Deep Learning in the Automotive Industry: Applications and Tools

Deep Learning refers to a set of machine learning techniques that utilize neural networks with many hidden layers for tasks, such as image classification, speech recognition, language understanding. Deep learning has been proven to be very effective in these domains and is pervasively used by many Internet services. In this paper, we describe different automotive uses cases for deep learning in particular in the domain of computer vision. We surveys the current state-of-the-art in libraries, tools and infrastructures (e.\,g.\ GPUs and clouds) for implementing, training and deploying deep neural networks. We particularly focus on convolutional neural networks and computer vision use cases, such as the visual inspection process in manufacturing plants and the analysis of social media data. To train neural networks, curated and labeled datasets are essential. In particular, both the availability and scope of such datasets is typically very limited. A main contribution of this paper is the creation of an automotive dataset, that allows us to learn and automatically recognize different vehicle properties. We describe an end-to-end deep learning application utilizing a mobile app for data collection and process support, and an Amazon-based cloud backend for storage and training. For training we evaluate the use of cloud and on-premises infrastructures (including multiple GPUs) in conjunction with different neural network architectures and frameworks. We assess both the training times as well as the accuracy of the classifier. Finally, we demonstrate the effectiveness of the trained classifier in a real world setting during manufacturing process.Comment: 10 page

Composting Swine Manure from High Rise Finishing Facilities

Swine production has restructured considerably in recent years with increased production on fewer farms (Key et al., 2011). Most swine production facilities manage manure in liquid form either in deep pits underneath production facilities or in lagoons adjacent to the production facilities (Key et al., 2011). This management uses water to rinse manure from the facilities, which dilutes the nutrient concentration and value of the manure. The liquid forms are applied to land through irrigation systems or by liquid manure spreaders. Liquid manure management can have some operational constraints that composting eliminates (Bernal et al., 2009). The most common issue with handling liquid manure is that the manure has diluted nutrients and it is often not economical to transport large volumes of lagoon effluent to off‐site locations. Surface spreading through an irrigator is commonly used, but wet environments can delay application. Odor can be a concern if liquid manure is surface applied and not incorporated; and although soil incorporation does reduce manure odors, they can still be a concern

The design of a sampling mill to treat a south east Missouri lead ore

The purpose of the work that was undertaken in preparing this thesis was to provide plans and specifications for a sampling mill to be erected by the St. Louis Smelting and Refining Co. at their plant near St. Francois, Mo... It was intended at the outset to design the plant completely and to provide full working drawings and specifications for all parts of the mill. On account of the lack of time, however, it has been found necessary to somewhat reduce the amount of work. As a result only general plans and specifications with a few of the more important details are contained in the finished thesis --Thesis Subject, pages 1-2

Using Big Data to Optimally Develop Water Quality Temperature

2010 S.C. Water Resources Conference - Science and Policy Challenges for a Sustainable Futur

Estimation of Tidal Marsh Loading Effects in a Complex Estuary

2010 S.C. Water Resources Conference - Science and Policy Challenges for a Sustainable Futur

Nuclear Astrophysics Before 1957

I discuss especially my summer with Willy Fowler at Kellogg Radiation in 1951, where I did my "triple-alpha" work. I also go back even earlier to Arthur Eddington and Hans Bethe. I also mention the 1953 summer school in Ann Arbor.Comment: 16 page

Saccadic eye movement abnormalities in autism spectrum disorder indicate dysfunctions in cerebellum and brainstem

BACKGROUND: Individuals with autism spectrum disorder (ASD) show atypical scan paths during social interaction and when viewing faces, and recent evidence suggests that they also show abnormal saccadic eye movement dynamics and accuracy when viewing less complex and non-social stimuli. Eye movements are a uniquely promising target for studies of ASD as their spatial and temporal characteristics can be measured precisely and the brain circuits supporting them are well-defined. Control of saccade metrics is supported by discrete circuits within the cerebellum and brainstem - two brain regions implicated in magnetic resonance (MR) morphometry and histopathological studies of ASD. The functional integrity of these distinct brain systems can be examined by evaluating different parameters of visually-guided saccades. METHODS: A total of 65 participants with ASD and 43 healthy controls, matched on age (between 6 and 44-years-old), gender and nonverbal IQ made saccades to peripheral targets. To examine the influence of attentional processes, blocked gap and overlap trials were presented. We examined saccade latency, accuracy and dynamics, as well as the trial-to-trial variability of participants’ performance. RESULTS: Saccades of individuals with ASD were characterized by reduced accuracy, elevated variability in accuracy across trials, and reduced peak velocity and prolonged duration. In addition, their saccades took longer to accelerate to peak velocity, with no alteration in the duration of saccade deceleration. Gap/overlap effects on saccade latencies were similar across groups, suggesting that visual orienting and attention systems are relatively spared in ASD. Age-related changes did not differ across groups. CONCLUSIONS: Deficits precisely and consistently directing eye movements suggest impairment in the error-reducing function of the cerebellum in ASD. Atypical increases in the duration of movement acceleration combined with lower peak saccade velocities implicate pontine nuclei, specifically suggesting reduced excitatory activity in burst cells that drive saccades relative to inhibitory activity in omnipause cells that maintain stable fixation. Thus, our findings suggest that both cerebellar and brainstem abnormalities contribute to altered sensorimotor control in ASD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2040-2392-5-47) contains supplementary material, which is available to authorized users