Stealthy River Navigation in Jungle Combat Conditions

One of the biggest challenges for Brazilian military logisticians is to support effective jungle warfare for both real and training operations carried out by their combat forces in the Amazonian region. The jungle\u27s heat, humidity, and dense vegetation put significant demands on the supply chain. Further, because of the difficulties of land or air transportation, water transport is the most reasonable transportation option to sustain these deployed forces. Planners must select from among the available watercourses those whose surroundings provide stealthy navigation to the combat force location where the requested supplies can be safely unloaded. We seek a method of determining a path through a river network that blends short transit times with maximal shade coverage from forest growth along the riverbanks. We combine an astronomical algorithm for computing shadow coverage with Dijkstra\u27s shortest path algorithm to determine the start time and routing information necessary for a supply boat to travel from a depot to a resupply point that minimizes weighted risk, which is defined as the product of shade coverage and arc transit time

Ilmatorjunnan ilmasta-maahan -aseeseen aiheuttaman uhkan arviointi perustuen ilmatorjunnan ryhmityksen todennäköisyysmalliin

As a part of planning an air mission, the trajectory of an air-to-ground (A/G) weapon must be determined. In this thesis, the novel trajectory evaluation framework with which the best trajectory can be identified from a set of possible trajectories under uncertainty regarding the locations of surface-to-air (S/A) threats is presented. The best trajectory is the trajectory which has the highest survivability, i.e., the probability for the A/G weapon to traverse the trajectory without being intercepted. The trajectory evaluation framework relies on two new models introduced in this thesis which together provide the survivability of a given trajectory. The spatial prediction model is used to build a probability map for the location of an S/A threat based on Bayesian reasoning with geographical data and knowledge about common tactical principles utilised in forming an air defence. The Markov survivability model describes the process of intercepting an A/G weapon with the air defence consisting of radar sensors and S/A weapons with an inhomogeneous continuous-time Markov chain. Using the probability maps produced by the spatial prediction model, the Markov survivability model produces the survivability of the trajectory, such that uncertainties regarding the locations of the S/A threats are taken into account. The Markov survivability model presented in this thesis is compared with existing reference survivability models through numerical experiments by replacing it in the framework with each of the reference models. In the experiments, the survivabilities of different trajectories obtained with each model are evaluated and compared. The sensitivity of the models to uncertainty regarding the locations of S/A threats is studied by varying sizes of areas in which it is believed that the threats are located. The experiments imply that the novel framework gives intuitive results. In addition, the Markov survivability model is less affected by imprecise information regarding the locations of the S/A threats than the reference models.Ilmaoperaation suunnitteluun sisältyy operaatiossa käytettävien ilmasta-maahan -aseiden reittien valinta siten, että aseisiin kohdistuu ilmatorjunnasta mahdollisimman vähän uhkaa. Tässä työssä esitellään uusi menetelmä, jolla arvioidaan ilmatorjunnan aiheuttamaa uhkaa annetulla lentoradalla lentävään ilmasta-maahan -aseeseen, kun ilmatorjunnan tarkkaa ryhmitystä ei tiedetä. Menetelmässä käytetään kahta tässä työssä kehitettyä mallia: ryhmityksen sijaintijakauman tuottavaa mallia ja ilmasta-maahan -aseeseen annetulla lentoradalla kohdistuvan uhkan kertymistä kuvaavaa mallia. Ilmatorjunnan ryhmityksen sijaintijakauma määritetään Bayesiläisen päättelyn avulla käyttämällä maantieteellisiä tietolähteitä ja tiedustelutietoa todennäköisistä ryhmitysalueista. Ilmasta-maahan -aseeseen annetulla lentoradalla kohdistuva uhka arvioidaan jatkuva-aikaiseen Markov-ketjuun perustuvalla mallilla, joka kuvaa ilmatorjuntayksikön kykyä havaita ase, seurata asetta ja vaikuttaa aseeseen. Sijaintijakaumaa hyödyntämällä Markov-malli tuottaa todennäköisyyden sille, että yksi tai useampi ilmatorjunta-ase onnistuneesti torjuu ilmasta-maahan -aseen. Markov-mallin ja samalla koko menetelmän tuottama lopputulos huomioi ilmatorjunnan ryhmitykseen liittyvän epävarmuuden. Tässä työssä esiteltyä Markov-mallia verrataan numeerisin kokein kahteen ilmatorjuntaa kuvaavaan referenssimalliin. Kokeissa verrataan kunkin mallin tuottamia ilmasta-maahan -aseeseen kohdistuvia uhkia eri lentoradoilla kahdessa skenaariossa. Mallien alttiutta epätarkkuuksille sijaintitiedossa tutkitaan varioimalla ilmatorjunnan ryhmitysalueen suuruutta ja tarkastelemalla, kuinka hyvin mallit säilyttävät lentoratojen keskinäisen uhkajärjestyksen. Kokeiden tuloksena voidaan todeta, että uuden menetelmän hyödyntämä Markov-malli yhtäältä tuottaa realistisia uhka-arvioita ja toisaalta se on vähemmän altis epätarkkuuksille ilmatorjunnan ryhmityksen sijaintitiedossa verrattuna referenssimalleihin

Integrated helicopter survivability

A high level of survivability is important to protect military personnel and equipment and is central to UK defence policy. Integrated Survivability is the systems engineering methodology to achieve optimum survivability at an affordable cost, enabling a mission to be completed successfully in the face of a hostile environment. “Integrated Helicopter Survivability” is an emerging discipline that is applying this systems engineering approach within the helicopter domain. Philosophically the overall survivability objective is ‘zero attrition’, even though this is unobtainable in practice. The research question was: “How can helicopter survivability be assessed in an integrated way so that the best possible level of survivability can be achieved within the constraints and how will the associated methods support the acquisition process?” The research found that principles from safety management could be applied to the survivability problem, in particular reducing survivability risk to as low as reasonably practicable (ALARP). A survivability assessment process was developed to support this approach and was linked into the military helicopter life cycle. This process positioned the survivability assessment methods and associated input data derivation activities. The system influence diagram method was effective at defining the problem and capturing the wider survivability interactions, including those with the defence lines of development (DLOD). Influence diagrams and Quality Function Deployment (QFD) methods were effective visual tools to elicit stakeholder requirements and improve communication across organisational and domain boundaries. The semi-quantitative nature of the QFD method leads to numbers that are not real. These results are suitable for helping to prioritise requirements early in the helicopter life cycle, but they cannot provide the quantifiable estimate of risk needed to demonstrate ALARP. The probabilistic approach implemented within the Integrated Survivability Assessment Model (ISAM) was developed to provide a quantitative estimate of ‘risk’ to support the approach of reducing survivability risks to ALARP. Limitations in available input data for the rate of encountering threats leads to a probability of survival that is not a real number that can be used to assess actual loss rates. However, the method does support an assessment across platform options, provided that the ‘test environment’ remains consistent throughout the assessment. The survivability assessment process and ISAM have been applied to an acquisition programme, where they have been tested to support the survivability decision making and design process. The survivability ‘test environment’ is an essential element of the survivability assessment process and is required by integrated survivability tools such as ISAM. This test environment, comprising of threatening situations that span the complete spectrum of helicopter operations requires further development. The ‘test environment’ would be used throughout the helicopter life cycle from selection of design concepts through to test and evaluation of delivered solutions. It would be updated as part of the through life capability management (TLCM) process. A framework of survivability analysis tools requires development that can provide probabilistic input data into ISAM and allow derivation of confidence limits. This systems level framework would be capable of informing more detailed survivability design work later in the life cycle and could be enabled through a MATLAB® based approach. Survivability is an emerging system property that influences the whole system capability. There is a need for holistic capability level analysis tools that quantify survivability along with other influencing capabilities such as: mobility (payload / range), lethality, situational awareness, sustainability and other mission capabilities. It is recommended that an investigation of capability level analysis methods across defence should be undertaken to ensure a coherent and compliant approach to systems engineering that adopts best practice from across the domains. Systems dynamics techniques should be considered for further use by Dstl and the wider MOD, particularly within the survivability and operational analysis domains. This would improve understanding of the problem space, promote a more holistic approach and enable a better balance of capability, within which survivability is one essential element. There would be value in considering accidental losses within a more comprehensive ‘survivability’ analysis. This approach would enable a better balance to be struck between safety and survivability risk mitigations and would lead to an improved, more integrated overall design

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR

UNMANNED AERIAL VEHICLES: TRAJECTORY PLANNING AND ROUTING IN THE ERA OF ADVANCED AIR MOBILITY

Advanced air mobility (AAM) is a revolutionary concept that enables on-demand air mobility, cargo delivery, and emergency services via an integrated and connected multimodal transportation network. In the era of AAM, unmanned aerial vehicles are envisioned as the primary tool for transporting people and cargo from point A to point B. This thesis focuses on the development of a core decision-making engine for strategic vehicle routing and trajectory planning of autonomous vehicles (AVs) with the goal of enhancing the system-wide safety, efficiency, and scalability. Part I of the thesis addresses the routing and coordination of a drone-truck pairing, where the drone travels to multiple locations to perform specified observation tasks and rendezvous periodically with the truck to swap its batteries. Drones, as an alternative mode of transportation, have advantages in terms of lower costs, better service, or the potential to provide new services that were previously not possible. Typically, those services involve routing a fleet of drones to meet specific demands. Despite the potential benefits, the drone has a natural limitation on the flight range due to its battery capacity. As a result, enabling the combination of a drone with a ground vehicle, which can serve as a mobile charging platform for the drone, is an important opportunity for practical impact and research challenges. We first propose a Mixed Integer Quadratically-constrained Programming driven by critical operational constraints. Given the NP-hard nature of the so called Nested-VRP, we analyze the complexity of the MIQCP model and propose both enhanced exact approach and efficient heuristic for solving the Nested-VRP model. We envision that this framework will facilitate the planning and operations of combined drone-truck missions and further improve the scalability and efficiency of the AAM system. Part II of the thesis focuses on the survivability reasoning and trajectory planning of UAVs under uncertainty. Maintaining the survivability of an UAV requires that it precisely perceives and transitions between safe states in the airspace. We first propose a methodology to construct a survivability map for an UAV as a function of the vehicle's maneuverability, remaining lifetime, availability of landing sites, and the volume of air traffic. The issue of trajectory planning under uncertainty has received a lot of attention in the robotics and control communities. Traditional trajectory planning approaches rely primarily on the premise that the uncertainty of dynamic obstacles is either bounded or can be statistically modeled. This is not the case in the urban environment, where the sources of uncertainty are diverse, and their uncertain behavior is typically unpredictable, making precise modeling impossible. Motivated by this, we present a receding horizon control method with innovative trajectory planning policies that enable dynamic updating of planned trajectories in the presence of partially known and unknown uncertainty. The findings of this study have significant implications for achieving safe aviation autonomy within the AAM system.Ph.D

Artificial Intelligence and Supply Chain Management: A literature review

openIl presente elaborato si propone di analizzare l’affascinante ed intricata intersezione dei due campi dell’intelligenza artificiale (IA) e della supply chain (SC), in modo da esplorarne il potenziale impatto e chiarire come le organizzazioni possono sfruttare queste tecnologie. Gli ultimi progressi e le recenti rivoluzioni hanno infatti reso evidente le capacità ed i potenziali benefici di tali strumenti, sottolineandone l’indispensabile integrazione all’interno delle aziende che vogliono aumentare l’efficienza operativa ed ottenere un vantaggio competitivo. Questo fenomeno è particolarmente enfatizzato dalla crescente complessità nel gestire catene di fornitura in un ambiente commerciale sempre più competitivo, come dimostrato anche dalla recente pandemia di Covid-19. L’IA e le altre tecnologie emergenti possono dunque creare una simbiosi ottimale per il contesto odierno, portando numerosi benefici sia in termini di costo, produttività ed efficienza. Nonostante il crescente interesse per l’argomento e la graduale implementazione di questi strumenti innovativi all’interno delle aziende, permane una carenza di ricerca fatta su questo fronte. Questo studio ha dunque l’obbiettivo di colmare alcune lacune esistenti nelle pubblicazioni disponibili ad oggi, esaminando 518 articoli di ricerca pubblicati tra il 1999 ed il 2023 dal database di Scopus. Il lavoro è strutturato come segue: Nel primo capitolo introduttivo vengono presentati i due concetti chiave dell’Intelligenza Artificiale e del Supply Chain Management. Nel secondo capitolo viene fornita una panoramica sull’importanza dell’intersezione di queste due aree e del come la letteratura corrente ha affrontato questo argomento. Il terzo capitolo è dedicato alla metodologia e spiega come è stato costruito il database di articoli e come è stato visualizzato ed analizzato tramite l’utilizzo del software VOSviewer e dell’analisi bibliometrica. Nel quarto capitolo vengono presentati i risultati della ricerca tramite l’analisi delle tre mappe create con l’apposito software. L’ultimo capitolo riporta le principali conclusioni derivabili da questo elaborato, rimarcando l’importanza dell’argomento trattato e sottolineando le limitazioni del presente studio, nonché le possibili direzioni per i ricercatori futuri.This thesis aims to analyse the fascinating and intricate intersection of the two fields of artificial intelligence (AI) and supply chain (SC), in order to explore their potential impact and clarify how organizations can leverage these technologies. Recent advancements and revolutions have indeed highlighted the capabilities and potential benefits of such tools, underscoring their essential integration within companies seeking to enhance operational efficiency and gain a competitive advantage. This phenomenon is particularly emphasized by the growing complexity of managing supply chains in an increasingly competitive business environment, as demonstrated by the recent Covid-19 pandemic. AI and other emerging technologies can thus create an optimal symbiosis for the nowadays context, yielding numerous benefits in terms of cost, productivity, and efficiency. Despite the growing interest in the topic and the gradual implementation of these innovative tools within companies, there remains a research gap in this area. Therefore, this study aims to fill some of the existing voids in the available literature, examining 518 research articles published between 1999 and 2023 from the Scopus database. The work is structured as follows: The first introductory chapter presents the two key concepts of Artificial Intelligence and Supply Chain Management. The second chapter provides an overview of the importance of these two areas and how the current literature has addressed this topic. The third chapter is dedicated to the methodology and explains how the database of articles was constructed and how it was visualized and analysed using the VOSviewer software and bibliometric analysis. The fourth chapter presents the research results through the analysis of the three maps created with the software. The final chapter outlines the main conclusions drawn from this paper, emphasizing the significance of the treated topic and highlighting the limitations of the present study, as well as suggesting potential directions for future researchers

Design and implementation of a fault-tolerant multimedia network and a local map based (LMB) self-healing scheme for arbitrary topology networks.

by Arion Ko Kin Wa.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 101-[106]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Overview --- p.1Chapter 1.2 --- Service Survivability Planning --- p.2Chapter 1.3 --- Categories of Outages --- p.3Chapter 1.4 --- Goals of Restoration --- p.4Chapter 1.5 --- Technology Impacts on Network Survivability --- p.5Chapter 1.6 --- Performance Models and Measures in Quantifying Network Sur- vivability --- p.6Chapter 1.7 --- Organization of Thesis --- p.6Chapter 2 --- Design and Implementation of A Survivable High-Speed Mul- timedia Network --- p.8Chapter 2.1 --- An Overview of CUM LAUDE NET --- p.8Chapter 2.2 --- The Network Architecture --- p.9Chapter 2.2.1 --- Architectural Overview --- p.9Chapter 2.2.2 --- Router-Node Design --- p.11Chapter 2.2.3 --- Buffer Allocation --- p.12Chapter 2.2.4 --- Buffer Transmission Priority --- p.14Chapter 2.2.5 --- Congestion Control --- p.15Chapter 2.3 --- Protocols --- p.16Chapter 2.3.1 --- Design Overview --- p.16Chapter 2.3.2 --- ACTA - The MAC Protocol --- p.17Chapter 2.3.3 --- Protocol Layering --- p.18Chapter 2.3.4 --- "Segment, Datagram and Packet Format" --- p.20Chapter 2.3.5 --- Fast Packet Routing --- p.22Chapter 2.3.6 --- Local Host NIU --- p.24Chapter 2.4 --- The Network Restoration Strategy --- p.25Chapter 2.4.1 --- The Dual-Ring Model and Assumptions --- p.26Chapter 2.4.2 --- Scenarios of Network Failure and Remedies --- p.26Chapter 2.4.3 --- Distributed Fault-Tolerant Algorithm --- p.26Chapter 2.4.4 --- Distributed Auto-Healing Algorithm --- p.28Chapter 2.4.5 --- The Network Management Signals --- p.31Chapter 2.5 --- Performance Evaluation --- p.32Chapter 2.5.1 --- Restoration Time --- p.32Chapter 2.5.2 --- Reliability Measures --- p.34Chapter 2.5.3 --- Network Availability During Restoration --- p.41Chapter 2.6 --- The Prototype --- p.42Chapter 2.7 --- Technical Problems Encountered --- p.45Chapter 2.8 --- Chapter Summary and Future Development --- p.46Chapter 3 --- A Simple Experimental Network Management Software - NET- MAN --- p.48Chapter 3.1 --- Introduction to NETMAN --- p.48Chapter 3.2 --- Network Management Basics --- p.49Chapter 3.2.1 --- The Level of Management Protocols --- p.49Chapter 3.2.2 --- Architecture Model --- p.51Chapter 3.2.3 --- TCP/IP Network Management Protocol Architecture --- p.53Chapter 3.2.4 --- A Standard Network Management Protocol On Internet - SNMP --- p.54Chapter 3.2.5 --- A Standard For Managed Information --- p.55Chapter 3.3 --- The CUM LAUDE Network Management Protocol Suite (CNMPS) --- p.56Chapter 3.3.1 --- The Architecture --- p.53Chapter 3.3.2 --- Goals of the CNMPS --- p.59Chapter 3.4 --- Highlights of NETMAN --- p.61Chapter 3.5 --- Functional Descriptions of NETMAN --- p.63Chapter 3.5.1 --- Topology Menu --- p.64Chapter 3.5.2 --- Fault Manager Menu --- p.65Chapter 3.5.3 --- Performance Meter Menu --- p.65Chapter 3.5.4 --- Gateway Utility Menu --- p.67Chapter 3.5.5 --- Tools Menu --- p.67Chapter 3.5.6 --- Help Menu --- p.68Chapter 3.6 --- Chapter Summary --- p.68Chapter 4 --- A Local Map Based (LMB) Self-Healing Scheme for Arbitrary Topology Networks --- p.70Chapter 4.1 --- Introduction --- p.79Chapter 4.2 --- An Overview of Existing DCS-Based Restoration Algorithms --- p.72Chapter 4.3 --- The Network Model and Assumptions --- p.74Chapter 4.4 --- Basics of the LMB Scheme --- p.75Chapter 4.4.1 --- Restoration Concepts --- p.75Chapter 4.4.2 --- Terminology --- p.76Chapter 4.4.3 --- Algorithm Parameters --- p.77Chapter 4.5 --- Performance Assessments --- p.78Chapter 4.6 --- The LMB Network Restoration Scheme --- p.80Chapter 4.6.1 --- Initialization - Local Map Building --- p.80Chapter 4.6.2 --- The LMB Restoration Messages Set --- p.81Chapter 4.6.3 --- Phase I - Local Map Update Phase --- p.81Chapter 4.6.4 --- Phase II - Update Acknowledgment Phase --- p.82Chapter 4.6.5 --- Phase III - Restoration and Confirmation Phase --- p.83Chapter 4.6.6 --- Phase IV - Cancellation Phase --- p.83Chapter 4.6.7 --- Re-Initialization --- p.84Chapter 4.6.8 --- Path Route Monitoring --- p.84Chapter 4.7 --- Performance Evaluation --- p.84Chapter 4.7.1 --- The Testbeds --- p.84Chapter 4.7.2 --- Simulation Results --- p.86Chapter 4.7.3 --- Storage Requirements --- p.89Chapter 4.8 --- The LMB Scheme on ATM and SONET environment --- p.92Chapter 4.9 --- Future Work --- p.94Chapter 4.10 --- Chapter Summary --- p.94Chapter 5 --- Conclusion and Future Work --- p.96Chapter 5.1 --- Conclusion --- p.95Chapter 5.2 --- Future Work --- p.99Bibliography --- p.101Chapter A --- Derivation of Communicative Probability --- p.107Chapter B --- List of Publications --- p.11