Interpretable 3D Human Action Analysis with Temporal Convolutional Networks

The discriminative power of modern deep learning models for 3D human action recognition is growing ever so potent. In conjunction with the recent resurgence of 3D human action representation with 3D skeletons, the quality and the pace of recent progress have been significant. However, the inner workings of state-of-the-art learning based methods in 3D human action recognition still remain mostly black-box. In this work, we propose to use a new class of models known as Temporal Convolutional Neural Networks (TCN) for 3D human action recognition. Compared to popular LSTM-based Recurrent Neural Network models, given interpretable input such as 3D skeletons, TCN provides us a way to explicitly learn readily interpretable spatio-temporal representations for 3D human action recognition. We provide our strategy in re-designing the TCN with interpretability in mind and how such characteristics of the model is leveraged to construct a powerful 3D activity recognition method. Through this work, we wish to take a step towards a spatio-temporal model that is easier to understand, explain and interpret. The resulting model, Res-TCN, achieves state-of-the-art results on the largest 3D human action recognition dataset, NTU-RGBD.Comment: 8 pages, 5 figures, BNMW CVPR 2017 Submissio

Sex-associated differences in baseline urinary metabolites of healthy adults.

The biological basis for gender variability among disease states is not well established. There have been many prior efforts attempting to identify the unique urine metabolomic profiles associated with specific diseases. However, there has been little advancement in investigating the metabolomic differences associated with gender, which underlies the misconception that risk factors and treatment regimens should be the same for both male and female patients. This present study aimed to identify biologically-meaningful baseline sex-related differences using urine samples provided by healthy female and male participants. To elucidate whether urinary metabolic signatures are globally distinct between healthy males and females, we applied metabolomics profiling of primary metabolism with comprehensive bioinformatics analyses on urine samples from 60 healthy males and females. We found that levels of α-ketoglutarate and 4-hydroxybutyric acid increased 2.3-fold and 4.41-fold in males compared to females, respectively. Furthermore, chemical similarity enrichment analysis revealed that differentially expressed metabolites, such as saturated fatty acids, TCA, and butyrates, were significantly related to the gender effect. These findings indicate that there are baseline sex-related differences in urinary metabolism, which should be considered in biomarker discovery, diagnosis, and treatment of bladder diseases, such as interstitial cystitis

Analyzing Multidisciplinary Team Effectiveness in an Engineering Environment: A Case Study of the West Point Steel Bridge Design Team

The West Point Steel Bridge Design Team is a group of five undergraduate seniors working to design and build a steel bridge for the annual ASCE Steel Bridge Competition. The purpose of our group’s research is to discover how multidisciplinary teams perform in academically competitive environments. This project provides a unique opportunity in the field of multidisciplinary collaborative work because the team’s success can be objectively measured against this year’s competitors and the team’s performance in previous years. The traditional structure of the West Point team consisted of three-to-five civil engineering majors. This year’s team includes a law and legal studies major and five civil engineers, two of which recently switched from systems engineering. Past designs have relied heavily on the work of previous years, which has led to stagnant performance at competitions. Our hypothesis is that by entering different perspectives into the group at an early stage, a revolutionary approach will ensue and overall performance will increase. The team did not completely disregard the designs and methods of previous teams, but the reliance on their decision-making process was more heavily scrutinized with the current multidisciplinary team. Our research is not solely limited to competitive performance. We also analyzed the decision-making process of this year’s team in comparison to previous years. While data on decision-making is not readily available, both the faculty advisor and two current team members who served on the team last year were able to provide personal insight into how the teams compare. Ultimately, this research seeks to provide groups in similar academically competitive environments an indication of whether a multidisciplinary composition will provide benefit to their team’s performance.Cockrell School of Engineerin

Origin of micron-scale propagation lengths of heat-carrying acoustic excitations in amorphous silicon

The heat-carrying acoustic excitations of amorphous silicon are of interest because their mean free paths may approach micron scales at room temperature. Despite extensive investigation, the origin of the weak acoustic damping in the heat-carrying frequencies remains a topic of debate. Here, we report measurements of the frequency-dependent mean free path in amorphous silicon thin films from ∼0.1−3 THz and over temperatures from 60 - 315 K using picosecond acoustics and transient grating spectroscopy. The mean free paths are independent of temperature and exhibit a Rayleigh scattering trend from ∼0.3−3 THz, below which the trend is characteristic of damping from density fluctuations or two-level systems. The observed trend is inconsistent with the predictions of numerical studies based on normal mode analysis but agrees with diverse measurements on other glasses. The micron-scale MFPs in amorphous Si arise from the absence of Akhiezer and two-level system damping in the sub-THz frequencies, leading to heat-carrying acoustic excitations with room-temperature damping comparable to that of other glasses at cryogenic temperatures

Origin of micron-scale propagation lengths of heat-carrying acoustic excitations in amorphous silicon

The heat-carrying acoustic excitations of amorphous silicon are of interest because their mean free paths may approach micron scales at room temperature. Despite extensive investigation, the origin of the weak acoustic damping in the heat-carrying frequencies remains a topic of debate. Here, we report measurements of the frequency-dependent mean free path in amorphous silicon thin films from ∼0.1−3 THz and over temperatures from 60 - 315 K using picosecond acoustics and transient grating spectroscopy. The mean free paths are independent of temperature and exhibit a Rayleigh scattering trend from ∼0.3−3 THz, below which the trend is characteristic of damping from density fluctuations or two-level systems. The observed trend is inconsistent with the predictions of numerical studies based on normal mode analysis but agrees with diverse measurements on other glasses. The micron-scale MFPs in amorphous Si arise from the absence of Akhiezer and two-level system damping in the sub-THz frequencies, leading to heat-carrying acoustic excitations with room-temperature damping comparable to that of other glasses at cryogenic temperatures

Development of a real time trimodal spectroscopy diagnostic tool for Barrett's esophagus

Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaves 76-79).Barrett's esophagus (BE) is a condition of the lower esophagus caused by gastroesophageal reflux disease. Patients with BE have an increased probability of developing dysplasia, an abnormal growth or development of cells. This dysplasia in BE is a precursor to cancer of the esophagus, but is currently difficult to detect and diagnose. If the dysplasia is allowed to progress to cancer, it is very difficult to treat successfully. Treatment for dysplasia itself, however, is very effective if done at an early stage. The goal of this thesis project will be to develop a real-time tool that uses spectroscopy to improve upon the methods of detecting dysplasia in BE. This will involve analyzing spectra acquired from patients with BE using models and extracting quantitative information on different aspects of tissue morphology and biochemistry. Using this information, diagnostic algorithms will be developed, optimized and displayed to the physician through a useful interface.by Austin H. Kim.M.Eng.and S.B

"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts

Given the increasing popularity of customer service dialogue on Twitter, analysis of conversation data is essential to understand trends in customer and agent behavior for the purpose of automating customer service interactions. In this work, we develop a novel taxonomy of fine-grained "dialogue acts" frequently observed in customer service, showcasing acts that are more suited to the domain than the more generic existing taxonomies. Using a sequential SVM-HMM model, we model conversation flow, predicting the dialogue act of a given turn in real-time. We characterize differences between customer and agent behavior in Twitter customer service conversations, and investigate the effect of testing our system on different customer service industries. Finally, we use a data-driven approach to predict important conversation outcomes: customer satisfaction, customer frustration, and overall problem resolution. We show that the type and location of certain dialogue acts in a conversation have a significant effect on the probability of desirable and undesirable outcomes, and present actionable rules based on our findings. The patterns and rules we derive can be used as guidelines for outcome-driven automated customer service platforms.Comment: 13 pages, 6 figures, IUI 201