7,864 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Artificial Intelligence, Robots, and Philosophy
This book is a collection of all the papers published in the special issue “Artificial Intelligence, Robots, and Philosophy,” Journal of Philosophy of Life, Vol.13, No.1, 2023, pp.1-146. The authors discuss a variety of topics such as science fiction and space ethics, the philosophy of artificial intelligence, the ethics of autonomous agents, and virtuous robots. Through their discussions, readers are able to think deeply about the essence of modern technology and the future of humanity. All papers were invited and completed in spring 2020, though because of the Covid-19 pandemic and other problems, the publication was delayed until this year. I apologize to the authors and potential readers for the delay. I hope that readers will enjoy these arguments on digital technology and its relationship with philosophy. ***
Contents***
Introduction
: Descartes and Artificial Intelligence;
Masahiro Morioka***
Isaac Asimov and the Current State of Space Science Fiction
: In the Light of Space Ethics;
Shin-ichiro Inaba***
Artificial Intelligence and Contemporary Philosophy
: Heidegger, Jonas, and Slime Mold;
Masahiro Morioka***
Implications of Automating Science
: The Possibility of Artificial Creativity and the Future of Science;
Makoto Kureha***
Why Autonomous Agents Should Not Be Built for War;
István Zoltán Zárdai***
Wheat and Pepper
: Interactions Between Technology and Humans;
Minao Kukita***
Clockwork Courage
: A Defense of Virtuous Robots;
Shimpei Okamoto***
Reconstructing Agency from Choice;
Yuko Murakami***
Gushing Prose
: Will Machines Ever be Able to Translate as Badly as
Humans?;
Rossa Ă“ Muireartaigh**
Pathophysiology of Spinal Cord Injury (SCI)
Spinal cord injury (SCI) leads to paralysis, sensory, and autonomic nervous system dysfunctions. However, the pathophysiology of SCI is complex, and not limited to the nervous system. Indeed, several other organs and tissue are also affected by the injury, directly or not, acutely or chronically, which induces numerous health complications. Although a lot of research has been performed to repair motor and sensory functions, SCI-induced health issues are less studied, although they represent a major concern among patients. There is a gap of knowledge in pre-clinical models studying these SCI-induced health complications that limits translational applications in humans. This reprint describes several aspects of the pathophysiology of spinal cord injuries. This includes, but is not limited to, the impact of SCI on cardiovascular and respiratory functions, bladder and bowel function, autonomic dysreflexia, liver pathology, metabolic syndrome, bones and muscles loss, and cognitive functions
Data Tiling for Sparse Computation
Many real-world data contain internal relationships. Efficient analysis of these relationship data is crucial for important problems including genome alignment, network vulnerability analysis, ranking web pages, among others. Such relationship data is frequently sparse and analysis on it is called sparse computation. We demonstrate that the important technique of data tiling is more powerful than previously known by broadening its application space. We focus on three important sparse computation areas: graph analysis, linear algebra, and bioinformatics. We demonstrate data tiling's power by addressing key issues and providing significant improvements---to both runtime and solution quality---in each area. For graph analysis, we focus on fast data tiling techniques that can produce well-structured tiles and demonstrate theoretical hardness results. These tiles are suitable for graph problems as they reduce data movement and ultimately improve end-to-end runtime performance. For linear algebra, we introduce a new cache-aware tiling technique and apply it to the key kernel of sparse matrix by sparse matrix multiplication. This technique tiles the second input matrix and then uses a small, summary matrix to guide access to the tiles during computation. Our approach results in the fastest known implementation across three distinct CPU architectures. In bioinformatics, we develop a tiling based de novo genome assembly pipeline. We start with reads and develop either a graph or hypergraph that captures internal relationships between reads. This is then tiled to minimize connections while maintaining balance. We then treat each resulting tile independently as the input to an existing, shared-memory assembler. Our pipeline improves existing state-of-the-art de novo genome assemblers and brings both runtime and quality improvements to them on both real-world and simulated datasets.Ph.D
Intelligent computing : the latest advances, challenges and future
Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
Effective Dimension in Bandit Problems under Censorship
In this paper, we study both multi-armed and contextual bandit problems in
censored environments. Our goal is to estimate the performance loss due to
censorship in the context of classical algorithms designed for uncensored
environments. Our main contributions include the introduction of a broad class
of censorship models and their analysis in terms of the effective dimension of
the problem -- a natural measure of its underlying statistical complexity and
main driver of the regret bound. In particular, the effective dimension allows
us to maintain the structure of the original problem at first order, while
embedding it in a bigger space, and thus naturally leads to results analogous
to uncensored settings. Our analysis involves a continuous generalization of
the Elliptical Potential Inequality, which we believe is of independent
interest. We also discover an interesting property of decision-making under
censorship: a transient phase during which initial misspecification of
censorship is self-corrected at an extra cost, followed by a stationary phase
that reflects the inherent slowdown of learning governed by the effective
dimension. Our results are useful for applications of sequential
decision-making models where the feedback received depends on strategic
uncertainty (e.g., agents' willingness to follow a recommendation) and/or
random uncertainty (e.g., loss or delay in arrival of information).Comment: 45 pages, 5 figures, NeurIPS 202
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