Trust in Sharing Resources in Logistics Collaboration

Collaboration on resource sharing advocates a joint usage of resources by multiple parties (actors) to attain mutual benefits. Resource sharing becomes vital when resources under consideration are scarce, challenging, and expensive to attain; as well when they are idle or underutilized. In collaborative logistics, resource sharing entails the joint usage of the physical and non-physical assets. Shared assets include the transportation vehicles (trucks), warehouses, distribution centers, information, on-demand staffing, and logistics services offered under cloud computing. Through sharing, collaborating partners in logistics can reduce costs and harms to the environment, but also improve the efficiency of logistical functions. Although collaborative sharing is beneficial, still many difficulties impede its uptake. The difficulties include how to choose partners, establish and maintain trust among partners involved. Indeed, in both academia and industry, low-level trust inhibits the collaboration critically on sharing logistics resources. To this end, the present dissertation addresses the trust problem encountered by collaborating partners when they are sharing logistics resources. It deals with the trust problem by developing the Trust Mechanism (TrustMech) concept. The primary role of the TrustMech is to help logistics stakeholders acquire the far-reaching understanding about the trustworthiness of prospective networks of sharing they configure, before advancing them to an implementation stage. The TrustMech stands on a mitigation approach that focuses on estimating outcomes of trust uncertainties a rather than a their sources. Henceforth, this dissertation advances on estimating outcomes of trust uncertainties to answer the following central Research Question (RQ): how can collaborating partners acquire the far-reaching understanding about the trustworthiness of prospective networks of sharing they configure? An approach to the research problem, which as well answers the RQ proceeds as follows. The first steps involve establishing behavioral factors and parameters, which influence trust in collaborative sharing of logistics resources. The second stage entails establishing a conceptual framework that depicts and guides trust-based interaction of collaborating partners. The third step comprises developing the TrustMech concept, validating it in both the conceptual and operational aspects, and demonstrating its application by carrying out controlled (simulation) experiments in Multi-Agent Systems. In particular, the proposed TrustMech concept characterizes fundamental logical processes that account for trusting decisions, actions, and reactions of collaborating partners to reinforce emergent trusting outcomes The core contributions of this dissertation are the general-purpose TrustMech and the operational TrustMech. The operational TrustMech is customary for collaborative sharing of logistics resources. Regarding its application, the operational TrustMech provides logistics managers and stakeholders the ability to forecast how a configured network of sharing may, in respect of trustworthiness, function upon its implementation. To clarify further, the operational TrustMech scrutinizes many issues. For example, it scrutinizes trustworthiness of the configured network regarding possible strengths and pitfalls and provides pathway explanations underlying such foreseen strengths and pitfalls. Secondly, the operational TrustMech scrutinizes effects which such strengths and pitfalls can generate. Moreover, the operational TrustMech estimates an extent to which behavioral factors influence the trustworthiness of the individual partner and entire resource sharing network. Future research works include extending the TrustMech and replicating the study using system data. Additional future work consists of adjusting the design and settings used, as well as incorporating additional predictor and response variables into the operational TrustMech

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Unmanned Vehicle Systems & Operations on Air, Sea, Land

Unmanned Vehicle Systems & Operations On Air, Sea, Land is our fourth textbook in a series covering the world of Unmanned Aircraft Systems (UAS) and Counter Unmanned Aircraft Systems (CUAS). (Nichols R. K., 2018) (Nichols R. K., et al., 2019) (Nichols R. , et al., 2020)The authors have expanded their purview beyond UAS / CUAS systems. Our title shows our concern for growth and unique cyber security unmanned vehicle technology and operations for unmanned vehicles in all theaters: Air, Sea and Land – especially maritime cybersecurity and China proliferation issues. Topics include: Information Advances, Remote ID, and Extreme Persistence ISR; Unmanned Aerial Vehicles & How They Can Augment Mesonet Weather Tower Data Collection; Tour de Drones for the Discerning Palate; Underwater Autonomous Navigation & other UUV Advances; Autonomous Maritime Asymmetric Systems; UUV Integrated Autonomous Missions & Drone Management; Principles of Naval Architecture Applied to UUV’s; Unmanned Logistics Operating Safely and Efficiently Across Multiple Domains; Chinese Advances in Stealth UAV Penetration Path Planning in Combat Environment; UAS, the Fourth Amendment and Privacy; UV & Disinformation / Misinformation Channels; Chinese UAS Proliferation along New Silk Road Sea / Land Routes; Automaton, AI, Law, Ethics, Crossing the Machine – Human Barrier and Maritime Cybersecurity.Unmanned Vehicle Systems are an integral part of the US national critical infrastructure The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. Unmanned Vehicle (UV) Systems & Operations On Air, Sea, Land discusses state-of-the-art technology / issues facing U.S. UV system researchers / designers / manufacturers / testers. We trust our newest look at Unmanned Vehicles in Air, Sea, and Land will enrich our students and readers understanding of the purview of this wonderful technology we call UV.https://newprairiepress.org/ebooks/1035/thumbnail.jp

Electronic Imaging & the Visual Arts. EVA 2019 Florence

The Publication is following the yearly Editions of EVA FLORENCE. The State of Art is presented regarding the Application of Technologies (in particular of digital type) to Cultural Heritage. The more recent results of the Researches in the considered Area are presented. Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Science and Culture Developments & Applications; New Technical Developments & Applications; Cultural Activities – Real and Virtual Galleries and Related Initiatives, Access to the Culture Information. One Workshop regards Innovation and Enterprise. The more recent results of the Researches at national and international level are reported in the Area of Technologies and Culture Heritage, also with experimental demonstrations of developed Activities

Cross-fertilising methods in naturalistic decision-making and managerial cognition

The aim of this thesis is to examine the potential for methodological exchange between the fields of naturalistic decision-making (NDM) and managerial cognition. The research outlined makes a contribution towards methodological choice and research design within these fields. It also contributes by highlighting the theoretical value of applying a naturalistic mode of enquiry to the study of investment professionals. This research is situated in response to a number of calls for inter-disciplinary conversation in the study of cognition (Hodgkinson and Healey, 2008; Hodgkinson and Thomas, 1997; Lipshitz, Klein and Carroll, 2006). As such, it is located within the wider organisational debates of the social, management and behavioural sciences. Building upon the arguable inappropriateness of existing managerial cognition - behavioural decision-making (BDM) collaborations, this thesis advocates a naturalistic approach for progressing understanding of 'real-world' decision-making. In doing so, and in addressing the methodological challenges associated with these fields, the thesis examines the utility of connectionist architectures and structured qualitative approaches for the elicitation and representation of cognition. Three studies progressively examine the boundaries of cross-fertilisation using investment professionals as a backdrop for study. The results suggest inter-disciplinary collaboration to be useful not only in developing the reperto.ire of methodological tools available to the social sciences researcher, but in progressing theoretical thought (ie. through the concepts of coherence and sense-making) and in addressing epistemological debates within these fields. This thesis therefore contributes towards rapprochement of quantitative-qualitative approaches in NDM and computational-interpretative perspectives in the field of managerial cognition by modelling their dynamic interplay. The results also draw attention to the importance of understanding the socially situated aspects of expertise and the value in obtaining a multi-perspective understanding of cognition through mixed-methods designs. This thesis suggests that further collaboration both in a theoretical and methodological sense has much to offer these two fields and is an appropriate avenue for progression.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Do strategic alliances add value?: an empirical examination at industry and firm levels in European banking

Strategic alliances are a prevalent form of business organization. The critical characteristics of strategic alliances are detailed using Coase (1937) and the resulting definition tested through primary research and the alternative form, the infrastructure alliance posited. The thesis examines whether strategic alliances add value in the European banking sector through four types of analysis at two levels of engagement - a 23 historical review (at industry level); a review of over 400 papers in the academic literature; a questionnaire survey (at firm level) and in-depth interviews (at firm level). Bankers high pre-existing propensity to enter into strategic alliances is determined and three lifecycles, and the underpinning, conditions identified - Clubs and Consortium Banks, Bankassurance and the Virtual bank - the latter involving a fundamental change in Coase (1937) enabled by the underpinning technology. Bankers were found to be followers of potential business steams and the strategic alliance was one form of market entry. The questionnaire research, however, identified European bankers prefer to enter into alliances (as opposed to own branch or M&A) only in countries which had the appropriate supporting conditions such as definable, enforceable and terminable contracts, the provision of accounting information, stable governments and economic freedom. Direct discussions with senior bankers resulted in a number of valuable insights into the conceiving, forming, organizing evolving and dissolving of alliances. Further research into the infrastructure alliance, including 'oscillation' between infrastructure and strategic forms is proposed. The Co-Evolution Model of Strategic Alliances is proposed and taxonomy consisting of parallel co-evolution, convergent coevolution, divergent co-evolution and the subsidiary taxonomy of differential parallel coevolution, differential convergent co-evolution and differential divergent co-evolution detailed and further research suggested. Strategic alliances are found to add value in European banking but this value is contingent on the strength of the business stream, the global, national and industry conditions and the nature of managerial decisions and drive

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

White Paper 11: Artificial intelligence, robotics & data science

198 p. : 17 cmSIC white paper on Artificial Intelligence, Robotics and Data Science sketches a preliminary roadmap for addressing current R&D challenges associated with automated and autonomous machines. More than 50 research challenges investigated all over Spain by more than 150 experts within CSIC are presented in eight chapters. Chapter One introduces key concepts and tackles the issue of the integration of knowledge (representation), reasoning and learning in the design of artificial entities. Chapter Two analyses challenges associated with the development of theories –and supporting technologies– for modelling the behaviour of autonomous agents. Specifically, it pays attention to the interplay between elements at micro level (individual autonomous agent interactions) with the macro world (the properties we seek in large and complex societies). While Chapter Three discusses the variety of data science applications currently used in all fields of science, paying particular attention to Machine Learning (ML) techniques, Chapter Four presents current development in various areas of robotics. Chapter Five explores the challenges associated with computational cognitive models. Chapter Six pays attention to the ethical, legal, economic and social challenges coming alongside the development of smart systems. Chapter Seven engages with the problem of the environmental sustainability of deploying intelligent systems at large scale. Finally, Chapter Eight deals with the complexity of ensuring the security, safety, resilience and privacy-protection of smart systems against cyber threats.18 EXECUTIVE SUMMARY ARTIFICIAL INTELLIGENCE, ROBOTICS AND DATA SCIENCE Topic Coordinators Sara Degli Esposti ( IPP-CCHS, CSIC ) and Carles Sierra ( IIIA, CSIC ) 18 CHALLENGE 1 INTEGRATING KNOWLEDGE, REASONING AND LEARNING Challenge Coordinators Felip Manyà ( IIIA, CSIC ) and Adrià Colomé ( IRI, CSIC – UPC ) 38 CHALLENGE 2 MULTIAGENT SYSTEMS Challenge Coordinators N. Osman ( IIIA, CSIC ) and D. López ( IFS, CSIC ) 54 CHALLENGE 3 MACHINE LEARNING AND DATA SCIENCE Challenge Coordinators J. J. Ramasco Sukia ( IFISC ) and L. Lloret Iglesias ( IFCA, CSIC ) 80 CHALLENGE 4 INTELLIGENT ROBOTICS Topic Coordinators G. Alenyà ( IRI, CSIC – UPC ) and J. Villagra ( CAR, CSIC ) 100 CHALLENGE 5 COMPUTATIONAL COGNITIVE MODELS Challenge Coordinators M. D. del Castillo ( CAR, CSIC) and M. Schorlemmer ( IIIA, CSIC ) 120 CHALLENGE 6 ETHICAL, LEGAL, ECONOMIC, AND SOCIAL IMPLICATIONS Challenge Coordinators P. Noriega ( IIIA, CSIC ) and T. Ausín ( IFS, CSIC ) 142 CHALLENGE 7 LOW-POWER SUSTAINABLE HARDWARE FOR AI Challenge Coordinators T. Serrano ( IMSE-CNM, CSIC – US ) and A. Oyanguren ( IFIC, CSIC - UV ) 160 CHALLENGE 8 SMART CYBERSECURITY Challenge Coordinators D. Arroyo Guardeño ( ITEFI, CSIC ) and P. Brox Jiménez ( IMSE-CNM, CSIC – US )Peer reviewe