Deep Reinforcement Learning for Mobile App Prediction
This research focuses on a system, known as ATPP, based on deep marked temporal point processes, designed for predicting mobile app usage patterns. By leveraging deep reinforcement learning frameworks and context-aware modules, the system aims to predict the next app a user will open, along with its
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Address Prediction and Recovery in EECS 470 Lecture Winter 2024
Explore the concepts of address prediction, recovery, and interrupt recovery in EECS 470 lecture featuring slides developed by prominent professors. Topics include branch predictors, limitations of Tomasulo's Algorithm, various prediction schemes, branch history tables, and more. Dive into bimodal,
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Hydrologic Modeling Methods in HEC-HMS: A Comprehensive Overview
Explore the transformative methods within HEC-HMS hydrologic modeling, including unit hydrograph derivation, excess precipitation transformation, hydrograph illustration, surface transform methods, and concepts like the kinematic wave and 2D diffusion wave. Learn about the unit hydrograph, kinematic
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Analyzing Hydrologic Time-Series for Flood Frequency Analysis
This content delves into the methods and assumptions involved in studying hydrologic time-series data for flood frequency analysis. It covers topics such as different types of assumptions, including independence and persistence, and highlights how streamflow data can be analyzed to find annual maxim
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Understanding Routing Methods in Hydrologic Engineering Center (HEC-ResSim)
Explore the differences between hydrologic and hydraulic routing, learn about open channel flow processes, and delve into channel routing within HEC-ResSim. Discover various reach routing methods, parameter estimation techniques, and calibration approaches. Dive into the Muskingum method and its app
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Understanding H.264/AVC: Key Concepts and Features
Exploring the fundamentals of MPEG-4 Part 10, also known as H.264/AVC, this overview delves into the codec flow, macroblocks, slices, profiles, reference picture management, inter prediction techniques, motion vector compensation, and intra prediction methods used in this advanced video compression
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Computer Vision in Agriculture: Optimizing Crop Management and Yield Prediction
In recent years, the agriculture industry has witnessed a significant transformation fueled by technological advancements. Among these innovations, computer vision has emerged as a game-changer, offering unparalleled opportunities to optimize crop management and enhance yield prediction. Leveraging
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Understanding Machine Learning for Stock Price Prediction
Explore the world of machine learning in stock price prediction, covering algorithms, neural networks, LSTM techniques, decision trees, ensemble learning, gradient boosting, and insightful results. Discover how machine learning minimizes cost functions and supports various learning paradigms for cla
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Hydrologic Modeling with Gridded Precipitation Data
Learn about utilizing gridded precipitation data for hydrologic modeling with HEC-HMS. Explore the advantages of spatially distributed precipitation sources such as RADAR and gauge comparisons, and understand the various national and regional products available. Discover utilities for converting and
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Historic Precipitation Hydrologic Modeling with HEC-HMS Slides by Greg Karlovits, Emily Moe, Daniel Black
Delve into the world of hydrologic modeling with HEC-HMS through a detailed presentation by experts Greg Karlovits, Emily Moe, and Daniel Black. Explore meteorologic models, atmospheric boundary conditions, basin modeling, and simulation runs in this informative slide series.
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Advancements in Air Pollution Prediction Models for Urban Centers
Efficient air pollution monitoring and prediction models are essential due to the increasing urbanization trend. This research aims to develop novel attention-based long-short term memory models for accurate air pollution prediction. By leveraging machine learning and deep learning approaches, the s
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Understanding State of Charge Prediction in Lithium-ion Batteries
Explore the significance of State of Charge (SOC) prediction in lithium-ion batteries, focusing on battery degradation models, voltage characteristics, accurate SOC estimation, SOC prediction methodologies, and testing equipment like Digatron Lithium Cell Tester. The content delves into SOC manageme
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KFRE: Validated Risk Prediction Tool for Kidney Replacement Therapy
KFRE, a validated risk prediction tool, aids in predicting the need for kidney replacement therapy in adults with chronic kidney disease. Developed in Canada in 2011, KFRE has undergone validation in over 30 countries, showing superior clinical accuracy in KRT prediction. Caution is advised when usi
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Understanding Gage Weights and Precipitation Methods in Hydrologic Modeling
Exploring the concept of gage weights and precipitation methods in hydrologic modeling using the HEC-HMS software. Dive into the pros and cons of flexible gage weighting, calibration processes, and best practices for estimating time and depth weights. Discover how to set up a gage weights model, inc
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Real-time Experimental Lightning Flash Prediction Report
This Real-time Experimental Lightning Flash Prediction Report presents a detailed analysis of lightning flash forecasts based on initial conditions. Prepared by a team at the Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, India, the report includes data on accumulated total li
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Privacy-Preserving Prediction and Learning in Machine Learning Research
Explore the concepts of privacy-preserving prediction and learning in machine learning research, including differential privacy, trade-offs, prediction APIs, membership inference attacks, label aggregation, classification via aggregation, and prediction stability. The content delves into the challen
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Wetland Prediction Model Assessment in GIS Pilot Study for Kinston Bypass
Wetland Prediction Model Assessment was conducted in a GIS pilot study for the Kinston Bypass project in Lenoir County. The goal was to streamline project delivery through GIS resources. The study focused on Corridor 36, assessing various wetland types over a vast area using statistical and spatial
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Clipper: A Low Latency Online Prediction Serving System
Machine learning often requires real-time, accurate, and robust predictions under heavy query loads. However, many existing frameworks are more focused on model training than deployment. Clipper is an online prediction system with a modular architecture that addresses concerns such as latency, throu
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Over-the-Loop Streamflow Forecasting Project Summary
Joint project by USBR, USACE, and NCAR focusing on improving streamflow forecasting using automated over-the-loop approaches. Key challenges include model calibration, data assimilation, and real-time forcings. Objectives involve building an automated system for short- to long-term flow predictions
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Address-first Value-next Predictor with Value Prefetching
Improving single-thread performance in modern processors efficiently is crucial. AVPP proposes optimizations to reduce hardware cost for load value prediction, introducing a new taxonomy of Value Prediction Policies. AVPP outperforms state-of-the-art predictors, providing system performance improvem
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Theoretical Justification of Popular Link Prediction Heuristics
This content discusses the theoretical justification of popular link prediction heuristics such as predicting connections between nodes based on common neighbors, shortest paths, and weights assigned to low-degree common neighbors. It also explores link prediction generative models and previous empi
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Using Decision Trees for Program-Based Static Branch Prediction
This presentation discusses the use of decision trees to enhance program-based static branch prediction, focusing on improving the Ball and Larus heuristics. It covers the importance of static branch prediction, motivation behind the research, goals of the study, and background on Ball and Larus heu
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Understanding the Hydrologic Cycle and Water Distribution
The hydrologic cycle, water distribution in the hydrosphere, water usage in the United States in 2005, condensation processes forming fog, cloud types, precipitation processes including ice-crystal and coalescence processes, and types of precipitation like sleet, freezing rain, hail, and graupel are
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Advancements in Hydrologic Modeling for Enhanced Predictions
Explore the future of hydrologic modeling with a focus on distributed models, data assimilation, ensemble forecasts, and verification. Discover the potential benefits of continued research in physically based models for more accurate forecasts in various conditions. Uncover challenges facing hydrolo
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Understanding Causality in News Event Prediction
Learning about the significance of predictions in news events and the process of causality mining for accurate forecasting. The research delves into problem definition, solution representation, algorithms, and evaluation in event prediction. Emphasis is placed on events, time representation, predict
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Overview of Synthetic Models in Transcriptional Data Analysis
This content showcases various synthetic models for analyzing transcriptome data, including integrative models, trait prediction, and deep Boltzmann machines. It explores the generation of synthetic transcriptome data and the training processes involved in these models. The use of Restricted Boltzma
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Network Coordinate-based Web Service Positioning Framework for Response Time Prediction
This paper presents the WSP framework, a network coordinate-based approach for predicting response times in web services. It explores the motivation behind web service composition, quality-of-service evaluation, and the challenges of QoS prediction. The WSP framework enables the selection of web ser
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Understanding the Hydrologic Cycle and Water in the Atmosphere
Exploring the intricate processes of evaporation, condensation, and cloud formation in the atmosphere, the hydrologic cycle's closed system, and the impact of global warming on Earth's water resources. Dive into the essential concepts of water absorption, redistribution of energy, humidity, and the
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Understanding Peer Prediction Mechanisms in Learning Agents
Peer prediction mechanisms play a crucial role in soliciting high-quality information from human agents. This study explores the importance of peer prediction, the mechanisms involved in incentivizing truthful reporting, and the convergence of learning agents to truthful strategies. The Correlated A
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Enhancing Processor Performance Through Rollback-Free Value Prediction
Mitigating memory and bandwidth walls, this research extends rollback-free value prediction to GPUs, achieving up to 2x improvement in energy and performance while maintaining 10% quality degradation. Utilizing microarchitecturally-triggered approximation to predict missed loads, this work focuses o
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Understanding the Hydrological Cycle and Flood Hazards
This session with Dr. Patrick Asamoah Sakyi delves into the hydrologic cycle, causes of flooding, and ways to mitigate flood hazards. Topics covered include the hydrologic cycle, stream systems, flood consequences, factors affecting flood severity, and strategies for reducing flood risks. Recommende
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Understanding Abiotic Cycles in Ecosystems: Hydrologic, Carbon, Nitrogen, and More
Abiotic cycles play a crucial role in regulating ecosystems. The hydrologic cycle involves processes like evaporation, condensation, precipitation, and transpiration. The carbon cycle relies on photosynthesis, respiration, and human activities like deforestation and burning fossil fuels. The nitroge
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CloudScale: Elastic Resource Scaling for Multi-Tenant Cloud Systems
CloudScale is an automatic resource scaling system designed to meet Service Level Objective (SLO) requirements with minimal resource and energy cost. The architecture involves resource demand prediction, host prediction, error correction, virtual machine scaling, and conflict handling. Module 1 focu
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Amendments to WIPPS Manual for Climate Prediction at INFCOM-3, April 2024
The document discusses amendments to the Manual on WIPPS for climate prediction, including new recommendations for weather, climate, water, and environmental prediction activities. It introduces concepts such as Global Climate Reanalysis and the coordination of multi-model ensembles for sub-seasonal
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Protein Secondary Structure Prediction: Insights and Methods
Accurate prediction of protein secondary structure is crucial for understanding tertiary structure, predicting protein function, and classification. This prediction involves identifying key elements like alpha helices, beta sheets, turns, and loops. Various methods such as manual assignment by cryst
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ACE RAM Workshop - Barcelona 2019: Reliability and Maintenance Concepts
The ACE RAM Workshop conducted by George Pruteanu in Barcelona focused on topics such as RAM prediction, FMEA, maintenance concepts, preventive and predictive maintenance, condition monitoring systems, corrective maintenance, and design for maintenance. The workshop delved into reliability predictio
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Implementation of the Community Hydrologic Prediction System
The Community Hydrologic Prediction System (CHPS) is a revolutionary initiative replacing the outdated NWS River Forecast System. It aims to improve hydrologic modeling infrastructure by incorporating modern forecasting concepts and models, enhancing data sharing, and fostering collaboration within
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Numerical Modeling for Hydraulic Fracture Prediction on Fused Silica Samples
Goal of the project is to predict the overpressures required to fracture fused silica cylindrical samples using numerical modeling. The study focuses on a homogeneous pure material with known mechanical properties compared to experimental results from a lab-scale stimulation system. The model includ
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Hydrologic Systems Analysis for Water Quality Assessment
Principals Thomas Burke and Operations Impacts in the Hydrologic Systems exhibit a comprehensive analysis of scenarios and comparison between Preferred Alternative (PA) and No Action Alternative (NAA). The assessment covers river stage reductions, channel siltation, and the impact on water quality i
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Analysis and Comparison of Wave Equation Prediction for Propagating Waves
Initial analysis and comparison of the wave equation and asymptotic prediction of a receiver experiment at depth for one-way propagating waves. The study examines the amplitude and information derived from a wave equation migration algorithm and its asymptotic form. The focus is on the prediction of
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