SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams

Learning from demonstration (LfD) and imitation learning offer new paradigms for transferring task behavior to robots. A class of methods that enable such online learning require the robot to observe the task being performed and decompose the sensed streaming data into sequences of state-action pairs, which are then input to the methods. Thus, recognizing the state-action pairs correctly and quickly in sensed data is a crucial prerequisite for these methods. We present SA-Net a deep neural network architecture that recognizes state-action pairs from RGB-D data streams. SA-Net performed well in two diverse robotic applications of LfD -- one involving mobile ground robots and another involving a robotic manipulator -- which demonstrates that the architecture generalizes well to differing contexts. Comprehensive evaluations including deployment on a physical robot show that \sanet{} significantly improves on the accuracy of the previous method that utilizes traditional image processing and segmentation.Comment: (in press

Gendered narratives of alcohol/drug consumption and violent nationalism in India

Alcoholism and drug addiction have come to be regarded as psychological and social disorders in recent times. The international diagnostic system ICD (International Classification of Diseases) provides a diagnosis for severe cases of alcoholism/addiction that meet clinical standards. However, the consumption of these substances even recreationally has been challenged. In the case of India the problem of alcohol and drug consumption is tied to nationalism and is gendered. My work in a rehabilitation clinic in India introduced me to learning about the non-clinical side of the condition. While literature from around the world supports the idea that female alcoholics and addicts in recovery are treated differently by medical staff, it does not look at how some of these narratives about the addict are sometimes tied to the prejudice against the substances themselves. This leads to the research question - How are gendered narratives of alcohol and drug consumption represented in Indian society in general, and Bollywood movies in particular. The thesis also explores to what extent, if any, such representations relate to the rise of violent nationalism within Indian society. Tracing the history back to the disease model that has come to dominate our understanding of the condition, one can observe that these diagnostic criteria have been evolving, as has the social milieu that creates these breaches in normality. I am not looking at the clinical diagnosis itself but at the fears that surround addiction narratives. These narratives are to be found in everyday life, in cinema, in policy, in crime. The ‘addict’ is not only a clinical being but tells a different story which varies according to the identity that they embody. Women in India who transgress boundaries of ‘culture’ are often at risk of being sexualised even by their recreational use of psychoactive substances. These narratives are present everywhere, especially in cinema. The work of postcolonial theorists such as Ashis Nandy and Partha Chatterjee is used to trace a nationalistic discourse, that in recent years has turned violent, providing a critique of the modern Indian state. Writing by black feminists such as Audre Lorde, bell hooks and Gloria Anzaldúa provide another critique and that is of gender and race in opposition to culture. The methodology used (eccletic, feminist and discourse analysis) positions me as a researcher not a neutral bystander, but entrenched in and participating in the production of knowledge that makes me question my privilege. Bollywood films have been used to trace these gendered, nationalistic and violent narratives. I show how a popular form of entertainment is also used as a means of propaganda. Cinema in India is an important medium of communication that permeates most aspects of our lives. Widely imitated for its fashion, dialogues and ideology too are imitated. Similar to cinema around the world, Bollywood uses tropes, westernised women who consume drugs and alcohol is one such trope. Reading the discourse that runs through these films reveals there is subversion in the way in which women’s bodies are exploited on screen yet a guise of decency is maintained. The discourse that runs on screen through films is similar to incidents of violence against women in everyday life. Nationalism runs through these narratives, as does gendered violence

Agent-Based Simulation Disaster Evacuation Awareness on Night Situation in Aceh

In 2004 at least 230,000 people were victims of the Aceh tsunami disaster. To prevent the recurrence of many victims, the Aceh government held an evacuation exercise in 2008. To improve effectiveness dan reduce the cost reduction during evacuations drills, simulation is the best option. Agent-Based Modeling is a simulation program that was employed for tsunami evacuation in Aceh. This study on tsunami evacuation using agent-based modelling presented and evaluated the different control parameters that affect the evacuation rate. Evacuation scenario during day or night has different environmental, agent base, road modelling, and population approach. The Road Network Model has explained that to analyze the effect of agents in the evacuation process, resident agents are presumed to know the direction and shortest path to the nearest evacuation points. This simulation designed in Netlogo is also able to assess the congestion possibility on the road network. The road network emphasized the different scenarios to discover the possibility of congestion points. Nighttime is proven to be the best scenario for performing the evacuation in the simulation. The key reason to select the night scenario is to maximize the effects of an evaluation of the road network. In addition, simulation using night scenarios is also expected to raise people’s awareness

A Conversation With Luis Argueta

Synopsis: An interview with filmmaker Luis Argueta during his visit to UNI on October 13, 2017. Students from the Digital Media Production II class, taught by Professor Francesca Soans, planned, recorded, and edited the interview, as part of a 30-minute television show on immigration. Luis Argueta directed a trilogy on immigration in Iowa: AbUSed: The Postville Raid (2010); ABRAZOS (2014); and The U-Turn (2017)

What Are Little Girls Made Of?

What Are Little Girls Made Of? is a postcolonial exploration of nursery rhymes in which animation and the textures of personal memories are ironically juxtaposed to comment on the continued legacy of European cultural colonialism in India. As an Indian woman reminisces about growing up in India, a child’s drawing unfolds on the screen, narrating the well-known English nursery rhyme, “Little Miss Muffet.” The woman recalls her deep desire for a white dress and blond hair, as her own dark skin relegates her to the position of “boy” in school plays. The memories, seemingly nostalgic, are juxtaposed with an ironic depiction of a blond Miss Muffet’s encounter with the “other”—the spider—inside herself. Through this juxtaposition, a dissonance is set up between the memories and the animation, providing a commentary on western standards of beauty and the legacy of cultural colonialism in India. Mixing computer animation, video, and interview footage, this video explores the fictionalization of documentary memory through animated drawings that reflect the subjectivity of the memories being narrated. Through this, the video challenges conventional forms of documentary

REASONS FOR PATIENT DELAYS & HEALTH SYSTEM DELAYS FOR TUBERCULOSIS IN SOUTH INDIA

Background: Globally, the burden of Tuberculosis is escalating. Early diagnosis and prompt initiation of tuberculosis treatment is essential for an effective tuberculosis control programme. Objectives: To study the self reported reasons for patient and health system (diagnosis & treatment) delays in Tuberculosis patients. Methods: A community based cross sectional study was conducted among 98 new sputum positive TB cases aged > 15 years registered under RNTCP from Oct 2006 to June 2007 & receiving treatment under DOTS in Udupi taluk by interviewing them. Results: Total 98 patients were recruited and 68% were males. Out of 17 patients with patient delays, 82% felt that their symptoms were not severe, 71% felt that patient delay was due to lack of awareness and 71% did not take it seriously. Out of 86 patients with health system delays, 82.6% of patients mentioned that doctor has not advised for sputum examination, 76.7% of patients told that they first consulted a private doctor, 21% of them mentioned that doctor was unaware to diagnose TB. Conclusion: Symptoms not severe is the main reason for the patient delay and doctor didn’t advise for sputum examination is the main reason for health system delays

Patients Prefer a Virtual Reality Approach Over a Similarly Performing Screen-Based Approach for Continuous Oculomotor-Based Screening of Glaucomatous and Neuro-Ophthalmological Visual Field Defects

Standard automated perimetry (SAP) is the gold standard for evaluating the presence of visual field defects (VFDs). Nevertheless, it has requirements such as prolonged attention, stable fixation, and a need for a motor response that limit application in various patient groups. Therefore, a novel approach using eye movements (EMs) – as a complementary technique to SAP – was developed and tested in clinical settings by our group. However, the original method uses a screen-based eye-tracker which still requires participants to keep their chin and head stable. Virtual reality (VR) has shown much promise in ophthalmic diagnostics – especially in terms of freedom of head movement and precise control over experimental settings, besides being portable. In this study, we set out to see if patients can be screened for VFDs based on their EM in a VR-based framework and if they are comparable to the screen-based eyetracker. Moreover, we wanted to know if this framework can provide an effective and enjoyable user experience (UX) compared to our previous approach and the conventional SAP. Therefore, we first modified our method and implemented it on a VR head-mounted device with built-in eye tracking. Subsequently, 15 controls naïve to SAP, 15 patients with a neuro-ophthalmological disorder, and 15 glaucoma patients performed three tasks in a counterbalanced manner: (1) a visual tracking task on the VR headset while their EM was recorded, (2) the preceding tracking task but on a conventional screen-based eye tracker, and (3) SAP. We then quantified the spatio-temporal properties (STP) of the EM of each group using a cross-correlogram analysis. Finally, we evaluated the human–computer interaction (HCI) aspects of the participants in the three methods using a user-experience questionnaire. We find that: (1) the VR framework can distinguish the participants according to their oculomotor characteristics; (2) the STP of the VR framework are similar to those from the screen-based eye tracker; and (3) participants from all the groups found the VR-screening test to be the most attractive. Thus, we conclude that the EM-based approach implemented in VR can be a user-friendly and portable companion to complement existing perimetric techniques in ophthalmic clinics

Deep learning-based Segmentation of Rabbit fetal skull with limited and sub-optimal annotations

In this paper, we propose a deep learning-based method to segment the skeletal structures in the micro-CT images of Dutch-Belted rabbit fetuses which can assist in the assessment of drug-induced skeletal abnormalities as a required study in developmental and reproductive toxicology (DART). Our strategy leverages sub-optimal segmentation labels of 22 skull bones from 26 micro-CT volumes and maps them to 250 unlabeled volumes on which a deep CNN-based segmentation model is trained. In the experiments, our model was able to achieve an average Dice Similarity Coefficient (DSC) of 0.89 across all bones on the testing set, and 14 out of the 26 skull bones reached average DSC >0.93. Our next steps are segmenting the whole body followed by developing a model to classify abnormalities.Comment: Accepted short paper - MIDL 202

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system\u27s use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications