Unsupervised Neural Hidden Markov Models

In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model. We evaluate our approach on tag in- duction. Our approach outperforms existing generative models and is competitive with the state-of-the-art though with a simpler model easily extended to include additional context.Comment: accepted at EMNLP 2016, Workshop on Structured Prediction for NLP. Oral presentatio

Efficient Feature Learning Using Perturb-and-MAP

Perturb-and-MAP [1] is a technique for efficiently drawing approximate samples from discrete probabilistic graphical models. These samples are useful for both characterizing the uncertainty in the model, as well as learning its parameters. In this work, we show that this same technique is effective at learning features from images using graphical models with complex dependencies between variables. In particular, we apply this technique in order to learn the parameters of a latentvariable model, the restricted Boltzmann machine, with additional higher-order potentials. We also use it in a bipartite matching model to learn features that are specifically tailored to tracking image patches in video sequences. Our final contribution is the proposal of a novel method for generating perturbations.

Waypoint Profiler

Ocean health monitoring is crucial for maintaining the health of the ocean ecosystem. Currently, divers are deployed to collect data manually, which is both time and resource-consuming. Additionally, this process poses significant dangers to the divers. Therefore, a more efficient method for collecting oceanic data is needed. This thesis describes the design of a novel autonomous marine vehicle, the waypoint profiler. Launched from shore with scientific sensors, it autonomously navigates to ocean locations of interest and dives to measure key ocean health markers. The system integrates subsystems for scientific sensing, health monitoring, structural integrity, communications, and navigation/control, tailored to meet stakeholder needs such as the Monterey Bay Aquarium Research Institute (MBARI), the US Army Corps of Engineers, and Occidental College. The Scientific sensing subsystem measures water temperature and captures water samples. The Health subsystem tracks battery levels and detects leaks. The Structural subsystem protects components and supports operation in various conditions. The Navigation and Control subsystem uses GPS and thrusters for precise movement. Extensive testing and validation were conducted to ensure the system\u27s performance and reliability. The results show a partial success of our vehicle\u27s ability to navigate to GPS waypoints and dive vertically to profile water columns. In the future, improvements can be made to the design of an internal charging system, eliminating the need to disassemble the vehicle to remove the batteries for charging. Another area for improvement is the cluster control capabilities, allowing one or more vehicles to be deployed and work collaboratively to complete tasks more efficiently

Putting context into organizational intervention design:Using tailored questionnaires to measure initiatives for worker well-being

Realistic evaluation emphasizes the importance of exploring the mechanisms through which organizational interventions are effected. A well-known mechanism in organizational interventions is the screening process. Standardized questionnaires, in popular use, neither consider individuals’ appraisals of working conditions nor the specific context of the workplace. Screening with items tailored to intervention contexts may overcome the limitations of standardized questionnaires. In the present study, we evaluate an approach to develop a tailored questionnaire to measure employees’ appraisals of their specific working conditions. First, we interviewed 56 employees and 17 managers and, later, developed tailored items focused on the working conditions in a postal service. In follow-up interviews, we explore participants’ experiences with the tailored questionnaire, including the development of initiatives, compared to their previous experiences with the company´s annual attitude survey that used standardized scales. Results indicated that participants felt the tailored questionnaire highlighted issues that had previously been ignored, that initiatives were easier to develop due to its specificity, and that the feedback strategy was useful in prioritizing questionnaires. Overall, it can be concluded that tailored questionnaires may be appropriate for use in organizational intervention research and more broadly that evaluations of organizational interventions need to be contextually grounded

Applications of Tightly Focused Ultrafast Laser in the Fabrication of Micro Total Analysis Systems and Biological Research.

Tight focusing of femtosecond pulses accentuates the non-linear effect of optical breakdown to achieve damage regions smaller than the light resolution limit. When pulse energy is near the breakdown threshold, optical breakdown using tightly focused ultrafast laser is extraordinary precise and induces minimal collateral damage. These characteristics enable the surgical manipulation of sub-cellular structures and its importance becomes apparent when dealing with intrinsically mechanical cellular processes such as mitosis. We examine the role of polar ejection forces (PEFs) in guiding directional instability of vertebrate mitotic chromosomes. Taking advantage of extremely precise character of femtosecond pulsed laser microsurgery, we abruptly alter PEFs by severing chromosome arms. Reduction of PEFs increases the amplitude of directional instability without altering other characteristics, or the speed of chromosome movement. We find that PEFs limit the range of chromosome oscillation by increasing the probability that motors at a leading kinetochore abruptly fail or disengage, leading to a direction reversal. From the relation between the change in oscillation amplitude and the length of the chromosome arm shortened, we are able to map the distribution of PEFs across spindle, which is surprisingly different from distributions previously assumed. These results allow us to differentiate between models of directional instability, and reveal relations between forces within the spindle and chromosome movements fundamental to the intrinsically mechanical mitotic process. In the course of developing this surgical technique, we fabricated devices such as nanochannels and resistive-pulsed sensors in glass in order to study the capabilities of laser-induced optical breakdown. We found microbubbles created with this technique highly damped and contribute little collateral damage compared to shockwave-forming cavitation bubbles produced by longer pulsed lasers. In their own right, these studies contribute to the field of medical diagnosis and biodefense by establishing methods capable of speeding up chemical separation and detection of viruses. Transitioning from glass to cells, we studied the effect of microsurgical removal of proteinaceous ASC aggregates, which play an important role in inflammatory diseases.Ph.D.Biomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58456/1/kke_1.pd

An integrated multiple criteria preference ranking approach to the Canadian west coast port congestion conflict

An integrative conflict analysis approach, incorporating an Analytic Hierarchy Process (AHP) based preference ranking method into the Graph Model for Conflict Resolution (GMCR), is employed to investigate the Canadian west coast port congestion dispute. The Canadian west coast has historically been an important gateway connecting North America to Asia thanks to its specific geographical and strategic location. Despite successful operations and maintenance of the port facilities to handle international trade during the past few decades, the west coast is now facing increasing congestion problems, resulting in significant delays in transporting goods from the west coast to other parts of Canada and the USA. The strategic analyses carried out in this research suggest potential resolutions in which Canada would expand port facilities at various locations, encouraging traders to continue choosing the Canadian west coast as one of their trade gateways to North America

Micro-Resonator Optical Frequency Combs for Photonic Doppler Velocimetry

Author Institution: University of Nevada, Las Vegas; Nevada National Security SiteSlides presented at the 2018 Photonic Doppler Velocimetry (PDV) Users Workshop, Drury Plaza Hotel, Santa Fe, New Mexico, May 16-18, 2018

A Whole-Body Model for Glycogen Regulation Reveals a Critical Role for Substrate Cycling in Maintaining Blood Glucose Homeostasis

Timely, and sometimes rapid, metabolic adaptation to changes in food supply is critical for survival as an organism moves from the fasted to the fed state, and vice versa. These transitions necessitate major metabolic changes to maintain energy homeostasis as the source of blood glucose moves away from ingested carbohydrates, through hepatic glycogen stores, towards gluconeogenesis. The integration of hepatic glycogen regulation with extra-hepatic energetics is a key aspect of these adaptive mechanisms. Here we use computational modeling to explore hepatic glycogen regulation under fed and fasting conditions in the context of a whole-body model. The model was validated against previous experimental results concerning glycogen phosphorylase a (active) and glycogen synthase a dynamics. The model qualitatively reproduced physiological changes that occur during transition from the fed to the fasted state. Analysis of the model reveals a critical role for the inhibition of glycogen synthase phosphatase by glycogen phosphorylase a. This negative regulation leads to high levels of glycogen synthase activity during fasting conditions, which in turn increases substrate (futile) cycling, priming the system for a rapid response once an external source of glucose is restored. This work demonstrates that a mechanistic understanding of the design principles used by metabolic control circuits to maintain homeostasis can benefit from the incorporation of mathematical descriptions of these networks into “whole-body” contextual models that mimic in vivo conditions

Cascaded deep monocular 3D human pose estimation with evolutionary training data

End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data. This paper proposes a novel data augmentation method that: (1) is scalable for synthesizing massive amount of training data (over 8 million valid 3D human poses with corresponding 2D projections) for training 2D-to-3D networks, (2) can effectively reduce dataset bias. Our method evolves a limited dataset to synthesize unseen 3D human skeletons based on a hierarchical human representation and heuristics inspired by prior knowledge. Extensive experiments show that our approach not only achieves state-of-the-art accuracy on the largest public benchmark, but also generalizes significantly better to unseen and rare poses. Code, pre-trained models and tools are available at this HTTPS URL.Comment: Accepted to CVPR 2020 as Oral Presentatio