97 research outputs found
Parameter estimation bias of dichotomous logistic item response theory models using different variables
The aim of this study was to examine the precision of item parameter estimation in different sample sizes and test lengths under three parameter logistic model (3PL) item response theory (IRT) model, where the trait measured by a test was not normally distributed or had a skewed distribution.In the study, number of categories (1-0), and item response model were identified as fixed conditions, and sample size, test length variables, and the ability distributions were selected as manipulated conditions. This is a simulation study. So data simulation and data analysis were done via packages in the R programming language. Results of the study showed that item parameter estimations performed under normal distribution were much stronger and bias-free compared to non-normal distribution. Moreover, the sample size had some limited positive effect on parameter estimation. However, the test length had no effect parameter estimation. As a result the importance of normality assumptions for IRT models were highlighted and findings were discussed based on relevant literature
An analysis of the differential item function through Mantel-Haenszel, SIBTEST and Logistic Regression MethodsMantel-Haenszel, SIBTEST ve Lojistik Regresyon Yöntemleri ile değişen madde fonksiyonunu analizi
This study performs a Differential Item Function (DIF) analysis in terms of gender and culture on the items available in the PISA 2009 mathematics literacy sub-test. The DIF analyses were done through the Mantel Haenszel, Logistic Regression and the SIBTEST methods. The data for the gender variable were collected from the responses given by 332 students to the items in the mathematics literacy sub-test during the administration of the 5th booklet in the PISA 2009 application whereas the data for the culture variable were collected through the application of the 5th booklet in Turkey, Germany, Finland and the United States in the PISA 2009 application. As a result of DIF analysis according to gender, 4 items carried out in favor of men, only one item can be said to be advantageous in favor of girls. As a result of DIF analysis according to culture, 16 items for Turkish and German students, 14 items for Turkish and Finn students, 18 items for Turkish and United States students were determined. ÖzetBu çalışmada, PISA 2009 uygulaması Matematik okuryazarlığı alttestinde, cinsiyete ve kültüre göre değişen madde fonksiyonu (DMF) içeren madde bulunup bulunmadığı incelenmiştir. DMF analizleri Mantel Haenszel, Lojistik Regresyon ve SIBTEST yöntemleriyle gerçekleştirilmiştir. Çalışmanın veri setini, cinsiyet değişkeni için PISA 2009 uygulamasında Türkiye’de 5. kitapçığındaki matematik okuryazarlığı alt testindeki maddelere 332 öğrencinin verdikleri cevaplar, kültür değişkeni için ise PISA 2009 uygulamasında Türkiye, Almanya, Finlandiya ve ABD’deki öğrencilerin 5. kitaptaki matematik testine verdikleri cevaplar oluşturmaktadır. Cinsiyet değişkenine göre 5 maddenin 4’ü erkekler lehine, bir maddenin kızlar lehine avantajlı olduğu söylenebilir. DMF analizi sonucunda Türkiye ile Almanya’dan katılan öğrencilerden elde edilen veri setlerinde 16, Türkiye ile Finlandiya’dan katılan öğrencilerden elde edilen veri setlerinde 14, Türkiye ile ABD’den katılan öğrencilerden elde edilen veri setlerinde 18 maddede DMF bulunduğu görülmüştür.
Genetic polymorphism in the serotonin transporter gene-linked polymorphic region and response to serotonin reuptake inhibitors in patients with premature ejaculation
OBJECTIVES: Serotonin plays a central role in ejaculation and selective serotonin reuptake inhibitors have been successfully used to treat premature ejaculation. Here, we evaluated the relationship between a polymorphism in the serotonin transporter gene-linked polymorphic region (5-HTTLPR) and the response of patients with premature ejaculation to SSRI medication. METHODS: Sixty-nine premature ejaculation patients were treated with 20 mg/d paroxetine for three months. The Intravaginal Ejaculatory Latency Time and International Index of Erectile Function scores were compared with baseline values. The patients were scored as having responded to therapy when a 2-fold or greater increase was observed in Intravaginal Ejaculatory Latency Time compared with baseline values after three months. Three genotypes of 5-HTTLPR were studied: LL, LS and SS. The appropriateness of the allele frequencies in 5-HTTLPR were analyzed according to Hardy-Weinberg equilibrium using the χ2-test. RESULTS: The short (S) allele of 5-HTTLPR was significantly more frequent in responders than in nonresponders (
Letrozole as an adjunct treatment in antagonist cycles that previously failed in poor responders
Objectives: To investigate whether adding letrozole in the early follicular phase of a gonadotropin-releasing hormone (GnRH) antagonist (GA) stimulation cycle improves in vitro fertilization (IVF) outcomes in poor responder patients.
Material and methods: To be included in this study, patients had to have had at least one previous GA cycle and a subsequent GA cycle with added early follicular phase letrozole (LzGA). A total of 41 poor responder patients were identified based on the Bologna criteria.
Results: The LzGA group had a lower dosage of follicular stimulating hormone (FSH) (p = 0.001), the duration of stimulation days (p = 0.015) and the duration of GnRH antagonist stimulation days (p = 0.033) when compared with controls. Comprehensive analysis of the cycle characteristics showed that the number of oocytes retrieved, the number of MII oocytes retrieved, the number of fertilized oocytes, and the fertilization rate were significantly higher in the LzGA cycle (p = 0.041, p = 0.019, p = 0.008, p = 0.01, respectively). The rate of cycle cancellation was lower in the LzGA group (24.4%) than in the GA group (48.8%), (p < 0.001). Although LzGA administration demonstrated a trend toward improved implantation and clinical pregnancy rates, this was an insignificant trend (p = 1.000, p = 0.177, respectively).
Conclusions: Adjunctive letrozole administration seems to restore an IVF cycle by improving the cycle characteristics and reducing the total gonadotrophin dosage.
Single-center experience with routine clinical use of 3D technologies in surgical planning for pediatric patients with complex congenital heart disease
PURPOSEThis study was planned to assess the application of three-dimensional (3D) cardiac modeling in preoperative evaluation for complex congenital heart surgeries.METHODSFrom July 2015 to September 2019, 18 children diagnosed with complex congenital heart diseases (CHDs) were enrolled in this study (double outlet right ventricle in nine patients, complex types of transposition of the great arteries in six patients, congenitally corrected transposition of the great arteries in two patients, and univentricular heart in one patient). The patients’ age ranged from 7 months to 19 years (median age, 14 months). Before the operation, 3D patient-specific cardiac models were created based on computed tomography (CT) data. Using each patient’s data, a virtual computer model (3D mesh) and stereolithographic (SLA) file that would be printed as a 3D model were generated. These 3D cardiac models were used to gather additional data about cardiac anatomy for presurgical decision-making.RESULTSAll 18 patients successfully underwent surgeries, and there were no mortalities. The 3D patient-specific cardiac models led to a change from the initial surgical plans in 6 of 18 cases (33%), and biventricular repair was considered feasible. Moreover, the models helped to modify the planned biventricular repair in five cases, for left ventricular outflow tract obstruction removal and ventricular septal defect enlargement. 3D cardiac models enable pediatric cardiologists to better understand the spatial relationships between the ventricular septal defect and great vessels, and they help surgeons identify risk structures more clearly for detailed planning of surgery. There was a strong correlation between the models of the patients and the anatomy encountered during the operation.CONCLUSION3D cardiac models accurately reveal the patient’s anatomy in detail and are therefore beneficial for planning surgery in patients with complex intracardiac anatomy
In a real-life setting, direct-acting antivirals to people who inject drugs with chronic hepatitis c in Turkey
Background: People who inject drugs (PWID) should be treated in order to eliminate hepatitis C virus in the world. The aim of this study
was to compare direct-acting antivirals treatment of hepatitis C virus for PWID and non-PWID in a real-life setting.
Methods: We performed a prospective, non-randomized, observational multicenter cohort study in 37 centers. All patients treated with
direct-acting antivirals between April 1, 2017, and February 28, 2019, were included. In total, 2713 patients were included in the study
among which 250 were PWID and 2463 were non-PWID. Besides patient characteristics, treatment response, follow-up, and side effects
of treatment were also analyzed.
Results: Genotype 1a and 3 were more prevalent in PWID-infected patients (20.4% vs 9.9% and 46.8% vs 5.3%). The number of naïve
patients was higher in PWID (90.7% vs 60.0%), while the number of patients with cirrhosis was higher in non-PWID (14.1% vs 3.7%). The
loss of follow-up was higher in PWID (29.6% vs 13.6%). There was no difference in the sustained virologic response at 12 weeks after
treatment (98.3% vs 98.4%), but the end of treatment response was lower in PWID (96.2% vs 99.0%). In addition, the rate of treatment
completion was lower in PWID (74% vs 94.4%).
Conclusion: Direct-acting antivirals were safe and effective in PWID. Primary measures should be taken to prevent the loss of follow-up
and poor adherence in PWID patients in order to achieve World Health Organization’s objective of eliminating viral hepatitis
The efficacy of cinacalcet in the treatment of hyperparathyroidism in Turkish hemodialysis patient population
WOS: 000393291900012OBJECTIVE: Cinacalcet reduces parathyroid hormone levels by increasing the sensitivity of the parathyroid gland to calcium. in this study, we firstly aimed to evaluate the efficacy of cinacalcet in Turkish hemodialysis patients. MATERIAL and METHODS: 4483 hemodialysis patients were screened and 469 patients who had used cinacalcet were included in the study. the patients were divided into 4 groups according to drug usage durations (Group 1: 3 months, Group 2: 6 months, Group 3: 9 months and Group 4: 12 months). the patients' Parathormone, Ca, P and CaxP levels at the 3rd, 6th, 9th and 12th months were compared to the start of treatment and previous months. RESULTS: the levels of Parathormone, Ca, P and CaxP significantly decreased compared to their initial levels in all groups (from 1412 pg/ml to 1222 pg/mL for Parathormone, p< 0,001) in the 3rd month. However, this reduction was not continued in the subsequent months (Parathormone: 1381 pg/ml for the 12th month). CONCLUSION: Cinacalcet may not provide adequate benefit in control of hyperparathyroidism in Turkish hemodialysis patient population
Locality aware task scheduling in heterogeneous computing enviroments
ÖZETHETEROJEN HESAPLAMA ORTAMLARINDA YERSELLİK BİLİNÇLİ GÖREV ÇİZELGELEME Heterojen hesaplama ortamları için etkili görev çizelgeleme “NP-Complete” olan bir problemdir ve genel görev çizelgeleme probleminin çözümü için literatürde birçok algoritma önerilmiştir. Görev çizelgelemeye ek olarak önbelleklerin kullanımı da performans ve güç tüketimi açısından kritik bir öneme sahiptir. Literatürdeki ilgili çalışmalar, önbellek kullanımını etkin kılmayı genellikle donanım ya da derleme seviyesinde hedeflemişlerdir. Önbellek davranışlarının Görev seviyesinde optimize edilmesinin hedeflenmesi iyi bir katkı olabilir. Çalışmamızda öncelikle veriye bağımlılıkları ve tekrar veri kullanımını göz önüne alarak oluşturduğumuz yersellik bilinçli modeli tanıtıyoruz. Daha sonra bu modeli temel alarak Yersellik-Bilinçli Heterojen Erken Bitiş Zamanı (LHEFT) ve Melez Genetik Algoritma (HGA) olarak iki algoritma öneriyoruz. Önerilen algoritmaların performansları, sentetik olarak oluşturulmuş görev çizgeleri kullanılarak literatürde önde gelen üç algoritma ile karşılaştırıldı. Bu çalışmamızda sunduğumuz karşılaştırma çalışmasına göre melez genetik algoritmamız tüm performans göstergelerinde diğer tüm ilgili çalışmalardan daha iyi sonuç göstermiştir. Anahtar Kelimeler: Görev Çizelgeleme, Heterojen Hesaplama Ortamları, Yersellik, Heuristik, Genetik Algoritmalar ABSTRACTLOCALITY AWARE TASK SCHEDULING IN HETEROGENEOUS COMPUTING ENVIRONMENTS Efficient task scheduling in heterogeneous computing environments is an NP-complete problem and there are many algorithms proposed in the literature so far to solve various types of the general task scheduling problem. In addition to task scheduling decisions, utilizing caches is also critical for both performance and power perspectives. Related work in the literature usually target for optimizing caches at hardware level or compilation level. Targeting task level optimizations for cache behaviors could be good asset and it can be performed at application level. In this study, we first present a locality aware task scheduling model by considering data dependencies and data reuses between tasks. Additionally two locality aware task scheduling heuristics are proposed in this thesis based on the proposed model, which are Locality-aware Heterogeneous Earliest Finish Time (LHEFT) algorithm and a Hybrid Genetic Algorithm (HGA). The performance of the proposed algorithms is compared with the three leading scheduling algorithms in the literature by using synthetically generated task graphs. According to comparative study presented in this study, our hybrid genetic algorithm outperforms the related work with respect to all performance metrics considered in this study. Keywords: Task Scheduling, Heterogeneous Computing Environment, Locality, Heuristics, Genetic Algorithm
Locality aware task scheduling in heterogeneous computing enviroments
HETEROJEN HESAPLAMA ORTAMLARINDA YERSELLİK BİLİNÇLİ GÖREV ÇİZELGELEME
Heterojen hesaplama ortamları için etkili görev çizelgeleme “NP-Complete” olan bir problemdir ve genel görev çizelgeleme probleminin çözümü için literatürde birçok algoritma önerilmiştir. Görev çizelgelemeye ek olarak önbelleklerin kullanımı da performans ve güç tüketimi açısından kritik bir öneme sahiptir. Literatürdeki ilgili çalışmalar, önbellek kullanımını etkin kılmayı genellikle donanım ya da derleme seviyesinde hedeflemişlerdir. Önbellek davranışlarının Görev seviyesinde optimize edilmesinin hedeflenmesi iyi bir katkı olabilir. Çalışmamızda öncelikle veriye bağımlılıkları ve tekrar veri kullanımını göz önüne alarak oluşturduğumuz yersellik bilinçli modeli tanıtıyoruz. Daha sonra bu modeli temel alarak Yersellik-Bilinçli Heterojen Erken Bitiş Zamanı (LHEFT) ve Melez Genetik Algoritma (HGA) olarak iki algoritma öneriyoruz. Önerilen algoritmaların performansları, sentetik olarak oluşturulmuş görev çizgeleri kullanılarak literatürde önde gelen üç algoritma ile karşılaştırıldı. Bu çalışmamızda sunduğumuz karşılaştırma çalışmasına göre melez genetik algoritmamız tüm performans göstergelerinde diğer tüm ilgili çalışmalardan daha iyi sonuç göstermiştir.
Anahtar Kelimeler: Görev Çizelgeleme, Heterojen Hesaplama Ortamları, Yersellik, Heuristik, Genetik Algoritmalar
ABSTRACT
LOCALITY AWARE TASK SCHEDULING IN HETEROGENEOUS COMPUTING ENVIRONMENTS
Efficient task scheduling in heterogeneous computing environments is an NP-complete problem and there are many algorithms proposed in the literature so far to solve various types of the general task scheduling problem. In addition to task scheduling decisions, utilizing caches is also critical for both performance and power perspectives. Related work in the literature usually target for optimizing caches at hardware level or compilation level. Targeting task level optimizations for cache behaviors could be good asset and it can be performed at application level. In this study, we first present a locality aware task scheduling model by considering data dependencies and data reuses between tasks. Additionally two locality aware task scheduling heuristics are proposed in this thesis based on the proposed model, which are Locality-aware Heterogeneous Earliest Finish Time (LHEFT) algorithm and a Hybrid Genetic Algorithm (HGA). The performance of the proposed algorithms is compared with the three leading scheduling algorithms in the literature by using synthetically generated task graphs. According to comparative study presented in this study, our hybrid genetic algorithm outperforms the related work with respect to all performance metrics considered in this study.
Keywords: Task Scheduling, Heterogeneous Computing Environment, Locality, Heuristics, Genetic Algorithm
Differential Entropy of the Conditional Expectation under Gaussian Noise
The conditional mean is a fundamental and important quantity whose
applications include the theories of estimation and rate-distortion. It is also
notoriously difficult to work with. This paper establishes novel bounds on the
differential entropy of the conditional mean in the case of finite-variance
input signals and additive Gaussian noise. The main result is a new lower bound
in terms of the differential entropies of the input signal and the noisy
observation. The main results are also extended to the vector Gaussian channel
and to the natural exponential family. Various other properties such as upper
bounds, asymptotics, Taylor series expansion, and connection to Fisher
Information are obtained. Two applications of the lower bound in the
remote-source coding and CEO problem are discussed.Comment: Partially presented at the 2021 IEEE Information Theory Workshop,
Japa
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