scholarly journals Mean-Based Breakpoint Selection on Circular Histogram

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiulun Fan ◽  
Jipeng Yang
Keyword(s):  
Selection Criteria ◽  
Color Image ◽  
Selection Criterion ◽  
Threshold Value ◽  
Simple Expression ◽  
Circular Data ◽  
Cumulative Distribution ◽  
Color Model ◽  
Hsi Color Model ◽  
Selection Of

Circular histogram represents the statistical distribution of circular data; the H component histogram of HSI color model is a typical example of the circular histogram. When using H component to segment color image, a feasible way is to transform the circular histogram into a linear histogram, and then, the mature gray image thresholding methods are used on the linear histogram to select the threshold value. Thus, the reasonable selection of the breakpoint on circular histogram to linearize the circular histogram is the key. In this paper, based on the angles mean on circular histogram and the line mean on linear histogram, a simple breakpoint selection criterion is proposed, and the suitable range of this method is analyzed. Compared with the existing breakpoint selection criteria based on Lorenz curve and cumulative distribution entropy, the proposed method has the advantages of simple expression and less calculation and does not depend on the direction of rotation.

scholarly journals P126: Development of inclusion and exclusion criteria for ECPR in a regional hospital

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S101-S101
Author(s):  
D. Rollo ◽  
P. Atkinson ◽  
J. Fraser ◽  
J. Mekwan ◽  
J. P. French ◽  
...  
Keyword(s):  
Selection Criteria ◽  
Selection Process ◽  
Selection Criterion ◽  
Flow Time ◽  
Regional Hospital ◽  
Current Evidence ◽  
Inclusion Criteria ◽  
Exclusion Criteria ◽  
Patient Selection Criterion ◽  
Selection Of

Introduction: Extracorporeal cardiopulmonary resuscitation (ECPR), a method of cardiopulmonary bypass, is increasingly being used to supplement traditional CPR to improve outcomes for cardiac arrest (CA). CA and particularly out of hospital CA (OHCA) have poor outcomes. Prior to development of a 3 phase ECPR program in a Canadian regional hospital, we wished to identify and optimize a practical selection process (inclusion and exclusion criteria) for patients who may benefit from ECPR. Methods: Using a locally modified Delphi technique, we followed a literature review to construct a proposed set of evidence based criteria with a questionnaire, where inclusion and exclusion criteria were scored by a selected group of 13 experts. Following 3 rounds, and additional review by an international expert in the field of ECPR, consensus was achieved for patient selection criterion. Results: First round responses achieved 87.5% agreement for selection of exclusion criteria. Inclusion criteria had agreement 62.5%. Responses to the second round for selection of inclusion criteria were unanimous at 100% with the exception of age parameters (<65 years vs. <70 years). The third and final set of criteria achieved 100% consensus though subsequent expert review refined a single exclusion criteria (asystole). Agreed inclusion criteria were: witnessed CA, age <70, refractory arrest, no flow time <10min, total downtime <60min, and a cardiac or select non-cardiac etiology (PE, drug OD, poisoning, hypothermia). Exclusion criteria were : unwitnessed arrest, asystole, certain etiologies (uncontrolled bleeding, irreversible brain damage, trauma), and comorbidities (severe disability limiting ADLs, standing DNR, palliation). Simplified criteria for EMS transport included witnessed OHCA, age, and no flow time. Conclusion: Selection criteria of candidates for ECPR are important components for any program. Expert consensus review of current evidence is an effective method for development of ECPR selection criteria.

scholarly journals Mother wavelet selection using signal energy for cracks detection in the rotation shafts

2020 ◽  
Vol XXIII (2) ◽  
pp. 64-74
Author(s):  
Pricop Codruta
Keyword(s):  
Selection Criteria ◽  
Selection Criterion ◽  
Mother Wavelet ◽  
Signal Energy ◽  
Frequency Bands ◽  
Optimum Selection ◽  
Rotating Shafts ◽  
Wavelet Selection ◽  
Energy Dissipated ◽  
Selection Of

The mother wavelet greatly influences the wavelet analysis of a non-stationary and nonlinear recorded signal. Choosing mother wavelet must be done to determine cracks in rotating shafts so as to take into account the nature and type of information signals to be extracted from the signal. The difficulty in optimum selection of the mother wavelet is determined by their complex properties that determine different selection criteria. In the paper, several families of functions (Haar, Daubechies, Symlets, Coiflet, BiorSplines) were used for analysis and the proposed selection criterion is the energy dissipated on the frequency bands. Signal recordings were made on a stand to determine the presence of cracks in rotating shafts and their classification. For discrete decomposition of recorded signals (DWT) and the calculation of energy dissipated on the frequency bands the Matlab wavelet instrument was used.

Selection of one-dimensional sedimentation: models for on-line use

1995 ◽  
Vol 31 (2) ◽  
pp. 193-204 ◽  
Author(s):  
Koen Grijspeerdt ◽  
Peter Vanrolleghem ◽  
Willy Verstraete
Keyword(s):  
Steady State ◽  
Selection Criteria ◽  
Data Sets ◽  
Concentration Profiles ◽  
A Posteriori ◽  
One Dimensional ◽  
On Line ◽  
Dynamic Concentration ◽  
Selection Of ◽  
Modelling Task

A comparative study of several recently proposed one-dimensional sedimentation models has been made. This has been achieved by fitting these models to steady-state and dynamic concentration profiles obtained in a down-scaled secondary decanter. The models were evaluated with several a posteriori model selection criteria. Since the purpose of the modelling task is to do on-line simulations, the calculation time was used as one of the selection criteria. Finally, the practical identifiability of the models for the available data sets was also investigated. It could be concluded that the model of Takács et al. (1991) gave the most reliable results.

Discovery of five new Galactic symbiotic stars in the VPHAS+ survey

2021 ◽  
Vol 502 (2) ◽  
pp. 2513-2517
Author(s):  
Stavros Akras ◽  
Denise R Gonçalves ◽  
Alvaro Alvarez-Candal ◽  
Claudio B Pereira
Keyword(s):  
Spectroscopic Data ◽  
Selection Criterion ◽  
Optical Spectra ◽  
Emission Lines ◽  
High Rate ◽  
Symbiotic Stars ◽  
Selection Of

ABSTRACT We report the validation of a recently proposed infrared (IR) selection criterion for symbiotic stars (SySts). Spectroscopic data were obtained for seven candidates, selected from the SySt candidates of Akras et al. by employing the new supplementary IR selection criterion for SySts in the VST/OmegaCAM Photometric H-Alpha Survey. Five of them turned out to be genuine SySts after the detection of H α, He ii, and [O iii] emission lines as well as TiO molecular bands. The characteristic O vi Raman-scattered line is also detected in one of these SySts. According to their IR colours and optical spectra, all five newly discovered SySts are classified as S-type. The high rate of true SySts detections of this work demonstrates that the combination of the H α emission and the new IR criterion improves the selection of target lists for follow-up observations by minimizing the number of contaminants and optimizing the observing time.

scholarly journals Introgression of Resistance to Leafminer (Liriomyza cicerina Rondani) from Cicer reticulatum Ladiz. to C. arietinum L. and Relationships between Potential Biochemical Selection Criteria

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Nesrine Chrigui ◽  
Duygu Sari ◽  
Hatice Sari ◽  
Tuba Eker ◽  
Mehmet Fatih Cengiz ◽  
...  
Keyword(s):  
Organic Acids ◽  
Succinic Acid ◽  
Selection Criteria ◽  
Insect Pests ◽  
Recombinant Inbred Lines ◽  
Selection Criterion ◽  
Leaf Miner ◽  
Interspecific Crosses ◽  
Visual Scale ◽  
Resistant Varieties

The chickpea leafminer, Liriomyza cicerina (Rondani), is one of the most destructive insect pests of cultivated chickpea (Cicer arietinum L.) in the Mediterranean region under field conditions. For sustainable and environmentally friendly chickpea production, efforts have been devoted to managing the leafminer via decreasing the use of insecticides. Breeding of new resistant varieties is not only an efficient and practical approach, but also cost-effective and environmentally sensitive. To improve resistant varieties, breeders need reliable biochemical selection criteria that can be used in breeding programs. The first objective was to investigate the possible introgression of resistance to the leafminer from C. reticulatum Ladiz. (resistant) to C. arietinum (susceptible), then, to estimate inheritance of resistance to the leafminer for efficient breeding strategies, and finally, to study organic acid contents as selection criteria. Recombinant inbred lines (RILs) and their parents were evaluated using a visual scale of 1–9 (1 = free from leafminer damage and 9 = mines in more than 91% of the leaflets and defoliation greater than 31%) in the field under natural infestation conditions after the susceptible parent and check had scores of >7 on the visual scale. Superior RILs were found for resistance to the leafminer, and agro-morphological traits indicating that introgression of resistance to leaf miner from C. reticulatum to C. arietinum could be possible using interspecific crosses. The inheritance pattern of resistance to the leafminer in RILs was shown to be quantitative. Organic acids, including oxalic, malic, quinic, tartaric, citric and succinic acids in RILs grown in the field under insect epidemic conditions and in the greenhouse under non-infested conditions were detected by using high performance liquid chromatography (HPLC). In general, organic acids were found to be higher in resistant RILs than susceptible RILs. Path and correlation coefficients showed that succinic acid exhibited the highest direct effects on resistance to the leafminer. Multivariate analyses, including path, correlation and factor analyses suggested that a high level of succinic acid could be used as a potential biochemical selection criterion for resistance to leafminer in chickpea. Resistant RILs with a high seed yield resembling kabuli chickpea can be grown directly in the target environments under leaf miner infestation conditions.

scholarly journals Monotonic Functions Method and Its Application to Staging of Patients with Prostate Cancer According to Pretreatment Data

2021 ◽  
Vol 11 (9) ◽  
pp. 3836
Author(s):  
Valeri Gitis ◽  
Alexander Derendyaev ◽  
Konstantin Petrov ◽  
Eugene Yurkov ◽  
Sergey Pirogov ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Learning Algorithm ◽  
Binary Classification ◽  
Preoperative Staging ◽  
Threshold Value ◽  
Logical Function ◽  
Adequate Treatment ◽  
Monotonic Functions ◽  
Selection Of

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.

Individual effects in variation analysis: Model, software, and research design

2013 ◽  
Vol 25 (1) ◽  
pp. 89-118 ◽  
Author(s):  
John C. Paolillo
Keyword(s):  
Research Design ◽  
Fixed Effects ◽  
Selection Criteria ◽  
Current Approach ◽  
Variation Analysis ◽  
Analysis Model ◽  
Individual Level ◽  
Mixed Effects Modeling ◽  
Variationist Sociolinguistics ◽  
Selection Of

AbstractIndividual-level variation is a recurrent issue in variationist sociolinguistics. One current approach recommends addressing this via mixed-effects modeling. This paper shows that a closely related model with fixed effects for individual speakers can be directly estimated using Goldvarb. The consequences of employing different approaches to speaker variation are explored by using different model selection criteria. We conclude by discussing the relation of the statistical model to the assumptions of the research design, pointing out that nonrandom selection of speakers potentially violates the assumptions of models with random effects for speaker, and suggesting that a model with fixed effects for speakers may be a better alternative in these cases.

scholarly journals Improved selection of participants in genetic longevity studies: family scores revisited

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mar Rodríguez-Girondo ◽  
Niels van den Berg ◽  
Michel H. Hof ◽  
Marian Beekman ◽  
Eline Slagboom
Keyword(s):  
Missing Data ◽  
The Netherlands ◽  
Family Size ◽  
Simulation Study ◽  
Missing Values ◽  
Selection Criterion ◽  
Limited Success ◽  
Main Challenge ◽  
Historical Sample ◽  
Selection Of

Abstract Background Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data. Methods We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN). Results Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score . Conclusions Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.

Selection of Representative Scenarios Using Multiple Simulation Outputs for Robust Well Placement Optimization in Greenfields

2021 ◽  
Author(s):  
Seyed Kourosh Mahjour ◽  
Antonio Alberto Souza Santos ◽  
Susana Margarida da Graca Santos ◽  
Denis Jose Schiozer
Keyword(s):  
Reference Model ◽  
Simulation Models ◽  
Cumulative Distribution ◽  
Small Subset ◽  
Fine Grid ◽  
Well Placement ◽  
Placement Optimization ◽  
Well Placement Optimization ◽  
Selection Of ◽  
Dynamic Uncertainties

Abstract In greenfield projects, robust well placement optimization under different scenarios of uncertainty technically requires hundreds to thousands of evaluations to be processed by a flow simulator. However, the simulation process for so many evaluations can be computationally expensive. Hence, simulation runs are generally applied over a small subset of scenarios called representative scenarios (RS) approximately showing the statistical features of the full ensemble. In this work, we evaluated two workflows for robust well placement optimization using the selection of (1) representative geostatistical realizations (RGR) under geological uncertainties (Workflow A), and (2) representative (simulation) models (RM) under the combination of geological and reservoir (dynamic) uncertainties (Workflow B). In both workflows, an existing RS selection technique was used by measuring the mismatches between the cumulative distribution of multiple simulation outputs from the subset and the full ensemble. We applied the Iterative Discretized Latin Hypercube (IDLHC) to optimize the well placements using the RS sets selected from each workflow and maximizing the expected monetary value (EMV) as the objective function. We evaluated the workflows in terms of (1) representativeness of the RS in different production strategies, (2) quality of the defined robust strategies, and (3) computational costs. To obtain and validate the results, we employed the synthetic UNISIM-II-D-BO benchmark case with uncertain variables and the reference fine- grid model, UNISIM-II-R, which works as a real case. This work investigated the overall impacts of the robust well placement optimization workflows considering uncertain scenarios and application on the reference model. Additionally, we highlighted and evaluated the importance of geological and dynamic uncertainties in the RS selection for efficient robust well placement optimization.

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