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Axially Loaded Drilled Shafts: LRFD Resistance Factor Calibration and Predictive Techniques for Settlement
In areas where local geology consists of unique or uncommon subsurface materials, uncertainty in deep foundation design may lead to excessive construction costs and inadequate reliability. While the calibration of area-specific ...
Using Pre- and Post-Process Labeling Techniques for Cluster Analysis
As the amount and variety of data increases through technological and investigative advances, the means to analyze and manage this data becomes more critical. Unsupervised machine learning algorithms can be used to group ...
Deep Convolutional Neural Networks Based Single Image Super-Resolution And Classification For Crater Detection
Craters are among the most abundant features on the surface of many planets with great importance for planetary scientists. Craters reveal chronology information about planets and may be used for autonomous spacecraft ...
HMM-Based Techniques for Intent Recognition in a Simulated Realistic Naval Environment
Activity recognition aims to recognize the actions of one or more agents froma series of observations. Intent recognition is an area of research dedicated toautomatically detecting and predicting the intentions of agents ...
Evolving Effective Micro Behaviors for Real-Time Strategy Games
Real-Time Strategy games have become a new frontier of artificial intelligence research. Advances in real-time strategy game AI, like with chess and checkers before, will significantly advance the state of the art in AI ...
Network Security Monitoring and Analysis based on Big Data Technologies
Network flow data provides valuable information to understand the network status and tobe aware of the network security threads. However, handling the large amount of datacollected from the network and providing real time ...
Recursive Hyperspheric Classification
Data guide decisions and processes. Moreover, while the practice of obtaining data may be mundane, the analysis of data provides vision and understanding. Within data -- ideally -- are hidden patterns and metadata that ...
Global Ensemble Streamflow and Flood Modeling with Application of Large Data Analytics, Deep learning and GIS
ABSTRACTFlooding is one of the most dangerous natural disasters that repeatedly occur globally, and flooding frequently leads to major urban, financial, anthropogenic, and environmental impacts in the subjected area. ...