of adverse patient safety events for robotic prostatectomy early in the national diffusion period. Learning curves for robotic urologic surgery are subjective and based on non-validated metrics. The urological community should develop rigorous, evidence-based processes by which future technological innovations may diffuse in an organized and safe manner.

Contrast agents provide a faster learning curve in dipyridamole stress echocardiography.

Science.gov (United States)

Zamorano, Jose; Sánchez, Violeta; Moreno, Raúl; Almería, Carlos; Rodrigo, Jose; Serra, Viviana; Azcona, Luis; Aubele, Adalia; Mataix, Luis; Sánchez-Harguindey, Luis

2002-12-01

Interobserver variability is an important limitation of the stress echocardiography and depends on the echocardiographer training. Our aim was to evaluate if the use of contrast agents during dipyridamole stress echocardiography would improve the agreement between an experienced and a non-experienced observer in stress echo and therefore if contrast would affect the learning period of dypyridamole stress echo. Two independent observers without knowledge of any patient data interpreted all stress studies. One observer was an experienced one and the other had experience in echocardiography but not in stress echo. Two observers analysed 87 non-selected and consecutive studies. Out of the 87 studies, 46 were performed without contrast administration, whereas i.v. contrast (2.5 g Levovist by two bolus at rest and at peak stress) was administered in 41. In all cases, second harmonic imaging and stress digitalisation pack was used. The agreement between observers showed a kappa index of 0.58 and 0.83 without and with contrast administration, respectively. The use of contrast agents provides a better agreement in the evaluation of stress echo between an experienced and a non-experienced observer in stress echo. Adding routinely contrast agents could probably reduce the number of exams required for the necessary learning curve in stress echocardiography.

The learning curve of the three-port two-instrument complete thoracoscopic lobectomy for lung cancer—A feasible technique worthy of popularization

Directory of Open Access Journals (Sweden)

Yu-Jen Cheng

2015-07-01

Conclusion: Three-port complete thoracoscopic lobectomy with the two-instrument technique is feasible for lung cancer treatment. The length of the learning curve consisted of 28 cases. This TPTI technique should be popularized.

Development Process and Technical Aspects of Laparoscopic Hepatectomy: Learning Curve Based on 15 Years of Experience.

Science.gov (United States)

Komatsu, Shohei; Scatton, Olivier; Goumard, Claire; Sepulveda, Ailton; Brustia, Raffaele; Perdigao, Fabiano; Soubrane, Olivier

2017-05-01

Laparoscopic hepatectomy continues to be a challenging operation associated with a steep learning curve. This study aimed to evaluate the learning process during 15 years of experience with laparoscopic hepatectomy and to identify approaches to standardization of this procedure. Prospectively collected data of 317 consecutive laparoscopic hepatectomies performed from January 2000 to December 2014 were reviewed retrospectively. The operative procedures were classified into 4 categories (minor hepatectomy, left lateral sectionectomy [LLS], left hepatectomy, and right hepatectomy), and indications were classified into 5 categories (benign-borderline tumor, living donor, metastatic liver tumor, biliary malignancy, and hepatocellular carcinoma). During the first 10 years, the procedures were limited mainly to minor hepatectomy and LLS, and the indications were limited to benign-borderline tumor and living donor. Implementation of major hepatectomy rapidly increased the proportion of malignant tumors, especially hepatocellular carcinoma, starting from 2011. Conversion rates decreased with experience for LLS (13.3% vs 3.4%; p = 0.054) and left hepatectomy (50.0% vs 15.0%; p = 0.012), but not for right hepatectomy (41.4% vs 35.7%; p = 0.661). Our 15-year experience clearly demonstrates the stepwise procedural evolution from LLS through left hepatectomy to right hepatectomy, as well as the trend in indications from benign-borderline tumor/living donor to malignant tumors. In contrast to LLS and left hepatectomy, a learning curve was not observed for right hepatectomy. The ongoing development process can contribute to faster standardization necessary for future advances in laparoscopic hepatectomy. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Experience Curves: A Tool for Energy Policy Assessment

Energy Technology Data Exchange (ETDEWEB)

Neij, Lena; Helby, Peter [Lund Univ. (Sweden). Environmental and Energy Systems Studies; Dannemand Andersen, Per; Morthorst, Poul Erik [Riso National Laboratory, Roskilde (Denmark); Durstewitz, Michael; Hoppe-Kilpper, Martin [Inst. fuer Solare Energieversorgungstechnik e.V., Kassel (DE); and others

2003-07-01

The objective of the project, Experience curves: a tool for energy policy assessment (EXTOOL), was to analyse the experience curve as a tool for the assessment of energy policy measures. This is of special interest, since the use of experience curves for the assessment of energy policy measures requires the development of the established experience curve methodology. This development raises several questions which have been addressed and analysed in this project. The analysis is based on case studies of wind power, an area with considerable experience in technology development, deployment and policy measures. Therefore, a case study based on wind power provides a good opportunity to study the usefulness of experience curves as a tool for the assessment of energy policy measures. However, the results are discussed in terms of using experience curves for the assessment of any energy technology. The project shows that experience curves can be used to assess the effect of combined policy measures in terms of cost reductions. Moreover, the result of the project show that experience curves could be used to analyse international 'learning systems', i.e. cost reductions brought about by the development of wind power and policy measures used in other countries. Nevertheless, the use of experience curves for the assessment of policy programmes has several limitations. First, the analysis and assessment of policy programmes cannot be achieved unless relevant experience curves based on good data can be developed. The authors are of the opinion that only studies that provide evidence of the validity, reliability and relevance of experience curves should be taken into account in policy making. Second, experience curves provide an aggregated picture of the situation and more detailed analysis of various sources of cost reduction, and cost reductions resulting from individual policy measures, requires additional data and analysis tools. Third, we do not recommend the use of

A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs

International Nuclear Information System (INIS)

Smith, Sarah Josephine; Wei, Max; Sohn, Michael D.

2016-01-01

Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North American datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate. - Highlights: • We develop a segmented regression technique to estimate historical CFL learning curves. • CFL experience curves do not have a constant learning rate. • CFLs exhibited a learning rate of approximately 21% from 1990 to 1997. • The CFL learning rate significantly increased after 1998. • Increased CFL learning rate is correlated to technology deployment programs.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

Science.gov (United States)

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

Impact of cap-assisted colonoscopy on the learning curve and quality in colonoscopy: a randomized controlled trial.

Science.gov (United States)

Tang, Zhouwen; Zhang, Daniel S; Thrift, Aaron P; Patel, Kalpesh K

2018-03-01

Colonoscopy competency assessment in trainees traditionally has been informal. Comprehensive metrics such as the Assessment of Competency in Endoscopy (ACE) tool suggest that competency thresholds are higher than assumed. Cap-assisted colonoscopy (CAC) may improve competency, but data regarding novice trainees are lacking. We compared CAC versus standard colonoscopy (SC) performed by novice trainees in a randomized controlled trial. All colonoscopies performed by 3 gastroenterology fellows without prior experience were eligible for the study. Exclusion criteria included patient age 90 years, pregnancy, prior colon resection, diverticulitis, colon obstruction, severe hematochezia, referral for EMR, or a procedure done without patient sedation. Patients were randomized to either CAC or SC in a 1:1 fashion. The primary outcome was the independent cecal intubation rate (ICIR). Secondary outcomes were cecal intubation time, polyp detection rate, polyp miss rate, adenoma detection rate, ACE tool scores, and cumulative summation learning curves. A total of 203 colonoscopies were analyzed, 101 in CAC and 102 in SC. CAC resulted in a significantly higher cecal intubation rate, at 79.2% in CAC compared with 66.7% in SC (P = .04). Overall cecal intubation time was significantly shorter at 13.7 minutes for CAC versus 16.5 minutes for SC (P =.02). Cecal intubation time in the case of successful independent fellow intubation was not significantly different between CAC and SC (11.6 minutes vs 12.7 minutes; P = .29). Overall ACE tool motor and cognitive scores were higher with CAC. Learning curves for ICIR approached the competency threshold earlier with cap use but reached competency for only 1 fellow. The polyp detection rate, polyp miss rate, and adenoma detection rate were not significantly different between groups. CAC resulted in significant improvement in ICIR, overall ACE tool scores, and trend toward competency on learning curves when compared with SC in colonoscopy

Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

Energy Technology Data Exchange (ETDEWEB)

Harrison, T. J. [ORNL

2014-02-01

The cost of nuclear power is a straightforward yet complicated topic. It is straightforward in that the cost of nuclear power is a function of the cost to build the nuclear power plant, the cost to operate and maintain it, and the cost to provide fuel for it. It is complicated in that some of those costs are not necessarily known, introducing uncertainty into the analysis. For large light water reactor (LWR)-based nuclear power plants, the uncertainty is mainly contained within the cost of construction. The typical costs of operations and maintenance (O&M), as well as fuel, are well known based on the current fleet of LWRs. However, the last currently operating reactor to come online was Watts Bar 1 in May 1996; thus, the expected construction costs for gigawatt (GW)-class reactors in the United States are based on information nearly two decades old. Extrapolating construction, O&M, and fuel costs from GW-class LWRs to LWR-based small modular reactors (SMRs) introduces even more complication. The per-installed-kilowatt construction costs for SMRs are likely to be higher than those for the GW-class reactors based on the property of the economy of scale. Generally speaking, the economy of scale is the tendency for overall costs to increase slower than the overall production capacity. For power plants, this means that doubling the power production capacity would be expected to cost less than twice as much. Applying this property in the opposite direction, halving the power production capacity would be expected to cost more than half as much. This can potentially make the SMRs less competitive in the electricity market against the GW-class reactors, as well as against other power sources such as natural gas and subsidized renewables. One factor that can potentially aid the SMRs in achieving economic competitiveness is an economy of numbers, as opposed to the economy of scale, associated with learning curves. The basic concept of the learning curve is that the more a

The Impact of Learning Curve Model Selection and Criteria for Cost Estimation Accuracy in the DoD

Science.gov (United States)

2016-04-30

different in the future due to machines” • Heightened scrutiny of cost estimates • Budget Control Act of 2011 seeks to reduce federal deficit ...qÜáêíÉÉåíÜ=^ååì~ä= ^Åèìáëáíáçå=oÉëÉ~êÅÜ= póãéçëáìã= qÜìêëÇ~ó=pÉëëáçåë= sçäìãÉ=ff= = The Impact of Learning Curve Model Selection and Criteria for Cost...Assistant Division Director, Institute for Defense Analyses Bruce Harmon, Research Staff Member, Institute for Defense Analyses The Impact of Learning

Taking the brakes off the learning curve.

Science.gov (United States)

Gheysen, Freja; Lasne, Gabriel; Pélégrini-Issac, Mélanie; Albouy, Genevieve; Meunier, Sabine; Benali, Habib; Doyon, Julien; Popa, Traian

2017-03-01

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The learning curve to achieve satisfactory completion rates in upper GI endoscopy: an analysis of a national training database.

Science.gov (United States)

Ward, S T; Hancox, A; Mohammed, M A; Ismail, T; Griffiths, E A; Valori, R; Dunckley, P

2017-06-01

The aim of this study was to determine the number of OGDs (oesophago-gastro-duodenoscopies) trainees need to perform to acquire competency in terms of successful unassisted completion to the second part of the duodenum 95% of the time. OGD data were retrieved from the trainee e-portfolio developed by the Joint Advisory Group on GI Endoscopy (JAG) in the UK. All trainees were included unless they were known to have a baseline experience of >20 procedures or had submitted data for 90% trainees had attained a 95% completion rate. Total number of OGDs performed, trainee age and experience in lower GI endoscopy were factors independently associated with OGD completion. There are limited published data on the OGD learning curve. This is the largest study to date analysing the learning curve for competency acquisition. The JAG competency requirement for 200 procedures appears appropriate. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Evaluation of learning curves for ovariohysterectomy of dogs and cats and castration of dogs.

Science.gov (United States)

Freeman, Lynetta J; Ferguson, Nancy; Fellenstein, Carol; Johnson, Ron; Constable, Peter D

2017-08-01

OBJECTIVE To define learning curves for fourth-year veterinary students performing ovariohysterectomy procedures in dogs and cats and castration in dogs. DESIGN Retrospective study. SAMPLE 3,196 ovariohysterectomies or castrations performed in dogs and cats by 88 veterinary students during a spay-neuter surgery and animal shelter rotation (n = 3,056) or by 1 experienced general practitioner (n = 140). PROCEDURES Data collected from medical records included patient signalment, type and duration of procedure, and sequence (by date and time) of the procedure within a list of procedures of the same type generated for each student. For each procedure type, geometric mean surgery time and 95% confidence intervals were determined for each number of surgeries completed by ≥ 10 students. Median surgery times for the same procedure types were determined for the experienced practitioner. The learning curve for each procedure was modeled with nonlinear (3-factor exponential equation with a nonzero asymptote) and linear regression. For each procedure, the asymptote (optimal surgery time) for students was compared with the experienced practitioner's median surgery time. RESULTS 2,945 surgeries (mean, 33/student) performed by ≥ 10 students were analyzed. Surgery time decreased in a nonlinear manner as student experience increased for castration of adult or pediatric dogs and ovariohysterectomy of pediatric dogs and adult or pediatric cats. Surgery time decreased in a linear manner as experience increased for ovariohysterectomy of adult dogs. CONCLUSIONS AND CLINICAL RELEVANCE To the authors' knowledge, this was the first study to map surgery times for common surgical procedures consecutively performed by veterinary students. Results clearly indicated the value of repetition to improve surgical skills (as measured by surgery time) during a 3-week period.

Laparoscopic colorectal surgery in learning curve: Role of implementation of a standardized technique and recovery protocol. A cohort study

Science.gov (United States)

Luglio, Gaetano; De Palma, Giovanni Domenico; Tarquini, Rachele; Giglio, Mariano Cesare; Sollazzo, Viviana; Esposito, Emanuela; Spadarella, Emanuela; Peltrini, Roberto; Liccardo, Filomena; Bucci, Luigi

2015-01-01

Background Despite the proven benefits, laparoscopic colorectal surgery is still under utilized among surgeons. A steep learning is one of the causes of its limited adoption. Aim of the study is to determine the feasibility and morbidity rate after laparoscopic colorectal surgery in a single institution, “learning curve” experience, implementing a well standardized operative technique and recovery protocol. Methods The first 50 patients treated laparoscopically were included. All the procedures were performed by a trainee surgeon, supervised by a consultant surgeon, according to the principle of complete mesocolic excision with central vascular ligation or TME. Patients underwent a fast track recovery programme. Recovery parameters, short-term outcomes, morbidity and mortality have been assessed. Results Type of resections: 20 left side resections, 8 right side resections, 14 low anterior resection/TME, 5 total colectomy and IRA, 3 total panproctocolectomy and pouch. Mean operative time: 227 min; mean number of lymph-nodes: 18.7. Conversion rate: 8%. Mean time to flatus: 1.3 days; Mean time to solid stool: 2.3 days. Mean length of hospital stay: 7.2 days. Overall morbidity: 24%; major morbidity (Dindo–Clavien III): 4%. No anastomotic leak, no mortality, no 30-days readmission. Conclusion Proper laparoscopic colorectal surgery is safe and leads to excellent results in terms of recovery and short term outcomes, even in a learning curve setting. Key factors for better outcomes and shortening the learning curve seem to be the adoption of a standardized technique and training model along with the strict supervision of an expert colorectal surgeon. PMID:25859386

Effects of Pathologic Stage on the Learning Curve for Radical Prostatectomy: Evidence That Recurrence in Organ-Confined Cancer Is Largely Related to Inadequate Surgical Technique

Science.gov (United States)

Vickers, Andrew J.; Bianco, Fernando J.; Gonen, Mithat; Cronin, Angel M.; Eastham, James A.; Schrag, Deborah; Klein, Eric A.; Reuther, Alwyn M.; Kattan, Michael W.; Pontes, J. Edson; Scardino, Peter T.

2008-01-01

Objectives We previously demonstrated that there is a learning curve for open radical prostatectomy. We sought to determine whether the effects of the learning curve are modified by pathologic stage. Methods The study included 7765 eligible prostate cancer patients treated with open radical prostatectomy by one of 72 surgeons. Surgeon experience was coded as the total number of radical prostatectomies conducted by the surgeon prior to a patient’s surgery. Multivariable regression models of survival time were used to evaluate the association between surgeon experience and biochemical recurrence, with adjustment for PSA, stage, and grade. Analyses were conducted separately for patients with organ-confined and locally advanced disease. Results Five-year recurrence-free probability for patients with organ-confined disease approached 100% for the most experienced surgeons. Conversely, the learning curve for patients with locally advanced disease reached a plateau at approximately 70%, suggesting that about a third of these patients cannot be cured by surgery alone. Conclusions Excellent rates of cancer control for patients with organ-confined disease treated by the most experienced surgeons suggest that the primary reason such patients recur is inadequate surgical technique. PMID:18207316

The future role of photovoltaics: A learning curve versus portfolio perspective

International Nuclear Information System (INIS)

Albrecht, Johan

2007-01-01

The current cost disadvantage of photovoltaics (PV) risks to reduce its relevance in climate policy strategies. Depending on the used assumptions, electricity from PV can become competitive between 2015 and 2040. Cost competitiveness is, however, a conditional criterion and as an alternative to the learning curve perspective, the future role of PV in electricity production is assessed from a portfolio theory or Capital Asset Pricing Model perspective. In this analysis, the focus is on the input price risks. Fossil fuel price volatility can strongly reduce the financial return of conventional generating technologies. From a welfare perspective, energy planners should try to minimise this risk by adding risk-neutral or no-risk technologies to their portfolio. With an analysis for the year 2025, we illustrate how the addition of renewable capacity to an existing portfolio can lower total portfolio risk without a significant reduction of profitability. PV then emerges as an attractive technology, especially once the best locations for wind energy are already developed

The future role of photovoltaics: a learning curve versus portfolio perspective

International Nuclear Information System (INIS)

Albrecht, J.

2007-01-01

The current cost disadvantage of photovoltaics (PV) risks to reduce its relevance in climate policy strategies. Depending on the used assumptions, electricity from PV can become competitive between 2015 and 2040. Cost competitiveness is, however, a conditional criterion and as an alternative to the learning curve perspective, the future role of PV in electricity production is assessed from a portfolio theory or Capital Asset Pricing Model perspective. In this analysis, the focus is on the input price risks. Fossil fuel price volatility can strongly reduce the financial return of conventional generating technologies. From a welfare perspective, energy planners should try to minimise this risk by adding risk-neutral or no-risk technologies to their portfolio. With an analysis for the year 2025, we illustrate how the addition of renewable capacity to an existing portfolio can lower total portfolio risk without a significant reduction of profitability. PV then emerges as an attractive technology, especially once the best locations for wind energy are already developed. (author)

Learning from the Sun. Analysis of the use of experience curves for energy policy purposes. The case of photovoltaic power. Final report of the Photex project

International Nuclear Information System (INIS)

Schaeffer, G.J.; Seebregts, A.J.; Beurskens, L.W.M.; De Moor, H.H.C.; Alsema, E.; Sark, W.; Durstewicz, M.; Perrin, M.; Boulanger, P.; Laukamp, H.; Zuccaro, C.

2004-08-01

Since the 1990s energy policy scientists have started to explore the possibilities of using the experience curve approach for energy policy making. The concept of the experience curve is simple, at least in principle. It states that, for every doubling of cumulative produced capacity of a product or technology, the cost for making it declines with a fixed percentage (learning rate). Historical statistical analysis can be used to define this percentage. Extrapolating the trend thus found, into the future will then give relevant information about future cost developments and will also give information how much 'learning money' will be needed to get to the break-even point. The Photex project used the development of solar PV as a case to further explore this approach, and also to deduce lessons for PV policy. Other aims were to look at learning rates of the different components of PV-systems and to combine the experience curve analyses with bottom-up engineering studies. The main conclusion with regard to the use of experience curves for energy policy making is that this is an interesting approach, but that such an analysis should be done with much care. For the historical analysis the availability of reliable and firm data is essential. As cost data often are not available, price data could be used as a proxy, as long as sufficient long time ranges are used. Also, the analyst should take care he considers the right learning system boundaries. Furthermore the number of years to be included in the statistical analysis should at least be 10 years and this period sample should not over-represent stable price periods or periods of steep price decline. If possible, data uncertainties should be taken into account as well. An interesting finding was that, at least in the case of PV, the learning rate is not a constant, but can vary over time. In the case of PV it improved from 20% to 23%. Extrapolations into the future should take uncertainties into account and always be

The learning curve of laparoscopic treatment of rectal cancer does not increase morbidity.

Science.gov (United States)

Luján, Juan; Gonzalez, Antonio; Abrisqueta, Jesús; Hernandez, Quiteria; Valero, Graciela; Abellán, Israel; Frutos, María Dolores; Parrilla, Pascual

2014-01-01

The treatment of rectal cancer via laparoscopy is controversial due to its technical complexity. Several randomized prospective studies have demonstrated clear advantages for the patient with similar oncological results to those of open surgery, although during the learning of this surgical technique there may be an increase in complications and a worse prognosis. Our aim is to analyze how the learning curve for rectal cancer via laparoscopy influences intra- and postoperative results and oncological markers. A retrospective review was conducted of the first 120 patients undergoing laparoscopic surgery for rectal neoplasia. The operations were performed by the same surgical team with a wide experience in the treatment of open colorectal cancer and qualified to perform advanced laparoscopic surgery. We analyzed sex, ASA, tumour location, neoadjuvant treatment, surgical technique, operating time, conversion, postoperative complications, length of hospital stay, number of lymph nodes, stage and involvement of margins. Significant differences were observed with regard to surgical time (224 min in the first group, 204 min in the second group), with a higher rate of conversion in the first group (22.5%) than in the second (11.3%). No significant differences were noted for rate of conservative sphincter surgery, length of hospital stay, post-surgical complications, number of affected/isolated lymph nodes or affected circumferential and distal margins. It is possible to learn this complex surgical technique without compromising the patient's safety and oncological outcome. Copyright © 2013 AEC. Published by Elsevier Espana. All rights reserved.

A randomized control trial to evaluate the importance of pre-training basic laparoscopic psychomotor skills upon the learning curve of laparoscopic intra-corporeal knot tying.

Science.gov (United States)

Molinas, Carlos Roger; Binda, Maria Mercedes; Sisa, Cesar Manuel; Campo, Rudi

2017-01-01

Training of basic laparoscopic psychomotor skills improves the acquisition of more advanced laparoscopic tasks, such as laparoscopic intra-corporeal knot tying (LICK). This randomized controlled trial was designed to evaluate whether pre-training of basic skills, as laparoscopic camera navigation (LCN), hand-eye coordination (HEC), and bimanual coordination (BMC), and the combination of the three of them, has any beneficial effect upon the learning curve of LICK. The study was carried out in a private center in Asunción, Paraguay, by 80 medical students without any experience in surgery. Four laparoscopic tasks were performed in the ENCILAP model (LCN, HEC, BMC, and LICK). Participants were allocated to 5 groups (G1-G5). The study was structured in 5 phases. In phase 1, they underwent a base-line test ( T 1 ) for all tasks (1 repetition of each task in consecutive order). In phase 2, participants underwent different training programs (30 consecutive repetitions) for basic tasks according to the group they belong to (G1: none; G2: LCN; G3: HEC; G4: BMC; and G5: LCN, HEC, and BMC). In phase 3, they were tested again ( T 2 ) in the same manner than at T 1 . In phase 4, they underwent a standardized training program for LICK (30 consecutive repetitions). In phase 5, they were tested again ( T 3 ) in the same manner than at T 1 and T 2 . At each repetition, scoring was based on the time taken for task completion system. The scores were plotted and non-linear regression models were used to fit the learning curves to one- and two-phase exponential decay models for each participant (individual curves) and for each group (group curves). The LICK group learning curves fitted better to the two-phase exponential decay model. From these curves, the starting points ( Y 0), the point after HEC training/before LICK training ( Y 1), the Plateau, and the rate constants ( K ) were calculated. All groups, except for G4, started from a similar point ( Y 0). At Y 1, G5 scored already

From curve fitting to machine learning an illustrative guide to scientific data analysis and computational intelligence

CERN Document Server

Zielesny, Achim

2016-01-01

This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with M...

Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance.

Science.gov (United States)

Gaschler, Robert; Progscha, Johanna; Smallbone, Kieran; Ram, Nilam; Bilalić, Merim

2014-01-01

Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tournaments for at least 10 years. We analyze the performance development with the goal to test the adequacy of learning curves, and the skill acquisition theories they are based on, for describing and predicting expertise acquisition. On the one hand, we show that the skill acquisition theories implying a negative exponential learning curve do a better job in both describing early performance gains and predicting later trajectories of chess performance than those theories implying a power function learning curve. On the other hand, the learning curves of a large proportion of players show systematic qualitative deviations from the predictions of either type of skill acquisition theory. While skill acquisition theories predict larger performance gains in early years and smaller gains in later years, a substantial number of players begin to show substantial improvements with a delay of several years (and no improvement in the first years), deviations not fully accounted for by quantity of practice. The current work adds to the debate on how learning processes on a small time scale combine to large-scale changes.

Establishing the minimal number of virtual reality simulator training sessions necessary to develop basic laparoscopic skills competence: evaluation of the learning curve

Directory of Open Access Journals (Sweden)

Ricardo Jordao Duarte

2013-09-01

Full Text Available Introduction Medical literature is scarce on information to define a basic skills training program for laparoscopic surgery (peg and transferring, cutting, clipping. The aim of this study was to determine the minimal number of simulator sessions of basic laparoscopic tasks necessary to elaborate an optimal virtual reality training curriculum. Materials and Methods Eleven medical students with no previous laparoscopic experience were spontaneously enrolled. They were submitted to simulator training sessions starting at level 1 (Immersion Lap VR, San Jose, CA, including sequentially camera handling, peg and transfer, clipping and cutting. Each student trained twice a week until 10 sessions were completed. The score indexes were registered and analyzed. The total of errors of the evaluation sequences (camera, peg and transfer, clipping and cutting were computed and thereafter, they were correlated to the total of items evaluated in each step, resulting in a success percent ratio for each student for each set of each completed session. Thereafter, we computed the cumulative success rate in 10 sessions, obtaining an analysis of the learning process. By non-linear regression the learning curve was analyzed. Results By the non-linear regression method the learning curve was analyzed and a r2 = 0.73 (p < 0.001 was obtained, being necessary 4.26 (∼five sessions to reach the plateau of 80% of the estimated acquired knowledge, being that 100% of the students have reached this level of skills. From the fifth session till the 10th, the gain of knowledge was not significant, although some students reached 96% of the expected improvement. Conclusions This study revealed that after five simulator training sequential sessions the students' learning curve reaches a plateau. The forward sessions in the same difficult level do not promote any improvement in laparoscopic basic surgical skills, and the students should be introduced to a more difficult training

Establishing the minimal number of virtual reality simulator training sessions necessary to develop basic laparoscopic skills competence: evaluation of the learning curve.

Science.gov (United States)

Duarte, Ricardo Jordão; Cury, José; Oliveira, Luis Carlos Neves; Srougi, Miguel

2013-01-01

Medical literature is scarce on information to define a basic skills training program for laparoscopic surgery (peg and transferring, cutting, clipping). The aim of this study was to determine the minimal number of simulator sessions of basic laparoscopic tasks necessary to elaborate an optimal virtual reality training curriculum. Eleven medical students with no previous laparoscopic experience were spontaneously enrolled. They were submitted to simulator training sessions starting at level 1 (Immersion Lap VR, San Jose, CA), including sequentially camera handling, peg and transfer, clipping and cutting. Each student trained twice a week until 10 sessions were completed. The score indexes were registered and analyzed. The total of errors of the evaluation sequences (camera, peg and transfer, clipping and cutting) were computed and thereafter, they were correlated to the total of items evaluated in each step, resulting in a success percent ratio for each student for each set of each completed session. Thereafter, we computed the cumulative success rate in 10 sessions, obtaining an analysis of the learning process. By non-linear regression the learning curve was analyzed. By the non-linear regression method the learning curve was analyzed and a r2 = 0.73 (p sessions) to reach the plateau of 80% of the estimated acquired knowledge, being that 100% of the students have reached this level of skills. From the fifth session till the 10th, the gain of knowledge was not significant, although some students reached 96% of the expected improvement. This study revealed that after five simulator training sequential sessions the students' learning curve reaches a plateau. The forward sessions in the same difficult level do not promote any improvement in laparoscopic basic surgical skills, and the students should be introduced to a more difficult training tasks level.

Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

Energy Technology Data Exchange (ETDEWEB)

Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-07-01

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

Fluoroscopy Learning Curve in Hip Arthroscopy-A Single Surgeon's Experience.

Science.gov (United States)

Smith, Kevin M; Duplantier, Neil L; Crump, Kimbelyn H; Delgado, Domenica A; Sullivan, Stephanie L; McCulloch, Patrick C; Harris, Joshua D

2017-10-01

To determine if (1) absorbed radiation dose and (2) fluoroscopy time decreased with experience over the first 100 cases of a single surgeon's hip arthroscopy practice. Subjects who underwent hip arthroscopy for symptomatic femoroacetabular impingement and labral injury were eligible for analysis. Inclusion criteria included the first 100 subjects who underwent hip arthroscopy by a single surgeon (December 2013 to December 2014). Subject demographics, procedure details, fluoroscopy absorbed dose (milligray [mGy]), and time were recorded. Subjects were categorized by date of surgery to one of 4 possible groups (25 per group). One-way analysis of variance was used to determine if a significant difference in dose (mGy) or time was present between groups. Simple linear regression analysis was performed to determine the relation between case number and both radiation dose and fluoroscopy time. Subjects underwent labral repair (n = 93), cam osteoplasty (n = 90), and pincer acetabuloplasty (n = 65). There was a significant (P arthroscopy practice learning curve. Level IV, therapeutic, retrospective, noncomparative case series. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

The Learning Curve in neurofeedback of Peter Van Deusen: A review article

Directory of Open Access Journals (Sweden)

Valdenilson Ribeiro Ribas

Full Text Available ABSTRACT The Learning Curve (TLC in neurofeedback concept emerged after Peter Van Deusen compiled the results of articles on the expected electrical activity of the brain. This concept was subsequently tested on patients at four clinics in Atlanta between 1994 and 2001. The aim of this paper was to report the historical aspects of TLC. Articles published on the electronic databases MEDLINE/PubMed and Web of Science were reviewed. During patient evaluation, TLC investigates categories called disconnected, hot temporal lobes, reversal of alpha and beta waves, blocking, locking, and filtering or processing. This enables neuroscientists to use their training designs and, by means of behavioral psychology, to work on neuroregulation, as self-regulation for patients. TLC shows the relationships between electrical, mental and behavioral activity in patients. It also identifies details of patterns that can assist physicians in their choice of treatment.

The New Keynesian Phillips Curve

DEFF Research Database (Denmark)

Ólafsson, Tjörvi

This paper provides a survey on the recent literature on the new Keynesian Phillips curve: the controversies surrounding its microfoundation and estimation, the approaches that have been tried to improve its empirical fit and the challenges it faces adapting to the open-economy framework. The new......, learning or state-dependant pricing. The introduction of openeconomy factors into the new Keynesian Phillips curve complicate matters further as it must capture the nexus between price setting, inflation and the exchange rate. This is nevertheless a crucial feature for any model to be used for inflation...... forecasting in a small open economy like Iceland....

How Good Is Good: Improved Tracking and Managing of Safety Goals, Performance Indicators, Production Targets and Significant Events Using Learning Curves

International Nuclear Information System (INIS)

Duffey, Rommey B.; Saull, John W.

2002-01-01

We show a new way to track and measure safety and performance using learning curves derived on a mathematical basis. When unusual or abnormal events occur in plants and equipment, the regulator and good management practice requires they be reported, investigated, understood and rectified. In addition to reporting so-called 'significant events', both management and the regulator often set targets for individual and collective performance, which are used for both reward and criticism. For almost completely safe systems, like nuclear power plants, commercial aircraft and chemical facilities, many parameters are tracked and measured. Continuous improvement has to be demonstrated, as well as meeting reduced occurrence rates, which are set as management goals or targets. This process usually takes the form of statistics for availability of plant and equipment, forced or unplanned maintenance outage, loss of safety function, safety or procedural violations, etc. These are often rolled up into a set of so-called 'Performance Indicators' as measures of how well safety and operation is being managed at a given facility. The overall operating standards of an industry are also measured. A whole discipline is formed of tracking, measuring, reporting, managing and understanding the plethora of indicators and data. Decreasing occurrence rates and meeting or exceeding goals are seen and rewarded as virtues. Managers and operators need to know how good is their safety management system that has been adopted and used (and paid for), and whether it can itself be improved. We show the importance of accumulated experience in correctly measuring and tracking the decreasing event and error rates speculating a finite minimum rate. We show that the rate of improvement constitutes a measurable 'learning curve', and the attainment of the goals and targets can be affected by the adopted measures. We examine some of the available data on significant events, reportable occurrences, and loss of

Learning curves of basic laparoscopic psychomotor skills in SINERGIA VR simulator.

Science.gov (United States)

Sánchez-Peralta, L F; Sánchez-Margallo, F M; Moyano-Cuevas, J L; Pagador, J B; Enciso, S; Gómez-Aguilera, E J; Usón-Gargallo, J

2012-11-01

Surgical simulators are currently essential within any laparoscopic training program because they provide a low-stakes, reproducible and reliable environment to acquire basic skills. The purpose of this study is to determine the training learning curve based on different metrics corresponding to five tasks included in SINERGIA laparoscopic virtual reality simulator. Thirty medical students without surgical experience participated in the study. Five tasks of SINERGIA were included: Coordination, Navigation, Navigation and touch, Accurate grasping and Coordinated pulling. Each participant was trained in SINERGIA. This training consisted of eight sessions (R1-R8) of the five mentioned tasks and was carried out in two consecutive days with four sessions per day. A statistical analysis was made, and the results of R1, R4 and R8 were pair-wise compared with Wilcoxon signed-rank test. Significance is considered at P value psychomotor skills that can be trained in SINERGIA. Therefore, and based on these results together with previous works, SINERGIA could be used as training tool with a properly designed training program.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

International Nuclear Information System (INIS)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin [Dept. of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2015-04-15

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Learning curve of laparoscopy-assisted distal gastrectomy with systemic lymphadenectomy for early gastric cancer

Institute of Scientific and Technical Information of China (English)

Min-Chan Kim; Ghap-Joong Jung; Hyung-Ho Kim

2005-01-01

AIM: To evaluate the nature of the "learning curve" for laparoscopy-assisted distal gastrectomy (LADG) with systemic lymphadenectomy for early gastric cancer. METHODS: The data of 90 consecutive patients with early gastric cancer who underwent LADG with systemic lymphadenectomy between April 2003 and November 2004 were reviewed. The 90 patients were divided into 9 sequential groups of 10 cases in each group and the average operative time of these 9 groups were determined. Other learning indicators, such as transfusion requirements, conversion rates to open surgery, postoperative complication, time to first flatus, and postoperative hospital stay, were evaluated. RESULTS: After the first 10 LADGs, the operative time reached its first plateau (230-240 min/operation) and then reached a second plateau (＜200 min/operation) for the final 30 cases. Although a significant improvement in the operative time was noted after the first 50 cases, there were no significant differences in transfusion requirements, conversion rates to open surgery, postoperative complications, time to first flatus, or postoperative hospital stay between the groups. CONCLUSION: Based on operative time analysis, this study show that experience of 50 cases of LADG with systemic lymphadenectomy for early gastric cancer is required to achieve optimum proficiency.

Rapid learning curve assessment in an ex vivo training system for microincisional glaucoma surgery.

Science.gov (United States)

Dang, Yalong; Waxman, Susannah; Wang, Chao; Parikh, Hardik A; Bussel, Igor I; Loewen, Ralitsa T; Xia, Xiaobo; Lathrop, Kira L; Bilonick, Richard A; Loewen, Nils A

2017-05-09

Increasing prevalence and cost of glaucoma have increased the demand for surgeons well trained in newer, microincisional surgery. These procedures occur in a highly confined space, making them difficult to learn by observation or assistance alone as is currently done. We hypothesized that our ex vivo outflow model is sensitive enough to allow computing individual learning curves to quantify progress and refine techniques. Seven trainees performed nine trabectome-mediated ab interno trabeculectomies in pig eyes (n = 63). An expert surgeon rated the procedure using an Operating Room Score (ORS). The extent of outflow beds accessed was measured with canalograms. Data was fitted using mixed effect models. ORS reached a half-maximum on an asymptote after only 2.5 eyes. Surgical time decreased by 1.4 minutes per eye in a linear fashion. The ablation arc followed an asymptotic function with a half-maximum inflection point after 5.3 eyes. Canalograms revealed that this progress did not correlate well with improvement in outflow, suggesting instead that about 30 eyes are needed for true mastery. This inexpensive pig eye model provides a safe and effective microsurgical training model and allows objective quantification of outcomes for the first time.

Learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer.

Science.gov (United States)

Lendínez-Cano, G; Osman García, I; Congregado Ruiz, C B; Conde Sánchez, J M; Medina López, R A

2018-03-07

To analyse the learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer. We evaluated 32 consecutive patients treated in our department for metastatic renal cancer with tyrosine kinase inhibitors (pazopanib or sunitinib) as first-line treatment between September 2012 and November 2015. We retrospectively analysed this sample. We measured the time to the withdrawal of the first-line treatment, the time to progression and overall survival using Kaplan-Meier curves. The learning curve was analysed with the cumulative sum (CUSUM) methodology. In our series, the median time to the withdrawal of the first-line treatment was 11 months (95% CI 4.9-17.1). The mean time to progression was 30.4 months (95% CI 22.7-38.1), and the mean overall survival was 34.9 months (95% CI 27.8-42). By applying the CUSUM methodology, we obtained a graph for the CUSUM value of the time to withdrawal of the first-line treatment (CUSUM TW), observing 3 well-differentiated phases: phase 1 or initial learning phase (1-15), phase 2 (16-26) in which the management of the drug progressively improved and phase 3 (27-32) of maximum experience or mastery of the management of these drugs. The number of treated patients needed to achieve the proper management of these patients was estimated at 15. Despite the limitations of the sample size and follow-up time, we estimated (in 15 patients) the number needed to reach the necessary experience in the management of these patients with tyrosine kinase inhibitors. We observed no relationship between the time to the withdrawal of the first-line treatment for any cause and progression. Copyright © 2018 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Preoperative risk factors for conversion and learning curve of minimally invasive distal pancreatectomy.

Science.gov (United States)

Hua, Yongfei; Javed, Ammar A; Burkhart, Richard A; Makary, Martin A; Weiss, Matthew J; Wolfgang, Christopher L; He, Jin

2017-11-01

Although laparoscopic distal pancreatectomy is considered a standard approach, 10% to 40% of these are converted. The preoperative risk factors for conversion are not well described. The aim of this study was to identify risk factors associated with conversion. Clinicopathological variables of 211 consecutive patients who underwent laparoscopic distal pancreatectomy between January 2007 and December 2015 at Johns Hopkins were analyzed to identify factors associated with conversion. Furthermore, the learning curve for laparoscopic distal pancreatectomy was studied. On univariate analysis of diabetes mellitus, preoperative diagnosis of malignant disease, multiorgan resection, surgeons' years and case experience were significantly associated with conversion (all P pancreatectomy with a preoperative diagnosis of malignant disease or possible multiorgan resection are at a higher risk of conversion. Surgeon experience of performing >15 procedures significantly reduces the risk of conversion. Copyright © 2017 Elsevier Inc. All rights reserved.

Femtosecond laser-assisted cataract surgery with bimanual technique: learning curve for an experienced cataract surgeon.

Science.gov (United States)

Cavallini, Gian Maria; Verdina, Tommaso; De Maria, Michele; Fornasari, Elisa; Volpini, Elisa; Campi, Luca

2017-11-29

To describe the intraoperative complications and the learning curve of microincision cataract surgery assisted by femtosecond laser (FLACS) with bimanual technique performed by an experienced surgeon. It is a prospective, observational, comparative case series. A total of 120 eyes which underwent bimanual FLACS by the same experienced surgeon during his first experience were included in the study; we considered the first 60 cases as Group A and the second 60 cases as Group B. In both groups, only nuclear sclerosis of grade 2 or 3 was included; an intraocular lens was implanted through a 1.4-mm incision. Best-corrected visual acuity (BCVA), surgically induced astigmatism (SIA), central corneal thickness and endothelial cell loss (ECL) were evaluated before and at 1 and 3 months after surgery. Intraoperative parameters, and intra- and post-operative complications were recorded. In Group A, we had femtosecond laser-related minor complications in 11 cases (18.3%) and post-operative complications in 2 cases (3.3%); in Group B, we recorded 2 cases (3.3%) of femtosecond laser-related minor complications with no post-operative complications. Mean effective phaco time (EPT) was 5.32 ± 3.68 s in Group A and 4.34 ± 2.39 s in Group B with a significant difference (p = 0.046). We recorded a significant mean BCVA improvement at 3 months in both groups (p  0.05). Finally, we found significant ECL in both groups with a significant difference between the two groups (p = 0.042). FLACS with bimanual technique and low-energy LDV Z8 is associated with a necessary initial learning curve. After the first adjustments in the surgical technique, this technology seems to be safe and effective with rapid visual recovery and it helps surgeons to standardize the crucial steps of cataract surgery.

Bypassing the learning curve in permanent seed implants using state-of-the-art technology

International Nuclear Information System (INIS)

Beaulieu, Luc; Evans, Dee-Ann Radford; Aubin, Sylviane; Angyalfi, Steven; Husain, Siraj; Kay, Ian; Martin, Andre-Guy; Varfalvy, Nicolas; Vigneault, Eric; Dunscombe, Peter

2007-01-01

Purpose: The aim of this study was to demonstrate, based on clinical postplan dose distributions, that technology can be used efficiently to eliminate the learning curve associated with permanent seed implant planning and delivery. Methods and Materials: Dose distributions evaluated 30 days after the implant of the initial 22 consecutive patients treated with permanent seed implants at two institutions were studied. Institution 1 (I1) consisted of a new team, whereas institution 2 (I2) had performed more than 740 preplanned implantations over a 9-year period before the study. Both teams had adopted similar integrated systems based on three-dimensional (3D) transrectal ultrasonography, intraoperative dosimetry, and an automated seed delivery and needle retraction system (FIRST, Nucletron). Procedure time and dose volume histogram parameters such as D90, V100, V150, V200, and others were collected in the operating room and at 30 days postplan. Results: The average target coverage from the intraoperative plan (V100) was 99.4% for I1 and 99.9% for I2. D90, V150, and V200 were 191.4 Gy (196.3 Gy), 75.3% (73.0%), and 37.5% (34.1%) for I1 (I2) respectively. None of these parameters shows a significant difference between institutions. The postplan D90 was 151.2 Gy for I1 and 167.3 Gy for I2, well above the 140 Gy from the Stock et al. analysis, taking into account differences at planning, results in a p value of 0.0676. The procedure time required on average 174.4 min for I1 and 89 min for I2. The time was found to decrease with the increasing number of patients. Conclusion: State-of-the-art technology enables a new brachytherapy team to obtain excellent postplan dose distributions, similar to those achieved by an experienced team with proven long-term clinical results. The cost for bypassing the usual dosimetry learning curve is time, with increasing team experience resulting in shorter treatment times

Kant, curves and medical learning practice: a reply to Le Morvan and Stock.

Science.gov (United States)

Ives, J

2007-02-01

In a recent paper published in the Journal of Medical Ethics, Le Morvan and Stock claim that the kantian ideal of treating people always as ends in themselves and never merely as a means is in direct and insurmountable conflict with the current medical practice of allowing practitioners at the bottom of their "learning curve" to "practise their skills" on patients. In this response, I take up the challenge they issue [corrected] and try to reconcile this conflict. The kantian ideal offered in the paper is an incomplete characterisation of Kant's moral philosophy, and the formula of humanity is considered in isolation without taking into account other salient kantian principles. I also suggest that their argument based on "necessary for the patient" assumes too narrow a reading of "necessary". This reply is intended as an extension to, rather than a criticism of, their work.

A variation reduction allocation model for quality improvement to minimize investment and quality costs by considering suppliers’ learning curve

Science.gov (United States)

Rosyidi, C. N.; Jauhari, WA; Suhardi, B.; Hamada, K.

2016-02-01

Quality improvement must be performed in a company to maintain its product competitiveness in the market. The goal of such improvement is to increase the customer satisfaction and the profitability of the company. In current practice, a company needs several suppliers to provide the components in assembly process of a final product. Hence quality improvement of the final product must involve the suppliers. In this paper, an optimization model to allocate the variance reduction is developed. Variation reduction is an important term in quality improvement for both manufacturer and suppliers. To improve suppliers’ components quality, the manufacturer must invest an amount of their financial resources in learning process of the suppliers. The objective function of the model is to minimize the total cost consists of investment cost, and quality costs for both internal and external quality costs. The Learning curve will determine how the employee of the suppliers will respond to the learning processes in reducing the variance of the component.

An application of the learning curve-cumulative summation test to evaluate training for endotracheal intubation in emergency medicine.

Science.gov (United States)

Je, Sangmo; Cho, Youngsuk; Choi, Hyuk Joong; Kang, Boseung; Lim, Taeho; Kang, Hyunggoo

2015-04-01

The learning curve-cumulative summation (LC-CUSUM) test allows for quantitative and individual assessments of the learning process. In this study, we evaluated the process of skill acquisition for performing endotracheal intubation (ETI) in three emergency medicine (EM) residents over a 2 year period in their first 2 years of their EM residency. We evaluated 342 ETI cases performed by three EM residents using the LC-CUSUM test according to their rate of success or failure of ETI. A 90% success rate (SR) was chosen to define adequate performance and an SR of 80% was considered inadequate. After the learning phase, the standard CUSUM test was applied to ensure that performance was maintained. The mean number of ETI cases required to reach the predefined level of performance was 74.7 (95% CI 62.0 to 87.3). CUSUM tests confirmed that performance was maintained after the learning phase. By using the LC-CUSUM test, we were able to quantitatively monitor the acquisition of the skill of ETI by EM residents. The LC-CUSUM could be useful for monitoring the learning process for the training of airway management in the practice of EM. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Rational points on elliptic curves

CERN Document Server

Silverman, Joseph H

2015-01-01

The theory of elliptic curves involves a pleasing blend of algebra, geometry, analysis, and number theory. This book stresses this interplay as it develops the basic theory, thereby providing an opportunity for advanced undergraduates to appreciate the unity of modern mathematics. At the same time, every effort has been made to use only methods and results commonly included in the undergraduate curriculum. This accessibility, the informal writing style, and a wealth of exercises make Rational Points on Elliptic Curves an ideal introduction for students at all levels who are interested in learning about Diophantine equations and arithmetic geometry. Most concretely, an elliptic curve is the set of zeroes of a cubic polynomial in two variables. If the polynomial has rational coefficients, then one can ask for a description of those zeroes whose coordinates are either integers or rational numbers. It is this number theoretic question that is the main subject of this book. Topics covered include the geometry and ...

Is there a learning curve for the TVT-O procedure? A prospective single-surgeon study of 372 consecutive cases.

Science.gov (United States)

Serati, Maurizio; Bogani, Giorgio; Braga, Andrea; Sorice, Paola; Salvatore, Stefano; Uccella, Stefano; Ghezzi, Fabio

2015-03-01

To evaluate for the first time in the literature the learning curve of Inside-out transobturator tape (TVT-O™). A prospective observational study was conducted in a tertiary reference center. Consecutive women treated by TVT-O™ performed by one surgeon were included. Data regarding subjective, objective cure rates, and adverse events were collected. Trends, over the number of procedures, were estimated using assay analyses. Number of procedures and variables were interpolating in standard curves using linear lines. Three hundred and seventy two procedures were included. Postoperative pain levels decreased with the increase in the level of expertise (pain levels: 1-day: from 6.6 (±3.3) to 4.3 (±3.1); 95%CI: -0.01603 to 0.001235, p=0.04; 2-day: from 5.6 (±4.1) to 3.6 (±3.7); 95%CI: -0.02092 to -0.002497, p=0.01; 12-month: from 0.1 (±0.7) to 0 (±0); 95%CI: -0.001814 to 0.05019, p=0.07). Overall, objective cure rate was achieved in 93.5% of patients. Additionally, 88.2% and 88.7% patients reported "much better" feeling at PGI-I scale and 80% reduction in UDI score, respectively. We observed, that delta ICIQ-sf (from 12 (±8.7) to 14 (±6.0); p=0.04) and delta-UDI (from 91% to 97%; p=0.04) improved over the time. TVT-O procedure offers excellent outcomes with high objective and subjective cure rates and low complications rate, even at the beginning of the surgeon's learning curve. However, a high experience of the surgeon could significantly improve the subjective cure rate and could reduce postoperative the groin pain. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Análise de conglomerados em curvas de aprendizado para formação de agrupamentos homogêneos de trabalhadores Cluster analysis of learning curves for grouping workers with homogeneous learning profiles

Directory of Open Access Journals (Sweden)

Renato Eduardo Stroieke

2012-01-01

Full Text Available Em diversos setores da indústria é desejado que trabalhadores reunidos em uma estação de trabalho apresentem perfil de aprendizado similar. O presente artigo apresenta um método de agrupamento de trabalhadores utilizando modelagem por curva de aprendizado e técnicas de clusterização. O método modela dados de desempenho de trabalhadores por intermédio de diversos modelos de curvas de aprendizado; os parâmetros de aprendizado dos modelos testados permitem predizer o desempenho dos trabalhadores em intervalos de tempo pré-determinados. Os valores preditos são agrupados através de ferramentas de clusterização. O maior índice de ajuste (IA, gerado a partir do Silhouette Index e do coeficiente de determinação, indica o modelo de curva mais consistente em termos de aderência aos dados e qualidade de agrupamento de perfis de aprendizado. Ao ser aplicado em dados de uma indústria de calçados, o método gerou agrupamentos consistentes de trabalhadores com base nos distintos perfis de aprendizado.In many industrial segments, it is desirable to allocate workers with similar learning profiles in the same workstation. This paper presents a method that groups workers based on learning curve modeling and clustering techniques. Workers' performance data are modeled through several learning curve models; learning parameters allow for workers' performance prediction at intervals of predetermined time. The predicted values are then grouped by clustering techniques. The largest Adjustment Index (AI, derived from the Silhouette Index and Coefficient of Determination, indicates the model yielding superior adherence to data and better clustering of learning profiles. When applied to a shoe manufacturing process, the method generated consistent groups of workers based on their learning profiles.

Initial laparoscopic basic skills training shortens the learning curve of laparoscopic suturing and is cost-effective.

Science.gov (United States)

Stefanidis, Dimitrios; Hope, William W; Korndorffer, James R; Markley, Sarah; Scott, Daniel J

2010-04-01

Laparoscopic suturing is an advanced skill that is difficult to acquire. Simulator-based skills curricula have been developed that have been shown to transfer to the operating room. Currently available skills curricula need to be optimized. We hypothesized that mastering basic laparoscopic skills first would shorten the learning curve of a more complex laparoscopic task and reduce resource requirements for the Fundamentals of Laparoscopic Surgery suturing curriculum. Medical students (n = 20) with no previous simulator experience were enrolled in an IRB-approved protocol, pretested on the Fundamentals of Laparoscopic Surgery suturing model, and randomized into 2 groups. Group I (n = 10) trained (unsupervised) until proficiency levels were achieved on 5 basic tasks; Group II (n = 10) received no basic training. Both groups then trained (supervised) on the Fundamentals of Laparoscopic Surgery suturing model until previously reported proficiency levels were achieved. Two weeks later, they were retested to evaluate their retention scores, training parameters, instruction requirements, and cost between groups using t-test. Baseline characteristics and performance were similar for both groups, and 9 of 10 subjects in each group achieved the proficiency levels. The initial performance on the simulator was better for Group I after basic skills training, and their suturing learning curve was shorter compared with Group II. In addition, Group I required less active instruction. Overall time required to finish the curriculum was similar for both groups; but the Group I training strategy cost less, with a savings of $148 per trainee. Teaching novices basic laparoscopic skills before a more complex laparoscopic task produces substantial cost savings. Additional studies are needed to assess the impact of such integrated curricula on ultimate educational benefit. Copyright (c) 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Transcatheter closure of patent ductus arteriosus: Evaluating the effect of the learning curve on the outcome

Directory of Open Access Journals (Sweden)

Azhar Ahmad

2009-01-01

Full Text Available Background and Objectives : Initial experience with transcatheter closure of patent ductus arteriosus (PDA using detachable coils and Amplatzer duct occluder devices is reported. We evaluated the outcome, complications, and influence of the learning curve, and also assessed the need of surgical backup for such interventional procedures. Methods: From January 2000 to December 2004, 121 patients underwent transcatheter closure of PDA. Aortic angiogram was performed to evaluate the size, position, and shape of the duct for appropriately choosing the occluder device type and size. A second aortic angiogram was performed 10 minutes after device deployment. Echocardiography was repeated at intervals of 24 hours, then at 1, 3, and 6 months after the procedure to assess complications. Stepwise multiple regression analysis was used to assess the role of experience in improving the outcome of the procedure. Results: Of 121 cases, four patients had pulmonary artery embolization of the occluder device which was successfully retrieved in the catheterization laboratory, while two others had embolization that required surgical intervention. Four patients had temporary residual leak, nine had protrusion of the device into the aorta without significant Doppler pressure gradient or hemolysis on follow-up, and five had partial hemodynamically insignificant obstruction to the left pulmonary artery. Statistical analysis showed that the effect of the learning curve and experience was responsible for 93% improvement in the procedural outcome over the five-year study period. Conclusion: Transcatheter occlusion of PDA is safe and effective alternative to surgery. Complications occurred in those with unfavorable duct anatomy and with the use of multiple coils. Surgical backup was important for such interventional procedures. Experience played a major role in the proper choice of device type and size which greatly influenced the outcome of the procedure.

Technology learning in a global - local perspective: - the interplay between technology diffusion, niche markets and experience curves

International Nuclear Information System (INIS)

Martinsen, Thomas

2010-01-01

Preventing dangerous global climate change requires timely deployment of nascent energy technologies with zero or low Co2 emissions. Managing the shift to a common sustainable technology path calls for insight about the influence of global technological change on the national energy system. Moreover, national policies are required to promote the shift to the new technology path. This calls for methods to analyse the national energy system within a global perspective. The objective of the work presented in this thesis was to investigate interplay between technology diffusion, niche markets and technology learning from the perspective of a small open economy like Norway. More specifically, develop methods to include the influence of technology learning manifested in experience and learning curves into national energy-economy-environment models. Moreover, apply the methods to investigate the potential influence and sensitivity to technology learning in a small open economy. In this thesis three such methods have been developed, applied and its importance assessed using Norway as an example. In this work three models have been linked. They are the global Energy Technology Perspectives model operated by the International Energy Agency, the Norwegian Markal model at the Institute for Energy Technology and the macro economic model MSG6 at Statistics Norway. Method one and two has been developed to manage the interplay between the models. In a local perspective technology learning in the global market is perceived as spillover. Based upon a review of the characteristics of technological change and learning curves and its application to energy system modelling some criteria important for the parameterization and modelling of spillover in a small open economy are suggested. The first method incorporates spillover into the national Markal model. The second method establishes a soft-link between the national models. The soft-link served two purposes; to provide input on demand

Fast algorithm selection using learning curves

NARCIS (Netherlands)

Rijn, van J.N.; Abdulrahman, S.M.; Brazdil, P.; Vanschoren, J.; Fromont, E.; De Bie, T.; Leeuwen, van M.

2015-01-01

One of the challenges in Machine Learning to find a classifier and parameter settings that work well on a given dataset. Evaluating all possible combinations typically takes too much time, hence many solutions have been proposed that attempt to predict which classifiers are most promising to try. As

Assessment of performance measures and learning curves for use of a virtual-reality ultrasound simulator in transvaginal ultrasound examination

DEFF Research Database (Denmark)

Madsen, M E; Konge, L; Nørgaard, L N

2014-01-01

OBJECTIVE: To assess the validity and reliability of performance measures, develop credible performance standards and explore learning curves for a virtual-reality simulator designed for transvaginal gynecological ultrasound examination. METHODS: A group of 16 ultrasound novices, along with a group......-6), corresponding to an average of 219 min (range, 150-251 min) of training. The test/retest reliability was high, with an intraclass correlation coefficient of 0.93. CONCLUSIONS: Competence in the performance of gynecological ultrasound examination can be assessed in a valid and reliable way using virtual-reality...

Equilibrium spherically curved two-dimensional Lennard-Jones systems

NARCIS (Netherlands)

Voogd, J.M.; Sloot, P.M.A.; van Dantzig, R.

2005-01-01

To learn about basic aspects of nano-scale spherical molecular shells during their formation, spherically curved two-dimensional N-particle Lennard-Jones systems are simulated, studying curvature evolution paths at zero-temperature. For many N-values (N < 800) equilibrium configu- rations are traced

Facilitating students' application of the integral and the area under the curve concepts in physics problems

Science.gov (United States)

Nguyen, Dong-Hai

This research project investigates the difficulties students encounter when solving physics problems involving the integral and the area under the curve concepts and the strategies to facilitate students learning to solve those types of problems. The research contexts of this project are calculus-based physics courses covering mechanics and electromagnetism. In phase I of the project, individual teaching/learning interviews were conducted with 20 students in mechanics and 15 students from the same cohort in electromagnetism. The students were asked to solve problems on several topics of mechanics and electromagnetism. These problems involved calculating physical quantities (e.g. velocity, acceleration, work, electric field, electric resistance, electric current) by integrating or finding the area under the curve of functions of related quantities (e.g. position, velocity, force, charge density, resistivity, current density). Verbal hints were provided when students made an error or were unable to proceed. A total number of 140 one-hour interviews were conducted in this phase, which provided insights into students' difficulties when solving the problems involving the integral and the area under the curve concepts and the hints to help students overcome those difficulties. In phase II of the project, tutorials were created to facilitate students' learning to solve physics problems involving the integral and the area under the curve concepts. Each tutorial consisted of a set of exercises and a protocol that incorporated the helpful hints to target the difficulties that students expressed in phase I of the project. Focus group learning interviews were conducted to test the effectiveness of the tutorials in comparison with standard learning materials (i.e. textbook problems and solutions). Overall results indicated that students learning with our tutorials outperformed students learning with standard materials in applying the integral and the area under the curve

Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times.

Science.gov (United States)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyungjin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ≤ 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

LCC: Light Curves Classifier

Science.gov (United States)

Vo, Martin

2017-08-01

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio). Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

Designing learning curves for carbon capture based on chemical absorption according to the minimum work of separation

International Nuclear Information System (INIS)

Rochedo, Pedro R.R.; Szklo, Alexandre

2013-01-01

Highlights: • This work defines the minimum work of separation (MWS) for a capture process. • Findings of the analysis indicated a MWS of 0.158 GJ/t for post-combustion. • A review of commercially available processes based on chemical absorption was made. • A review of learning models was conducted, with the addition on a novel model. • A learning curve for post-combustion carbon capture was successfully designed. - Abstract: Carbon capture is one of the most important alternatives for mitigating greenhouse gas emissions in energy facilities. The post-combustion route based on chemical absorption with amine solvents is the most feasible alternative for the short term. However, this route implies in huge energy penalties, mainly related to the solvent regeneration. By defining the minimum work of separation (MWS), this study estimated the minimum energy required to capture the CO 2 emitted by coal-fired thermal power plants. Then, by evaluating solvents and processes and comparing it to the MWS, it proposes the learning model with the best fit for the post-combustion chemical absorption of CO 2 . Learning models are based on earnings from experience, which can include the intensity of research and development. In this study, three models are tested: Wright, DeJong and D and L. Findings of the thermochemical analysis indicated a MWS of 0.158 GJ/t for post-combustion. Conventional solvents currently present an energy penalty eight times the MWS. By using the MWS as a constraint, this study found that the D and L provided the best fit to the available data of chemical solvents and absorption plants. The learning rate determined through this model is very similar to the ones found in the literature

What have we learned from quantum field theory in curved space-time

International Nuclear Information System (INIS)

Fulling, S.A.

1984-01-01

The paper reviews the quantum field theory in curved space-time. Field quantization in gravitational backgrounds; particle creation by black holes; Hawking radiation; quantum field theory in curved space-time; covariant renormalization of the stress-energy-momentum tensor; quantum field theory and quantum gravity; are all discussed. (U.K.)

The learning curve, interobserver, and intraobserver agreement of endoscopic confocal laser endomicroscopy in the assessment of mucosal barrier defects.

Science.gov (United States)

Chang, Jeff; Ip, Matthew; Yang, Michael; Wong, Brendon; Power, Theresa; Lin, Lisa; Xuan, Wei; Phan, Tri Giang; Leong, Rupert W

2016-04-01

Confocal laser endomicroscopy can dynamically assess intestinal mucosal barrier defects and increased intestinal permeability (IP). These are functional features that do not have corresponding appearance on histopathology. As such, previous pathology training may not be beneficial in learning these dynamic features. This study aims to evaluate the diagnostic accuracy, learning curve, inter- and intraobserver agreement for identifying features of increased IP in experienced and inexperienced analysts and pathologists. A total of 180 endoscopic confocal laser endomicroscopy (Pentax EC-3870FK; Pentax, Tokyo, Japan) images of the terminal ileum, subdivided into 6 sets of 30 were evaluated by 6 experienced analysts, 13 inexperienced analysts, and 2 pathologists, after a 30-minute teaching session. Cell-junction enhancement, fluorescein leak, and cell dropout were used to represent increased IP and were either present or absent in each image. For each image, the diagnostic accuracy, confidence, and quality were assessed. Diagnostic accuracy was significantly higher for experienced analysts compared with inexperienced analysts from the first set (96.7% vs 83.1%, P 0.86 for experienced observers. Features representative of increased IP can be rapidly learned with high inter- and intraobserver agreement. Confidence and image quality were significant predictors of accurate interpretation. Previous pathology training did not have an effect on learning. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

Science.gov (United States)

Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Lagrangian Curves on Spectral Curves of Monopoles

International Nuclear Information System (INIS)

Guilfoyle, Brendan; Khalid, Madeeha; Ramon Mari, Jose J.

2010-01-01

We study Lagrangian points on smooth holomorphic curves in TP 1 equipped with a natural neutral Kaehler structure, and prove that they must form real curves. By virtue of the identification of TP 1 with the space LE 3 of oriented affine lines in Euclidean 3-space, these Lagrangian curves give rise to ruled surfaces in E 3 , which we prove have zero Gauss curvature. Each ruled surface is shown to be the tangent lines to a curve in E 3 , called the edge of regression of the ruled surface. We give an alternative characterization of these curves as the points in E 3 where the number of oriented lines in the complex curve Σ that pass through the point is less than the degree of Σ. We then apply these results to the spectral curves of certain monopoles and construct the ruled surfaces and edges of regression generated by the Lagrangian curves.

Modeling Patterns of Activities using Activity Curves.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

Clinical experience with the first 40 cases with femtosecond laser cataract surgery technology: safety of the learning curve

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Joao Crispim

2015-10-01

Full Text Available ABSTRACT Objective: To evaluate the introduction of the femtosecond laser (FSL to perform the key steps of the traditional cataract surgery process and the operational difficulties and safety of this new technology during routine use in an operating room in Brazil. Methods A retrospective study was conducted using the first cases operated on at a single center using the laser platform LenSx/Alcon with a soft contact lens patient interface.All patients underwent a detailed preoperative assessment.The anterior capsulotomy, nuclear fragmentation, and corneal incisions were created with the FSL; then, the surgery was completed following the standard phacoemulsification procedure. The main outcome measurements were difficulties and complications related to the learning curve and an analysis of postoperative uncorrected distance visual acuity (UDVA. Results: Of 31 patients (40 eyes, 9 patients had FSL cataract surgery in both eyes.The mean age was 64 ± 12 years (ranging from 42 to 82, the mean cataract nuclear sclerosis was grading 2 ± 0.6 (ranging from 1 to 4, and the preoperative mean UDVA in logMAR was 0.4 ± 0.2 (ranging from 0.1 to 1.3. Anterior capsulotomy was complete in all patients, and scissors were not needed to cut off any intact portion. The postoperative corneal incisions were not completely linear and showed some irregularities. Laser phaco-fragmentation was effective, with the division of the nucleus into smaller segments easily performed before phacoemulsification.After 1 month, the postoperative mean UDVA in logMAR was 0.1 ± 0.1 (ranging from 0.0 to 0.4 (P < 0.0001. Conclusion: With increasing surgical cases and experience, the phacoemulsification steps are performed precisely and effectively with FSL pretreatment, resulting in a safe learning curve.

The integration of computerised accounting in the accounting curriculum as an educational learning curve for students entering the business world

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Elmarie Papageorgiou

2014-06-01

Full Text Available At universities, educating students on real-life practices is one of the key drivers in a changing academic environment. Academic institutions encourage the study of the learning environment and ensure that appropriate strategies are in place for educating students. A first-year Accounting I student stated the importance of computerised accounting: ‘Computerised accounting is used in the workplace and therefore using it in varsity, grants students a view on how things will be after completion of their respective degrees.’ Accordingly, the purpose of this study was to empirically investigate the perceived acquisition of information technology (IT knowledge and determine the skills required for students to convert the knowledge gained into actions as a learning curve for accounting students entering the business world. The results indicated that students’ knowledge of Accounting I increased with the integration of computerised Accounting in the Accounting I Curriculum.

Evaluating the Learning Curve for Percutaneous Nephrolithotomy under Total Ultrasound Guidance.

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Yan Song

Full Text Available To investigate the learning curve of percutaneous nephrolithotomy under total ultrasound guidance.One hundred and twenty consecutive PCNL operations under total ultrasound guidance performed by a novice surgeon in a tertiary referral center were studied. Operations were analyzed in cohorts of 15 to determine when a plateau was reached for the variables such as operation duration, ultrasound screening time, tract dilation time, stone-free rate and complication rate. Comparison was made with the results of a surgeon who had performed more than 1000 PCNLs. Fluoroscopy was not used at all during procedure.The mean operation time dropped from 82.5 min for the first 15 patients to a mean of 64.7 min for cases 46 through 60(P = 0.047. The ultrasound screening time was a peak of 6.4 min in the first 15 cases, whereas it dropped to a mean of 3.9 min for cases 46 through 60(P = 0.01. The tract dilation time dropped from 4.9 min for the first 15 patients to a mean of 3.8 min for cases 46 through 60(P = 0.036. The senior surgeon had a mean operating time, screening time and tract dilation time equivalent to those of the novice surgeon after 60 cases. There was no significant difference in stone free rate and complication rate.The competence of ultrasound guided PCNL is reached after 60 cases with good stone free rate and without major complications.

Evaluation of the learning curve of non-penetrating glaucoma surgery.

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Aslan, Fatih; Yuce, Berna; Oztas, Zafer; Ates, Halil

2017-08-11

To evaluate the learning curve of non-penetrating glaucoma surgery (NPGS). The study included 32 eyes of 27 patients' (20 male and 7 female) with medically uncontrolled glaucoma. Non-penetrating glaucoma surgeries performed by trainees under control of an experienced surgeon between 2005 and 2007 at our tertiary referral hospital were evaluated. Residents were separated into two groups. Humanistic training model applied to the one in the first group, he studied with experimental models before performing NPGS. Two residents in the second group performed NPGS after a conventional training model. Surgeries of the residents were recorded on video and intraoperative parameters were scored by the experienced surgeon at the end of the study. Postoperative intraocular pressure, absolute and total success rates were analyzed. In the first group 19 eyes of 16 patients and in the second group 13 eyes of 11 patients had been operated by residents. Intraoperative parameters and complication rates were not statistically significant between groups (p > 0.05, Chi-square). The duration of surgery was 32.7 ± 5.6 min in the first group and 45 ± 3.8 min in the second group. The difference was statistically significant (p < 0.001, Student's t test). Absolute and total success was 68.8 and 93.8% in the first group and 62.5 and 87.5% in the second group, respectively. The difference was not statistically significant. Humanistic and conventional training models under control of an experienced surgeon are safe and effective for senior residents who manage phacoemulsification surgery in routine cataract cases. Senior residents can practice these surgical techniques with reasonable complication rates.

Learning curve of robot-assisted laparoscopic radical prostatectomy for a single experienced surgeon: comparison with simultaneous laparoscopic radical prostatectomy.

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Ku, Ja Yoon; Ha, Hong Koo

2015-04-01

Despite the large number of analytical reports regarding the learning curve in the transition from open to robot-assisted radical prostatectomy (RARP), few comparative results with laparoscopic radical prostatectomy (LRP) have been reported. Thus, we evaluated operative and postoperative outcomes in RARP versus 100 simultaneously performed LRPs. A single surgeon had performed more than 1,000 laparoscopic operations, including 415 cases of radical nephrectomy, 85 radical cystectomies, 369 radical prostatectomies, and treatment of 212 other urological tumors, since 2009. We evaluated operative (operation time, intraoperative transfusion, complications, hospital stay, margin status, pathological stage, Gleason score) and postoperative (continence and erectile function) parameters in initial cases of RARP without tutoring compared with 100 recently performed LRPs. Mean operation time and length of hospital stay for RARP and LRP were 145.5±43.6 minutes and 118.1±39.1 minutes, and 6.4±0.9 days and 6.6±1.1 days, respectively (p=0.003 and p=0.721). After 17 cases, the mean operation time for RARP was similar to LRP (less than 2 hours). Positive surgical margins in localized cancer were seen in 11.1% and 8.9% of cases in RARP and LRP, respectively (p=0.733). At postoperative 3 months, sexual intercourse was reported in 14.0% and 12.0%, and pad-free continence in 96.0% and 81.0% in patients with RARP and LRP, respectively (p=0.796 and p=0.012). Previous large-volume experience of LRPs may shorten the learning curve for RARP in terms of oncological outcome. Additionally, previous experience with laparoscopy may improve the functional outcomes of RARP.

Reliability assessment of a manual-based procedure towards learning curve modeling and fmea analysis

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Gustavo Rech

2013-03-01

Full Text Available Separation procedures in drug Distribution Centers (DC are manual-based activities prone to failures such as shipping exchanged, expired or broken drugs to the customer. Two interventions seem as promising in improving the reliability in the separation procedure: (i selection and allocation of appropriate operators to the procedure, and (ii analysis of potential failure modes incurred by selected operators. This article integrates Learning Curves (LC and FMEA (Failure Mode and Effect Analysis aimed at reducing the occurrence of failures in the manual separation of a drug DC. LCs parameters enable generating an index to identify the recommended operators to perform the procedures. The FMEA is then applied to the separation procedure carried out by the selected operators in order to identify failure modes. It also deployed the traditional FMEA severity index into two sub-indexes related to financial issues and damage to company´s image in order to characterize failures severity. When applied to a drug DC, the proposed method significantly reduced the frequency and severity of failures in the separation procedure.

Validation of the NASA-TLX Score in Ongoing Assessment of Mental Workload During a Laparoscopic Learning Curve in Bariatric Surgery.

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Ruiz-Rabelo, Juan Francisco; Navarro-Rodriguez, Elena; Di-Stasi, Leandro Luigi; Diaz-Jimenez, Nelida; Cabrera-Bermon, Juan; Diaz-Iglesias, Carlos; Gomez-Alvarez, Manuel; Briceño-Delgado, Javier

2015-12-01

Fatigue and mental workload are directly associated with high-complexity tasks. In general, difficult tasks produce a higher mental workload, leaving little opportunity to deal with new/unexpected events and increasing the likelihood of performance errors. The laparoscopic Roux-en-Y gastric bypass (LRYGB) learning curve is considered to be one of the most difficult to complete in laparoscopic surgery. We wished to validate the National Aeronautics and Space Administration Task Load Index (NASA-TLX) in LRYGB and identify factors that could provoke a higher mental workload for surgeons during the learning curve. A single surgeon was enrolled to undertake 70 consecutive LRYGB procedures with two internal surgeons mentoring the first 35 cases. Patients were consecutive and ranked from case 35 to case 105 according to the date of the surgical procedure ("case rank"). Self-ratings of satisfaction, performance, and fatigue were measured at the end of surgery using a validated NASA-TLX questionnaire. The procedure was recorded for later viewing by two external evaluators. General data for patients and surgical variables were collected prospectively. A moderate correlation between the NASA-TLX score, BMI, operative time, and volumes of blood drainage was observed. There was no correlation between the NASA-TLX score and duration of hospital stay or time of drain removal. BMI ≥50 kg/m(2), male sex, inexperienced first assistant, and type 2 diabetes mellitus were identified as independent predictive factors of a higher NASA-TLX score. The NASA-TLX is a valid tool to gauge mental workload in LRYGB.

Mild decentration measured by a Scheimpflug camera and its impact on visual quality following SMILE in the early learning curve.

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Li, Meiyan; Zhao, Jing; Miao, Huamao; Shen, Yang; Sun, Ling; Tian, Mi; Wadium, Elizabeth; Zhou, Xingtao

2014-05-20

To measure decentration following femtosecond laser small incision lenticule extraction (SMILE) for the correction of myopia and myopic astigmatism in the early learning curve, and to investigate its impact on visual quality. A total of 55 consecutive patients (100 eyes) who underwent the SMILE procedure were included. Decentration was measured using a Scheimpflug camera 6 months after surgery. Uncorrected and corrected distance visual acuity (UDVA, CDVA), manifest refraction, and wavefront errors were also measured. Associations between decentration and the preoperative spherical equivalent were analyzed, as well as the associations between decentration and wavefront aberrations. Regarding efficacy and safety, 40 eyes (40%) had an unchanged CDVA; 32 eyes (32%) gained one line; and 11 eyes (11%) gained two lines. Fifteen eyes (15%) lost one line of CDVA, and two eyes (2%) lost two lines. Ninety-nine of the treated eyes (99%) had a postoperative UDVA better than 1.0, and 100 eyes (100%) had a UDVA better than 0.8. The mean decentered displacement was 0.17 ± 0.09 mm. The decentered displacement of all treated eyes (100%) was within 0.50 mm; 70 eyes (70%) were within 0.20 mm; and 90 eyes (90%) were within 0.30 mm. The vertical coma showed the greatest increase in magnitude. The magnitude of horizontal decentration was found to be associated with an induced horizontal coma. This study suggests that, although mild decentration occurred in the early learning curve, good visual outcomes were achieved after the SMILE surgery. Special efforts to minimize induced vertical coma are necessary. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Changing the Learning Curve in Novice Laparoscopists: Incorporating Direct Visualization into the Simulation Training Program.

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Dawidek, Mark T; Roach, Victoria A; Ott, Michael C; Wilson, Timothy D

A major challenge in laparoscopic surgery is the lack of depth perception. With the development and continued improvement of 3D video technology, the potential benefit of restoring 3D vision to laparoscopy has received substantial attention from the surgical community. Despite this, procedures conducted under 2D vision remain the standard of care, and trainees must become proficient in 2D laparoscopy. This study aims to determine whether incorporating 3D vision into a 2D laparoscopic simulation curriculum accelerates skill acquisition in novices. Postgraduate year-1 surgical specialty residents (n = 15) at the Schulich School of Medicine and Dentistry, at Western University were randomized into 1 of 2 groups. The control group practiced the Fundamentals of Laparoscopic Surgery peg-transfer task to proficiency exclusively under standard 2D laparoscopy conditions. The experimental group first practiced peg transfer under 3D direct visualization, with direct visualization of the working field. Upon reaching proficiency, this group underwent a perceptual switch, changing to standard 2D laparoscopy conditions, and once again trained to proficiency. Incorporating 3D direct visualization before training under standard 2D conditions significantly (p learning curves for each respective training protocol. An adaptive learning approach, which incorporates 3D direct visualization into a 2D laparoscopic simulation curriculum, accelerates skill acquisition. This is in contrast to previous work, possibly owing to the proficiency-based methodology employed, and has implications for resource savings in surgical training. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Irreversible electroporation ablation (IRE of unresectable soft tissue tumors: learning curve evaluation in the first 150 patients treated.

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Prejesh Philips

Full Text Available BACKGROUND: Irreversible electroporation (IRE is a novel technology that uses peri-target discrete probes to deliver high-voltage localized electric current to induce cell death without thermal-induced coagulative necrosis. "Learnability" and consistently effective results by novice practitioners is essential for determining acceptance of novel techniques. This multi-center prospectively-collected database study evaluates the learning curve of IRE. METHODS: Analysis of 150 consecutive patients over 7 institutions from 9/2010-7/2012 was performed with patients treated divided into 3 groups A (1(st 50 patients treated, B (2(nd 50 and C (3(rd 50 patients treated chronologically and analyzed for outcomes. RESULTS: A total of 167 IRE procedures were performed, with a majority being liver(39.5% and pancreatic(35.5% lesions. The three groups were similar with respect to co-morbidities and demographics. Group C had larger lesions (3.9 vs 3 cm,p=0.001, more numerous lesions (3.2 vs 2.2,p=0.07, more vascular invasion(p=0.001, underwent more associated procedures(p=0.001 and had longer operative times(p<0.001. Despite this, they had similar complication and high-grade complication rates(p=0.24. Attributable morbidity rate was 13.3%(total 29.3% and high-grade complications were seen in 4.19%(total 12.6%. Pancreatic lesions(p=0.001 and laparotomy(p=0.001 were associated with complications. CONCLUSION: The review represents that single largest review of IRE soft tissue ablation demonstrating initial patient selection and safety. Over time, complex treatments of larger lesions and lesions with greater vascular involvement were performed without a significant increase in adverse effects or impact on local relapse free survival. This evolution demonstrates the safety profile of IRE and speed of graduation to more complex lesions, which was greater than 5 cases by institution. IRE is a safe and effective alternative to conventional ablation with a demonstrable

Experience curve for natural gas production by hydraulic fracturing

International Nuclear Information System (INIS)

Fukui, Rokuhei; Greenfield, Carl; Pogue, Katie; Zwaan, Bob van der

2017-01-01

From 2007 to 2012 shale gas production in the US expanded at an astounding average growth rate of over 50%/yr, and thereby increased nearly tenfold over this short time period alone. Hydraulic fracturing technology, or “fracking”, as well as new directional drilling techniques, played key roles in this shale gas revolution, by allowing for extraction of natural gas from previously unviable shale resources. Although hydraulic fracturing technology had been around for decades, it only recently became commercially attractive for large-scale implementation. As the production of shale gas rapidly increased in the US over the past decade, the wellhead price of natural gas dropped substantially. In this paper we express the relationship between wellhead price and cumulative natural gas output in terms of an experience curve, and obtain a learning rate of 13% for the industry using hydraulic fracturing technology. This learning rate represents a measure for the know-how and skills accumulated thus far by the US shale gas industry. The use of experience curves for renewable energy options such as solar and wind power has allowed analysts, practitioners, and policy makers to assess potential price reductions, and underlying cost decreases, for these technologies in the future. The reasons for price reductions of hydraulic fracturing are fundamentally different from those behind renewable energy technologies – hence they cannot be directly compared – and hydraulic fracturing may soon reach, or maybe has already attained, a lower bound for further price reductions, for instance as a result of its water requirements or environmental footprint. Yet, understanding learning-by-doing phenomena as expressed by an industry-wide experience curve for shale gas production can be useful for strategic planning in the gas sector, as well as assist environmental policy design, and serve more broadly as input for projections of energy system developments. - Highlights: • Hydraulic

Can CCM law properly represent all extinction curves?

International Nuclear Information System (INIS)

Geminale, Anna; Popowski, Piotr

2005-01-01

We present the analysis of a large sample of lines of sight with extinction curves covering wavelength range from near-infrared (NIR) to ultraviolet (UV). We derive total to selective extinction ratios based on the Cardelli, Clayton and Mathis (1989, CCM) law, which is typically used to fit the extinction data both for diffuse and dense interstellar medium. We conclude that the CCM law is able to fit most of the extinction curves in our sample. We divide the remaining lines of sight with peculiar extinction into two groups according to two main behaviors: a) the optical/IR or/and UV wavelength region cannot be reproduced by the CCM formula; b) the optical/NIR and UV extinction data are best fit by the CCM law with different values of R v . We present examples of such curves. The study of both types of peculiar cases can help us to learn about the physical processes that affect dust in the interstellar medium, e.g., formation of mantles on the surface of grains, evaporation, growing or shattering

"Alarm-corrected" ergonomic armrest use could improve learning curves of novices on robotic simulator.

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Yang, Kun; Perez, Manuela; Hossu, Gabriela; Hubert, Nicolas; Perrenot, Cyril; Hubert, Jacques

2017-01-01

In robotic surgery, the professional ergonomic habit of using an armrest reduces operator fatigue and increases the precision of motion. We designed and validated a pressure surveillance system (PSS) based on force sensors to investigate armrest use. The objective was to evaluate whether adding an alarm to the PSS system could shorten ergonomic training and improve performance. Twenty robot and simulator-naïve participants were recruited and randomized in two groups (A and B). The PSS was installed on a robotic simulator, the dV-Trainer, to detect contact with the armrest. The Group A members completed three tasks on the dV-Trainer without the alarm, making 15 attempts at each task. The Group B members practiced the first two tasks with the alarm and then completed the final tasks without the alarm. The simulator provided an overall score reflecting the trainees' performance. We used the new concept of an "armrest load" score to describe the ergonomic habit of using the armrest. Group B had a significantly higher performance score (p ergonomic errors and accelerated professional ergonomic habit acquisition. The combination of the PSS and alarm is effective in significantly shortening the learning curve in the robotic training process.

On-line learning through simple perceptron learning with a margin.

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Hara, Kazuyuki; Okada, Masato

2004-03-01

We analyze a learning method that uses a margin kappa a la Gardner for simple perceptron learning. This method corresponds to the perceptron learning when kappa = 0 and to the Hebbian learning when kappa = infinity. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Placement of central venous port catheters and peripherally inserted central catheters in the routine clinical setting of a radiology department: analysis of costs and intervention duration learning curve.

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Rotzinger, Roman; Gebauer, Bernhard; Schnapauff, Dirk; Streitparth, Florian; Wieners, Gero; Grieser, Christian; Freyhardt, Patrick; Hamm, Bernd; Maurer, Martin H

2017-12-01

Background Placement of central venous port catheters (CVPS) and peripherally inserted central catheters (PICC) is an integral component of state-of-the-art patient care. In the era of increasing cost awareness, it is desirable to have more information to comprehensively assess both procedures. Purpose To perform a retrospective analysis of interventional radiologic implantation of CVPS and PICC lines in a large patient population including a cost analysis of both methods as well as an investigation the learning curve in terms of the interventions' durations. Material and Methods All CVPS and PICC line related interventions performed in an interventional radiology department during a three-year period from January 2011 to December 2013 were examined. Documented patient data included sex, venous access site, and indication for CVPS or PICC placement. A cost analysis including intervention times was performed based on the prorated costs of equipment use, staff costs, and expenditures for disposables. The decrease in intervention duration in the course of time conformed to the learning curve. Results In total, 2987 interventions were performed by 16 radiologists: 1777 CVPS and 791 PICC lines. An average implantation took 22.5 ± 0.6 min (CVPS) and 10.1 ± 0.9 min (PICC lines). For CVPS, this average time was achieved by seven radiologists newly learning the procedures after performing 20 CVPS implantations. Total costs per implantation were €242 (CVPS) and €201 (PICC lines). Conclusion Interventional radiologic implantations of CVPS and PICC lines are well-established procedures, easy to learn by residents, and can be implanted at low costs.

Analysis of the learning curve for pre-cut corneal specimens in preparation for lamellar transplantation: a prospective, single-centre, consecutive case series prepared at the Lions New South Wales Eye Bank.

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Martin, Aifric Isabel; Devasahayam, Rajnesh; Hodge, Christopher; Cooper, Simon; Sutton, Gerard L

2017-09-01

This study is the first paper to establish a learning curve by a single technician. Preparation of pre-cut corneal endothelial grafts commenced at Lions New South Wales Eye Bank in December 2014. The primary objective of this study was to review the safety and reliability of the preparation method during the first year of production. This is a hospital-based, prospective case series. There were 234 consecutive donor corneal lenticules. Donor lenticules were prepared by a single operator using a linear cutting microkeratome. Immediately prior to cutting, central corneal thickness values were recorded. Measurements of the corneal bed were taken immediately following lenticule preparation. Outcomes were separated by blade sizes, and intended thickness was compared to actual thickness for each setting. Early specimens were compared to later ones to assess for a learning curve within the technique. The main parameter measured is the mean difference from intended lamellar cut thickness. The mean final cut thickness was 122.36 ± 20.35 μm, and the mean difference from intended cut was 30.17 ± 37.45 μm. No significant difference was found between results achieved with early specimens versus those achieved with later specimens (P = 0.425). Thin, reproducible endothelial grafts can routinely be produced by trained technicians at their respective eye banks without significant concerns for an extended learning curve. This service can reduce perioperative surgical complexity, required surgical paraphernalia and theatre times. The consistent preparation of single-pass, ultrathin pre-cut corneas may have additional advantages for surgeons seeking to introduce lamellar techniques. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

Spaghetti Sine Curves: Virtual Environments for Reasoning and Sense Making

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Özgün-Koca, S. Asli; Edwards, Michael Todd; Meagher, Michael

2013-01-01

In a recent collaboration with an area high school teacher, the authors were asked to develop an introductory sinusoidal curves lesson for a group of second-year algebra students. Because the topic was abstract and unfamiliar to these tenth graders, they looked for hands-on lessons to support their learning. One lesson that they found, which they…

Use of the cumulative sum method (CUSUM) to assess the learning curves of ultrasound-guided continuous femoral nerve block.

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Kollmann-Camaiora, A; Brogly, N; Alsina, E; Gilsanz, F

2017-10-01

Although ultrasound is a basic competence for anaesthesia residents (AR) there is few data available on the learning process. This prospective observational study aims to assess the learning process of ultrasound-guided continuous femoral nerve block and to determine the number of procedures that a resident would need to perform in order to reach proficiency using the cumulative sum (CUSUM) method. We recruited 19 AR without previous experience. Learning curves were constructed using the CUSUM method for ultrasound-guided continuous femoral nerve block considering 2 success criteria: a decrease of pain score>2 in a [0-10] scale after 15minutes, and time required to perform it. We analyse data from 17 AR for a total of 237 ultrasound-guided continuous femoral nerve blocks. 8/17 AR became proficient for pain relief, however all the AR who did more than 12 blocks (8/8) became proficient. As for time of performance 5/17 of AR achieved the objective of 12minutes, however all the AR who did more than 20 blocks (4/4) achieved it. The number of procedures needed to achieve proficiency seems to be 12, however it takes more procedures to reduce performance time. The CUSUM methodology could be useful in training programs to allow early interventions in case of repeated failures, and develop competence-based curriculum. Copyright © 2017 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

Handbook of elliptic and hyperelliptic curve cryptography

CERN Document Server

Cohen, Henri; Avanzi, Roberto; Doche, Christophe; Lange, Tanja; Nguyen, Kim; Vercauteren, Frederik

2005-01-01

… very comprehensive coverage of this vast subject area … a useful and essential treatise for anyone involved in elliptic curve algorithms … this book offers the opportunity to grasp the ECC technology with a diversified and comprehensive perspective. … This book will remain on my shelf for a long time and will land on my desk on many occasions, if only because the coverage of the issues common to factoring and discrete log cryptosystems is excellent.-IACR Book Reviews, June 2011… the book is designed for people who are working in the area and want to learn more about a specific issue. The chapters are written to be relatively independent so that readers can focus on the part of interest for them. Such readers will be grateful for the excellent index and extensive bibliography. … the handbook covers a wide range of topics and will be a valuable reference for researchers in curve-based cryptography. -Steven D. Galbraith, Mathematical Reviews, Issue 2007f.

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models.

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Ledonne, Norman C; Rissolo, Kevin; Bulgarelli, James; Tini, Leonard

2011-02-07

Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

Ensemble Learning Method for Outlier Detection and its Application to Astronomical Light Curves

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Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Chen, Wesley

2016-09-01

Outlier detection is necessary for automated data analysis, with specific applications spanning almost every domain from financial markets to epidemiology to fraud detection. We introduce a novel mixture of the experts outlier detection model, which uses a dynamically trained, weighted network of five distinct outlier detection methods. After dimensionality reduction, individual outlier detection methods score each data point for “outlierness” in this new feature space. Our model then uses dynamically trained parameters to weigh the scores of each method, allowing for a finalized outlier score. We find that the mixture of experts model performs, on average, better than any single expert model in identifying both artificially and manually picked outliers. This mixture model is applied to a data set of astronomical light curves, after dimensionality reduction via time series feature extraction. Our model was tested using three fields from the MACHO catalog and generated a list of anomalous candidates. We confirm that the outliers detected using this method belong to rare classes, like Novae, He-burning, and red giant stars; other outlier light curves identified have no available information associated with them. To elucidate their nature, we created a website containing the light-curve data and information about these objects. Users can attempt to classify the light curves, give conjectures about their identities, and sign up for follow up messages about the progress made on identifying these objects. This user submitted data can be used further train of our mixture of experts model. Our code is publicly available to all who are interested.

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models

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LeDonne Norman C

2011-02-01

Full Text Available Abstract Background Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI curves via the SALI curve integral (SCI as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. Results The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. Conclusion The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

The influence of prior multiport experience on the learning curve for single-port thoracoscopic lobectomy: a multicentre comparative study†.

Science.gov (United States)

Martin-Ucar, Antonio E; Aragon, Javier; Bolufer Nadal, Sergio; Galvez Munoz, Carlos; Luo, Qigang; Perez Mendez, Itzel; Sihoe, Alan D L; Socci, Laura

2017-06-01

Competency in video-assisted thoracoscopic (VATS) lobectomy is estimated to be reached after the surgeon completes 50 cases. We wanted to explore the impact of competency in performing multiport VATS lobectomies on completing the needed number of single-port VATS. In a retrospective multicentre study, 6 individual surgeons (3 with previous competency in multiport VATS lobectomy and 3 without) submitted their first 50 cases of single-port VATS lobectomies. Extended and sublobar resections were excluded. Pre-, peri- and postoperative data were compared between the groups of surgeons. Chi-square and Wilcoxon's rank tests were used. The less experienced surgeons had previously attended dedicated training courses and visited with experts. A total of 300 cases were included [150 in Group A (surgeons with previous experience performing multiport VATS) and 150 in Group B (surgeons without extensive experience performing multiport VATS)]. Surgeons in Group B performed significantly more elective open lobectomies during their learning curve period than surgeons of Group A (58 vs 1). Patients in Group B were older and had more risk factors. There were 3 in-hospital deaths (respiratory failure, sepsis and fatal stroke). There were no differences between the groups in operative time, intensive care unit admissions, hospital stay, total complications, tumour size or number of N2 stations explored. Only the duration of intercostal drainage (2 vs 3 days, 0.012), incidence of respiratory tract infections (1% vs 7%, P  = 0.002) and conversion rates (4% vs 12%, P  = 0.018) were better in Group A. Patients characteristics played a role in the development of respiratory infections and longer drainage times but not in the need for conversion. Overall, postoperative outcomes during the learning curve period for single-port VATS lobectomies are not noticeably affected by previous multiport VATS experience. Less experienced surgeons were more selective in order to achieve

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

International Nuclear Information System (INIS)

Sanders, N. E.; Soderberg, A. M.; Betancourt, M.

2015-01-01

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

Energy Technology Data Exchange (ETDEWEB)

Sanders, N. E.; Soderberg, A. M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Betancourt, M., E-mail: nsanders@cfa.harvard.edu [Department of Statistics, University of Warwick, Coventry CV4 7AL (United Kingdom)

2015-02-10

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST.

Analyzing price and efficiency dynamics of large appliances with the experience curve approach

International Nuclear Information System (INIS)

Weiss, Martin; Patel, Martin K.; Junginger, Martin; Blok, Kornelis

2010-01-01

Large appliances are major power consumers in households of industrialized countries. Although their energy efficiency has been increasing substantially in past decades, still additional energy efficiency potentials exist. Energy policy that aims at realizing these potentials faces, however, growing concerns about possible adverse effects on commodity prices. Here, we address these concerns by applying the experience curve approach to analyze long-term price and energy efficiency trends of three wet appliances (washing machines, laundry dryers, and dishwashers) and two cold appliances (refrigerators and freezers). We identify a robust long-term decline in both specific price and specific energy consumption of large appliances. Specific prices of wet appliances decline at learning rates (LR) of 29±8% and thereby much faster than those of cold appliances (LR of 9±4%). Our results demonstrate that technological learning leads to substantial price decline, thus indicating that the introduction of novel and initially expensive energy efficiency technologies does not necessarily imply adverse price effects in the long term. By extending the conventional experience curve approach, we find a steady decline in the specific energy consumption of wet appliances (LR of 20-35%) and cold appliances (LR of 13-17%). Our analysis suggests that energy policy might be able to bend down energy experience curves. (author)

Solar cost reduction through technical improvements: the concepts of learning and experience

Energy Technology Data Exchange (ETDEWEB)

Krawiec, F.; Flaim, T.

1979-10-01

The concepts of learning and experience are reviewed and their usefulness for predicting the future costs of solar technologies are evaluated. The literature review indicated that the cost estimates for solar energy technologies are typically made assuming a fixed production process, characterized by standard capacity factors, overhead, and labor costs. The learning curve is suggested as a generalization of the costs of potential solar energy systems. The concept of experience is too ambiguous to be useful for cost estimation. There is no logical reason to believe that costs will decline purely as a function of cumulative production, and experience curves do not allow the analyst to identify logical sources of cost reduction directly. The procedures for using learning and aggregated cost curves to estimate the costs of solar technologies are outlined. It is recommended that production histories of analogous products and processes are analyzed and the learning and cost curves for these surrogates are estimated. These curves, if judged applicable, can be used to predict the cost reductions in manufacturing solar energy technologies.

The role of experience curves for setting MEPS for appliances

International Nuclear Information System (INIS)

Siderius, Hans-Paul

2013-01-01

Minimum efficiency performance standards (MEPS) are an important policy instrument to raise the efficiency of products. In most schemes the concept of life cycle costs (LCC) is used to guide setting the MEPS levels. Although a large body of literature shows that product cost is decreasing with increasing cumulative production, the experience curve, this is currently not used for setting MEPS. This article shows how to integrate the concept of the experience curve into LCC calculations for setting MEPS in the European Union and applies this to household laundry driers, refrigerator-freezers and televisions. The results indicate that for driers and refrigerator-freezers at least twice the energy savings compared to the current approach can be achieved. These products also show that energy label classes can successfully be used for setting MEPS. For televisions an experience curve is provided, showing a learning rate of 29%. However, television prices do not show a relation with energy efficiency but are to a large extent determined by the time the product is placed on the market. This suggests to policy makers that for televisions and other products with a short (re)design and market cycle timing is more important than the MEPS levels itself. - Highlights: • We integrate experience curves into life cycle cost calculations for MEPS. • For driers and refrigerators this results in at least twice the energy savings. • For flat panel televisions an experience curve is provided

Prototype-based active learning for lemmatization

CSIR Research Space (South Africa)

Daelemans, W

2009-09-01

Full Text Available ] and Word Length [Long to Short] with the prototypical curves (e.g. Word Frequency [High to Low] and [Word Length Short to Long]). (With regard to the learning curves representing word frequency, refer to 4.1 for an explanation of why [High to Low... of language usage [15]. Secondly, in memory-based language processing [16] it has been argued, on the basis of com- parative machine learning experiments on natural lan- guage processing data, that exceptions are crucial for obtaining high generalization...

Stenting for curved lesions using a novel curved balloon: Preliminary experimental study.

Science.gov (United States)

Tomita, Hideshi; Higaki, Takashi; Kobayashi, Toshiki; Fujii, Takanari; Fujimoto, Kazuto

2015-08-01

Stenting may be a compelling approach to dilating curved lesions in congenital heart diseases. However, balloon-expandable stents, which are commonly used for congenital heart diseases, are usually deployed in a straight orientation. In this study, we evaluated the effect of stenting with a novel curved balloon considered to provide better conformability to the curved-angled lesion. In vitro experiments: A Palmaz Genesis(®) stent (Johnson & Johnson, Cordis Co, Bridgewater, NJ, USA) mounted on the Goku(®) curve (Tokai Medical Co. Nagoya, Japan) was dilated in vitro to observe directly the behavior of the stent and balloon assembly during expansion. Animal experiment: A short Express(®) Vascular SD (Boston Scientific Co, Marlborough, MA, USA) stent and a long Express(®) Vascular LD stent (Boston Scientific) mounted on the curved balloon were deployed in the curved vessel of a pig to observe the effect of stenting in vivo. In vitro experiments: Although the stent was dilated in a curved fashion, stent and balloon assembly also rotated conjointly during expansion of its curved portion. In the primary stenting of the short stent, the stent was dilated with rotation of the curved portion. The excised stent conformed to the curved vessel. As the long stent could not be negotiated across the mid-portion with the balloon in expansion when it started curving, the mid-portion of the stent failed to expand fully. Furthermore, the balloon, which became entangled with the stent strut, could not be retrieved even after complete deflation. This novel curved balloon catheter might be used for implantation of the short stent in a curved lesion; however, it should not be used for primary stenting of the long stent. Post-dilation to conform the stent to the angled vessel would be safer than primary stenting irrespective of stent length. Copyright © 2014 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

A new approach to the analysis of Mira light curves

International Nuclear Information System (INIS)

Mennessier, M.O.; Barthes, D.; Mattei, J.A.

1990-01-01

Two different but complementary methods for predicting Mira luminosities are presented. One method is derived from a Fourier analysis, it requires performing deconvolution, and its results are not certain due to the inherent instability of deconvolution problems. The other method is a learning method utilizing artificial intelligence techniques where a light curve is presented as an ordered sequence of pseudocycles, and rules are learned by linking the characteristics of several consecutive pseudocycles to one characteristic of the future cycle. It is observed that agreement between these methods is obtainable when it is possible to eliminate similar false frequencies from the preliminary power spectrum and to improve the degree of confidence in the rules

Curve Boxplot: Generalization of Boxplot for Ensembles of Curves.

Science.gov (United States)

Mirzargar, Mahsa; Whitaker, Ross T; Kirby, Robert M

2014-12-01

In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.

JUMPING THE CURVE

Directory of Open Access Journals (Sweden)

René Pellissier

2012-01-01

Full Text Available This paper explores the notion ofjump ing the curve,following from Handy 's S-curve onto a new curve with new rules policies and procedures. . It claims that the curve does not generally lie in wait but has to be invented by leadership. The focus of this paper is the identification (mathematically and inferentially ofthat point in time, known as the cusp in catastrophe theory, when it is time to change - pro-actively, pre-actively or reactively. These three scenarios are addressed separately and discussed in terms ofthe relevance ofeach.

Dual Smarandache Curves of a Timelike Curve lying on Unit dual Lorentzian Sphere

OpenAIRE

Kahraman, Tanju; Hüseyin Ugurlu, Hasan

2016-01-01

In this paper, we give Darboux approximation for dual Smarandache curves of time like curve on unit dual Lorentzian sphere. Firstly, we define the four types of dual Smarandache curves of a timelike curve lying on dual Lorentzian sphere.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Retroperitoneal laparoscopic nephrectomy: the effect of the learning curve, and concentrating expertise, on operating times.

Science.gov (United States)

Skinner, Adrian; Maoate, Kiki; Beasley, Spencer

2010-05-01

Laparoscopic nephrectomy is an accepted alternative to open nephrectomy. We analyzed our first 80 procedures of laparoscopic nephrectomy to evaluate the effect of experience and configuration of service on operative times. A retrospective review of 80 consecutive children who underwent retroperitoneal laparoscopic nephrectomy or heminephrectomy during an 11-year period from 1997 at Christchurch Hospital (Christchurch, New Zealand) was conducted. Operative times, in relation to the experience of the surgeon for this procedure, were analyzed. Four surgeons, assisted by an annually rotating trainee registrar, performed the procedure in 26 girls and 54 boys (range, 8 months to 15 years). Operating times ranged from 38 to 225 minutes (mean, 104). The average operative time fell from 105 to 90 minutes. One surgeon performed 40% of the procedures and assisted with a further 55%. The operative times for all surgeons showed a tendency to reduce, but this was not marked. Most procedures were performed by two surgeons working together, although one surgeon was involved in the majority of cases. The lead surgeon is often assisted by a fellow consultant colleague. Operative times were influenced by experience, but not markedly so. The shorter operative times and minimal "learning curve," compared with other reported series, may, in part, be due to the involvement of two surgeons experienced in laparoscopy for the majority of cases.

Accuracy of progress ratios determined from experience curves: the case of photovoltaic technology development

NARCIS (Netherlands)

van Sark, W.G.J.H.M.|info:eu-repo/dai/nl/074628526; Alsema, E.A.|info:eu-repo/dai/nl/073416258; Junginger, H.M.|info:eu-repo/dai/nl/202130703; de Moor, H.H.C.; Schaeffer, G.J.

2008-01-01

Learning curves are extensively used in policy and scenario studies. Progress ratios (PRs) are derived from historical data and are used for forecasting cost development of many technologies, including photovoltaics (PV). Forecasts are highly sensitive to uncertainties in the PR. A PR usually is

ECM using Edwards curves

DEFF Research Database (Denmark)

Bernstein, Daniel J.; Birkner, Peter; Lange, Tanja

2013-01-01

-arithmetic level are as follows: (1) use Edwards curves instead of Montgomery curves; (2) use extended Edwards coordinates; (3) use signed-sliding-window addition-subtraction chains; (4) batch primes to increase the window size; (5) choose curves with small parameters and base points; (6) choose curves with large...

Efficacy of tension-free vaginal tape compared with transobturator tape in the treatment of stress urinary incontinence in women: analysis of learning curve, perioperative changes of voiding function

Science.gov (United States)

2011-01-01

Background In this study, by comparing TVT surgery and TOT surgery for stress urinary incontinence in women, the characteristics and learning curves of both operative methods were studied. Methods A total of 83 women with stress urinary incontinence treated with tension-free vaginal tape (TVT) (n = 38) or transobturator tape (TOT) (n = 45) at Saiseikai Central Hospital between April 2004 and September 2009 were included. We compare the outcomes and learning curves between TVT surgery and TOT surgery. In statistical analysis, Student's t test, Fisher's exact test, and Mann-Whitney's U test were used. Results The surgical durations were 37.4 ± 15.7 minutes with TVT surgery and 31.0 ± 8.3 minutes with TOT surgery. A longer period of time was required for TVT surgery (p = 0.025). The residual urine at post-operative day 1 was higher in TVT surgery (25.9 ± 44.2 ml) than in TOT surgery (10.6 ± 19.2 ml) (p = 0.0452). The surgical duration of TVT surgery was shortened after the operator had performed 15 operations (p = 0.019). Conclusions In comparison of TVT surgery and TOT surgery, the surgical duration of TVT surgery was longer and the residual urine of TVT surgery was higher at post-operative day 1. Surgical experience could shorten the duration of TVT surgery. PMID:21726448

Efficacy of tension-free vaginal tape compared with transobturator tape in the treatment of stress urinary incontinence in women: analysis of learning curve, perioperative changes of voiding function

Directory of Open Access Journals (Sweden)

Kanai Kunimitsu

2011-07-01

Full Text Available Abstract Background In this study, by comparing TVT surgery and TOT surgery for stress urinary incontinence in women, the characteristics and learning curves of both operative methods were studied. Methods A total of 83 women with stress urinary incontinence treated with tension-free vaginal tape (TVT (n = 38 or transobturator tape (TOT (n = 45 at Saiseikai Central Hospital between April 2004 and September 2009 were included. We compare the outcomes and learning curves between TVT surgery and TOT surgery. In statistical analysis, Student's t test, Fisher's exact test, and Mann-Whitney's U test were used. Results The surgical durations were 37.4 ± 15.7 minutes with TVT surgery and 31.0 ± 8.3 minutes with TOT surgery. A longer period of time was required for TVT surgery (p = 0.025. The residual urine at post-operative day 1 was higher in TVT surgery (25.9 ± 44.2 ml than in TOT surgery (10.6 ± 19.2 ml (p = 0.0452. The surgical duration of TVT surgery was shortened after the operator had performed 15 operations (p = 0.019. Conclusions In comparison of TVT surgery and TOT surgery, the surgical duration of TVT surgery was longer and the residual urine of TVT surgery was higher at post-operative day 1. Surgical experience could shorten the duration of TVT surgery.

Analyzing the Learning Path of US Shale Players by Using the Learning Curve Method

Directory of Open Access Journals (Sweden)

Jong-Hyun Kim

2017-12-01

Full Text Available The US shale exploration and production (E&P industry has grown since 2007 due to the development of new techniques such as hydraulic fracturing and horizontal drilling. As a result, the share of shale gas in the US natural gas production is almost 50%, and the share of tight oil in the US crude oil production is almost 52%. Even though oil and gas prices decreased sharply in 2014, the production amounts of shale gas and tight oil increased between 2014 and 2015. We show that many players in the US shale E&P industry succeeded in decreasing their production costs to maintain their business activity and production. However, most of the companies in the US petroleum E&P industry incurred losses in 2015 and 2016. Furthermore, crude oil and natural gas prices could not rebound to their 2015 price levels. Therefore, many companies in the US petroleum E&P industry need to increase their productivity to overcome the low commodity prices situation. Hence, to test the change in their productivity and analyze their ability to survive in the petroleum industry, this study calculates the learning rate using the US shale E&P players’ annual report data from 2008 to 2016. The result of the calculation is that the long-term learning rate is 1.87% and the short-term learning rate is 3.16%. This indicates a change in the technological development trend.

The training and learning process of transseptal puncture using a modified technique.

Science.gov (United States)

Yao, Yan; Ding, Ligang; Chen, Wensheng; Guo, Jun; Bao, Jingru; Shi, Rui; Huang, Wen; Zhang, Shu; Wong, Tom

2013-12-01

As the transseptal (TS) puncture has become an integral part of many types of cardiac interventional procedures, its technique that was initial reported for measurement of left atrial pressure in 1950s, continue to evolve. Our laboratory adopted a modified technique which uses only coronary sinus catheter as the landmark to accomplishing TS punctures under fluoroscopy. The aim of this study is prospectively to evaluate the training and learning process for TS puncture guided by this modified technique. Guided by the training protocol, TS puncture was performed in 120 consecutive patients by three trainees without previous personal experience in TS catheterization and one experienced trainer as a controller. We analysed the following parameters: one puncture success rate, total procedure time, fluoroscopic time, and radiation dose. The learning curve was analysed using curve-fitting methodology. The first attempt at TS crossing was successful in 74 (82%), a second attempt was successful in 11 (12%), and 5 patients failed to puncture the interatrial septal finally. The average starting process time was 4.1 ± 0.8 min, and the estimated mean learning plateau was 1.2 ± 0.2 min. The estimated mean learning rate for process time was 25 ± 3 cases. Important aspects of learning curve can be estimated by fitting inverse curves for TS puncture. The study demonstrated that this technique was a simple, safe, economic, and effective approach for learning of TS puncture. Base on the statistical analysis, approximately 29 TS punctures will be needed for trainee to pass the steepest area of learning curve.

Analysis on learning curves of end-use appliances for the establishment of price-sensitivity load model in competitive electricity market

Energy Technology Data Exchange (ETDEWEB)

Hwang, Sung Wook; Kim, Jung Hoon [Hongik University (Korea); Song, Kyung Bin [Keimyung University (Korea); Choi, Joon Young [Jeonju University (Korea)

2001-07-01

The change of the electricity charge from cost base to price base due to the introduction to the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding to-price loads, the price-sensitive load model is needed. And the development of state-of- the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns. (author). 6 refs., 4 figs., 4 tabs.

Learning of couplings for random asymmetric kinetic Ising models revisited: random correlation matrices and learning curves

International Nuclear Information System (INIS)

Bachschmid-Romano, Ludovica; Opper, Manfred

2015-01-01

We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the nontrivial equal time correlations between spins induced by the dynamics for the speed of learning. These correlations become more important as the spin’s stochasticity is decreased. We also analyse the deviation of the estimation error (paper)

Evaluation of the learning curve for thulium laser enucleation of the prostate with the aid of a simulator tool but without tutoring: comparison of two surgeons with different levels of endoscopic experience.

Science.gov (United States)

Saredi, Giovanni; Pirola, Giacomo Maria; Pacchetti, Andrea; Lovisolo, Jon Alexander; Borroni, Giacomo; Sembenini, Federico; Marconi, Alberto Mario

2015-06-09

The aim of this study was to determine the learning curve for thulium laser enucleation of the prostate (ThuLEP) for two surgeons with different levels of urological endoscopic experience. From June 2012 to August 2013, ThuLEP was performed on 100 patients in our institution. We present the results of a prospective evaluation during which we analyzed data related to the learning curves for two surgeons of different levels of experience. The prostatic adenoma volumes ranged from 30 to 130 mL (average 61.2 mL). Surgeons A and B performed 48 and 52 operations, respectively. Six months after surgery, all patients were evaluated with the International Prostate Symptom Score questionnaire, uroflowmetry, and prostate-specific antigen test. Introduced in 2010, ThuLEP consists of blunt enucleation of the prostatic apex and lobes using the sheath of the resectoscope. This maneuver allows clearer visualization of the enucleation plane and precise identification of the prostatic capsule. These conditions permit total resection of the prostatic adenoma and coagulation of small penetrating vessels, thereby reducing the laser emission time. Most of the complications in this series were encountered during morcellation, which in some cases was performed under poor vision because of venous bleeding due to surgical perforation of the capsule during enucleation. Based on this analysis, we concluded that it is feasible for laser-naive urologists with endoscopic experience to learn to perform ThuLEP without tutoring. Those statements still require further validation in larger multicentric study cohort by several surgeon. The main novelty during the learning process was the use of a simulator that faithfully reproduced all of the surgical steps in prostates of various shapes and volumes.

From Experiment to Theory: What Can We Learn from Growth Curves?

Science.gov (United States)

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.

Science.gov (United States)

Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G

2012-05-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program

International Nuclear Information System (INIS)

Afouxenidis, D.; Polymeris, G. S.; Tsirliganis, N. C.; Kitis, G.

2012-01-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the Glow Curve Analysis Intercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters. (authors)

Learning curves of theta/beta neurofeedback in children with ADHD

NARCIS (Netherlands)

Janssen, T.W.P.; Bink, M.; Weeda, W.D.; Gelade, K.N.; Van, Mourik R.; Maras, A.; Oosterlaan, J.

2017-01-01

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and

Approximation by planar elastic curves

DEFF Research Database (Denmark)

Brander, David; Gravesen, Jens; Nørbjerg, Toke Bjerge

2016-01-01

We give an algorithm for approximating a given plane curve segment by a planar elastic curve. The method depends on an analytic representation of the space of elastic curve segments, together with a geometric method for obtaining a good initial guess for the approximating curve. A gradient......-driven optimization is then used to find the approximating elastic curve....

Learn ggplot2 using Shiny App

CERN Document Server

Moon, Keon-Woong

2016-01-01

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual—"integrating" R, ggplot2, and Shiny—introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to bec...

Technological learning in bioenergy systems

International Nuclear Information System (INIS)

Junginger, Martin; Visser, Erika de; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, Andre; Turkenburg, Wim

2006-01-01

The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions

Bragg Curve Spectroscopy

International Nuclear Information System (INIS)

Gruhn, C.R.

1981-05-01

An alternative utilization is presented for the gaseous ionization chamber in the detection of energetic heavy ions, which is called Bragg Curve Spectroscopy (BCS). Conceptually, BCS involves using the maximum data available from the Bragg curve of the stopping heavy ion (HI) for purposes of identifying the particle and measuring its energy. A detector has been designed that measures the Bragg curve with high precision. From the Bragg curve the range from the length of the track, the total energy from the integral of the specific ionization over the track, the dE/dx from the specific ionization at the beginning of the track, and the Bragg peak from the maximum of the specific ionization of the HI are determined. This last signal measures the atomic number, Z, of the HI unambiguously

From the curve of the snake, and the scene of the crocodile: musings on learning and losing space, place and body

Directory of Open Access Journals (Sweden)

Susanne Gannon

2012-12-01

Full Text Available Where else can educational research begin and end, if not with the body of the researcher, if not with the particular material/ corporeal/ affective assemblages that this body is and has been part of? This paper traces the mutual constitution of bodies, identities and landscapes through memory as the body of this educator travels through multiple scenes of geo-spatial-temporal movement, and down the east coast of Australia. This movement parallels the movement from being a school teacher to becoming an academic. Throughout the paper landscape is foregrounded, and the body in landscape is evoked through poetic and literary modes of writing around the themes of learning and losing. The body in landscape is not merely the body of the writer. Other bodies in the landscape include ‘the curve of the snake’ - the row of protective hills that were said to protect her tropical home from cyclones – and the ‘scene of the crocodile’ – the rock that hung over the valley she passed on her way to school that she had learned of from Indigenous teachers. The political and ethical consequences of memory work, of body and place writing, and of genres of writing in educational research, are also considered. The paper argues for an embodied and reflexive literacy of place that incorporates multiple modes of knowing, being and writing.

Learning neuroendoscopy with an exoscope system (video telescopic operating monitor): Early clinical results.

Science.gov (United States)

Parihar, Vijay; Yadav, Y R; Kher, Yatin; Ratre, Shailendra; Sethi, Ashish; Sharma, Dhananjaya

2016-01-01

Steep learning curve is found initially in pure endoscopic procedures. Video telescopic operating monitor (VITOM) is an advance in rigid-lens telescope systems provides an alternative method for learning basics of neuroendoscopy with the help of the familiar principle of microneurosurgery. The aim was to evaluate the clinical utility of VITOM as a learning tool for neuroendoscopy. Video telescopic operating monitor was used 39 cranial and spinal procedures and its utility as a tool for minimally invasive neurosurgery and neuroendoscopy for initial learning curve was studied. Video telescopic operating monitor was used in 25 cranial and 14 spinal procedures. Image quality is comparable to endoscope and microscope. Surgeons comfort improved with VITOM. Frequent repositioning of scope holder and lack of stereopsis is initial limiting factor was compensated for with repeated procedures. Video telescopic operating monitor is found useful to reduce initial learning curve of neuroendoscopy.

The new courses of ethanol production in Brazil: an analysis from learning curves; Os novos rumos da producao de alcool combustivel no Brasil: uma analise a partir de curvas de aprendizagem

Energy Technology Data Exchange (ETDEWEB)

Pereira, Junior, Amaro Olimpio [Empresa de Pesquisa Energetica (EPE), Brasilia, DF (Brazil); Pereira, Andre Santos [Centre de Recherche sur Environement et Developement (CIRED), Paris (France); Mendonca, Marco Aurelio [Instituto de Pesquisa Economica Aplicada (IPEA), Brasilia, DF (Brazil); Costa, Ricardo Cunha da [Universidade Federal do Rio de Janeiro (PPE/COPPE/UFRJ), RJ (Brazil). Coordenacao do Programa de Pos-Graduacao em Engenharia. Programa de Pos-Graduacao em Planejamento Energetico

2008-07-01

PROALCOOL is known internationally as the most successful biofuel promotion program. Prior analysis of the effectiveness of such a program is fundamental to formulation of public policy, not only in the area of energy, but in all sectors of the economy. The article applies learning curve methodology to evaluate the ethanol market in Brazil in order to give an idea about the effort, in terms of investments, required for its advancement. (author)

A review of learning rates for electricity supply technologies

International Nuclear Information System (INIS)

Rubin, Edward S.; Azevedo, Inês M.L.; Jaramillo, Paulina; Yeh, Sonia

2015-01-01

A variety of mathematical models have been proposed to characterize and quantify the dependency of electricity supply technology costs on various drivers of technological change. The most prevalent model form, called a learning curve, or experience curve, is a log-linear equation relating the unit cost of a technology to its cumulative installed capacity or electricity generated. This one-factor model is also the most common method used to represent endogenous technical change in large-scale energy-economic models that inform energy planning and policy analysis. A characteristic parameter is the “learning rate,” defined as the fractional reduction in cost for each doubling of cumulative production or capacity. In this paper, a literature review of the learning rates reported for 11 power generation technologies employing an array of fossil fuels, nuclear, and renewable energy sources is presented. The review also includes multi-factor models proposed for some energy technologies, especially two-factor models relating cost to cumulative expenditures for research and development (R&D) as well as the cumulative installed capacity or electricity production of a technology. For all technologies studied, we found substantial variability (as much as an order of magnitude) in reported learning rates across different studies. Such variability is not readily explained by systematic differences in the time intervals, geographic regions, choice of independent variable, or other parameters of each study. This uncertainty in learning rates, together with other limitations of current learning curve formulations, suggests the need for much more careful and systematic examination of the influence of how different factors and assumptions affect policy-relevant outcomes related to the future choice and cost of electricity supply and other energy technologies. - Highlights: • We review models explaining the cost of 11 electricity supply technologies. • The most prevalent model

Contractibility of curves

Directory of Open Access Journals (Sweden)

Janusz Charatonik

1991-11-01

Full Text Available Results concerning contractibility of curves (equivalently: of dendroids are collected and discussed in the paper. Interrelations tetween various conditions which are either sufficient or necessary for a curve to be contractible are studied.

Roc curves for continuous data

CERN Document Server

Krzanowski, Wojtek J

2009-01-01

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamental theory of ROC curvesThe book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated. Further building on the theory, the authors prese

Learning Curves: Making Quality Online Health Information Available at a Fitness Center

OpenAIRE

Dobbins, Montie T.; Tarver, Talicia; Adams, Mararia; Jones, Dixie A.

2012-01-01

Meeting consumer health information needs can be a challenge. Research suggests that women seek health information from a variety of resources, including the Internet. In an effort to make women aware of reliable health information sources, the Louisiana State University Health Sciences Center – Shreveport Medical Library engaged in a partnership with a franchise location of Curves International, Inc. This article will discuss the project, its goals and its challenges.

Learning Curves: Making Quality Online Health Information Available at a Fitness Center.

Science.gov (United States)

Dobbins, Montie T; Tarver, Talicia; Adams, Mararia; Jones, Dixie A

2012-01-01

Meeting consumer health information needs can be a challenge. Research suggests that women seek health information from a variety of resources, including the Internet. In an effort to make women aware of reliable health information sources, the Louisiana State University Health Sciences Center - Shreveport Medical Library engaged in a partnership with a franchise location of Curves International, Inc. This article will discuss the project, its goals and its challenges.

Atlas of stress-strain curves

CERN Document Server

2002-01-01

The Atlas of Stress-Strain Curves, Second Edition is substantially bigger in page dimensions, number of pages, and total number of curves than the previous edition. It contains over 1,400 curves, almost three times as many as in the 1987 edition. The curves are normalized in appearance to aid making comparisons among materials. All diagrams include metric (SI) units, and many also include U.S. customary units. All curves are captioned in a consistent format with valuable information including (as available) standard designation, the primary source of the curve, mechanical properties (including hardening exponent and strength coefficient), condition of sample, strain rate, test temperature, and alloy composition. Curve types include monotonic and cyclic stress-strain, isochronous stress-strain, and tangent modulus. Curves are logically arranged and indexed for fast retrieval of information. The book also includes an introduction that provides background information on methods of stress-strain determination, on...

Post-operative 3D CT feedback improves accuracy and precision in the learning curve of anatomic ACL femoral tunnel placement.

Science.gov (United States)

Sirleo, Luigi; Innocenti, Massimo; Innocenti, Matteo; Civinini, Roberto; Carulli, Christian; Matassi, Fabrizio

2018-02-01

tunnel placement in order to obtain anatomic ACL reconstruction and helps to reduce also arthroscopic time and learning curve. For clinical relevance, trainee-surgeons should use feedback from post-operative 3DCT to learn anatomic ACL femoral tunnel placement and apply it appropriately. Consecutive case series, Level IV.

Can Online Learning Bend the Higher Education Cost Curve?

OpenAIRE

David J. Deming; Claudia Goldin; Lawrence F. Katz; Noam Yuchtman

2015-01-01

We examine whether online learning technologies have led to lower prices in higher education. Using data from the Integrated Postsecondary Education Data System, we show that online education is concentrated in large for-profit chains and less-selective public institutions. We find that colleges with a higher share of online students charge lower tuition prices. We present evidence of declining real and relative prices for full-time undergraduate online education from 2006 to 2013. Although t...

Tornado-Shaped Curves

Science.gov (United States)

Martínez, Sol Sáez; de la Rosa, Félix Martínez; Rojas, Sergio

2017-01-01

In Advanced Calculus, our students wonder if it is possible to graphically represent a tornado by means of a three-dimensional curve. In this paper, we show it is possible by providing the parametric equations of such tornado-shaped curves.

A versatile curve-fit model for linear to deeply concave rank abundance curves

NARCIS (Netherlands)

Neuteboom, J.H.; Struik, P.C.

2005-01-01

A new, flexible curve-fit model for linear to concave rank abundance curves was conceptualized and validated using observational data. The model links the geometric-series model and log-series model and can also fit deeply concave rank abundance curves. The model is based ¿ in an unconventional way

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

In-Vehicle Dynamic Curve-Speed Warnings at High-Risk Rural Curves

Science.gov (United States)

2018-03-01

Lane-departure crashes at horizontal curves represent a significant portion of fatal crashes on rural Minnesota roads. Because of this, solutions are needed to aid drivers in identifying upcoming curves and inform them of a safe speed at which they s...

SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.

Science.gov (United States)

Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga

2013-01-01

High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.

The curve shortening problem

CERN Document Server

Chou, Kai-Seng

2001-01-01

Although research in curve shortening flow has been very active for nearly 20 years, the results of those efforts have remained scattered throughout the literature. For the first time, The Curve Shortening Problem collects and illuminates those results in a comprehensive, rigorous, and self-contained account of the fundamental results.The authors present a complete treatment of the Gage-Hamilton theorem, a clear, detailed exposition of Grayson''s convexity theorem, a systematic discussion of invariant solutions, applications to the existence of simple closed geodesics on a surface, and a new, almost convexity theorem for the generalized curve shortening problem.Many questions regarding curve shortening remain outstanding. With its careful exposition and complete guide to the literature, The Curve Shortening Problem provides not only an outstanding starting point for graduate students and new investigations, but a superb reference that presents intriguing new results for those already active in the field.

The learning curve for access creation in solo ultrasonography-guided percutaneous nephrolithotomy and the associated skills.

Science.gov (United States)

Yu, Weimin; Rao, Ting; Li, Xing; Ruan, Yuan; Yuan, Run; Li, Chenglong; Li, Haoyong; Cheng, Fan

2017-03-01

The aim of the current trial was to evaluate the learning curve of access creation through solo ultrasonography (US)-guided percutaneous nephrolithotomy (PCNL), and clarify the technical details of the procedure. We evaluated the first 240 solo US-guided PCNLs performed by one surgeon at our institution. The data including the puncture procedure, access characteristics, access-related complications and stone-free rates were assessed in four sequential groups. The puncture duration and number of times decreased from a mean of 4.4 min and 2.1 times for the first 60 patients to 1.3 min and 1.2 times for the last 60 patients. There was a significant decrease from 3.7 min and 1.8 times for the 61th-120th patients to 1.5 min and 1.3 times for the 121th-180th patients. All of the access-related severe bleeding appeared in the first 120 patients, while perforations only occurred in the first 60 patients. The stone-free rates were 68.3, 83.3, 90.0, and 93.3% for the four sequential groups. The increase in experience lead to an improvement in the puncture duration and times, which accompany with better stone-free rates and lower complications. We propose that 60 operations are sufficient to gain competency, and a cutoff point of 120 operations will allow the surgeon to achieve excellence in the solo US-guided PCNL.

What are the key drivers of MAC curves? A partial-equilibrium modelling approach for the UK

International Nuclear Information System (INIS)

Kesicki, Fabian

2013-01-01

Marginal abatement cost (MAC) curves are widely used for the assessment of costs related to CO 2 emissions reduction in environmental economics, as well as domestic and international climate policy. Several meta-analyses and model comparisons have previously been performed that aim to identify the causes for the wide range of MAC curves. Most of these concentrate on general equilibrium models with a focus on aspects such as specific model type and technology learning, while other important aspects remain almost unconsidered, including the availability of abatement technologies and level of discount rates. This paper addresses the influence of several key parameters on MAC curves for the United Kingdom and the year 2030. A technology-rich energy system model, UK MARKAL, is used to derive the MAC curves. The results of this study show that MAC curves are robust even to extreme fossil fuel price changes, while uncertainty around the choice of the discount rate, the availability of key abatement technologies and the demand level were singled out as the most important influencing factors. By using a different model type and studying a wider range of influencing factors, this paper contributes to the debate on the sensitivity of MAC curves. - Highlights: ► A partial-equilibrium model is employed to test key sensitivities of MAC curves. ► MAC curves are found to be robust to wide-ranging changes in fossil fuel prices. ► Most influencing factors are the discount rate, availability of key technologies. ► Further important uncertainty in MAC curves is related to demand changes

Part 5: Receiver Operating Characteristic Curve and Area under the Curve

Directory of Open Access Journals (Sweden)

Saeed Safari

2016-04-01

Full Text Available Multiple diagnostic tools are used by emergency physicians,every day. In addition, new tools are evaluated to obtainmore accurate methods and reduce time or cost of conventionalones. In the previous parts of this educationalseries, we described diagnostic performance characteristicsof diagnostic tests including sensitivity, specificity, positiveand negative predictive values, and likelihood ratios. Thereceiver operating characteristics (ROC curve is a graphicalpresentation of screening characteristics. ROC curve is usedto determine the best cutoff point and compare two or moretests or observers by measuring the area under the curve(AUC. In this part of our educational series, we explain ROCcurve and two methods to determine the best cutoff value.

Learning thoracoscopic lobectomy

DEFF Research Database (Denmark)

Petersen, René Horsleben; Hansen, Henrik Jessen

2010-01-01

Thoracoscopic (video-assisted thoracoscopic surgery (VATS)) lobectomy is a safe and effective method for treating early-stage lung cancer. Despite this, it is still not widely practised, which could be due to a shallow learning curve. We have evaluated the surgical outcome in a training programme...

Signature Curves Statistics of DNA Supercoils

OpenAIRE

Shakiban, Cheri; Lloyd, Peter

2004-01-01

In this paper we describe the Euclidean signature curves for two dimensional closed curves in the plane and their generalization to closed space curves. The focus will be on discrete numerical methods for approximating such curves. Further we will apply these numerical methods to plot the signature curves related to three-dimensional simulated DNA supercoils. Our primary focus will be on statistical analysis of the data generated for the signature curves of the supercoils. We will try to esta...

Method of construction spatial transition curve

Directory of Open Access Journals (Sweden)

S.V. Didanov

2013-04-01

Full Text Available Purpose. The movement of rail transport (speed rolling stock, traffic safety, etc. is largely dependent on the quality of the track. In this case, a special role is the transition curve, which ensures smooth insertion of the transition from linear to circular section of road. The article deals with modeling of spatial transition curve based on the parabolic distribution of the curvature and torsion. This is a continuation of research conducted by the authors regarding the spatial modeling of curved contours. Methodology. Construction of the spatial transition curve is numerical methods for solving nonlinear integral equations, where the initial data are taken coordinate the starting and ending points of the curve of the future, and the inclination of the tangent and the deviation of the curve from the tangent plane at these points. System solutions for the numerical method are the partial derivatives of the equations of the unknown parameters of the law of change of torsion and length of the transition curve. Findings. The parametric equations of the spatial transition curve are calculated by finding the unknown coefficients of the parabolic distribution of the curvature and torsion, as well as the spatial length of the transition curve. Originality. A method for constructing the spatial transition curve is devised, and based on this software geometric modeling spatial transition curves of railway track with specified deviations of the curve from the tangent plane. Practical value. The resulting curve can be applied in any sector of the economy, where it is necessary to ensure a smooth transition from linear to circular section of the curved space bypass. An example is the transition curve in the construction of the railway line, road, pipe, profile, flat section of the working blades of the turbine and compressor, the ship, plane, car, etc.

A Learning Algorithm based on High School Teaching Wisdom

OpenAIRE

Philip, Ninan Sajeeth

2010-01-01

A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate a student and to give them training on the examples for which they repeatedly fail, until, they can correctly answer all types of questions. This incremental learning procedure produces better learning curves by demanding the student to optimally dedicate their learning time on the failed examples. When used in machine learning, the algorithm is found to train a machine...

On the necessity of U-shaped learning.

Science.gov (United States)

Carlucci, Lorenzo; Case, John

2013-01-01

A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning English past tense) has become a central topic in the Cognitive Science debate about learning models. Antagonist models (e.g., connectionism versus nativism) are often judged on their ability of modeling or accounting for U-shaped behavior. The prior literature is mostly occupied with explaining how U-shaped behavior occurs. Instead, we are interested in the necessity of this kind of apparently inefficient strategy. We present and discuss a body of results in the abstract mathematical setting of (extensions of) Gold-style computational learning theory addressing a mathematically precise version of the following question: Are there learning tasks that require U-shaped behavior? All notions considered are learning in the limit from positive data. We present results about the necessity of U-shaped learning in classical models of learning as well as in models with bounds on the memory of the learner. The pattern emerges that, for parameterized, cognitively relevant learning criteria, beyond very few initial parameter values, U-shapes are necessary for full learning power! We discuss the possible relevance of the above results for the Cognitive Science debate about learning models as well as directions for future research. Copyright © 2013 Cognitive Science Society, Inc.

Photoelectic BV Light Curves of Algol and the Interpretations of the Light Curves

Directory of Open Access Journals (Sweden)

Ho-Il Kim

1985-06-01

Full Text Available Standardized B and V photoelectric light curves of Algol are made with the observations obtained during 1982-84 with the 40-cm and the 61-cm reflectors of Yonsei University Observatory. These light curves show asymmetry between ascending and descending shoulders. The ascending shoulder is 0.02 mag brighter than descending shoulder in V light curve and 0.03 mag in B light curve. These asymmetric light curves are interpreted as the result of inhomogeneous energy distribution on the surface of one star of the eclipsing pair rather than the result of gaseous stream flowing from KOIV to B8V star. The 180-year periodicity, so called great inequality, are most likely the result proposed by Kim et al. (1983 that the abrupt and discrete mass losses of cooler component may be the cause of this orbital change. The amount of mass loss deduced from these discrete period changes turned out to be of the order of 10^(-6 - 10^(-5 Msolar.

A Journey Between Two Curves

Directory of Open Access Journals (Sweden)

Sergey A. Cherkis

2007-03-01

Full Text Available A typical solution of an integrable system is described in terms of a holomorphic curve and a line bundle over it. The curve provides the action variables while the time evolution is a linear flow on the curve's Jacobian. Even though the system of Nahm equations is closely related to the Hitchin system, the curves appearing in these two cases have very different nature. The former can be described in terms of some classical scattering problem while the latter provides a solution to some Seiberg-Witten gauge theory. This note identifies the setup in which one can formulate the question of relating the two curves.

Bond yield curve construction

Directory of Open Access Journals (Sweden)

Kožul Nataša

2014-01-01

Full Text Available In the broadest sense, yield curve indicates the market's view of the evolution of interest rates over time. However, given that cost of borrowing it closely linked to creditworthiness (ability to repay, different yield curves will apply to different currencies, market sectors, or even individual issuers. As government borrowing is indicative of interest rate levels available to other market players in a particular country, and considering that bond issuance still remains the dominant form of sovereign debt, this paper describes yield curve construction using bonds. The relationship between zero-coupon yield, par yield and yield to maturity is given and their usage in determining curve discount factors is described. Their usage in deriving forward rates and pricing related derivative instruments is also discussed.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

Directory of Open Access Journals (Sweden)

Tjeerd V. olde Scheper

2018-01-01

Full Text Available Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized

Curve Digitizer – A software for multiple curves digitizing

Directory of Open Access Journals (Sweden)

Florentin ŞPERLEA

2010-06-01

Full Text Available The Curve Digitizer is software that extracts data from an image file representing a graphicand returns them as pairs of numbers which can then be used for further analysis and applications.Numbers can be read on a computer screen stored in files or copied on paper. The final result is adata set that can be used with other tools such as MSEXCEL. Curve Digitizer provides a useful toolfor any researcher or engineer interested in quantifying the data displayed graphically. The image filecan be obtained by scanning a document

Learning ActionScript 30

CERN Document Server

Shupe, Rich

2010-01-01

If you're new to ActionScript 3.0, or want to enhance your skill set, this bestselling book is the ideal guide. Designers, developers, and programmers alike will find Learning ActionScript 3.0 invaluable for navigating ActionScript 3.0's learning curve. You'll learn the language by getting a clear look at essential topics such as logic, event handling, displaying content, classes, and much more. Updated for Flash Professional CS5, this revised and expanded edition delivers hands-on exercises and full-color code samples to help you increase your abilities as you progress through the book. Top

On-line learning through simple perceptron with a margin

OpenAIRE

Hara, Kazuyuki; Okada, Masato

2003-01-01

We analyze a learning method that uses a margin $\\kappa$ {\\it a la} Gardner for simple perceptron learning. This method corresponds to the perceptron learning when $\\kappa=0$, and to the Hebbian learning when $\\kappa \\to \\infty$. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and...

Estimating reaction rate constants: comparison between traditional curve fitting and curve resolution

NARCIS (Netherlands)

Bijlsma, S.; Boelens, H. F. M.; Hoefsloot, H. C. J.; Smilde, A. K.

2000-01-01

A traditional curve fitting (TCF) algorithm is compared with a classical curve resolution (CCR) approach for estimating reaction rate constants from spectral data obtained in time of a chemical reaction. In the TCF algorithm, reaction rate constants an estimated from the absorbance versus time data

A catalog of special plane curves

CERN Document Server

Lawrence, J Dennis

2014-01-01

Among the largest, finest collections available-illustrated not only once for each curve, but also for various values of any parameters present. Covers general properties of curves and types of derived curves. Curves illustrated by a CalComp digital incremental plotter. 12 illustrations.

Intersection numbers of spectral curves

CERN Document Server

Eynard, B.

2011-01-01

We compute the symplectic invariants of an arbitrary spectral curve with only 1 branchpoint in terms of integrals of characteristic classes in the moduli space of curves. Our formula associates to any spectral curve, a characteristic class, which is determined by the laplace transform of the spectral curve. This is a hint to the key role of Laplace transform in mirror symmetry. When the spectral curve is y=\\sqrt{x}, the formula gives Kontsevich--Witten intersection numbers, when the spectral curve is chosen to be the Lambert function \\exp{x}=y\\exp{-y}, the formula gives the ELSV formula for Hurwitz numbers, and when one chooses the mirror of C^3 with framing f, i.e. \\exp{-x}=\\exp{-yf}(1-\\exp{-y}), the formula gives the Marino-Vafa formula, i.e. the generating function of Gromov-Witten invariants of C^3. In some sense this formula generalizes ELSV, Marino-Vafa formula, and Mumford formula.

Elliptic curves for applications (Tutorial)

NARCIS (Netherlands)

Lange, T.; Bernstein, D.J.; Chatterjee, S.

2011-01-01

More than 25 years ago, elliptic curves over finite fields were suggested as a group in which the Discrete Logarithm Problem (DLP) can be hard. Since then many researchers have scrutinized the security of the DLP on elliptic curves with the result that for suitably chosen curves only exponential

Differential geometry and topology of curves

CERN Document Server

Animov, Yu

2001-01-01

Differential geometry is an actively developing area of modern mathematics. This volume presents a classical approach to the general topics of the geometry of curves, including the theory of curves in n-dimensional Euclidean space. The author investigates problems for special classes of curves and gives the working method used to obtain the conditions for closed polygonal curves. The proof of the Bakel-Werner theorem in conditions of boundedness for curves with periodic curvature and torsion is also presented. This volume also highlights the contributions made by great geometers. past and present, to differential geometry and the topology of curves.

Models of genus one curves

OpenAIRE

Sadek, Mohammad

2010-01-01

In this thesis we give insight into the minimisation problem of genus one curves defined by equations other than Weierstrass equations. We are interested in genus one curves given as double covers of P1, plane cubics, or complete intersections of two quadrics in P3. By minimising such a curve we mean making the invariants associated to its defining equations as small as possible using a suitable change of coordinates. We study the non-uniqueness of minimisations of the genus one curves des...

Learning Curve

Directory of Open Access Journals (Sweden)

Mary Caponegro

2012-01-01

Full Text Available “What’s the matter with Mary Caponegro ?” Françoise Palleau-Papin Were I to introduce Mary Caponegro formally, in an official biographical notice, it would go something like this: Mary Caponegro is the Richard B. Fisher Family Professor in Literature and Writing at Bard College, where William Gaddis once taught. She is the author of five works of fiction: Tales from the Next Village (Lost Roads, 1985, The Star Cafe (Scribner, 1990, Five Doubts (Marsilio, 1998, The Complexities of Intimacy ...

The crime kuznets curve

OpenAIRE

Buonanno, Paolo; Fergusson, Leopoldo; Vargas, Juan Fernando

2014-01-01

We document the existence of a Crime Kuznets Curve in US states since the 1970s. As income levels have risen, crime has followed an inverted U-shaped pattern, first increasing and then dropping. The Crime Kuznets Curve is not explained by income inequality. In fact, we show that during the sample period inequality has risen monotonically with income, ruling out the traditional Kuznets Curve. Our finding is robust to adding a large set of controls that are used in the literature to explain the...

Short-radius horizontal well re-entry learning curve: prize, cost and operational experience

Energy Technology Data Exchange (ETDEWEB)

Boote, K. [Ocelot Energy Inc., Calgary, AB (Canada); MacDonald, R. [Lauron Engineering Ltd, Calgary, AB (Canada)

1997-12-01

Six mature vertical wells in Alberta belonging to Ocelot Energy Inc., were reentered and drilled horizontally. Experiences gained, the modifications made to the drilling program and the rewards in the form of incremental oil, were discussed. Details of pre- and post-performance, operational experiences with exiting the casing, building the curve, overbalance versus underbalanced drilling, motors, directional equipment, setting liners, remedial workovers and the cost of the operation were part of the discussion.

ROBUST DECLINE CURVE ANALYSIS

Directory of Open Access Journals (Sweden)

Sutawanir Darwis

2012-05-01

Full Text Available Empirical decline curve analysis of oil production data gives reasonable answer in hyperbolic type curves situations; however the methodology has limitations in fitting real historical production data in present of unusual observations due to the effect of the treatment to the well in order to increase production capacity. The development ofrobust least squares offers new possibilities in better fitting production data using declinecurve analysis by down weighting the unusual observations. This paper proposes a robustleast squares fitting lmRobMM approach to estimate the decline rate of daily production data and compares the results with reservoir simulation results. For case study, we usethe oil production data at TBA Field West Java. The results demonstrated that theapproach is suitable for decline curve fitting and offers a new insight in decline curve analysis in the present of unusual observations.

Putting experience curves in context : links to and between technology development, market diffusion, learning mechanisms and systems innovation theory

NARCIS (Netherlands)

Junginger, M.; Suurs, R.; Verbong, G.P.J.; Schaeffer, G.J.; Sark, W. van; Faaij, A. xx

2010-01-01

As far as the experience curve approach goes, the focus is mainly on quantifying the cost reductions of the technological artefact (e.g. a wind turbine or biomass power plant) due to technological development. However, the experience curve by itself offers no explanation why costs should decline in

NEW CONCEPTS AND TEST METHODS OF CURVE PROFILE AREA DENSITY IN SURFACE: ESTIMATION OF AREAL DENSITY ON CURVED SPATIAL SURFACE

OpenAIRE

Hong Shen

2011-01-01

The concepts of curve profile, curve intercept, curve intercept density, curve profile area density, intersection density in containing intersection (or intersection density relied on intersection reference), curve profile intersection density in surface (or curve intercept intersection density relied on intersection of containing curve), and curve profile area density in surface (AS) were defined. AS expressed the amount of curve profile area of Y phase in the unit containing surface area, S...

Can a teaching assistant experience in a surgical anatomy course influence the learning curve for nontechnical skill development for surgical residents?

Science.gov (United States)

Heidenreich, Mark J; Musonza, Tashinga; Pawlina, Wojciech; Lachman, Nirusha

2016-01-01

The foundation upon which surgical residents are trained to work comprises more than just critical cognitive, clinical, and technical skill. In an environment where the synchronous application of expertise is vital to patient outcomes, the expectation for optimal functioning within a multidisciplinary team is extremely high. Studies have shown that for most residents, one of the most difficult milestones in the path to achieving professional expertise in a surgical career is overcoming the learning curve. This view point commentary provides a reflection from the two senior medical students who have participated in the Student-as-Teacher program developed by the Department of Anatomy at Mayo Clinic, designed to prepare students for their teaching assistant (TA) role in anatomy courses. Both students participated as TAs in a six week surgical anatomy course for surgical first assistant students offered by the School of Health Sciences at Mayo Clinic. Development of teaching skills, nontechnical leadership, communication, and assessment skills, are discussed in relation to their benefits in preparing senior medical students for surgical residency. © 2015 American Association of Anatomists.

M-curves and symmetric products

Indian Academy of Sciences (India)

Indranil Biswas

2017-08-03

Aug 3, 2017 ... is bounded above by g + 1, where g is the genus of X [11]. Curves which have exactly the maximum number (i.e., genus +1) of components of the real part are called M-curves. Classifying real algebraic curves up to homeomorphism is straightforward, however, classifying even planar non-singular real ...

Precision Learning Assessment: An Alternative to Traditional Assessment Techniques.

Science.gov (United States)

Caltagirone, Paul J.; Glover, Christopher E.

1985-01-01

A continuous and curriculum-based assessment method, Precision Learning Assessment (PLA), which integrates precision teaching and norm-referenced techniques, was applied to a math computation curriculum for 214 third graders. The resulting districtwide learning curves defining average annual progress through the computation curriculum provided…

Undergraduate Student Self-Efficacy and Perceptions of Virtual World Learning Experience

Science.gov (United States)

Stanton, Lorraine May

2017-01-01

Virtual worlds are innovative teaching and learning methods that can provide immersive and engaging learning experiences (Lu, 2010). Though they have potential benefits, students sometimes experience a steep learning curve and discomfort with the technology (Warburton, 2009). This study explored how students in two American Studies classes using…

Titration Curves: Fact and Fiction.

Science.gov (United States)

Chamberlain, John

1997-01-01

Discusses ways in which datalogging equipment can enable titration curves to be measured accurately and how computing power can be used to predict the shape of curves. Highlights include sources of error, use of spreadsheets to generate titration curves, titration of a weak acid with a strong alkali, dibasic acids, weak acid and weak base, and…

Inverse Diffusion Curves Using Shape Optimization.

Science.gov (United States)

Zhao, Shuang; Durand, Fredo; Zheng, Changxi

2018-07-01

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.

Retrograde curves of solidus and solubility

International Nuclear Information System (INIS)

Vasil'ev, M.V.

1979-01-01

The investigation was concerned with the constitutional diagrams of the eutectic type with ''retrograde solidus'' and ''retrograde solubility curve'' which must be considered as diagrams with degenerate monotectic transformation. The solidus and the solubility curves form a retrograde curve with a common retrograde point representing the solubility maximum. The two branches of the Aetrograde curve can be described with the aid of two similar equations. Presented are corresponding equations for the Cd-Zn system and shown is the possibility of predicting the run of the solubility curve

[Customized and non-customized French intrauterine growth curves. II - Comparison with existing curves and benefits of customization].

Science.gov (United States)

Ego, A; Prunet, C; Blondel, B; Kaminski, M; Goffinet, F; Zeitlin, J

2016-02-01

Our aim is to compare the new French EPOPé intrauterine growth curves, developed to address the guidelines 2013 of the French College of Obstetricians and Gynecologists, with reference curves currently used in France, and to evaluate the consequences of their adjustment for fetal sex and maternal characteristics. Eight intrauterine and birthweight curves, used in France were compared to the EPOPé curves using data from the French Perinatal Survey 2010. The influence of adjustment on the rate of SGA births and the characteristics of these births was analysed. Due to their birthweight values and distribution, the selected intrauterine curves are less suitable for births in France than the new curves. Birthweight curves led to low rates of SGA births from 4.3 to 8.5% compared to 10.0% with the EPOPé curves. The adjustment for maternal and fetal characteristics avoids the over-representation of girls among SGA births, and reclassifies 4% of births. Among births reclassified as SGA, the frequency of medical and obstetrical risk factors for growth restriction, smoking (≥10 cigarettes/day), and neonatal transfer is higher than among non-SGA births (P<0.01). The EPOPé curves are more suitable for French births than currently used curves, and their adjustment improves the identification of mothers and babies at risk of growth restriction and poor perinatal outcomes. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks

Science.gov (United States)

Brosch, Tobias; Neumann, Heiko; Roelfsema, Pieter R.

2015-01-01

The processing of a visual stimulus can be subdivided into a number of stages. Upon stimulus presentation there is an early phase of feedforward processing where the visual information is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This is followed by a later phase where horizontal connections within areas and feedback connections from higher areas back to lower areas come into play. In this later phase, image elements that are behaviorally relevant are grouped by Gestalt grouping rules and are labeled in the cortex with enhanced neuronal activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mechanisms for reward-based learning of new grouping rules. We derive a learning rule that can explain how rewards influence the information flow through feedforward, horizontal and feedback connections. We illustrate the efficiency with two tasks that have been used to study the neuronal correlates of perceptual organization in early visual cortex. The first task is called contour-integration and demands the integration of collinear contour elements into an elongated curve. We show how reward-based learning causes an enhancement of the representation of the to-be-grouped elements at early levels of a recurrent neural network, just as is observed in the visual cortex of monkeys. The second task is curve-tracing where the aim is to determine the endpoint of an elongated curve composed of connected image elements. If trained with the new learning rule, neural networks learn to propagate enhanced activity over the curve, in accordance with neurophysiological data. We close the paper with a number of model predictions that can be tested in future neurophysiological and computational studies

Extended analysis of cooling curves

International Nuclear Information System (INIS)

Djurdjevic, M.B.; Kierkus, W.T.; Liliac, R.E.; Sokolowski, J.H.

2002-01-01

Thermal Analysis (TA) is the measurement of changes in a physical property of a material that is heated through a phase transformation temperature range. The temperature changes in the material are recorded as a function of the heating or cooling time in such a manner that allows for the detection of phase transformations. In order to increase accuracy, characteristic points on the cooling curve have been identified using the first derivative curve plotted versus time. In this paper, an alternative approach to the analysis of the cooling curve has been proposed. The first derivative curve has been plotted versus temperature and all characteristic points have been identified with the same accuracy achieved using the traditional method. The new cooling curve analysis also enables the Dendrite Coherency Point (DCP) to be detected using only one thermocouple. (author)

Impact of Three-Dimensional Laparoscopy in a Bariatric Surgery Program: Influence in the Learning Curve.

Science.gov (United States)

Padin, Esther Mariño; Santos, Raquel Sánchez; Fernández, Sonia González; Jimenez, Antonia Brox; Fernández, Sergio Estevez; Dacosta, Ester Carrera; Duran, Agata Rial; Artime Rial, Maria; Dominguez Sanchez, Ivan

2017-10-01

3D laparoscopy allows the surgeon to regain the sense of depth and improve accuracy. The aim of the study was to assess the impact of 3D in bariatric surgery. A retrospective cohort study was conducted. All our patients who underwent bariatric surgery (sleeve gastrectomy (SG) or gastric bypass (GB)) between 2013 and 2016 were included. We compared 3D laparoscopy cohort and 2D laparoscopy cohort. Variables are as follows: age, sex, DM, hypertension, surgeon experience, and type of intervention. Comparisons of operative time, hospital stay, conversion, complications, reoperation, and exitus are completed. Three hundred twelve consecutive patients were included. 56.9% of patients underwent GB and 43.1% SG. Global complications were 3.2% (fistula 2.5%, hemoperitoneum 0.3%, others 0.4%). One hundred four procedures were performed in the 3D cohort and 208 in the 2D cohort. The 2D cohort and 3D cohort were similar regarding the following: percentage of GB vs SG, age, gender, learning curve, diabetes mellitus 2, hypertension, and sleep apnea. The operating time and hospital stay were significantly reduced in the 3D cohort (144.07 ± 58.07 vs 172.11 ± 76.11 min and 5.12 ± 9.6 vs 7.7 ± 13.2 days. It was the same when we stratified the sample by type of surgery or experience of the surgeon. Complications were reduced in the 3D cohort in the surgeries performed by novice surgeons (10.2 vs 1.8%, p = 0.034). The use of 3D laparoscopy in bariatric surgery in our center has helped reducing the operating time and hospital stay, and improving the safety of the surgery, either in GB or SG, being equally favorable in novice or more experienced surgeons.

Technological learning in energy-environment-economy modelling: A survey

International Nuclear Information System (INIS)

Kahouli-Brahmi, Sondes

2008-01-01

This paper aims at providing an overview and a critical analysis of the technological learning concept and its incorporation in energy-environment-economy models. A special emphasis is put on surveying and discussing, through the so-called learning curve, both studies estimating learning rates in the energy field and studies incorporating endogenous technological learning in bottom-up and top-down models. The survey of learning rate estimations gives special attention to interpreting and explaining the sources of variability of estimated rates, which is shown to be mainly inherent in R and D expenditures, the problem of omitted variable bias, the endogeneity relationship and the role of spillovers. Large-scale models survey show that, despite some methodological and computational complexity related to the non-linearity and the non-convexity associated with the learning curve incorporation, results of the numerous modelling experiments give several new insights with regard to the analysis of the prospects of specific technological options and their cost decrease potential (bottom-up models), and with regard to the analysis of strategic considerations, especially inherent in the innovation and energy diffusion process, in particular the energy sector's endogenous responses to environment policy instruments (top-down models)

Tempo curves considered harmful

NARCIS (Netherlands)

Desain, P.; Honing, H.

1993-01-01

In the literature of musicology, computer music research and the psychology of music, timing or tempo measurements are mostly presented in the form of continuous curves. The notion of these tempo curves is dangerous, despite its widespread use, because it lulls its users into the false impression

Nonlinear dynamical modes of climate variability: from curves to manifolds

Science.gov (United States)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

Science.gov (United States)

McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

2015-07-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

Image scaling curve generation

NARCIS (Netherlands)

2012-01-01

The present invention relates to a method of generating an image scaling curve, where local saliency is detected in a received image. The detected local saliency is then accumulated in the first direction. A final scaling curve is derived from the detected local saliency and the image is then

Image scaling curve generation.

NARCIS (Netherlands)

2011-01-01

The present invention relates to a method of generating an image scaling curve, where local saliency is detected in a received image. The detected local saliency is then accumulated in the first direction. A final scaling curve is derived from the detected local saliency and the image is then

Anterior Overgrowth in Primary Curves, Compensatory Curves and Junctional Segments in Adolescent Idiopathic Scoliosis.

Science.gov (United States)

Schlösser, Tom P C; van Stralen, Marijn; Chu, Winnie C W; Lam, Tsz-Ping; Ng, Bobby K W; Vincken, Koen L; Cheng, Jack C Y; Castelein, René M

2016-01-01

Although much attention has been given to the global three-dimensional aspect of adolescent idiopathic scoliosis (AIS), the accurate three-dimensional morphology of the primary and compensatory curves, as well as the intervening junctional segments, in the scoliotic spine has not been described before. A unique series of 77 AIS patients with high-resolution CT scans of the spine, acquired for surgical planning purposes, were included and compared to 22 healthy controls. Non-idiopathic curves were excluded. Endplate segmentation and local longitudinal axis in endplate plane enabled semi-automatic geometric analysis of the complete three-dimensional morphology of the spine, taking inter-vertebral rotation, intra-vertebral torsion and coronal and sagittal tilt into account. Intraclass correlation coefficients for interobserver reliability were 0.98-1.00. Coronal deviation, axial rotation and the exact length discrepancies in the reconstructed sagittal plane, as defined per vertebra and disc, were analyzed for each primary and compensatory curve as well as for the junctional segments in-between. The anterior-posterior difference of spinal length, based on "true" anterior and posterior points on endplates, was +3.8% for thoracic and +9.4% for (thoraco)lumbar curves, while the junctional segments were almost straight. This differed significantly from control group thoracic kyphosis (-4.1%; P<0.001) and lumbar lordosis (+7.8%; P<0.001). For all primary as well as compensatory curves, we observed linear correlations between the coronal Cobb angle, axial rotation and the anterior-posterior length difference (r≥0.729 for thoracic curves; r≥0.485 for (thoraco)lumbar curves). Excess anterior length of the spine in AIS has been described as a generalized growth disturbance, causing relative anterior spinal overgrowth. This study is the first to demonstrate that this anterior overgrowth is not a generalized phenomenon. It is confined to the primary as well as the

Development of a statistically-based lower bound fracture toughness curve (Ksub(IR) curve)

International Nuclear Information System (INIS)

Wullaert, R.A.; Server, W.L.; Oldfield, W.; Stahlkopf, K.E.

1977-01-01

A program of initiation fracture toughness measurements on fifty heats of nuclear pressure vessel production materials (including weldments) was used to develop a methodology for establishing a revised reference toughness curve. The new methodology was statistically developed and provides a predefined confidence limit (or tolerance limit) for fracture toughness based upon many heats of a particular type of material. Overall reference curves were developed for seven specific materials using large specimen static and dynamic fracture toughness results. The heat-to-heat variation was removed by normalizing both the fracture toughness and temperature data with the precracked Charpy tanh curve coefficients for each particular heat. The variance and distribution about the curve were determined, and lower bounds of predetermined statistical significance were drawn based upon a Pearson distribution in the lower shelf region (since the data were skewed to high values) and a t-distribution in the transition temperature region (since the data were normally distributed)

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

Energy Technology Data Exchange (ETDEWEB)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K. [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom); McEwen, Jason D., E-mail: dr.michelle.lochner@gmail.com [Mullard Space Science Laboratory, University College London, Surrey RH5 6NT (United Kingdom)

2016-08-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

International Nuclear Information System (INIS)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.; McEwen, Jason D.

2016-01-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

Energy Technology Data Exchange (ETDEWEB)

Palaversa, Lovro; Eyer, Laurent; Rimoldini, Lorenzo [Observatoire Astronomique de l' Université de Genève, 51 chemin des Maillettes, CH-1290 Sauverny (Switzerland); Ivezić, Željko; Loebman, Sarah; Hunt-Walker, Nicholas; VanderPlas, Jacob; Westman, David; Becker, Andrew C. [Department of Astronomy, University of Washington, P.O. Box 351580, Seattle, WA 98195-1580 (United States); Ruždjak, Domagoj; Sudar, Davor; Božić, Hrvoje [Hvar Observatory, Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Galin, Mario [Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Kroflin, Andrea; Mesarić, Martina; Munk, Petra; Vrbanec, Dijana [Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb (Croatia); Sesar, Branimir [Division of Physics, Mathematics, and Astronomy, Caltech, Pasadena, CA 91125 (United States); Stuart, J. Scott [Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood Street, Lexington, MA 02420-9108 (United States); Srdoč, Gregor, E-mail: lovro.palaversa@unige.ch [Saršoni 90, 51216 Viškovo (Croatia); and others

2013-10-01

We describe the construction of a highly reliable sample of ∼7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ∼0.03 mag at r = 15 to ∼0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ∼200,000 most probable candidate variables with r < 17 and visually confirmed and classified ∼7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the

A note on families of fragility curves

International Nuclear Information System (INIS)

Kaplan, S.; Bier, V.M.; Bley, D.C.

1989-01-01

In the quantitative assessment of seismic risk, uncertainty in the fragility of a structural component is usually expressed by putting forth a family of fragility curves, with probability serving as the parameter of the family. Commonly, a lognormal shape is used both for the individual curves and for the expression of uncertainty over the family. A so-called composite single curve can also be drawn and used for purposes of approximation. This composite curve is often regarded as equivalent to the mean curve of the family. The equality seems intuitively reasonable, but according to the authors has never been proven. The paper presented proves this equivalence hypothesis mathematically. Moreover, the authors show that this equivalence hypothesis between fragility curves is itself equivalent to an identity property of the standard normal probability curve. Thus, in the course of proving the fragility curve hypothesis, the authors have also proved a rather obscure, but interesting and perhaps previously unrecognized, property of the standard normal curve

MICA: Multiple interval-based curve alignment

Science.gov (United States)

Mann, Martin; Kahle, Hans-Peter; Beck, Matthias; Bender, Bela Johannes; Spiecker, Heinrich; Backofen, Rolf

2018-01-01

MICA enables the automatic synchronization of discrete data curves. To this end, characteristic points of the curves' shapes are identified. These landmarks are used within a heuristic curve registration approach to align profile pairs by mapping similar characteristics onto each other. In combination with a progressive alignment scheme, this enables the computation of multiple curve alignments. Multiple curve alignments are needed to derive meaningful representative consensus data of measured time or data series. MICA was already successfully applied to generate representative profiles of tree growth data based on intra-annual wood density profiles or cell formation data. The MICA package provides a command-line and graphical user interface. The R interface enables the direct embedding of multiple curve alignment computation into larger analyses pipelines. Source code, binaries and documentation are freely available at https://github.com/BackofenLab/MICA

Power forward curves: a managerial perspective

International Nuclear Information System (INIS)

Nagarajan, Shankar

1999-01-01

This chapter concentrates on managerial application of power forward curves, and examines the determinants of electricity prices such as transmission constraints, its inability to be stored in a conventional way, its seasonality and weather dependence, the generation stack, and the swing risk. The electricity forward curve, classical arbitrage, constructing a forward curve, volatilities, and electricity forward curve models such as the jump-diffusion model, the mean-reverting heteroscedastic volatility model, and an econometric model of forward prices are examined. A managerial perspective of the applications of the forward curve is presented covering plant valuation, capital budgeting, performance measurement, product pricing and structuring, asset optimisation, valuation of transmission options, and risk management

Development of a Portable Motor Learning Laboratory (PoMLab).

Science.gov (United States)

Takiyama, Ken; Shinya, Masahiro

2016-01-01

Most motor learning experiments have been conducted in a laboratory setting. In this type of setting, a huge and expensive manipulandum is frequently used, requiring a large budget and wide open space. Subjects also need to travel to the laboratory, which is a burden for them. This burden is particularly severe for patients with neurological disorders. Here, we describe the development of a novel application based on Unity3D and smart devices, e.g., smartphones or tablet devices, that can be used to conduct motor learning experiments at any time and in any place, without requiring a large budget and wide open space and without the burden of travel on subjects. We refer to our application as POrtable Motor learning LABoratory, or PoMLab. PoMLab is a multiplatform application that is available and sharable for free. We investigated whether PoMLab could be an alternative to the laboratory setting using a visuomotor rotation paradigm that causes sensory prediction error, enabling the investigation of how subjects minimize the error. In the first experiment, subjects could adapt to a constant visuomotor rotation that was abruptly applied at a specific trial. The learning curve for the first experiment could be modeled well using a state space model, a mathematical model that describes the motor leaning process. In the second experiment, subjects could adapt to a visuomotor rotation that gradually increased each trial. The subjects adapted to the gradually increasing visuomotor rotation without being aware of the visuomotor rotation. These experimental results have been reported for conventional experiments conducted in a laboratory setting, and our PoMLab application could reproduce these results. PoMLab can thus be considered an alternative to the laboratory setting. We also conducted follow-up experiments in university physical education classes. A state space model that was fit to the data obtained in the laboratory experiments could predict the learning curves

Development of a Portable Motor Learning Laboratory (PoMLab.

Directory of Open Access Journals (Sweden)

Ken Takiyama

Full Text Available Most motor learning experiments have been conducted in a laboratory setting. In this type of setting, a huge and expensive manipulandum is frequently used, requiring a large budget and wide open space. Subjects also need to travel to the laboratory, which is a burden for them. This burden is particularly severe for patients with neurological disorders. Here, we describe the development of a novel application based on Unity3D and smart devices, e.g., smartphones or tablet devices, that can be used to conduct motor learning experiments at any time and in any place, without requiring a large budget and wide open space and without the burden of travel on subjects. We refer to our application as POrtable Motor learning LABoratory, or PoMLab. PoMLab is a multiplatform application that is available and sharable for free. We investigated whether PoMLab could be an alternative to the laboratory setting using a visuomotor rotation paradigm that causes sensory prediction error, enabling the investigation of how subjects minimize the error. In the first experiment, subjects could adapt to a constant visuomotor rotation that was abruptly applied at a specific trial. The learning curve for the first experiment could be modeled well using a state space model, a mathematical model that describes the motor leaning process. In the second experiment, subjects could adapt to a visuomotor rotation that gradually increased each trial. The subjects adapted to the gradually increasing visuomotor rotation without being aware of the visuomotor rotation. These experimental results have been reported for conventional experiments conducted in a laboratory setting, and our PoMLab application could reproduce these results. PoMLab can thus be considered an alternative to the laboratory setting. We also conducted follow-up experiments in university physical education classes. A state space model that was fit to the data obtained in the laboratory experiments could predict the

Consistent Valuation across Curves Using Pricing Kernels

Directory of Open Access Journals (Sweden)

Andrea Macrina

2018-03-01

Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

Optimized curve design for image analysis using localized geodesic distance transformations

Science.gov (United States)

Braithwaite, Billy; Niska, Harri; Pöllänen, Irene; Ikonen, Tiia; Haataja, Keijo; Toivanen, Pekka; Tolonen, Teemu

2015-03-01

We consider geodesic distance transformations for digital images. Given a M × N digital image, a distance image is produced by evaluating local pixel distances. Distance Transformation on Curved Space (DTOCS) evaluates shortest geodesics of a given pixel neighborhood by evaluating the height displacements between pixels. In this paper, we propose an optimization framework for geodesic distance transformations in a pattern recognition scheme, yielding more accurate machine learning based image analysis, exemplifying initial experiments using complex breast cancer images. Furthermore, we will outline future research work, which will complete the research work done for this paper.

The estimation of I–V curves of PV panel using manufacturers’ I–V curves and evolutionary strategy

International Nuclear Information System (INIS)

Barukčić, M.; Hederić, Ž.; Špoljarić, Ž.

2014-01-01

Highlights: • The approximation of a I–V curve by two linear and a sigmoid functions is proposed. • The sigmoid function is used to estimate the knee of the I–V curve. • Dependence on irradiance and temperature of sigmoid function parameters is proposed. • The sigmoid function is used to estimate maximum power point (MPP). - Abstract: The method for estimation of I–V curves of photovoltaic (PV) panel by analytic expression is presented in the paper. The problem is defined in the form of an optimization problem. The optimization problem objective is based on data from I–V curves obtained by manufacturers’ or measured I–V curves. In order to estimate PV panel parameters, the optimization problem is solved by using an evolutionary strategy. The proposed method is tested for different PV panel technologies using data sheets. In this method the I–V curve approximation with two linear and a sigmoid function is proposed. The method for estimating the knee of the I–V curve and maximum power point at any irradiance and temperature is proposed

Prediction of ttt curves of cold working tool steels using support vector machine model

Science.gov (United States)

Pillai, Nandakumar; Karthikeyan, R., Dr.

2018-04-01

The cold working tool steels are of high carbon steels with metallic alloy additions which impart higher hardenability, abrasion resistance and less distortion in quenching. The microstructure changes occurring in tool steel during heat treatment is of very much importance as the final properties of the steel depends upon these changes occurred during the process. In order to obtain the desired performance the alloy constituents and its ratio plays a vital role as the steel transformation itself is complex in nature and depends very much upon the time and temperature. The proper treatment can deliver satisfactory results, at the same time process deviation can completely spoil the results. So knowing time temperature transformation (TTT) of phases is very critical which varies for each type depending upon its constituents and proportion range. To obtain adequate post heat treatment properties the percentage of retained austenite should be lower and metallic carbides obtained should be fine in nature. Support vector machine is a computational model which can learn from the observed data and use these to predict or solve using mathematical model. Back propagation feedback network will be created and trained for further solutions. The points on the TTT curve for the known transformations curves are used to plot the curves for different materials. These data will be trained to predict TTT curves for other steels having similar alloying constituents but with different proportion range. The proposed methodology can be used for prediction of TTT curves for cold working steels and can be used for prediction of phases for different heat treatment methods.

Statistical mechanics of learning orthogonal signals for general covariance models

International Nuclear Information System (INIS)

Hoyle, David C

2010-01-01

Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation

Ultrasensitive prostate specific antigen assay following laparoscopic radical prostatectomy--an outcome measure for defining the learning curve.

Science.gov (United States)

Viney, R; Gommersall, L; Zeif, J; Hayne, D; Shah, Z H; Doherty, A

2009-07-01

Radical retropubic prostatectomy (RRP) performed laparoscopically is a popular treatment with curative intent for organ-confined prostate cancer. After surgery, prostate specific antigen (PSA) levels drop to low levels which can be measured with ultrasensitive assays. This has been described in the literature for open RRP but not for laparoscopic RRP. This paper describes PSA changes in the first 300 consecutive patients undergoing non-robotic laparoscopic RRP by a single surgeon. To use ultrasensitive PSA (uPSA) assays to measure a PSA nadir in patients having laparoscopic radical prostatectomy below levels recorded by standard assays. The aim was to use uPSA nadir at 3 months' post-prostatectomy as an early surrogate end-point of oncological outcome. In so doing, laparoscopic oncological outcomes could then be compared with published results from other open radical prostatectomy series with similar end-points. Furthermore, this end-point could be used in the assessment of the surgeon's learning curve. Prospective, comprehensive, demographic, clinical, biochemical and operative data were collected from all patients undergoing non-robotic laparoscopic RRP. We present data from the first 300 consecutive patients undergoing laparoscopic RRP by a single surgeon. uPSA was measured every 3 months post surgery. Median follow-up was 29 months (minimum 3 months). The likelihood of reaching a uPSA of bench-marking performance. With experience, a surgeon can achieve in excess of an 80% chance of obtaining a uPSA nadir of < or = 0.01 ng/ml at 3 months after laparoscopic RRP for a British population. This is equivalent to most published open series.

Dual Smarandache Curves and Smarandache Ruled Surfaces

OpenAIRE

Tanju KAHRAMAN; Mehmet ÖNDER; H. Hüseyin UGURLU

2013-01-01

In this paper, by considering dual geodesic trihedron (dual Darboux frame) we define dual Smarandache curves lying fully on dual unit sphere S^2 and corresponding to ruled surfaces. We obtain the relationships between the elements of curvature of dual spherical curve (ruled surface) x(s) and its dual Smarandache curve (Smarandache ruled surface) x1(s) and we give an example for dual Smarandache curves of a dual spherical curve.

Implementing Machine Learning in the PCWG Tool

Energy Technology Data Exchange (ETDEWEB)

Clifton, Andrew; Ding, Yu; Stuart, Peter

2016-12-13

The Power Curve Working Group (www.pcwg.org) is an ad-hoc industry-led group to investigate the performance of wind turbines in real-world conditions. As part of ongoing experience-sharing exercises, machine learning has been proposed as a possible way to predict turbine performance. This presentation provides some background information about machine learning and how it might be implemented in the PCWG exercises.

Cost development of future technologies for power generation-A study based on experience curves and complementary bottom-up assessments

International Nuclear Information System (INIS)

Neij, Lena

2008-01-01

Technology foresight studies have become an important tool in identifying realistic ways of reducing the impact of modern energy systems on the climate and the environment. Studies on the future cost development of advanced energy technologies are of special interest. One approach widely adopted for the analysis of future cost is the experience curve approach. The question is, however, how robust this approach is, and which experience curves should be used in energy foresight analysis. This paper presents an analytical framework for the analysis of future cost development of new energy technologies for electricity generation; the analytical framework is based on an assessment of available experience curves, complemented with bottom-up analysis of sources of cost reductions and, for some technologies, judgmental expert assessments of long-term development paths. The results of these three methods agree in most cases, i.e. the cost (price) reductions described by the experience curves match the incremental cost reduction described in the bottom-up analysis and the judgmental expert assessments. For some technologies, the bottom-up analysis confirms large uncertainties in future cost development not captured by the experience curves. Experience curves with a learning rate ranging from 0% to 20% are suggested for the analysis of future cost development

Perceptual learning as improved probabilistic inference in early sensory areas.

Science.gov (United States)

Bejjanki, Vikranth R; Beck, Jeffrey M; Lu, Zhong-Lin; Pouget, Alexandre

2011-05-01

Extensive training on simple tasks such as fine orientation discrimination results in large improvements in performance, a form of learning known as perceptual learning. Previous models have argued that perceptual learning is due to either sharpening and amplification of tuning curves in early visual areas or to improved probabilistic inference in later visual areas (at the decision stage). However, early theories are inconsistent with the conclusions of psychophysical experiments manipulating external noise, whereas late theories cannot explain the changes in neural responses that have been reported in cortical areas V1 and V4. Here we show that we can capture both the neurophysiological and behavioral aspects of perceptual learning by altering only the feedforward connectivity in a recurrent network of spiking neurons so as to improve probabilistic inference in early visual areas. The resulting network shows modest changes in tuning curves, in line with neurophysiological reports, along with a marked reduction in the amplitude of pairwise noise correlations.

The writhe of open and closed curves

International Nuclear Information System (INIS)

Berger, Mitchell A; Prior, Chris

2006-01-01

Twist and writhe measure basic geometric properties of a ribbon or tube. While these measures have applications in molecular biology, materials science, fluid mechanics and astrophysics, they are under-utilized because they are often considered difficult to compute. In addition, many applications involve curves with endpoints (open curves); but for these curves the definition of writhe can be ambiguous. This paper provides simple expressions for the writhe of closed curves, and provides a new definition of writhe for open curves. The open curve definition is especially appropriate when the curve is anchored at endpoints on a plane or stretches between two parallel planes. This definition can be especially useful for magnetic flux tubes in the solar atmosphere, and for isotropic rods with ends fixed to a plane

F(α) curves: Experimental results

International Nuclear Information System (INIS)

Glazier, J.A.; Gunaratne, G.; Libchaber, A.

1988-01-01

We study the transition to chaos at the golden and silver means for forced Rayleigh-Benard (RB) convection in mercury. We present f(α) curves below, at, and above the transition, and provide comparisons to the curves calculated for the one-dimensional circle map. We find good agreement at both the golden and silver means. This confirms our earlier observation that for low amplitude forcing, forced RB convection is well described by the one-dimensional circle map and indicates that the f(α) curve is a good measure of the approach to criticality. For selected subcritical experimental data sets we calculate the degree of subcriticality. We also present both experimental and calculated results for f(α) in the presence of a third frequency. Again we obtain agreement: The presence of random noise or a third frequency narrows the right-hand (negative q) side of the f(α) curve. Subcriticality results in symmetrically narrowed curves. We can also distinguish these cases by examining the power spectra and Poincare sections of the time series

Dissolution glow curve in LLD

International Nuclear Information System (INIS)

Haverkamp, U.; Wiezorek, C.; Poetter, R.

1990-01-01

Lyoluminescence dosimetry is based upon light emission during dissolution of previously irradiated dosimetric materials. The lyoluminescence signal is expressed in the dissolution glow curve. These curves begin, depending on the dissolution system, with a high peak followed by an exponentially decreasing intensity. System parameters that influence the graph of the dissolution glow curve, are, for example, injection speed, temperature and pH value of the solution and the design of the dissolution cell. The initial peak does not significantly correlate with the absorbed dose, it is mainly an effect of the injection. The decay of the curve consists of two exponential components: one fast and one slow. The components depend on the absorbed dose and the dosimetric materials used. In particular, the slow component correlates with the absorbed dose. In contrast to the fast component the argument of the exponential function of the slow component is independent of the dosimetric materials investigated: trehalose, glucose and mannitol. The maximum value, following the peak of the curve, and the integral light output are a measure of the absorbed dose. The reason for the different light outputs of various dosimetric materials after irradiation with the same dose is the differing solubility. The character of the dissolution glow curves is the same following irradiation with photons, electrons or neutrons. (author)

Development of the curve of Spee.

Science.gov (United States)

Marshall, Steven D; Caspersen, Matthew; Hardinger, Rachel R; Franciscus, Robert G; Aquilino, Steven A; Southard, Thomas E

2008-09-01

Ferdinand Graf von Spee is credited with characterizing human occlusal curvature viewed in the sagittal plane. This naturally occurring phenomenon has clinical importance in orthodontics and restorative dentistry, yet we have little understanding of when, how, or why it develops. The purpose of this study was to expand our understanding by examining the development of the curve of Spee longitudinally in a sample of untreated subjects with normal occlusion from the deciduous dentition to adulthood. Records of 16 male and 17 female subjects from the Iowa Facial Growth Study were selected and examined. The depth of the curve of Spee was measured on their study models at 7 time points from ages 4 (deciduous dentition) to 26 (adult dentition) years. The Wilcoxon signed rank test was used to compare changes in the curve of Spee depth between time points. For each subject, the relative eruption of the mandibular teeth was measured from corresponding cephalometric radiographs, and its contribution to the developing curve of Spee was ascertained. In the deciduous dentition, the curve of Spee is minimal. At mean ages of 4.05 and 5.27 years, the average curve of Spee depths are 0.24 and 0.25 mm, respectively. With change to the transitional dentition, corresponding to the eruption of the mandibular permanent first molars and central incisors (mean age, 6.91 years), the curve of Spee depth increases significantly (P < 0.0001) to a mean maximum depth of 1.32 mm. The curve of Spee then remains essentially unchanged until eruption of the second molars (mean age, 12.38 years), when the depth increases (P < 0.0001) to a mean maximum depth of 2.17 mm. In the adolescent dentition (mean age, 16.21 years), the depth decreases slightly (P = 0.0009) to a mean maximum depth of 1.98 mm, and, in the adult dentition (mean age 26.98 years), the curve remains unchanged (P = 0.66), with a mean maximum depth of 2.02 mm. No significant differences in curve of Spee development were found between

GLOBAL AND STRICT CURVE FITTING METHOD

NARCIS (Netherlands)

Nakajima, Y.; Mori, S.

2004-01-01

To find a global and smooth curve fitting, cubic B­Spline method and gathering­ line methods are investigated. When segmenting and recognizing a contour curve of character shape, some global method is required. If we want to connect contour curves around a singular point like crossing points,

Simulating Supernova Light Curves

Energy Technology Data Exchange (ETDEWEB)

Even, Wesley Paul [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dolence, Joshua C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-05

This report discusses supernova light simulations. A brief review of supernovae, basics of supernova light curves, simulation tools used at LANL, and supernova results are included. Further, it happens that many of the same methods used to generate simulated supernova light curves can also be used to model the emission from fireballs generated by explosions in the earth’s atmosphere.

Simulating Supernova Light Curves

International Nuclear Information System (INIS)

Even, Wesley Paul; Dolence, Joshua C.

2016-01-01

This report discusses supernova light simulations. A brief review of supernovae, basics of supernova light curves, simulation tools used at LANL, and supernova results are included. Further, it happens that many of the same methods used to generate simulated supernova light curves can also be used to model the emission from fireballs generated by explosions in the earth's atmosphere.

Trigonometric Characterization of Some Plane Curves

Indian Academy of Sciences (India)

IAS Admin

(Figure 1). A relation between tan θ and tanψ gives the trigonometric equation of the family of curves. In this article, trigonometric equations of some known plane curves are deduced and it is shown that these equations reveal some geometric characteristics of the families of the curves under consideration. In Section 2,.

Predicting the costs of photovoltaic solar modules in 2020 using experience curve models

International Nuclear Information System (INIS)

La Tour, Arnaud de; Glachant, Matthieu; Ménière, Yann

2013-01-01

Except in few locations, photovoltaic generated electricity remains considerably more expensive than conventional sources. It is however expected that innovation and learning-by-doing will lead to drastic cuts in production cost in the near future. The goal of this paper is to predict the cost of PV modules out to 2020 using experience curve models, and to draw implications about the cost of PV electricity. Using annual data on photovoltaic module prices, cumulative production, R and D knowledge stock and input prices for silicon and silver over the period 1990–2011, we identify a experience curve model which minimizes the difference between predicted and actual module prices. This model predicts a 67% decrease of module price from 2011 to 2020. This rate implies that the cost of PV generated electricity will reach that of conventional electricity by 2020 in the sunniest countries with annual solar irradiation of 2000 kWh/year or more, such as California, Italy, and Spain. - Highlights: • We predict the cost of PV modules out to 2020 using experience curve models. • The model predicts a 67% decrease of module price from 2011 to 2020. • We draw implications about the cost of PV electricity

Considerations for reference pump curves

International Nuclear Information System (INIS)

Stockton, N.B.

1992-01-01

This paper examines problems associated with inservice testing (IST) of pumps to assess their hydraulic performance using reference pump curves to establish acceptance criteria. Safety-related pumps at nuclear power plants are tested under the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (the Code), Section 11. The Code requires testing pumps at specific reference points of differential pressure or flow rate that can be readily duplicated during subsequent tests. There are many cases where test conditions cannot be duplicated. For some pumps, such as service water or component cooling pumps, the flow rate at any time depends on plant conditions and the arrangement of multiple independent and constantly changing loads. System conditions cannot be controlled to duplicate a specific reference value. In these cases, utilities frequently request to use pump curves for comparison of test data for acceptance. There is no prescribed method for developing a pump reference curve. The methods vary and may yield substantially different results. Some results are conservative when compared to the Code requirements; some are not. The errors associated with different curve testing techniques should be understood and controlled within reasonable bounds. Manufacturer's pump curves, in general, are not sufficiently accurate to use as reference pump curves for IST. Testing using reference curves generated with polynomial least squares fits over limited ranges of pump operation, cubic spline interpolation, or cubic spline least squares fits can provide a measure of pump hydraulic performance that is at least as accurate as the Code required method. Regardless of the test method, error can be reduced by using more accurate instruments, by correcting for systematic errors, by increasing the number of data points, and by taking repetitive measurements at each data point

[Surgical learning curve for creation of vascular accesses for haemodialysis: value of medico-radio-surgical collaboration].

Science.gov (United States)

Van Glabeke, Emmanuel; Belenfant, Xavier; Barrou, Benoît; Adhemar, Jean-Pierre; Laedrich, Joëlle; Mavel, Marie-Christine; Challier, Emmanuel

2005-04-01

Creation of a vascular access (VA) for haemodialysis is a surgical procedure which comprises a failure rate related to the quality of the vessels and the operator's experience. The authors report the first 2 years of a young urologist's experience with this procedure in a local hospital in collaboration with the nephrology team. Patients undergoing creation of VA were divided into 2 chronological groups. The patient's age and gender, the cause of renal failure, the presence of diabetes, clinical examination of the upper limb, preoperative assessment of upper limb vessels, the type of anaesthesia, the operating time and the start of dialysis after the operation, as well as the functional results of the VA at 6 months were studied. Results concerning the patients of the first period were discussed by the operator and the nephrology team. During the first 9 months, 28 patients were operated, corresponding to 36 operations including 32 direct fistulas. Over the following 15 months, 61 patients were operated, with the creation of 63 VAs, including 55 direct fistulas. The failure rate (thrombosis or non-functioning VA) decreased from 32.1% to 11.1% (p=0.07), while the 2 groups were globally comparable. Evaluation of a new surgical procedure shows a number of failures, as for all learning curves. However, it helps to improve the results. Collaboration with nephrologists must comprise a discussion allowing the acceptance of certain failures, as they reflect compliance with a strategy of preservation of the vascular capital and a rational attempt to avoid a non-essential proximal access or bypass graft. The support of a motivated radiology team (preoperative assessment and management of complications) and the assistance of a more experienced operator are essential.

Computational aspects of algebraic curves

CERN Document Server

Shaska, Tanush

2005-01-01

The development of new computational techniques and better computing power has made it possible to attack some classical problems of algebraic geometry. The main goal of this book is to highlight such computational techniques related to algebraic curves. The area of research in algebraic curves is receiving more interest not only from the mathematics community, but also from engineers and computer scientists, because of the importance of algebraic curves in applications including cryptography, coding theory, error-correcting codes, digital imaging, computer vision, and many more.This book cove

Mannheim Curves in Nonflat 3-Dimensional Space Forms

Directory of Open Access Journals (Sweden)

Wenjing Zhao

2015-01-01

Full Text Available We consider the Mannheim curves in nonflat 3-dimensional space forms (Riemannian or Lorentzian and we give the concept of Mannheim curves. In addition, we investigate the properties of nonnull Mannheim curves and their partner curves. We come to the conclusion that a necessary and sufficient condition is that a linear relationship with constant coefficients will exist between the curvature and the torsion of the given original curves. In the case of null curve, we reveal that there are no null Mannheim curves in the 3-dimensional de Sitter space.

Learning Curve Analyses in Neurodevelopmental Disorders: Are Children with Autism Spectrum Disorder Truly Visual Learners?

Science.gov (United States)

Erdodi, Laszlo; Lajiness-O'Neill, Renee; Schmitt, Thomas A.

2013-01-01

Visual and auditory verbal learning using a selective reminding format was studied in a mixed clinical sample of children with autism spectrum disorder (ASD) (n = 42), attention-deficit hyperactivity disorder (n = 83), velocardiofacial syndrome (n = 17) and neurotypicals (n = 38) using the Test of Memory and Learning to (1) more thoroughly…

String Sigma Models on Curved Supermanifolds

Directory of Open Access Journals (Sweden)

Roberto Catenacci

2018-04-01

Full Text Available We use the techniques of integral forms to analyze the easiest example of two-dimensional sigma models on a supermanifold. We write the action as an integral of a top integral form over a D = 2 supermanifold, and we show how to interpolate between different superspace actions. Then, we consider curved supermanifolds, and we show that the definitions used for flat supermanifolds can also be used for curved supermanifolds. We prove it by first considering the case of a curved rigid supermanifold and then the case of a generic curved supermanifold described by a single superfield E.

Power Curve Measurements FGW

DEFF Research Database (Denmark)

Georgieva Yankova, Ginka; Federici, Paolo

This report describes power curve measurements carried out on a given turbine in a chosen period. The measurements are carried out in accordance to IEC 61400-12-1 Ed. 1 and FGW Teil 2.......This report describes power curve measurements carried out on a given turbine in a chosen period. The measurements are carried out in accordance to IEC 61400-12-1 Ed. 1 and FGW Teil 2....

Preclinical endoscopic training using a part-task simulator: learning curve assessment and determination of threshold score for advancement to clinical endoscopy.

Science.gov (United States)

Jirapinyo, Pichamol; Abidi, Wasif M; Aihara, Hiroyuki; Zaki, Theodore; Tsay, Cynthia; Imaeda, Avlin B; Thompson, Christopher C

2017-10-01

Preclinical simulator training has the potential to decrease endoscopic procedure time and patient discomfort. This study aims to characterize the learning curve of endoscopic novices in a part-task simulator and propose a threshold score for advancement to initial clinical cases. Twenty novices with no prior endoscopic experience underwent repeated endoscopic simulator sessions using the part-task simulator. Simulator scores were collected; their inverse was averaged and fit to an exponential curve. The incremental improvement after each session was calculated. Plateau was defined as the session after which incremental improvement in simulator score model was less than 5%. Additionally, all participants filled out questionnaires regarding simulator experience after sessions 1, 5, 10, 15, and 20. A visual analog scale and NASA task load index were used to assess levels of comfort and demand. Twenty novices underwent 400 simulator sessions. Mean simulator scores at sessions 1, 5, 10, 15, and 20 were 78.5 ± 5.95, 176.5 ± 17.7, 275.55 ± 23.56, 347 ± 26.49, and 441.11 ± 38.14. The best fit exponential model was [time/score] = 26.1 × [session #] -0.615 ; r 2  = 0.99. This corresponded to an incremental improvement in score of 35% after the first session, 22% after the second, 16% after the third and so on. Incremental improvement dropped below 5% after the 12th session corresponding to the predicted score of 265. Simulator training was related to higher comfort maneuvering an endoscope and increased readiness for supervised clinical endoscopy, both plateauing between sessions 10 and 15. Mental demand, physical demand, and frustration levels decreased with increased simulator training. Preclinical training using an endoscopic part-task simulator appears to increase comfort level and decrease mental and physical demand associated with endoscopy. Based on a rigorous model, we recommend that novices complete a minimum of 12 training

Construction of calibration curve for accountancy tank

International Nuclear Information System (INIS)

Kato, Takayuki; Goto, Yoshiki; Nidaira, Kazuo

2009-01-01

Tanks are equipped in a reprocessing plant for accounting solution of nuclear material. The careful measurement of volume in tanks is very important to implement rigorous accounting of nuclear material. The calibration curve relating the volume and level of solution needs to be constructed, where the level is determined by differential pressure of dip tubes. Several calibration curves are usually employed, but it's not explicitly decided how many segment are used, where to select segment, or what should be the degree of polynomial curve. These parameters, i.e., segment and degree of polynomial curve are mutually interrelated to give the better performance of calibration curve. Here we present the construction technique of giving optimum calibration curves and their characteristics. (author)

51Cr - erythrocyte survival curves

International Nuclear Information System (INIS)

Paiva Costa, J. de.

1982-07-01

Sixteen patients were studied, being fifteen patients in hemolytic state, and a normal individual as a witness. The aim was to obtain better techniques for the analysis of the erythrocytes, survival curves, according to the recommendations of the International Committee of Hematology. It was used the radiochromatic method as a tracer. Previously a revisional study of the International Literature was made in its aspects inherent to the work in execution, rendering possible to establish comparisons and clarify phonomena observed in cur investigation. Several parameters were considered in this study, hindering both the exponential and the linear curves. The analysis of the survival curves of the erythrocytes in the studied group, revealed that the elution factor did not present a homogeneous answer quantitatively to all, though, the result of the analysis of these curves have been established, through listed programs in the electronic calculator. (Author) [pt

Accuracy of progress ratios determined from experience curves: the case of photovoltaic technology development

OpenAIRE

van Sark, W.G.J.H.M.; Alsema, E.A.; Junginger, H.M.; de Moor, H.H.C.; Schaeffer, G.J.

2008-01-01

Learning curves are extensively used in policy and scenario studies. Progress ratios (PRs) are derived from historical data and are used for forecasting cost development of many technologies, including photovoltaics (PV). Forecasts are highly sensitive to uncertainties in the PR. A PR usually is determined together with the coefficient of determination R2, which should approach unity for a good fit of the available data. Although the R2 is instructive, we recommend using the error in the PR d...

Hoarding behaviors in children with learning disabilities.

Science.gov (United States)

Testa, Renée; Pantelis, Christos; Fontenelle, Leonardo F

2011-05-01

Our objective was to describe the prevalence, comorbidity, and neuropsychological profiles of children with hoarding and learning disabilities. From 61 children with learning disabilities, 16.4% exhibited hoarding as a major clinical issue. Although children with learning disabilities and hoarding displayed greater rates of obsessive-compulsive disorder (30%) as compared to those with learning disabilities without hoarding (5.9%), the majority of patients belonging to the former group did not display obsessive-compulsive disorder diagnosis. When learning disability patients with hoarding were compared to age-, sex-, and IQ-matched learning disability subjects without hoarding, hoarders exhibited a slower learning curve on word list-learning task. In conclusion, salient hoarding behaviors were found to be relatively common in a sample of children with learning disabilities and not necessarily associated with obsessive-compulsive disorder, supporting its nosological independence. It is unclear whether underlying cognitive features may play a major role in the development of hoarding behaviors in children with learning disabilities.

Adaptive learning fuzzy control of a mobile robot

International Nuclear Information System (INIS)

Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

1989-11-01

In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

Towards a local learning (innovation) model of solar photovoltaic deployment

International Nuclear Information System (INIS)

Shum, Kwok L.; Watanabe, Chihiro

2008-01-01

It is by now familiar that in the deployment of solar photovoltaic (PV) systems, the cost dynamics of major system component like solar cell/module is subjected to experience curve effects driven by production learning and research and development at the supplier side. What is less clear, however, is the economics of system integration or system deployment that takes place locally close to the user, involving other market players, in the downstream solar PV value chain. Experts have agreed that suppliers of solar PV system must customize their flexible characteristics to address local unique users' and applications requirements and compete on price/performance basis. A lack of understanding of the drivers of the economics of system customization therefore is a deficiency in our understanding of the overall economics of this renewable energy technology option. We studied the non-module BOS cost for grid-connected small PV system using the experience curve framework. Preliminary analysis of PV statistics of the US from IEA seems to suggest that learning in one application type is taking place with respect to the cumulative installation among all types of grid-connected small PV projects. The effectiveness of this learning is also improving over time. A novel aspect is the interpretation of such experience curve effect or learning pattern. We draw upon the notion of product platform in the industrial management literature and consider different types of local small-scale grid-tied PV customization projects as adapting a standard platform to different idiosyncratic and local application requirements. Economics of system customization, which is user-oriented, involves then a refined notion of inter-projects learning, rather than volume-driven learning by doing. We formalized such inter-projects learning as a dynamic economy of scope, which can potentially be leveraged to manage the local and downstream aspect of PV deployment. This dynamic economy may serve as a focus

Hyper-and-elliptic-curve cryptography

NARCIS (Netherlands)

Bernstein, D.J.; Lange, T.

2014-01-01

This paper introduces ‘hyper-and-elliptic-curve cryptography’, in which a single high-security group supports fast genus-2-hyperelliptic-curve formulas for variable-base-point single-scalar multiplication (for example, Diffie–Hellman shared-secret computation) and at the same time supports fast

The utilization of mind map painting on 3D shapes with curved faces

Science.gov (United States)

Nur Sholikhah, Ayuk; Usodo, Budi; Pramudya, Ikrar

2017-12-01

This paper aims to study on the use of mind map painting media on material with 3D shapes with curved faces and its effect on student’s interest. Observation and literature studies were applied as the research method with the sake design of utilization of mind map painting. The result of this research is the design of mind map painting media can improve students' ability to solve problems, improve the ability to think, and maximize brain power. In relation, mind map painting in learning activities is considered to improve student interest.

Power Curve Measurements REWS

DEFF Research Database (Denmark)

Gómez Arranz, Paula; Vesth, Allan

This report describes the power curve measurements carried out on a given wind turbine in a chosen period. The measurements were carried out following the measurement procedure in the draft of IEC 61400-12-1 Ed.2 [1], with some deviations mostly regarding uncertainty calculation. Here, the refere......This report describes the power curve measurements carried out on a given wind turbine in a chosen period. The measurements were carried out following the measurement procedure in the draft of IEC 61400-12-1 Ed.2 [1], with some deviations mostly regarding uncertainty calculation. Here......, the reference wind speed used in the power curve is the equivalent wind speed obtained from lidar measurements at several heights between lower and upper blade tip, in combination with a hub height meteorological mast. The measurements have been performed using DTU’s measurement equipment, the analysis...

A Data-driven Study of RR Lyrae Near-IR Light Curves: Principal Component Analysis, Robust Fits, and Metallicity Estimates

Science.gov (United States)

Hajdu, Gergely; Dékány, István; Catelan, Márcio; Grebel, Eva K.; Jurcsik, Johanna

2018-04-01

RR Lyrae variables are widely used tracers of Galactic halo structure and kinematics, but they can also serve to constrain the distribution of the old stellar population in the Galactic bulge. With the aim of improving their near-infrared photometric characterization, we investigate their near-infrared light curves, as well as the empirical relationships between their light curve and metallicities using machine learning methods. We introduce a new, robust method for the estimation of the light-curve shapes, hence the average magnitudes of RR Lyrae variables in the K S band, by utilizing the first few principal components (PCs) as basis vectors, obtained from the PC analysis of a training set of light curves. Furthermore, we use the amplitudes of these PCs to predict the light-curve shape of each star in the J-band, allowing us to precisely determine their average magnitudes (hence colors), even in cases where only one J measurement is available. Finally, we demonstrate that the K S-band light-curve parameters of RR Lyrae variables, together with the period, allow the estimation of the metallicity of individual stars with an accuracy of ∼0.2–0.25 dex, providing valuable chemical information about old stellar populations bearing RR Lyrae variables. The methods presented here can be straightforwardly adopted for other classes of variable stars, bands, or for the estimation of other physical quantities.

Geometric invariant theory for polarized curves

CERN Document Server

Bini, Gilberto; Melo, Margarida; Viviani, Filippo

2014-01-01

We investigate GIT quotients of polarized curves. More specifically, we study the GIT problem for the Hilbert and Chow schemes of curves of degree d and genus g in a projective space of dimension d-g, as d decreases with respect to g. We prove that the first three values of d at which the GIT quotients change are given by d=a(2g-2) where a=2, 3.5, 4. We show that, for a>4, L. Caporaso's results hold true for both Hilbert and Chow semistability. If 3.5curves. If 2curves. We also analyze in detail the critical values a=3.5 and a=4, where the Hilbert semistable locus is strictly smaller than the Chow semistable locus. As an application, we obtain three compactications of the universal Jacobian over the moduli space of stable curves, weakly-pseudo-stable curves and pseu...

Curved electromagnetic missiles

International Nuclear Information System (INIS)

Myers, J.M.; Shen, H.M.; Wu, T.T.

1989-01-01

Transient electromagnetic fields can exhibit interesting behavior in the limit of great distances from their sources. In situations of finite total radiated energy, the energy reaching a distant receiver can decrease with distance much more slowly than the usual r - 2 . Cases of such slow decrease have been referred to as electromagnetic missiles. All of the wide variety of known missiles propagate in essentially straight lines. A sketch is presented here of a missile that can follow a path that is strongly curved. An example of a curved electromagnetic missile is explicitly constructed and some of its properties are discussed. References to details available elsewhere are given

Machine learning models in breast cancer survival prediction.

Science.gov (United States)

Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

Learning curves in highly skilled chess players: a test of the generality of the power law of practice.

Science.gov (United States)

Howard, Robert W

2014-09-01

The power law of practice holds that a power function best interrelates skill performance and amount of practice. However, the law's validity and generality are moot. Some researchers argue that it is an artifact of averaging individual exponential curves while others question whether the law generalizes to complex skills and to performance measures other than response time. The present study tested the power law's generality to development over many years of a very complex cognitive skill, chess playing, with 387 skilled participants, most of whom were grandmasters. A power or logarithmic function best fit grouped data but individuals showed much variability. An exponential function usually was the worst fit to individual data. Groups differing in chess talent were compared and a power function best fit the group curve for the more talented players while a quadratic function best fit that for the less talented. After extreme amounts of practice, a logarithmic function best fit grouped data but a quadratic function best fit most individual curves. Individual variability is great and the power law or an exponential law are not the best descriptions of individual chess skill development. Copyright © 2014 Elsevier B.V. All rights reserved.

Learning a New Selection Rule in Visual and Frontal Cortex.

Science.gov (United States)

van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

2016-08-01

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

A simple transformation for converting CW-OSL curves to LM-OSL curves

DEFF Research Database (Denmark)

Bulur, E.

2000-01-01

A simple mathematical transformation is introduced to convert from OSL decay curves obtained in the conventional way to those obtained using a linear modulation technique based on a linear increase of the stimulation light intensity during OSL measurement. The validity of the transformation...... was tested by the IR-stimulated luminescence curves from feldspars, recorded using both the conventional and the linear modulation techniques. The transformation was further applied to green-light-stimulated OSL from K and Na feldspars. (C) 2000 Elsevier Science Ltd. All rights reserved....

Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.

Science.gov (United States)

Sengupta, Partho P; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

2016-06-01

Associating a patient's profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography data sets derived from patients with known constrictive pericarditis and restrictive cardiomyopathy. Clinical and echocardiographic data of 50 patients with constrictive pericarditis and 44 with restrictive cardiomyopathy were used for developing an associative memory classifier-based machine-learning algorithm. The speckle tracking echocardiography data were normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve of the associative memory classifier was evaluated for differentiating constrictive pericarditis from restrictive cardiomyopathy. Using only speckle tracking echocardiography variables, associative memory classifier achieved a diagnostic area under the curve of 89.2%, which improved to 96.2% with addition of 4 echocardiographic variables. In comparison, the area under the curve of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63.7%, respectively. Furthermore, the associative memory classifier demonstrated greater accuracy and shorter learning curves than other machine-learning approaches, with accuracy asymptotically approaching 90% after a training fraction of 0.3 and remaining flat at higher training fractions. This study demonstrates feasibility of a cognitive machine-learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine-learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. © 2016

Neural network analysis of head-flow curves in deep well pumps

International Nuclear Information System (INIS)

Goelcue, Mustafa

2006-01-01

In impellers with splitter blades, the difficulty in calculation of the flow area of the impeller is because of the unknown flow rate occurring in the two separate areas when the splitter blades are added. Experimental studies were made to investigate the effects of splitter blade length on deep well pump performance for different numbers of blades. Head-flow curves of deep well pump impellers with splitter blades were investigated using artificial neural networks (ANNs). Gradient descent (GD), Gradient descent with momentum (GDM) and Levenberg-Marquardt (LM) learning algorithms were used in the networks. Experimental studies were completed to obtain training and test data. Blade number (z), non-dimensional splitter blade length (L-bar ) and flow rate (Q) were used as the input layer, while the output is head (H m ). For the testing data, the root mean squared error (RMSE), fraction of variance (R 2 ) and mean absolute percentage error (MAPE) were found to be 0.1285, 0.9999 and 1.6821%, respectively. With these results, we believe that the ANN can be used for prediction of head-flow curves as an appropriate method in deep well pump impellers with splitter blades.

Fermionic fields on ZN-curves

International Nuclear Information System (INIS)

Bershadsky, M.; Radul, A.

1988-01-01

The line bundles of degree g-1 on Z N -curves corresponding to 1/N nonsingular characteristics are considered. The determinants of Dirac operators defined on these line bundles are evaluated in terms of branch points. The generalization of Thomae's formula for Z N -curves is derived. (orig.)

Mannheim Partner D-Curves in the Euclidean 3-space

Directory of Open Access Journals (Sweden)

Mustafa Kazaz

2015-02-01

Full Text Available In this paper, we consider the idea of Mannheim partner curves for curves lying on surfaces. By considering the Darboux frames of surface curves, we define Mannheim partner D-curves and give the characterizations for these curves. We also find the relations between geodesic curvatures, normal curvatures and geodesic torsions of these associated curves. Furthermore, we show that definition and characterizations of Mannheim partner D-curves include those of Mannheim partner curves in some special cases.

Remote sensing used for power curves

International Nuclear Information System (INIS)

Wagner, R; Joergensen, H E; Paulsen, U S; Larsen, T J; Antoniou, I; Thesbjerg, L

2008-01-01

Power curve measurement for large wind turbines requires taking into account more parameters than only the wind speed at hub height. Based on results from aerodynamic simulations, an equivalent wind speed taking the wind shear into account was defined and found to reduce the power standard deviation in the power curve significantly. Two LiDARs and a SoDAR are used to measure the wind profile in front of a wind turbine. These profiles are used to calculate the equivalent wind speed. The comparison of the power curves obtained with the three instruments to the traditional power curve, obtained using a cup anemometer measurement, confirms the results obtained from the simulations. Using LiDAR profiles reduces the error in power curve measurement, when these are used as relative instrument together with a cup anemometer. Results from the SoDAR do not show such promising results, probably because of noisy measurements resulting in distorted profiles

Rational points, rational curves, and entire holomorphic curves on projective varieties

CERN Document Server

Gasbarri, Carlo; Roth, Mike; Tschinkel, Yuri

2015-01-01

This volume contains papers from the Short Thematic Program on Rational Points, Rational Curves, and Entire Holomorphic Curves and Algebraic Varieties, held from June 3-28, 2013, at the Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada. The program was dedicated to the study of subtle interconnections between geometric and arithmetic properties of higher-dimensional algebraic varieties. The main areas of the program were, among others, proving density of rational points in Zariski or analytic topology on special varieties, understanding global geometric properties of rationally connected varieties, as well as connections between geometry and algebraic dynamics exploring new geometric techniques in Diophantine approximation.

Curves and Abelian varieties

CERN Document Server

Alexeev, Valery; Clemens, C Herbert; Beauville, Arnaud

2008-01-01

This book is devoted to recent progress in the study of curves and abelian varieties. It discusses both classical aspects of this deep and beautiful subject as well as two important new developments, tropical geometry and the theory of log schemes. In addition to original research articles, this book contains three surveys devoted to singularities of theta divisors, of compactified Jacobians of singular curves, and of "strange duality" among moduli spaces of vector bundles on algebraic varieties.

Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

Science.gov (United States)

Veli, Muhammed; Ozcan, Aydogan

2018-03-27

We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. Using S. aureus-specific antibodies and a surface chemistry protocol that is compatible with human tears, contact lenses are designed to specifically capture S. aureus. After the bacteria capture on the lens and right before its imaging, the captured bacteria are tagged with surface-functionalized polystyrene microparticles. These microbeads provide sufficient signal-to-noise ratio for the quantification of the captured bacteria on the contact lens, without any fluorescent labels, by 3D imaging of the curved surface of each lens using only one hologram taken with a lens-free on-chip microscope. After the 3D surface of the contact lens is computationally reconstructed using rotational field transformations and holographic digital focusing, a machine learning algorithm is employed to automatically count the number of beads on the lens surface, revealing the count of the captured bacteria. To demonstrate its proof-of-concept, we created a field-portable and cost-effective holographic microscope, which weighs 77 g, controlled by a laptop. Using daily contact lenses that are spiked with bacteria, we demonstrated that this computational sensing platform provides a detection limit of ∼16 bacteria/μL. This contact-lens-based wearable sensor can be broadly applicable to detect various bacteria, viruses, and analytes in tears using a cost-effective and portable computational imager that might be used even at home by consumers.

Test Framing Generates a Stability Bias for Predictions of Learning by Causing People to Discount their Learning Beliefs

Science.gov (United States)

Ariel, Robert; Hines, Jarrod C.; Hertzog, Christopher

2014-01-01

People estimate minimal changes in learning when making predictions of learning (POLs) for future study opportunities despite later showing increased performance and an awareness of that increase (Kornell & Bjork, 2009). This phenomenon is conceptualized as a stability bias in judgments about learning. We investigated the malleability of this effect, and whether it reflected people’s underlying beliefs about learning. We manipulated prediction framing to emphasize the role of testing vs. studying on memory and directly measured beliefs about multi-trial study effects on learning by having participants construct predicted learning curves before and after the experiment. Mean POLs were more sensitive to the number of study-test opportunities when performance was framed in terms of study benefits rather than testing benefits and POLs reflected pre-existing beliefs about learning. The stability bias is partially due to framing and reflects discounted beliefs about learning benefits rather than inherent belief in the stability of performance. PMID:25067885

Anatomical curve identification

Science.gov (United States)

Bowman, Adrian W.; Katina, Stanislav; Smith, Joanna; Brown, Denise

2015-01-01

Methods for capturing images in three dimensions are now widely available, with stereo-photogrammetry and laser scanning being two common approaches. In anatomical studies, a number of landmarks are usually identified manually from each of these images and these form the basis of subsequent statistical analysis. However, landmarks express only a very small proportion of the information available from the images. Anatomically defined curves have the advantage of providing a much richer expression of shape. This is explored in the context of identifying the boundary of breasts from an image of the female torso and the boundary of the lips from a facial image. The curves of interest are characterised by ridges or valleys. Key issues in estimation are the ability to navigate across the anatomical surface in three-dimensions, the ability to recognise the relevant boundary and the need to assess the evidence for the presence of the surface feature of interest. The first issue is addressed by the use of principal curves, as an extension of principal components, the second by suitable assessment of curvature and the third by change-point detection. P-spline smoothing is used as an integral part of the methods but adaptations are made to the specific anatomical features of interest. After estimation of the boundary curves, the intermediate surfaces of the anatomical feature of interest can be characterised by surface interpolation. This allows shape variation to be explored using standard methods such as principal components. These tools are applied to a collection of images of women where one breast has been reconstructed after mastectomy and where interest lies in shape differences between the reconstructed and unreconstructed breasts. They are also applied to a collection of lip images where possible differences in shape between males and females are of interest. PMID:26041943

A study of active learning methods for named entity recognition in clinical text.

Science.gov (United States)

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

MODELING THE TRANSITION CURVE ON A LIMITED TERAIN

Directory of Open Access Journals (Sweden)

V. D. Borisenko

2017-04-01

Full Text Available Purpose. Further development of the method of geometric modelling of transition curves, which are placed between rectilinear and circular sections of railway tracks and are created in localities, the relief of which causes certain restrictions on the size of the transition curves of the railway track. Methodology. The equation of the transition curve is taken in parametric form, in which the length of the arc of the modelled curve is used as a parameter. As initial data in the modelling of the transition curve, the coordinates of its initial point and the angle of inclination in it are tangent, the radius of the circumference of the circular section and the parameter that is used as a constraint when placing a section of the railway track. The transition curve is modelled under the condition that the distribution of its curvature from the length of the arc - the natural parameter - is described by a cubic dependence. This dependence contains four unknown coefficients; the unknown is also the length of the arc. The coefficients of the cubic dependence and the length of the arc of the transition curve, the coordinates of its end point, the angle of inclination in it of the tangent are determined during the simulation of the transition curve. The application of boundary conditions and methods of differential geometry with respect to the distribution of the slope angle of the tangent to the simulated curve from the initial to the end points of the transition curve and the calculation of the coordinates of the end point of the curve allows us to reduce the problem of modelling the transition curve to determine the arc length of this curve. Directly the length of the transition curve is in the process of minimizing the deviation of the circumference of the circular path from its current value obtained when searching for the arc length. Findings. As a result of the computational experiment, the possibility of modelling a transition curve between a

Global experience curves for wind farms

International Nuclear Information System (INIS)

Junginger, M.; Faaij, A.; Turkenburg, W.C.

2005-01-01

In order to forecast the technological development and cost of wind turbines and the production costs of wind electricity, frequent use is made of the so-called experience curve concept. Experience curves of wind turbines are generally based on data describing the development of national markets, which cause a number of problems when applied for global assessments. To analyze global wind energy price development more adequately, we compose a global experience curve. First, underlying factors for past and potential future price reductions of wind turbines are analyzed. Also possible implications and pitfalls when applying the experience curve methodology are assessed. Second, we present and discuss a new approach of establishing a global experience curve and thus a global progress ratio for the investment cost of wind farms. Results show that global progress ratios for wind farms may lie between 77% and 85% (with an average of 81%), which is significantly more optimistic than progress ratios applied in most current scenario studies and integrated assessment models. While the findings are based on a limited amount of data, they may indicate faster price reduction opportunities than so far assumed. With this global experience curve we aim to improve the reliability of describing the speed with which global costs of wind power may decline

Polar representation of centrifugal pump homologous curves

International Nuclear Information System (INIS)

Veloso, Marcelo Antonio; Mattos, Joao Roberto Loureiro de

2008-01-01

Essential for any mathematical model designed to simulate flow transient events caused by pump operations is the pump performance data. The performance of a centrifugal pump is characterized by four basic parameters: the rotational speed, the volumetric flow rate, the dynamic head, and the hydraulic torque. Any one of these quantities can be expressed as a function of any two others. The curves showing the relationships between these four variables are called the pump characteristic curves, also referred to as four-quadrant curves. The characteristic curves are empirically developed by the pump manufacturer and uniquely describe head and torque as functions of volumetric flow rate and rotation speed. Because of comprising a large amount of points, the four-quadrant configuration is not suitable for computational purposes. However, it can be converted to a simpler form by the development of the homologous curves, in which dynamic head and hydraulic torque ratios are expressed as functions of volumetric flow and rotation speed ratios. The numerical use of the complete set of homologous curves requires specification of sixteen partial curves, being eight for the dynamic head and eight for the hydraulic torque. As a consequence, the handling of homologous curves is still somewhat complicated. In solving flow transient problems that require the pump characteristic data for all the operation zones, the polar form appears as the simplest way to represent the homologous curves. In the polar method, the complete characteristics of a pump can be described by only two closed curves, one for the dynamic head and other for the hydraulic torque, both in function of a single angular coordinate defined adequately in terms of the quotient between volumetric flow ratio and rotation speed ratio. The usefulness and advantages of this alternative method are demonstrated through a practical example in which the homologous curves for a pump of the type used in the main coolant loops of a

Applying active learning to supervised word sense disambiguation in MEDLINE.

Science.gov (United States)

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models.

Parametric representation of centrifugal pump homologous curves

International Nuclear Information System (INIS)

Veloso, Marcelo A.; Mattos, Joao R.L. de

2015-01-01

Essential for any mathematical model designed to simulate flow transient events caused by pump operations is the pump performance data. The performance of a centrifugal pump is characterized by four basic quantities: the rotational speed, the volumetric flow rate, the dynamic head, and the hydraulic torque. The curves showing the relationships between these four variables are called the pump characteristic curves. The characteristic curves are empirically developed by the pump manufacturer and uniquely describe head and torque as functions of volumetric flow rate and rotation speed. Because of comprising a large amount of points, this configuration is not suitable for computational purposes. However, it can be converted to a simpler form by the development of the homologous curves, in which dynamic head and hydraulic torque ratios are expressed as functions of volumetric flow and rotation speed ratios. The numerical use of the complete set of homologous curves requires specification of sixteen partial curves, being eight for the dynamic head and eight for the hydraulic torque. As a consequence, the handling of homologous curves is still somewhat complicated. In solving flow transient problems that require the pump characteristic data for all the operation zones, the parametric form appears as the simplest way to deal with the homologous curves. In this approach, the complete characteristics of a pump can be described by only two closed curves, one for the dynamic head and other for the hydraulic torque, both in function of a single angular coordinate defined adequately in terms of the quotient between volumetric flow ratio and rotation speed ratio. The usefulness and advantages of this alternative method are demonstrated through a practical example in which the homologous curves for a pump of the type used in the main coolant loops of a pressurized water reactor (PWR) are transformed to the parametric form. (author)

Section curve reconstruction and mean-camber curve extraction of a point-sampled blade surface.

Directory of Open Access Journals (Sweden)

Wen-long Li

Full Text Available The blade is one of the most critical parts of an aviation engine, and a small change in the blade geometry may significantly affect the dynamics performance of the aviation engine. Rapid advancements in 3D scanning techniques have enabled the inspection of the blade shape using a dense and accurate point cloud. This paper proposes a new method to achieving two common tasks in blade inspection: section curve reconstruction and mean-camber curve extraction with the representation of a point cloud. The mathematical morphology is expanded and applied to restrain the effect of the measuring defects and generate an ordered sequence of 2D measured points in the section plane. Then, the energy and distance are minimized to iteratively smoothen the measured points, approximate the section curve and extract the mean-camber curve. In addition, a turbine blade is machined and scanned to observe the curvature variation, energy variation and approximation error, which demonstrates the availability of the proposed method. The proposed method is simple to implement and can be applied in aviation casting-blade finish inspection, large forging-blade allowance inspection and visual-guided robot grinding localization.

NOISY DISPERSION CURVE PICKING (NDCP): a Matlab friendly suite package for fully control dispersion curve picking

Science.gov (United States)

Granados, I.; Calo, M.; Ramos, V.

2017-12-01

We developed a Matlab suite package (NDCP, Noisy Dispersion Curve Picking) that allows a full control over parameters to identify correctly group velocity dispersion curves in two types of datasets: correlograms between two stations or surface wave records from earthquakes. Using the frequency-time analysis (FTAN), the procedure to obtain the dispersion curves from records with a high noise level becomes difficult, and sometimes, the picked curve result in a misinterpreted character. For correlogram functions, obtained with cross-correlation of noise records or earthquake's coda, a non-homogeneous noise sources distribution yield to a non-symmetric Green's function (GF); to retrieve the complete information contained in there, NDCP allows to pick the dispersion curve in the time domain both in the causal and non-causal part of the GF. Then the picked dispersion curve is displayed on the FTAN diagram to in order to check if it matches with the maximum of the signal energy avoiding confusion with overtones or spike of noise. To illustrate how NDCP performs, we show exemple using: i) local correlograms functions obtained from sensors deployed into a volcanic caldera (Los Humeros, in Puebla, Mexico), ii) regional correlograms functions between two stations of the National Seismological Service (SSN, Servicio Sismológico Nacional in Spanish), and iii) surface wave seismic record for an earthquake located in the Pacific Ocean coast of Mexico and recorded by the SSN. This work is supported by the GEMEX project (Geothermal Europe-Mexico consortium).

A simple Lissajous curves experimental setup

Science.gov (United States)

Şahin Kızılcık, Hasan; Damlı, Volkan

2018-05-01

The aim of this study is to develop an experimental setup to produce Lissajous curves. The setup was made using a smartphone, a powered speaker (computer speaker), a balloon, a laser pointer and a piece of mirror. Lissajous curves are formed as follows: a piece of mirror is attached to a balloon. The balloon is vibrated with the sound signal provided by the speaker that is connected to a smartphone. The laser beam is reflected off the mirror and the reflection is shaped as a Lissajous curve. Because of the intersection of two frequencies (frequency of the sound signal and natural vibration frequency of the balloon), these curves are formed. They can be used to measure the ratio of frequencies.

Quantum fields in curved space

International Nuclear Information System (INIS)

Birrell, N.D.; Davies, P.C.W.

1982-01-01

The book presents a comprehensive review of the subject of gravitational effects in quantum field theory. Quantum field theory in Minkowski space, quantum field theory in curved spacetime, flat spacetime examples, curved spacetime examples, stress-tensor renormalization, applications of renormalization techniques, quantum black holes and interacting fields are all discussed in detail. (U.K.)

SRHA calibration curve

Data.gov (United States)

U.S. Environmental Protection Agency — an UV calibration curve for SRHA quantitation. This dataset is associated with the following publication: Chang, X., and D. Bouchard. Surfactant-Wrapped Multiwalled...

The learning potential of photovoltaics: implications for energy policy

International Nuclear Information System (INIS)

Zwaan, Bob van der; Rabl, Ari

2004-01-01

This article examines the prospects for cost reductions of flat panel photovoltaic (PV) electricity. Current PV production cost ranges are presented, in terms of cost per peak W and cost per kWh, for single crystalline and multi-crystalline silicon, as well as for thin-film technologies. Possible decreases of these costs are assessed, as expected based on learning curves. The cumulative production needed to reach 'breakeven' (at which PV is competitive with conventional alternatives) is estimated for a range of values of the learning curve parameter. The cost of this cumulative production is calculated, and the question is posed whether and how the 'cost cap' can be bridged, the latter being the difference between what this cumulative production will cost and what it would cost if it could be produced at a currently competitive level. We also estimate how much PV could gain if external costs (due to environmental and health damage) of energy were internalised, for example by an energy tax. The conclusions are: (1) mainly due its high costs, PV electricity is unlikely to play a major role in global energy supply and carbon emissions abatement before 2020, (2) extrapolating past learning curves, one can expect its costs to decrease significantly, so that a considerable PV electricity share world-wide could materialise after 2020, (3) niche-market applications, e.g. using stand-alone systems in remote areas, are crucial for continuing 'the ride along the learning curve', (4) damage costs of conventional (fossil) power sources are considerable, and they could provide an important part of the rationale behind major policy efforts to encourage increased use of PV. The costs involved with such policies would be elevated, but a considerable share of these costs could be justified by the fact that conventional power damage costs constitute a significant fraction of the cost gap, although probably not enough to close it

Holomorphic curves in exploded manifolds: Kuranishi structure

OpenAIRE

Parker, Brett

2013-01-01

This paper constructs a Kuranishi structure for the moduli stack of holomorphic curves in exploded manifolds. To avoid some technicalities of abstract Kuranishi structures, we embed our Kuranishi structure inside a moduli stack of curves. The construction also works for the moduli stack of holomorphic curves in any compact symplectic manifold.

Transition curves for highway geometric design

CERN Document Server

Kobryń, Andrzej

2017-01-01

This book provides concise descriptions of the various solutions of transition curves, which can be used in geometric design of roads and highways. It presents mathematical methods and curvature functions for defining transition curves. .

Crashes and near-crashes on horizontal curves along rural two-lane highways: Analysis of naturalistic driving data.

Science.gov (United States)

Wang, Bo; Hallmark, Shauna; Savolainen, Peter; Dong, Jing

2017-12-01

Prior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves. The second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions. Logistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions. This paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data. This paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit

Super-quantum curves from super-eigenvalue models

Energy Technology Data Exchange (ETDEWEB)

Ciosmak, Paweł [Faculty of Mathematics, Informatics and Mechanics, University of Warsaw,ul. Banacha 2, 02-097 Warsaw (Poland); Hadasz, Leszek [M. Smoluchowski Institute of Physics, Jagiellonian University,ul. Łojasiewicza 11, 30-348 Kraków (Poland); Manabe, Masahide [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Sułkowski, Piotr [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E. California Blvd, Pasadena, CA 91125 (United States)

2016-10-10

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

International Nuclear Information System (INIS)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-01-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

Science.gov (United States)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-10-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/ β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Bragg Curve, Biological Bragg Curve and Biological Issues in Space Radiation Protection with Shielding

Science.gov (United States)

Honglu, Wu; Cucinotta, F.A.; Durante, M.; Lin, Z.; Rusek, A.

2006-01-01

The space environment consists of a varying field of radiation particles including high-energy ions, with spacecraft shielding material providing the major protection to astronauts from harmful exposure. Unlike low-LET gamma or X-rays, the presence of shielding does not always reduce the radiation risks for energetic charged particle exposure. Since the dose delivered by the charged particle increases sharply as the particle approaches the end of its range, a position known as the Bragg peak, the Bragg curve does not necessarily represent the biological damage along the particle traversal since biological effects are influenced by the track structure of both primary and secondary particles. Therefore, the biological Bragg curve is dependent on the energy and the type of the primary particle, and may vary for different biological endpoints. To achieve a Bragg curve distribution, we exposed cells to energetic heavy ions with the beam geometry parallel to a monolayer of fibroblasts. Qualitative analyses of gamma-H2AX fluorescence, a known marker of DSBs, indicated increased clustering of DNA damage before the Bragg peak, enhanced homogenous distribution at the peak, and provided visual evidence of high linear energy transfer (LET) particle traversal of cells beyond the Bragg peak. A quantitative biological response curve generated for micronuclei (MN) induction across the Bragg curve did not reveal an increased yield of MN at the location of the Bragg peak. However, the ratio of mono-to bi-nucleated cells, which indicates inhibition in cell progression, increased at the Bragg peak location. These results, along with other biological concerns, show that space radiation protection with shielding can be a complicated issue.

Theoretical melting curve of caesium

International Nuclear Information System (INIS)

Simozar, S.; Girifalco, L.A.; Pennsylvania Univ., Philadelphia

1983-01-01

A statistical-mechanical model is developed to account for the complex melting curve of caesium. The model assumes the existence of three different species of caesium defined by three different electronic states. On the basis of this model, the free energy of melting and the melting curve are computed up to 60 kbar, using the solid-state data and the initial slope of the fusion curve as input parameters. The calculated phase diagram agrees with experiment to within the experimental error. Other thermodynamic properties including the entropy and volume of melting were also computed, and they agree with experiment. Since the theory requires only one adjustable constant, this is taken as strong evidence that the three-species model is satisfactory for caesium. (author)

Curve collection, extension of databases

International Nuclear Information System (INIS)

Gillemot, F.

1992-01-01

Full text: Databases: generally calculated data only. The original measurements: diagrams. Information loss between them Expensive research eg. irradiation, aging, creep etc. Original curves should be stored for reanalysing. The format of the stored curves: a. Data in ASCII files, only numbers b. Other information in strings in a second file Same name, but different extension. Extensions shows the type of the test and the type of the file. EXAMPLES. TEN is tensile information, TED is tensile data, CHN is Charpy informations, CHD is Charpy data. Storing techniques: digitalised measurements, digitalising old curves stored on paper. Use: making catalogues, reanalysing, comparison with new data. Tools: mathematical software packages like quattro, genplot, exel, mathcad, qbasic, pascal, fortran, mathlab, grapher etc. (author)

Practically perfect: learning by doing at AVS congress.

Science.gov (United States)

2017-02-18

It has been some time since Cambridge vet school last hosted the annual AVS congress, which meant that this year's congress committee faced a steep learning curve. However, as Gill Harris reports, it rose to the occasion. British Veterinary Association.

Impact of learning curve and technical changes on dosimetry in low-dose brachytherapy for prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Le Fur, E. [CHU Brest (France). Radiation Therapy Dept.; Universite de Bretagne Occidentale, Brest (France). Faculte de Medecine et des Sciences de la Sante; Malhaire, J.P.; Baverez, D.; Schlurmann, F. [CHU Brest (France). Radiation Therapy Dept.; Delage, F.; Perrouin-Verbe, M.A. [CHU Brest (France). Urology Dept.; Guerif, S. [University Hospital La Miletrie, Poitiers (France). Radiation Therapy Dept.; Poitiers Univ. (France); Fournier, G.; Valeri, A. [CHU Brest (France). Urology Dept.; Universite de Bretagne Occidentale, Brest (France). Faculte de Medecine et des Sciences de la Sante; Universite Europeenne de Bretagne, Rennes (France); APHP, Hopital Tenon, Paris (France). CeRe.PP; Pradier, O. [CHU Brest (France). Radiation Therapy Dept.; Universite de Bretagne Occidentale, Brest (France). Faculte de Medecine et des Sciences de la Sante; Universite Europeenne de Bretagne, Rennes (France); CHU Brest (France). LaTIM, INSERM U650

2012-12-15

Purpose: To assess the impact of experience and technical changes on peri- and postimplantation (1 month later) dosimetry for permanent prostate brachytherapy (PPB). Patients and methods: From July 2003 to May 2010, 150 prostate cancer patients underwent low-dose, loose-seed I{sup 125} PPB as monotherapy with intraoperative planning. Patients were divided into three groups - P1 (n = 64), P2 (n = 45), P3 (n = 41) - according to the technical changes that occurred during the study period: use of an automatic stepper at the beginning of P2 and a high-frequency ultrasound probe in P3. Peri- and postimplantation dosimetric parameters (on day 30) were reported: D90 (dose received by 90% of prostate volume), V100 and V150 (prostate volume receiving, respectively, 100% and 150% of the prescribed dose), D2 cc and D0.1 cc (doses received by 2 cc and 0.1 cc of the rectum), R100 (rectum volume that received 100% of the prescribed dose), and D10 and D30 (doses received by 10% and 30% of the urethra, only during peri-implantation). Results: We observed a decrease in the number of needles and seeds used over time. The mean peri-implantation D90 was 187.52 Gy without a significant difference between the three periods (p = 0.48). The postimplantation D90, V100, and V150 parameters were, respectively, 168.3 Gy, 91.9%, and 55% with no significant difference between the three periods. The peri-implantation and postimplantation D0.1 cc and R100 significantly decreased over time; on day 30: D0.1 cc P1 = 223.1 Gy vs. D0.1 cc P3 = 190.4 Gy (p = 8.10- 5) and R100 P1 = 1.06 cc vs. R100 P3 = 0.53 cc (p = 0.0008). Conclusion: We observed a learning curve for the implantation parameters, which led to a significant decrease in the rectal doses without having any impact on the prostate dosimetric parameters. (orig.)

Impact of learning curve and technical changes on dosimetry in low-dose brachytherapy for prostate cancer

International Nuclear Information System (INIS)

Le Fur, E.; Fournier, G.; Valeri, A.; Universite de Bretagne Occidentale, Brest; Universite Europeenne de Bretagne, Rennes; APHP, Hopital Tenon, Paris; Pradier, O.; Universite de Bretagne Occidentale, Brest; Universite Europeenne de Bretagne, Rennes; CHU Brest

2012-01-01

Purpose: To assess the impact of experience and technical changes on peri- and postimplantation (1 month later) dosimetry for permanent prostate brachytherapy (PPB). Patients and methods: From July 2003 to May 2010, 150 prostate cancer patients underwent low-dose, loose-seed I 125 PPB as monotherapy with intraoperative planning. Patients were divided into three groups - P1 (n = 64), P2 (n = 45), P3 (n = 41) - according to the technical changes that occurred during the study period: use of an automatic stepper at the beginning of P2 and a high-frequency ultrasound probe in P3. Peri- and postimplantation dosimetric parameters (on day 30) were reported: D90 (dose received by 90% of prostate volume), V100 and V150 (prostate volume receiving, respectively, 100% and 150% of the prescribed dose), D2 cc and D0.1 cc (doses received by 2 cc and 0.1 cc of the rectum), R100 (rectum volume that received 100% of the prescribed dose), and D10 and D30 (doses received by 10% and 30% of the urethra, only during peri-implantation). Results: We observed a decrease in the number of needles and seeds used over time. The mean peri-implantation D90 was 187.52 Gy without a significant difference between the three periods (p = 0.48). The postimplantation D90, V100, and V150 parameters were, respectively, 168.3 Gy, 91.9%, and 55% with no significant difference between the three periods. The peri-implantation and postimplantation D0.1 cc and R100 significantly decreased over time; on day 30: D0.1 cc P1 = 223.1 Gy vs. D0.1 cc P3 = 190.4 Gy (p = 8.10- 5) and R100 P1 = 1.06 cc vs. R100 P3 = 0.53 cc (p = 0.0008). Conclusion: We observed a learning curve for the implantation parameters, which led to a significant decrease in the rectal doses without having any impact on the prostate dosimetric parameters. (orig.)

Sibling curves of quadratic polynomials | Wiggins | Quaestiones ...

African Journals Online (AJOL)

Sibling curves were demonstrated in [1, 2] as a novel way to visualize the zeroes of real valued functions. In [3] it was shown that a polynomial of degree n has n sibling curves. This paper focuses on the algebraic and geometric properites of the sibling curves of real and complex quadratic polynomials. Key words: Quadratic ...

Retiring the Short-Run Aggregate Supply Curve

Science.gov (United States)

Elwood, S. Kirk

2010-01-01

The author argues that the aggregate demand/aggregate supply (AD/AS) model is significantly improved--although certainly not perfected--by trimming it of the short-run aggregate supply (SRAS) curve. Problems with the SRAS curve are shown first for the AD/AS model that casts the AD curve as identifying the equilibrium level of output associated…

Comparison of power curve monitoring methods

Directory of Open Access Journals (Sweden)

Cambron Philippe

2017-01-01

Full Text Available Performance monitoring is an important aspect of operating wind farms. This can be done through the power curve monitoring (PCM of wind turbines (WT. In the past years, important work has been conducted on PCM. Various methodologies have been proposed, each one with interesting results. However, it is difficult to compare these methods because they have been developed using their respective data sets. The objective of this actual work is to compare some of the proposed PCM methods using common data sets. The metric used to compare the PCM methods is the time needed to detect a change in the power curve. Two power curve models will be covered to establish the effect the model type has on the monitoring outcomes. Each model was tested with two control charts. Other methodologies and metrics proposed in the literature for power curve monitoring such as areas under the power curve and the use of statistical copulas have also been covered. Results demonstrate that model-based PCM methods are more reliable at the detecting a performance change than other methodologies and that the effectiveness of the control chart depends on the types of shift observed.

Principal Curves on Riemannian Manifolds.

Science.gov (United States)

Hauberg, Soren

2016-09-01

Euclidean statistics are often generalized to Riemannian manifolds by replacing straight-line interpolations with geodesic ones. While these Riemannian models are familiar-looking, they are restricted by the inflexibility of geodesics, and they rely on constructions which are optimal only in Euclidean domains. We consider extensions of Principal Component Analysis (PCA) to Riemannian manifolds. Classic Riemannian approaches seek a geodesic curve passing through the mean that optimizes a criteria of interest. The requirements that the solution both is geodesic and must pass through the mean tend to imply that the methods only work well when the manifold is mostly flat within the support of the generating distribution. We argue that instead of generalizing linear Euclidean models, it is more fruitful to generalize non-linear Euclidean models. Specifically, we extend the classic Principal Curves from Hastie & Stuetzle to data residing on a complete Riemannian manifold. We show that for elliptical distributions in the tangent of spaces of constant curvature, the standard principal geodesic is a principal curve. The proposed model is simple to compute and avoids many of the pitfalls of traditional geodesic approaches. We empirically demonstrate the effectiveness of the Riemannian principal curves on several manifolds and datasets.

RMS fatigue curves for random vibrations

International Nuclear Information System (INIS)

Brenneman, B.; Talley, J.G.

1984-01-01

Fatigue usage factors for deterministic or constant amplitude vibration stresses may be calculated with well known procedures and fatigue curves given in the ASME Boiler and Pressure Vessel Code. However, some phenomena produce nondeterministic cyclic stresses which can only be described and analyzed with statistical concepts and methods. Such stresses may be caused by turbulent fluid flow over a structure. Previous methods for solving this statistical fatigue problem are often difficult to use and may yield inaccurate results. Two such methods examined herein are Crandall's method and the ''3sigma'' method. The objective of this paper is to provide a method for creating ''RMS fatigue curves'' which accurately incorporate the requisite statistical information. These curves are given and may be used by analysts with the same ease and in the same manner as the ASME fatigue curves

A framework for technological learning in the supply chain: A case study on CdTe photovoltaics

International Nuclear Information System (INIS)

Bergesen, Joseph D.; Suh, Sangwon

2016-01-01

Highlights: • A framework for technological learning in the supply chain is proposed. • This framework separates learning effects on value added and intermediate inputs. • Supply-chain learning can project both changing environmental impacts and costs. • Learning upstream in the supply chain can influence observed learning rates. • An example for CdTe photovoltaics illustrates how this framework can be implemented. - Abstract: Accounting for technological changes and innovation is important when assessing the implications of rapidly-developing greenhouse gas (GHG) mitigation technologies. Technological learning curves have been commonly used as a tool to understand technological change as a function of cumulative production. Traditional learning curve approaches, however, do not distinguish the direct and upstream, supply chain technological changes by which cost reductions are achieved. While recent advances in learning curves have focused on distinguishing the different physical and economic drivers of learning, forecasted technological changes have not been applied to estimate the potential changes in the environmental performance of a technology. This article illustrates how distinguishing the different effects of technological learning throughout the supply chain can help assess the changing costs, environmental impacts and natural resource implications of technologies as they develop. We propose a mathematical framework to distinguish the effects of learning on the direct inputs to a technology from the effects of learning on value added, and we incorporate those effects throughout the supply chain of a technology using a life cycle assessment (LCA) framework. An example for cadmium telluride (CdTe) photovoltaics (PV) illustrates how the proposed framework can be implemented. Results show that that life cycle GHG emissions can decrease at least 40% and costs can decrease at least 50% as cumulative production of CdTe reaches 100 GW. Technological

Overcoming the learning curve of single-port total laparoscopic hysterectomy with barbed suture: a single surgeon's initial experience.

Science.gov (United States)

Lee, Yoon Hee; Chong, Gun Oh; Kim, Mi Ju; Gy Hong, Dae; Lee, Yoon Soon

2017-09-01

Single-port total laparoscopic hysterectomy (TLH) has not been widely used because of its technical difficulty and steep learning curve, especially the laparoscopic suturing of the vaginal stump. Barbed suturing is a new technology that has the potential to greatly facilitate laparoscopic suturing. To compare surgical outcomes and vaginal vault healing between barbed sutures and traditional sutures in the repair of the vaginal vault during single-port TLH. Between August 2013 and June 2015, we performed single-port TLH in 85 consecutive patients for benign or premalignant gynecological conditions. The first 48 patients underwent single-port TLH with traditional interrupted sutures, and the next 37 patients underwent single-port TLH with absorbable unidirectional knotless barbed sutures for repair of the vaginal vault. The patient characteristics (age, body mass index), procedures performed, uterine weight, and uterine disease were similar between the groups. There were no differences in blood loss, hemoglobin change, length of hospital stay, or perioperative complications. Operative time and the time required for vaginal cuff suturing were significantly shorter in the barbed suture group than in the traditional suture group (57.8 ±13.5 vs. 80.1 ±18.7 min, p < 0.001; 5.5 ±1.7 vs. 12.9 ±3.5 min, p < 0.001). Moreover, the use of barbed sutures significantly reduced the incidence of vaginal granulation tissue formation (2.7% vs. 35.4%, p < 0.001). Use of barbed sutures in single-port TLH reduced the operative time, suturing time of the vaginal vault, and formation of vaginal granulation tissue. Barbed suturing may help overcome surgical difficulties and vaginal cuff complications.

Projection-based curve clustering

International Nuclear Information System (INIS)

Auder, Benjamin; Fischer, Aurelie

2012-01-01

This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

Applying active learning to supervised word sense disambiguation in MEDLINE

Science.gov (United States)

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

Objectives This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. Methods We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Results Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. Conclusions This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models. PMID:23364851

Minimal families of curves on surfaces

KAUST Repository

Lubbes, Niels

2014-01-01

A minimal family of curves on an embedded surface is defined as a 1-dimensional family of rational curves of minimal degree, which cover the surface. We classify such minimal families using constructive methods. This allows us to compute the minimal

Methods for predicting isochronous stress-strain curves

International Nuclear Information System (INIS)

Kiyoshige, Masanori; Shimizu, Shigeki; Satoh, Keisuke.

1976-01-01

Isochronous stress-strain curves show the relation between stress and total strain at a certain temperature with time as a parameter, and they are drawn up from the creep test results at various stress levels at a definite temperature. The concept regarding the isochronous stress-strain curves was proposed by McVetty in 1930s, and has been used for the design of aero-engines. Recently the high temperature characteristics of materials are shown as the isochronous stress-strain curves in the design guide for the nuclear energy equipments and structures used in high temperature creep region. It is prescribed that these curves are used as the criteria for determining design stress intensity or the data for analyzing the superposed effects of creep and fatigue. In case of the isochronous stress-strain curves used for the design of nuclear energy equipments with very long service life, it is impractical to determine the curves directly from the results of long time creep test, accordingly the method of predicting long time stress-strain curves from short time creep test results must be established. The method proposed by the authors, for which the creep constitution equations taking the first and second creep stages into account are used, and the method using Larson-Miller parameter were studied, and it was found that both methods were reliable for the prediction. (Kako, I.)

A strategic systems perspective of organizational learning theory: models for a case study at the Jet Propulsion Laboratory

Science.gov (United States)

Neece, O.

2000-01-01

Organizational learning is an umbrella term that covers a variety of topics including; learning curves, productivity, organizational memory, organizational forgetting, knowledge transfer, knowledge sharing and knowledge creation. This treatise will review some of these theories in concert with a model of how organizations learn.

Comparison of wind turbines based on power curve analysis

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-02-01

In the study measured power curves for 46 wind turbines were analyzed with the purpose to establish the basis for a consistent comparison of the efficiency of the wind turbines. Emphasis is on wind turbines above 500 kW rated power, with power curves measured after 1994 according to international recommendations. The available power curves fulfilling these requirements were smoothened according to a procedure developed for the purpose in such a way that the smoothened power curves are equally representative as the measured curves. The resulting smoothened power curves are presented in a standardized format for the subsequent processing. Using wind turbine data from the power curve documentation the analysis results in curves for specific energy production (kWh/M{sup 2}/yr) versus specific rotor load (kW/M{sup 2}) for a range of mean wind speeds. On this basis generalized curves for specific annual energy production versus specific rotor load are established for a number of generalized wind turbine concepts. The 46 smoothened standardized power curves presented in the report, the procedure developed to establish them, and the results of the analysis based on them aim at providers of measured power curves as well as users of them including manufacturers, advisors and decision makers. (au)

Algebraic curves and cryptography

CERN Document Server

Murty, V Kumar

2010-01-01

It is by now a well-known paradigm that public-key cryptosystems can be built using finite Abelian groups and that algebraic geometry provides a supply of such groups through Abelian varieties over finite fields. Of special interest are the Abelian varieties that are Jacobians of algebraic curves. All of the articles in this volume are centered on the theme of point counting and explicit arithmetic on the Jacobians of curves over finite fields. The topics covered include Schoof's \\ell-adic point counting algorithm, the p-adic algorithms of Kedlaya and Denef-Vercauteren, explicit arithmetic on

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

Science.gov (United States)

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Statistics from dynamics in curved spacetime

International Nuclear Information System (INIS)

Parker, L.; Wang, Y.

1989-01-01

We consider quantum fields of spin 0, 1/2, 1, 3/2, and 2 with a nonzero mass in curved spacetime. We show that the dynamical Bogolubov transformations associated with gravitationally induced particle creation imply the connection between spin and statistics: By embedding two flat regions in a curved spacetime, we find that only when one imposes Bose-Einstein statistics for an integer-spin field and Fermi-Dirac statistics for a half-integer-spin field in the first flat region is the same type of statistics propagated from the first to the second flat region. This derivation of the flat-spacetime spin-statistics theorem makes use of curved-spacetime dynamics and does not reduce to any proof given in flat spacetime. We also show in the same manner that parastatistics, up to the fourth order, are consistent with the dynamical evolution of curved spacetime

Environmental bias and elastic curves on surfaces

International Nuclear Information System (INIS)

Guven, Jemal; María Valencia, Dulce; Vázquez-Montejo, Pablo

2014-01-01

The behavior of an elastic curve bound to a surface will reflect the geometry of its environment. This may occur in an obvious way: the curve may deform freely along directions tangent to the surface, but not along the surface normal. However, even if the energy itself is symmetric in the curve's geodesic and normal curvatures, which control these modes, very distinct roles are played by the two. If the elastic curve binds preferentially on one side, or is itself assembled on the surface, not only would one expect the bending moduli associated with the two modes to differ, binding along specific directions, reflected in spontaneous values of these curvatures, may be favored. The shape equations describing the equilibrium states of a surface curve described by an elastic energy accommodating environmental factors will be identified by adapting the method of Lagrange multipliers to the Darboux frame associated with the curve. The forces transmitted to the surface along the surface normal will be determined. Features associated with a number of different energies, both of physical relevance and of mathematical interest, are described. The conservation laws associated with trajectories on surface geometries exhibiting continuous symmetries are also examined. (paper)

Greater Activity in the Frontal Cortex on Left Curves: A Vector-Based fNIRS Study of Left and Right Curve Driving.

Directory of Open Access Journals (Sweden)

Noriyuki Oka

Full Text Available In the brain, the mechanisms of attention to the left and the right are known to be different. It is possible that brain activity when driving also differs with different horizontal road alignments (left or right curves, but little is known about this. We found driver brain activity to be different when driving on left and right curves, in an experiment using a large-scale driving simulator and functional near-infrared spectroscopy (fNIRS.The participants were fifteen healthy adults. We created a course simulating an expressway, comprising straight line driving and gentle left and right curves, and monitored the participants under driving conditions, in which they drove at a constant speed of 100 km/h, and under non-driving conditions, in which they simply watched the screen (visual task. Changes in hemoglobin concentrations were monitored at 48 channels including the prefrontal cortex, the premotor cortex, the primary motor cortex and the parietal cortex. From orthogonal vectors of changes in deoxyhemoglobin and changes in oxyhemoglobin, we calculated changes in cerebral oxygen exchange, reflecting neural activity, and statistically compared the resulting values from the right and left curve sections.Under driving conditions, there were no sites where cerebral oxygen exchange increased significantly more during right curves than during left curves (p > 0.05, but cerebral oxygen exchange increased significantly more during left curves (p < 0.05 in the right premotor cortex, the right frontal eye field and the bilateral prefrontal cortex. Under non-driving conditions, increases were significantly greater during left curves (p < 0.05 only in the right frontal eye field.Left curve driving was thus found to require more brain activity at multiple sites, suggesting that left curve driving may require more visual attention than right curve driving. The right frontal eye field was activated under both driving and non-driving conditions.

Greater Activity in the Frontal Cortex on Left Curves: A Vector-Based fNIRS Study of Left and Right Curve Driving

Science.gov (United States)

Oka, Noriyuki; Yoshino, Kayoko; Yamamoto, Kouji; Takahashi, Hideki; Li, Shuguang; Sugimachi, Toshiyuki; Nakano, Kimihiko; Suda, Yoshihiro; Kato, Toshinori

2015-01-01

Objectives In the brain, the mechanisms of attention to the left and the right are known to be different. It is possible that brain activity when driving also differs with different horizontal road alignments (left or right curves), but little is known about this. We found driver brain activity to be different when driving on left and right curves, in an experiment using a large-scale driving simulator and functional near-infrared spectroscopy (fNIRS). Research Design and Methods The participants were fifteen healthy adults. We created a course simulating an expressway, comprising straight line driving and gentle left and right curves, and monitored the participants under driving conditions, in which they drove at a constant speed of 100 km/h, and under non-driving conditions, in which they simply watched the screen (visual task). Changes in hemoglobin concentrations were monitored at 48 channels including the prefrontal cortex, the premotor cortex, the primary motor cortex and the parietal cortex. From orthogonal vectors of changes in deoxyhemoglobin and changes in oxyhemoglobin, we calculated changes in cerebral oxygen exchange, reflecting neural activity, and statistically compared the resulting values from the right and left curve sections. Results Under driving conditions, there were no sites where cerebral oxygen exchange increased significantly more during right curves than during left curves (p > 0.05), but cerebral oxygen exchange increased significantly more during left curves (p right premotor cortex, the right frontal eye field and the bilateral prefrontal cortex. Under non-driving conditions, increases were significantly greater during left curves (p right frontal eye field. Conclusions Left curve driving was thus found to require more brain activity at multiple sites, suggesting that left curve driving may require more visual attention than right curve driving. The right frontal eye field was activated under both driving and non-driving conditions

Modelling curves of manufacturing feasibilities and demand

Directory of Open Access Journals (Sweden)

Soloninko K.S.

2017-03-01

Full Text Available The authors research the issue of functional properties of curves of manufacturing feasibilities and demand. Settlement of the problem, and its connection with important scientific and practical tasks. According to its nature, the market economy is unstable and is in constant movement. Economy has an effective instrument for explanation of changes in economic environment; this tool is called the modelling of economic processes. The modelling of economic processes depends first and foremost on the building of economic model which is the base for the formalization of economic process, that is, the building of mathematical model. The effective means for formalization of economic process is the creation of the model of hypothetic or imaginary economy. The building of demand model is significant for the market of goods and services. The problem includes the receiving (as the result of modelling definite functional properties of curves of manufacturing feasibilities and demand according to which one can determine their mathematical model. Another problem lies in obtaining majorant properties of curves of joint demand on the market of goods and services. Analysis of the latest researches and publications. Many domestic and foreign scientists dedicated their studies to the researches and building of the models of curves of manufacturing feasibilities and demand. In spite of considerable work of the scientists, such problems as functional properties of the curves and their practical use in modelling. The purpose of the article is to describe functional properties of curves of manufacturing feasibilities and demand on the market of goods and services on the base of modelling of their building. Scientific novelty and practical value. The theoretical regulations (for functional properties of curves of manufacturing feasibilities and demand received as a result of the present research, that is convexity, give extra practical possibilities in a microeconomic

Reflected Light Curves of Extrasolar Planets

Science.gov (United States)

Green, D.; Matthews, J.; Kuschnig, R.; Seager, S.

The planned launches of ultra-precise photometric satellites such as MOST, COROT and MONS should provide the first opportunity to study the reflected light curves from extrasolar planets. To predict the capabilities of these missions, we have constructed a series of models of such light curves, improving upon the Monte Carlo simulations by Seager et al. (2000). These models include more realistic features such limb darkening of the star and broad band photometry. For specific models, the resulting planet light curves exhibit unique behavior with the variation of radius, inclination and presence or absence of clouds.

Growth curves for twins in Slovenia.

Science.gov (United States)

Bricelj, Katja; Blickstein, Isaac; Bržan-Šimenc, Gabrijela; Janša, Vid; Lučovnik, Miha; Verdenik, Ivan; Trojner-Bregar, Andreja; Tul, Nataša

2017-02-01

Abnormalities of fetal growth are more common in twins. We introduce the growth curves for monitoring fetal growth in twin pregnancies in Slovenia. Slovenian National Perinatal Information System for the period between 2002 and 2010 was used to calculate birth weight percentiles for all live born twins for each week from 22nd to 40th week. The calculated percentiles of birth weight for all live-born twins in Slovenia served as the basis for drawing 'growth' curves. The calculated growth curves for twins will help accurately diagnose small or large twin fetuses for their gestational age in the native central European population.

Laws governing the energy conversion of ionization curves

International Nuclear Information System (INIS)

Gorgoskii, V.I.

1986-01-01

The author attempts to determine if ionization curves are structured or smooth, the cause of the smoothing of the curves, the possibility of the curves having maxima and why, how many maxima are on the ionization curve, and which of these maxima is the fundamental maxima. The study shows that ionization curves without and additional maximum, i.e., with one fundamental maximum, can be obtained for potassium, rubidium, and cesium. This requires reduction of the density of the electrons in the stream and the density of the atoms of the target gas. It is also shown that in order to obtain ionization curves with additional maxima in the cases of neon, argon, and krypton, the measurements must be carried out at high densities of the electrons in the stream and of the atoms of the target gas

An Alternate Light Curve Solution of AR Lacertae

Directory of Open Access Journals (Sweden)

Hong Suh Park

1984-09-01

Full Text Available Photoelectric UBV light curves of AR Lacertae made in one season during 1981-82 are presented. Although the shape of the light curves in the outside eclipses show a strong distortion, the scatter of observations as well as phase coverage are better than those previously available. Fourier coefficients are derived from the V-light curve and observed curve successfully rectified to the Russell model. Light curve solutions are computed and the geometrical and physical parameters of AR Lac are derived as as = 0.812, ag = 0.341, j = 86°3, Ls = 0.372, Lg = 0.628, k = 0.53, Xs = 0.85, Xg = 0.4.

Migration and the Wage-Settings Curve

DEFF Research Database (Denmark)

Brücker, Herbert; Jahn, Elke

Germany on basis of a wage-setting curve. The wage-setting curve relies on the assumption that wages respond to a hange in the unemployment rate, albeit imperfectly. This allows one to derive the wage and employment effects of migration simultaneously in a general equilibrium framework. Using...

Deep-learnt classification of light curves

DEFF Research Database (Denmark)

Mahabal, Ashish; Gieseke, Fabian; Pai, Akshay Sadananda Uppinakudru

2017-01-01

Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and techniques to classify light curves. A common approach is to d...

Symmetry Properties of Potentiometric Titration Curves.

Science.gov (United States)

Macca, Carlo; Bombi, G. Giorgio

1983-01-01

Demonstrates how the symmetry properties of titration curves can be efficiently and rigorously treated by means of a simple method, assisted by the use of logarithmic diagrams. Discusses the symmetry properties of several typical titration curves, comparing the graphical approach and an explicit mathematical treatment. (Author/JM)

Laffer Curves and Home Production

Directory of Open Access Journals (Sweden)

Kotamäki Mauri

2017-06-01

Full Text Available In the earlier related literature, consumption tax rate Laffer curve is found to be strictly increasing (see Trabandt and Uhlig (2011. In this paper, a general equilibrium macro model is augmented by introducing a substitute for private consumption in the form of home production. The introduction of home production brings about an additional margin of adjustment – an increase in consumption tax rate not only decreases labor supply and reduces the consumption tax base but also allows a substitution of market goods with home-produced goods. The main objective of this paper is to show that, after the introduction of home production, the consumption tax Laffer curve exhibits an inverse U-shape. Also the income tax Laffer curves are significantly altered. The result shown in this paper casts doubt on some of the earlier results in the literature.

a new approach of Analysing GRB light curves

International Nuclear Information System (INIS)

Varga, B.; Horvath, I.

2005-01-01

We estimated the T xx quantiles of the cumulative GRB light curves using our recalculated background. The basic information of the light curves was extracted by multivariate statistical methods. The possible classes of the light curves are also briefly discussed

The South Carolina bridge-scour envelope curves

Science.gov (United States)

Benedict, Stephen T.; Feaster, Toby D.; Caldwell, Andral W.

2016-09-30

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a series of three field investigations to evaluate historical, riverine bridge scour in the Piedmont and Coastal Plain regions of South Carolina. These investigations included data collected at 231 riverine bridges, which lead to the development of bridge-scour envelope curves for clear-water and live-bed components of scour. The application and limitations of the South Carolina bridge-scour envelope curves were documented in four reports, each report addressing selected components of bridge scour. The current investigation (2016) synthesizes the findings of these previous reports into a guidance manual providing an integrated procedure for applying the envelope curves. Additionally, the investigation provides limited verification for selected bridge-scour envelope curves by comparing them to field data collected outside of South Carolina from previously published sources. Although the bridge-scour envelope curves have limitations, they are useful supplementary tools for assessing the potential for scour at riverine bridges in South Carolina.

Automorphisms of double coverings of curves

International Nuclear Information System (INIS)

Torres, F.

1994-11-01

We study automorphisms of curves that commute with each other. We prove that the order and the number of fixed points of one of them satisfy certain relations involving those of the other. Then, we specialize our results to the case of double coverings of curves. For instance, if the genus of the curve is at least 4γ + 2 and γ >= 1 (γ = the genus of the covered curve) we prove that the order of an automorphism is bounded above by 2γ + 1 (resp. 4γ + 2) provided it is prime (resp. it has at least five fixed points). We also improve Farkas' bound on the number of fixed points namely 4γ + 4 by showing that it involves the order of the automorphism except in the case of even order when such an improvement is obtained provided the automorphism and the γ-involution has at least one common fixed point. (author). 15 refs

Flow over riblet curved surfaces

Energy Technology Data Exchange (ETDEWEB)

Loureiro, J B R; Freire, A P Silva, E-mail: atila@mecanica.ufrj.br [Mechanical Engineering Program, Federal University of Rio de Janeiro (COPPE/UFRJ), C.P. 68503, 21.941-972, Rio de Janeiro, RJ (Brazil)

2011-12-22

The present work studies the mechanics of turbulent drag reduction over curved surfaces by riblets. The effects of surface modification on flow separation over steep and smooth curved surfaces are investigated. Four types of two-dimensional surfaces are studied based on the morphometric parameters that describe the body of a blue whale. Local measurements of mean velocity and turbulence profiles are obtained through laser Doppler anemometry (LDA) and particle image velocimetry (PIV).

Illusory Paschen curves associated with strongly electronegative gases

DEFF Research Database (Denmark)

McAllister, Iain Wilson

1991-01-01

Using analytical linear regression analysis, it is shown that, for a strongly electronegative gas, the (direct) breakdown voltage curve obtained with a moderately nonuniform field is effectively linear. For a strongly electronegative gas, breakdown voltage measurements made on a moderately...... nonuniform field test gap give rise to an apparently liner curve. The curve can be designated a Paschen curve, but the erroneous nature of this designation becomes apparent from a linear regression analysis of the experimental breakdown data...

Learning in Baja California micro-enterprises

Directory of Open Access Journals (Sweden)

Michelle Texis Flores

2011-01-01

Full Text Available Mexico’s business structure has been characterized by the presence of microenterprises, particularly those averaging two workers, representing 65% of establishments in 2008 and 18% of employment. This makes them important for equity and welfare improvement of their members. This paper analyzes the performance of a group of 227 microenterprises in the state of Baja California, by the use of a practical application of the concept of learning curve arranged to incorporate returns to scale. The results indicate that in 48% of cases there is evidence of learning processes and 58% exhibited increasing returns to scale. This allows evaluating the development potential of these microenterprises and the design and implementation of proactive programs that encourage their learning and consolidation in the market.

IGMtransmission: Transmission curve computation

Science.gov (United States)

Harrison, Christopher M.; Meiksin, Avery; Stock, David

2015-04-01

IGMtransmission is a Java graphical user interface that implements Monte Carlo simulations to compute the corrections to colors of high-redshift galaxies due to intergalactic attenuation based on current models of the Intergalactic Medium. The effects of absorption due to neutral hydrogen are considered, with particular attention to the stochastic effects of Lyman Limit Systems. Attenuation curves are produced, as well as colors for a wide range of filter responses and model galaxy spectra. Photometric filters are included for the Hubble Space Telescope, the Keck telescope, the Mt. Palomar 200-inch, the SUBARU telescope and UKIRT; alternative filter response curves and spectra may be readily uploaded.

Natural frequencies of the frames having curved member

International Nuclear Information System (INIS)

Tekelioglu, M.; Ozyigit, H.A.; Ridvan, H.

2001-01-01

In-plane and out-of-plane vibrations of a frame having a curved member are studied. Although the analysis is carried out on a frame having a straight and a curve beam, it can be applicable for all the frame type structures. Different end conditions are considered for the system. Rotary inertia and extensional effects are included for the curved member. Finite element method is used as analysis tool. Natural frequencies of the curved beams for different end conditions are calculated first, and then the frequencies of the frames are investigated. The transformation from local coordinates to global coordinates for curved beams needs special attention in the analysis. The results are compared with other methods. (author)

The learning curve for laparoscopic colectomy in colorectal cancer at a new regional hospital

Directory of Open Access Journals (Sweden)

Kuei-Yen Tsai

2016-01-01

Conclusion: Laparoscopic colectomy for colorectal cancer in a new regional hospital is feasible and safe. It does not need additional time for learning. Laparoscopic sigmoidectomy can be considered as the initial surgery for a trainee.

Speed choice and steering behavior in curve driving

NARCIS (Netherlands)

Winsum, W. van; Godthelp, J.

1996-01-01

The relation between speed choice and steering performance during curve negotiation was studied in a driving simulator. The hypothesis was that curve radius and steering competence both affect steering error during curve driving, resulting in compensatory speed choice. In this, the control of safety

Influence of pavement condition on horizontal curve safety.

Science.gov (United States)

Buddhavarapu, Prasad; Banerjee, Ambarish; Prozzi, Jorge A

2013-03-01

Crash statistics suggest that horizontal curves are the most vulnerable sites for crash occurrence. These crashes are often severe and many involve at least some level of injury due to the nature of the collisions. Ensuring the desired pavement surface condition is one potentially effective strategy to reduce the occurrence of severe accidents on horizontal curves. This study sought to develop crash injury severity models by integrating crash and pavement surface condition databases. It focuses on developing a causal relationship between pavement condition indices and severity level of crashes occurring on two-lane horizontal curves in Texas. In addition, it examines the suitability of the existing Skid Index for safety maintenance of two-lane curves. Significant correlation is evident between pavement condition and crash injury severity on two-lane undivided horizontal curves in Texas. Probability of a crash becoming fatal is appreciably sensitive to certain pavement indices. Data suggested that road facilities providing a smoother and more comfortable ride are vulnerable to severe crashes on horizontal curves. In addition, the study found that longitudinal skid measurement barely correlates with injury severity of crashes occurring on curved portions. The study recommends exploring the option of incorporating lateral friction measurement into Pavement Management System (PMS) databases specifically at curved road segments. Copyright © 2012 Elsevier Ltd. All rights reserved.

Subjective Estimates of Job Performance after Job Preview: Determinants of Anticipated Learning Curves

Science.gov (United States)

Ackerman, Phillip L.; Shapiro, Stacey; Beier, Margaret E.

2011-01-01

When people choose a particular occupation, they presumably make an implicit judgment that they will perform well on a job at some point in the future, typically after extensive education and/or on-the-job experience. Research on learning and skill acquisition has pointed to a power law of practice, where large gains in performance come early in…

Carbon Lorenz Curves

Energy Technology Data Exchange (ETDEWEB)

Groot, L. [Utrecht University, Utrecht School of Economics, Janskerkhof 12, 3512 BL Utrecht (Netherlands)

2008-11-15

The purpose of this paper is twofold. First, it exhibits that standard tools in the measurement of income inequality, such as the Lorenz curve and the Gini-index, can successfully be applied to the issues of inequality measurement of carbon emissions and the equity of abatement policies across countries. These tools allow policy-makers and the general public to grasp at a single glance the impact of conventional distribution rules such as equal caps or grandfathering, or more sophisticated ones, on the distribution of greenhouse gas emissions. Second, using the Samuelson rule for the optimal provision of a public good, the Pareto-optimal distribution of carbon emissions is compared with the distribution that follows if countries follow Nash-Cournot abatement strategies. It is shown that the Pareto-optimal distribution under the Samuelson rule can be approximated by the equal cap division, represented by the diagonal in the Lorenz curve diagram.

Migration and the Wage Curve:

DEFF Research Database (Denmark)

Brücker, Herbert; Jahn, Elke J.

in a general equilibrium framework. For the empirical analysis we employ the IABS, a two percent sample of the German labor force. We find that the elasticity of the wage curve is particularly high for young workers and workers with a university degree, while it is low for older workers and workers......  Based on a wage curve approach we examine the labor market effects of migration in Germany. The wage curve relies on the assumption that wages respond to a change in the unemployment rate, albeit imperfectly. This allows one to derive the wage and employment effects of migration simultaneously...... with a vocational degree. The wage and employment effects of migration are moderate: a 1 percent increase in the German labor force through immigration increases the aggregate unemployment rate by less than 0.1 percentage points and reduces average wages by less 0.1 percent. While native workers benefit from...

Vertex algebras and algebraic curves

CERN Document Server

Frenkel, Edward

2004-01-01

Vertex algebras are algebraic objects that encapsulate the concept of operator product expansion from two-dimensional conformal field theory. Vertex algebras are fast becoming ubiquitous in many areas of modern mathematics, with applications to representation theory, algebraic geometry, the theory of finite groups, modular functions, topology, integrable systems, and combinatorics. This book is an introduction to the theory of vertex algebras with a particular emphasis on the relationship with the geometry of algebraic curves. The notion of a vertex algebra is introduced in a coordinate-independent way, so that vertex operators become well defined on arbitrary smooth algebraic curves, possibly equipped with additional data, such as a vector bundle. Vertex algebras then appear as the algebraic objects encoding the geometric structure of various moduli spaces associated with algebraic curves. Therefore they may be used to give a geometric interpretation of various questions of representation theory. The book co...

Calibration curves for biological dosimetry