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The process of spatially aligning two or more images acquired from different devices or imaging protocols is known as multi-modal image registration. As the similarity measure used is one of the most significant aspects of this process, certain measures have been proposed to enhance multi-modal image registration. However, the currently available measures are either not sufficiently accurate or are...
Accurate and energy-efficient navigation and localization methods for autonomous underwater vehicles continues to be an active area of research. As we increase the endurance of autonomous underwater vehicles, we will require navigation and localization solutions that are robust over the entire deployment duration. Rather than look at expensive and high-energy instrumentation, we examine the utility...
Accurate and energy-efficient navigation and localization methods for autonomous underwater vehicles continues to be an active area of research. As interesting as they are important, ocean processes are spatiotemporally dynamic and their study requires vehicles that can maneuver and sample intelligently while underwater for extended durations. In this paper, we present a new technique for augmenting...
This work describes relevant design considerations for the fabrication of a miniaturized thermal interface material characterization instrument that is capable of resolving interfacial thermal resistances (Rt) below 1 mm2.K/W. Leveraging previous work (Warzoha et al., 2017, Smith et al. 2016), the authors propose a reduction in the length scale of the primary heat meter bars to below 4 mm in order...
Modeling the dynamic, time-varying behavior of systems and processes is a common design and analysis task in the systems engineering community. A popular method for performing such analysis is the use of Markov chains. Additionally, automated methods may be used to automatically determine new system state values for a system under observation or test. Unfortunately, the state-transition space of a...
To effectively examine ocean processes, sampling campaigns require persistent autonomous underwater vehicles that are able to spend a majority of their deployment time maneuvering and gathering data underwater. Current navigation techniques rely either on high-powered sensors (e.g. Doppler Velocity Loggers) resulting in decreased deployment time, or dead reckoning (compass and IMU) with motion models...
It is known that the learning rate is the most important hyper-parameter to tune for training deep neural networks. This paper describes a new method for setting the learning rate, named cyclical learning rates, which practically eliminates the need to experimentally find the best values and schedule for the global learning rates. Instead of monotonically decreasing the learning rate, this method...
Automatic image registration algorithms that rely on a gradient descent based approach may fail when the initial misalignment between objects is large. The registration task is even more difficult for multi-modal images because of the non-linear relationship between the pixel intensities in the images to be aligned. In this paper we will present a multi-modal image registration algorithm which successfully...
To date, there has not been a single method suitable for large-scale or regular-basis implementation to analyze the locomotion of quadruped animals. Existing methods are not sensitive enough for detecting minor deviations from healthy gaits. That is important because these minor deviations could develop into a severe painful lameness condition. We introduce a dynamic novel proxy for early stage lameness...
The 2015 Gold King Mine spill exposed the Animas River (located in Durango, Colorado) to over 3 million gallons of toxic water with spiked levels of arsenic and lead among other metals. In response to public concern for the quality of the river's water, a water quality monitoring system has been developed and deployed. Multiple organizations, both local and federal, have joined forces to understand...
We introduce the concept of dynamically growing a neural network during training. In particular, an untrainable deep network starts as a trainable shallow network and newly added layers are slowly, organically added during training, thereby increasing the network's depth. This is accomplished by a new layer, which we call DropIn. The DropIn layer starts by passing the output from a previous layer...
Efforts to miniaturize electronic components within the semiconductor industry continue to intensify stresses on the primary thermal pathways that are used for heat dissipation in electronics packaging equipment. This is particularly true for heat flow pathways that traverse interfaces. Consequently, an increasing priority for thermal engineers is to design materials that are capable of reducing the...
In this paper, an improved rotor flux estimation method for the Torque model reference adaptive schemes (TMRAS) sensorless induction machine drive is proposed to enhance its performance in low and zero speed conditions. The conventional TMRAS scheme uses an open loop flux estimator and a feedforward term, with basic low pass filters replacing the pure integrators. However, the performance of this...
The ocean, as vast as it is complex, has a plethora of phenomena that are of legitimate scientific interest, e.g., ocean fronts and Lagrangian Coherent Structures. These coherent ocean features occur from tidal mixing and ocean circulation, and are generally characterized with narrow bands of locally intensive physical gradients with enhanced circulation, biological productivity, and optimal transport...
Optical computing elements offer benefits over traditional CMOS-based electronic logic gates such as increased performance and reduced power. Using polarization to encode the information to be processed allows for the possibility of non-binary switching theory to be applied that further offers the benefit of reducing the number of required elements in an optical computing circuit. A methodology for...
Root growth and development are critical for plant survival and productivity. While systems have been developed to automate the process of extracting root traits using 2D and 3D imaging under controlled conditions, to date, no systems exist that can non-destructively and repeatedly provide high-quality information on roots of field-grown plants. At the same time, Terahertz (THz) imaging is becoming...
The paper deals with relationship between two approaches to derive approximate formulae of one specific numerical inverse Laplace transform (NILT) method, which is based on the approximation of the exp(st) function in the definition Bromwich integral, and the method based on the direct numerical integration of this ILT integral. It is shown that respective approximate formulae can also be derived...
To effectively examine ocean processes we must often sample over the duration of long (weeks to months) oscillation patterns. Such sampling requires persistent autonomous underwater vehicles, that have a similarly long deployment duration. Actively actuated (propeller-driven) underwater vehicles have proven effective in multiple sampling scenarios, however they have limited deployment endurance. The...
This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A*-like algorithms. Vehicle performance limits are incorporated...
Similar to the atmosphere, coherent structures, e.g., fronts, exist in the ocean. These frontal structures are known to be highly productive, supporting the whole spectrum of marine life. Ocean fronts are dynamic in time and space, and are a key component to a comprehensive knowledge of ocean dynamics and aquatic ecosystems in relation to climate change. However, dynamic features such as fronts are...
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