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Articles 361 - 390 of 5281
Full-Text Articles in Entire DC Network
Topological Indices And Qspr/Qsar Analysis Of Some Drugs Being Investigated For The Treatment Of Alzheimer's Disease Patients, Mohammed Yasin H, Suresh M, Jalal Hatem Hussein Bayati
Topological Indices And Qspr/Qsar Analysis Of Some Drugs Being Investigated For The Treatment Of Alzheimer's Disease Patients, Mohammed Yasin H, Suresh M, Jalal Hatem Hussein Bayati
Baghdad Science Journal
The quantitative structure-property/activity relationships (QSAR/QSPR) analysis are important for the several properties of estimating/predicting drug-related activities, particularly in the context of the drugs used for the treatment of Alzheimer’s disease. This study uses innovative methods, such as the utilization of -degree and -degree-based topological indices, to evaluate the physicochemical features and attributes of five medications used for the treat Alzheimer’s disease: Tacrine, Donepezil, Rivastigmine, Galantamine and Huperzine A. By reducing the number of descriptors and improving their correlation with a variety of molecular properties, these topological indices provide a unique method for capturing critical molecular structural information. The main objective …
Analysing The Performance Of M/M(A,B)/1/ Mwv Queuing Model With The Busy Period Breakdown, Lidiya P, K Julia Rose Mary
Analysing The Performance Of M/M(A,B)/1/ Mwv Queuing Model With The Busy Period Breakdown, Lidiya P, K Julia Rose Mary
Baghdad Science Journal
This paper aims to analyze the M/M(a,b)/1 multiple working vacations queuing model with a breakdown. Instead of the server being fully idle during the vacation period, the server serves at a different rate during multiple working vacations. The system has only one server, and the service rate varies depending on the arrival state. Customers’ enter the system to get service with parameter λ_v following the Poisson distribution. The server provides service for customers’ in regular busy periods with parameter μ and under multiple working vacations, the server provides service with parameter μ_v with the exponential distribution. In this model, batches …
K –Mixed Modulus Of Smoothness, Rehab Amer Kamel, Eman Samir Bhaya
K –Mixed Modulus Of Smoothness, Rehab Amer Kamel, Eman Samir Bhaya
Baghdad Science Journal
The modulus of smoothness is essential for modern analysis and its applications. Is a versatile tool in approximation theory that helps in understanding the properties of approximation methods, characterizing function spaces, and analyzing the convergence and accuracy of numerical algorithms. It helps in determining the optimal number of terms or the optimal choice of basic functions to achieve the desired level of accuracy in approximation of a function and rate of convergence. The smoothness modulus has many applications, including its applications in numerical analysis, particularly in the analysis of numerical methods for solving differential equations, optimization problems, and integral equations. …
See, Anchor, And Frame Math With Coding, Beverly Sanders, Brittany Wall, Debi Alexander, Jessica Shumway
See, Anchor, And Frame Math With Coding, Beverly Sanders, Brittany Wall, Debi Alexander, Jessica Shumway
Publications
In this presentation, we will share our experiences with integrating mathematics and programming in fifth-grade classrooms. We approached this integration with three key features in our lessons: visualization of important math concepts, anchor ideas that cross coding and math, and the framing of content to help students make connections. We will share our exponents, fractions, and geometry lessons and show how we used coding to provide students with meaningful spaces to engage with interactive contexts to broaden their mathematics conceptions.
Infographic: Who’S Studying Stem?, Andrew Broadley
Infographic: Who’S Studying Stem?, Andrew Broadley
Teacher infographics
Thinking about your own school context, is there a gender imbalance in STEM-related subjects? How do you encourage girls to consider taking STEM subjects? In this infographic, we look at gender inequality in students entering tertiary education in a STEM field.
Mathematics In Everyday Life: Exploring Practical Applications And Real-World Impact, Priyant Banerjee, Arshad Bhat
Mathematics In Everyday Life: Exploring Practical Applications And Real-World Impact, Priyant Banerjee, Arshad Bhat
Himalayan Research Papers Archive
Mathematics is an essential part of daily life and influences decisions and problem-solving in various aspects of life. This study explores how mathematical concepts are embedded in daily activities such as financial management, cooking, travel planning, and technological interactions. We will show how arithmetic, algebra, geometry, and statistics are applied in real life to improve decision-making, efficiency, and productivity. Findings indicate that people with higher mathematical literacy solve problems more efficiently, especially in budgeting, as accurate calculations minimize financial mistakes and facilitate long-term financial planning. In cooking, proportional reasoning ensures the accuracy of recipes, thus providing consistent culinary results. Travel …
Math 341-002: Stats Methods I, K. Carfora
Math 341-002: Stats Methods I, K. Carfora
Mathematical Sciences Syllabi
No abstract provided.
Math 745-002: Mathematical Analysis Ii, A. Bose
Math 745-002: Mathematical Analysis Ii, A. Bose
Mathematical Sciences Syllabi
No abstract provided.
Math 110: University Mathematics B Ii, D. Schmidt
Math 110: University Mathematics B Ii, D. Schmidt
Mathematical Sciences Syllabi
No abstract provided.
Math 656-002: Complex Variables I, A. Sagiv
Math 656-002: Complex Variables I, A. Sagiv
Mathematical Sciences Syllabi
No abstract provided.
Math 105-020: Elem Probability & Statistics, K. Horwitz
Math 105-020: Elem Probability & Statistics, K. Horwitz
Mathematical Sciences Syllabi
No abstract provided.
Math 665-102: Statistical Inference, S. Subramanian
Math 665-102: Statistical Inference, S. Subramanian
Mathematical Sciences Syllabi
No abstract provided.
Math 138-102: General Calculus I, J. Ro
Math 138-102: General Calculus I, J. Ro
Mathematical Sciences Syllabi
No abstract provided.
Math 699-102: Des & Analy Experiments, C. Shi
Math 699-102: Des & Analy Experiments, C. Shi
Mathematical Sciences Syllabi
No abstract provided.
Math 341-004: Stats Methods I, J. Porus
Math 341-004: Stats Methods I, J. Porus
Mathematical Sciences Syllabi
No abstract provided.
Math 689-002: Adv Applied Math Ii, M. Booty
Math 689-002: Adv Applied Math Ii, M. Booty
Mathematical Sciences Syllabi
No abstract provided.
Math 279-002 Jamedar: Stats & Probabilty For Engr, F. Jamedar
Math 279-002 Jamedar: Stats & Probabilty For Engr, F. Jamedar
Mathematical Sciences Syllabi
No abstract provided.
Math 328-002: Math Methods For Sci & Engr, W. Choi
Math 328-002: Math Methods For Sci & Engr, W. Choi
Mathematical Sciences Syllabi
No abstract provided.
Math 105-022: Elem Probability & Statistics, C. Kim
Math 105-022: Elem Probability & Statistics, C. Kim
Mathematical Sciences Syllabi
No abstract provided.
Math 112: Calculus Ii, J. Bechtold
Math 112: Calculus Ii, J. Bechtold
Mathematical Sciences Syllabi
No abstract provided.
Math 105-002: Elem Probability & Statistics, S. Carter
Math 105-002: Elem Probability & Statistics, S. Carter
Mathematical Sciences Syllabi
No abstract provided.
Math 661-106: Applied Statistics, P. Natarajan
Math 661-106: Applied Statistics, P. Natarajan
Mathematical Sciences Syllabi
No abstract provided.
Math 337: Linear Algebra, J. Luke
Math 478-002: Stat Methods In Data Sci, Z. Shang
Math 478-002: Stat Methods In Data Sci, Z. Shang
Mathematical Sciences Syllabi
No abstract provided.
Math 791-002: Graduate Seminar, R. Goodman
Math 791-002: Graduate Seminar, R. Goodman
Mathematical Sciences Syllabi
No abstract provided.
Math 238-102: General Calculus Ii, M. Hercules-Mejivar
Math 238-102: General Calculus Ii, M. Hercules-Mejivar
Mathematical Sciences Syllabi
No abstract provided.
Math 105-014: Elem Probability & Statistics, K. Horwitz
Math 105-014: Elem Probability & Statistics, K. Horwitz
Mathematical Sciences Syllabi
No abstract provided.
Math 322-006: Diff Eqns For Tech, P. Milojevic
Math 322-006: Diff Eqns For Tech, P. Milojevic
Mathematical Sciences Syllabi
No abstract provided.
Math 309-002: Math Analysis For Tech, I. Cohanoschi
Math 309-002: Math Analysis For Tech, I. Cohanoschi
Mathematical Sciences Syllabi
No abstract provided.
Math 373-002: Intro To Mathematical Biology, J. Maclaurin
Math 373-002: Intro To Mathematical Biology, J. Maclaurin
Mathematical Sciences Syllabi
No abstract provided.