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Successful aging with and into disability is a challenge in various countries due to an increasing aging population. Prior research indicate that brain training may stimulate but significant improvement may take time. To sustain improvement, this exploratory study suggests adopting a technology-assisted affective socio-cognitive approach to arrest cognitive and social decline holistically. WHO's International Classification of Functioning, Disability and Health (ICF) supports the holistic dimensions to adaptive, and engaging sustenance of quality of life. We scope our study to the participation aspect; extending context and various context-aware interactions. This study reports on the use of semiotics for inclusive design to increase cognitive engagement with youth and some seniors with Mild Cognitive Impairment (MCI), forming the bases for design thinking-based technology-assisted scaffolds/affordances.

Online knowledge building communities (OKBCs) prove beneficial in informal learning settings. Extending their use to the instructional design of formal learning environments requires identification methods of the central, intermediate and peripheral community layers. This study proposes such a social learning analytics method, i.e., an automated discourse analysis based on Natural Language Processing. The method was applied to the dialog produced by N = 1,990 participants in 20 blogger communities. Centrality criteria based on Cohesion Network Analysis were highly consistent and could successfully identify the socio-cognitive layers of the analyzed OKBCs. Ongoing research proposes instructional design based on formal learners’ interactions with OKBCs.

One of the challenges confronted by teachers in the context of teaching English as a Second Language (ESL) is to enhance second language learning by using technology based cognitive and socio cognitive approaches. Supportively various research studies have proved that technology plays a major role in supporting the learners in a number of ways in the process of which they become self-directed and independent. This paper examines the use of 'text constructing software' and 'multimedia simulation' in teaching paraphrasing and logo designing to a group of students pursuing Masters programme in Business Management. It was found that students could effectively learn to improve socio cognitive skills in their writing samples.

International audience; Artificial agents are becoming artificial companions, interacting with the user on a long-term basis. This evolution brought new challenges to the affective computing domain, such as designing artificial agents with personalities to the benefits of the user. Endowing artificial agents with personality could help to increase the agent's believability, hence easing the interaction. This paper touches on two questions pertaining to computational personality modeling: 1/ how to produce artificial personalities which can inform personality researchers, whether from computer sciences or psychology and 2/ will behaviors produced by artificial agents be perceived by users as putting the programmed personality across as such. We propose to use a data-driven approach to endow artificial agents with personality, using the regulatory focus theory as a framework. We used machine-learned game strategies, in the form of alternative decision trees computed from human data, to convey the personality of artificial agents. We then tested whether these personalities can be perceived by users after playing a game against these agents. We used two artificial agents as controls: one randomly playing and one with an " average / depersonalized " strategy. On the one hand, our results show that agents' regulatory focus, when programmed, can be accurately perceived by users. On the other hand, our results also point out that personality will be perceived by users even if the agent's design does not intend to transmit one.

In the last decade, the availability of massive amounts of new data, and the development of new machine learning technologies, have augmented reasoning systems to give rise to a new class of computing systems. These Cognitive Systems learn from data, reason from models, and interact naturally with us, to perform complex tasks better than either humans or machines can do by themselves. In essence, cognitive systems help us perform like the best in each domain by penetrating the complexity of big data and leveraging the power of models. O ne of the first cognitive systems, Watson, demonstrated through a Jeopardy! exhibition match, that it was capable of answering complex factoid questions as effectively as the worlds champions. Follow-on cognitive systems perform other tasks, such as discovery, reasoning, and multi-modal understanding in a variety of domains, such as healthcare, insurance, and education. We believe such cognitive systems will transform every profession, industry, and our everyday life for the better. In this talk, I will give an overview of the applications and key capabilities of cognitive systems, and highlight the role pervasive computing will play in such systems.

This paper reviews challenges and summarize the progress accomplished by the Social Cognitive Networks Academic Research Center of the Network Science Collaborative Technology Alliance. The focus is on potential impact that this research may have on unique needs of military, foremost the US Army, to effectively and efficiently operate in the increasingly complex and interconnected networks of societies and their component communities. The review of the progress and current status of research of the center provide state-of-the-art view of the relevant areas of social cognitive network science.

In this talk, I would like to illustrate how humans minds and brains may be approached scientifically, with a particular focus on human visual system and its cognitive characteristics. As we shall see in the Special sessions “Fluency in Communication between Human, Machine, and Environment” in this afternoon, the cognitive science perspective can be applied to many issues of human perception, cognition, attention, action, and decision making.

Effective relationships between people and technology are essential for organizational response (agility, adaptation, and innovation). Advances in computing power, and the rise of complex ubiquitous systems, raise a challenge for managing this relationship given limits of human physical and cognitive capacities. To re-align people with computing technology involves either improved human training, or streamlining technologies to fit human needs, abilities, and perceptions. This paper looks at this socio-technical gap and makes a case for intelligent agent mediation through passive human-input monitoring (human-context awareness) and basic models of human behavior. The target audience is interdisciplinary, involving the cognitive informatics, agent systems, bodynet, socio-technical systems, and human-computer-interface communities. The overall contribution is in the combination of socio-technical systems engineering and human factors concepts with the agent-based paradigm and cognitive sensing technologies towards new, “Human-tech” friendly agent applications for everyday socio-technical systems. As such an early architectural design for such agents is presented, as well as future research directions toward its development.

Recently, product models serve lifecycle product information for wide area of engineering activities. This extended purpose results very large and complex product models with high number of relations. Restricted capability of product models for representation of some important elements of the human thinking process during definition of engineering objects in current industrial modeling systems makes it impossible to evaluate, revise, and change hundreds of already decided engineering object parameters. In this paper, a new methodology and several related processes are introduced in order to better communication between human and model generation processes. The main essence of the proposed product modeling is that human intent controlled development of engineering objects is realized by an extension to current industrial product model called as model of information content. Engineering objectives and contextual connections are defined as human intent driven features and applied at decision on engineering object parameters and at control of processes for engineering object parameter optimization and relating. The proposed modeling is connected to knowledge handling and knowledge based advisory functionalities of industrial product modeling systems. As a conclusion, a new modeling is placed between human and model information generation procedures in order to represent human originated background of model information for engineering objects.

The richness of today's electronic communications mirrors physical world: activities such as shopping, business and scientific collaboration are conducted online. Current interactions have become a form of social exchange where participants must deal with complexity, uncertainty and risk. We propose a policy specification approach that combines social sciences and trust theory to facilitate ad-hoc interactions of self-interested parties in open environments. Our socio-cognitive approach allows us to reason about uncertainty and risk involved in a transaction, and automatically calculate the minimum trust threshold needed to mitigate the vulnerabilities. The trust threshold comprises the core of security policies that govern the interactions. The threshold calculation is based on balancing objective and subjective trust components, which together predict that a transaction will result in an acceptable outcome. We propose to apply the prospect theory (D. Kahneman and A. Tversky, 1979) to specify policies that determine a set of acceptable outcomes. We present the trust threshold negotiation primitives.

Many modern systems consist of a dynamic network of interconnected people, processes and technologies. The evolution of such complex adaptive systems is governed by multiple stakeholders with varying value propositions and equities. Enlightened systems engineering and management must deal holistically with these systems using interacting processes from both disciplines. Linking fundamentals from cognitive science, organizational theory, networks, systems engineering and technology development, we identify the patterns and deep structures in their evolution. This results in a framework of innovation, integration and governance processes for combined systems engineering and management of complex adaptive systems.

There is often a fundamental mismatch between the way human process knowledge and the way it is processed by technology support system for product design. It is needed to develop tools, methods and technology which integrate smoothly with the design process. In this paper, a cognitive model of knowledge processing is described. A cognitive knowledge modeling method is presented. Suggestions on cognitive support for knowledge based system are provided. Cognitive knowledge modeling will result in a natural integration of knowledge based systems into the design process.

From the very beginning of technological development, humans have had the goal to build systems that can capture the cognitive abilities of nature. The ability to process control and communications information on the battlefield is important. Such control can be offered in the form of a software-defined radio (SDR) based on cognitive radio technology. Cognitive radio technology could theoretically interoperate amongst incompatible communication systems used by friendly and coalition forces. According to Dr. Joseph Mitola, the cognitive radio vision is as follows: a smart radio that could switch spectrum on the fly. Put another way, a cognitive radio is a radio function that would be capable of switching from a crowded part of the radio frequency spectrum to a radio frequency region that is more sparsely populated but can still receive the original signals of interest. Cognitive radio technology and cognitive engineering is based upon the human cognitive hierarchy process, however, for its practicable realization to occur, the authors argue a holistic systems engineering approach that appears to include physical, informational, cognitive, social domain along with machine-, application-, and human-centered sub-domain combat conditions and thermal management systems engineering concepts must, from the beginning, be considered.

There is a lack of educational technology to support cognitive systems engineering topics such as models of human performance in dynamic environments. This paper describes the Cognitive Systems Engineering Educational Software (CSEES) system, an integrated toolset designed to facilitate curricula related to human judgment and decision-making performance modeling and evaluation. CSEES provides students with the means to generate and analyze performance data using multiple methods. It also includes documentation and tutorials. Its flexible design facilitates adding new judgment and decision making task environments. The paper describes the initial system implementation as a Microsoft Excel add-on, a preliminary evaluation as part of a graduate engineering course, and planned future work.

The infusion of cognitive engineering (CogE) methods and tools into traditional systems engineering processes and practices is becoming an important priority as the systems engineering community begins to tackle system of systems (SoS) problems. As one illustration, the military is interested in creating cognitively-inspired systems (as small as a PDA and as large as a weapon platform) that maximally exploit human potential while also accelerating both human supported and automated decision making. To date, cognitive engineering has been successfully applied to the planning and requirements definition phases of systems engineering (also known as front-end analysis) but has yet to be infused into the remaining phases of systems engineering. To span the full systems engineering lifecycle, it is important, first and foremost, to communicate the return-on-investment to the various stakeholders to get their buy in. The second question that needs to be answered is whether or not "cognitive engineering is ready for primetime". This paper presents promising technical and management strategies to overcome the challenges in introducing cognitive engineering into system-of-systems engineering (SOSE). Specifically, it presents a representative set of cognitive engineering methods and tools to span the full SoS life-cycle as well as cognitive engineering awareness initiatives to penetrate both the DoD acquisition community and commercial industry.

The aim of this article is to pave way for a rough set based calculus of approximate judgment by socio-cognitive agents. As the major basis of judgment is matching, we examine two general kinds of matching within the framework of Skowron-Stepaniuk's approximation spaces: whether or not, and to which extent a particular matches an ideal and whether or not, and to which extent two universals match each other. We define several forms of rough judgment concerning the following aspects: satisfiability of formulas and sets of formulas, applicability and validity of rules, and results of rule application.

Human traits and needs are the fundamental force underlying almost all phenomena in human task performances, engineering organizations, and societies. This paper explores the cognitive foundations of human traits and cognitive properties of human factors in engineering. The fundamental traits of human beings are identified, and the hierarchical model of basic human needs is formally describes. The characteristics of human factors and their influences in engineering organizations and socialization are explored. Based on the models of basic human traits, needs, and their influences, driving forces behind the human factors in engineering and society are revealed. A formal model of human errors in task performing is derived, and case studies of the error model in software engineering are presented.

This paper presents a rigorous treatment of human perceptual processes such as emotions, motivations, and attitudes. A set of mathematical models and formally described cognitive processes is developed. The interactions and relationships between motivation and attitude are formally described in real-time process algebra (RTPA). Applications of the mathematical models of motivations and attitudes in software engineering are demonstrated. This work is the detailed description of a part of the layered reference model of the brain (LRMB) that provides a comprehensive model for explaining the fundamental cognitive processes of the brain and their interactions.

Decision problems in which multiple actors with different interests play a role abound in fields like transport policy, telecommunications policy, water resource management, and environmental management. As, in essence, decision making is a process of and between the actors, the social sciences have relevant insights to offer to analysts who aim to support decision makers in these situations. This paper briefly outlines a number of social science models of multi-actor decision making, and explores their consequences for systems analytic support. Given the variety of social science models and of multi-actor decision situations, a meta-design problem emerges: what line of approach to follow, and which tools to use in what situation? A few elementary guidelines for this methodological design problem are given.

Cognitive engineering is largely concerned with creating environmental designs to support skillful and effective human activity. Psychological models must meet special constraints in order to effectively support this enterprise. The goal is to identify a set of constraints that models must meet if they can usefully guide design. The author discusses two types of constraints on acceptable psychological models that arise due to the need to represent both internal and external influences on cognition and behavior. The first set of constraints is structural. The second set of constraints concerns the content of acceptable models. It is concluded that cognitive engineering most requires models capable of representing the human and environment as an integrated unit, and which represent the activities underlying fluent, skilled behavior. >

We develop a framework for improving knowledge-intensive aspects of administrative processes. We depart from the premise that changing business processes amounts to manipulating process knowledge in humans and machines, and can thus be seen as a special case of knowledge management. Such a view requires a clear view of what process knowledge is. In this paper, we develop such a view based on concepts from cognitive science. We give some implications of this model for analyzing, redesigning, and implementing knowledge-intensive processes.