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Article: Evaluation of the synthetic estimators with non-respondent for small domain.

Alomair, Abdullah Mohammed / Ashutosh, Ashutosh

2024 Volume 10, Issue 8, Page(s) e29592

Abstract: The present work gives generalized form of the class of estimators if unit non-response is acquired in small domains. We have obtained indirect method like synthetic. It has provided specific instances where the proposed estimators are unbiased. It has ... ...

Abstract	The present work gives generalized form of the class of estimators if unit non-response is acquired in small domains. We have obtained indirect method like synthetic. It has provided specific instances where the proposed estimators are unbiased. It has also given a generalized form of the synthetic estimators. The four estimators were investigated with coefficient of variation and kurtosis constants. Because, these are obtained from the available variable. We conducted atheoretical comparison between traditional and proposed calibration estimators for estimating the domain totals. It found that the proposed estimators are more efficient than traditional estimators for investigate small domains.
Language	English
Publishing date	2024-04-15
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e29592
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Compromise optimum allocation in neutrosophic multi-character survey under stratified random sampling using neutrosophic fuzzy programming.

Ullah, Atta / Shabbir, Javid / Alomair, Abdullah Mohammed / Alarfaj, Fawaz Khaled

Heliyon

2024 Volume 10, Issue 7, Page(s) e28327

Abstract: Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number ... ...

Abstract	Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS.
Language	English
Publishing date	2024-03-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e28327
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Article: Antibiogram data of urinary tract infection in spinal cord injury patients in an outpatient setting.

Alshahri, Saeed / Alghaiheb, Abdullah / Alanazi, Abdullah / Alshammari, Sultanah / Alomair, Abdullah

Neurosciences (Riyadh, Saudi Arabia)

2024 Volume 29, Issue 1, Page(s) 57–62

Abstract: Objectives: To establish antibiogram data for patients with spinal cord injury (SCI) that would help differentiate the organisms commonly present depending on the voiding method and antibiotic sensitivity for empirical treatment.: Methods: A total of ...

Abstract	Objectives: To establish antibiogram data for patients with spinal cord injury (SCI) that would help differentiate the organisms commonly present depending on the voiding method and antibiotic sensitivity for empirical treatment. Methods: A total of 499 urine culture results were obtained from 151 SCI patients with symptomatic urinary tract infection (UTI) with significant bacteriuria and pyuria with more than 10 white blood cells per high power field. The voiding method was categorized as follows: self-intermittent catheterization (SIC), suprapubic catheter (SPC), Foley catheter, condom catheter, or voiding freely. Results: The demographic data were as follows: male, n=124 (82.2%); female, n=27 (17.8%); mean age, 39; paraplegic n=105 (69.5%); and tetraplegic, n=45 (29.8%). The SIC was the most common voiding method (n=64, 42.3%), followed by Foley catheter (n=39, 25.8%). Escherichia coli was the most common organism overall (29%) and more frequent in patients using SIC as the voiding method. Conclusion: Increased preference of the local population to foley catheter as a voiding method which needs to be investigated more. The type of voiding methods in patients with SCI results in different common causative organisms of UTI. Ciprofloxacin resistance profile increased overall except in patients voiding with SPC. Nitrofurantoin is the most overall sensitive oral antibiotic in our sample followed by Augmentin then Cefuroxime.
MeSH term(s)	Humans ; Female ; Male ; Adult ; Outpatients ; Nitrofurantoin ; Amoxicillin-Potassium Clavulanate Combination ; Urinary Tract Infections/drug therapy ; Urinary Tract Infections/epidemiology ; Spinal Cord Injuries/complications ; Ciprofloxacin ; Anti-Bacterial Agents/therapeutic use
Chemical Substances	Nitrofurantoin (927AH8112L) ; Amoxicillin-Potassium Clavulanate Combination (74469-00-4) ; Ciprofloxacin (5E8K9I0O4U) ; Anti-Bacterial Agents
Language	English
Publishing date	2024-01-07
Publishing country	Saudi Arabia
Document type	Journal Article
ZDB-ID	2214806-1
ISSN	1319-6138
ISSN	1319-6138
DOI	10.17712/nsj.2024.1.20230063
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Article: Enhanced exponential ratio-cum-ratio estimator in ranked set sampling using transformed auxiliary information.

Khan, Lakhkar / Ahmad, Sohaib / Alomair, Abdullah Mohammed / Alomair, Mohammed Ahmed

Heliyon

2024 Volume 10, Issue 6, Page(s) e27522

Abstract: Estimation of population mean is a determined subject issue in sampling surveys and many efforts have been paid by various researchers to enhance the precision of the estimates by utilizing the correlated auxiliary information. In connection with this, ... ...

Abstract	Estimation of population mean is a determined subject issue in sampling surveys and many efforts have been paid by various researchers to enhance the precision of the estimates by utilizing the correlated auxiliary information. In connection with this, we suggest an improved exponential ratio-cum-ratio estimator using transformed auxiliary variables under ranked set sampling scheme. Theoretical comparison between estimators is made in terms of mean square errors (
Language	English
Publishing date	2024-03-07
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e27522
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Article ; Online: A new extension of Poisson distribution for asymmetric count data: theory, classical and Bayesian estimation with application to lifetime data.

Alomair, Abdullah / Ahsan-Ul-Haq, Muhammad

PeerJ. Computer science

2023 Volume 9, Page(s) e1748

Abstract: Several research investigations have stressed the importance of discrete data analysis and its relevance to actual events. The current work focuses on a new discrete distribution with a single parameter that can be derived using the Poisson mixing ... ...

Abstract	Several research investigations have stressed the importance of discrete data analysis and its relevance to actual events. The current work focuses on a new discrete distribution with a single parameter that can be derived using the Poisson mixing technique. The new distribution is named the Poisson Entropy-Based Weighted Exponential Distribution. It is useful for discussing asymmetric "right-skewed" data with "heavy" tails. Its failure rate function can be used to explain situations with increasing failure rates. The statistical properties of the new distribution are expressed explicitly. The proposed model is simple to manage for under-, equal-, and over-dispersed datasets. The model parameters are estimated using the maximum likelihood method. We consider the parameter estimation for the new model based on right-censored data with a cure fraction. One more focus of the present study is the Bayesian estimation of the model parameters. In the end, three real-world dataset examples were utilized to show the value of the new distribution. These applications revealed that the new model outperforms other standard discrete models.
Language	English
Publishing date	2023-12-15
Publishing country	United States
Document type	Journal Article
ISSN	2376-5992
ISSN (online)	2376-5992
DOI	10.7717/peerj-cs.1748
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Article: An exponentiated XLindley distribution with properties, inference and applications.

Alomair, Abdullah M / Ahmed, Mukhtar / Tariq, Saadia / Ahsan-Ul-Haq, Muhammad / Talib, Junaid

Heliyon

2024 Volume 10, Issue 3, Page(s) e25472

Abstract: In this paper, we propose exponentiated XLindley (EXL) distribution. The novel model is adaptable due to the mixt shapes of its density and failure rate functions. The following key statistical properties of EXL distribution are derived: quantile ... ...

Abstract	In this paper, we propose exponentiated XLindley (EXL) distribution. The novel model is adaptable due to the mixt shapes of its density and failure rate functions. The following key statistical properties of EXL distribution are derived: quantile function, moments, hazard function, mean residual life, and Rényi entropy. The parameters are estimated using the maximum likelihood, Anderson Darling, Cramer von Misses, maximum product spacing, ordinary and weighted least square estimation procedures. To examine the behavior of the estimate, Monte Carlo simulation is used. Further Bayesian technique is also utilized to estimate the EXL parameters. The traceplot and Geweke diagnostics are used to track the convergence of simulated processes. The applicability of the EXL distribution is demonstrated by three datasets from different domains such as mortality rate due to COVID-19, precipitation in inches, and failure time for repairable items. The proposed distribution provides efficient results as compared to renowned competitive distributions.
Language	English
Publishing date	2024-01-29
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e25472
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Article: Classical and Bayesian inference for the new four-parameter Lomax distribution with applications.

Abdullah, Mahreen / Ahsan-Ul-Haq, Muhammad / Alomair, Abdullah M / Alomair, Mohammed A

Heliyon

2024 Volume 10, Issue 4, Page(s) e25842

Abstract: In this study, a new four-parameter Lomax distribution is proposed using a new alpha power transformation technique. The new distribution is named "New Alpha Power Transformed Power Lomax Distribution." Mathematical properties, including moments, the ... ...

Abstract	In this study, a new four-parameter Lomax distribution is proposed using a new alpha power transformation technique. The new distribution is named "New Alpha Power Transformed Power Lomax Distribution." Mathematical properties, including moments, the moment-generating function, the mean residual life, order statistics, and the quantile function, are obtained. The maximum likelihood estimation approach is used to estimate the model parameters. A comprehensive simulation is used to evaluate the behavior of maximum likelihood estimators. Two real-world data sets were used to demonstrate the significance of the proposed model, and the results show that the new model performs better when interpreting lifetime data sets. In the end, for the data sets, Bayesian estimation and Metropolis-Hasting's approach were also utilized to construct the approximate Bayes estimates, and convergence diagnostic methods based on Markov Chain Monte Carlo techniques were applied.
Language	English
Publishing date	2024-02-05
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e25842
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Article: A new modification of the flexible Weibull distribution based on power transformation: Monte Carlo simulation and applications.

Khan, Faridoon / Ahmad, Zubair / Khosa, Saima K / Alomair, Mohammed Ahmed / Alomair, Abdullah Mohammed / Alsharidi, Abdulaziz Khalid

Heliyon

2023 Volume 9, Issue 6, Page(s) e17238

Abstract: Statistical modeling is a crucial phase for decision-making and predicting future events. Data arising from engineering-related fields have most often complex structures whose failure rate possesses mixed state behaviors (i.e., non-monotonic shapes). For ...

Abstract	Statistical modeling is a crucial phase for decision-making and predicting future events. Data arising from engineering-related fields have most often complex structures whose failure rate possesses mixed state behaviors (i.e., non-monotonic shapes). For the data sets whose failure rates are in the mixed state, the utilization of the traditional probability models is not a suitable choice. Therefore, searching for more flexible probability models that are capable of adequately describing the mixed state failure data sets is an interesting research topic for researchers. In this paper, we propose and study a new statistical model to achieve the above goal. The proposed model is called a new beta power very flexible Weibull distribution and is capable of capturing five different patterns of the failure rate such as uni-modal, decreasing-increasing-decreasing, bathtub, decreasing, increasing-decreasing-increasing shapes. The estimators of the new beta power very flexible Weibull distribution are obtained using the maximum likelihood method. The evaluation of the estimators is assessed by conducting a simulation study. Finally, the usefulness and applicability of the new beta power very flexible Weibull distribution are shown by analyzing two engineering data sets. Using four information criteria, it is observed that the new beta power very flexible Weibull distribution is the best-suited model for dealing with failure times data sets.
Language	English
Publishing date	2023-06-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e17238
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Article ; Online: On solving textual ambiguities and semantic vagueness in MRC based question answering using generative pre-trained transformers.

Ahmed, Muzamil / Khan, Hikmat / Iqbal, Tassawar / Khaled Alarfaj, Fawaz / Alomair, Abdullah / Almusallam, Naif

PeerJ. Computer science

2023 Volume 9, Page(s) e1422

Abstract: Machine reading comprehension (MRC) is one of the most challenging tasks and active fields in natural language processing (NLP). MRC systems aim to enable a machine to understand a given context in natural language and to answer a series of questions ... ...

Abstract	Machine reading comprehension (MRC) is one of the most challenging tasks and active fields in natural language processing (NLP). MRC systems aim to enable a machine to understand a given context in natural language and to answer a series of questions about it. With the advent of bi-directional deep learning algorithms and large-scale datasets, MRC achieved improved results. However, these models are still suffering from two research issues: textual ambiguities and semantic vagueness to comprehend the long passages and generate answers for abstractive MRC systems. To address these issues, this paper proposes a novel Extended Generative Pretrained Transformers-based Question Answering (ExtGPT-QA) model to generate precise and relevant answers to questions about a given context. The proposed architecture comprises two modified forms of encoder and decoder as compared to GPT. The encoder uses a positional encoder to assign a unique representation with each word in the sentence for reference to address the textual ambiguities. Subsequently, the decoder module involves a multi-head attention mechanism along with affine and aggregation layers to mitigate semantic vagueness with MRC systems. Additionally, we applied syntax and semantic feature engineering techniques to enhance the effectiveness of the proposed model. To validate the proposed model's effectiveness, a comprehensive empirical analysis is carried out using three benchmark datasets including SQuAD, Wiki-QA, and News-QA. The results of the proposed ExtGPT-QA outperformed state of art MRC techniques and obtained 93.25% and 90.52% F1-score and exact match, respectively. The results confirm the effectiveness of the ExtGPT-QA model to address textual ambiguities and semantic vagueness issues in MRC systems.
Language	English
Publishing date	2023-07-24
Publishing country	United States
Document type	Journal Article
ISSN	2376-5992
ISSN (online)	2376-5992
DOI	10.7717/peerj-cs.1422
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Tobacco consumption and environmental exposure among healthcare students in King Saud University in Riyadh.

Amin, Hussein S / Alomair, Abdullah N / Alhammad, Abdulaziz H / Altwijri, Faisal A / Altaweel, Abdulaziz A / Alandejani, Tawfeq A

Journal of family medicine and primary care

2020 Volume 9, Issue 2, Page(s) 657–663

Abstract: Objectives: The goal of this study was to determine the prevalence of tobacco smoking in healthcare students at a university in Riyadh, Saudi Arabia, along with environmental exposure and potential influential factors.: Methods: This observational ... ...

Abstract	Objectives: The goal of this study was to determine the prevalence of tobacco smoking in healthcare students at a university in Riyadh, Saudi Arabia, along with environmental exposure and potential influential factors. Methods: This observational cross-sectional study was conducted at King Saud University from January-April 2019. It included 1,273 randomly selected male and female first- to fifth-year undergraduate healthcare students from all health colleges at the university. The study used a self-administrated questionnaire and descriptive data analysis. Associations between variables were tested using a Chi-square test with the statistical significance set at Results: Among the 1,273 respondents, the prevalence of tobacco product smoking was 13.7%. The prevalence was highest in the College of Applied Science (34.5%) and lowest in the College of Pharmacy (10.9%). Among those 18- to 21-year-olds, the prevalence was 43.1%, while it was 51.1% for the 22-25 age group and only 5.8% for those 26 or older. Common reasons for smoking cigarettes included having fun or passing time (45.2%) and relieving stress (33.3%). Among those who smoked a water-pipe (12.5%), the most common reason was to enjoy its flavors (42.1%). The prevalence of secondhand smoking at home was 31.7%, and environmental exposure was 42.5%. Conclusion: Tobacco consumption is a common problem among healthcare students including cigarette as well as the increasing consumption of water-pipe in addition to secondhand smoking. Along with proven strategies to promote smoking cessation, including smoke-free laws, improved access to effective quitting treatments and media campaigns are needed to reduce tobacco consumption.
Language	English
Publishing date	2020-02-28
Publishing country	India
Document type	Journal Article
ZDB-ID	2735275-4
ISSN	2278-7135 ; 2249-4863
ISSN (online)	2278-7135
ISSN	2249-4863
DOI	10.4103/jfmpc.jfmpc_1217_19
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