باسم صالح عمران الصاعدي

الخبرات والمناصب الإدارية

أستاذ مساعد في قسم الاحصاء
أستاذ مشارك - في قسم الإحصاء

المؤهلات العلمية

دكتوراه في الأحصاء
ماجستير في الاحصاء
ماجستير في العلوم الرياضية
بكالوريس في الرياضيات

الاهتمامات البحثية

Cancer Research

MRI Imaging

Bayesian Statistics

اليوم	المادة	الوقت
الأحد	STAT 262	12:00 - 14:00
الأحد	MATH325	14:00 - 15:30
الإثنين	STAT1201	12:00 - 14:00
الثلاثاء	STAT 262	12:00 - 14:00
الأربعاء	STAT1201	12:00 - 14:00

Sirohi, Anu, et al "Biased proportional hazard regression estimator in the existence of collinearity" Heliyon 911 (2023)
Almassabi, Rehab F, et al "Differential Expression of Serum Proinflammatory Cytokine TNF-α and Genetic Determinants of TNF-α, CYP2C19* 17, miR-423 Genes and Their Effect on Coronary Artery Disease Predisposition and Progression" Life 1311 (2023): 2142
Elangeeb, M E, et al "In Silico Investigation of AKT2 Gene and Protein Abnormalities Reveals Potential Association with Insulin Resistance and Type 2 Diabetes" Current Issues in Molecular Biology 459 (2023): 7449-7475
Mir, Rashid, et al "Comprehensive Molecular Evaluation of HNF-1 Alpha, miR-27a, and miR-146 Gene Variants and Their Link with Predisposition and Progression in Type 2 Diabetes Patients" Journal of Personalized Medicine 138 (2023): 1270
Jalal, Mohammed M, et al "Association of Genetic and Allelic Variants of Von Willebrand Factor (VWF), Glutathione S-Transferase and Tumor Necrosis Factor Alpha with Ischemic Stroke Susceptibility and Progression in the Saudi Population" Life 135 (2023): 1200
Ogbonnaya, Chidozie N, et al "Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer" Journal of Clinical Medicine 127 (2023): 2605
Alsaedi, Basim SO, et al "A sustainable green supply chain model with carbon emissions for defective items under learning in a fuzzy environment" Mathematics 112 (2023): 301
Alshomrani, Faisal, et al "Radiomics Approach to the Detection of Prostate Cancer Using Multiparametric MRI: A Validation Study Using Prostate-Cancer-Tissue-Mimicking Phantoms" Applied Sciences 131 (2022): 576

اسم المشروع	وصف المشروع
A Sustainable Green Supply Chain Model with Carbon Emissions for Defective Items under Learning in a Fuzzy Environment	Assuming the significance of sustainability, it is considered necessary to ensure the conservation of our natural resources, in addition to minimizing waste To promote significant sustainable effects, factors including production, transportation, energy usage, product control management, etc, act as the chief supports of any modern supply chain model The buyer performs the firsthand inspection and returns any defective items received from the customer to the vendor in a process that is known as first-level inspection The vendor uses the policy of recovery product management to obtain greater profit A concluding inspection is accomplished at the vendor’s end in order to distinguish the returned item as belonging to one of four specific categories, namely re-workable, reusable, recyclable, and disposable, a process that is known as second-level inspection Then, it is observed that some defective items are suitable for a secondary market, while some are reusable, and some can be disassembled to shape new derived products, and leftovers can be scrapped at the disposal cost This ensures that we can meet our target to promote a cleaner drive with a lower percentage of carbon emissions, reducing the adverse effects of landfills The activity of both players in this model is presented briefly in the flowchart shown in the abstract Thus, our aim of product restoration is to promote best practices while maintaining economic value, with the ultimate goal of removing the surrounding waste with minimum financial costs In this regard, it is assumed that the demand rate is precise in nature The learning effect and fuzzy environment are also considered in the present model The proposed model studies the impacts of learning and carbon emissions on an integrated green supply chain model for defective items in fuzzy environment and shortage conditions We optimized the integrated total fuzzy profit with respect to the order quantity and shortages We described the vendor’s strategy and buyer’s strategy through flowcharts for the proposed integrated supply chain model, and here, in the flowchart, R-R-R stands for re-workable, reusable, and recyclable The demand rate was treated as a triangular fuzzy number In this paper, a numerical example, sensitivity analysis, limitations, future scope, and conclusion are presented for the validation of the proposed model

اسم المشروع

وصف المشروع

A Sustainable Green Supply Chain Model with Carbon Emissions for Defective Items under Learning in a Fuzzy Environment

Assuming the significance of sustainability, it is considered necessary to ensure the conservation of our natural resources, in addition to minimizing waste To promote significant sustainable effects, factors including production, transportation, energy usage, product control management, etc, act as the chief supports of any modern supply chain model The buyer performs the firsthand inspection and returns any defective items received from the customer to the vendor in a process that is known as first-level inspection The vendor uses the policy of recovery product management to obtain greater profit A concluding inspection is accomplished at the vendor’s end in order to distinguish the returned item as belonging to one of four specific categories, namely re-workable, reusable, recyclable, and disposable, a process that is known as second-level inspection Then, it is observed that some defective items are suitable for a secondary market, while some are reusable, and some can be disassembled to shape new derived products, and leftovers can be scrapped at the disposal cost This ensures that we can meet our target to promote a cleaner drive with a lower percentage of carbon emissions, reducing the adverse effects of landfills The activity of both players in this model is presented briefly in the flowchart shown in the abstract Thus, our aim of product restoration is to promote best practices while maintaining economic value, with the ultimate goal of removing the surrounding waste with minimum financial costs In this regard, it is assumed that the demand rate is precise in nature The learning effect and fuzzy environment are also considered in the present model The proposed model studies the impacts of learning and carbon emissions on an integrated green supply chain model for defective items in fuzzy environment and shortage conditions We optimized the integrated total fuzzy profit with respect to the order quantity and shortages We described the vendor’s strategy and buyer’s strategy through flowcharts for the proposed integrated supply chain model, and here, in the flowchart, R-R-R stands for re-workable, reusable, and recyclable The demand rate was treated as a triangular fuzzy number In this paper, a numerical example, sensitivity analysis, limitations, future scope, and conclusion are presented for the validation of the proposed model

جائزة التميز البحثي من الجمعية الأسترالية

balsaedi@UT.EDU.SA

باسم صالح عمران الصاعدي

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