Cloud-Based Deep Learning: End-To-End Full-Stack Handwritten Digit Recognition

Herein, we present Stratus, an end-to-end full-stack deep learning application deployed on the cloud. The rise of productionized deep learning necessitates infrastructure in the cloud that can provide such service (IaaS). In this paper, we explore the use of modern cloud infrastructure and micro-services to deliver accurate and high-speed predictions to an end-user, using a Deep Neural Network (DNN) to predict handwritten digit input, interfaced via a full-stack application. We survey tooling from Spark ML, Apache Kafka, Chameleon Cloud, Ansible, Vagrant, Python Flask, Docker, and Kubernetes in order to realize this machine learning pipeline. Through our cloud-based approach, we are able to demonstrate benchmark performance on the MNIST dataset with a deep learning model

Microwave Enhanced Combustion on a Constant Volume Combustion Chamber for Lean Combustion and EGR Dilution

The effect of microwave enhancement on combustion was investigated using a spherical, constant-volume combustion chamber. Microwave energy at 2.45 GHz was coupled into the spherical chamber using a quarter-wavelength dipole antenna. Standing waves of high-strength electrical fields were created to enhance the flames ignited by a spark plug. Pressure traces of combustion with and without microwaves were recorded to compare the combustion improvements. Microwave power levels and discharge durations were also varied to understand their impact on the level of improvement. Results indicated that the microwave system can effectively accelerate combustion and improve cycle stability for dilute combustion, including lean burn at about 0.8 equivalence ratio and stoichiometric operation with 20% exhaust gas recirculation (EGR) dilution

Advanced Endoscopic Navigation:Surgical Big Data,Methodology,and Applications

随着科学技术的飞速发展，健康与环境问题日益成为人类面临的最重大问题之一。信息科学、计算机技术、电子工程与生物医学工程等学科的综合应用交叉前沿课题，研究现代工程技术方法，探索肿瘤癌症等疾病早期诊断、治疗和康复手段。本论文综述了计算机辅助微创外科手术导航、多模态医疗大数据、方法论及其临床应用：从引入微创外科手术导航概念出发，介绍了医疗大数据的术前与术中多模态医学成像方法、阐述了先进微创外科手术导航的核心流程包括计算解剖模型、术中实时导航方案、三维可视化方法及交互式软件技术，归纳了各类微创外科手术方法的临床应用。同时，重点讨论了全球各种手术导航技术在临床应用中的优缺点，分析了目前手术导航领域内的最新技术方法。在此基础上，提出了微创外科手术方法正向数字化、个性化、精准化、诊疗一体化、机器人化以及高度智能化的发展趋势。【Abstract】Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.X.L. acknowledges funding from the Fundamental Research Funds for the Central Universities. T.M.P. acknowledges funding from the Canadian Foundation for Innovation, the Canadian Institutes for Health Research, the National Sciences and Engineering Research Council of Canada, and a grant from Intuitive Surgical Inc

70 DA White Dwarfs Identified in Lamost Pilot Survey

We present a spectroscopically identified catalog of 70 DA white dwarfs (WDs) from the LAMOST pilot survey. Thirty-five are found to be new identifications after cross-correlation with the Eisenstein et al. and Villanova catalogs. The effective temperature and gravity of these WDs are estimated by Balmer lines fitting. Most of them are hot WDs. The cooling times and masses of these WDs are estimated by interpolation in theoretical evolution tracks. The peak of the mass distribution is found to be ∼0.6M, which is consistent with prior work in the literature. The distances of these WDs are estimated using the method of synthetic spectral distances. All of these WDs are found to be in the Galactic disk from our analysis of space motions. Our sample supports the expectation that WDs with high mass are concentrated near the plane of the Galactic disk

Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection. If we can intelligently track healthcare staff, patients, and visitors, we can better understand the sources of such infections. We envision a smart hospital capable of increasing operational efficiency and improving patient care with less spending. In this paper, we propose a non-intrusive vision-based system for tracking people's activity in hospitals. We evaluate our method for the problem of measuring hand hygiene compliance. Empirically, our method outperforms existing solutions such as proximity-based techniques and covert in-person observational studies. We present intuitive, qualitative results that analyze human movement patterns and conduct spatial analytics which convey our method's interpretability. This work is a step towards a computer-vision based smart hospital and demonstrates promising results for reducing hospital acquired infections.Comment: Machine Learning for Healthcare Conference (MLHC

Neuroprotective effects and mechanism of cognitive-enhancing choline analogs JWB 1-84-1 and JAY 2-22-33 in neuronal culture and Caenorhabditis elegans

<p>Abstract</p> <p>Background</p> <p>Our previous work indicated that novel analogs of choline have cytoprotective effects <it>in vitro </it>that might be useful in neurodegenerative conditions such as Alzheimer's disease (AD). Furthermore, two lead compounds (JWB1-84-1 and JAY2-22-33) from a library of more than 50 improved cognitive performances in a transgenic mouse model of AD. The purpose of these experiments was to more specifically investigate the neuroprotective capabilities of these lead compounds both <it>in vitro </it>and <it>in vivo</it>.</p> <p>Results</p> <p>We used N2a cells which express a Swedish mutation in the amyloid precursor protein and presenilin 1 genes to investigate the effect of JWB1-84-1 and JAY2-22-33 on β-amyloid (Aβ) levels and found that both compounds significantly reduced Aβ levels. JWB1-84-1 and JAY2-22-33 also protected rat primary cortical neurons from Aβ toxicity. Subsequently, we utilized the nematode <it>Caenorhabditis elegans </it>(<it>C. elegans</it>) as an <it>in vivo </it>model organism to identify potential molecular targets of these compounds. In the <it>C. elegans </it>model of Aβ toxicity, human Aβ is expressed intracellularly in the body wall muscle. The expression and subsequent aggregation of Aβ in the muscle leads to progressive paralysis.</p> <p>Conclusion</p> <p>We found that JAY2-22-33 (but not JWB1-84-1) significantly reduced Aβ toxicity by delaying paralysis and this protective effect required both the insulin signaling pathway and nicotinic acetylcholine receptors (nAChRs).</p