<p>Syftet med detta examensarbete var att undersöka, utifrån en etnografisk och kvalitativ ståndpunkt, möjligheten till att utöka kunskapen om Situation Awareness (SA). Forskning inom området har länge präglats av ett kvantitativt förhållningssätt vilket anses ha missgynnat och till en viss del hindrat alternativa kvalitativa forsningsansatser för att studera detta intressanta fenomen. Detta arbete försöker, i form av två studier (en litteraturstudie och en fallstudie), bryta trenden av kvalitativ forskning och presentera en annan infallsvinkel för hur SA kan vara organiserat och ett annat förhållningssätt för hur forskning kring SA kan bedrivas. Utgångspunkten för detta försök är teorierna bakom <i>Distributed Cognition</i> (DC), vilka föreslår studien av mänsklig kognition i ett större sammanhang där hjärna, kropp och omgivning bildar ett kognitivt system. </p><p>Resultatet från litteraturstudien visar på att det finns stöd för användningen av DC då utifrån dessa teorier uppstår möjligheten till att studera andra aspekter och förhållanden kring SA. Resultatet från fallstudien i sin tur ger indikationer på att inom forskningsområdet finns ett dominerat kvantitativt förhållningssätt samt går det att identifiera ett behov av kvalitativa ansatser som ett sätt att komplettera den nuvarande forskningen. </p><p>Sammanfattningsvis uppvisar detta arbete indicier som tyder på att DC och kvalitativa ansatser erbjuder andra användbara utgångspunkter och forskningsmöjligheter för studier av SA.</p>

A training method utilized in a few martial arts was found to agree strongly with current cognitive psychology theory. Further study extracted a procedural model for learning a complex set of whole-body, dyadic motor skills involving high-speed, interactive, continuous situation assessment and decision making. A broader literature survey found relevance in several fields of research, supporting the definition of four performance dimensions in the activity. Data collected from one experienced student partnering with each of ten students of various experience levels was analyzed on these four dimensions. These dimensions were found sufficient to show both individual differences and changes across an instructional intervention. Strong correlations found under linear regression were supportive of anecdotal evidence from the model??s long empirical history in training. Data provided evidence of a self-organizing dynamic emerging from the interaction of a dyad participating in this activity, and of individual differences in cognitive resource management dynamically setting allocation priorities among specific aspects of a complex motor/cognitive activity. Highly individual responses demonstrate a mechanism for insight into students that are difficult to read. Numerous comparisons and contrasts show interactivity of performance dimensions. Impact is foreseen for research, training and testing in motor learning fields, as well as situation awareness, decision making and military tactical training. Further research is recommended to replicate these findings, test hypotheses derived from them, and to extend testing of the drill-network model into other fields of learning.

In emergency management and in military operations, command and control comprises the collection of functions, systems and staff personnel that one or several executives draw on to arrive at decisions and seeing that these decisions are carried out. The large amount of available information coupled with modern computers and computer networks brings along the potential for making well-informed and quick decisions. Hence, decision-making is a central aspect in command and control, emphasizing an obvious need for development of adequate decision-supporting tools to be used in command and control centers. However, command and control takes place in a versatile environment, including both humans and artifacts, making the design of useful computer tools both challenging and multi-faceted. This thesis deals with preparatory action in command and control settings with a focus on the strategic properties of a situation, i.e., to aid commanders in their operational planning activities with the utmost goal of ensuring that strategic interaction occurs under the most favorable circumstances possible. The thesis highlights and investigates the common features of interaction by approaching them broadly using a gaming perspective, taking into account various forms of strategic interaction in command and control. This governing idea, the command and control gaming perspective, is considered an overall contribution of the thesis. Taking the gaming perspective, it turns out that the area ought to be approached from several research directions. In particular, the persistent gap between theory and applications can be bridged by approaching the command and control gaming perspective using both an applied and a theoretical research direction. On the one hand, the area of game theory in conjunction with research findings stemming from artificial intelligence need to be modified to be of use in applied command and control settings. On the other hand, existing games and simulations need to be adapted further to take theoretical game models into account. Results include the following points: (1) classification of information with proposed measurements for a piece of information's precision, fitness for purpose and expected benefit, (2) identification of decision help and decision analysis as the two main directions for development of computerized tools in support of command and control, (3) development and implementation of a rule based algorithm for map-based decision analysis, (4) construction of an open source generic simulation environment to support command and control microworld research, (5) development of a generic tool for prediction of forthcoming troop movements using an algorithm stemming from particle filtering, (6) a non-linear multi-attribute utility function intended to take prevailing cognitive decision-making models into account, and (7) a framework based on game theory and influence diagrams to be used for command and control situation awareness enhancements. Field evaluations in cooperation with military commanders as well as game-theoretic computer experiments are presented in support of the results. / QC 20100825

A training method utilized in a few martial arts was found to agree strongly with current cognitive psychology theory. Further study extracted a procedural model for learning a complex set of whole-body, dyadic motor skills involving high-speed, interactive, continuous situation assessment and decision making. A broader literature survey found relevance in several fields of research, supporting the definition of four performance dimensions in the activity. Data collected from one experienced student partnering with each of ten students of various experience levels was analyzed on these four dimensions. These dimensions were found sufficient to show both individual differences and changes across an instructional intervention. Strong correlations found under linear regression were supportive of anecdotal evidence from the model??s long empirical history in training. Data provided evidence of a self-organizing dynamic emerging from the interaction of a dyad participating in this activity, and of individual differences in cognitive resource management dynamically setting allocation priorities among specific aspects of a complex motor/cognitive activity. Highly individual responses demonstrate a mechanism for insight into students that are difficult to read. Numerous comparisons and contrasts show interactivity of performance dimensions. Impact is foreseen for research, training and testing in motor learning fields, as well as situation awareness, decision making and military tactical training. Further research is recommended to replicate these findings, test hypotheses derived from them, and to extend testing of the drill-network model into other fields of learning.

Train traffic control is a complex task in a dynamic environment. Different actors have to cooperate to meet strong requirements regarding safety, punctuality, capacity utilization, energy consumption, and more. The GMOC model has been developed and utilized in a number of studies in several different areas. This thesis describes GMOC and uses train traffic control as the application area for evaluating its utility. The GMOC model has its origin in control theory and relates to concepts of dynamic decision making. Human operators in complex, dynamic control environments must have clear goals, reflecting states to reach or to keep a system in. Mental models contain the operator’s knowledge about the task, the process, and the control environment. Systems have to provide observability, means for the operator to observe the system’s states and dynamics, and controllability, allowing the operators to influence the system’s states. GMOC allows us to constructively describe complex environments, focusing on all relevant parts. It can be utilized in user-centred system design to analyse existing systems, and design and evaluate future control systems. Our application of GMOC shows that automation providing clear observability and sufficient controllability is seen as transparent and most helpful. GMOC also helps us to argue for visualization that rather displays the whole complexity of a process than tries to hide it. Our studies in train traffic control show that GMOC is useful to analyse complex work situations. We identified the need to introduce a new control strategy improving the traffic plan by supporting planning ahead. Using GMOC, we designed STEG, an interface implementing this strategy. Improvements that have been done to observability helped the operators to develop more adequate mental models, reducing use of cognitive capacity but increasing precision of the operative traffic plans. In order to improve the traffic controllers’ controllability, one needs to introduce and share a real-time traffic plan, and provide the train drivers with up-to-date information on the surrounding traffic. Our studies indicate that driver advisory systems, including such information, reduce the need for traffic re-planning, improve energy consumption, and increase quality and capacity of train traffic. / KAJT / FTTS

This thesis problematizes the concept of usefulness, in part by taking questions to the extreme. The starting point is the contemporary view of usefulness, a view that remains within a traditional paradigm of technical rationality in which important aspects are disregarded or not perceived because they are not part of the equation. For scrutiny of technological usefulness that is a socially situated phenomenon regarding physical systems, neither interpretivist nor positivist research approaches are sufficient. Both views are required. Critical Realism supports such duality, facilitating the combination of elements from different paradigms, and provides methodological guidelines for doing this. The critical realist approach makes it possible to transcend the boundaries of technical rationality and contribute an alternative definition of usefulness that takes into account also the situated, the contextual, and the unpredictable. The aim is that this definition will contribute to a transformation of society. Concepts related to usefulness, such as predictability, controllability, effectiveness, and safety, are revisited, redefined, or complemented. Underlying aspects and mechanisms are explored and tensions identified, resulting in a theoretical contribution with models and frameworks explaining what is argued to be the true nature of usefulness. Potentiality is suggested as a complementary concept to effectiveness, similar to how resilience complements safety. Situated usefulness is then defined using these four concepts. The phenomenon known as situation awareness is scrutinized as well, and complemented by system awareness and the thesis title concept, edge awareness. Four cases, two airline crashes and two nuclear power plant events, and three future scenarios, constitute the empirical contribution. The analysis shows that the contributed frameworks and redefinition of usefulness facilitate different or extended explanations of all four events, and that future cases lack considerations of situated usefulness. Research implications center on the human role and our responsibilities in relation to the technology that we use, and on the meaning of concepts defining this role. We are situated human beings. Our role is to be involved and responsible, a role requiring awareness and controllability. The escalating ubiquity and the character of computerized technological systems make therefore the quest for edge awareness more important than ever.

The objective of the proposed research is to study the integration of humans and automation for the operation of regenerative life support systems (RLSS). RLSS combine physico-chemical and biological processes with the purpose of increasing the autonomy of space habitats and the life quality of their living organisms by properly reusing byproducts and regenerating consumable resources. However, these processes require energy and time to transform chemical compounds and organic wastes into nutrients, consumables, and edible products. Consequently, the maintenance of RLSS imposes a considerable workload on human operators. In addition, the uncertainties introduced by unintended chemical reactions promoted by material loop closure may create unexpected situations that, if unattended, could translate into performance deterioration, human errors, and failures. The availability of novel chemical and biological sensors together with computational resources enable the development of monitoring and automation systems to alleviate human workload, help avoid human error, and increase the overall reliability of these systems. This research aggregates sensor data and human-expert situation assessments to create a representation of their situation knowledge base (\gloss{skb}). The representation is used in a switched control approach to the automation of RLSS, for decision support, and human-automation coordination. The aggregation method consists of an optimization process based on particle swarms. The purpose of this work is to contribute to the methodological development of situation-oriented and user-centered design approaches to human-automation systems. Experiments and simulations are supported on the process of respiration in an aquatic habitat acting as a RLSS.

Situation awareness and collective intelligence are two technologies used in smart systems. The former renders those systems able to reason upon their abstract knowledge of what is going on. The latter enables them learning and deriving new information from a composition of experiences of their users. In this dissertation we present a doctoral research on an attempt to combine the two in order to obtain, in a collaborative fashion, situation-based rules that the whole community of entities would benefit of sharing. We introduce the KRAMER recommendation system, which we designed and implemented as a solution to the problem of not having decision support tools both situation-aware and collaborative. The system is independent from any domain of application in particular, in other words generic, and we apply its prototype implementation to context-enriched social communication scenario.

Our society is increasingly demanding situation-aware smarter software (SASS) systems, whose goals change over time and depend on context situations. A system with such properties must sense their dynamic environment and respond to changes quickly, accurately, and reliably, that is, to be context-aware and self-adaptive. The problem addressed in this dissertation is the dynamic management of context information, with the goal of improving the relevance of SASS systems' context-aware capabilities with respect to changes in their requirements and execution environment. Therefore, this dissertation focuses on the investigation of dynamic context management and self-adaptivity to: (i) improve context-awareness and exploit context information to enhance quality of user experience in SASS systems, and (ii) improve the dynamic capabilities of self-adaptivity in SASS systems. Context-awareness and self-adaptivity pose signi cant challenges for the engineering of SASS systems. Regarding context-awareness, the rst challenge addressed in this dissertation is the impossibility of fully specifying environmental entities and the corresponding monitoring requirements at design-time. The second challenge arises from the continuous evolution of monitoring requirements due to changes in the system caused by self-adaptation. As a result, context monitoring strategies must be modeled and managed in such a way that they support the addition and deletion of context types and monitoring conditions at runtime. For this, the user must be integrated into the dynamic context management process. Concerning self-adaptivity, the third challenge is to control the dynamicity of adaptation goals, adaptation mechanisms, and monitoring infrastructures, and the way they a ect each other in the adaptation process. This is to preserve the eff ectiveness of context monitoring requirements and thus self-adaptation. The fourth challenge, related also to self-adaptivity,concerns the assessment of adaptation mechanisms at runtime to prevent undesirable system states as a result of self-adaptation. Given these challenges, to improve context-awareness we made three contributions. First, we proposed the personal context sphere concept to empower users to control the life cycle of personal context information in user-centric SASS systems. Second, we proposed the SmarterContext ontology to model context information and its monitoring requirements supporting changes in these models at runtime. Third, we proposed an effi cient context processing engine to discover implicit contextual facts from context information speci fied in changing context models. To improve self-adaptivity we made three contributions. First, we proposed a framework for the identi cation of adaptation properties and goals, which is useful to evaluate self-adaptivity and to derive monitoring requirements mapped to adaptation goals. Second, we proposed a reference model for designing highly dynamic self-adaptive systems, for which the continuous pertinence between monitoring mechanisms and both changing system goals and context situations is a major concern. Third, we proposed a model with explicit validation and veri cation (V&V) tasks for self-adaptive software, where dynamic context monitoring plays a major role. The seventh contribution of this dissertation, the implementation of Smarter-Context infrastructure, addresses both context-awareness and self-adaptivity. To evaluate our contributions, qualitatively and quantitatively, we conducted several comprehensive literature reviews, a case study on user-centric situation-aware online shopping, and a case study on dynamic governance of service-oriented applications. / Graduate

Submitted by Claudia Berti (claudiabberti@gmail.com) on 2018-06-04T08:46:28Z No. of bitstreams: 2 Tese_DOC_702806.pdf: 2723844 bytes, checksum: 41136d680ab0e665de58c6e74bbe7fe5 (MD5) Carta Comprovante_DOC_702806.pdf: 377043 bytes, checksum: 09e3818f3e8c5eaed8195aa5beef0112 (MD5) / Approved for entry into archive by Eunice Nunes (eunicenunes6@gmail.com) on 2018-06-04T12:44:18Z (GMT) No. of bitstreams: 2 Tese_DOC_702806.pdf: 2723844 bytes, checksum: 41136d680ab0e665de58c6e74bbe7fe5 (MD5) Carta Comprovante_DOC_702806.pdf: 377043 bytes, checksum: 09e3818f3e8c5eaed8195aa5beef0112 (MD5) / Approved for entry into archive by Eunice Nunes (eunicenunes6@gmail.com) on 2018-06-04T12:59:57Z (GMT) No. of bitstreams: 2 Tese_DOC_702806.pdf: 2723844 bytes, checksum: 41136d680ab0e665de58c6e74bbe7fe5 (MD5) Carta Comprovante_DOC_702806.pdf: 377043 bytes, checksum: 09e3818f3e8c5eaed8195aa5beef0112 (MD5) / Made available in DSpace on 2018-06-04T13:00:10Z (GMT). No. of bitstreams: 2 Tese_DOC_702806.pdf: 2723844 bytes, checksum: 41136d680ab0e665de58c6e74bbe7fe5 (MD5) Carta Comprovante_DOC_702806.pdf: 377043 bytes, checksum: 09e3818f3e8c5eaed8195aa5beef0112 (MD5) Previous issue date: 2017-08-28 / Não recebi financiamento / Situation Awareness (SAW) is a concept widely used in areas that require critical decision making, and refers to the ability of an individual or team to perceive, understand and anticipate the future state of a current situation, which is influenced by the dynamicity and critical nature of events. SAW is considered as the main precursor of the decision-making process. In the emergency response area, obtaining and maintaining SAW requires a great effort from the human operator, the cognitive overload required in the activity, high level of stress involving the care, exhaustive shifts that may negatively reflect the care process and consequently the decision process as one all. Decision support systems that address aspects of the SAW can contribute to the enrichment and maintenance of the operator's SAW and in the decision-making process. Given this context, this work presents a Situational Predictive Model to systematize the development of modules to support the human operator's SAW in emergency response systems, which provides for the use of service models and protocols of institutions acting as prototypical situations. Objectively the model proposes the prediction and or the premature identification of the situation while the applicant has emergency assistance. A Conceptual Model was developed that guided the construction of the Predictive Model and will serve as basis for other developments. So-called human sensors and social sensors have become important sources of information especially in social networks. For the treatment of this data, text classifier methods are used with satisfactory results that cover the areas of education, security, entertainment, commercial, among others. For the emergency responses domain, object of this thesis, human sensors are the main source of information and machine learning techniques as text classifiers show important alternatives. In order to be validated, the Predictive Situations Model was implemented with the creation of a vocabulary based on the actual decision-making models of the Military Police of the State of São Paulo (PMESP) and the development of algorithms two classifying methods (Bag of Words and Naïve Bayes). Tests were performed with four different types of input instances (sentences). For all the metrics analyzed (accuracy, accuracy and coverage) the tests demonstrated superiority of the Naïve Bayes algorithm. The difference between the hit rates in relation to the Bag of Word algorithm for the class of instances with the highest degree of identification difficulty was over 37%. These results demonstrated good potential the Predictive Situations Model to collaborate with the existing systems of emergency services, allowing more attendance effectiveness and reduction of the cognitive overload that the attendants are routinely subjected to. / Consciência da situação ou consciência situacional (Situation Awareness – SAW) é um conceito amplamente utilizado em áreas que requerem tomada de decisão crítica, e se refere à habilidade de um indivíduo ou equipe de percepção, compreensão e antecipação de estado futuro de uma situação corrente, que é influenciada pela dinamicidade e natureza crítica de eventos. SAW é considerada como principal precursora do processo decisório. Em domínios, por exemplo, de resposta à emergência, obter e manter SAW requer do operador humano grande esforço, pela sobrecarga cognitiva exigida na atividade, alto nível de estresse que envolve o atendimento, turnos exaustivos que podem refletir negativamente no processo de atendimento e consequentemente no processo decisório como um todo. Sistemas de apoio à tomada de decisão que contemplam aspectos da SAW podem contribuir no enriquecimento e manutenção da SAW do operador e no processo decisório. Diante desse contexto, este trabalho apresenta um Modelo Preditivo de Situações para sistematizar o desenvolvimento de módulos de apoio a SAW de operadores humanos em sistemas de resposta à emergência, que prevê a utilização de modelos de atendimento e protocolos das instituições atuando como situações prototípicas. Objetivamente o modelo propõe a previsão e ou a identificação prematura da situação em tempo real ao atendimento da emergência. Conjuntamente foi desenvolvido um Modelo Conceitual que norteou a construção do Modelo Preditivo e servirá como base a outros desenvolvimentos. Atualmente os denominados sensores humanos e sensores sociais, especialmente de redes sociais, estão sendo utilizados, de forma crescente, como importantes fontes de informação para a melhor compreensão de situações em diferentes áreas de aplicação. No domínio de resposta à emergência, objeto de estudo desta tese, os sensores humanos são a principal fonte de informação, sobre a qual técnicas de aprendizagem de máquina como classificadores de texto foram aplicadas com resultados muito positivos. Para ser validado, o Modelo Preditivo de Situações foi implementado com a criação de um vocabulário baseado nos modelos decisórios reais da Polícia Militar do Estado de São Paulo (PMESP) e com o desenvolvimento de algoritmos de dois métodos classificadores (Bag of Words e Naïve Bayes). Testes foram realizados com quatro tipos diferentes de instâncias de entrada (frases). Para todas as métricas analisadas (precisão, acurácia e cobertura) os testes demostraram superioridade do algoritmo Naïve Bayes. A diferença entre a taxa de acerto em relação ao algoritmo Bag of Word para a classe de instâncias com maior grau de dificuldade de identificação foi superior a 37%. Tais resultados demonstraram bom potencial do Modelo Preditivo de Situações de colaborar com os sistemas já existentes de atendimento emergencial, possibilitando maior efetividade no atendimento e diminuição da sobrecarga cognitiva a que são submetidos os atendentes cotidianamente.