A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data
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paper_title: Perceptions of moral character modulate the neural systems of reward during the trust game

paper_content:

Studies of reward learning have implicated the striatum as part of a neural circuit that guides and adjusts future behavior on the basis of reward feedback. Here we investigate whether prior social and moral information about potential trading partners affects this neural circuitry. Participants made risky choices about whether to trust hypothetical trading partners after having read vivid descriptions of life events indicating praiseworthy, neutral or suspect moral character. Despite equivalent reinforcement rates for all partners, participants were persistently more likely to make risky choices with the 'good' partner. As expected from previous studies, activation of the caudate nucleus differentiated between positive and negative feedback, but only for the 'neutral' partner. Notably, it did not do so for the 'good' partner and did so only weakly for the 'bad' partner, suggesting that prior social and moral perceptions can diminish reliance on feedback mechanisms in the neural circuitry of trial-and-error reward learning.
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paper_title: Computational trust and reputation models for open multi-agent systems: a review

paper_content:

In open environments, agents depend on reputation and trust mechanisms to evaluate the behavior of potential partners. The scientific research in this field has considerably increased, and in fact, reputation and trust mechanisms have been already considered a key elements in the design of multi-agent systems. In this paper we provide a survey that, far from being exhaustive, intends to show the most representative models that currently exist in the literature. For this enterprise we consider several dimensions of analysis that appeared in three existing surveys, and provide new dimensions that can be complementary to the existing ones and that have not been treated directly. Moreover, besides showing the original classification that each one of the surveys provide, we also classify models that where not taken into account by the original surveys. The paper illustrates the proliferation in the past few years of models that follow a more cognitive approach, in which trust and reputation representation as mental attitudes is as important as the final values of trust and reputation. Furthermore, we provide an objective definition of trust, based on Castelfranchi's idea that trust implies a decision to rely on someone.
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paper_title: On trust and influence: A computational red teaming game theoretic perspective

paper_content:

The concept of trust has attracted the attention of many researchers over the years who studied the impact of trust in many domains. Trust is a ubiquitous concept. It is pervasive in every aspect of our life, from interpersonal relationships to national defence and security applications. However, despite the vast literature on trust, we are not close enough to mastering the dynamics of trust. One reason is that if we define procedural steps for trust, we simultaneously define steps for deception; thus, we simply define a vacuous cycle. Another reason is that, the dynamics of trust change as the world changes. But how can we then study trust? This paper connects the interdisciplinary literature to synthesize a Computational Red Teaming (CRT) based model of trust that defines opportunities whereby computational intelligence techniques, more specifically, evolutionary game theory researchers, can contribute to this vastly growing research area. We offer a position on the topic by reviewing games for trust and introduce a new theoretic game to study influence and transfer of trust.
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paper_title: Managers as Initiators of Trust: An Exchange Relationship Framework for Understanding Managerial Trustworthy Behavior

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In many approaches to interpersonal and organizational trust, researchers focus on employees' perceptions that their managers are trustworthy. We turn the tables, however, and examine the antecedents of managerial trustworthy behavior and the challenge of initiating trust. Drawing on agency and social exchange theories, we present an exchange relationship framework that identifies organizational, relational, and individual factors that encourage or constrain managerial trustworthy behavior.
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paper_title: Trust in the workplace: Factors affecting trust formation between team members

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The authors used survey data from 127 professional-level employees working in 8 industries to assess the effects of respondent's trusting stance and (a) the trustee's organization membership (internal or external), (b) the hierarchical relationship (supervisor or peer), and (c) the gender of the trustee, on initial trust level for a new project team member. The authors found that trusting stance was positively related to initial trust level. The authors also found an interaction effect between respondent gender and trustee gender on initial trust. Specifically, male initial trust level was higher for a new male team member and lower for a new female team member. The present study provided additional understanding of the formation of initial trust levels and its importance for team functioning.
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paper_title: SecSDLC: A Practical Life Cycle Approach for Cloud-based Information Security

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Cloud computing services offer significant benefits to information technology (IT) systems such as reduced cost and shorter implementation time compared to traditional IT environments. However, the cloud multi-tenancy and web-enabled architecture creates a complex environment in which to develop and manage information security and compliance programs. At the enterprise level, risk and threat management can be an issue if it fails to protect cloud confidentiality, integrity, and availability (CIA). In this paper, a practical cloud security system development life cycle (SecSDLC) methodology is proposed to provide a holistic approach to effective and efficient cloud information security. The SecSDLC is based on industry best practices, and widely used and accepted methodologies such as waterfall SDLC, and NIST SP 800-64 revision 2 information security. Our previously developed solutions for cloud intrusion detection and prevention, security system monitoring, secure SLA, and compliance auditing are incorporated into the SecSDLC. A formal methodology is proposed to address concerns regarding cloud security and compliance requirements. The goal is to increase the probability of a successful information security program and reduce the likelihood of missing or inadequate components that may compromise cloud information security.
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paper_title: On trust and influence: A computational red teaming game theoretic perspective

paper_content:

The concept of trust has attracted the attention of many researchers over the years who studied the impact of trust in many domains. Trust is a ubiquitous concept. It is pervasive in every aspect of our life, from interpersonal relationships to national defence and security applications. However, despite the vast literature on trust, we are not close enough to mastering the dynamics of trust. One reason is that if we define procedural steps for trust, we simultaneously define steps for deception; thus, we simply define a vacuous cycle. Another reason is that, the dynamics of trust change as the world changes. But how can we then study trust? This paper connects the interdisciplinary literature to synthesize a Computational Red Teaming (CRT) based model of trust that defines opportunities whereby computational intelligence techniques, more specifically, evolutionary game theory researchers, can contribute to this vastly growing research area. We offer a position on the topic by reviewing games for trust and introduce a new theoretic game to study influence and transfer of trust.
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paper_title: The N-Player Trust Game and its Replicator Dynamics

paper_content:

Trust is a fundamental concept that underpins the coherence and resilience of social systems and shapes human behavior. Despite the importance of trust as a social and psychological concept, the concept has not gained much attention from evolutionary game theorists. In this letter, an ${N}$ -player trust-based social dilemma game is introduced. While the theory shows that a society with no untrustworthy individuals would yield maximum wealth to both the society as a whole and the individuals in the long run, evolutionary dynamics show this ideal situation is reached only in a special case when the initial population contains no untrustworthy individuals. When the initial population consists of even the slightest number of untrustworthy individuals, the society converges to zero trusters, with many untrustworthy individuals. The promotion of trust is an uneasy task, despite the fact that a combination of trusters and trustworthy trustees is the most rational and optimal social state. This letter presents the game and results of replicator dynamics in a hope that researchers in evolutionary games see opportunities in filling this critical gap in the literature.
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paper_title: Supporting trust in virtual communities

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At any given time, the stability of a community depends on the right balance of trust and distrust. Furthermore, we face information overload, increased uncertainty and risk taking as a prominent feature of modern living. As members of society, we cope with these complexities and uncertainties by relying trust, which is the basis of all social interactions. Although a small number of trust models have been proposed for the virtual medium, we find that they are largely impractical and artificial. In this paper we provide and discuss a trust model that is grounded in real-world social trust characteristics, and based on a reputation mechanism, or word-of-mouth. Our proposed model allows agents to decide which other agents' opinions they trust more and allows agents to progressively tune their understanding of another agent's subjective recommendations.
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paper_title: Using trust for secure collaboration in uncertain environments

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The SECURE project investigates the design of security mechanisms for pervasive computing based on trust. It addresses how entities in unfamiliar pervasive computing environments can overcome initial suspicion to provide secure collaboration.
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paper_title: Dynamic trust model for reliable transactions in multi-agent systems

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Most network applications such as pervasive computing, grid computing, P2P etc. can be viewed as multi-agent systems which are open, anonymous and dynamic in nature. Due to such nature multi-agent systems present potential threats in ensuring secured communication. One of the key feasible ways to minimize threats is to evaluate the trust and reputation of the interacting agents. Many trust models have done so, but they fail to properly evaluate trust when malicious agents behave in an unpredictable way. Not only that they are also ineffective in providing quick response to a malicious agent's oscillating behavior i.e., they are unable to assess the true nature of an opportunistic agent. To cope with such strategically altering behavior this paper presents a dynamic trust model where we analyze the different factors related to the trust of an agent and then propose a comprehensive mathematical model for evaluating trust. Simulations show that our model compared to other existing models can effectively cope with the strategic behavioral change of an agent and at the same time efficiently isolate the malicious agents.
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paper_title: Modelling Trade and Trust Across Cultures

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Misunderstandings arise in international trade due to difference in cultural background of trade partners. Trust and the role it plays in trade are influenced by culture. Considering that trade always involves working on the relationship with the trade partner, understanding the behaviour of the other is of the essence. This paper proposes to involve cultural dimensions in the modelling of trust in trade situations. A case study is presented to show a conceptualisation of trust with respect to the cultural dimension of performance orientation versus cooperation orientation.
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paper_title: Review on Computational Trust and Reputation Models

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The scientific research in the area of computational mechanisms for trust and reputation in virtual societies is a recent discipline oriented to increase the reliability and performance of electronic communities. Computer science has moved from the paradigm of isolated machines to the paradigm of networks and distributed computing. Likewise, artificial intelligence is quickly moving from the paradigm of isolated and non-situated intelligence to the paradigm of situated, social and collective intelligence. The new paradigm of the so called intelligent or autonomous agents and multi-agent systems (MAS) together with the spectacular emergence of the information society technologies (specially reflected by the popularization of electronic commerce) are responsible for the increasing interest on trust and reputation mechanisms applied to electronic societies. This review wants to offer a panoramic view on current computational trust and reputation models.
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paper_title: Reasoning about Rational Agents

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One goal of modern computer science is to engineer computer programs that can act as autonomous, rational agents; software that can independently make good decisions about what actions to perform on our behalf and execute those actions. Applications range from small programs that intelligently search the Web buying and selling goods via electronic commerce, to autonomous space probes. This book focuses on the belief-desire-intention (BDI) model of rational agents, which recognizes the primacy of beliefs, desires, and intentions in rational action. The BDI model has three distinct strengths: an underlying philosophy based on practical reasoning in humans, a software architecture that is implementable in real systems, and a family of logics that support a formal theory of rational agency.The book introduces a BDI logic called LORA (Logic of Rational Agents). In addition to the BDI component, LORA contains a temporal component, which allows one to represent the dynamics of how agents and their environments change over time, and an action component, which allows one to represent the actions that agents perform and the effects of the actions. The book shows how LORA can be used to capture many components of a theory of rational agency, including such notions as communication and cooperation.
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paper_title: TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources

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In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for another, may betray that trust by not performing the action as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. There is therefore a need to develop a model of trust and reputation that will ensure good interactions among software agents in large scale open systems. Against this background, we have developed TRAVOS (Trust and Reputation model for Agent-based Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents, and when there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate.
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paper_title: Motivated Reinforcement Learning Curious Characters For Multiuser Games Motivated Reinforcement Learning Curious Characters For Multiuser Games

paper_content:

Motivated learning is an emerging research field in artificial intelligence and cognitive modelling. Computational models of motivation extend reinforcement learning to adaptive, multitask learning in complex, dynamic environments the goal being to understand how machines can develop new skills and achieve goals that were not predefined by human engineers. In particular, this book describes how motivated reinforcement learning agents can be used in computer games for the design of non-player characters that can adapt their behaviour in response to unexpected changes in their environment. This book covers the design, application and evaluation of computational models of motivation in reinforcement learning. The authors start with overviews of motivation and reinforcement learning, then describe models for motivated reinforcement learning. The performance of these models is demonstrated by applications in simulated game scenarios and a live, open-ended virtual world. Researchers in artificial intelligence, machine learning and artificial life will benefit from this book, as will practitioners working on complex, dynamic systems in particular multiuser, online games.
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paper_title: Trust in LORA: towards a formal definition of trust in BDI agents

paper_content:

Trust plays a fundamental role in multi-agent systems in which tasks are delegated or agents must rely on others to perform actions that they themselves cannot do. Dating from the mid-1980s, the Belief-Desire-Intention architecture (BDI) is the longest-standing model of intelligent agency used in multi-agent systems. Part of the attraction of BDI is that it is amenable to logical formalisms such as Wooldridge’s Logic Of Rational Agents (LORA). In a previous paper the present authors introduced a model of trust, here named the Ability-Belief-Commitment-Desire (ABCD) model, that could be implemented within the BDI framework. This paper explores the definition of the ABCD model within the LORA formalism.
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paper_title: PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities

paper_content:

Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.
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paper_title: Computational trust and reputation models for open multi-agent systems: a review

paper_content:

In open environments, agents depend on reputation and trust mechanisms to evaluate the behavior of potential partners. The scientific research in this field has considerably increased, and in fact, reputation and trust mechanisms have been already considered a key elements in the design of multi-agent systems. In this paper we provide a survey that, far from being exhaustive, intends to show the most representative models that currently exist in the literature. For this enterprise we consider several dimensions of analysis that appeared in three existing surveys, and provide new dimensions that can be complementary to the existing ones and that have not been treated directly. Moreover, besides showing the original classification that each one of the surveys provide, we also classify models that where not taken into account by the original surveys. The paper illustrates the proliferation in the past few years of models that follow a more cognitive approach, in which trust and reputation representation as mental attitudes is as important as the final values of trust and reputation. Furthermore, we provide an objective definition of trust, based on Castelfranchi's idea that trust implies a decision to rely on someone.
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paper_title: PSO-TPS: An Optimal Trust Path Selection Algorithm Based on Particle Swarm Optimization in Small World Network

paper_content:

Small world network is a type of mathematical graph, in which most nodes are not neighbors of one another, but can be reached from every other by a small number of hops. P2P network is a typical small world network, it has a large scale and high risks, so trust model building and Trust Path Selecting (TPS) become big challenges. To solve TPS problem, we first reduce the scale of the complex P2P network by identifying and deleting the equivalent nodes. Then we provide a Trust Path Selection Algorithm based on Particle Swarm Optimization (PSO). In the algorithm, after initializing the particle swarm, each particle can update the speed and location according to its information, and then produce a new particle with better value. Repeating that process continually to implement the global search of the space, we can get the better trust path in the networks. The experimental results show that this algorithm is effective and efficient in finding the sub optimal solution of trust path, hence it can be applied in trust path searching in such small-world networks as P2P network.
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paper_title: Incorporating trust into the BDI architecture

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Trust is becoming a major issue in Multi-Agent Systems (MAS), in which agents need to delegate some tasks to others. Trust can be defined as the degree of confidence in an agent's prediction of another agent's future behaviour. In the context of the BDI model, trust can be defined as the beliefs that one agent has of another's beliefs, desires, intentions and capabilities. This paper first presents our own version of BDI interpreter. Then, the above vision of trust is incorporated into the BDI interpreter in order to help an agent in the decision process before delegating tasks to other agents.
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paper_title: FCTrust: A Robust and Efficient Feedback Credibility-Based Distributed P2P Trust Model

paper_content:

The open, sharing and anonymous nature of peer-to-peer (P2P) network has offered opportunities and threats. One feasible way to minimize threats is to establish the reputation-based global trust model. Previous work about the global trust model is almost based on the assumption that the peer with higher trust value will provide more honest feedbacks, and make the quality of feedback of a peer approximately equal to that of service of the peer. However, this is not always true. As for this problem, this paper proposes a robust feedback credibility (FC) based distributed P2P global trust model (FCTrust), used for quantifying and evaluating the trustworthiness of participants. Theoretical analysis and simulation experiments show that, FCTrust has advantages in combating various malicious behaviors such as dishonest feedbacks and collusions, over the current global trust models, and demonstrates more robustness and effectiveness. Moreover, we find more performance gains in convergence speed and message overhead than previous models.
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paper_title: Optimism and Pessimism in Trust

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Artificial agents do not exist in the world in solitude. They are required to interact with others, and thus must reason in some fashion about those they interact with. This paper presents a view of trust which artificial agents can use to help in such reasoning processes, providing them with a means to judge possible future behaviour on the basis of past experience. The paper discusses the notion of ‘dispositions’ of trusting behaviour, which we call Optimism, Pessimism and Realism. Each different disposition results in different trust estimations from an agent. We discuss the possible effects of these differences. Finally, we present the concept of memory in trusting agents, and briefly suggest some ways in which memory spans can affect the trusting decisions of such agents, with different dispositions.
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paper_title: Using fuzzy logic and Q-learning for trust modeling in multi-agent systems

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Often in multi-agent systems, agents interact with other agents to fulfill their own goals. Trust is, therefore, considered essential to make such interactions effective. This work describes a trust model that augments fuzzy logic with Q-learning to help trust evaluating agents select beneficial trustees for interaction in uncertain, open, dynamic, and untrusted multi-agent systems. The performance of the proposed model is evaluated using simulation. The simulation results indicate that the proper augmentation of fuzzy subsystem to Q-learning can be useful for trust evaluating agents, and the resulting model can respond to dynamic changes in the environment.
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paper_title: Spreading activation models for trust propagation

paper_content:

Semantic Web endeavors have mainly focused on issues pertaining to knowledge representation and ontology design. However, besides understanding information metadata stated by subjects, knowing about their credibility becomes equally crucial. Hence, trust and trust metrics, conceived as computational means to evaluate trust relationships between individuals, come into play. Our major contributions to semantic Web trust management are twofold. First, we introduce our classification scheme for trust metrics along various axes and discuss advantages and drawbacks of existing approaches for semantic Web scenarios. Hereby, we devise our advocacy for local group trust metrics, guiding us to the second part which presents Appleseed, our novel proposal for local group trust computation. Compelling in its simplicity, Appleseed borrows many ideas from spreading activation models in psychology and relates their concepts to trust evaluation in an intuitive fashion.
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paper_title: A Fuzzy Approach to Reasoning with Trust, Distrust and Insufficient Trust

paper_content:

Multi-agent systems are based upon cooperative interactions between agents, in which agents provide information, resources and services to others. Typically agents are autonomous and self-interested, meaning that they have control over their own actions, and that they seek to maximise their own goal achievement, rather than necessarily acting in a benevolent or socially-oriented manner. Consequently, interaction outcomes are uncertain since commitments can be broken and the actual services rendered may differ from expectations in terms of cost or quality. Cooperation is, therefore, an uncertain interaction, that has an inherent risk of failure or reduced performance. In this paper we show how agents can use trust to manage this risk. Our approach uses fuzzy logic to represent trust and allow agents to reason with uncertain and imprecise information regarding others' trustworthiness.
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paper_title: A Multi-agent Model of Deceit and Trust in Intercultural Trade

paper_content:

Trust is a sine qua non for trade. According to transaction cost economics, a contract always offers some opportunity to defect. In the case of asymmetric product information, where the seller is better informed about product quality than the buyer is, the buyer either has to rely on information provided by the seller or has to check the information by testing the product or tracing the supply chain processes, thus incurring extra transaction cost. An opportunistic seller who assumes the buyer to trust, may deliver a lower quality product than agreed upon. In human decisions to deceive and to show trust or distrust toward business partners, issues like morality, shame, self-esteem, and reputation are involved. These factors depend strongly on trader's cultural background. This paper develops an agent model of deceit and trust and describes a multi-agent simulation where trading agents are differentiated according to Hofstede's dimensions of national culture.
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paper_title: SFTrust: A double trust metric based trust model in unstructured P2P system

paper_content:

The P2P system is an anonymous and dynamic system, which offers enormous opportunities, and also presents potential threats and risks. In order to restrain malicious behaviors in P2P system, previous studies try to establish efficient trust models on P2P system. However, most of the trust models use a single trust metric, which can not reflect the practical trust values of the peers effectively. In this paper, we propose a trust model called SFTrust based on a double trust metric. SFTrust separates trust between the service providing and feedbacking. The system is based on the topology adaptation protocol, which was proposed in the unstructured P2P system. Simulation results show that SFTrust can efficiently resist general attacks. Compared with the single trust metric model, our mechanism can take full advantages of all the peers' service abilities for high performance.
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paper_title: A Survey of Multi-Agent Trust Management Systems

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In open and dynamic multiagent systems (MASs), agents often need to rely on resources or services provided by other agents to accomplish their goals. During this process, agents are exposed to the risk of being exploited by others. These risks, if not mitigated, can cause serious breakdowns in the operation of MASs and threaten their long-term wellbeing. To protect agents from the uncertainty in the behavior of their interaction partners, the age-old mechanism of trust between human beings is re-contexted into MASs. The basic idea is to let agents self-police the MAS by rating each other on the basis of their observed behavior and basing future interaction decisions on such information. Over the past decade, a large number of trust management models were proposed. However, there is a lack of research effort in several key areas, which are critical to the success of trust management in MASs where human beings and agents coexist. The purpose of this paper is to give an overview of existing research in trust management in MASs. We analyze existing trust models from a game theoretic perspective to highlight the special implications of including human beings in an MAS, and propose a possible research agenda to advance the state of the art in this field.
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paper_title: A specification of the Agent Reputation and Trust (ART) testbed: experimentation and competition for trust in agent societies

paper_content:

A diverse collection of trust-modeling algorithms for multi-agent systems has been developed in recent years, resulting in significant breadth-wise growth without unified direction or benchmarks. Based on enthusiastic response from the agent trust community, the Agent Reputation and Trust (ART) Testbed initiative has been launched, charged with the task of establishing a testbed for agent trust- and reputation-related technologies. This testbed serves in two roles: (1) as a competition forum in which researchers can compare their technologies against objective metrics, and (2) as a suite of tools with flexible parameters, allowing researchers to perform customizable, easily-repeatable experiments. This paper first enumerates trust research objectives to be addressed in the testbed and desirable testbed characteristics, then presents a competition testbed specification that is justified according to these requirements. In the testbed's artwork appraisal domain, agents, who valuate paintings for clients, may gather opinions from other agents to produce accurate appraisals. The testbed's implementation architecture is discussed briefly, as well.
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paper_title: Coalition formation through motivation and trust

paper_content:

Cooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable, there must be appropriate mechanisms to cope with the uncertainty that arises. In particular, agents must manage the risk associated with interacting with others who have different objectives, or who may fail to fulfil their commitments. Previous work has utilised the notions of motivation and trust in engendering successful cooperation between self-interested agents. Motivations provide a means for representing and reasoning about agents' overall objectives, and trust offers a mechanism for modelling and reasoning about reliability, honesty, veracity and so forth. This paper extends that work to address some of its limitations. In particular, we introduce the concept of a clan: a group of agents who trust each other and have similar objectives. Clan members treat each other favourably when making private decisions about cooperation, in order to gain mutual benefit. We describe mechanisms for agents to form, maintain, and dissolve clans in accordance with their self-interested nature, along with giving details of how clan membership influences individual decision making. Finally, through some simulation experiments we illustrate the effectiveness of clan formation in addressing some of the inherent problems with cooperation among self-interested agents.
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paper_title: Attack Resistant Trust Metrics

paper_content:

The Internet is an amazingly powerful tool for connecting people together, unmatched in human history. Yet, with that power comes great potential for spam and abuse. Trust metrics are an attempt to compute the set of which people are trustworthy and which are likely attackers. This chapter presents two specific trust metrics developed and deployed on the Advogato Website, which is a community blog for free software developers. This real-world experience demonstrates that the trust metrics fulfilled their goals, but that for good results, it is important to match the assumptions of the abstract trust metric computation to the real-world implementation.
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paper_title: Modelling and Simulation of Selling and Deceit for the Trust and Tracing Game

paper_content:

Deceit is commonplace in trade. Understanding deceit is vital for detecting deceit, and for the design of governance mechanisms in trading to discourage deceit. This paper presents a number of observed regularities related to trust that are gained from human simulation games in supply networks. These regularities form the basis of models for deceit and sellers capable of cheating as presented in this paper. The models were used to simulate the game. Analysis of the simulation results show the same regularities as observed in the human game results.
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paper_title: Trust Region Methods

paper_content:

Preface 1. Introduction Part I. Preliminaries: 2. Basic Concepts 3. Basic Analysis and Optimality Conditions 4. Basic Linear Algebra 5. Krylov Subspace Methods Part II. Trust-Region Methods for Unconstrained Optimization: 6. Global Convergence of the Basic Algorithm 7.The Trust-Region Subproblem 8. Further Convergence Theory Issues 9. Conditional Models 10. Algorithmic Extensions 11. Nonsmooth Problems Part III. Trust-Region Methods for Constrained Optimization with Convex Constraints: 12. Projection Methods for Convex Constraints 13. Barrier Methods for Inequality Constraints Part IV. Trust-Region Mewthods for General Constained Optimization and Systems of Nonlinear Equations: 14. Penalty-Function Methods 15. Sequential Quadratic Programming Methods 16. Nonlinear Equations and Nonlinear Fitting Part V. Final Considerations: Practicalities Afterword Appendix: A Summary of Assumptions Annotated Bibliography Subject and Notation Index Author Index.
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paper_title: Trust and deception in multi-agent trading systems. A logical viewpoint

paper_content:

Trust and deception have been of concern to researchers since the earliest research into multi-agent trading systems (MATS). In an open trading environment, trust can be established by external mechanisms e.g. using secret keys or digital signatures or by internal mechanisms e.g. learning and reasoning from experience. However, in a MATS, where distrust exists among the agents, and deception might be used between agents, how to recognise and remove fraud and deception in MATS becomes a significant issue in order to maintain a trustworthy MATS environment. This paper will propose an architecture for a multiagent trading system (MATS) and explore how fraud and deception changes the trust required in a multi-agent trading system/environment. This paper will also illustrate several forms of logical reasoning that involve trust and deception in a MATS. The research is of significance in deception recognition and trust sustainability in e-business and e-commerce.
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paper_title: Formal Analysis of Models for the Dynamics of Trust Based on Experiences

paper_content:

The aim of this paper is to analyse and formalise the dynamics of trust in the light of experiences. A formal framework is introduced for the analysis and specification of models for trust evolution and trust update. Different properties of these models are formally defined.
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paper_title: The influence of agent reliability on trust in human-agent collaboration

paper_content:

Motivation - To investigate ways to support human-automation teams with real-world, imperfect automation where many system failures are the result of systematic failure. Research approach - An experimental approach was used to investigate how variance in agent reliability may influence human's trust and subsequent reliance on agent's decision aids. Sixty command and control (C2) teams, each consisting of a human operator and two cognitive agents, were asked to detect and respond to battlefield threats in six ten-minute scenarios. At the end of each scenario, participants completed the SAGAT queries, followed by the NASA TLX queries. Findings/Design - Results revealed that teams with experienced human operators accepted significantly less inappropriate recommendations from agents than teams with inexperienced operators. More importantly, the knowledge of agent's reliability and the ratio of unreliable tasks have significant effects on human's trust, as manifested in both team performance and human operators' rectification of inappropriate recommendations from agents. Originality/Value - It represents an important step toward uncovering the nature of human trust in human-agent collaboration. Take away message - This research has shown that given even minimal basis for understanding when the operator should and should not trust the agent recommendations allows operators to make better AUDs, to have better situation awareness on the critical issues associated with automation error, and to establish better trust in intelligent agents.
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paper_title: A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents

paper_content:

This paper offers a multi-disciplinary review of knowledge acquisition methods in human activity systems. The review captures the degree of involvement of various types of agencies in the knowledge acquisition process, and proposes a classification with three categories of methods: the human agent, the human-inspired agent, and the autonomous machine agent methods. In the first two categories, the acquisition of knowledge is seen as a cognitive task analysis exercise, while in the third category knowledge acquisition is treated as an autonomous knowledge-discovery endeavour. The motivation for this classification stems from the continuous change over time of the structure, meaning and purpose of human activity systems, which are seen as the factor that fuelled researchers' and practitioners' efforts in knowledge acquisition for more than a century.We show through this review that the KA field is increasingly active due to the higher and higher pace of change in human activity, and conclude by discussing the emergence of a fourth category of knowledge acquisition methods, which are based on red-teaming and co-evolution.
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paper_title: On trust and influence: A computational red teaming game theoretic perspective

paper_content:

The concept of trust has attracted the attention of many researchers over the years who studied the impact of trust in many domains. Trust is a ubiquitous concept. It is pervasive in every aspect of our life, from interpersonal relationships to national defence and security applications. However, despite the vast literature on trust, we are not close enough to mastering the dynamics of trust. One reason is that if we define procedural steps for trust, we simultaneously define steps for deception; thus, we simply define a vacuous cycle. Another reason is that, the dynamics of trust change as the world changes. But how can we then study trust? This paper connects the interdisciplinary literature to synthesize a Computational Red Teaming (CRT) based model of trust that defines opportunities whereby computational intelligence techniques, more specifically, evolutionary game theory researchers, can contribute to this vastly growing research area. We offer a position on the topic by reviewing games for trust and introduce a new theoretic game to study influence and transfer of trust.
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paper_title: The N-Player Trust Game and its Replicator Dynamics

paper_content:

Trust is a fundamental concept that underpins the coherence and resilience of social systems and shapes human behavior. Despite the importance of trust as a social and psychological concept, the concept has not gained much attention from evolutionary game theorists. In this letter, an ${N}$ -player trust-based social dilemma game is introduced. While the theory shows that a society with no untrustworthy individuals would yield maximum wealth to both the society as a whole and the individuals in the long run, evolutionary dynamics show this ideal situation is reached only in a special case when the initial population contains no untrustworthy individuals. When the initial population consists of even the slightest number of untrustworthy individuals, the society converges to zero trusters, with many untrustworthy individuals. The promotion of trust is an uneasy task, despite the fact that a combination of trusters and trustworthy trustees is the most rational and optimal social state. This letter presents the game and results of replicator dynamics in a hope that researchers in evolutionary games see opportunities in filling this critical gap in the literature.
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paper_title: Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems

paper_content:

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT). The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilberts principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of readers. Coherence: where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blended together systematically to present CRT as the science of Risk Analytics and Challenge Analytics. Utility: where the author draws on a wide range of examples, ranging from job interviews to Cyber operations, before presenting three case studies from air traffic control technologies, human behavior, and complex socio-technical systems involving real-time mining and integration of human brain data in the decision making environment.
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paper_title: Control performance assessment based on sensor fusion techniques

paper_content:

Abstract Control performance assessment techniques are widely studied and many performance assessment indices have been proposed. In this paper, a control performance assessment technique for multi-loop control systems is presented based on the decision fusion strategy. Since decisions based on individual indices can lead to erroneous results, decision fusion of different indices can improve the assessment accuracy, especially in multi-loop control systems in the presence of loop interactions. Performance assessment indices are individually evaluated and decisions based on these indices are fused. The results of simulation and practical implementation on series cascade control structures illustrate the effectiveness of the proposed algorithm.
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paper_title: A rule-based phonocardiographic method for long-term fetal heart rate monitoring

paper_content:

A real-time method for fetal heart rate (FHR) monitoring based on signal processing of the fetal heart sounds is presented. The acoustic method, which utilizes an adaptive time pattern analysis to select and analyze those heartbeats that can be recorded without artefact, is guided by a number of rules involving an introduced confidence factor on the timing prediction. The algorithm was implemented in a low-power portable electronic instrument to enable long-term fetal surveillance. A large number of clinical tests have shown the very good performance of the phonocardiographic method in comparison with FHR curves simultaneously recorded with ultrasound cardiotocography. Indeed, approximately 90% of the time, the acoustic FHR curve remained inside a /spl plusmn/3 beats/min tolerance limit of the reference ultrasound method. The confidence was typically CF>0.85. The acoustic method exceeded a /spl plusmn/5 beats/min limit relative to the ultrasound method approximately 5% of the time. Finally, no relevant FHR data was measured approximately 5% of the time.
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paper_title: Augmented Cognition using Real-time EEG-based Adaptive Strategies for Air Traffic Control:

paper_content:

Future air traffic systems aim at increasing both the capacity and safety of the system, necessitating the development of new metrics and advisory tools for controllers' workload in real-time. Psychophysiologi- cal data such as Electroencephalography (EEG) are used to contrast and validate subjective assessments and workload indices. EEG used within augmented cognition systems form situation awareness advisory tools that are able to provide real-time feedback to air-traffic control supervisors and planners. This aug- mented cognition system and experiments using the system with air traffic controllers are presented. Traf- fic indicators are used in conjunction with EEG-driven cognitive indicators to adapt the traffic in real-time through Computational Red Teaming (CRT) based adaptive control mechanisms. The metrics, measures, and adaptive control mechanisms are described and evaluated. The best mechanism to improve system ef- ficacy was found when the system allowed for real-time adaptation of traffic based on engagement met- rics driven from the EEG data.
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paper_title: Magnetic Sensors Based on Amorphous Ferromagnetic Materials: A Review

paper_content:

Currently there are many types of sensors that are used in lots of applications. Among these, magnetic sensors are a good alternative for the detection and measurement of different phenomena because they are a "simple" and readily available technology. For the construction of such devices there are many magnetic materials available, although amorphous ferromagnetic materials are the most suitable. The existence in the market of these materials allows the production of different kinds of sensors, without requiring expensive manufacture investments for the magnetic cores. Furthermore, these are not fragile materials that require special care, favouring the construction of solid and reliable devices. Another important feature is that these sensors can be developed without electric contact between the measuring device and the sensor, making them especially fit for use in harsh environments. In this review we will look at the main types of developed magnetic sensors. This work presents the state of the art of magnetic sensors based on amorphous ferromagnetic materials used in modern technology: security devices, weapon detection, magnetic maps, car industry, credit cards, etc.
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paper_title: A review on system architectures for sensor fusion applications

paper_content:

In the literature there exist many proposed architectures for sensor fusion applications. This paper briefly reviews some of the most common approaches, i. e., the JDL fusion architecture, the Waterfall model, the Intelligence cycle, the Boyd loop, the LAAS architecture, the Omnibus model, Mr. Fusion, the DFuse framework, and the Time-Triggered Sensor Fusion Model, and categorizes them into abstract models, generic and rigid architectures. While an abstract model does not guide the designer in the concrete implementation, the generic architectures provide a generic design but leave open several design decisions regarding operating system, hardware, communication system, or database system. Rigid architectures specify at least some of these aspects and therefore provide existing hardware designs, tools, and source code at the cost of flexibility.
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paper_title: Non-invasive wearable electrochemical sensors: a review.

paper_content:

Wearable sensors have garnered considerable recent interest owing to their tremendous promise for a plethora of applications. Yet the absence of reliable non-invasive chemical sensors has greatly hindered progress in the area of on-body sensing. Electrochemical sensors offer considerable promise as wearable chemical sensors that are suitable for diverse applications owing to their high performance, inherent miniaturization, and low cost. A wide range of wearable electrochemical sensors and biosensors has been developed for real-time non-invasive monitoring of electrolytes and metabolites in sweat, tears, or saliva as indicators of a wearer's health status. With continued innovation and attention to key challenges, such non-invasive electrochemical sensors and biosensors are expected to open up new exciting avenues in the field of wearable wireless sensing devices and body-sensor networks, and thus find considerable use in a wide range of personal health-care monitoring applications, as well as in sport and military applications.
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paper_title: Sensor and CFD data fusion for airflow field estimation

paper_content:

Abstract This paper presents how an airflow field can be quickly estimated by fusing isolated and sparse sensor observations with a given computational fluid dynamics (CFD) solution. The given CFD data represent the airflow field with a certain boundary condition while the sensor data provide sparse and sampled information of the actual field with a new/changed boundary condition. Essentially, we need to determine a dominant proper orthogonal decomposition (POD) basis from a limited number of snapshots obtained from CFD simulations of a spatial domain. Then, for the given CFD solution, we estimate its difference from the actual field based on the sensor observations and the dominant POD basis. With the estimation result, the given CFD solution can then be efficiently corrected based on new sensor information. That is, with sparse sensor observations, we are able to transfer the given CFD solution into an ‘actual’ one that corresponds to the new boundary condition. Additionally, we present a new greedy algorithm to determine the sensor placement, which plays a critical role in airflow field estimation. Finally, a simple example is provided to illustrate the effectiveness of the proposed sensor–CFD data fusion procedure and the new sensor placement algorithm.
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paper_title: Wearable Electronics and Smart Textiles: A Critical Review

paper_content:

Electronic Textiles (e-textiles) are fabrics that feature electronics and interconnections woven into them, presenting physical flexibility and typical size that cannot be achieved with other existing electronic manufacturing techniques. Components and interconnections are intrinsic to the fabric and thus are less visible and not susceptible of becoming tangled or snagged by surrounding objects. E-textiles can also more easily adapt to fast changes in the computational and sensing requirements of any specific application, this one representing a useful feature for power management and context awareness. The vision behind wearable computing foresees future electronic systems to be an integral part of our everyday outfits. Such electronic devices have to meet special requirements concerning wearability. Wearable systems will be characterized by their ability to automatically recognize the activity and the behavioral status of their own user as well as of the situation around her/him, and to use this information to adjust the systems' configuration and functionality. This review focuses on recent advances in the field of Smart Textiles and pays particular attention to the materials and their manufacturing process. Each technique shows advantages and disadvantages and our aim is to highlight a possible trade-off between flexibility, ergonomics, low power consumption, integration and eventually autonomy.
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paper_title: Inertial Sensor-Based Gait Recognition: A Review

paper_content:

With the recent development of microelectromechanical systems (MEMS), inertial sensors have become widely used in the research of wearable gait analysis due to several factors, such as being easy-to-use and low-cost. Considering the fact that each individual has a unique way of walking, inertial sensors can be applied to the problem of gait recognition where assessed gait can be interpreted as a biometric trait. Thus, inertial sensor-based gait recognition has a great potential to play an important role in many security-related applications. Since inertial sensors are included in smart devices that are nowadays present at every step, inertial sensor-based gait recognition has become very attractive and emerging field of research that has provided many interesting discoveries recently. This paper provides a thorough and systematic review of current state-of-the-art in this field of research. Review procedure has revealed that the latest advanced inertial sensor-based gait recognition approaches are able to sufficiently recognise the users when relying on inertial data obtained during gait by single commercially available smart device in controlled circumstances, including fixed placement and small variations in gait. Furthermore, these approaches have also revealed considerable breakthrough by realistic use in uncontrolled circumstances, showing great potential for their further development and wide applicability.
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paper_title: On Sensor Sampling and Quality of Information: A Starting Point

paper_content:

Many sensor-based applications (re)act following the detection of certain events of interest. Hence, the effectiveness of these applications depends on the quality of the information (QoI) provided by their sensor-based event detectors. In this paper, we derive relationships between the QoI attributes of timeliness and confidence and the operational characteristics of sensor systems and the events they detect. By building upon the Neyman-Pearson hypothesis testing procedure, we study the dependence of these characteristics and attributes on each other and establish their theoretical performance boundaries
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paper_title: Multiple Arousal Theory and Daily-Life Electrodermal Activity Asymmetry

paper_content:

Using “big data” from sensors worn continuously outside the lab, researchers have observed patterns of objective physiology that challenge some of the long-standing theoretical concepts of emotion and its measurement. One challenge is that emotional arousal, when measured as sympathetic nervous system activation through electrodermal activity, can sometimes differ significantly across the two halves of the upper body. We show that traditional measures on only one side may lead to misjudgment of arousal. This article presents daily life and controlled study data, as well as existing evidence from neuroscience, supporting the influence of multiple emotional substrates in the brain causing innervation on different sides of the body. We describe how a theory of multiple arousals explains the asymmetric EDA findings.
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paper_title: Wearable Sensors for Human Activity Monitoring: A Review

paper_content:

An increase in world population along with a significant aging portion is forcing rapid rises in healthcare costs. The healthcare system is going through a transformation in which continuous monitoring of inhabitants is possible even without hospitalization. The advancement of sensing technologies, embedded systems, wireless communication technologies, nano technologies, and miniaturization makes it possible to develop smart systems to monitor activities of human beings continuously. Wearable sensors detect abnormal and/or unforeseen situations by monitoring physiological parameters along with other symptoms. Therefore, necessary help can be provided in times of dire need. This paper reviews the latest reported systems on activity monitoring of humans based on wearable sensors and issues to be addressed to tackle the challenges.
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paper_title: Sensor fusion potential exploitation-innovative architectures and illustrative applications

paper_content:

Sensor fusion models have been characterized in the literature in a number of distinctly different ways: in terms of information levels at which the fusion is accomplished; the objectives of the fusion process, the application domain; the types of sensors employed, the sensor suite configuration and so on. The characterization most commonly encountered in the rapidly growing sensor fusion literature based on level of detail in the information is that of the now well known triplet: data level, feature level, and decision level. We consider here a generalized input-output (I/O) descriptor pair based characterization of the sensor fusion process that can be looked upon as a natural out growth of the trilevel characterization. The fusion system design philosophy expounded here is that an exhaustive exploitation of the sensor fusion potential should explore fusion under all of the different I/O-based fusion modes conceivable under such a characterization. Fusion system architectures designed to permit such exploitation offer the requisite flexibility for developing the most effective fusion system designs for a given application. A second facet of this exploitation is aimed at exploring the new concept of self-improving multisensor fusion system architectures wherein the central (fusion system) and focal (individual sensor subsystems) decision makers mutually enhance the other's performance by providing reinforced learning. A third facet is that of investigating fusion system architectures for environments wherein the different local decision makers may only be capable of narrower decisions that span only a subset of decision choices. The paper discusses these flexible fusion system architectures along with related issues and illustrates them with examples of their application to real-world scenarios.
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paper_title: Data Fusion Architectures for Sensor Platforms

paper_content:

The role of data fusion in sensor platforms is becoming increasingly important in various domains of science, technology and business. Fusion pertains to the merging or integration of information towards an enhanced level of awareness. Multi-sensor fusion can be applied to any system that must retrieve and synthesize data from numerous sources. Its applications can be found in a variety of technology settings, from robotics, structural and vehicle health monitoring to communications, space science and telemedicine. This work is a canonical overview of several major fusion architectures developed from the remote sensing and defense community. We present several types of architecture for managing multi-sensor data fusion, specifically as they relate to the tracking-correlation function and blackboard processing representations in knowledge engineering. Object-Process Methods are used to model the information fusion process and supporting subsystems. Finally, we discuss the importance of fusion to the concept and operation of the Semantic Web. Semantic networks offer powerful ways to exploit the synergy of multi-sensor data platforms. Their operation is based on synthesis of fusion with ontology models for knowledge representation. We discuss the importance of fusion as a reuse process in ontological engineering, and review key lifecycle models in ontology development. The evolutionary approach to ontology development is considered the most useful and adaptable to the complexities of semantic networks. Several potential applications for data fusion are screened and ranked according to the Joint Directors of Laboratories (JDL) process model for information fusion. Based on these predetermined criteria, the case of medical diagnostic imaging was found to offer the most promising applications for fusion, on which future product platforms can be built.
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paper_title: A survey of sensor fusion methods in wearable robotics

paper_content:

Modern wearable robots are not yet intelligent enough to fully satisfy the demands of end-users, as they lack the sensor fusion algorithms needed to provide optimal assistance and react quickly to perturbations or changes in user intentions. Sensor fusion applications such as intention detection have been emphasized as a major challenge for both robotic orthoses and prostheses. In order to better examine the strengths and shortcomings of the field, this paper presents a review of existing sensor fusion methods for wearable robots, both stationary ones such as rehabilitation exoskeletons and portable ones such as active prostheses and full-body exoskeletons. Fusion methods are first presented as applied to individual sensing modalities (primarily electromyography, electroencephalography and mechanical sensors), and then four approaches to combining multiple modalities are presented. The strengths and weaknesses of the different methods are compared, and recommendations are made for future sensor fusion research. Overview of sensor fusion in wearable robots like prostheses and exoskeletons.Main sensors: electromyography, electroencephalography, and mechanical sensors.Emphasizes multimodality, adaptation and switching between sensor fusion schemes.Online evaluation of sensor fusion methods is crucial.
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paper_title: Managers as Initiators of Trust: An Exchange Relationship Framework for Understanding Managerial Trustworthy Behavior

paper_content:

In many approaches to interpersonal and organizational trust, researchers focus on employees' perceptions that their managers are trustworthy. We turn the tables, however, and examine the antecedents of managerial trustworthy behavior and the challenge of initiating trust. Drawing on agency and social exchange theories, we present an exchange relationship framework that identifies organizational, relational, and individual factors that encourage or constrain managerial trustworthy behavior.
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paper_title: Multi-sensor Multi-resolution Data Fusion Modeling

paper_content:

Abstract Inspection analysis of 3D objects has progressed significantly due to the evolution of advanced sensors. Current sensors facilitate surface scanning at high or low resolution levels. In the inspection field, data from multi-resolution sensors have significant advantages over single-scale data. However, most data fusion methods are single-scale and are not suitable in their current form for multi-resolution sensors. Currently the main challenge is to integrate the diverse scanned information into a single geometric hierarchical model. In this work, a new approach for data fusion from multi-resolution sensors is presented. In addition, a correction function for data fusion, based on statistic models, for processing highly dense data (low accuracy) with respect to sparse data (high accuracy) is described. The feasibility of the methods is demonstrated on synthetic data that imitates CMM and laser measurements.
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paper_title: A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor

paper_content:

Accurate estimation of heart rates from photoplethysmogram (PPG) signals during intense physical activity is a very challenging problem. This is because strenuous and high intensity exercise can result in severe motion artifacts in PPG signals, making accurate heart rate (HR) estimation difficult. In this study we investigated a novel technique to accurately reconstruct motion-corrupted PPG signals and HR based on time-varying spectral analysis. The algorithm is called Spectral filter algorithm for Motion Artifacts and heart rate reconstruction (SpaMA). The idea is to calculate the power spectral density of both PPG and accelerometer signals for each time shift of a windowed data segment. By comparing time-varying spectra of PPG and accelerometer data, those frequency peaks resulting from motion artifacts can be distinguished from the PPG spectrum. The SpaMA approach was applied to three different datasets and four types of activities: (1) training datasets from the 2015 IEEE Signal Process. Cup Database recorded from 12 subjects while performing treadmill exercise from 1 km/h to 15 km/h; (2) test datasets from the 2015 IEEE Signal Process. Cup Database recorded from 11 subjects while performing forearm and upper arm exercise. (3) Chon Lab dataset including 10 min recordings from 10 subjects during treadmill exercise. The ECG signals from all three datasets provided the reference HRs which were used to determine the accuracy of our SpaMA algorithm. The performance of the SpaMA approach was calculated by computing the mean absolute error between the estimated HR from the PPG and the reference HR from the ECG. The average estimation errors using our method on the first, second and third datasets are 0.89, 1.93 and 1.38 beats/min respectively, while the overall error on all 33 subjects is 1.86 beats/min and the performance on only treadmill experiment datasets (22 subjects) is 1.11 beats/min. Moreover, it was found that dynamics of heart rate variability can be accurately captured using the algorithm where the mean Pearson’s correlation coefficient between the power spectral densities of the reference and the reconstructed heart rate time series was found to be 0.98. These results show that the SpaMA method has a potential for PPG-based HR monitoring in wearable devices for fitness tracking and health monitoring during intense physical activities.
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paper_title: Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

paper_content:

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.
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paper_title: Microelectronics-Based Biosensors Dedicated to the Detection of Neurotransmitters: A Review

paper_content:

Dysregulation of neurotransmitters (NTs) in the human body are related to diseases such as Parkinson's and Alzheimer's. The mechanisms of several neurological disorders, such as epilepsy, have been linked to NTs. Because the number of diagnosed cases is increasing, the diagnosis and treatment of such diseases are important. To detect biomolecules including NTs, microtechnology, micro and nanoelectronics have become popular in the form of the miniaturization of medical and clinical devices. They offer high-performance features in terms of sensitivity, as well as low-background noise. In this paper, we review various devices and circuit techniques used for monitoring NTs in vitro and in vivo and compare various methods described in recent publications.
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paper_title: Wearable Sensing of In-Ear Pressure for Heart Rate Monitoring with a Piezoelectric Sensor

paper_content:

In this study, we developed a novel heart rate (HR) monitoring approach in which we measure the pressure variance of the surface of the ear canal. A scissor-shaped apparatus equipped with a piezoelectric film sensor and a hardware circuit module was designed for high wearability and to obtain stable measurement. In the proposed device, the film sensor converts in-ear pulse waves (EPW) into electrical current, and the circuit module enhances the EPW and suppresses noise. A real-time algorithm embedded in the circuit module performs morphological conversions to make the EPW more distinct and knowledge-based rules are used to detect EPW peaks. In a clinical experiment conducted using a reference electrocardiogram (ECG) device, EPW and ECG were concurrently recorded from 58 healthy subjects. The EPW intervals between successive peaks and their corresponding ECG intervals were then compared to each other. Promising results were obtained from the samples, specifically, a sensitivity of 97.25%, positive predictive value of 97.17%, and mean absolute difference of 0.62. Thus, highly accurate HR was obtained from in-ear pressure variance. Consequently, we believe that our proposed approach could be used to monitor vital signs and also utilized in diverse applications in the near future.
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paper_title: Trust in the workplace: Factors affecting trust formation between team members

paper_content:

The authors used survey data from 127 professional-level employees working in 8 industries to assess the effects of respondent's trusting stance and (a) the trustee's organization membership (internal or external), (b) the hierarchical relationship (supervisor or peer), and (c) the gender of the trustee, on initial trust level for a new project team member. The authors found that trusting stance was positively related to initial trust level. The authors also found an interaction effect between respondent gender and trustee gender on initial trust. Specifically, male initial trust level was higher for a new male team member and lower for a new female team member. The present study provided additional understanding of the formation of initial trust levels and its importance for team functioning.
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paper_title: Synthetic analog computation in living cells

paper_content:

Synthetic analog gene circuits can be engineered to execute logarithmically linear sensing, addition, ratiometric and power-law computations in living cells using just three transcription factors.
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paper_title: A field programmable neural array

paper_content:

An analog circuit capable of accurately emulating large complex cells, or multiple less complex ones is described. This circuit is termed the FPNA or the field programmable neural array. It is analogous to the more familiar FPGA, but is composed of biologically relevant circuit components including active channels, dendrites, and synapses. Taking each of these circuit models, and adding a routing structure capable of routing outputs from cells (or external inputs) to any individual synapse at any node yields a device which is capable of emulating complex biological circuits. This circuit opens doors to investigating what particular types of computation individual cells are performing, as well as small networks simpler cells.
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paper_title: Distortion Analysis Of Analog Integrated Circuits

paper_content:

From the Publisher: ::: Distortion Analysis of Analog Integrated Circuits provides both qualitative and quantitative insight into the nonlinear behavior of analog integrated circuits at low and high frequencies. General techniques to suppress nonlinear behavior such as pre-distortion, linear and nonlinear feedback are explained in detail and illustrated with realistic examples. In this way the book fills the gap between the theory of nonlinear systems and practical analog integrated circuits. Distortion Analysis of Analog Integrated Circuits is essential reading for practicing analog and mixed-signal design engineers and researchers in the field. It is also suitable as a text for an advanced course on the subject.
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paper_title: A Study of the Speedups and Competitiveness of FPGA Soft Processor Cores using Dynamic Hardware/Software Partitioning

paper_content:

Field programmable gate arrays (FPGAs) provide designers with the ability to quickly create hardware circuits. Increases in FPGA configurable logic capacity and decreasing FPGA costs have enabled designers to more readily incorporate FPGAs in their designs. FPGA vendors have begun providing configurable soft processor cores that can be synthesized onto their FPGA products. While FPGAs with soft processor cores provide designers with increased flexibility, such processors typically have degraded performance and energy consumption compared to hard-core processors. Previously, we proposed warp processing, a technique capable of optimizing a software application by dynamically and transparently re-implementing critical software kernels as custom circuits in on-chip configurable logic. In this paper, we study the potential of a MicroBlaze soft-core based warp processing system to eliminate the performance and energy overhead of a soft-core processor compared to a hard-core processor. We demonstrate that the soft-core based warp processor achieves average speedups of 5.8 and energy reductions of 57% compared to the soft core alone. Our data shows that a soft-core based warp processor yields performance and energy consumption competitive with existing hard-core processors, thus expanding the usefulness of soft processor cores on FPGAs to a broader range of applications.
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paper_title: Natural computation and non-Turing models of computation

paper_content:

We propose certain non-Turing models of computation, but our intent is not to advocate models that surpass the power of Turing machines (TMs), but to defend the need for models with orthogonal notions of power. We review the nature of models and argue that they are relative to a domain of application and are ill-suited to use outside that domain. Hence we review the presuppositions and context of the TM model and show that it is unsuited to natural computation (computation occurring in or inspired by nature). Therefore we must consider an expanded definition of computation that includes alternative (especially analog) models as well as the TM. Finally we present an alternative model, of continuous computation, more suited to natural computation. We conclude with remarks on the expressivity of formal mathematics.
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paper_title: Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations

paper_content:

In this paper, we describe the design of Neurogrid, a neuromorphic system for simulating large-scale neural models in real time. Neuromorphic systems realize the function of biological neural systems by emulating their structure. Designers of such systems face three major design choices: 1) whether to emulate the four neural elementsVaxonal arbor, synapse, dendritic tree, and somaVwith dedicated or shared electronic circuits; 2) whether to implement these electronic circuits in an analog or digital manner; and 3) whether to interconnect arrays of these silicon neurons with a mesh or a tree network. The choices we made were: 1) we emulated all neural elements except the soma with shared electronic circuits; this choice maximized the number of synaptic connections; 2) we realizedallelectroniccircuitsexcept those foraxonal arbors in an analog manner; this choice maximized energy efficiency; and
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paper_title: Continuous-time hybrid computation with programmable nonlinearities

paper_content:

We present the first continuous-time hybrid computing unit in 65nm CMOS, capable of solving nonlinear differential equations up to 4th order, and scalable to higher orders. Arbitrary nonlinear functions used in such equations are implemented by a programmable clockless continuous-time 8b hybrid architecture (ADC+SRAM+DAC) with activity- dependent power dissipation. We also demonstrate the use of the unit in a low-power cyber-physical systems application.
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paper_title: General-purpose electronic analog computing: 1945-1965

paper_content:

An account of the development and commercialization of general-purpose electronic analog computing in Britain and the United States of America from 1945 to the mid-1990s is presented. It is argued that the principal influence on the growth and maturation of postwar commercial analog computing was the demand for aids to calculation in aeronautical design. The drive to develop military aircraft, guided weapons, and ICBMs provided the primary motivation and funds to develop analog and subsequently hybrid computer systems. The transition from mechanical to electronic analog computing, the formative and pioneering firms, and the commercialization of in-house computing systems are described. >
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paper_title: Cognitive computing programming paradigm: A Corelet Language for composing networks of neurosynaptic cores

paper_content:

Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. The sequential programming paradigm of the von Neumann architecture is wholly unsuited for TrueNorth. Therefore, as our main contribution, we develop a new programming paradigm that permits construction of complex cognitive algorithms and applications while being efficient for TrueNorth and effective for programmer productivity. The programming paradigm consists of (a) an abstraction for a TrueNorth program, named Corelet, for representing a network of neurosynaptic cores that encapsulates all details except external inputs and outputs; (b) an object-oriented Corelet Language for creating, composing, and decomposing corelets; (c) a Corelet Library that acts as an ever-growing repository of reusable corelets from which programmers compose new corelets; and (d) an end-to-end Corelet Laboratory that is a programming environment which integrates with the TrueNorth architectural simulator, Compass, to support all aspects of the programming cycle from design, through development, debugging, and up to deployment. The new paradigm seamlessly scales from a handful of synapses and neurons to networks of neurosynaptic cores of progressively increasing size and complexity. The utility of the new programming paradigm is underscored by the fact that we have designed and implemented more than 100 algorithms as corelets for TrueNorth in a very short time span.
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paper_title: Efficient parallel processing by improved CPU-GPU interaction

paper_content:

In this digital world, more than 90% of desktop and notebook computers have integrated Graphics Processing Units i.e. GPU's, for better graphics processing. Graphics Processing Unit is not only for graphics applications, even for non-graphics applications too. In the past few years, the graphics programmable processor has evolved into an increasingly convincing computational resource. But GPU sits idle if graphics job queue is empty, which decreases the GPU's efficiency. This paper focuses on various tact to overcome this problem and to make the CPU-GPU processing more powerful and efficient. The graphics programmable processor or Graphics processing unit is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. The objective of this paper is to increase the capabilities and flexibility of recent GPU hardware combined with high level GPU programming languages: to accelerate the building of images in a frame buffer intended for output to a display, and, to provide tremendous acceleration for numerically intensive scientific applications. This paper also gives some light on major applicative areas where GPU is in use and where GPU can be used in future.
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paper_title: A VLSI analog computer/math co-processor for a digital computer

paper_content:

A single-chip VLSI analog computer having 80 integrators and 336 other programmable linear and nonlinear circuits is fabricated in a 0.25 /spl mu/m CMOS process. The chip can be used to accelerate a digital computer's numerical routines. The IC is 1 cm/sup 2/ and consumes 300 mW.
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paper_title: A Clockless ADC/DSP/DAC System with Activity-Dependent Power Dissipation and No Aliasing

paper_content:

In this work, these issues are addressed and solved, and an entire ADC/DSP/DAC 8b system is implemented in a UMC 90nm CMOS process with a 1V supply.
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paper_title: Controller verification in adaptive learning systems towards trusted autonomy

paper_content:

With the increasing levels of adaptation and autonomy in complex cyber-physical systems (CPS), the traditional notion that such systems can be fully tested and validated offline is becoming an impossible task. It is virtually impossible to analyze or test ahead of time all the possible parameter values resulting from the uncertainty in system operational and environmental conditions. This paper considers the problem of online controller verification in a class of first-order nonlinear uncertain systems incorporating neural network based learning algorithms. Based on several critical assumptions, an on-line neural network model is employed to ensure robustness and fault-tolerance to certain modeling uncertainty and physical faults under consideration. However, these assumptions may be violated in the presence of software faults or unanticipated physical faults in the closed-loop system, leading to unstable learning behaviors and controller malfunctions. Based on Lyapunov stability theory, a online controller verification scheme is developed to detect such unstable learning behaviors by continuously monitoring the decrease of Lyapunov functions. Adaptive thresholds for detecting malfunctions of the adaptive learning controller are derived, ensuring the robustness with respect to modeling uncertainty and neural network approximation error. Additionally, the detectability conditions are investigated, characterizing the class of detectable software faults and unanticipated hardware faults. An upper bound on the detection time of controller malfunction is also derived. Some simulation results using a two-tank system are shown to illustrate the effectiveness of the controller verification method.
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paper_title: Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems

paper_content:

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT). The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilberts principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of readers. Coherence: where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blended together systematically to present CRT as the science of Risk Analytics and Challenge Analytics. Utility: where the author draws on a wide range of examples, ranging from job interviews to Cyber operations, before presenting three case studies from air traffic control technologies, human behavior, and complex socio-technical systems involving real-time mining and integration of human brain data in the decision making environment.
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Title: A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data

Section 1: INTRODUCTION
Description 1: Introduce the concept of Trusted Autonomous Systems (TAS) and outline the integration of trust and autonomy. Highlight the importance and complexity of mutual trust between humans and machines and present the paper's structure.

Section 2: COMPUTATIONS FOR AND BY TRUST
Description 2: Discuss trust as a fundamental aspect of TAS and review computational models of trust — both trust modelling and computations by trust. Present key facets such as reliability, privacy, and various computational approaches used to model trust in multi-agent systems.

Section 3: BIG DATA AT THE HUMAN-MACHINE INTERFACE
Description 3: Define what constitutes a big data problem, particularly in the context of TAS, and introduce sensor technologies that facilitate human-machine interaction. Discuss the challenges and technologies involved in processing large volumes of sensor data.

Section 4: TRUSTED AUTONOMOUS SYSTEMS: THE BIG DATA CHALLENGE REVEALED
Description 4: Extend the discussion on autonomy and integrate it with the concept of trust. Present the architecture required for TAS to exhibit both autonomy and trust, and outline the significant big data challenges in the implementation and operation of TAS.