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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
A Systemic Mapping Study On Intrusion Response Systems, Adel Rezapour, Mohammad Ghasemigol, Daniel Takabi
A Systemic Mapping Study On Intrusion Response Systems, Adel Rezapour, Mohammad Ghasemigol, Daniel Takabi
School of Cybersecurity Faculty Publications
With the increasing frequency and sophistication of network attacks, network administrators are facing tremendous challenges in making fast and optimum decisions during critical situations. The ability to effectively respond to intrusions requires solving a multi-objective decision-making problem. While several research studies have been conducted to address this issue, the development of a reliable and automated Intrusion Response System (IRS) remains unattainable. This paper provides a Systematic Mapping Study (SMS) for IRS, aiming to investigate the existing studies, their limitations, and future directions in this field. A novel semi-automated research methodology is developed to identify and summarize related works. The innovative …
Embok 5.0 - Industry 4.0/5.0 Manifest And Latent Dimensions Mapping To The Asem Embok, T. Steven Cotter
Embok 5.0 - Industry 4.0/5.0 Manifest And Latent Dimensions Mapping To The Asem Embok, T. Steven Cotter
Engineering Management & Systems Engineering Faculty Publications
Industry 3.0 automation emerged replacing human labor with high volume processes and robotics. Industry 4.0, cyber-physical systems, and Industry 5.0, mass customization and cognitive systems, are in the early stages of emergence. Research into the impact of Industry 4.0 and 5.0 is focused at the strategic or organizational levels or on the technological challenges. Research into the impact of Industry 4.0 and 5.0 on engineering management has been limited to their impact on project management. This leaves open the question of the directions in which ASEM should evolve the Engineering Management Body of Knowledge (EMBOK) under the emergence of Industry …
Unsupervised Automatic Speech Recognition: A Review, Hanan Aldarmaki, Asad Ullah, Sreepratha Ram, Nazar Zaki
Unsupervised Automatic Speech Recognition: A Review, Hanan Aldarmaki, Asad Ullah, Sreepratha Ram, Nazar Zaki
Natural Language Processing Faculty Publications
Automatic Speech Recognition (ASR) systems can be trained to achieve remarkable performance given large amounts of manually transcribed speech, but large labeled data sets can be difficult or expensive to acquire for all languages of interest. In this paper, we review the research literature to identify models and ideas that could lead to fully unsupervised ASR, including unsupervised sub-word and word modeling, unsupervised segmentation of the speech signal, and unsupervised mapping from speech segments to text. The objective of the study is to identify the limitations of what can be learned from speech data alone and to understand the minimum …
Research Of Liver Solid Texture Synthesis And Mapping Method With Cuda Acceleration, Guodong Chen, Hanxin He
Research Of Liver Solid Texture Synthesis And Mapping Method With Cuda Acceleration, Guodong Chen, Hanxin He
Journal of System Simulation
Abstract: A liver solid texture synthesis and mapping method based on Computer Unified Device Architecture acceleration (CUDA) was proposed to solve the problem of the overlong time consuming within the period of synthesizing liver solid texture in traditional way. The relevance in traditional serial texture synthesis was elim inated in the new method. The work of selecting and distributing blocks of space synthesis of the liver solid texture was processed by using the parallel processing of multiple threads based on CUDA. Both the procedures of tinting the surface grid nodes of liver model and internal point set traversal in mapping …
A Deep Learning Approach To Mapping Irrigation: U-Net Irrmapper, Thomas Henry Colligan Iv
A Deep Learning Approach To Mapping Irrigation: U-Net Irrmapper, Thomas Henry Colligan Iv
Graduate Student Theses, Dissertations, & Professional Papers
Accurate maps of irrigation are essential for understanding and managing water resources in light of a warming climate. We present a new method for mapping irrigation and apply it to the state of Montana over the years 2000-2019. The method is based on an ensemble of convolutional neural networks that only rely on raw Landsat surface reflectance data. The ensemble of networks method learns to mask clouds and ignore Landsat 7 scan-line failures without supervision, reducing the need for preprocessing data or feature engineering. Unlike other approaches to mapping irrigation, the method doesn't use other mapping products like the Cropland …
Learning To Map The Visual And Auditory World, Tawfiq Salem
Learning To Map The Visual And Auditory World, Tawfiq Salem
Theses and Dissertations--Computer Science
The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training …
Computer Vision Evidence Supporting Craniometric Alignment Of Rat Brain Atlases To Streamline Expert-Guided, First-Order Migration Of Hypothalamic Spatial Datasets Related To Behavioral Control, Arshad M. Khan, Jose G. Perez, Claire E. Wells, Olac Fuentes
Computer Vision Evidence Supporting Craniometric Alignment Of Rat Brain Atlases To Streamline Expert-Guided, First-Order Migration Of Hypothalamic Spatial Datasets Related To Behavioral Control, Arshad M. Khan, Jose G. Perez, Claire E. Wells, Olac Fuentes
Arshad M. Khan, Ph.D.
Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger
Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger
Theses and Dissertations--Computer Science
Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship …
Recognition Of Quadric Surfaces From Range Data: An Analytical Approach, Ivan X. D. D'Cunha
Recognition Of Quadric Surfaces From Range Data: An Analytical Approach, Ivan X. D. D'Cunha
Electrical & Computer Engineering Theses & Dissertations
In this dissertation, a new technique based on analytic geometry for the recognition and description of three-dimensional quadric surfaces from range images is presented. Beginning with the explicit representation of quadrics, a set of ten coefficients are determined for various three-dimensional surfaces. For each quadric surface, a unique set of two-dimensional curves which serve as a feature set is obtained from the various angles at which the object is intersected with a plane. Based on a discriminant method, each of the curves is classified as a parabola, circle, ellipse, hyperbola, or a line. Each quadric surface is shown to be …