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Artículos de revistas sobre el tema "Progressive data analysis"

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Publicado: 25 de mayo de 2024

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P, Veeramuthu. "Analysis of Progressive Duplicate Data Detection." Journal of Computational Mathematica 3, no. 2 (2019): 41–50. http://dx.doi.org/10.26524/cm53.

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Lee, Kyeong-Jun, Jae-Ik Lee, and Chan-Keun Park. "Analysis of generalized progressive hybrid censored competing risks data." Journal of the Korean Society of Marine Engineering 40, no. 2 (2016): 131–37. http://dx.doi.org/10.5916/jkosme.2016.40.2.131.

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Rinzivillo, Salvatore, Dino Pedreschi, Mirco Nanni, Fosca Giannotti, Natalia Andrienko, and Gennady Andrienko. "Visually driven analysis of movement data by progressive clustering." Information Visualization 7, no. 3-4 (2008): 225–39. http://dx.doi.org/10.1057/palgrave.ivs.9500183.

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The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities. Trajectories are complex spatio-temporal constructs characterized by diverse non-trivial properties. To assess the degree of (dis)similarity between trajectories, specific methods (distance functions) are required. A single distance function accounting for all properties of trajectories, (1) is difficult to build, (2) would require much time to compute, and (3) might be difficult to understand and to use. We suggest the procedure of progressive clustering where a simple distance function with a clear meaning is applied on each step, which leads to easily interpretable outcomes. Successive application of several different functions enables sophisticated analyses through gradual refinement of earlier obtained results. Besides the advantages from the sense-making perspective, progressive clustering enables a rational work organization where time-consuming computations are applied to relatively small potentially interesting subsets obtained by means of ‘cheap’ distance functions producing quick results. We introduce the concept of progressive clustering by an example of analyzing a large real data set. We also review the existing clustering methods, describe the method OPTICS suitable for progressive clustering of trajectories, and briefly present several distance functions for trajectories.

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Wang, Tao, Lianbin Deng, Yuhong Li, and Hao Peng. "Progressive TIN Densification with Connection Analysis for Urban Lidar Data." Photogrammetric Engineering & Remote Sensing 87, no. 3 (2021): 205–13. http://dx.doi.org/10.14358/pers.87.3.207.

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Urban lidar data are advantageous for capturing the terrain surface of built-up areas, which can be directly used to provide digital surface models. Cloud points are classified into ground points to obtain digital terrain models. This study proposes a method to improve the progressive triangulated irregular network (TIN ) densification method using a TIN connection analysis algorithm, namely, connection analysis via slope analysis. The proposed method comprises five steps: selection of seed points, connection and slope analysis, increasing the seed points, construction of the TIN model of the seed points, and an iterative construction of the final TIN. Seven data sets from the International Society for Photogrammetry and Remote Sensing Working Group are used to test whether the proposed method can preserve discontinuities of landscapes and reduce omission and total errors by an average of 9% and 5%, respectively; achieving such results can reduce the amount of workload required for result modification during posttreatment, thus decreasing costs.

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Hassan, Amal S., Rana M. Mousa, and Mahmoud H. Abu-Moussa. "Analysis of Progressive Type-II Competing Risks Data, with Applications." Lobachevskii Journal of Mathematics 43, no. 9 (2022): 2479–92. http://dx.doi.org/10.1134/s1995080222120149.

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Azarang, Leyla, and Manuel,Oviedo,de,la Fuente. "idmTPreg: Regression Model for Progressive Illness Death Data." R Journal 10, no. 2 (2019): 317. http://dx.doi.org/10.32614/rj-2018-081.

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Koch, Marcus W., Jop Mostert, Bernard Uitdehaag, and Gary Cutter. "Clinical outcome measures in SPMS trials: An analysis of the IMPACT and ASCEND original trial data sets." Multiple Sclerosis Journal 26, no. 12 (2019): 1540–49. http://dx.doi.org/10.1177/1352458519876701.

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Background: Still too little is known about the natural history of clinical outcome measures beyond the Expanded Disability Status Scale (EDSS), such as the timed 25-foot walk (T25FW) and nine-hole peg test (9HPT) in secondary progressive multiple sclerosis (SPMS). Objective: To describe progression on the EDSS, T25FW, 9HPT, and their combinations. To investigate the association of the baseline characteristics age, sex, EDSS, T25FW, gadolinium-enhancing lesions, and relapse activity with EDSS and T25FW progression. Methods: Using original trial data from the placebo arms of the IMPACT and ASCEND randomized controlled trials, we describe disability progression (with and without 3- or 6-month confirmation). We investigated the association of selected baseline characteristics with EDSS and T25FW progression over 2 years using binary logistic regression. Results: T25FW was the single outcome measure with the largest proportion of patients progressing, followed by EDSS and 9HPT. EDSS and T25FW at baseline were associated with EDSS and T25FW progression in both data sets. Age and relapse activity were only mild and inconsistent predictors, while sex and gadolinium enhancement at baseline did not predict disability progression in either data set. Conclusion: Our analyses inform the selection of primary outcome measures as well as inclusion criteria for clinical trials in SPMS.

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Turkay, Cagatay, Erdem Kaya, Selim Balcisoy, and Helwig Hauser. "Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis." IEEE Transactions on Visualization and Computer Graphics 23, no. 1 (2017): 131–40. http://dx.doi.org/10.1109/tvcg.2016.2598470.

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Shilpa, Author, and Sunita Parashar. "Performance Analysis of Apriori Algorithm with Progressive Approach for Mining Data." International Journal of Computer Applications 31, no. 1 (2011): 13–18. http://dx.doi.org/10.5120/3788-5216.

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Al-Hossain, Abdullah Y. "Predictive Inference from the Exponentiated Weibull Model Given Adaptive Progressive Censored Data." Applied Mathematics & Information Sciences 10, no. 3 (2016): 1177–84. http://dx.doi.org/10.18576/amis/100336.

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Elshahhat, Ahmed, and Mazen Nassar. "Bayesian survival analysis for adaptive Type-II progressive hybrid censored Hjorth data." Computational Statistics 36, no. 3 (2021): 1965–90. http://dx.doi.org/10.1007/s00180-021-01065-8.

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Mohammed, Heba S., Mazen Nassar, Refah Alotaibi, and Ahmed Elshahhat. "Analysis of Adaptive Progressive Type-II Hybrid Censored Dagum Data with Applications." Symmetry 14, no. 10 (2022): 2146. http://dx.doi.org/10.3390/sym14102146.

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In life testing and reliability studies, obtaining whole data always takes a long time and lots of monetary and human resources. In this case, the experimenters prefer to gather data using censoring schemes that make a balance between the length of the test, the desired sample size, and the cost. Lately, an adaptive progressive type-II hybrid censoring scheme is suggested to enhance the efficiency of the statistical inference. By utilizing this scheme, this paper seeks to investigate classical and Bayesian estimations of the Dagum distribution. The maximum likelihood and Bayesian estimation methods are considered to estimate the distribution parameters and some reliability indices. The Bayesian estimation is developed under the assumption of independent gamma priors and by employing symmetric and asymmetric loss functions. Due to the tough form of the joint posterior distribution, the Markov chain Monte Carlo technique is implemented to gather samples from the full conditional distributions and in turn obtain the Bayes estimates. The approximate confidence intervals and the highest posterior density credible intervals are also obtained. The effectiveness of the various suggested methods is compared through a simulated study. The optimal progressive censoring plans are also shown, and number of optimality criteria are explored. To demonstrate the applicability of the suggested point and interval estimators, two real data sets are also examined. The outcomes of the simulation study and data analysis demonstrated that the proposed scheme is adaptable and very helpful in ending the experiment when the experimenter’s primary concern is the number of failures.

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Helu, Amal, and Hani Samawi. "Statistical Analysis Based on Adaptive Progressive Hybrid Censored Data From Lomax Distribution." Statistics, Optimization & Information Computing 9, no. 4 (2021): 789–808. http://dx.doi.org/10.19139/soic-2310-5070-1330.

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In this article, we consider statistical inferences about the unknown parameters of the Lomax distribution basedon the Adaptive Type-II Progressive Hybrid censoring scheme, this scheme can save both the total test time and the cost induced by the failure of the units and increases the efficiency of statistical analysis. The estimation of the parameters is derived using the maximum likelihood (MLE) and the Bayesian procedures. The Bayesian estimators are obtained based on the symmetric and asymmetric loss functions. There are no explicit forms for the Bayesian estimators, therefore, we propose Lindley’s approximation method to compute the Bayesian estimators. A comparison between these estimators is provided by using extensive simulation. A real-life data example is provided to illustrate our proposed estimators.

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Staab, Jennifer M., Thomas M. O'Connell, and Shawn M. Gomez. "Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)." BMC Bioinformatics 11, no. 1 (2010): 123. http://dx.doi.org/10.1186/1471-2105-11-123.

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Zhao, Hanqing, Huijun Zhang, Yan Liu, Yongzhen Zhang, and Xiaolong (Luke) Zhang. "Pattern discovery: A progressive visual analytic design to support categorical data analysis." Journal of Visual Languages & Computing 43 (December 2017): 42–49. http://dx.doi.org/10.1016/j.jvlc.2017.05.004.

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Noori Asl, M., R. Arabi Belaghi, and H. Bevrani. "On Burr XII Distribution Analysis Under Progressive Type-II Hybrid Censored Data." Methodology and Computing in Applied Probability 19, no. 2 (2016): 665–83. http://dx.doi.org/10.1007/s11009-016-9514-7.

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Alotaibi, Refah, Ehab M. Almetwally, and Hoda Rezk. "Reliability Analysis of Kavya Manoharan Kumaraswamy Distribution under Generalized Progressive Hybrid Data." Symmetry 15, no. 9 (2023): 1671. http://dx.doi.org/10.3390/sym15091671.

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Generalized progressive hybrid censoring approaches have been developed to reduce test time and cost. This paper investigates the difficulties associated with estimating the unobserved model parameters and the reliability time functions of the Kavya Manoharan Kumaraswamy (KMKu) distribution based on generalized type-II progressive hybrid censoring using classical and Bayesian estimation techniques. The frequentist estimators’ normal approximations are also used to construct the appropriate estimated confidence intervals for the unknown parameter model. Under symmetrical squared error loss, independent gamma conjugate priors are used to produce the Bayesian estimators. The Bayesian estimators and associated highest posterior density intervals cannot be derived analytically since the joint likelihood function is provided in a complicated form. However, they may be evaluated using Monte Carlo Markov chain (MCMC) techniques. Out of all the censoring choices, the best one is selected using four optimality criteria.

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Elshahhat, Ahmed, Vikas Kumar Sharma, and Heba S. Mohammed. "Statistical analysis of progressively first-failure-censored data via beta-binomial removals." AIMS Mathematics 8, no. 9 (2023): 22419–46. http://dx.doi.org/10.3934/math.20231144.

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<abstract><p>Progressive first-failure censoring has been widely-used in practice when the experimenter desires to remove some groups of test units before the first-failure is observed in all groups. Practically, some test groups may haphazardly quit the experiment at each progressive stage, which cannot be determined in advance. As a result, in this article, we propose a progressively first-failure censored sampling with random removals, which allows the removal of the surviving group(s) during the execution of the life test with uncertain probability, called the beta-binomial probability law. Generalized extreme value lifetime model has been widely-used to analyze a variety of extreme value data, including flood flows, wind speeds, radioactive emissions, and others. So, when the sample observations are gathered using the suggested censoring plan, the Bayes and maximum likelihood approaches are used to estimate the generalized extreme value distribution parameters. Furthermore, Bayes estimates are produced under balanced symmetric and asymmetric loss functions. A hybrid Gibbs within the Metropolis-Hastings method is suggested to gather samples from the joint posterior distribution. The highest posterior density intervals are also provided. To further understand how the suggested inferential approaches actually work in the long run, extensive Monte Carlo simulation experiments are carried out. Two applications of real-world datasets from clinical trials are examined to show the applicability and feasibility of the suggested methodology. The numerical results showed that the proposed sampling mechanism is more flexible to operate a classical (or Bayesian) inferential approach to estimate any lifetime parameter.</p></abstract>

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Abd El-Raheem, Abd El-Raheem M., Mona Hosny, and Mahmoud H. Abu-Moussa. "On Progressive Censored Competing Risks Data: Real Data Application and Simulation Study." Mathematics 9, no. 15 (2021): 1805. http://dx.doi.org/10.3390/math9151805.

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Competing risks are frequently overlooked, and the event of interest is analyzed with conventional statistical techniques. In this article, we consider the analysis of bi-causes of failure in the context of competing risk models using the extension of the exponential distribution under progressive Type-II censoring. Maximum likelihood estimates for the unknown parameters via the expectation-maximization algorithm are obtained. Moreover, the Bayes estimates of the unknown parameters are approximated using Tierney-Kadane and MCMC techniques. Interval estimates using Bayesian and classical techniques are also considered. Two real data sets are investigated to illustrate the different estimation methods, and to compare the suggested model with Weibull distribution. Furthermore, the estimation methods are compared through a comprehensive simulation study.

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DE WIT, ASTRID, PETER PETRÉ, and FRANK BRISARD. "Standing out with the progressive." Journal of Linguistics 56, no. 3 (2020): 479–514. http://dx.doi.org/10.1017/s0022226719000501.

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In this paper we demonstrate on the basis of diachronic and synchronic data from a variety of languages that progressives are particularly liable to be used for the expression of extravagance. We define extravagant language use as a signaling mechanism that consists in the exploitation of an unconventional construction in a given context as a way for speakers to indicate that there is something non-canonical about the situation that they are reporting. Novel constructions naturally lend themselves to such extravagant exploitation, since they are by definition to a certain extent unconventional. This is why, as we will demonstrate, the English, Dutch and French progressives were notably often recruited in extravagant contexts at the onset of their development. However, our synchronic data reveal that Present-day English, Dutch and French progressives continue to be used for extravagant purposes, which suggests that there is something inherent about progressive aspect that makes it liable to such expressive usage. This is confirmed by data from other, typologically diverse languages. We offer a cognitive-semantic analysis in terms of epistemic contingency in order to account for this intrinsic association of progressive aspect and extravagance across languages. Our analysis thus reveals that extravagance is not a transient property of emerging progressives, but that, instead, the semantics of these constructions makes them particularly liable to be recruited for extravagant purposes. It also demonstrates that in order to analyze the range of uses of progressive constructions in a unified fashion, we need to look beyond the temporal import of these constructions.

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Ricks, Trenton M., Evan J. Pineda, Brett A. Bednarcyk, et al. "Multiscale Progressive Failure Analysis of 3D Woven Composites." Polymers 14, no. 20 (2022): 4340. http://dx.doi.org/10.3390/polym14204340.

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Application of three-dimensional (3D) woven composites is growing as an alternative to the use of ply-based composite materials. However, the design, analysis, modeling, and optimization of these materials is more challenging due to their complex and inherently multiscale geometries. Herein, a multiscale modeling procedure, based on efficient, semi-analytical micromechanical theories rather than the traditional finite element approach, is presented and applied to a 3D woven carbon–epoxy composite. A crack-band progressive damage model was employed for the matrix constituent to capture the globally observed nonlinear response. Realistic microstructural dimensions and tow-fiber volume fractions were determined from detailed X-ray computed tomography (CT) and scanning electron microscopy data. Pre-existing binder-tow disbonds and weft-tow waviness, observed in X-ray CT scans of the composite, were also included in the model. The results were compared with experimental data for the in-plane tensile and shear behavior of the composite. The tensile predictions exhibited good correlations with the test data. While the model was able to capture the less brittle nature of the in-plane shear response, quantitative measures were underpredicted to some degree.

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Ralovich, K., J. Zhang, S. K. Zhou, D. Comaniciu, and M. Sofka. "Progressive Data Transmission for Anatomical Landmark Detection in a Cloud." Methods of Information in Medicine 51, no. 03 (2012): 268–78. http://dx.doi.org/10.3414/me11-02-0017.

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SummaryBackground: In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis.Objectives: This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server.Methods: The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined.Results: Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data.Conclusions: The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.

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Ahmed, Naveed, JeeWoong Park, Cristian Arteaga, and Haroon Stephen. "Investigation of Progressive Learning within a Statics Course: An Analysis of Performance Retention, Critical Topics, and Active Participation." Education Sciences 13, no. 6 (2023): 576. http://dx.doi.org/10.3390/educsci13060576.

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Previous research has demonstrated a link between prior knowledge and student success in engineering courses. However, while course-to-course relations exist, researchers have paid insufficient attention to internal course performance development. This study aims to address this gap—designed to quantify and thus extract meaningful insights—by examining a fundamental engineering course, Statics, from three perspectives: (1) progressive learning reflected in performance retention throughout the course; (2) critical topics and their influence on students’ performance progression; and (3) student active participation as a surrogate measure of progressive learning. By analyzing data collected from 222 students over five semesters, this study draws insights on student in-course progressive learning. The results show that early learning had significant implications in building a foundation in progressive learning throughout the semester. Additionally, insufficient knowledge on certain topics can hinder student learning progression more than others, which eventually leads to course failure. Finally, student participation is a pathway to enhance learning and achieve excellent course performance. The presented analysis approach provides educators with a mechanism for diagnosing and devising strategies to address conceptual lapses for STEM (science, technology, engineering, and mathematics) courses, especially where progressive learning is essential.

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Horáková, Dana, Aaron Boster, Antonio Bertolotto, et al. "Proportion of alemtuzumab-treated patients converting from relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis over 6 years." Multiple Sclerosis Journal - Experimental, Translational and Clinical 6, no. 4 (2020): 205521732097213. http://dx.doi.org/10.1177/2055217320972137.

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Background Few data exist concerning conversion to secondary progressive MS in patients treated with disease-modifying therapies. Objective Determine the proportion of alemtuzumab-treated patients converting from relapsing-remitting to secondary progressive MS during the CARE-MS core and extension studies. Methods Patients ( N = 811) were analyzed post hoc for secondary progressive MS conversion. Optimal conversion definition: Expanded Disability Status Scale (EDSS) score ≥4, pyramidal functional system score ≥2, and confirmed progression over ≥3 months including confirmation within the functional system leading to progression, independent of relapse. Results Over 6.2 years median follow-up, 20 alemtuzumab-treated patients converted (Kaplan-Meier estimate, 2.7%; 95% confidence interval, 1.8%–4.2%). Sensitivity analysis accounting for dropouts showed similar results (3%), as did analyses using alternative definitions with different EDSS thresholds and/or confirmation periods, and analysis of core study subcutaneous interferon beta-1a-treated patients who received alemtuzumab in the extension. Patients converting to secondary progressive MS were older, and had higher EDSS scores and greater brain lesion volumes at baseline, but did not need additional alemtuzumab or other therapies. Conclusions The 6-year conversion rate to secondary progressive MS was low for alemtuzumab-treated patients, supporting further study of the role alemtuzumab may play in reducing risk of secondary progression. ClinicalTrials.gov identifiers: NCT00530348, NCT00548405, NCT00930553.

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Zhu, J., Z. Zhang, X. Hu, and Z. Li. "ANALYSIS AND APPLICATION OF LIDAR WAVEFORM DATA USING A PROGRESSIVE WAVEFORM DECOMPOSITION METHOD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W12 (September 3, 2012): 31–36. http://dx.doi.org/10.5194/isprsarchives-xxxviii-5-w12-31-2011.

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Meng, Yang, Grant McCarthy, Anthony Berthon, and Jerome Dinet. "VP133 Patient-Reported Health State Utilities In Neuroendocrine Tumours." International Journal of Technology Assessment in Health Care 33, S1 (2017): 210. http://dx.doi.org/10.1017/s0266462317003828.

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INTRODUCTION:Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are rare cancers most often found in the gastrointestinal system or the pancreas. However, patient-reported health state utilities based on clinical trials have not been previously reported in this disease area.METHODS:The CLARINET study collected the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 data from patients in both stable and progressive disease states, although data for the latter were only available during the early stage of progression due to trial design. Using published algorithms, data were mapped to EQ-5D utility values. Random-effects generalized least squares models were used to investigate the impacts of progression status, tumour site and other patient characteristics on mapped utility values.RESULTS:In total, 1,053 observations from 204 patients were mapped to EuroQol (EQ-5D) utilities using the McKenzie mapping algorithm. The final random-effects model included age, gender, baseline utility and progression status as covariates; it was not feasible to investigate time-to-death utility due to a limited number of death in the CLARINET study. Tumour location (midgut versus pancreas) does not seem to affect utility. However, the difference in utilities based on progression status is statistically significant (p<.05) in the base case analysis, and the estimated utilities for stable and progressive disease are .776 and .726, respectively. Furthermore, scenario analyses showed that utility for progressive disease is numerically lower than for stable disease, but this may not be statistically significant in some scenarios.CONCLUSIONS:Patients with GEP-NETs experience worse utility values in the progressive disease state compared to the stable disease state, based on patient-reported health-related quality of life (HRQL) data from the CLARINET study. The decline of utility in the progressive disease state may be underestimated because progressive HRQL data were only collected shortly after the progression event in the trial. The estimated trial-based utilities can be used in future economic evaluations for GEP-NET treatments and to provide more insights to physicians on patient-reported quality of life outcomes in GEP-NETs.

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YEHOSHYNA, H. A., S. M. VORONOY, O. I. POLIKAROVSKYKH, and R. O. GOKHMAN. "INTERFACES SIMILARITY ANALYSIS FOR PROGRESSIVE WEB APPS AND WEB-APPLICATIONS BASED ON DISTILBERT TRANSFORMER." Scientific papers of Donetsk National Technical University. Series: Informatics, Cybernetics and Computer Science 2 - №1, no. 35-36 (2023): 51–60. http://dx.doi.org/10.31474/1996-1588-2023-1-36-51-60.

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An approach to automated testing of components of Progressive Web Applications interfaces by determining their relevance to elements of the corresponding web versions of applications is proposed. An analysis of modern trends and existing categories in the field of Web Mining was carried out. It is shown that the predominant trend in the analysis of the interface structures of modern web applications is the use of Deep Learning technologies. Features and functioning of the latest Transformers neural network architecture are considered. The choice of the Transformers type model to determine the correspondence between the site structure and the PWA application interface is justified. It is shown that in the comparison of fragments of the interfaces of the web service and the PWA application, some elements have more impact (weight) than others. It is proposed to use the mechanism of multidimensional "self-attention" to take into account this feature of the content. It is shown that the analysis of correspondence of interfaces is a task of binary classification. Features of transformers of the Bidirectional Encoder Representations (BERT) type are viewed. Pretrained BERT model can be configured with only one additional output layer to create modern and powerful models for a wide range of problems. It is proposed to use transfer learning, namely the DistilBERT model and its fine tuning using the DistilBertForSequenceClassification class. For the basic architecture of DistillBert (embedding and encoder layers), the weights of the English-language model "distilbert-base-uncased-finetuned-sst-2-english" were used. The model was optimized using a modification of the Adam stochastic gradient descent method. It is also suggested to use a low learning rate to avoid "forgetting". The features of data preprocessing using DistilBertTokenizer are shown. The architecture of the model was designed and its research was done based on data set of CSS properties, which provide styling and layout of interface elements.

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Procopio, Marianne, Carlos Scheidegger, Eugene Wu, and Remco Chang. "Selective Wander Join: Fast Progressive Visualizations for Data Joins." Informatics 6, no. 1 (2019): 14. http://dx.doi.org/10.3390/informatics6010014.

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Progressive visualization offers a great deal of promise for big data visualization; however, current progressive visualization systems do not allow for continuous interaction. What if users want to see more confident results on a subset of the visualization? This can happen when users are in exploratory analysis mode but want to ask some directed questions of the data as well. In a progressive visualization system, the online aggregation algorithm determines the database sampling rate and resulting convergence rate, not the user. In this paper, we extend a recent method in online aggregation, called Wander Join, that is optimized for queries that join tables, one of the most computationally expensive operations. This extension leverages importance sampling to enable user-driven sampling when data joins are in the query. We applied user interaction techniques that allow the user to view and adjust the convergence rate, providing more transparency and control over the online aggregation process. By leveraging importance sampling, our extension of Wander Join also allows for stratified sampling of groups when there is data distribution skew. We also improve the convergence rate of filtering queries, but with additional overhead costs not needed in the original Wander Join algorithm.

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Puente, I., R. Lindenbergh, A. Van Natijne, R. Esposito, and R. Schipper. "MONITORING OF PROGRESSIVE DAMAGE IN BUILDINGS USING LASER SCAN DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 923–29. http://dx.doi.org/10.5194/isprs-archives-xlii-2-923-2018.

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Vulnerability of buildings to natural and man-induced hazards has become a main concern for our society. Ensuring their serviceability, safety and sustainability is of vital importance and the main reason for setting up monitoring systems to detect damages at an early stage. In this work, a method is presented for detecting changes from laser scan data, where no registration between different epochs is needed. To show the potential of the method, a case study of a laboratory test carried out at the Stevin laboratory of Delft University of Technology was selected. The case study was a quasi-static cyclic pushover test on a two-story high unreinforced masonry structure designed to simulate damage evolution caused by cyclic loading. During the various phases, we analysed the behaviour of the masonry walls by monitoring the deformation of each masonry unit. First a plane is fitted to the selected wall point cloud, consisting of one single terrestrial laser scan, using Principal Component Analysis (PCA). Second, the segmentation of individual elements is performed. Then deformations with respect to this plane model, for each epoch and specific element, are determined by computing their corresponding rotation and cloud-to-plane distances. The validation of the changes detected within this approach is done by comparison with traditional deformation analysis based on co-registered TLS point clouds between two or more epochs of building measurements. Initial results show that the sketched methodology is indeed able to detect changes at the mm level while avoiding 3D point cloud registration, which is a main issue in computer vision and remote sensing.

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van Riel, Natal A. W., Christian A. Tiemann, Joep Vanlier, and Peter A. J. Hilbers. "Applications of analysis of dynamic adaptations in parameter trajectories." Interface Focus 3, no. 2 (2013): 20120084. http://dx.doi.org/10.1098/rsfs.2012.0084.

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Metabolic profiling in combination with pathway-based analyses and computational modelling are becoming increasingly important in clinical and preclinical research. Modelling multi-factorial, progressive diseases requires the integration of molecular data at the metabolome, proteome and transcriptome levels. Also the dynamic interaction of organs and tissues needs to be considered. The processes involved cover time scales that are several orders of magnitude different. We report applications of a computational approach to bridge the scales and different levels of biological detail. Analysis of dynamic adaptations in parameter trajectories (ADAPTs) aims to investigate phenotype transitions during disease development and after a therapeutic intervention. ADAPT is based on a time-dependent evolution of model parameters to describe the dynamics of metabolic adaptations. The progression of metabolic adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages. To get a better understanding of the concept, the ADAPT approach is illustrated in a theoretical study. Its application in research on progressive changes in lipoprotein metabolism is also discussed.

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McGlynn, Mary Claire, Mohammad H. Abu-Arja, Sumanth Nagabushan, et al. "RARE-08. MULTI-INSTITUTIONAL ANALYSIS OF PEDIATRIC RELAPSED/REFRACTORY CENTRAL NERVOUS SYSTEM GERMINOMA." Neuro-Oncology 25, Supplement_1 (2023): i35. http://dx.doi.org/10.1093/neuonc/noad073.137.

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Abstract BACKGROUND Relapsed central nervous system (CNS) germinomas are rare with no universal agreement regarding management. We explore prognostic factors that may impact the treatment of patients with relapsed CNS germinoma. METHODS An international multi-institutional retrospective study of relapsed/progressive CNS germinomas was conducted. Data was summarized using descriptive statistics. Overall survival (OS) was evaluated using Kaplan-Meier and Fischer’s exact test to estimate odds ratios (OR) and 95% confidence intervals (CI). RESULTS Analysis included 21 patients (Male 71.4%) with relapsed/progressive germinomas from 7 sites. Median age at diagnosis was 15 years (interquartile range (IQR): 9.9-19) with 5% presenting with metastatic disease. Twelve patients (57.1%) achieved complete remission (CR) after initial therapy. Nineteen children (90.5%) suffered relapse. One (4.8%) suffered progression. The median time from diagnosis to relapse/progression was 21 months (range: 10-56 months) with 90.5% occurring within 24 months. 19 (90.5%) underwent chemotherapy, 9 (42.9%) bone marrow ablative therapy (HDCx), and 13 (61.9%) radiotherapy. At last follow-up, 88.9% of HDCx and 92.3% of radiotherapy recipients were alive. Of patients receiving radiation, 45% received whole ventricular irradiation, 25% craniospinal irradiation, and 5% focal irradiation (remainder unreported). Eleven children (52.4%) achieved CR after relapse/progression therapy and 16 (76.2%) were alive at last follow-up. Median time to last follow-up was 39 months (IQR: 18.43–89.50). Re-irradiation at relapse (OR=16, 95% CI: 1.27-200.9) and achieving complete response (CR) at relapse/progression (OR=4, 95% CI: 1.04-1.78) were associated with improved OS. CR after initial therapy (OR=0.857, 95%CI: 0.11-6.62) and HDCx at relapse/progression (OR=4, 95%CI: 0.36-44.13) were not associated with improved OS. CONCLUSIONS Relapsed CNS germinomas are radiosensitive and salvageable by re-irradiation at relapse. This ongoing multi-institutional study will contribute to existing knowledge about relapsed/progressive CNS germinomas and inform prospective clinical trials to improve outcomes for children with relapsed/progressive disease.

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Jung, Jaeyong, Dong Sik Kim, Beom Jin Chung, and Young Mo Chung. "Analysis on the Residential Progressive and Time-of-use Rates based on AMI Data." Journal of the Institute of Electronics and Information Engineers 58, no. 9 (2021): 66–77. http://dx.doi.org/10.5573/ieie.2021.58.9.66.

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Nassar, Mazen Mohammed, and Samir Kamel Ashour. "Analysis of Exponential Distribution Under Adaptive Type-I Progressive Hybrid Censored Competing Risks Data." Pakistan Journal of Statistics and Operation Research 10, no. 2 (2014): 229. http://dx.doi.org/10.18187/pjsor.v10i2.705.

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Seo, Jung-In, Suk-Bok Kang, and Ho-Yong Kim. "New approach for analysis of progressive Type-II censored data from the Pareto distribution." Communications for Statistical Applications and Methods 25, no. 5 (2018): 569–75. http://dx.doi.org/10.29220/csam.2018.25.5.569.

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Liu, Dongyu, Panpan Xu, and Liu Ren. "TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (2019): 1–11. http://dx.doi.org/10.1109/tvcg.2018.2865018.

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A. Modhesh, A. "Analysis of Progressive First-Failure-Censoring for Non-normal Model Using Competing Risks Data." American Journal of Theoretical and Applied Statistics 4, no. 6 (2015): 610. http://dx.doi.org/10.11648/j.ajtas.20150406.33.

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Aminat, Suleman-Alabi, Fauzah Abd Ghani, Nor Fadhlina Zakaria, Malina Osman, and Rafidah Hod. "Immunoglobulin A Nephropathy: A 10-year Analysis in a Single Malaysian Centre." BMSC 19, s12 (2023): 29–37. http://dx.doi.org/10.47836/mjmhs.19.s12.5.

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Introduction: Immunoglobulin A nephropathy (IgAN), also referred to as Berger’s disease, is the leading primary glomerular disease cause of end-stage kidney disease (ESKD). Its prevalence, presentation, and progression have been shown to vary between different regions and ethnicities. This study aims to explore the presentation, predictors of disease progression, and outcome in a cohort of Malaysian patients with IgAN. Methods: This study evaluated retrospective data from 82 patients with renal biopsy-proven IgAN. The patients were classified into two categories based on their estimated glomerular filtration rate (eGFR) at the last follow-up: those with progressive disease (50% reduction in eGFR from the time of biopsy and/or eGFR <15 ml/min/1.73 m2) and those with non-progressive disease. Results: The majority of patients (75.6%) were female and, 47.6% were less than 30 years old at the time of the renal biopsy. The most common clinical presentation was proteinuria (86.4%). At the end of a median follow-up of 2.7 (IQR 1.2-5.1) years, 29.3% of patients reached the combined renal outcome. Males were more likely than females to have progressive disease (OR = 2.89). The survival rates without ESKD at five and ten years are 82% and 78%, respectively. Multivariate cox regression analysis showed MAP (HR =1.05 95% CI 1.01-1.10), UPCI (HR=13.67 95%CI 1.06-175.88), and MESTC score >3 (HR=3.95 95%CI 1.09-14.23) as predictors of the combined renal outcome. Conclusion: IgAN is not a benign disease, with a significant progression to ESKD in this cohort. MAP, UPCI, and MESTC >3 are predictors of disease progression.

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Zuo, Xuanjia, Liang Wang, Huizhong Lin, Sanku Dey, and Li Yan. "Estimation for Weibull Parameters with Generalized Progressive Hybrid Censored Data." Journal of Mathematics 2021 (December 3, 2021): 1–13. http://dx.doi.org/10.1155/2021/5561191.

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In this paper, the interest is in estimating the Weibull products when the available data is obtained via generalized progressive hybrid censoring. The testing scheme conducts products of interest under a more flexible way and allows collecting failure data in efficient and adaptable experimental scenarios than traditional lifetime testing. When the latent lifetime of products follows Weibull distribution, classical and Bayesian inferences are considered for unknown parameters. The existence and uniqueness of maximum likelihood estimates are established, and approximate confidence intervals are also constructed via asymptotic theory. Bayes point estimates as well as the credible intervals of the parameters are obtained, and correspondingly, Monte Carlo sampling technique is also provided for complex posterior computation. Extensive numerical analysis is carried out, and the results show that the generalized progressive hybrid censoring is an adaptive procedure in practical lifetime experiment, both proposed classical and Bayesian inferential approaches perform satisfactorily, and the Bayesian results are superior to conventional likelihood estimates.

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Madan Kumar, K. M. V., and B. Srinivasa Rao. "Mining Frequent Utility Sequential Patterns in Progressive Databases by U-Pisa." Journal of Computational and Theoretical Nanoscience 17, no. 4 (2020): 1786–95. http://dx.doi.org/10.1166/jctn.2020.8442.

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Sequential pattern mining is one of the most important aspects of data mining world and has a significant role in many applications like market analysis, biomedical analysis, weather forecasting etc. In the category of mining sequential patterns the usage of progressive database as an input database is relatively new and has a wide impact in decision-making system. In progressive sequential pattern mining, we discover the frequent sequences progressively with the help of period of Interest. As the traditional approaches of frequency based framework are not much more informative for decision making, in recent effort utility framework has been incorporated instead of frequency. This addressed many typical business concerns such as profit value associated with each pattern. In this paper, we applied the concept of frequent utility over the progressive database and discovered the sequential pattern efficiently. To do so we proposed an algorithm called U-Pisa which works progressively with the help of a quantitative progressive database. We conducted sub-stantial experiments on the proposed algorithm and proved that this process performs well.

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Kuter, Semih, Gerhard-Wilhelm Weber, and Zuhal Akyürek. "A progressive approach for processing satellite data by operational research." Operational Research 17, no. 2 (2016): 371–93. http://dx.doi.org/10.1007/s12351-016-0229-x.

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Bakoban, R. A., and G. A. Abd-Elmougod. "MCMC in Analysis of Progressively First Failure Censored Competing Risks Data for Gompertz Model." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 6662–70. http://dx.doi.org/10.1166/jctn.2016.5612.

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In medical studies or in reliability analysis, it is quite common that the failure of any individual or any item may be attributable to more than one cause. So in this paper, we consider the competing risks model with very general censoring scheme, namely progressive first-failure censored scheme under the Gompertz life time distribution. The results in each of first-failure censoring, progressive Type II censoring, Type II censoring and complete sample are a special cases. We provide different methods for the analysis of the model under the assumption of independent causes of failure and Gompertz distribution lifetimes. The maximum likelihood estimators (MLE’s) of the different parameters as well as approximate confidence intervals are presented. Bayesian estimation using MCMC method under the joint prior density as a product of a conditional gamma density and inverted gamma density for unknown Gompertz parameters are presented. The analysis of a real data set to assess the performance of all these estimators, confidence intervals are developed using asymptotic distributions and Bayesian credible intervals for the parameters. The different methods are compared through a simulation study.

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Liu, Yifeng, Wei Zhang, and Wenhao Du. "Progressive System: A Deep-Learning Framework for Real-Time Data in Industrial Production." Processes 8, no. 6 (2020): 649. http://dx.doi.org/10.3390/pr8060649.

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Deep learning based on a large number of high-quality data plays an important role in many industries. However, deep learning is hard to directly embed in the real-time system, because the data accumulation of the system depends on real-time acquisitions. However, the analysis tasks of such systems need to be carried out in real time, which makes it impossible to complete the analysis tasks by accumulating data for a long time. In order to solve the problems of high-quality data accumulation, high timeliness of the data analysis, and difficulty in embedding deep-learning algorithms directly in real-time systems, this paper proposes a new progressive deep-learning framework and conducts experiments on image recognition. The experimental results show that the proposed framework is effective and performs well and can reach a conclusion similar to the deep-learning framework based on large-scale data.

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Ashour, Samir, and Mazen Nassar. "Analysis of Generalized Exponential Distribution Under Adaptive Type-II Progressive Hybrid Censored Competing Risks Data." International Journal of Advanced Statistics and Probability 2, no. 2 (2014): 108. http://dx.doi.org/10.14419/ijasp.v2i2.3423.

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Tse, Siu Keung, Chunyan Yang, and Hak-Keung Yuen. "Statistical analysis of Weibull distributed lifetime data under Type II progressive censoring with binomial removals." Journal of Applied Statistics 27, no. 8 (2000): 1033–43. http://dx.doi.org/10.1080/02664760050173355.

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Alafuzoff, I., K. Iqbal, H. Friden, R. Adolfsson, and B. Winblad. "Histopathological criteria for progressive dementia disorders: clinical-pathological correlation and classification by multivariate data analysis." Acta Neuropathologica 74, no. 3 (1987): 209–25. http://dx.doi.org/10.1007/bf00688184.

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Herani, Isti Endila, and Cynantia Rachmijati. "AN ANALYSIS OF TENSE AND ASPECT IN THE “TANGLED” MOVIE SCRIPT." PROJECT (Professional Journal of English Education) 2, no. 2 (2019): 187. http://dx.doi.org/10.22460/project.v2i2.p187-193.

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This study is an attempt to analyze the tense and aspects found inside the ”Tangled” movie script. The data source is a sentence or speech the verb contains tense and aspects found on “Tangled” movie script. The study applied descriptive qualitative method.This study belongs to a descriptive research because it collects and analyzes the data, after that draws a conclusion based on the data. Then this research belongs to qualitative research because it involves analyzing and explaining the data. Additionally, this research is designed in descriptive qualitative research because the research examines the types of the language used of Tense and Aspects in "Tangled" Movie Scripts. In this research the data source is “Tangled” Movie Script.In “Tangled” movie script, there was 61 sentences that researcher found in the uses of tense and aspect. From the result above the dominant types on tense and aspect in “Tangled” movie script was simple future and present perfect. In the “Tangled” movie script the researcher didn’t find tense and aspect in past perfect progressive, future progressive, future perfect and future perfect progressive.

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Kapoor, Raju, Kathryn E. Smith, Mark Allegretta, et al. "Serum neurofilament light as a biomarker in progressive multiple sclerosis." Neurology 95, no. 10 (2020): 436–44. http://dx.doi.org/10.1212/wnl.0000000000010346.

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There is an unmet need in multiple sclerosis (MS) therapy for treatments to stop progressive disability. The development of treatments may be accelerated if novel biomarkers are developed to overcome the limitations of traditional imaging outcomes revealed in early phase trials. In January 2019, the International Progressive MS Alliance convened a standing expert panel to consider potential tissue fluid biomarkers in MS in general and in progressive MS specifically. The panel focused their attention on neurofilament light chain (NfL) in serum or plasma, examining data from both relapsing and progressive MS. Here, we report the initial conclusions of the panel and its recommendations for further research. Serum NfL (sNfL) is a plausible marker of neurodegeneration that can be measured accurately, sensitively, and reproducibly, but standard procedures for sample processing and analysis should be established. Findings from relapsing and progressive cohorts concur and indicate that sNfL concentrations correlate with imaging and disability measures, predict the future course of the disease, and can predict response to treatment. Importantly, disease activity from active inflammation (i.e., new T2 and gadolinium-enhancing lesions) is a large contributor to sNfL, so teasing apart disease activity from the disease progression that drives insidious disability progression in progressive MS will be challenging. More data are required on the effects of age and comorbidities, as well as the relative contributions of inflammatory activity and other disease processes. The International Progressive MS Alliance is well positioned to advance these initiatives by connecting and supporting relevant stakeholders in progressive MS.

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Poole, Matthew L., Amy Brodtmann, David Darby, and Adam P. Vogel. "Motor Speech Phenotypes of Frontotemporal Dementia, Primary Progressive Aphasia, and Progressive Apraxia of Speech." Journal of Speech, Language, and Hearing Research 60, no. 4 (2017): 897–911. http://dx.doi.org/10.1044/2016_jslhr-s-16-0140.

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Purpose Our purpose was to create a comprehensive review of speech impairment in frontotemporal dementia (FTD), primary progressive aphasia (PPA), and progressive apraxia of speech in order to identify the most effective measures for diagnosis and monitoring, and to elucidate associations between speech and neuroimaging. Method Speech and neuroimaging data described in studies of FTD and PPA were systematically reviewed. A meta-analysis was conducted for speech measures that were used consistently in multiple studies. Results The methods and nomenclature used to describe speech in these disorders varied between studies. Our meta-analysis identified 3 speech measures which differentiate variants or healthy control-group participants (e.g., nonfluent and logopenic variants of PPA from all other groups, behavioral-variant FTD from a control group). Deficits within the frontal-lobe speech networks are linked to motor speech profiles of the nonfluent variant of PPA and progressive apraxia of speech. Motor speech impairment is rarely reported in semantic and logopenic variants of PPA. Limited data are available on motor speech impairment in the behavioral variant of FTD. Conclusions Our review identified several measures of speech which may assist with diagnosis and classification, and consolidated the brain–behavior associations relating to speech in FTD, PPA, and progressive apraxia of speech.

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Caligiuri, Maria Eugenia, Giuseppe Tradigo, and Patrizia Vizza. "Using Hybrid Bioimaging Analysis for Rare Neurological Diseases." ACM SIGBioinformatics Record 12, no. 1 (2023): 1–2. http://dx.doi.org/10.1145/3615362.3615365.

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Hybrid PET/MRI is a promising new approach for simultaneously investigating the relationships between intrinsic metabolic and functional brain changes. In this abstract, we present an analysis workflow for longitudinal PET/MRI studies in rare neurological diseases. We envision that software tools based on the presented workflow can be used to evaluate progressive disease-related volumetric, functional, and metabolic alterations. Furthermore, it could be useful for characterize degenerative pathologies with fast dynamics. Our main contribution is the use of multimodal hybrid PET/MRI data fusion to identify potential markers of disease progression, which could support physicians in future trials to test disease-modifying drugs.

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Pytel, Vanesa, Laura Hernández-Lorenzo, Laura Torre-Fuentes, et al. "Whole-Exome Sequencing and C9orf72 Analysis in Primary Progressive Aphasia." Journal of Alzheimer's Disease 80, no. 3 (2021): 985–90. http://dx.doi.org/10.3233/jad-201310.

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Primary progressive aphasia (PPA) is mainly considered a sporadic disease and few studies have systematically analyzed its genetic basis. We here report the analyses of C9orf72 genotyping and whole-exome sequencing data in a consecutive and well-characterized cohort of 50 patients with PPA. We identified three pathogenic GRN variants, one of them unreported, and two cases with C9orf72 expansions. In addition, one likely pathogenic variant was found in the SQSTM1 gene. Overall, we found 12%of patients carrying pathogenic or likely pathogenic variants. These results support the genetic role in the pathophysiology of a proportion of patients with PPA.

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