№ lp_1_2_30388
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The document reviews current data science applications in demand forecasting and inventory management, highlighting challenges and future research directions for supply chain transformation.
Year:
2023
Region / City:
Not specified
Topic:
Demand forecasting, inventory management, machine learning, supply chain optimization
Document Type:
Review paper
Author:
Not specified
Target Audience:
Researchers, supply chain practitioners
Period of Action:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Price: 8 / 10 USD
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Year:
2024
Region / City:
United States
Topic:
Veterans Affairs, Criminal Justice
Document Type:
Webinar Transcript
Organization:
Bureau of Justice Assistance
Author:
Scott Tirocchi, Katherine Stewart
Target Audience:
Criminal Justice Professionals, Veterans Affairs Specialists
Date Approved:
July 25, 2024
Date of Changes:
N/A
Year:
2023
Region / City:
Texas, USA
Topic:
Healthcare Data Integration, OMOP CDM, Epic ETL
Document Type:
Research Paper
Organization / Institution:
University of Texas Southwestern Medical Center, Texas Health Resources
Authors:
Aamirah Vadsariya, Mereeja Varghese, Bhavini Nayee, Jessica Moon, Chaitanya Katterapalli, Clark Walker, Chris Gonzalez, Sonam Sohal, Christoph U. Lehmann, Ferdinand Velasco, Mujeeb Basit, DuWayne Willett
Target Audience:
Healthcare professionals, researchers in healthcare data systems
Period of Action:
2023
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2023
Region / City:
United States
Topic:
Workforce Development, AI, Financial Literacy, Employee Well-being
Document Type:
Research Paper
Organization / Institution:
Unknown
Author:
Ahlheit, Gill
Target Audience:
Organizational Leaders, HR Professionals, Employees
Period of Validity:
Ongoing
Approval Date:
2023-05-10
Modification Date:
N/A
Year:
2026
Organization:
J&J; Lumanity
Speakers:
Damian Eade, Kristina Ogneva, Mattias Blomgren
Topic:
Synthetic Research; Market Segmentation; Generative AI Applications
Document Type:
Conference Paper / Case Study
Target Audience:
Market Researchers; Sales Teams; AI Practitioners
Key Challenges:
Underutilized research outputs, balancing accuracy and authenticity, human-first technology adoption
Methods:
Development of synthetic personas, phased proof-of-concept, iterative testing and user feedback
Applications:
Customer engagement, business decision support, sales force enablement
Context:
Market research within a large disease area requiring actionable segmentation
Key Learnings:
Managing calculated risks, prioritizing authenticity, human-centered technology deployment
Date Presented:
2026
Year:
2020
Organization:
NASA Goddard Space Flight Center
Authors:
Yen Wong, Scott Schaire, Chitra Patel, Leslie Ambrose, Obadiah Kegege, Denise Thorsen
Location:
Greenbelt, MD, USA; Fairbanks, AK, USA
Document type:
Conference paper
Field:
Space communications, Small satellite technology
Target audience:
Space mission planners, satellite engineers
Period of applicability:
Near-Earth missions up to 2030
Communication technologies discussed:
DVB-S2, Variable Coding and Modulation (VCM), X-band and Ka-band radios
Collaborating institutions:
University of Alaska Fairbanks
Commercial service providers mentioned:
Amazon Web Service Ground Station (AGS), KSATLITE
Year:
2023
Region / Institution:
Unspecified medical research institution
Topic:
Medical imaging, prostate cancer, MRI, machine learning
Document type:
Supplemental Digital Content
Methodology:
PI-RADS guided contrastive learning, convolutional neural networks, transformer encoders, ensemble models
Data:
Bi-parametric prostate MR images, clinical variables including PSA, PSAD, age, and prostate volume
Audience:
Radiologists, medical researchers, AI in healthcare professionals
Parameters:
T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), echo-planar imaging sequences, b-values 50, 1000, 1500 s/mm²
Model details:
36M parameter Representation Learner (RL) combining CNN and transformer encoders
Validation:
t-SNE visualization, box and whisker plots, binary cross-entropy loss, early stopping, hyper-parameter tuning
Performance metrics:
csPCa detection, avoidance of benign biopsies, ensemble prediction combining RL and clinical models
Training:
50 epochs for RL, 1000 epochs for biopsy decision models, AdamW optimizer, stochastic gradient descent with momentum, data augmentation including rotations, cropping, brightness/contrast adjustments, elastic deformations
Reference literature:
Umapathy et al. 2023, Yala et al. 2021, Shen et al. 2023
Year:
2025
Region / City:
California
Theme:
Energy, Forecasting, Grid Operations, Renewable Energy
Document Type:
Grant Funding Opportunity
Organization:
California Energy Commission
Author:
California Energy Commission
Target Audience:
Researchers, Utilities, Energy Market Participants, Policy Makers
Period of Validity:
October 2025 onwards
Approval Date:
October 2025
Date of Modifications:
N/A
Year:
2024-2025
Region / City:
Florida
Subject:
Transportation forecasting, travel demand modeling
Document Type:
Work Plan
Organization / Institution:
Florida Department of Transportation (FDOT)
Author:
Florida Transportation Forecasting Forum (TFF)
Target Audience:
Transportation planners, engineers, decision-makers, modeling professionals
Period of Validity:
2024-2025
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2024
Region / City:
Nigeria
Topic:
Hydrology, Aquifers, Marine Science
Document Type:
Report
Author:
Not specified
Target Audience:
Researchers, Hydrologists, Marine Scientists
Period of Validity:
June 2024
Approval Date:
Not specified
Modification Date:
Not specified
Year:
Not specified
Region / City:
Not specified
Topic:
Weather forecasting, meteorology
Document Type:
Lab report
Organization / Institution:
University of Illinois
Author:
Not specified
Target Audience:
Students studying meteorology
Period of validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2022
Region / City:
United States
Topic:
Climate-Informed Forecasting, Epidemiology, West Nile Virus
Document Type:
Scientific Research
Institution:
R Core Team, Goodrich et al.
Author:
Not specified
Target Audience:
Researchers, epidemiologists, climate scientists
Period of Validity:
2022
Date of Approval:
Not specified
Date of Changes:
Not specified
Year:
N/A
Region / City:
N/A
Theme:
Forecasting Techniques
Document Type:
Exam Questions
Organization / Institution:
N/A
Author:
Scott Stevens
Target Audience:
Students
Period of Action:
N/A
Approval Date:
N/A
Date of Changes:
N/A
Authors:
Vineeta Prakaulya; Prof. Roopesh Sharma; Upendra Singh; Ravikant Itare
Affiliation:
Patel College of Science and Technology, Indore
Department:
Computer Science and Engineering (CSE)
Document Type:
Review Article
Subject Area:
Data Mining and Climate Forecasting
Keywords:
Data mining, agriculture, soil fertility, crop yield, ANNs, FIS, LVQ, bi clustering
Geographical Focus:
India
Thematic Focus:
Precipitation prediction and agricultural productivity
Methods Discussed:
Artificial Neural Networks (ANNs), Fuzzy Inference System (FIS), Decision Tree (SLIQ), Time Series Analysis, Learning Vector Quantization (LVQ), Support Vector Machine (SVM), Bi-clustering
Data Scope:
Historical precipitation data including 45-year monsoon records and monthly precipitation series (1956–2008)
Intended Audience:
Researchers and practitioners in data mining, meteorology, and agricultural management
Chapter:
12
Subject:
Forecasting
Discipline:
Operations Management
Type of document:
Educational textbook exercises with solutions
Topics covered:
Moving average; Exponential smoothing; Adjusted exponential smoothing; Seasonal forecasting; Linear trend line; Linear regression; Multiple regression; Forecast accuracy measures; Control charts
Statistical measures:
MAD; Cumulative error (E); Average error (Ē); Correlation coefficient; Coefficient of determination
Organizations mentioned:
Tech; Bee Line Café; ITown; State University
Time references:
Eight semesters; Twelve quarters; Ten years; Forecast for 2005; Forecast for year 11
Software referenced:
Excel
Intended audience:
Students of operations management
Year:
2019
Region / City:
Australia
Topic:
Tobacco Excise
Document Type:
Working Paper
Organization:
The Treasury
Author:
Jonathan O’Bannon, John Clark
Target Audience:
Government policy makers, economists
Period of Validity:
Ongoing
Approval Date:
June 2019
Date of Modifications:
N/A
Year:
2023
Region / City:
Glassboro, NJ, USA
Theme:
Environmental Impact, Life Cycle Assessment, Machine Learning
Document Type:
Research Article
Organization / Institution:
Rowan University
Author:
Harriet Dufie Appiah, Matthew Conway, Jahnvi Patel, Marcella McMahon, Robert Hesketh, Kirti M. Yenkie
Target Audience:
Researchers, Environmental Scientists, Engineers
Period of Action:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Keywords:
Life Cycle Assessment, Machine Learning, Environmental Impact, Emissions
Contextual Description:
A research article discussing the application of machine learning models to predict environmental impacts of chemicals at the early design stage based on their molecular properties and life cycle data.
Year:
2023
Region / City:
Global
Topic:
Weather Forecasting, Machine Learning
Document Type:
Research Paper
Organization / Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers, Meteorologists, Machine Learning Practitioners
Period of Validity:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Keywords:
Weather forecasting, Regression Techniques, Prediction, MSE
Context:
The document presents a research study on applying machine learning regression techniques for real-time weather forecasting and prediction.
Year:
2023
Region / City:
Aurangabad District, Maharashtra
Subject:
Potential Evapotranspiration Forecasting
Document Type:
Research Article
Author:
Not specified
Target Audience:
Researchers, Hydrologists, Water Resource Managers
Period of Study:
1970–2023
Date of Approval:
Not specified
Date of Modifications:
Not specified
Keywords:
PET Forecasting, ANN, Thornthwaite Method, Water Resource Management
Year:
1998
Region / City:
Global
Subject:
Demand Forecasting
Document Type:
Educational Text
Institution:
Not specified
Author:
Not specified
Target Audience:
Students, Business Professionals
Period of Validity:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Year:
2023
Region / City:
Aurangabad, Marathwada region, Maharashtra
Theme:
Water resource management, Evapotranspiration forecasting, Agricultural planning
Document type:
Research article
Organization / Institution:
Not specified
Author:
Not specified
Target Audience:
Researchers, water resource managers, agricultural planners
Period of validity:
1970-2023
Approval date:
Not specified
Date of modifications:
Not specified
Methodology:
Thornthwaite method, Artificial Neural Network (ANN)
Keywords:
Potential Evapotranspiration, Artificial Neural Network, Thornthwaite method, Time series analysis, Hydrological forecasting
Note:
Contextual description