Monitoring water quality of small inland lakes and reservoirs is a critical component of the US Army Corps of Engineers (USACE) water qualitymanagement plans. However, limited resources for traditional field-based mon...
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Monitoring water quality of small inland lakes and reservoirs is a critical component of the US Army Corps of Engineers (USACE) water qualitymanagement plans. However, limited resources for traditional field-based monitoring of numerous lakes and reservoirs covering vast geographicareas often leads to reactional responses to harmful algal bloom (HAB) outbreaks.
Steady state voltage problems in power systems are those associated with undervoltages resulting from increasing loads. Steady overvoltages can also arise when loads served by networks are reduced, and the problem can...
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ISBN:
(纸本)9781467396578
Steady state voltage problems in power systems are those associated with undervoltages resulting from increasing loads. Steady overvoltages can also arise when loads served by networks are reduced, and the problem can be exacerbated if lines supplying load centres are long. This paper reports on a study that was conducted to assess the impact of derating voltage of lines, by using step down transformers on the lowest load a network can accommodate without overvoltages. A program written in python and using PSS/E to perform loadflows, was used to perform analyses at various load levels. The study showed that with derating transformers installed, voltages in the system were better, there was less reactive power flow, and active power losses were lower. Derating lines using step down transformers is therefore a potential solution for serving low load levels.
Modern advancements in text to speech and voice conversion techniques make it increasingly difficult to distinguish an authentic voice from a synthetically generated voice. These techniques, though complex, are relati...
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Modern advancements in text to speech and voice conversion techniques make it increasingly difficult to distinguish an authentic voice from a synthetically generated voice. These techniques, though complex, are relatively easy to use, even for non-technical users. It is important to develop mechanisms for detecting false content that easily scale to the size of the monitoring requirement. Current approaches for detecting spoofed audio are difficult to scale because of their processing requirements. Individually analyzing spectrograms for aberrations at higher frequencies relies too much on independent verification and is more resource intensive. Our method addresses the resource consideration by only looking at the residual differences between an audio files smoothed signal and its actual signal. We conjecture that natural audio has greater variance than spoofed audio because spoofed audios generation is conditioned on trying to mimic an existing pattern. To test this, we develop a classifier that distinguishes between spoofed and real audio by analyzing the differences in residual patterns between audio files.
This project investigated patterns in the training data of Navy aviators in an attempt to predict their success in training. With the help of the sponsor, we assembled a database from many sources of training data. Th...
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This project investigated patterns in the training data of Navy aviators in an attempt to predict their success in training. With the help of the sponsor, we assembled a database from many sources of training data. This database covered 18,596 pilot and Naval Flight Officer candidates through their pretesting, classroom instruction, candidate training in generic aircraft, and candidate training in specialized aircraft. This data was a challenge to organize because it had incompatible formats and missing data. After standardizing the formats and fixing errors in the data, and aggregating sparse records to a smaller set of average scores, we had 301 features for the candidates. We then correlated their features using both numeric-correlation and nonnumeric-association (class-characterization) methods. We identified 38 kinds of measures of success in the program and particularly focused on correlations involving those. We did confirm some early indicators of success and failure in the program, but most were not surprising. We conclude that the Navy is doing a good job of identifying candidates likely to be successful.
This Coastal and Hydraulics Engineering Technical Note describes the approach, methodology, and utilities of a python code to flexibly create finite element meshes for a single catchment, multiple catchments, or an en...
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This Coastal and Hydraulics Engineering Technical Note describes the approach, methodology, and utilities of a python code to flexibly create finite element meshes for a single catchment, multiple catchments, or an entire watershed. This tool was developed with the intent of model development for rapid responses with an emphasis on Adaptive Hydraulics 5.0 Diffusive Wave AdH-DW applications, though any numerical code that uses an unstructured mesh could be applied.
Categorical Attribute traNsformation Environment (CANE) is a simpler but powerful data categorical preprocessing python package. The package is valuable since there is currently a large range of Machine Learning (ML) ...
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Categorical Attribute traNsformation Environment (CANE) is a simpler but powerful data categorical preprocessing python package. The package is valuable since there is currently a large range of Machine Learning (ML) algorithms that can only be trained using numerical data (e.g., Deep Learning, Support Vector Machines) and several real-world ML applications are associated with categorical data attributes. Currently, CANE offers three categorical to numeric transformation methods, namely: Percentage Categorical Pruned (PCP), Inverse Document Frequency (IDF) and a simpler One-Hot-Encoding method. Additionally, the CANE module is well documented with several code examples that can help in its adoption by non expert users.
A ubiquitous, reliable, and affordable method to determine surface water quality (SWQ) is still evasive. In the current study, we compared two easily accessible statistical tools: fuzzy logic (FL) inference and water ...
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