Usability of Urban Air Mobility: Quantitative and Qualitative Assessments of Usage in Emergency Situations

The purpose of these four studies was to determine participants’ willingness to support the use of urban air mobility (UAM) in response to natural disasters, along with the preferred locations to establish vertiports. Study 1 assessed the willingness to support using a mixed factorial design. The findings demonstrated strong, robust support for the use of UAM when responding to natural disasters. Study 2 worked to create and validate a scale that could assess vertiports\u27 current and proposed locations. The Vertiport Usability Scale was developed and shown to have strong psychometric properties to validly assess vertiport locations through a multi-stage process. Study 3 used the Vertiport Usability Scale to understand the most highly preferred locations for vertiports in three conditions from a multi-stage process: temporary disaster locations, permanent disaster locations, and permanent consumer locations. Study 4 was conducted using qualitative methods to complement the earlier quantitative approaches. Through an initial survey and follow-on interview, three themes emerged related to UAM in response to natural disasters and vertiports: 1) human involvement in UAM operations, 2) scenarios for usage, and 3) setup and deployment of vehicles

Artificial Intelligence Through the Eyes of the Public

Artificial Intelligence is becoming a popular field in computer science. In this report we explored its history, major accomplishments and the visions of its creators. We looked at how Artificial Intelligence experts influence reporting and engineered a survey to gauge public opinion. We also examined expert predictions concerning the future of the field as well as media coverage of its recent accomplishments. These results were then used to explore the links between expert opinion, public opinion and media coverage

ADOPTION AND UTILISATION OF ARTIFICIAL INTELLIGENCE BY LIBRARIANS IN UNIVERSITY LIBRARIES IN SOUTHERN NIGERIA

The study investigated how librarians working in the various university libraries in Southern Nigeria adopted and used artificial intelligence. The researcher was able to retrieve 704 copies of the 848 questionnaires that were given to the responders. However, the return rate was 83%, which is a respectable amount. The descriptive statistics approach was used to analyse the data that the questionnaire produced. The results showed that there has been little adoption of AI in university libraries in Southern Nigeria. The research also reveals that security scanning devices at university libraries\u27 entrances and exits are the most prevalent AIs, while other AIs like robots, chatbots, face recognition, touch recognition, RFID technologies, humanoids, AI classification tools, machine-readable catalogues, and AI smart features are still lacking in Southern Nigeria\u27s university libraries. The results of this study also suggest that the university library\u27s librarians are knowledgeable about the many ways that AI may be applied to provide services. The study\u27s findings indicate that adoption hurdles include considerable disruption brought on by AI to conventional library services, a lack of skills and the need for training prior to adoption, erratic power supply, a lack of suitable infrastructure for adoption, among other problems. It was recommended in the study that training should be organized for librarians to boost their skills in the use of AI for service delivery and university and library management should be committed and give the needed support towards the adoption of AI by making available the needed infrastructure to ensure their swift implementatio

Exploring Concepts of Operations for On-Demand Passenger Air Transportation

In recent years, a surge of interest in "flying cars" for city commutes has led to rapid development of new technologies to help make them and similar on-demand mobility platforms a reality. To this end, this paper provides analyses of the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Three system architectures emerged from the analyses, ranging from conventional air taxi to revolutionary fully autonomous aircraft operations, each with vehicle safety functions allocated differently between humans and machines. Advancements for enabling technologies such as distributed electric propulsion and artificial intelligence have had major investments and initial experimental success, but may be some years away from being deployed for on-demand passenger air transportation at scale

Cyber-Physical Embedded Systems with Transient Supervisory Command and Control: A Framework for Validating Safety Response in Automated Collision Avoidance Systems

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness of its design. However, by using both human and machine agency at different levels of automation, or autonomy, the levels of automation have profound implications and affects to the reliability and safety of the CPS. The human-agent and the machine-agent are in a tidal lock of decision-making using both feedforward and feedback information flows in similar processes, where a transient shift within the level of automation when the CPS is operating can have undesired consequences. As CPS systems become more common, and higher levels of autonomy are embedded within them, the relationship between human-agent and machine-agent also becomes more complex, and the testing methodologies for verification and validation of performance and correctness also become more complex and less clear. A framework then is developed to help the practitioner to understand the difficulties and pitfalls of CPS designs and provides guidance to test engineering design of soft computational systems using combinations of modeling, simulation, and prototyping

The Algorithmic Divide and Equality in the Age of Artificial Intelligence

In the age of artificial intelligence, highly sophisticated algorithms have been deployed to provide analysis, detect patterns, optimize solutions, accelerate operations, facilitate self-learning, minimize human errors and biases and foster improvements in technological products and services. Notwithstanding these tremendous benefits, algorithms and intelligent machines do not provide equal benefits to all. Just as the digital divide has separated those with access to the Internet, information technology and digital content from those without, an emerging and ever-widening algorithmic divide now threatens to take away the many political, social, economic, cultural, educational and career opportunities provided by machine learning and artificial intelligence.Although policy makers, commentators and the mass media have paid growing attention to algorithmic bias and the shortcomings of machine learning and artificial intelligence, the algorithmic divide has yet to attract much policy and scholarly attention. To fill this lacuna, this article draws on the digital divide literature to systematically analyze this new inequitable gap between the technology haves and have-nots. Utilizing an analytical framework that the Author developed in the early 2000s, the article begins by discussing the five attributes of the algorithmic divide: awareness, access, affordability, availability and adaptability.This article then turns to three major problems precipitated by an emerging and fast-expanding algorithmic divide: (1) algorithmic deprivation; (2) algorithmic discrimination; and (3) algorithmic distortion. While the first two problems affect primarily those on the unfortunate side of the divide, the last problem impacts individuals on both sides. This article concludes by proposing seven non-exhaustive clusters of remedial actions to help bridge this emerging and ever-widening algorithmic divide. Combining law, communications policy, ethical principles, institutional mechanisms and business practices, the article fashions a holistic response to help foster equality in the age of artificial intelligence

Mission-based mobility models for UAV networks

Las redes UAV han atraído la atención de los investigadores durante la última década. Las numerosas posibilidades que ofrecen los sistemas single-UAV aumentan considerablemente al usar múltiples UAV. Sin embargo, el gran potencial del sistema multi-UAV viene con un precio: la complejidad de controlar todos los aspectos necesarios para garantizar que los UAVs cumplen la misión que se les ha asignado. Ha habido numerosas investigaciones dedicadas a los sistemas multi-UAV en el campo de la robótica en las cuales se han utilizado grupos de UAVs para diferentes aplicaciones. Sin embargo, los aspectos relacionados con la red que forman estos sistemas han comenzado a reclamar un lugar entre la comunidad de investigación y han hecho que las redes de UAVs se consideren como un nuevo paradigma entre las redes multi-salto. La investigación de redes de UAVs, de manera similar a otras redes multi-salto, se divide principalmente en dos categorías: i) modelos de movilidad que capturan la movilidad de la red, y ii) algoritmos de enrutamiento. Ambas categorías han heredado muchos algoritmos que pertenecían a las redes MANET, que fueron el primer paradigma de redes multi-salto que atrajo la atención de los investigadores. Aunque hay esfuerzos de investigación en curso que proponen soluciones para ambas categorías, el número de modelos de movilidad y algoritmos de enrutamiento específicos para redes UAV es limitado. Además, en el caso de los modelos de movilidad, las soluciones existentes propuestas son simplistas y apenas representan la movilidad real de un equipo de UAVs, los cuales se utilizan principalmente en operaciones orientadas a misiones, en la que cada UAV tiene asignados movimientos específicos. Esta tesis propone dos modelos de movilidad basados en misiones para una red de UAVs que realiza dos operaciones diferentes. El escenario elegido en el que se desarrollan las misiones corresponde con una región en la que ha ocurrido, por ejemplo, un desastre natural. La elección de este tipo de escenario se debe a que en zonas de desastre, la infraestructura de comunicaciones comúnmente está dañada o totalmente destruida. En este tipo de situaciones, una red de UAVs ofrece la posibilidad de desplegar rápidamente una red de comunicaciones. El primer modelo de movilidad, llamado dPSO-U, ha sido diseñado para capturar la movilidad de una red UAV en una misión con dos objetivos principales: i) explorar el área del escenario para descubrir las ubicaciones de los nodos terrestres, y ii) hacer que los UAVs converjan de manera autónoma a los grupos en los que se organizan los nodos terrestres (también conocidos como clusters). El modelo de movilidad dPSO-U se basa en el conocido algoritmo particle swarm optimization (PSO), considerando los UAV como las partículas del algoritmo, y también utilizando el concepto de valores dinámicos para la inercia, el local best y el neighbour best de manera que el modelo de movilidad tenga ambas capacidades: la de exploración y la de convergencia. El segundo modelo, denominado modelo de movilidad Jaccard-based, captura la movilidad de una red UAV que tiene asignada la misión de proporcionar servicios de comunicación inalámbrica en un escenario de mediano tamaño. En este modelo de movilidad se ha utilizado una combinación del virtual forces algorithm (VFA), de la distancia Jaccard entre cada par de UAVs y metaheurísticas como hill climbing y simulated annealing, para cumplir los dos objetivos de la misión: i) maximizar el número de nodos terrestres (víctimas) que se encuentran bajo el área de cobertura inalámbrica de la red UAV, y ii) mantener la red UAV como una red conectada, es decir, evitando las desconexiones entre UAV. Se han realizado simulaciones exhaustivas con herramientas software específicamente desarrolladas para los modelos de movilidad propuestos. También se ha definido un conjunto de métricas para cada modelo de movilidad. Estas métricas se han utilizado para validar la capacidad de los modelos de movilidad propuestos de emular los movimientos de una red UAV en cada misión.UAV networks have attracted the attention of the research community in the last decade. The numerous capabilities of single-UAV systems increase considerably by using multiple UAVs. The great potential of a multi-UAV system comes with a price though: the complexity of controlling all the aspects required to guarantee that the UAV team accomplish the mission that it has been assigned. There have been numerous research works devoted to multi-UAV systems in the field of robotics using UAV teams for different applications. However, the networking aspects of multi-UAV systems started to claim a place among the research community and have made UAV networks to be considered as a new paradigm among the multihop ad hoc networks. UAV networks research, in a similar manner to other multihop ad hoc networks, is mainly divided into two categories: i) mobility models that capture the network mobility, and ii) routing algorithms. Both categories have inherited previous algorithms mechanisms that originally belong to MANETs, being these the first multihop networking paradigm attracting the attention of researchers. Although there are ongoing research efforts proposing solutions for the aforementioned categories, the number of UAV networks-specific mobility models and routing algorithms is limited. In addition, in the case of the mobility models, the existing solutions proposed are simplistic and barely represent the real mobility of a UAV team, which are mainly used in missions-oriented operations. This thesis proposes two mission-based mobility models for a UAV network carrying out two different operations over a disaster-like scenario. The reason for selecting a disaster scenario is because, usually, the common communication infrastructure is malfunctioning or completely destroyed. In these cases, a UAV network allows building a support communication network which is rapidly deployed. The first mobility model, called dPSO-U, has been designed for capturing the mobility of a UAV network in a mission with two main objectives: i) exploring the scenario area for discovering the location of ground nodes, and ii) making the UAVs to autonomously converge to the groups in which the nodes are organized (also referred to as clusters). The dPSO-U mobility model is based on the well-known particle swarm optimization algorithm (PSO), considering the UAVs as the particles of the algorithm, and also using the concept of dynamic inertia, local best and neighbour best weights so the mobility model can have both abilities: exploration and convergence. The second one, called Jaccard-based mobility model, captures the mobility of a UAV network that has been assigned with the mission of providing wireless communication services in a medium-scale scenario. A combination of the virtual forces algorithm (VFA), the Jaccard distance between each pair of UAVs and metaheuristics such as hill climbing or simulated annealing have been used in this mobility model in order to meet the two mission objectives: i) to maximize the number of ground nodes (i.e. victims) under the UAV network wireless coverage area, and ii) to maintain the UAV network as a connected network, i.e. avoiding UAV disconnections. Extensive simulations have been performed with software tools that have been specifically developed for the proposed mobility models. Also, a set of metrics have been defined and measured for each mobility model. These metrics have been used for validating the ability of the proposed mobility models to emulate the movements of a UAV network in each mission

DRONE DELIVERY OF CBNRECy – DEW WEAPONS Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD)

Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD) is our sixth textbook in a series covering the world of UASs and UUVs. Our textbook takes on a whole new purview for UAS / CUAS/ UUV (drones) – how they can be used to deploy Weapons of Mass Destruction and Deception against CBRNE and civilian targets of opportunity. We are concerned with the future use of these inexpensive devices and their availability to maleficent actors. Our work suggests that UASs in air and underwater UUVs will be the future of military and civilian terrorist operations. UAS / UUVs can deliver a huge punch for a low investment and minimize human casualties.https://newprairiepress.org/ebooks/1046/thumbnail.jp

Disruptive Technologies with Applications in Airline & Marine and Defense Industries

Disruptive Technologies With Applications in Airline, Marine, Defense Industries is our fifth textbook in a series covering the world of Unmanned Vehicle Systems Applications & Operations On Air, Sea, and Land. The authors have expanded their purview beyond UAS / CUAS / UUV systems that we have written extensively about in our previous four textbooks. Our new title shows our concern for the emergence of Disruptive Technologies and how they apply to the Airline, Marine and Defense industries. Emerging technologies are technologies whose development, practical applications, or both are still largely unrealized, such that they are figuratively emerging into prominence from a background of nonexistence or obscurity. A Disruptive technology is one that displaces an established technology and shakes up the industry or a ground-breaking product that creates a completely new industry.That is what our book is about. The authors think we have found technology trends that will replace the status quo or disrupt the conventional technology paradigms.The authors have collaborated to write some explosive chapters in Book 5:Advances in Automation & Human Machine Interface; Social Media as a Battleground in Information Warfare (IW); Robust cyber-security alterative / replacement for the popular Blockchain Algorithm and a clean solution for Ransomware; Advanced sensor technologies that are used by UUVs for munitions characterization, assessment, and classification and counter hostile use of UUVs against U.S. capital assets in the South China Seas. Challenged the status quo and debunked the climate change fraud with verifiable facts; Explodes our minds with nightmare technologies that if they come to fruition may do more harm than good; Propulsion and Fuels: Disruptive Technologies for Submersible Craft Including UUVs; Challenge the ammunition industry by grassroots use of recycled metals; Changing landscape of UAS regulations and drone privacy; and finally, Detailing Bioterrorism Risks, Biodefense, Biological Threat Agents, and the need for advanced sensors to detect these attacks.https://newprairiepress.org/ebooks/1038/thumbnail.jp

The Algorithmic Divide and Equality in the Age of Artificial Intelligence

In the age of artificial intelligence, highly sophisticated algorithms have been deployed to provide analysis, detect patterns, optimize solutions, accelerate operations, facilitate self-learning, minimize human errors and biases and foster improvements in technological products and services. Notwithstanding these tremendous benefits, algorithms and intelligent machines do not provide equal benefits to all. Just as the digital divide has separated those with access to the Internet, information technology and digital content from those without, an emerging and ever-widening algorithmic divide now threatens to take away the many political, social, economic, cultural, educational and career opportunities provided by machine learning and artificial intelligence.Although policy makers, commentators and the mass media have paid growing attention to algorithmic bias and the shortcomings of machine learning and artificial intelligence, the algorithmic divide has yet to attract much policy and scholarly attention. To fill this lacuna, this article draws on the digital divide literature to systematically analyze this new inequitable gap between the technology haves and have-nots. Utilizing an analytical framework that the Author developed in the early 2000s, the article begins by discussing the five attributes of the algorithmic divide: awareness, access, affordability, availability and adaptability.This article then turns to three major problems precipitated by an emerging and fast-expanding algorithmic divide: (1) algorithmic deprivation; (2) algorithmic discrimination; and (3) algorithmic distortion. While the first two problems affect primarily those on the unfortunate side of the divide, the last problem impacts individuals on both sides. This article concludes by proposing seven non-exhaustive clusters of remedial actions to help bridge this emerging and ever-widening algorithmic divide. Combining law, communications policy, ethical principles, institutional mechanisms and business practices, the article fashions a holistic response to help foster equality in the age of artificial intelligence