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Distribution of Value of Time and Ways to Model Value of Time in Long-Range Planning Models
As managed lanes (ML) become more integrated in regional urban networks with existing general purpose (GP) lanes, the distribution of travelers’ value of time (VOT) is becoming more important for transportation planning agencies to quantify in order to accurately predict future travel patterns. Since travelers’ VOT varies depending on a multitude of factors, this study investigates ways that we can determine the VOT distribution of a region from existing travel data as well as effective ways that we can model VOT using traffic assignment algorithms. In networks with available link volumes and toll data on segments where travelers have the option of choosing to stay on the GP lanes or entering a ML facility, a VOT distribution can be inferred assuming that travelers who enter the ML choose to do so based on a certain “threshold” VOT. When modeling these VOT distributions, errors are observed in the traffic assignment results when both the continuous nature of VOT distributions are discretized, and when varying toll values are assumed to be constant. Specifically in the context of TransCAD software, link travel time errors appear to be much less significant than flow errors when tested on a nine node network. Additional experimentation on larger regional networks is needed to verify the significance of these errors and their impact on predicted travel patterns.Civil, Architectural, and Environmental Engineerin
Memristor Crossbar-based Hardware Implementation of IDS Method
Ink Drop Spread (IDS) is the engine of Active Learning Method (ALM), which is
the methodology of soft computing. IDS, as a pattern-based processing unit,
extracts useful information from a system subjected to modeling. In spite of
its excellent potential in solving problems such as classification and modeling
compared to other soft computing tools, finding its simple and fast hardware
implementation is still a challenge. This paper describes a new hardware
implementation of IDS method based on the memristor crossbar structure. In
addition of simplicity, being completely real-time, having low latency and the
ability to continue working after the occurrence of power breakdown are some of
the advantages of our proposed circuit.Comment: 16 pages, 13 figures, Submitted to IEEE Transaction on Fuzzy System
An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones
Drone susceptibility to jamming or spoofing attacks of GPS, RF, Wi-Fi, and
operator signals presents a danger to future medical delivery systems. A
detection framework capable of sensing attacks on drones could provide the
capability for active responses. The identification of interference attacks has
applicability in medical delivery, disaster zone relief, and FAA enforcement
against illegal jamming activities. A gap exists in the literature for solo or
swarm-based drones to identify radio frequency spectrum attacks. Any
non-delivery specific function, such as attack sensing, added to a drone
involves a weight increase and additional complexity; therefore, the value must
exceed the disadvantages. Medical delivery, high-value cargo, and disaster zone
applications could present a value proposition which overcomes the additional
costs. The paper examines types of attacks against drones and describes a
framework for designing an attack detection system with active response
capabilities for improving the reliability of delivery and other medical
applications.Comment: 7 pages, 1 figures, 5 table
Artificial intelligence in the cyber domain: Offense and defense
Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41
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