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Air pollution has become health hazard. With the growth of industries, the air quality has now become an issue both for the environment as well to the society over the last few years. Due to the rising degradation of air quality, the need for control has risen. Artificial neural network have been applied to many environmental engineering problems and have demonstrated good degree of success in processing...
In order to understand the hydrologie changes in the watersheds due to climate changes, the EPSCoR jurisdictions of Idaho, Nevada, and New Mexico have collaborated to create the Western Consortium for Watershed Analysis, Visualization and Exploration (WC-WAVE). WC-WAVE will create a Virtual Watershed Platform (VWP) framework for assisting watershed scientists in their research. This software environment...
We describe here a simple, inexpensive and effective system for simultaneous evaluation of a subject's driving ability and spatial auditory and visual perception and attention. It consists of a commercial steering wheel and virtual glasses and a program for driving on a two-lane road with curvatures at about 100 km/h speed, and simultaneously reacting by pressing two buttons attached to the steering...
The wide-ranging requirements of computing to support scientific services and research can make the development and maintenance of infrastructure challenging and costly. Numerical simulation and forecasting generally requires a high performance computing environment including high speed, low latency networks supporting parallel execution, whereas the management of output data and analysis of the data...
El diseño de la IU suele ser basado en la experiencia del desarrollador, y por lo tanto de ella depende la calidad del prototipo, uno de los principales métodos usados en el ámbito de la ingeniería para plasmar el conocimiento adquirido por la experiencia es el uso de patrones. En este trabajo se propone un método orientado desde los datos, que permita a partir de una triada formada por patrón de...
As machine learning (ML) becomes increasingly popular, developers without deep experience in ML — who we will refer to as ML practitioners — are facing the need to diagnose problems with ML models. Yet successful diagnosis requires high-level expertise that practitioners lack. As in many complex data-oriented domains, visualization could help. This two-phase study explored the design of visualizations...
To define queries on domain-specific data-structures, end-users have to be familiar with the underlying data model. This is challenging if the data model evolves continuously and through collaborative model management. While visual languages address this issue by providing strong guidance for non-technical end-users, they suffer from a limited expressiveness due to their focus on usability. Therefore,...
Certain professions rely on the ability to maintain attention constant throughout long periods of time, like truck drivers, air traffic controllers, health professionals, among others. These could greatly benefit from the development of a real-time alerting system that will call subjects back to task even before lapses occur or shortly after they happened. Attention levels have been shown to relate...
Technology trends and market changes force modern manufacturing companies to employ complex, standalone mechatronic components for automating their production. The complexity of mechatronic components induces adverse effects on their corrective maintenance. Handling downtime of these components requires knowledge of system composition, effect of external and internal disturbances on the component...
The Data on the Web Best Practices Working Group, as part of W3C Data Activity, is standardizing the Data Quality Vocabulary (DQV) for expressing data quality of datasets published on the Web. By exploiting such DQV-based quality metadata associated to the datasets in a data portal, data consumers can achieve data quality-based filtering and ranking of datasets on the portal's conventional search...
BGM (background music) of a video plays an important role for making a video impressive. Although a large number of royalty-free music clips are available on the web, it is still difficult for amateur video creators to select appropriate music clips for their videos. In this paper, we propose a computational method for estimating the impression of a video from auditory and visual features of a video...
In this study, we make use of brain activation data to investigate the perceptual plausibility of a visual and an auditory model for visual and auditory saliency in video processing. These models have already been successfully employed in a number of applications. In addition, we experiment with parameters, modifications and suitable fusion schemes. As part of this work, fMRI data from complex video...
Zero shot learning (ZSL) provides a solution to recognising unseen classes without class labelled data for model learning. Most ZSL methods aim to learn a mapping from a visual feature space to a semantic embedding space, e.g. attribute or word vector spaces. The use of word vector space is particularly attractive as compared to attribute, it offers vast auxiliary classes with free parts embedding...
Most existing person re-identification (ReID) methods assume the availability of extensively labelled cross-view person pairs and a closed-set scenario (i.e. all the probe people exist in the gallery set). These two assumptions significantly limit their usefulness and scalability in real-world applications, particularly with large scale camera networks. To overcome the limitations, we introduce a...
In complex visual recognition systems, feature fusion has become crucial to discriminate between a large number of classes. In particular, fusing high-level context information with image appearance models can be effective in object/scene recognition. To this end, we develop an auto-context modeling approach under the RKHS (Reproducing Kernel Hilbert Space) setting, wherein a series of supervised...
The growth of digital data is tremendous. Any aspect of life and matter is being recorded and stored on cheap disks, either in the cloud, in businesses, or in research labs. We can now afford to explore very complex relationships with many variables playing a part. But for this we need powerful tools that allow us to be creative, to sculpt this intricate insight formulated as models from the raw block...
This study focused on driver behavior by inferring it from driving recorder data. We refer to this inference function as meta-cognition. Using this meta-cognition, we attempt to determine the characteristics of driver behavior on the highway. By comparing ACTR simulation results and recorder data, we investigated the driver cognitive process in highway driving in response to lane keeping, curve negotiation,...
In our study, we sought to generate rules for cognitive distractions of car drivers using data from a driving simulation environment. We collected drivers' eye-movement and driving data from 18 research participants using a simulator. Each driver drove the same 15-minute course two times. The first drive was normal driving (no-load driving), and the second drive was driving with a mental arithmetic...
This paper proposes a novel dynamic Hierarchical Dirichlet Process topic model that considers the dependence between successive observations. Conventional posterior inference algorithms for this kind of models require processing of the whole data through several passes. It is computationally intractable for massive or sequential data. We design the batch and online inference algorithms, based on the...
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