Papers by Reyhaneh Rikhtehgaran
Cognitive Neurodynamics, 2022
Dry Sliding Wear Characteristics of NiP/TiN Duplex Coated Aluminum Alloy and Wear Analysis Using Response Surface Method
Journal of Materials Engineering and Performance, 2022
In this work, the effects of applied load, sliding velocity, and sliding distance on the tribolog... more In this work, the effects of applied load, sliding velocity, and sliding distance on the tribological characteristics of 6061 aluminum alloy coated with NiP/TiN duplex coating were experimentally investigated and simulated by Response Surface Methodology (RSM). Dry sliding wear tests were conducted using a ball-on-disc apparatus. A developed model was proposed to predict the wear depth and friction coefficient of the coated specimens. According to the outcome of developed model, coefficient of determination values of 99.95 and 94.39% were obtained for the wear depth and friction coefficient, respectively. Scanning electron microscopy (SEM) examination of the worn surfaces after 500 m sliding revealed slight wear on the surface of the duplex coating under 2 N load (with the final friction coefficient of 0.35). By increasing the load to 7 N, heavier wear was observed, and the final friction coefficient was increased to 0.5. At the load of 12 N, both TiN and NiP layers were removed, and the final friction coefficient of 0.8 was recorded. Ultimately, wear analysis using RSM revealed that the applied load was the most important factor influencing the wear depth and friction coefficient of the coated specimens.
Spike Sorting of Non-Stationary Data in Successive Intervals Based on Dirichlet Process Mixtures
Cognitive Neurodynamics, 2022
Cognitive Neurodynamics, 2022
Dry Sliding Wear Characteristics of NiP/TiN Duplex Coated Aluminum Alloy and Wear Analysis Using Response Surface Method
Journal of Materials Engineering and Performance, 2022
In this work, the effects of applied load, sliding velocity, and sliding distance on the tribolog... more In this work, the effects of applied load, sliding velocity, and sliding distance on the tribological characteristics of 6061 aluminum alloy coated with NiP/TiN duplex coating were experimentally investigated and simulated by Response Surface Methodology (RSM). Dry sliding wear tests were conducted using a ball-on-disc apparatus. A developed model was proposed to predict the wear depth and friction coefficient of the coated specimens. According to the outcome of developed model, coefficient of determination values of 99.95 and 94.39% were obtained for the wear depth and friction coefficient, respectively. Scanning electron microscopy (SEM) examination of the worn surfaces after 500 m sliding revealed slight wear on the surface of the duplex coating under 2 N load (with the final friction coefficient of 0.35). By increasing the load to 7 N, heavier wear was observed, and the final friction coefficient was increased to 0.5. At the load of 12 N, both TiN and NiP layers were removed, and the final friction coefficient of 0.8 was recorded. Ultimately, wear analysis using RSM revealed that the applied load was the most important factor influencing the wear depth and friction coefficient of the coated specimens.
Spike Sorting of Non-Stationary Data in Successive Intervals Based on Dirichlet Process Mixtures
Cognitive Neurodynamics, 2022
Emergency Radiology, 2021
Background The COVID-19 pandemic is straining the health care systems worldwide. Therefore, healt... more Background The COVID-19 pandemic is straining the health care systems worldwide. Therefore, health systems should make strategic shifts to ensure that limited resources provide the highest benefit for COVID-19 patients. Objective This study aimed to describe the risk factors associated with poor in-hospital outcomes to help clinicians make better patient care decisions. Material and methods This retrospective observational study enrolled 176 laboratory-confirmed COVID-19 patients. Demographic characteristics, clinical data, lymphocyte count, CT imaging findings on admission, and clinical outcomes were collected and compared. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement. The receiver operating characteristic (ROC) curve was used to determine the optimum cutoff point for possible effective variables on patients' outcomes. Multivariable logistic regression models were used to determine the risk factors associated with ICU admission and in-hospital death. Result Thirty-eight (21.5%) patients were either died or admitted to ICU from a total of 176 enrolled ones. The mean age of the patients was 57.5 ± 16.1 years (males: 61%). The best cutoff point for predicting poor outcomes based on age, CT score, and O 2 saturation was 60 years (
Emergency Radiology, 2021
Background The COVID-19 pandemic is straining the health care systems worldwide. Therefore, healt... more Background The COVID-19 pandemic is straining the health care systems worldwide. Therefore, health systems should make strategic shifts to ensure that limited resources provide the highest benefit for COVID-19 patients. Objective This study aimed to describe the risk factors associated with poor in-hospital outcomes to help clinicians make better patient care decisions. Material and methods This retrospective observational study enrolled 176 laboratory-confirmed COVID-19 patients. Demographic characteristics, clinical data, lymphocyte count, CT imaging findings on admission, and clinical outcomes were collected and compared. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement. The receiver operating characteristic (ROC) curve was used to determine the optimum cutoff point for possible effective variables on patients' outcomes. Multivariable logistic regression models were used to determine the risk factors associated with ICU admission and in-hospital death. Result Thirty-eight (21.5%) patients were either died or admitted to ICU from a total of 176 enrolled ones. The mean age of the patients was 57.5 ± 16.1 years (males: 61%). The best cutoff point for predicting poor outcomes based on age, CT score, and O 2 saturation was 60 years (
Detection of alteration zones using the Dirichlet process Stick-Breaking model-based clustering algorithm to hyperion data: the case study of Kuh-Panj porphyry copper deposits, Southern Iran
Geocarto International, 2022
رویکرد نیمهپارامتری بیزی به خوشهبندی رگرسیونی کودکان و نوجوانان ایرانی بر اساس ریسک ابتلا به بیماریهای قلبی- عروقی و دیابت
چكيده مقدمه: در این مقاله، خوشهبندی رگرسیونی(Regression clustering) با استفاده از فرایند دیریکل... more چكيده مقدمه: در این مقاله، خوشهبندی رگرسیونی(Regression clustering) با استفاده از فرایند دیریکله (Dirichlet process) جهت به‌دست آوردن بینشی جامع از الگوی سلامت کودکان و نوجوانان بررسی‌شده در مطالعات ملی ایران، درنظر گرفته شد. در این رویکرد به خوشهبندی، ضمن این‌که تأثیر عوامل مزاحم، حذف و تحلیل‌های دقیق‌تری از وضعیت افراد به‌دست می‌آید، تعداد خوشه‌ها و الگوهای موجود در داده‌ها نیز تخمین زده می‌شود. در این پژوهش، خوشهبندی افراد نمونه از نظر دو شاخص چربی‌خون و قند خون، مدنظر قرار گرفته و میزان تأثیر شاخص تن‌سنجی (Anthropometric)، رده سنی و جنسیت بر نحوه خوشهبندی افراد، مورد ارزیابی قرار گرفته است. روش‌ها: به منظور برآورد پارامترهای مجهول مدل، با رویکرد بیز (Bayesian approach) به مسأله، از روش‌های شبیه‌سازی مونت کارلوی زنجیر مارکفی (Markov chain Monte Carlo) در نرم‌افزار اپن‌باگز (Open Bugs) استفاده شده است. به‌منظور به‌دست آوردن بینش مناسب در رابطه با تعداد الگوهای افراد در معرض خطر بیماریهای قلبی- عروقی و دیابت، بر مبنای شاخص چربی‌خون و قند خون، از فرایند دیریکله استفاده شده است...
Spike sorting: Which clustering method should be chosen? Which circumstances affect this selection?
2017 Iranian Conference on Electrical Engineering (ICEE), 2017
There have been several researches on spike sorting, the process of detection, feature extraction... more There have been several researches on spike sorting, the process of detection, feature extraction and clustering neural signals generated by brain neurons. How accurate spike sorting is performed, determines how much the results are reliable. Therefore, selecting among several proposed methods for each spike sorting step is a very important task. In this paper, we want to answer this question for the clustering step. We used the most common feature extraction method, i.e. PCA and the first two principal components as features. In order to have fair judgment, 3 datasets with different noise levels were used. We compared some of the most popular methods, selecting between: model-based/non model-based, simple mixtures/Dirichlet process mixtures, Normal/t-distributions for observations, Bayesian/EM clustering. Eventually, some direct and some situation-based conclusions were obtained.
Minerals, 2021
The application of machine learning (ML) algorithms for processing remote sensing data is momento... more The application of machine learning (ML) algorithms for processing remote sensing data is momentous, particularly for mapping hydrothermal alteration zones associated with porphyry copper deposits. The unsupervised Dirichlet Process (DP) and the supervised Support Vector Machine (SVM) techniques can be executed for mapping hydrothermal alteration zones associated with porphyry copper deposits. The main objective of this investigation is to practice an algorithm that can accurately model the best training data as input for supervised methods such as SVM. For this purpose, the Zefreh porphyry copper deposit located in the Urumieh-Dokhtar Magmatic Arc (UDMA) of central Iran was selected and used as training data. Initially, using ASTER data, different alteration zones of the Zefreh porphyry copper deposit were detected by Band Ratio, Relative Band Depth (RBD), Linear Spectral Unmixing (LSU), Spectral Feature Fitting (SFF), and Orthogonal Subspace Projection (OSP) techniques. Then, usin...
Journal of Research in Health Sciences, 2020
Background: Frequency, severity, and duration of attacks are some major parameters in headache ma... more Background: Frequency, severity, and duration of attacks are some major parameters in headache management, affected by some other factors. Ignoring these factors in headache-related studies can lead to incorrect results. We aimed to model both socio-demographic characteristics and headache-associated symptoms related to frequency, severity and duration of headache attacks. Study design: A longitudinal panel study. Methods: Overall, 275 migraines or tension Type Headache (TTH) patients were visited at three different times in 2012 in Isfahan, Iran. On the first visit socio-demographic characteristics and headache symptoms of the patients were asked. In all of the visits, headache frequency, severity and attack duration were recorded. Results: Frequency of headaches was influenced by headache type, age, job status, working hours, residency, disease duration, laterality, and type of pain onset. In terms of intensity, headaches were more severe in patients with migraine-type; those suff...
Emergency Radiology, 2021
Statistical Modelling, 2017
In this article, the Dirichlet process (DP) is applied to cluster subjects with longitudinal obse... more In this article, the Dirichlet process (DP) is applied to cluster subjects with longitudinal observations. The basis of clustering is the ability of subjects to adapt themselves to new circumstances. Indeed, the basis of clustering depends on the time of changing response variability. This is done by providing a random change-point time in the variance structure of mixed-effects models. The DP is assumed as a prior for the distribution of the random change point. The discrete nature of the DP is utilized to cluster subjects according to the time of adaption. The proposed model is useful to identify groups of subjects with distinctive time-based progressions or declines. Transition mixed-effects models are also used to account for the serial correlation among observations over time. A joint modelling approach is utilized to handle the bias created in these models. The Gibbs sampling technique is adopted to achieve parameter estimates. Performance of the proposed method is evaluated v...
IET Image Processing, 2017
Saliency detection has shown a great role in many image processing applications. This study intro... more Saliency detection has shown a great role in many image processing applications. This study introduces a new Bayesian framework for saliency detection. In this framework, image saliency is computed as product of three saliencies: location-based, feature-based and centre-surround saliencies. Each of these saliencies is estimated using statistical approaches. The centre-surround saliency is estimated using Dirichlet process mixture model. The authors evaluate their method using five different databases and it is shown that it outperform state-of-the-art methods. Also, they show that the proposed method has a low computational cost.
Journal of the American Academy of Dermatology, 2017
define county status. We categorized dermatologist density as ''none'' (counties with no dermatol... more define county status. We categorized dermatologist density as ''none'' (counties with no dermatologists), ''low'' (0.1-11 dermatologists/100,000), ''intermediate-low'' (11.1-32 dermatologists/100,000), ''intermediate-high'' (32.1-82 dermatologists/100,000), and ''high'' (82.1-422 dermatologists/100,000). County status included metropolitan, nonmetropolitan, or urban counties. Tumor stage was derived from the American Joint Committee on Cancer (AJCC) stage, 6th edition, 4 and was categorized as ''early'' (I/II) and ''advanced'' (III/IV). We used 2 and analysis of variance to calculate univariate differences. Overall survival analysis was conducted using Kaplan-Meier method with log-rank statistic and Cox proportional hazards modeling. The data were analyzed using statistical software (SPSS, Version 23.0, IBM Corp, Armonk, NY). We examined 2709 patients with MCC. Increased dermatologist density was significantly associated J AM ACAD DERMATOL VOLUME 76, NUMBER 3 Letters 571 Dr Stein was supported by the Irwin I. Lubowe Fellowship in Dermatology.
Statistics in Medicine, 2014
In this paper, we investigate the impact of time-invariant covariates when fitting transition mix... more In this paper, we investigate the impact of time-invariant covariates when fitting transition mixed models. This is carried out by emphasizing on the role of baseline responses on the estimation process. Transition models are allowed for two cases of exogenous and endogenous baseline responses. We illustrate these concepts in the special case of transition linear mixed models with centered time-varying covariates. Results of our simulation studies show that the omission, or the inclusion, of time-invariant covariates is not important in models with exogenous baseline responses, while it has an essential effect on fitting models with the endogenous baseline responses. It is also emphasized that the effect becomes minor when the endogeneity issue is handled. The practical consequences are illustrated in the analysis of a real data set taken from medical sciences.
Prediction of fabric handle value using ordinal regression model
The Journal of The Textile Institute, 2014
ABSTRACT Bed sheet fabric as a kind of home textile has been used since many years ago. Bed sheet... more ABSTRACT Bed sheet fabric as a kind of home textile has been used since many years ago. Bed sheet is very significant because of being in direct contact with body consecutively for a long period of time. Bed sheet surplus qualitative parameters such as fiber substance, method of printing, finishing, etc., have a significant parameter called handle. In this paper, we proceeded to consider the relationship between fabric handle as a qualitative parameter and physical parameters which influenced the fabric handle using statistical modeling. The statistical model used was ordinal regression model. The modeling was done by SPSS V.19 software. We used 15 bed sheet fabrics. For subjective evaluation of 15 bed sheet fabrics, we selected 55 persons randomly as sample members according to Cochran’s formula. Population was selected from senior BS students and MS students at Isfahan University of Technology (IUT). We asked persons to classify bed sheet fabrics based on their preference of fabric handle from 1 (lowest) to 5 (highest). Physical parameters values were obtained through standard experiments. Finally, we analyzed obtained data through SPSS V.19 using ordinal regression model. Results showed a satisfying match between extracted data from the software and the real data from person’s evaluation.
Piecewise transition models with random effects for unequally spaced longitudinal measurements
Statistical Modelling, 2012
In this paper, we consider the analysis of unequally spaced longitudinal data using transition re... more In this paper, we consider the analysis of unequally spaced longitudinal data using transition regression models with random effects. Diffusion as well as stabilization processes will be discussed, but our main focus will be on the latter. The initial conditions problem, which usually arises in transition models with random effects, is addressed. The usefulness of the proposed model is assessed on a large database of longitudinal haemoglobin values collected from blood donations by a Dutch private organization.
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Papers by Reyhaneh Rikhtehgaran