Enhancing maritime defence and security through persistently autonomous operations and situation awareness systems

This thesis is concerned with autonomous operations with Autonomous Underwater Vehicles(AUVs) and maritime situation awareness in the context of enhancing maritime defence and security. The problem of autonomous operations with AUVs is one of persistence. That is, AUVs get stuck due to a lack of cognitive ability to deal with a situation and require intervention from a human operator. This thesis focuses on addressing vehicle subsystem failures and changes in high level mission priorities in a manner that preserves autonomy during Mine Counter measures (MCM) operations in unknown environments. This is not a trivial task. The approach followed utilizes ontologies for representing knowledge about the operational environment, the vehicle as well as mission planning and execution. Reasoning about the vehicle capabilities and consequently the actions it can execute is continuous and occurs in real time. Vehicle component faults are incorporated into the reasoning process as a means of driving adaptive planning and execution. Adaptive planning is based on a Planning Domain Definition Language (PDDL) planner. Adaptive execution is prioritized over adaptive planning as mission planning can be very demanding in terms of computational resources. Changes in high level mission priorities are also addressed as part of the adaptive planning behaviour of the system. The main contribution of this thesis regarding persistently autonomous operations is an ontological framework that drives an adaptive behaviour for increasing persistent autonomy of AUVs in unexpected situations. That is, when vehicle component faults threaten to put the mission at risk and changes in high level mission priorities should be incorporated as part of decision making. Building maritime situation awareness for maritime security is a very difficult task. High volumes of information gathered from various sources as well as their efficient fusion taking into consideration any contradictions and the requirement for reliable decision making and (re)action under potentially multiple interpretations of a situation are the most prominent challenges. To address those challenges and help alleviate the burden from humans which usually undertake such tasks, this thesis is concerned with maritime situation awareness built with Markov Logic Networks(MLNs) that support humans in their decision making. However, commonly maritime situation awareness systems rely on human experts to transfer their knowledge into the system before it can be deployed. In that respect, a promising alternative for training MLNs with data is presented. In addition, an in depth evaluation of their performance is provided during which the significance of interpreting an unfolding situation in context is demonstrated. To the best of the author’s knowledge, it is the first time that MLNs are trained with data and evaluated using cross validation in the context of building maritime situation awareness for maritime security

Exploring the use of Artificial Intelligent Systems in STEM Classrooms

Human beings by nature have a predisposition towards learning and the exploration of the natural world. We are intrinsically intellectual and social beings knitted with adaptive cognitive architectures. As Foot (2014) succinctly sums it up: “humans act collectively, learn by doing, and communicate in and via their actions” and they “… make, employ, and adapt tools of all kinds to learn and communicate” and “community is central to the process of making and interpreting meaning—and thus to all forms of learning, communicating, and acting” (p.3). Education remains pivotal in the transmission of social values including language, knowledge, science, technology, and an avalanche of others. Indeed, Science, Technology, Engineering, and Mathematics (STEM) have been significant to the advancement of social cultures transcending every epoch to contemporary times. As Jasanoff (2004) poignantly observed, “the ways in which we know and represent the world (both nature and society) are inseparable from the ways in which we choose to live in it. […] Scientific knowledge [..] both embeds and is embedded in social practices, identities, norms, conventions, discourses, instruments, and institutions” (p.2-3). In essence, science remains both a tacit and an explicit cultural activity through which human beings explore their own world, discover nature, create knowledge and technology towards their progress and existence. This has been possible through the interaction and applications of artifacts, tools, and technologies within the purviews of their environments. The applications of technologies are found across almost every luster of organizational learning especially teacher education, STEM, architecture, manufacturing, and a flurry of others. Thus, human evolution and development are inexplicably linked with education either formally or informally. The 21st century has however seen a surge in the use of artificial intelligence (AI) and digital technologies in education. The proliferation of artificial intelligence and associated technologies are creating new overtures of digital multiculturalism with distinct worldviews of significance to education. For example, learners are demonstrating digital literacy skills and are knowledgeable about AI technologies across every specter of their lives (Bennett et al., 2008). It is also opening new artesian well-springs of educational opportunities and pedagogical applications. This includes mapping new methodological pathways, content creation and curriculum design, career preparations and indeed a seemingly new paradigm shift in teaching STEM. There is growing scholarly evidence about the use and diffusion of these technologies in K-12 and higher education (Bonk & Graham, 2012; Hew & Brush, 2007; Langer, 2018; Mishra & Koehler, 2006). Some of these include the Sphero robots, Micro Bit, Jill Watson, BrickPi3 Classroom kit, Engino STEM Mechanic, Lego Education WeDo Core Set and Spike. Both educators and learners are using these in STEM programs as well as other education related activities. Just as human activities and interactions with artifacts and tools shaped and redefined the scientific-technological feat of previous generations, so the contemporary digital technological era seems to be on a similar trajectory. However, there is sparsity of empirical scholarship on the pedagogical prospects and effectiveness of artificial intelligence in STEM classrooms. Also, it should be noted that scholarship on how AI impacts pedagogical content knowledge of STEM educators and how learners perceive these technologies are just emerging. In addition, the recent COVID-19 pandemic (Ghandhi et al., 2020; Rasmussen et al., 2020) has unexpectedly created a renewed synergy towards the applications of digital technologies in teaching STEM. In the context of this force majeure (COVID-19), the traditional brick and mortar educational spaces metamorphosed into digital spaces with the applications of many artificial intelligent technologies and resources in the arena of education. This doctoral dissertation study examined these enigmas including how educators use these technologies in STEM classrooms. The study is informed by activity theory or cultural-historical activity theory (Engeström et al., 2007; Hasan et al., 2014; Krinski & Barker, 2009; Oers, 2010; Vygotsky,1987). The study participants will be selected from educators currently integrating artificial intelligent systems and digital technologies in their respective STEM classrooms. Pre-data survey inquiry has shown that many educators were incorporating some forms of AIS into their STEM classrooms. In view of these, I have explored Sphero educational robots to interrogate the research topic. The Sphero Edu described as a “…STEAM-based toolset that weaves hardware, software, and community engagement to promote 21st century skills. While these skills are absolutely crucial, our edu program goes beyond code by nurturing students’ creativity and ingenuity like no other education program can” (Sphero, April 2020). The Sphero robots also have features and applications for designing and teaching STEM topics such as nature, space science, geometry, and other activities of pedagogical significance. Users could also design and write advanced engineering programs in JavaScript during STEM educational activities formally and outside of the classrooms. In essence, educators and students can learn designing, programming, engineering, mathematics, computational thinking, and hands-on skills reflective of the 21st century. In brief, the dissertation study research has explored artificial intelligence and emerging technologies and how these could transform and advance teaching and learning of STEM hence the research topic: Exploring the use of Artificial Intelligent Systems in STEM Classrooms. Methodologically, this is a qualitative study through the theoretical frameworks of activity theory as applicable to STEM education. The main research questions are: 1) Given that artificial intelligent systems and digital technologies have been applied in STEM educational domains (content, pedagogy, student learning, assessment). How does the application of AIS and digital technologies impact pedagogy in STEM educational activities? 2) Given that digital technology is transforming contemporary society in every facet. How/What does AIS tell us about how digital technology impacts STEM pedagogy? Data was collected from the study participants, archival sources, and others for analyses. It is hoped that the findings will inform and address theories of learning and teaching, policy and praxis in science education, teacher preparatory and professional development programs as it relates to STEM classroom

Design Ethnography

This open access book describes methods for research on and research through design. It posits that ethnography is an appropriate method for design research because it constantly orients itself, like design projects, towards social realities. In research processes, designers acquire project-specific knowledge, which happens mostly intuitively in practice. When this knowledge becomes the subject of reflection and explication, it strengthens the discipline of design and makes it more open to interdisciplinary dialogue. Through the use of the ethnographic method in design, this book shows how design researchers can question the certainties of the everyday world, deconstruct reality into singular aesthetic and semantic phenomena, and reconfigure them into new contexts of signification. It shows that design ethnography is a process in which the epistemic and creative elements flow into one another in iterative loops. The goal of design ethnography is not to colonize the discipline of design with a positivist and objectivist scientific ethos, but rather to reinforce and reflect upon the explorative and searching methods that are inherent to it. This innovative book is of interest to design researchers and professionals, including graphic artists, ethnographers, visual anthropologists and others involved with creative arts/media

SMT goes ABMS: Developing Strategic Management Theory using Agent-Based Modelling and Simulation.

For the emerging complexity theory of strategy (CTS), organizations are complex adaptive systems able to co-evolve with their dynamic environments through interaction and response, rather than purely analysis and planning. A promising approach within the CTS context, is to focus on a strategic logic of opportunity pursuit, one in which the distributed decision-makers behave audaciously despite unpredictable, unstable environments. Although there is only emergent support for it, intriguingly organizations can perform better when these decision-makers ‘throw caution to the wind’ even at their own possible expense. Since traditional research methods have had difficulty showing how this can work over time, this research adopts a complementary method, agent-based modelling and simulation (ABMS), to examine this phenomenon. The simulation model developed here, CTS-SIM, is based on quite simple constructs, but it introduces a rich and novel externally driven environment and represents individual decision-makers as having autonomous perceptions but constrainable decision-making freedom. Its primary contribution is the illumination of core dynamics and causal mechanisms in the opportunity-transitioning process. During model construction the apparently simple concept of opportunity-transitioning turns out to be complex, and the apparently complex integration of exogenous and endogenous environments with all three views of opportunity pursuit in the entrepreneurship literature, turns out to be relatively simple. Simulation outcomes using NetLogo contribute to CTS by confirming the positive effects on agent performance of opportunistic transitioning among opportunities in highly dynamic environments. The simulations also reveal tensions among some of the chosen variables and tipping points in emergent behaviours, point to areas where theoretical clarity is currently lacking, provoke some interesting questions and open up useful avenues for future research and data collection using other methods and models. Guidance through numerous stylized facts, flexible methods, careful documentation and description are all intended to inspire interest and facilitate critical discussion and ongoing scientific work

Journalistic Knowledge Platforms: from Idea to Realisation

Journalistiske kunnskapsplattformer (JKPer) er en type intelligente informasjonssystemer designet for å forbedre nyhetsproduksjonsprosesser ved å kombinere stordata, kunstig intelligens (KI) og kunnskapsbaser for å støtte journalister. Til tross for sitt potensial for å revolusjonere journalistikkfeltet, har adopsjonen av JKPer vært treg, med forskere og store nyhetsutløp involvert i forskning og utvikling av JKPer. Den langsomme adopsjonen kan tilskrives den tekniske kompleksiteten til JKPer, som har ført til at nyhetsorganisasjoner stoler på flere uavhengige og oppgavespesifikke produksjonssystemer. Denne situasjonen kan øke ressurs- og koordineringsbehovet og kostnadene, samtidig som den utgjør en trussel om å miste kontrollen over data og havne i leverandørlåssituasjoner. De tekniske kompleksitetene forblir en stor hindring, ettersom det ikke finnes en allerede godt utformet systemarkitektur som ville lette realiseringen og integreringen av JKPer på en sammenhengende måte over tid. Denne doktoravhandlingen bidrar til teorien og praksisen rundt kunnskapsgrafbaserte JKPer ved å studere og designe en programvarearkitektur som referanse for å lette iverksettelsen av konkrete løsninger og adopsjonen av JKPer. Den første bidraget til denne doktoravhandlingen gir en grundig og forståelig analyse av ideen bak JKPer, fra deres opprinnelse til deres nåværende tilstand. Denne analysen gir den første studien noensinne av faktorene som har bidratt til den langsomme adopsjonen, inkludert kompleksiteten i deres sosiale og tekniske aspekter, og identifiserer de største utfordringene og fremtidige retninger for JKPer. Den andre bidraget presenterer programvarearkitekturen som referanse, som gir en generisk blåkopi for design og utvikling av konkrete JKPer. Den foreslåtte referansearkitekturen definerer også to nye typer komponenter ment for å opprettholde og videreutvikle KI-modeller og kunnskapsrepresentasjoner. Den tredje presenterer et eksempel på iverksettelse av programvarearkitekturen som referanse og beskriver en prosess for å forbedre effektiviteten til informasjonsekstraksjonspipelines. Denne rammen muliggjør en fleksibel, parallell og samtidig integrering av teknikker for naturlig språkbehandling og KI-verktøy. I tillegg diskuterer denne avhandlingen konsekvensene av de nyeste KI-fremgangene for JKPer og ulike etiske aspekter ved bruk av JKPer. Totalt sett gir denne PhD-avhandlingen en omfattende og grundig analyse av JKPer, fra teorien til designet av deres tekniske aspekter. Denne forskningen tar sikte på å lette vedtaket av JKPer og fremme forskning på dette feltet.Journalistic Knowledge Platforms (JKPs) are a type of intelligent information systems designed to augment news creation processes by combining big data, artificial intelligence (AI) and knowledge bases to support journalists. Despite their potential to revolutionise the field of journalism, the adoption of JKPs has been slow, with scholars and large news outlets involved in the research and development of JKPs. The slow adoption can be attributed to the technical complexity of JKPs that led news organisation to rely on multiple independent and task-specific production system. This situation can increase the resource and coordination footprint and costs, at the same time it poses a threat to lose control over data and face vendor lock-in scenarios. The technical complexities remain a major obstacle as there is no existing well-designed system architecture that would facilitate the realisation and integration of JKPs in a coherent manner over time. This PhD Thesis contributes to the theory and practice on knowledge-graph based JKPs by studying and designing a software reference architecture to facilitate the instantiation of concrete solutions and the adoption of JKPs. The first contribution of this PhD Thesis provides a thorough and comprehensible analysis of the idea of JKPs, from their origins to their current state. This analysis provides the first-ever study of the factors that have contributed to the slow adoption, including the complexity of their social and technical aspects, and identifies the major challenges and future directions of JKPs. The second contribution presents the software reference architecture that provides a generic blueprint for designing and developing concrete JKPs. The proposed reference architecture also defines two novel types of components intended to maintain and evolve AI models and knowledge representations. The third presents an instantiation example of the software reference architecture and details a process for improving the efficiency of information extraction pipelines. This framework facilitates a flexible, parallel and concurrent integration of natural language processing techniques and AI tools. Additionally, this Thesis discusses the implications of the recent AI advances on JKPs and diverse ethical aspects of using JKPs. Overall, this PhD Thesis provides a comprehensive and in-depth analysis of JKPs, from the theory to the design of their technical aspects. This research aims to facilitate the adoption of JKPs and advance research in this field.Doktorgradsavhandlin

SUPPORTING THE CHALLENGES OF CROSS- BOUNDARY TEAMWORK THROUGH DESIGN SCIENCE RESEARCH

In this doctoral dissertation, I relate six studies I have performed to address three challenges that cross-boundary teams (teams with great knowledge diversity) face: the challenge of coordinating knowledge and contributions, the challenge of forming cooperative attitudes, and the challenge of solving wicked management problems. These studies are inscribed in design science research, which is a paradigm of research aiming to develop prescriptive knowledge through artificial and theoretical contributions for practical problems. The artificial contributions in this research project are (1) the Coopilot App which addresses the coordination challenges by allowing individuals to evaluate how much shared understanding there is between them on the four requirements for coordination (joint objectives, joint commitments, joint resources, and joint risks), and (2) the Team Alignment Map which addresses the cooperation challenges by supporting the emergence of shared leadership through a process of cooperative joint inquiry into the four requirements. Design principles for managing coordination and supporting cooperation (the two first cross-boundary challenges) are drawn from the two artifacts. This manuscript also provides a design theory for managing the third cross-boundary challenge, i.e. wicked problem solving. By comparing the Team Alignment Map with two other similar design science research projects (the Business Model Canvas and the Data Excellence Model), I develop a design theory for visual inquiry tools that help practitioners inquire into specific wicked problems. The theoretical contributions of my research project consist in prescriptions on how team members should interact between them to collaborate effectively and overcome the three cross-boundary challenges. I propose a new conceptualization of cross-boundary teamwork as a process of joint inquiry. The view I propose is different from traditional accounts, in that I stress the importance of language. I highlight the cognitive conditions that should be met through communication to done down the boundaries between cross-boundary team members

B!SON: A Tool for Open Access Journal Recommendation

Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project

International Journal on Artificial Intelligence Tools Vol. 9, No. 4 (2000) © World Scientific Publishing Company CONCURRENT ABDUCTIVE LOGIC PROGRAMMING IN PANDORA

The extension of logic programming with abduction (ALP) allows a form of hypothetical reasoning. The advantages of abduction lie in the ability to reason with incomplete information and the enhancement of the declarative representation of problems. On the other hand, concurrent logic programming is a framework which explores AND-parallelism and/or ORparallelism in logic programs in order to efficiently execute them on multi-processor / distributed machines. The aim of our work is to study a way to model abduction within the framework of concurrent logic programming, thus taking advantage of the latter’s potential for parallel and/or distributed execution. In particular, we describe Abductive Pandora, a syntactic sugar on top of the concurrent logic programming language Pandora, which provides the user with an abductive behavior for a concurrent logic program. Abductive Pandora programs are then transformed into Pandora programs which support the concurrent abductive behavior through a simple programming technique while at the same time taking advantage of the underlying Pandora machine infrastructure