Look for web articles/posts about how mathematics is used in specific areas. Summarize the contents of the web articles/posts in at least seven (7) sentences each. The first letter of your last name will be the basis of your assigned areas.
Technology
Engineering
Medicine/Health
Finance/Business
Last Names Areas of Applications
A-E 1 and 4
F-J 2 and 3
K-O 1 and 3
P-S 2 and 4
T-Z 3 and 4
Answer (1)
Answer:Assigned areas (based on last name initial N → group K–O): Technology and Medicine/Health.Below are two web-article summaries (each ≥7 sentences). I cited the main sources after key statements.Mathematics in Technology — summaryMathematics is the foundation of modern technology: linear algebra, calculus, probability, and optimization underlie machine learning, data science, and many algorithms that power apps and services today. Computer vision, natural language processing, and recommendation systems all depend on vector spaces and matrix operations to represent and transform data (for example, converting images or words into high-dimensional numerical vectors used by models). Probability and statistics are essential for model evaluation, uncertainty estimation, and safe deployment—engineers use statistical tests and metrics to decide whether a model is accurate or biased. Optimization (finding minima/maxima of cost functions) is what actually trains neural networks and tunes many other algorithms; advances in optimization theory directly improve training speed and model performance. Cryptography and cybersecurity rely on number theory and algebraic structures (e.g., modular arithmetic, prime factorization) to secure communications and protect data. Beyond AI, applied mathematics helps design physical systems—engineers use differential equations and numerical methods to simulate structures, fluid flows, and material behavior in civil, mechanical, and environmental technology. Finally, there is a two-way relationship: while technology (computers, ML) uses math, it also provides tools that let mathematicians explore new problems and create faster algorithms, accelerating both fields. Key sources: GeeksforGeeks on ML math; Nautilus/Caltech pieces on ML mathematics and the two-way street between math and ML; SINTEF on applied math in engineering; Google/WSJ description of transformer math. Mathematics in Medicine/Health — summaryMathematics underpins diagnostic imaging, epidemiology, clinical trials, and many routine clinical calculations; for example, the math behind CT and MRI image reconstruction (inverse problems) is essential to produce usable images from raw sensor data. Statistical methods and probability theory are at the heart of medical research: they are used to design trials, compute sample sizes, evaluate treatment effectiveness, and decide whether observed effects are statistically significant. Mathematical models (differential equations, agent-based models) simulate disease spread, predict outcomes, and help public-health officials plan interventions—models were central to pandemic forecasting and resource planning. Clinicians and allied health professionals use arithmetic and algebra in daily practice too (dosage calculations, flow rates for respiratory therapy, body-surface area dosing), so basic numeracy directly affects patient safety. Advanced analytics (biostatistics, bioinformatics) extract insights from genomic and clinical data; machine learning methods help detect patterns for diagnosis or to personalize treatments, but these approaches still require careful mathematical validation and interpretation. Finally, expository and research articles emphasize that collaboration between mathematicians, statisticians, clinicians, and engineers leads to medical advances—mathematics often converts messy biological questions into clear, testable models that improve decision making and patient care. Key sources: PMC/NCBI expository article on math in medical imaging and medicine; research on mathematical modeling in medical research; article on daily clinical math (dosages, respiratory therapy); journals on applied medical/bio math.
