Modelling Engagement in Multi-Party Conversations : Data-Driven Approaches to Understanding Human-Human Communication Patterns for Use in Human-Robot Interactions

OpenAIRE

Oertel, Catharine

2016-01-01

The aim of this thesis is to study human-human interaction in order to provide virtual agents and robots with the capability to engage into multi-party-conversations in a human-like-manner. The focus lies with the modelling of conversational dynamics and the appropriate realization of multi-modal feedback behaviour. For such an undertaking, it is important to understand how human-human communication unfolds in varying contexts and constellations over time. To this end, multi-modal human-human...

An ontology for human-like interaction systems

OpenAIRE

Albacete García, Esperanza

2016-01-01

This report proposes and describes the development of a Ph.D. Thesis aimed at building an ontological knowledge model supporting Human-Like Interaction systems. The main function of such knowledge model in a human-like interaction system is to unify the representation of each concept, relating it to the appropriate terms, as well as to other concepts with which it shares semantic relations. When developing human-like interactive systems, the inclusion of an ontological module can be valuab...

Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

Science.gov (United States)

Ancel, Ersin; Shih, Ann T.

2015-01-01

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system

Improving Language Models in Speech-Based Human-Machine Interaction

Directory of Open Access Journals (Sweden)

Raquel Justo

2013-02-01

Full Text Available This work focuses on speech-based human-machine interaction. Specifically, a Spoken Dialogue System (SDS that could be integrated into a robot is considered. Since Automatic Speech Recognition is one of the most sensitive tasks that must be confronted in such systems, the goal of this work is to improve the results obtained by this specific module. In order to do so, a hierarchical Language Model (LM is considered. Different series of experiments were carried out using the proposed models over different corpora and tasks. The results obtained show that these models provide greater accuracy in the recognition task. Additionally, the influence of the Acoustic Modelling (AM in the improvement percentage of the Language Models has also been explored. Finally the use of hierarchical Language Models in a language understanding task has been successfully employed, as shown in an additional series of experiments.

In silico modeling of human α2C-adrenoreceptor interaction with filamin-2.

Directory of Open Access Journals (Sweden)

Marcin Pawlowski

Full Text Available Vascular smooth muscle α2C-adrenoceptors (α2C-ARs mediate vasoconstriction of small blood vessels, especially arterioles. Studies of endogenous receptors in human arteriolar smooth muscle cells (referred to as microVSM and transiently transfected receptors in heterologous HEK293 cells show that the α2C-ARs are perinuclear receptors that translocate to the cell surface under cellular stress and elicit a biological response. Recent studies in microVSM unraveled a crucial role of Rap1A-Rho-ROCK-F-actin pathways in receptor translocation, and identified protein-protein interaction of α2C-ARs with the actin binding protein filamin-2 as an essential step in the process. To better understand the molecular nature and specificity of this interaction, in this study, we constructed comparative models of human α2C-AR and human filamin-2 proteins. Finally, we performed in silico protein-protein docking to provide a structural platform for the investigation of human α2C-AR and filamin-2 interactions. We found that electrostatic interactions seem to play a key role in this complex formation which manifests in interactions between the C-terminal arginines of α2C-ARs (particularly R454 and R456 and negatively charged residues from filamin-2 region between residues 1979 and 2206. Phylogenetic and sequence analysis showed that these interactions have evolved in warm-blooded animals.

Structuring Design and Evaluation of an Interactive Installation Through Swarms of Light Rays with Human-Artifact Model

DEFF Research Database (Denmark)

Erkut, Cumhur; Fehr, Jonas

2016-01-01

We present the design and evaluation of an interactive installation to be explored by movement and sound under Human-Activity Model. In the installation, movement qualities that are extracted from the motion tracking data excite a dynamical system (a synthetic flock of agents), which responds...... out a questionnaire afterwards. In this paper, we report our preliminary work on the analysis of the tensions of interaction with the installation under the Human-Artifact Model. Our results indicate exploration and discovery as the main motives of the interaction. This is different than utilitarian...

Modeling human dynamics of face-to-face interaction networks

OpenAIRE

Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

2013-01-01

Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here ...

Human thermoregulation model of RF-EMF interaction

International Nuclear Information System (INIS)

Niedermayr, F.

2012-01-01

A thermal model has been developed which allows accurate temperature computations in high resolution anatomical models. The model is based on the basic thermal model described by Pennes which neglects any of the thermoregulatory mechanisms in humans. The thermal model developed here overcomes major simplifications by the mathematical consideration of these mechanisms which is needed for modeling a physiologically correct reaction to a thermal stimulus. The local blood perfusion, as well as the local metabolic rate, is modified as a function of the local tissue temperature. The model implemented increases the blood temperature on the basis of the absorbed energy. The heat exchange at the tissue/air interface, including the skin and respiratory tract, is also improved. The model takes not only the heat dissipation by radiation, conduction and convection into consideration but also the insensible loss of water by evaporation. Furthermore, the thermal model also accounts for the active heat dissipation by sweating. The generic implementation of the thermal model makes it possible to use it for different human models (children, adults, pregnant women) and it is also possible to take implants into consideration. The performance of the model is validated by comparing the simulation results to actual temperature measurements in humans. The thermal model is used to compute the temperature elevation in humans exposed to radiofrequency electromagnetic fields. Until now, the tissue heating caused by radiofrequency electromagnetic fields could only be estimated by a surrogate, namely the specific absorption rate. The temperature elevations in children of different sizes and ages as well as pregnant women at different gestational stages exposed to plane waves is computed. Furthermore, the temperature elevation in human bodies is computed for a diagnostic modality (magnetic resonance imaging) and a therapeutic modality (medical diathermy). (author) [de

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

Science.gov (United States)

Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael

2013-01-01

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Experimental simulation: using generative modelling and palaeoecological data to understand human-environment interactions

Directory of Open Access Journals (Sweden)

George Perry

2016-10-01

Full Text Available The amount of palaeoecological information available continues to grow rapidly, providing improved descriptions of the dynamics of past ecosystems and enabling them to be seen from new perspectives. At the same time, there has been concern over whether palaeoecological enquiry needs to move beyond descriptive inference to a more hypothesis-focussed or experimental approach; however, the extent to which conventional hypothesis-driven scientific frameworks can be applied to historical contexts (i.e., the past is the subject of ongoing debate. In other disciplines concerned with human-environment interactions, including physical geography and archaeology, there has been growing use of generative simulation models, typified by agent-based approaches. Generative modelling encourages counter-factual questioning (what if…?, a mode of argument that is particularly important in systems and time-periods, such as the Holocene and now the Anthropocene, where the effects of humans and other biophysical processes are deeply intertwined. However, palaeoecologically focused simulation of the dynamics of the ecosystems of the past either seems to be conducted to assess the applicability of some model to the future or treats humans simplistically as external forcing factors. In this review we consider how generative simulation-modelling approaches could contribute to our understanding of past human-environment interactions. We consider two key issues: the need for null models for understanding past dynamics and the need to be able learn more from pattern-based analysis. In this light, we argue that there is considerable scope for palaeocology to benefit from developments in generative models and their evaluation. We discuss the view that simulation is a form of experiment and, by using case studies, consider how the many patterns available to palaeoecologists can support model evaluation in a way that moves beyond simplistic pattern-matching and how such models

Extended sequence diagram for human system interaction

International Nuclear Information System (INIS)

Hwang, Jong Rok; Choi, Sun Woo; Ko, Hee Ran; Kim, Jong Hyun

2012-01-01

Unified Modeling Language (UML) is a modeling language in the field of object oriented software engineering. The sequence diagram is a kind of interaction diagram that shows how processes operate with one another and in what order. It is a construct of a message sequence chart. It depicts the objects and classes involved in the scenario and the sequence of messages exchanged between the objects needed to carry out the functionality of the scenario. This paper proposes the Extended Sequence Diagram (ESD), which is capable of depicting human system interaction for nuclear power plants, as well as cognitive process of operators analysis. In the conventional sequence diagram, there is a limit to only identify the activities of human and systems interactions. The ESD is extended to describe operators' cognitive process in more detail. The ESD is expected to be used as a task analysis method for describing human system interaction. The ESD can also present key steps causing abnormal operations or failures and diverse human errors based on cognitive condition

Occupational stress in human computer interaction.

Science.gov (United States)

Smith, M J; Conway, F T; Karsh, B T

1999-04-01

There have been a variety of research approaches that have examined the stress issues related to human computer interaction including laboratory studies, cross-sectional surveys, longitudinal case studies and intervention studies. A critical review of these studies indicates that there are important physiological, biochemical, somatic and psychological indicators of stress that are related to work activities where human computer interaction occurs. Many of the stressors of human computer interaction at work are similar to those stressors that have historically been observed in other automated jobs. These include high workload, high work pressure, diminished job control, inadequate employee training to use new technology, monotonous tasks, por supervisory relations, and fear for job security. New stressors have emerged that can be tied primarily to human computer interaction. These include technology breakdowns, technology slowdowns, and electronic performance monitoring. The effects of the stress of human computer interaction in the workplace are increased physiological arousal; somatic complaints, especially of the musculoskeletal system; mood disturbances, particularly anxiety, fear and anger; and diminished quality of working life, such as reduced job satisfaction. Interventions to reduce the stress of computer technology have included improved technology implementation approaches and increased employee participation in implementation. Recommendations for ways to reduce the stress of human computer interaction at work are presented. These include proper ergonomic conditions, increased organizational support, improved job content, proper workload to decrease work pressure, and enhanced opportunities for social support. A model approach to the design of human computer interaction at work that focuses on the system "balance" is proposed.

Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations.

Directory of Open Access Journals (Sweden)

Tatiana Shashkova

Full Text Available Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes.In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery.The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial

Evaluation of the Humanity Research Paradigms based on Analysis of Human – Environment Interaction

Directory of Open Access Journals (Sweden)

Reza Sameh

2015-09-01

Full Text Available As claimed by many behavioral scientists, designing should be based on the knowledge of interaction between human and environment. Environmental quality is also created in the context in which humans interact with their environment. To achieve such quality, designers should develop appropriate models for explaining this relationship, and this requires an understanding of human nature and the environment. Criticisms on the Modern Movement have shown that architects have often used incomplete and simplistic models in this regard, while most of design ideas are based on the definitions of human and environment and the interaction between them. However, the most important question that is raised is that how understanding of human nature and the environment and their interaction, which depends on foundations of different views, can affect the pursuit of quality in designing? Therefore, the present paper, in addition to introduction and comparison of common paradigms in humanities as the and methodological foundation of human sciences, aims to deal with the relationship of human and the environment from the perspective of objectivist, relativist, and critical paradigms in order to identify the characteristics and differences in their views on the analysis of the quality of this interaction. This is the most important step that paves the way for understanding the qualitative foundations of the environment and human life quality and also the quality of interaction between them.

Shoe-Floor Interactions in Human Walking With Slips: Modeling and Experiments.

Science.gov (United States)

Trkov, Mitja; Yi, Jingang; Liu, Tao; Li, Kang

2018-03-01

Shoe-floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions.

Movement coordination in applied human-human and human-robot interaction

DEFF Research Database (Denmark)

Schubö, Anna; Vesper, Cordula; Wiesbeck, Mathey

2007-01-01

and describing human-human interaction in terms of goal-oriented movement coordination is considered an important and necessary step for designing and describing human-robot interaction. In the present scenario, trajectories of hand and finger movements were recorded while two human participants performed......The present paper describes a scenario for examining mechanisms of movement coordination in humans and robots. It is assumed that coordination can best be achieved when behavioral rules that shape movement execution in humans are also considered for human-robot interaction. Investigating...... coordination were affected. Implications for human-robot interaction are discussed....

The Semantic Environment: Heuristics for a Cross-Context Human-Information Interaction Model

Science.gov (United States)

Resmini, Andrea; Rosati, Luca

This chapter introduces a multidisciplinary holistic approach for the general design of successful bridge experiences as a cross-context human-information interaction model. Nowadays it is common to interact through a number of different domains in order to communicate successfully, complete a task, or elicit a desired response: Users visit a reseller’s web site to find a specific item, book it, then drive to the closest store to complete their purchase. As such, one of the crucial challenges user experience design will face in the near future is how to structure and provide bridge experiences seamlessly spanning multiple communication channels or media formats for a specific purpose.

Building a Formal Model of a Human-Interactive System: Insights into the Integration of Formal Methods and Human Factors Engineering

Science.gov (United States)

Bolton, Matthew L.; Bass, Ellen J.

2009-01-01

Both the human factors engineering (HFE) and formal methods communities are concerned with finding and eliminating problems with safety-critical systems. This work discusses a modeling effort that leveraged methods from both fields to use model checking with HFE practices to perform formal verification of a human-interactive system. Despite the use of a seemingly simple target system, a patient controlled analgesia pump, the initial model proved to be difficult for the model checker to verify in a reasonable amount of time. This resulted in a number of model revisions that affected the HFE architectural, representativeness, and understandability goals of the effort. If formal methods are to meet the needs of the HFE community, additional modeling tools and technological developments are necessary.

A Multilayer Hidden Markov Models-Based Method for Human-Robot Interaction

Directory of Open Access Journals (Sweden)

Chongben Tao

2013-01-01

Full Text Available To achieve Human-Robot Interaction (HRI by using gestures, a continuous gesture recognition approach based on Multilayer Hidden Markov Models (MHMMs is proposed, which consists of two parts. One part is gesture spotting and segment module, the other part is continuous gesture recognition module. Firstly, a Kinect sensor is used to capture 3D acceleration and 3D angular velocity data of hand gestures. And then, a Feed-forward Neural Networks (FNNs and a threshold criterion are used for gesture spotting and segment, respectively. Afterwards, the segmented gesture signals are respectively preprocessed and vector symbolized by a sliding window and a K-means clustering method. Finally, symbolized data are sent into Lower Hidden Markov Models (LHMMs to identify individual gestures, and then, a Bayesian filter with sequential constraints among gestures in Upper Hidden Markov Models (UHMMs is used to correct recognition errors created in LHMMs. Five predefined gestures are used to interact with a Kinect mobile robot in experiments. The experimental results show that the proposed method not only has good effectiveness and accuracy, but also has favorable real-time performance.

Duplicability of self-interacting human genes.

LENUS (Irish Health Repository)

Pérez-Bercoff, Asa

2010-01-01

BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

Hand Gesture Modeling and Recognition for Human and Robot Interactive Assembly Using Hidden Markov Models

Directory of Open Access Journals (Sweden)

Fei Chen

2015-04-01

Full Text Available Gesture recognition is essential for human and robot collaboration. Within an industrial hybrid assembly cell, the performance of such a system significantly affects the safety of human workers. This work presents an approach to recognizing hand gestures accurately during an assembly task while in collaboration with a robot co-worker. We have designed and developed a sensor system for measuring natural human-robot interactions. The position and rotation information of a human worker's hands and fingertips are tracked in 3D space while completing a task. A modified chain-code method is proposed to describe the motion trajectory of the measured hands and fingertips. The Hidden Markov Model (HMM method is adopted to recognize patterns via data streams and identify workers' gesture patterns and assembly intentions. The effectiveness of the proposed system is verified by experimental results. The outcome demonstrates that the proposed system is able to automatically segment the data streams and recognize the gesture patterns thus represented with a reasonable accuracy ratio.

A conceptual framework to evaluate human-wildlife interactions within coupled human and natural systems

Directory of Open Access Journals (Sweden)

Anita T. Morzillo

2014-09-01

Full Text Available Landscape characteristics affect human-wildlife interactions. However, there is a need to better understand mechanisms that drive those interactions, particularly feedbacks that exist between wildlife-related impacts, human reaction to and behavior as a result of those impacts, and how land use and landscape characteristics may influence those components within coupled human and natural systems. Current conceptual models of human-wildlife interactions often focus on species population size as the independent variable driving those interactions. Such an approach potentially overlooks important feedbacks among and drivers of human-wildlife interactions that result from mere wildlife presence versus absence. We describe an emerging conceptual framework that focuses on wildlife as a driver of human behavior and allows us to better understand linkages between humans, wildlife, and the broader landscape. We also present results of a pilot analysis related to our own ongoing study of urban rodent control behavior to illustrate one application of this framework within a study of urban landscapes.

Interactively human: Sharing time, constructing materiality.

Science.gov (United States)

Roepstorff, Andreas

2013-06-01

Predictive processing models of cognition are promising an elegant way to unite action, perception, and learning. However, in the current formulations, they are species-unspecific and have very little particularly human about them. I propose to examine how, in this framework, humans can be able to massively interact and to build shared worlds that are both material and symbolic.

Turn-Taking Based on Information Flow for Fluent Human-Robot Interaction

OpenAIRE

Thomaz, Andrea L.; Chao, Crystal

2011-01-01

Turn-taking is a fundamental part of human communication. Our goal is to devise a turn-taking framework for human-robot interaction that, like the human skill, represents something fundamental about interaction, generic to context or domain. We propose a model of turn-taking, and conduct an experiment with human subjects to inform this model. Our findings from this study suggest that information flow is an integral part of human floor-passing behavior. Following this, we implement autonomous ...

Experiments with a First Prototype of a Spatial Model of Cultural Meaning through Natural-Language Human-Robot Interaction

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Oliver Schürer

2018-01-01

Full Text Available When using assistive systems, the consideration of individual and cultural meaning is crucial for the utility and acceptance of technology. Orientation, communication and interaction are rooted in perception and therefore always happen in material space. We understand that a major problem lies in the difference between human and technical perception of space. Cultural policies are based on meanings including their spatial situation and their rich relationships. Therefore, we have developed an approach where the different perception systems share a hybrid spatial model that is generated by artificial intelligence—a joint effort by humans and assistive systems. The aim of our project is to create a spatial model of cultural meaning based on interaction between humans and robots. We define the role of humanoid robots as becoming our companions. This calls for technical systems to include still inconceivable human and cultural agendas for the perception of space. In two experiments, we tested a first prototype of the communication module that allows a humanoid to learn cultural meanings through a machine learning system. Interaction is achieved by non-verbal and natural-language communication between humanoids and test persons. This helps us to better understand how a spatial model of cultural meaning can be developed.

Sphericall: A Human/Artificial Intelligence interaction experience

Directory of Open Access Journals (Sweden)

Frack Gechter

2014-12-01

Full Text Available Multi-agent systems are now wide spread in scientific works and in industrial applications. Few applications deal with the Human/Multi-agent system interaction. Multi-agent systems are characterized by individual entities, called agents, in interaction with each other and with their environment. Multi-agent systems are generally classified into complex systems categories since the global emerging phenomenon cannot be predicted even if every component is well known. The systems developed in this paper are named reactive because they behave using simple interaction models. In the reactive approach, the issue of Human/system interaction is hard to cope with and is scarcely exposed in literature. This paper presents Sphericall, an application aimed at studying Human/Complex System interactions and based on two physics inspired multi-agent systems interacting together. The Sphericall device is composed of a tactile screen and a spherical world where agents evolve. This paper presents both the technical background of Sphericall project and a feedback taken from the demonstration performed during OFFF Festival in La Villette (Paris.

Poster Abstract: A Practical Model for Human-Smart Appliances Interaction

DEFF Research Database (Denmark)

Fürst, Jonathan; Fruergaard, Andreas; Johannesen, Marco Høvinghof

2016-01-01

for human-smart appliance interaction. We present a prototype implementation with an off-the-shelf smart lighting and heating system in a shared office space. Our approach minimizes the need for location metadata. It relies on a human-feedback loop (both sensor based and manual) to identify the optimal...

Identification of walking human model using agent-based modelling

Science.gov (United States)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Human-scale interaction for virtual model displays: a clear case for real tools

Science.gov (United States)

Williams, George C.; McDowall, Ian E.; Bolas, Mark T.

1998-04-01

We describe a hand-held user interface for interacting with virtual environments displayed on a Virtual Model Display. The tool, constructed entirely of transparent materials, is see-through. We render a graphical counterpart of the tool on the display and map it one-to-one with the real tool. This feature, combined with a capability for touch- sensitive, discrete input, results in a useful spatial input device that is visually versatile. We discuss the tool's design and interaction techniques it supports. Briefly, we look at the human factors issues and engineering challenges presented by this tool and, in general, by the class of hand-held user interfaces that are see-through.

Study on Human-structure Dynamic Interaction in Civil Engineering

Science.gov (United States)

Gao, Feng; Cao, Li Lin; Li, Xing Hua

2018-06-01

The research of human-structure dynamic interaction are reviewed. Firstly, the influence of the crowd load on structural dynamic characteristics is introduced and the advantages and disadvantages of different crowd load models are analyzed. Then, discussing the influence of structural vibration on the human-induced load, especially the influence of different stiffness structures on the crowd load. Finally, questions about human-structure interaction that require further study are presented.

MOLECULAR MODELLING OF HUMAN ALDEHYDE OXIDASE AND IDENTIFICATION OF THE KEY INTERACTIONS IN THE ENZYME-SUBSTRATE COMPLEX

Directory of Open Access Journals (Sweden)

Siavoush Dastmalchi

2005-05-01

Full Text Available Aldehyde oxidase (EC 1.2.3.1, a cytosolic enzyme containing FAD, molybdenum and iron-sulphur cluster, is a member of non-cytochrome P-450 enzymes called molybdenum hydroxylases which is involved in the metabolism of a wide range of endogenous compounds and many drug substances. Drug metabolism is one of the important characteristics which influences many aspects of a therapeutic agent such as routes of administration, drug interaction and toxicity and therefore, characterisation of the key interactions between enzymes and substrates is very important from drug development point of view. The aim of this study was to generate a three-dimensional model of human aldehyde oxidase (AO in order to assist us to identify the mode of interaction between enzyme and a set of phethalazine/quinazoline derivatives. Both sequence-based (BLAST and inverse protein fold recognition methods (THREADER were used to identify the crystal structure of bovine xanthine dehydrogenase (pdb code of 1FO4 as the suitable template for comparative modelling of human AO. Model structure was generated by aligning and then threading the sequence of human AO onto the template structure, incorporating the associated cofactors, and molecular dynamics simulations and energy minimization using GROMACS program. Different criteria which were measured by the PROCHECK, QPACK, VERIFY-3D were indicative of a proper fold for the predicted structural model of human AO. For example, 97.9 percentages of phi and psi angles were in the favoured and most favoured regions in the ramachandran plot, and all residues in the model are assigned environmentally positive compatibility scores. Further evaluation on the model quality was performed by investigation of AO-mediated oxidation of a set of phthalazine/quinazoline derivatives to develop QSAR model capable of describing the extent of the oxidation. Substrates were aligned by docking onto the active site of the enzyme using GOLD technology and then

Human-Robot Interaction and Human Self-Realization

DEFF Research Database (Denmark)

Nørskov, Marco

2014-01-01

is to test the basis for this type of discrimination when it comes to human-robot interaction. Furthermore, the paper will take Heidegger's warning concerning technology as a vantage point and explore the possibility of human-robot interaction forming a praxis that might help humans to be with robots beyond...

The human dynamic clamp as a paradigm for social interaction.

Science.gov (United States)

Dumas, Guillaume; de Guzman, Gonzalo C; Tognoli, Emmanuelle; Kelso, J A Scott

2014-09-02

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject's own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual "teacher." We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof.

Ferromagnetic interaction model of activity level in workplace communication

Science.gov (United States)

Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

2013-03-01

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

Transient interaction model of electromagnetic field generated by lightning current pulses and human body

International Nuclear Information System (INIS)

Iváncsy, T; Kiss, I; Tamus, Z Á; Szücs, L

2015-01-01

The lightning current generates time-varying magnetic field near the down-conductor and the down-conductors are mounted on the wall of the buildings where residential places might be situated. It is well known that the rapidly changing magnetic fields can generate dangerous eddy currents in the human body.The higher duration and gradient of the magnetic field can cause potentially life threatening cardiac stimulation. The coupling mechanism between the electromagnetic field and the human body is based on a well-known physical phenomena (e.g. Faradays law of induction). However, the calculation of the induced current is very complicated because the shape of the organs is complex and the determination of the material properties of living tissues is difficult, as well. Our previous study revealed that the cardiac stimulation is independent of the rising time of the lightning current and only the peak of the current counts.In this study, the authors introduce an improved model of the interaction of electromagnetic fields of lighting current near down-conductor and human body. Our previous models are based on the quasi stationer field calculations, the new improved model is a transient model. This is because the magnetic field around the down-conductor and in the human body can be determined more precisely, therefore the dangerous currents in the body can be estimated. (paper)

Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems

Science.gov (United States)

Mitchell, Christine M.

1993-01-01

This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.

Abstract robots with an attitude : applying interpersonal relation models to human-robot interaction

NARCIS (Netherlands)

Hiah, J.L.; Beursgens, L.; Haex, R.; Perez Romero, L.M.; Teh, Y.; Bhomer, ten M.; Berkel, van R.E.A.; Barakova, E.I.

2013-01-01

This paper explores new possibilities for social interaction between a human user and a robot with an abstract shape. The social interaction takes place by simulating behaviors such as submissiveness and dominance and analyzing the corresponding human reactions. We used an object that has no

DigitalHuman (DH): An Integrative Mathematical Model ofHuman Physiology

Science.gov (United States)

Hester, Robert L.; Summers, Richard L.; lIescu, Radu; Esters, Joyee; Coleman, Thomas G.

2010-01-01

Mathematical models and simulation are important tools in discovering the key causal relationships governing physiological processes and improving medical intervention when physiological complexity is a central issue. We have developed a model of integrative human physiology called DigitalHuman (DH) consisting of -5000 variables modeling human physiology describing cardiovascular, renal, respiratory, endocrine, neural and metabolic physiology. Users can view time-dependent solutions and interactively introduce perturbations by altering numerical parameters to investigate new hypotheses. The variables, parameters and quantitative relationships as well as all other model details are described in XML text files. All aspects of the model, including the mathematical equations describing the physiological processes are written in XML open source, text-readable files. Model structure is based upon empirical data of physiological responses documented within the peer-reviewed literature. The model can be used to understand proposed physiological mechanisms and physiological interactions that may not be otherwise intUitively evident. Some of the current uses of this model include the analyses of renal control of blood pressure, the central role of the liver in creating and maintaining insulin resistance, and the mechanisms causing orthostatic hypotension in astronauts. Additionally the open source aspect of the modeling environment allows any investigator to add detailed descriptions of human physiology to test new concepts. The model accurately predicts both qualitative and more importantly quantitative changes in clinically and experimentally observed responses. DigitalHuman provides scientists a modeling environment to understand the complex interactions of integrative physiology. This research was supported by.NIH HL 51971, NSF EPSCoR, and NASA

Drum-mate: interaction dynamics and gestures in human-humanoid drumming experiments

Science.gov (United States)

Kose-Bagci, Hatice; Dautenhahn, Kerstin; Syrdal, Dag S.; Nehaniv, Chrystopher L.

2010-06-01

This article investigates the role of interaction kinesics in human-robot interaction (HRI). We adopted a bottom-up, synthetic approach towards interactive competencies in robots using simple, minimal computational models underlying the robot's interaction dynamics. We present two empirical, exploratory studies investigating a drumming experience with a humanoid robot (KASPAR) and a human. In the first experiment, the turn-taking behaviour of the humanoid is deterministic and the non-verbal gestures of the robot accompany its drumming to assess the impact of non-verbal gestures on the interaction. The second experiment studies a computational framework that facilitates emergent turn-taking dynamics, whereby the particular dynamics of turn-taking emerge from the social interaction between the human and the humanoid. The results from the HRI experiments are presented and analysed qualitatively (in terms of the participants' subjective experiences) and quantitatively (concerning the drumming performance of the human-robot pair). The results point out a trade-off between the subjective evaluation of the drumming experience from the perspective of the participants and the objective evaluation of the drumming performance. A certain number of gestures was preferred as a motivational factor in the interaction. The participants preferred the models underlying the robot's turn-taking which enable the robot and human to interact more and provide turn-taking closer to 'natural' human-human conversations, despite differences in objective measures of drumming behaviour. The results are consistent with the temporal behaviour matching hypothesis previously proposed in the literature which concerns the effect that the participants adapt their own interaction dynamics to the robot's.

Understanding and modelling man-machine interaction

International Nuclear Information System (INIS)

Cacciabue, P.C.

1996-01-01

This paper gives an overview of the current state of the art in man-machine system interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to the design and analysis of man-machine interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans an their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (orig.)

Understanding and modelling Man-Machine Interaction

International Nuclear Information System (INIS)

Cacciabue, P.C.

1991-01-01

This paper gives an overview of the current state of the art in man machine systems interaction studies, focusing on the problems derived from highly automated working environments and the role of humans in the control loop. In particular, it is argued that there is a need for sound approaches to design and analysis of Man-Machine Interaction (MMI), which stem from the contribution of three expertises in interfacing domains, namely engineering, computer science and psychology: engineering for understanding and modelling plants and their material and energy conservation principles; psychology for understanding and modelling humans and their cognitive behaviours; computer science for converting models in sound simulations running in appropriate computer architectures. (author)

Interaction of Citrinin with Human Serum Albumin

Directory of Open Access Journals (Sweden)

Miklós Poór

2015-12-01

Full Text Available Citrinin (CIT is a mycotoxin produced by several Aspergillus, Penicillium, and Monascus species. CIT occurs worldwide in different foods and drinks and causes health problems for humans and animals. Human serum albumin (HSA is the most abundant plasma protein in human circulation. Albumin forms stable complexes with many drugs and xenobiotics; therefore, HSA commonly plays important role in the pharmacokinetics or toxicokinetics of numerous compounds. However, the interaction of CIT with HSA is poorly characterized yet. In this study, the complex formation of CIT with HSA was investigated using fluorescence spectroscopy and ultrafiltration techniques. For the deeper understanding of the interaction, thermodynamic, and molecular modeling studies were performed as well. Our results suggest that CIT forms stable complex with HSA (logK ~ 5.3 and its primary binding site is located in subdomain IIA (Sudlow’s Site I. In vitro cell experiments also recommend that CIT-HSA interaction may have biological relevance. Finally, the complex formations of CIT with bovine, porcine, and rat serum albumin were investigated, in order to test the potential species differences of CIT-albumin interactions.

Deep Predictive Models in Interactive Music

OpenAIRE

Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

2018-01-01

Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

Human Performance Modeling for Dynamic Human Reliability Analysis

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald Laurids [Idaho National Laboratory; Joe, Jeffrey Clark [Idaho National Laboratory; Mandelli, Diego [Idaho National Laboratory

2015-08-01

Part of the U.S. Department of Energy’s (DOE’s) Light Water Reac- tor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Charac- terization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk framework. In this paper, we review simulation based and non simulation based human reliability analysis (HRA) methods. This paper summarizes the founda- tional information needed to develop a feasible approach to modeling human in- teractions in RISMC simulations.

Socio-hydrology: conceptualising human-flood interactions

Directory of Open Access Journals (Sweden)

G. Di Baldassarre

2013-08-01

Full Text Available Over history, humankind has tended to settle near streams because of the role of rivers as transportation corridors and the fertility of riparian areas. However, human settlements in floodplains have been threatened by the risk of flooding. Possible responses have been to resettle away and/or modify the river system by building flood control structures. This has led to a complex web of interactions and feedback mechanisms between hydrological and social processes in settled floodplains. This paper is an attempt to conceptualise these interplays for hypothetical human-flood systems. We develop a simple, dynamic model to represent the interactions and feedback loops between hydrological and social processes. The model is then used to explore the dynamics of the human-flood system and the effect of changing individual characteristics, including external forcing such as technological development. The results show that the conceptual model is able to reproduce reciprocal effects between floods and people as well as the emergence of typical patterns. For instance, when levees are built or raised to protect floodplain areas, their presence not only reduces the frequency of flooding, but also exacerbates high water levels. Then, because of this exacerbation, higher flood protection levels are required by society. As a result, more and more flooding events are avoided, but rare and catastrophic events take place.

Modeling Users' Experiences with Interactive Systems

CERN Document Server

Karapanos, Evangelos

2013-01-01

Over the past decade the field of Human-Computer Interaction has evolved from the study of the usability of interactive products towards a more holistic understanding of how they may mediate desired human experiences.  This book identifies the notion of diversity in usersʼ experiences with interactive products and proposes methods and tools for modeling this along two levels: (a) interpersonal diversity in usersʽ responses to early conceptual designs, and (b) the dynamics of usersʼ experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in usersʼ responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data. iScale, a tool for the retrospective assessment of usersʼ experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited exper...

Human-Structure Dynamic Interaction during Short-Distance Free Falls

Directory of Open Access Journals (Sweden)

E. Shahabpoor

2016-01-01

Full Text Available The dynamic interactions of falling human bodies with civil structures, regardless of their potentially critical effects, have sparsely been researched in contact biomechanics. The physical contact models suggested in the existing literature, particularly for short-distant falls in home settings, assume the human body falls on a “rigid” (not vibrating ground. A similar assumption is usually made during laboratory-based fall tests, including force platforms. Based on observations from a set of pediatric head-first free fall tests, the present paper shows that the dynamics of the grounded force plate are not always negligible when doing fall test in a laboratory setting. By using a similar analogy for lightweight floor structures, it is shown that ignoring the dynamics of floors in the contact model can result in an up to 35% overestimation of the peak force experienced by a falling human. A nonlinear contact model is suggested, featuring an agent-based modelling approach, where the dynamics of the falling human and the impact object (force plate or a floor structure here are each modelled using a single-degree-of-freedom model to simulate their dynamic interactions. The findings of this research can have wide applications in areas such as impact biomechanics and sports science.

A dynamical systems model of progesterone receptor interactions with inflammation in human parturition.

Science.gov (United States)

Brubaker, Douglas; Barbaro, Alethea; R Chance, Mark; Mesiano, Sam

2016-08-19

Progesterone promotes uterine relaxation and is essential for the maintenance of pregnancy. Withdrawal of progesterone activity and increased inflammation within the uterine tissues are key triggers for parturition. Progesterone actions in myometrial cells are mediated by two progesterone receptor (PR) isoforms, PR-A and PR-B, that function as ligand-activated transcription factors. PR-B mediates relaxatory actions of progesterone, in part, by decreasing myometrial cell responsiveness to pro-inflammatory stimuli. These same pro-inflammatory stimuli promote the expression of PR-A which inhibits the anti-inflammatory activity of PR-B. Competitive interaction between the progesterone receptors then augments myometrial responsiveness to pro-inflammatory stimuli. The interaction between PR-B transcriptional activity and inflammation in the pregnancy myometrium is examined using a dynamical systems model in which quiescence and labor are represented as phase-space equilibrium points. Our model shows that PR-B transcriptional activity and the inflammatory load determine the stability of the quiescent and laboring phenotypes. The model is tested using published transcriptome datasets describing the mRNA abundances in the myometrium before and after the onset of labor at term. Surrogate transcripts were selected to reflect PR-B transcriptional activity and inflammation status. The model coupling PR-B activity and inflammation predicts contractile status (i.e., laboring or quiescent) with high precision and recall and outperforms uncoupled single and two-gene classifiers. Linear stability analysis shows that phase space bifurcations exist in our model that may reflect the phenotypic states of the pregnancy uterus. The model describes a possible tipping point for the transition of the quiescent to the contractile laboring phenotype. Our model describes the functional interaction between the PR-A:PR-B hypothesis and tissue level inflammation in the pregnancy uterus and is a

The ‘hit’ phenomenon: a mathematical model of human dynamics interactions as a stochastic process

Science.gov (United States)

Ishii, Akira; Arakaki, Hisashi; Matsuda, Naoya; Umemura, Sanae; Urushidani, Tamiko; Yamagata, Naoya; Yoshida, Narihiko

2012-06-01

A mathematical model for the ‘hit’ phenomenon in entertainment within a society is presented as a stochastic process of human dynamics interactions. The model uses only the advertisement budget time distribution as an input, and word-of-mouth (WOM), represented by posts on social network systems, is used as data to make a comparison with the calculated results. The unit of time is days. The WOM distribution in time is found to be very close to the revenue distribution in time. Calculations for the Japanese motion picture market based on the mathematical model agree well with the actual revenue distribution in time.

An object-oriented computational model to study cardiopulmonary hemodynamic interactions in humans.

Science.gov (United States)

Ngo, Chuong; Dahlmanns, Stephan; Vollmer, Thomas; Misgeld, Berno; Leonhardt, Steffen

2018-06-01

This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans. Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure-volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature. The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature. Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation. Copyright © 2018 Elsevier B.V. All rights reserved.

Modelling human factor with Petri nets

International Nuclear Information System (INIS)

Bedreaga, Luminita; Constantinescu, Cristina; Guzun, Basarab

2007-01-01

The human contribution to risk and safety of nuclear power plant operation can be best understood, assessed and quantified using tools to evaluate human reliability. Human reliability analysis becomes an important part of every probabilistic safety assessment and it is used to demonstrate that nuclear power plants designed with different safety levels are prepared to cope with severe accidents. Human reliability analysis in context of probabilistic safety assessment consists in: identifying human-system interactions important to safety; quantifying probabilities appropriate with these interactions. Nowadays, the complex system functions can be modelled using special techniques centred either on states space adequate to system or on events appropriate to the system. Knowing that complex system model consists in evaluating the likelihood of success, in other words, in evaluating the possible value for that system being in some state, the inductive methods which are based on the system states can be applied also for human reliability modelling. Thus, switching to the system states taking into account the human interactions, the underlying basis of the Petri nets can be successfully applied and the likelihoods appropriate to these states can also derived. The paper presents the manner to assess the human reliability quantification using Petri nets approach. The example processed in the paper is from human reliability documentation without a detailed human factor analysis (qualitative). The obtained results by these two kinds of methods are in good agreement. (authors)

A human protein interaction network shows conservation of aging processes between human and invertebrate species.

Directory of Open Access Journals (Sweden)

Russell Bell

2009-03-01

Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

Molecular interaction of PCB153 to human serum albumin: Insights from spectroscopic and molecular modeling studies

Energy Technology Data Exchange (ETDEWEB)

Han, Chao; Fang, Senbiao; Cao, Huiming; Lu, Yan; Ma, Yaqiong [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Wei, Dongfeng [Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700 (China); Xie, Xiaoyun [College of Earth and Environmental Science, Lanzhou University, Lanzhou 730000 (China); Liu, Xiaohua [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Li, Xin [College of Food and Bioengineering, Henan University of Science and Technology, Luoyang 471003 (China); Fei, Dongqing [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Zhao, Chunyan, E-mail: zhaochy07@lzu.edu.cn [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China)

2013-03-15

Highlights: ► We identify the binding mode of PCB153 to human serum albumin (HSA). ► Spectroscopic and molecular modeling results reveal that PCB153 binds at the site II. ► The interaction is mainly governed by hydrophobic and hydrogen bond forces. ► The work helps to probe transporting, distribution and toxicity effect of PCBs. -- Abstract: Polychlorinated biphenyls (PCBs) possessed much potential hazard to environment because of its chemical stability and biological toxicity. Here, we identified the binding mode of a representative compound, PCB153, to human serum albumin (HSA) using fluorescence and molecular dynamics simulation methods. The fluorescence study showed that the intrinsic fluorescence of HSA was quenched by addition of PCB153 through a static quenching mechanism. The thermodynamic analysis proved the binding behavior was mainly governed by hydrophobic force. Furthermore, as evidenced by site marker displacement experiments using two probe compounds, it revealed that PCB153 acted exactly on subdomain IIIA (site II) of HSA. On the other hand, the molecular dynamics studies as well as free energy calculations made another important contribution to understand the conformational changes of HSA and the stability of HSA-PCB153 system. Molecular docking revealed PCB153 can bind in a large hydrophobic activity of subdomain IIIA by the hydrophobic interaction and hydrogen bond interactions between chlorine atoms and residue ASN391. The present work provided reasonable models helping us further understand the transporting, distribution and toxicity effect of PCBs when it spread into human blood serum.

The Self-Organization of Human Interaction

DEFF Research Database (Denmark)

Dale, Rick; Fusaroli, Riccardo; Duran, Nicholas

2013-01-01

We describe a “centipede’s dilemma” that faces the sciences of human interaction. Research on human interaction has been involved in extensive theoretical debate, although the vast majority of research tends to focus on a small set of human behaviors, cognitive processes, and interactive contexts...

Measuring Multimodal Synchrony for Human-Computer Interaction

NARCIS (Netherlands)

Reidsma, Dennis; Nijholt, Antinus; Tschacher, Wolfgang; Ramseyer, Fabian; Sourin, A.

2010-01-01

Nonverbal synchrony is an important and natural element in human-human interaction. It can also play various roles in human-computer interaction. In particular this is the case in the interaction between humans and the virtual humans that inhabit our cyberworlds. Virtual humans need to adapt their

System dynamics model for environment - human systems interaction in the mining industry

International Nuclear Information System (INIS)

Pal, B.K.

1994-01-01

Use of advanced technology in the mining activities are polluting the natural environment, interfering with the normal life of the miners/residents. In this paper, health hazards due to underground workings and effect of environmental conditions on men are discussed. A composite system inter-relationship of the mining industries with the Government, society and environmental sectors is established. Allowing certain level of pollution, a system dynamics model is developed considering the parameters like more revenues from the mining industries, degradation of quality of life index - environmental index on long-term and short-term basis, new diseases due to pollution, social awareness, health care facilities, tax exemption etc. This model will help us to understand the optimisation of the parameters to establish the better interaction in the environment-human systems in the mining industries. 14 refs., 4 figs., 2 tabs

Emotion based human-robot interaction

Directory of Open Access Journals (Sweden)

Berns Karsten

2018-01-01

Full Text Available Human-machine interaction is a major challenge in the development of complex humanoid robots. In addition to verbal communication the use of non-verbal cues such as hand, arm and body gestures or mimics can improve the understanding of the intention of the robot. On the other hand, by perceiving such mechanisms of a human in a typical interaction scenario the humanoid robot can adapt its interaction skills in a better way. In this work, the perception system of two social robots, ROMAN and ROBIN of the RRLAB of the TU Kaiserslautern, is presented in the range of human-robot interaction.

Interaction debugging : an integral approach to analyze human-robot interaction

NARCIS (Netherlands)

Kooijmans, T.; Kanda, T.; Bartneck, C.; Ishiguro, H.; Hagita, N.

2006-01-01

Along with the development of interactive robots, controlled experiments and field trials are regularly conducted to stage human-robot interaction. Experience in this field has shown that analyzing human-robot interaction for evaluation purposes fosters the development of improved systems and the

On the application of motivation theory to human factors/ergonomics: motivational design principles for human-technology interaction.

Science.gov (United States)

Szalma, James L

2014-12-01

Motivation is a driving force in human-technology interaction. This paper represents an effort to (a) describe a theoretical model of motivation in human technology interaction, (b) provide design principles and guidelines based on this theory, and (c) describe a sequence of steps for the. evaluation of motivational factors in human-technology interaction. Motivation theory has been relatively neglected in human factors/ergonomics (HF/E). In both research and practice, the (implicit) assumption has been that the operator is already motivated or that motivation is an organizational concern and beyond the purview of HF/E. However, technology can induce task-related boredom (e.g., automation) that can be stressful and also increase system vulnerability to performance failures. A theoretical model of motivation in human-technology interaction is proposed, based on extension of the self-determination theory of motivation to HF/E. This model provides the basis for both future research and for development of practical recommendations for design. General principles and guidelines for motivational design are described as well as a sequence of steps for the design process. Human motivation is an important concern for HF/E research and practice. Procedures in the design of both simple and complex technologies can, and should, include the evaluation of motivational characteristics of the task, interface, or system. In addition, researchers should investigate these factors in specific human-technology domains. The theory, principles, and guidelines described here can be incorporated into existing techniques for task analysis and for interface and system design.

Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots

Directory of Open Access Journals (Sweden)

Mazen Ghandour

2017-06-01

Full Text Available In this paper, a novel approach for collision avoidance for indoor mobile robots based on human-robot interaction is realized. The main contribution of this work is a new technique for collision avoidance by engaging the human and the robot in generating new collision-free paths. In mobile robotics, collision avoidance is critical for the success of the robots in implementing their tasks, especially when the robots navigate in crowded and dynamic environments, which include humans. Traditional collision avoidance methods deal with the human as a dynamic obstacle, without taking into consideration that the human will also try to avoid the robot, and this causes the people and the robot to get confused, especially in crowded social places such as restaurants, hospitals, and laboratories. To avoid such scenarios, a reactive-supervised collision avoidance system for mobile robots based on human-robot interaction is implemented. In this method, both the robot and the human will collaborate in generating the collision avoidance via interaction. The person will notify the robot about the avoidance direction via interaction, and the robot will search for the optimal collision-free path on the selected direction. In case that no people interacted with the robot, it will select the navigation path autonomously and select the path that is closest to the goal location. The humans will interact with the robot using gesture recognition and Kinect sensor. To build the gesture recognition system, two models were used to classify these gestures, the first model is Back-Propagation Neural Network (BPNN, and the second model is Support Vector Machine (SVM. Furthermore, a novel collision avoidance system for avoiding the obstacles is implemented and integrated with the HRI system. The system is tested on H20 robot from DrRobot Company (Canada and a set of experiments were implemented to report the performance of the system in interacting with the human and avoiding

Study of interaction of butyl p-hydroxybenzoate with human serum albumin by molecular modeling and multi-spectroscopic method

Energy Technology Data Exchange (ETDEWEB)

Wang Qin, E-mail: wqing07@lzu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Zhang Yaheng, E-mail: zhangyah04@lzu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Sun Huijun, E-mail: sun.hui.jun-04@163.co [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Chen Hongli, E-mail: hlchen@lzu.edu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Chen Xingguo, E-mail: chenxg@lzu.edu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China)

2011-02-15

Study of the interaction between butyl p-hydroxybenzoate (butoben) and human serum albumin (HSA) has been performed by molecular modeling and multi-spectroscopic method. The interaction mechanism was predicted through molecular modeling first, then the binding parameters were confirmed using a series of spectroscopic methods, including fluorescence spectroscopy, UV-visible absorbance spectroscopy, circular dichroism (CD) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy. The thermodynamic parameters of the reaction, standard enthalpy {Delta}H{sup 0} and entropy {Delta}S{sup 0}, have been calculated to be -29.52 kJ mol{sup -1} and -24.23 J mol{sup -1} K{sup -1}, respectively, according to the Van't Hoff equation, which suggests the van der Waals force and hydrogen bonds are the predominant intermolecular forces in stabilizing the butoben-HSA complex. Results obtained by spectroscopic methods are consistent with that of the molecular modeling study. In addition, alteration of secondary structure of HSA in the presence of butoben was evaluated using the data obtained from UV-visible absorbance, CD and FT-IR spectroscopies. - Research highlights: The interaction between butyl p-hydroxybenzoate with HSA has been investigated for the first time. Molecular modeling study can provide theoretical direction for experimental design. Multi-spectroscopic method can provide the binding parameters and thermodynamic parameters. These results are important for food safety and human health when using parabens as a preservative.

Multispectroscopic and molecular modeling approach to investigate the interaction of diclofop-methyl enantiomers with human serum albumin

Energy Technology Data Exchange (ETDEWEB)

Zhang, Ping; Liu, Donghui; Li, Zhe; Shen, Zhigang; Wang, Peng [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China); Zhou, Meng [Business School, University of Bedfordshire, Luton LU1 3JU (United Kingdom); Zhou, Zhiqiang [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China); Zhu, Wentao, E-mail: wentaozhu@cau.edu.cn [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China)

2014-11-15

Pesticides and related environmental contaminants have always been threated to human health due to their intrinsic toxicity. In the context of this contribution, the interaction between diclofop-methyl (DM) enantiomers and human serum albumin (HSA) has been characterized by steady state and three-dimensional fluorescence, molecular modeling, circular dichroism (CD) and ultraviolet–visible (UV–vis) spectroscopy. The binding constants significantly showed the binding was enantioselective and HSA had higher affinity for S-DM. The thermodynamic parameters of the binding reaction (ΔG, ΔH and ΔS) clearly signified that hydrophobic effects and H-bonds contribute to the formation of DM-HSA complex. The alterations of protein secondary structure in the presence of DM enantiomers were confirmed by CD spectroscopy, UV–vis and three-dimensional fluorescence spectroscopy. In addition, both fluorescence probe study and molecular modeling simulation evidenced the binding of DM enantiomers to HSA primarily took place in subdomain IIIA (Sudlow's site II). This investigation highlights the binding mechanism, specific binding sites and binding region of DM enantiomers on human serum albumin at the first time. Besides, such task can provide important insight to the interaction of the physiological protein HSA with chiral aryloxyphenoxypropionate herbicides and give support to the human health risk assessment. - Highlights: • The binding of DM enantiomers to HSA was enantioselective. • HSA had higher affinity for S-DM than R-DM. • Hydrophobic effects and hydrogen bonds were involved in the DM-HSA interaction. • The binding of DM enantiomers to HSA primarily took place in Sudlow's site II. • DM enantiomers could alter the second structure of HSA.

Multispectroscopic and molecular modeling approach to investigate the interaction of diclofop-methyl enantiomers with human serum albumin

International Nuclear Information System (INIS)

Zhang, Ping; Liu, Donghui; Li, Zhe; Shen, Zhigang; Wang, Peng; Zhou, Meng; Zhou, Zhiqiang; Zhu, Wentao

2014-01-01

Pesticides and related environmental contaminants have always been threated to human health due to their intrinsic toxicity. In the context of this contribution, the interaction between diclofop-methyl (DM) enantiomers and human serum albumin (HSA) has been characterized by steady state and three-dimensional fluorescence, molecular modeling, circular dichroism (CD) and ultraviolet–visible (UV–vis) spectroscopy. The binding constants significantly showed the binding was enantioselective and HSA had higher affinity for S-DM. The thermodynamic parameters of the binding reaction (ΔG, ΔH and ΔS) clearly signified that hydrophobic effects and H-bonds contribute to the formation of DM-HSA complex. The alterations of protein secondary structure in the presence of DM enantiomers were confirmed by CD spectroscopy, UV–vis and three-dimensional fluorescence spectroscopy. In addition, both fluorescence probe study and molecular modeling simulation evidenced the binding of DM enantiomers to HSA primarily took place in subdomain IIIA (Sudlow's site II). This investigation highlights the binding mechanism, specific binding sites and binding region of DM enantiomers on human serum albumin at the first time. Besides, such task can provide important insight to the interaction of the physiological protein HSA with chiral aryloxyphenoxypropionate herbicides and give support to the human health risk assessment. - Highlights: • The binding of DM enantiomers to HSA was enantioselective. • HSA had higher affinity for S-DM than R-DM. • Hydrophobic effects and hydrogen bonds were involved in the DM-HSA interaction. • The binding of DM enantiomers to HSA primarily took place in Sudlow's site II. • DM enantiomers could alter the second structure of HSA

Two-Stage Hidden Markov Model in Gesture Recognition for Human Robot Interaction

Directory of Open Access Journals (Sweden)

Nhan Nguyen-Duc-Thanh

2012-07-01

Full Text Available Hidden Markov Model (HMM is very rich in mathematical structure and hence can form the theoretical basis for use in a wide range of applications including gesture representation. Most research in this field, however, uses only HMM for recognizing simple gestures, while HMM can definitely be applied for whole gesture meaning recognition. This is very effectively applicable in Human-Robot Interaction (HRI. In this paper, we introduce an approach for HRI in which not only the human can naturally control the robot by hand gesture, but also the robot can recognize what kind of task it is executing. The main idea behind this method is the 2-stages Hidden Markov Model. The 1st HMM is to recognize the prime command-like gestures. Based on the sequence of prime gestures that are recognized from the 1st stage and which represent the whole action, the 2nd HMM plays a role in task recognition. Another contribution of this paper is that we use the output Mixed Gaussian distribution in HMM to improve the recognition rate. In the experiment, we also complete a comparison of the different number of hidden states and mixture components to obtain the optimal one, and compare to other methods to evaluate this performance.

A study on the application of voice interaction in automotive human machine interface experience design

Science.gov (United States)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

Study on the interaction between tabersonine and human serum albumin by optical spectroscopy and molecular modeling methods

Energy Technology Data Exchange (ETDEWEB)

Jiang Hua; Chen, Rongrong [Department of Biology, College of Life Science and Technology, Jinan University, Guangzhou 510632 (China); Pu Hanlin, E-mail: tphl@jnu.edu.cn [Department of Biology, College of Life Science and Technology, Jinan University, Guangzhou 510632 (China)

2012-03-15

The mechanism of interaction between tabersonine (TAB) and human serum albumin (HSA) was investigated by the methods of fluorescence spectroscopy, UV-vis absorption spectroscopy and molecular modeling under simulative physiological conditions. Results obtained from analysis of fluorescence spectrum and fluorescence intensity indicated that TAB has a strong ability to quench the intrinsic fluorescence of HSA through a static quenching procedure. The binding site number n and apparent binding constant K{sub a}, corresponding thermodynamic parameters {Delta}G, {Delta}H and {Delta}S at different temperatures were calculated. The distance r between donor (human serum albumin) and acceptor (tabersonine) was obtained according to the Foerster theory of non-radiation energy transfer. The effect of common ions on binding constant was also investigated. The synchronous fluorescence and three-dimensional fluorescence spectra were used to investigate the structural change of HSA molecules with addition of TAB. Furthermore, the study of molecular modeling indicated that TAB could bind to the site I of HSA and hydrophobic interaction was the major acting force, which was in agreement with the binding mode study. - Highlights: Black-Right-Pointing-Pointer Fluorescence study of the mechanism of interaction between tabersonine and HSA. Black-Right-Pointing-Pointer The binding parameters and thermodynamic parameters were calculated. Black-Right-Pointing-Pointer The distance r was obtained and common ions effects was investigated. Black-Right-Pointing-Pointer Conformation of HSA and its molecular modeling was analyzed.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

Directory of Open Access Journals (Sweden)

Li Deng

2016-01-01

Full Text Available In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

Science.gov (United States)

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

Science.gov (United States)

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial

Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

Science.gov (United States)

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.

Predictive Mechanisms Are Not Involved the Same Way during Human-Human vs. Human-Machine Interactions: A Review

Directory of Open Access Journals (Sweden)

Aïsha Sahaï

2017-10-01

Full Text Available Nowadays, interactions with others do not only involve human peers but also automated systems. Many studies suggest that the motor predictive systems that are engaged during action execution are also involved during joint actions with peers and during other human generated action observation. Indeed, the comparator model hypothesis suggests that the comparison between a predicted state and an estimated real state enables motor control, and by a similar functioning, understanding and anticipating observed actions. Such a mechanism allows making predictions about an ongoing action, and is essential to action regulation, especially during joint actions with peers. Interestingly, the same comparison process has been shown to be involved in the construction of an individual's sense of agency, both for self-generated and observed other human generated actions. However, the implication of such predictive mechanisms during interactions with machines is not consensual, probably due to the high heterogeneousness of the automata used in the experimentations, from very simplistic devices to full humanoid robots. The discrepancies that are observed during human/machine interactions could arise from the absence of action/observation matching abilities when interacting with traditional low-level automata. Consistently, the difficulties to build a joint agency with this kind of machines could stem from the same problem. In this context, we aim to review the studies investigating predictive mechanisms during social interactions with humans and with automated artificial systems. We will start by presenting human data that show the involvement of predictions in action control and in the sense of agency during social interactions. Thereafter, we will confront this literature with data from the robotic field. Finally, we will address the upcoming issues in the field of robotics related to automated systems aimed at acting as collaborative agents.

Effect of cognitive biases on human-robot interaction: a case study of robot's misattribution

OpenAIRE

Biswas, Mriganka; Murray, John

2014-01-01

This paper presents a model for developing long-term human-robot interactions and social relationships based on the principle of 'human' cognitive biases applied to a robot. The aim of this work is to study how a robot influenced with human ‘misattribution’ helps to build better human-robot interactions than unbiased robots. The results presented in this paper suggest that it is important to know the effect of cognitive biases in human characteristics and interactions in order to better u...

Studying human-automation interactions: methodological lessons learned from the human-centred automation experiments 1997-2001

International Nuclear Information System (INIS)

Massaiu, Salvatore; Skjerve, Ann Britt Miberg; Skraaning, Gyrd Jr.; Strand, Stine; Waeroe, Irene

2004-04-01

This report documents the methodological lessons learned from the Human Centred Automation (HCA) programme both in terms of psychometric evaluation of the measurement techniques developed for human-automation interaction study, and in terms of the application of advanced statistical methods for analysis of experiments. The psychometric evaluation is based on data from the four experiments performed within the HCA programme. The result is a single-source reference text of measurement instruments for the study of human-automation interaction, part of which were specifically developed by the programme. The application of advanced statistical techniques is exemplified by additional analyses performed on the IPSN-HCA experiment of 1998. Special importance is given to the statistical technique Structural Equation Modeling, for the possibility it offers to advance, and empirically test, comprehensive explanations about human-automation interactions. The additional analyses of the IPSN-HCA experiment investigated how the operators formed judgments about their own performance. The issue is of substantive interest for human automation interaction research because the operators' over- or underestimation of their own performance could be seen as a symptom of human-machine mismatch, and a potential latent failure. These analyses concluded that it is the interplay between (1) the level of automation and several factors that determines the operators' bias in performance self-estimation: (2) the nature of the task, (3) the level of scenario complexity, and (4) the level of trust in the automatic system. A structural model that expresses the interplay of all these factors was empirically evaluated and was found able to provide a concise and elegant explanation of the intricate pattern of relationships between the identified factors. (Author)

Human-computer interaction : Guidelines for web animation

OpenAIRE

Galyani Moghaddam, Golnessa; Moballeghi, Mostafa

2006-01-01

Human-computer interaction in the large is an interdisciplinary area which attracts researchers, educators, and practioners from many differenf fields. Human-computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. This paper is related to the human side of human-computer interaction and focuses on animations. The growing use of animation in Web pages testifies to the increasing ease with which such multim...

Prosthetic Leg Control in the Nullspace of Human Interaction.

Science.gov (United States)

Gregg, Robert D; Martin, Anne E

2016-07-01

Recent work has extended the control method of virtual constraints, originally developed for autonomous walking robots, to powered prosthetic legs for lower-limb amputees. Virtual constraints define desired joint patterns as functions of a mechanical phasing variable, which are typically enforced by torque control laws that linearize the output dynamics associated with the virtual constraints. However, the output dynamics of a powered prosthetic leg generally depend on the human interaction forces, which must be measured and canceled by the feedback linearizing control law. This feedback requires expensive multi-axis load cells, and actively canceling the interaction forces may minimize the human's influence over the prosthesis. To address these limitations, this paper proposes a method for projecting virtual constraints into the nullspace of the human interaction terms in the output dynamics. The projected virtual constraints naturally render the output dynamics invariant with respect to the human interaction forces, which instead enter into the internal dynamics of the partially linearized prosthetic system. This method is illustrated with simulations of a transfemoral amputee model walking with a powered knee-ankle prosthesis that is controlled via virtual constraints with and without the proposed projection.

Investigation of the interaction between isomeric derivatives and human serum albumin by fluorescence spectroscopy and molecular modeling

Energy Technology Data Exchange (ETDEWEB)

Wang, Ruiyong, E-mail: wangry@zzu.edu.cn; Dou, Huanjing; Yin, Yujing; Xie, Yuanzhe; Sun, Li; Liu, Chunmei; Dong, Jingjing; Huang, Gang; Zhu, Yanyan; Song, Chuanjun, E-mail: chjsong@zzu.edu.cn; Chang, Junbiao, E-mail: changjunbiao@zzu.edu.cn

2014-10-15

In this paper, we have synthesized 9H-pyrrolo[1,2-a]indol-9-ones and the isomeric indeno[2,1-b]pyrrol-8-ones. The interactions of human serum albumin with series of isomeric derivatives have been studied by spectrophotometric methods. Results show the intrinsic fluorescence is quenched by the derivatives with a static quenching procedure. The thermodynamics parameters indicate that van der Waals forces and hydrogen bonds play a major role in the interactions. The results of synchronous fluorescence spectra demonstrate that the microenvironments of Trp residue of human serum albumin are disturbed by most derivatives. Thermodynamic results showed that the 9H-pyrrolo[1,2-a]indol-9-ones are stronger quenchers and bind to human serum albumin with the higher affinity than isomeric indeno[2,1-b]pyrrol-8-ones. The influence of molecular structure on the binding aspects has been investigated. - Highlights: • The interactions between isomeric derivatives and HSA have been investigated. • Results reveal that 9H-pyrrolo[1,2-a]indol-9-ones are stronger quenchers for HSA. • Hydrogen bonds and van der Waals forces play major role in the binding process. • The influence of molecular structure on the binding aspects has been investigated. • The binding study was also modeled by molecular docking.

Investigation of the interaction between isomeric derivatives and human serum albumin by fluorescence spectroscopy and molecular modeling

International Nuclear Information System (INIS)

Wang, Ruiyong; Dou, Huanjing; Yin, Yujing; Xie, Yuanzhe; Sun, Li; Liu, Chunmei; Dong, Jingjing; Huang, Gang; Zhu, Yanyan; Song, Chuanjun; Chang, Junbiao

2014-01-01

In this paper, we have synthesized 9H-pyrrolo[1,2-a]indol-9-ones and the isomeric indeno[2,1-b]pyrrol-8-ones. The interactions of human serum albumin with series of isomeric derivatives have been studied by spectrophotometric methods. Results show the intrinsic fluorescence is quenched by the derivatives with a static quenching procedure. The thermodynamics parameters indicate that van der Waals forces and hydrogen bonds play a major role in the interactions. The results of synchronous fluorescence spectra demonstrate that the microenvironments of Trp residue of human serum albumin are disturbed by most derivatives. Thermodynamic results showed that the 9H-pyrrolo[1,2-a]indol-9-ones are stronger quenchers and bind to human serum albumin with the higher affinity than isomeric indeno[2,1-b]pyrrol-8-ones. The influence of molecular structure on the binding aspects has been investigated. - Highlights: • The interactions between isomeric derivatives and HSA have been investigated. • Results reveal that 9H-pyrrolo[1,2-a]indol-9-ones are stronger quenchers for HSA. • Hydrogen bonds and van der Waals forces play major role in the binding process. • The influence of molecular structure on the binding aspects has been investigated. • The binding study was also modeled by molecular docking

Model-Based approaches to Human-Automation Systems Design

DEFF Research Database (Denmark)

Jamieson, Greg A.; Andersson, Jonas; Bisantz, Ann

2012-01-01

Human-automation interaction in complex systems is common, yet design for this interaction is often conducted without explicit consideration of the role of the human operator. Fortunately, there are a number of modeling frameworks proposed for supporting this design activity. However...... (and reportedly one or two critics) can engage one another on several agreed questions about such frameworks. The goal is to aid non-aligned practitioners in choosing between alternative frameworks for their human-automation interaction design challenges....

Personality and social skills in human-dog interaction

DEFF Research Database (Denmark)

Meyer, Iben Helene Coakley

developing a social tool set that makes it very successful in interacting and communicating with humans. Human evolution has similarly resulted in the development of complex social cognition in humans. This enables humans to form bonded relationships, besides pair-bonding, and it seems that humans are also...... of this thesis was to attain a better understanding of some of the factors related to the inter-action between humans and dogs. This aim was addressed by focusing on dog personality and hu-man social skills in relation to human-dog interaction. Two studies investigated dog personality and how it a) affects...... the relationship with the owner, and b) is affected by human breeding goals. Two studies investigated how human social skills affect the communication and interaction between hu-man and dog. As part of these studies it was also investigated how experience with dogs interacts with human social skills, perception...

Learning to Detect Human-Object Interactions

KAUST Repository

Chao, Yu-Wei; Liu, Yunfan; Liu, Xieyang; Zeng, Huayi; Deng, Jia

2017-01-01

In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

Learning to Detect Human-Object Interactions

KAUST Repository

Chao, Yu-Wei

2017-02-17

In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

Peer-to-Peer Human-Robot Interaction for Space Exploration

Science.gov (United States)

Fong, Terrence; Nourbakhsh, Illah

2004-01-01

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.

Quantifying Trust, Distrust, and Suspicion in Human-System Interactions

Science.gov (United States)

2015-10-26

communication, psychology , human factors, management, marketing, information technology, and brain/neurology. We first developed a generic model of state...task classification based upon topographic EEG data. Biological Psychology , 1995. 40: p. 239-250. 5. Gevins, A., et al., High-Resolution EEG...Interaction (submitted), 2013. 15. Pouliota, P., et al., Nonlinear hemodynamic responses in human epilepsy : A multimodal analysis with fNIRS-EEG and fMRI

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

Science.gov (United States)

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas

Science.gov (United States)

Background/Question/Methods In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment interactions. ...

Modeling object pursuit for 3D interactive tasks in virtual reality

NARCIS (Netherlands)

Liu, L.; Liere, van R.

2011-01-01

Models of interaction tasks are quantitative descriptions of relationships between human temporal performance and the spatial characteristics of the interactive tasks. Examples include Fitts' law for modeling the pointing task and Accot and Zhai's steering law for the path steering task, etc. Models

The Human-Robot Interaction Operating System

Science.gov (United States)

Fong, Terrence; Kunz, Clayton; Hiatt, Laura M.; Bugajska, Magda

2006-01-01

In order for humans and robots to work effectively together, they need to be able to converse about abilities, goals and achievements. Thus, we are developing an interaction infrastructure called the "Human-Robot Interaction Operating System" (HRI/OS). The HRI/OS provides a structured software framework for building human-robot teams, supports a variety of user interfaces, enables humans and robots to engage in task-oriented dialogue, and facilitates integration of robots through an extensible API.

Design Science in Human-Computer Interaction: A Model and Three Examples

Science.gov (United States)

Prestopnik, Nathan R.

2013-01-01

Humanity has entered an era where computing technology is virtually ubiquitous. From websites and mobile devices to computers embedded in appliances on our kitchen counters and automobiles parked in our driveways, information and communication technologies (ICTs) and IT artifacts are fundamentally changing the ways we interact with our world.…

A direct pedestrian-structure interaction model to characterize the human induced vibrations on slender footbridges

Directory of Open Access Journals (Sweden)

Jiménez-Alonso, J. F.

2014-12-01

Full Text Available Although the scientific community had knowledge of the human induced vibration problems in structures since the end of the 19th century, it was not until the occurrence of the vibration phenomenon happened in the Millennium Bridge (London, 2000 that the importance of the problem revealed and a higher level of attention devoted. Despite the large advances achieved in the determination of the human-structure interaction force, one of the main deficiencies of the existing models is the exclusion of the effect of changes in the footbridge dynamic properties due to the presence of pedestrians. In this paper, the formulation of a human-structure interaction model, addresses these limitations, is carried out and its reliability is verified from previously published experimental results.Aunque la comunidad científica tenía conocimiento de los problemas vibratorios inducidos por peatones en estructuras desde finales del siglo xix, no fue hasta la ocurrencia de los eventos vibratorios acontecidos en la pasarela del Milenio (Londres, 2000, cuando la importancia del problema se puso de manifiesto y se le comenzó a dedicar un mayor nivel de atención. A pesar de los grandes avances alcanzados en la caracterización de la fuerza de interacción peatón-estructura una de las principales deficiencias de los modelos existentes es la exclusión del cambio en las propiedades dinámicas de la pasarela por la presencia de peatones. En este artículo, se presenta la formulación de un modelo de interacción peatón-estructura que intenta dar respuesta a dichas limitaciones, y su validación a partir de resultados experimentales previamente publicados por otros autores.

Human-computer interaction and management information systems

CERN Document Server

Galletta, Dennis F

2014-01-01

""Human-Computer Interaction and Management Information Systems: Applications"" offers state-of-the-art research by a distinguished set of authors who span the MIS and HCI fields. The original chapters provide authoritative commentaries and in-depth descriptions of research programs that will guide 21st century scholars, graduate students, and industry professionals. Human-Computer Interaction (or Human Factors) in MIS is concerned with the ways humans interact with information, technologies, and tasks, especially in business, managerial, organizational, and cultural contexts. It is distinctiv

A Nonlinear Model for Gene-Based Gene-Environment Interaction

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Jian Sa

2016-06-01

Full Text Available A vast amount of literature has confirmed the role of gene-environment (G×E interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Host-pathogen interactions between the human innate immune system and Candida albicans—understanding and modeling defense and evasion strategies

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Dühring, Sybille; Germerodt, Sebastian; Skerka, Christine; Zipfel, Peter F.; Dandekar, Thomas; Schuster, Stefan

2015-01-01

The diploid, polymorphic yeast Candida albicans is one of the most important human pathogenic fungi. C. albicans can grow, proliferate and coexist as a commensal on or within the human host for a long time. However, alterations in the host environment can render C. albicans virulent. In this review, we describe the immunological cross-talk between C. albicans and the human innate immune system. We give an overview in form of pairs of human defense strategies including immunological mechanisms as well as general stressors such as nutrient limitation, pH, fever etc. and the corresponding fungal response and evasion mechanisms. Furthermore, Computational Systems Biology approaches to model and investigate these complex interactions are highlighted with a special focus on game-theoretical methods and agent-based models. An outlook on interesting questions to be tackled by Systems Biology regarding entangled defense and evasion mechanisms is given. PMID:26175718

The role of gut microbiota in health and disease: In vitro modeling of host-microbe interactions at the aerobe-anaerobe interphase of the human gut.

Science.gov (United States)

von Martels, Julius Z H; Sadaghian Sadabad, Mehdi; Bourgonje, Arno R; Blokzijl, Tjasso; Dijkstra, Gerard; Faber, Klaas Nico; Harmsen, Hermie J M

2017-04-01

The microbiota of the gut has many crucial functions in human health. Dysbiosis of the microbiota has been correlated to a large and still increasing number of diseases. Recent studies have mostly focused on analyzing the associations between disease and an aberrant microbiota composition. Functional studies using (in vitro) gut models are required to investigate the precise interactions that occur between specific bacteria (or bacterial mixtures) and gut epithelial cells. As most gut bacteria are obligate or facultative anaerobes, studying their effect on oxygen-requiring human gut epithelial cells is technically challenging. Still, several (anaerobic) bacterial-epithelial co-culture systems have recently been developed that mimic host-microbe interactions occurring in the human gut, including 1) the Transwell "apical anaerobic model of the intestinal epithelial barrier", 2) the Host-Microbiota Interaction (HMI) module, 3) the "Human oxygen-Bacteria anaerobic" (HoxBan) system, 4) the human gut-on-a-chip and 5) the HuMiX model. This review discusses the role of gut microbiota in health and disease and gives an overview of the characteristics and applications of these novel host-microbe co-culture systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Human Work Interaction Design. Work Analysis and HCI

DEFF Research Database (Denmark)

Paasch, Kasper

2013-01-01

. The papers reflect many different areas and address many complex and diverse work domains, ranging from medical user interfaces, work and speech interactions at elderly care facilities, greenhouse climate control, navigating through large oil industry engineering models, crisis management, library usability......This book constitutes the thoroughly refereed post-conference proceedings of the Third IFIP WG 13.6 Working Conference on Human Work Interaction Design, HWID 2012, held in Copenhagen, Denmark, in December 2012. The 16 revised papers presented were carefully selected for inclusion in this volume...

Effects of interactions between humans and domesticated animals

NARCIS (Netherlands)

Bokkers, E.A.M.

2006-01-01

Humans have many kinds of relationships with domesticated animals. To maintain relationships interactions are needed. Interactions with animals may be beneficial for humans but may also be risky. Scientific literature on effects of human¿animal relationships and interactions in a workplace,

Human Capital Variables and Economic Growth in Nigeria: An Interactive Effect

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Adenike Mosunmola Osoba

2017-05-01

Full Text Available Various studies have focused on the relationship between human capital and economic growth all over the world. However, there is still a missing gap on the joint influence of human capital investment components on economic growth particularly in Nigeria. This study therefore examines the interactive effects of the relationship between human capital investment components and economic growth in Nigeria for the period of 1986 – 2014. The study employed secondary annual data on education expenditure, health expenditure, real gross domestic product and gross capital formation obtained from the Central Bank Statistical bulletin, 2014. The data were analyzed using Fully Modified Ordinary Least Squares (FMOLS technique. The results of the study showed that there was positive and significant relationship between the interactive effects of human capital components and growth in Nigeria. The study concluded that the interactive effect of the human capital variables was also in conformity with the theoretical proposition that increase in human capital will enhance growth as stipulated in the modified Solow growth model by Mankiw, Romer & Weil (1992.

Modeling human diseases: an education in interactions and interdisciplinary approaches

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Leonard Zon

2016-06-01

Full Text Available Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic.

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents.

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Collins, Michael G; Juvina, Ion; Gluck, Kevin A

2016-01-01

When playing games of strategic interaction, such as iterated Prisoner's Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game's optimal outcome) as well as transfer of learning between games (e.g., a game's optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model's a priori predictions of human learning and transfer in 16 different conditions. The model's predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair.

Multimodal interaction for human-robot teams

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Burke, Dustin; Schurr, Nathan; Ayers, Jeanine; Rousseau, Jeff; Fertitta, John; Carlin, Alan; Dumond, Danielle

2013-05-01

Unmanned ground vehicles have the potential for supporting small dismounted teams in mapping facilities, maintaining security in cleared buildings, and extending the team's reconnaissance and persistent surveillance capability. In order for such autonomous systems to integrate with the team, we must move beyond current interaction methods using heads-down teleoperation which require intensive human attention and affect the human operator's ability to maintain local situational awareness and ensure their own safety. This paper focuses on the design, development and demonstration of a multimodal interaction system that incorporates naturalistic human gestures, voice commands, and a tablet interface. By providing multiple, partially redundant interaction modes, our system degrades gracefully in complex environments and enables the human operator to robustly select the most suitable interaction method given the situational demands. For instance, the human can silently use arm and hand gestures for commanding a team of robots when it is important to maintain stealth. The tablet interface provides an overhead situational map allowing waypoint-based navigation for multiple ground robots in beyond-line-of-sight conditions. Using lightweight, wearable motion sensing hardware either worn comfortably beneath the operator's clothing or integrated within their uniform, our non-vision-based approach enables an accurate, continuous gesture recognition capability without line-of-sight constraints. To reduce the training necessary to operate the system, we designed the interactions around familiar arm and hand gestures.

[Affective behavioural responses by dogs to tactile human-dog interactions].

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Kuhne, Franziska; Hössler, Johanna C; Struwe, Rainer

2012-01-01

The communication of dogs is based on complex, subtle body postures and facial expressions. Some social interaction between dogs includes physical contact. Humans generally use both verbal and tactile signals to communicate with dogs. Hence, interaction between humans and dogs might lead to conflicts because the behavioural responses of dogs to human-dog interaction may be misinterpreted and wrongly assessed. The behavioural responses of dogs to tactile human-dog interactions and human gestures are the focus of this study. The participating dogs (n = 47) were privately owned pets.They were of varying breed and gender.The test consisted of nine randomised test sequences (e. g. petting the dog's head or chest). A test sequence was performed for a period of 30 seconds. The inter-trial interval was set at 60 seconds and the test-retest interval was set at 10 minutes. The frequency and duration of the dogs'behavioural responses were recorded using INTERACT. To examine the behavioural responses of the dogs, a two-way analysis of variance within the linear mixed models procedure of IBM SPSS Statistics 19 was conducted. A significant influence of the test-sequenc order on the dogs' behaviour could be analysed for appeasement gestures (F8,137 = 2.42; p = 0.018), redirected behaviour (F8,161 = 6.31; p = 0.012) and socio-positive behaviour (F8,148 = 6.28; p = 0.012). The behavioural responses of the dogs, which were considered as displacement activities (F8,109 = 2.5; p = 0.014) differed significantly among the test sequences. The response of the dogs, measured as gestures of appeasement, redirected behaviours, and displacement activities, was most obvious during petting around the head and near the paws.The results of this study conspicuously indicate that dogs respond to tactile human-dog interactions with gestures of appeasement and displacement activities. Redirected behaviours, socio-positive behaviours as well displacement activities are behavioural responses which dogs

Synergistic interactions between Drosophila orthologues of genes spanned by de novo human CNVs support multiple-hit models of autism.

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Grice, Stuart J; Liu, Ji-Long; Webber, Caleb

2015-03-01

Autism spectrum disorders (ASDs) are highly heritable and characterised by deficits in social interaction and communication, as well as restricted and repetitive behaviours. Although a number of highly penetrant ASD gene variants have been identified, there is growing evidence to support a causal role for combinatorial effects arising from the contributions of multiple loci. By examining synaptic and circadian neurological phenotypes resulting from the dosage variants of unique human:fly orthologues in Drosophila, we observe numerous synergistic interactions between pairs of informatically-identified candidate genes whose orthologues are jointly affected by large de novo copy number variants (CNVs). These CNVs were found in the genomes of individuals with autism, including a patient carrying a 22q11.2 deletion. We first demonstrate that dosage alterations of the unique Drosophila orthologues of candidate genes from de novo CNVs that harbour only a single candidate gene display neurological defects similar to those previously reported in Drosophila models of ASD-associated variants. We then considered pairwise dosage changes within the set of orthologues of candidate genes that were affected by the same single human de novo CNV. For three of four CNVs with complete orthologous relationships, we observed significant synergistic effects following the simultaneous dosage change of gene pairs drawn from a single CNV. The phenotypic variation observed at the Drosophila synapse that results from these interacting genetic variants supports a concordant phenotypic outcome across all interacting gene pairs following the direction of human gene copy number change. We observe both specificity and transitivity between interactors, both within and between CNV candidate gene sets, supporting shared and distinct genetic aetiologies. We then show that different interactions affect divergent synaptic processes, demonstrating distinct molecular aetiologies. Our study illustrates

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

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Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are

Quantitative heartbeat coupling measures in human-horse interaction.

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Lanata, Antonio; Guidi, Andrea; Valenza, Gaetano; Baragli, Paolo; Scilingo, Enzo Pasquale

2016-08-01

We present a study focused on a quantitative estimation of a human-horse dynamic interaction. A set of measures based on magnitude and phase coupling between heartbeat dynamics of both humans and horses in three different conditions is reported: no interaction, visual/olfactory interaction and grooming. Specifically, Magnitude Squared Coherence (MSC), Mean Phase Coherence (MPC) and Dynamic Time Warping (DTW) have been used as estimators of the amount of coupling between human and horse through the analysis of their heart rate variability (HRV) time series in a group of eleven human subjects, and one horse. The rationale behind this study is that the interaction of two complex biological systems go towards a coupling process whose dynamical evolution is modulated by the kind and time duration of the interaction itself. We achieved a congruent and consistent statistical significant difference for all of the three indices. Moreover, a Nearest Mean Classifier was able to recognize the three classes of interaction with an accuracy greater than 70%. Although preliminary, these encouraging results allow a discrimination of three distinct phases in a real human-animal interaction opening to the characterization of the empirically proven relationship between human and horse.

Human-Robot Interaction

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Sandor, Aniko; Cross, E. Vincent, II; Chang, Mai Lee

2015-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces affect the human's ability to perform tasks effectively and efficiently when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. For efficient and effective remote navigation of a rover, a human operator needs to be aware of the robot's environment. However, during teleoperation, operators may get information about the environment only through a robot's front-mounted camera causing a keyhole effect. The keyhole effect reduces situation awareness which may manifest in navigation issues such as higher number of collisions, missing critical aspects of the environment, or reduced speed. One way to compensate for the keyhole effect and the ambiguities operators experience when they teleoperate a robot is adding multiple cameras and including the robot chassis in the camera view. Augmented reality, such as overlays, can also enhance the way a person sees objects in the environment or in camera views by making them more visible. Scenes can be augmented with integrated telemetry, procedures, or map information. Furthermore, the addition of an exocentric (i.e., third-person) field of view from a camera placed in the robot's environment may provide operators with the additional information needed to gain spatial awareness of the robot. Two research studies investigated possible mitigation approaches to address the keyhole effect: 1) combining the inclusion of the robot chassis in the camera view with augmented reality overlays, and 2) modifying the camera

Temporal stability in human interaction networks

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Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

2017-11-01

This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

The Representation of Human-Environment Interactions in Land Change Research and Modelling

NARCIS (Netherlands)

Verburg, P.H.; Manfredo, M.J.; Vaske, J.J.; Rechkemmer, A.; Duke, E.A.

2014-01-01

Land change is the result of multiple human-environment interactions operating across different scales. Land change research needs to account for processes ranging from global trade of food and energy to the local management of land resources at farm and landscape level. Land change has a pronounced

Safe physical human robot interaction- past, present and future

International Nuclear Information System (INIS)

Pervez, Aslam; Ryu, Jeha

2008-01-01

When a robot physically interacts with a human user, the requirements should be drastically changed. The most important requirement is the safety of the human user in the sense that robot should not harm the human in any situation. During the last few years, research has been focused on various aspects of safe physical human robot interaction. This paper provides a review of the work on safe physical interaction of robotic systems sharing their workspace with human users (especially elderly people). Three distinct areas of research are identified: interaction safety assessment, interaction safety through design, and interaction safety through planning and control. The paper then highlights the current challenges and available technologies and points out future research directions for realization of a safe and dependable robotic system for human users

Effects of interactions between humans and domesticated animals

OpenAIRE

Bokkers, E.A.M.

2006-01-01

Humans have many kinds of relationships with domesticated animals. To maintain relationships interactions are needed. Interactions with animals may be beneficial for humans but may also be risky. Scientific literature on effects of human¿animal relationships and interactions in a workplace, health-care and residential context has been reviewed to develop ideas about the effects farm animals can have on humans. Although there are quite a few studies, the variety of methods, the complexity of t...

Fundamentals of human-computer interaction

CERN Document Server

Monk, Andrew F

1985-01-01

Fundamentals of Human-Computer Interaction aims to sensitize the systems designer to the problems faced by the user of an interactive system. The book grew out of a course entitled """"The User Interface: Human Factors for Computer-based Systems"""" which has been run annually at the University of York since 1981. This course has been attended primarily by systems managers from the computer industry. The book is organized into three parts. Part One focuses on the user as processor of information with studies on visual perception; extracting information from printed and electronically presented

Socially intelligent robots: dimensions of human-robot interaction.

Science.gov (United States)

Dautenhahn, Kerstin

2007-04-29

Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human-robot interaction (HRI) poses many challenges regarding the nature of interactivity and 'social behaviour' in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a 'robotiquette') that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human-child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human-robot experiments. The paper concludes by examining different paradigms regarding 'social relationships' of robots and people interacting with them.

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome.

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Jens Christian Claussen

2017-06-01

Full Text Available The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.

User localization during human-robot interaction.

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Alonso-Martín, F; Gorostiza, Javi F; Malfaz, María; Salichs, Miguel A

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented.

Human pericyte-endothelial cell interactions in co-culture models mimicking the diabetic retinal microvascular environment.

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Tarallo, Sonia; Beltramo, Elena; Berrone, Elena; Porta, Massimo

2012-12-01

Pericytes regulate vascular tone, perfusion pressure and endothelial cell (EC) proliferation in capillaries. Thiamine and benfotiamine counteract high glucose-induced damage in vascular cells. We standardized two human retinal pericyte (HRP)/EC co-culture models to mimic the diabetic retinal microvascular environment. We aimed at evaluating the interactions between co-cultured HRP and EC in terms of proliferation/apoptosis and the possible protective role of thiamine and benfotiamine against high glucose-induced damage. EC and HRP were co-cultured in physiological glucose and stable or intermittent high glucose, with or without thiamine/benfotiamine. No-contact model: EC were plated on a porous membrane suspended into the medium and HRP on the bottom of the same well. Cell-to-cell contact model: EC and HRP were plated on the opposite sides of the same membrane. Proliferation (cell counts and DNA synthesis), apoptosis and tubule formation in Matrigel were assessed. In the no-contact model, stable high glucose reduced proliferation of co-cultured EC/HRP and EC alone and increased co-cultured EC/HRP apoptosis. In the contact model, both stable and intermittent high glucose reduced co-cultured EC/HRP proliferation and increased apoptosis. Stable high glucose had no effects on HRP in separate cultures. Both EC and HRP proliferated better when co-cultured. Thiamine and benfotiamine reversed high glucose-induced damage in all cases. HRP are sensitive to soluble factors released by EC when cultured in high glucose conditions, as suggested by conditioned media assays. In the Matrigel models, addition of thiamine and benfotiamine re-established the high glucose-damaged interactions between EC/HRP and stabilized microtubules.

TOPICAL REVIEW: Modelling the interaction of electromagnetic fields (10 MHz 10 GHz) with the human body: methods and applications

Science.gov (United States)

Hand, J. W.

2008-08-01

Numerical modelling of the interaction between electromagnetic fields (EMFs) and the dielectrically inhomogeneous human body provides a unique way of assessing the resulting spatial distributions of internal electric fields, currents and rate of energy deposition. Knowledge of these parameters is of importance in understanding such interactions and is a prerequisite when assessing EMF exposure or when assessing or optimizing therapeutic or diagnostic medical applications that employ EMFs. In this review, computational methods that provide this information through full time-dependent solutions of Maxwell's equations are summarized briefly. This is followed by an overview of safety- and medical-related applications where modelling has contributed significantly to development and understanding of the techniques involved. In particular, applications in the areas of mobile communications, magnetic resonance imaging, hyperthermal therapy and microwave radiometry are highlighted. Finally, examples of modelling the potentially new medical applications of recent technologies such as ultra-wideband microwaves are discussed.

Motor contagion during human-human and human-robot interaction.

Directory of Open Access Journals (Sweden)

Ambra Bisio

Full Text Available Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot. After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

Motor contagion during human-human and human-robot interaction.

Science.gov (United States)

Bisio, Ambra; Sciutti, Alessandra; Nori, Francesco; Metta, Giorgio; Fadiga, Luciano; Sandini, Giulio; Pozzo, Thierry

2014-01-01

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

Language evolution and human-computer interaction

Science.gov (United States)

Grudin, Jonathan; Norman, Donald A.

1991-01-01

Many of the issues that confront designers of interactive computer systems also appear in natural language evolution. Natural languages and human-computer interfaces share as their primary mission the support of extended 'dialogues' between responsive entities. Because in each case one participant is a human being, some of the pressures operating on natural languages, causing them to evolve in order to better support such dialogue, also operate on human-computer 'languages' or interfaces. This does not necessarily push interfaces in the direction of natural language - since one entity in this dialogue is not a human, this is not to be expected. Nonetheless, by discerning where the pressures that guide natural language evolution also appear in human-computer interaction, we can contribute to the design of computer systems and obtain a new perspective on natural languages.

Themes in human work interaction design

DEFF Research Database (Denmark)

Ørngreen, Rikke; Mark Pejtersen, Annelise; Clemmensen, Torkil

2008-01-01

Design (name HWID) through the last two and half years since the commencement of this Working Group. The paper thus provides an introduction to the theory and empirical evidence that lie behind the combination of empirical work studies and interaction design. It also recommends key topics for future......Abstract. This paper raises themes that are seen as some of the challenges facing the emerging practice and research field of Human Work Interaction Design. The paper has its offset in the discussions and writings that have been dominant within the IFIP Working Group on Human Work Interaction...

Intrinsically motivated reinforcement learning for human-robot interaction in the real-world.

Science.gov (United States)

Qureshi, Ahmed Hussain; Nakamura, Yutaka; Yoshikawa, Yuichiro; Ishiguro, Hiroshi

2018-03-26

For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learning framework in which an agent gets the intrinsic motivation-based rewards through the action-conditional predictive model. By using the proposed method, the robot learned the social skills from the human-robot interaction experiences gathered in the real uncontrolled environments. The results indicate that the robot not only acquired human-like social skills but also took more human-like decisions, on a test dataset, than a robot which received direct rewards for the task achievement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Eyeblink Synchrony in Multimodal Human-Android Interaction.

Science.gov (United States)

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-12-23

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human's attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners' eyeblinks were entrained to android speakers' eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android's hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions.

Quantifying human-environment interactions using videography in the context of infectious disease transmission.

Science.gov (United States)

Julian, Timothy R; Bustos, Carla; Kwong, Laura H; Badilla, Alejandro D; Lee, Julia; Bischel, Heather N; Canales, Robert A

2018-05-08

Quantitative data on human-environment interactions are needed to fully understand infectious disease transmission processes and conduct accurate risk assessments. Interaction events occur during an individual's movement through, and contact with, the environment, and can be quantified using diverse methodologies. Methods that utilize videography, coupled with specialized software, can provide a permanent record of events, collect detailed interactions in high resolution, be reviewed for accuracy, capture events difficult to observe in real-time, and gather multiple concurrent phenomena. In the accompanying video, the use of specialized software to capture humanenvironment interactions for human exposure and disease transmission is highlighted. Use of videography, combined with specialized software, allows for the collection of accurate quantitative representations of human-environment interactions in high resolution. Two specialized programs include the Virtual Timing Device for the Personal Computer, which collects sequential microlevel activity time series of contact events and interactions, and LiveTrak, which is optimized to facilitate annotation of events in real-time. Opportunities to annotate behaviors at high resolution using these tools are promising, permitting detailed records that can be summarized to gain information on infectious disease transmission and incorporated into more complex models of human exposure and risk.

Proxemics in Human-Computer Interaction

OpenAIRE

Greenberg, Saul; Honbaek, Kasper; Quigley, Aaron; Reiterer, Harald; Rädle, Roman

2014-01-01

In 1966, anthropologist Edward Hall coined the term "proxemics." Proxemics is an area of study that identifies the culturally dependent ways in which people use interpersonal distance to understand and mediate their interactions with others. Recent research has demonstrated the use of proxemics in human-computer interaction (HCI) for supporting users' explicit and implicit interactions in a range of uses, including remote office collaboration, home entertainment, and games. One promise of pro...

Situated dialog in speech-based human-computer interaction

CERN Document Server

Raux, Antoine; Lane, Ian; Misu, Teruhisa

2016-01-01

This book provides a survey of the state-of-the-art in the practical implementation of Spoken Dialog Systems for applications in everyday settings. It includes contributions on key topics in situated dialog interaction from a number of leading researchers and offers a broad spectrum of perspectives on research and development in the area. In particular, it presents applications in robotics, knowledge access and communication and covers the following topics: dialog for interacting with robots; language understanding and generation; dialog architectures and modeling; core technologies; and the analysis of human discourse and interaction. The contributions are adapted and expanded contributions from the 2014 International Workshop on Spoken Dialog Systems (IWSDS 2014), where researchers and developers from industry and academia alike met to discuss and compare their implementation experiences, analyses and empirical findings.

Human-Robot Interaction: Status and Challenges.

Science.gov (United States)

Sheridan, Thomas B

2016-06-01

The current status of human-robot interaction (HRI) is reviewed, and key current research challenges for the human factors community are described. Robots have evolved from continuous human-controlled master-slave servomechanisms for handling nuclear waste to a broad range of robots incorporating artificial intelligence for many applications and under human supervisory control. This mini-review describes HRI developments in four application areas and what are the challenges for human factors research. In addition to a plethora of research papers, evidence of success is manifest in live demonstrations of robot capability under various forms of human control. HRI is a rapidly evolving field. Specialized robots under human teleoperation have proven successful in hazardous environments and medical application, as have specialized telerobots under human supervisory control for space and repetitive industrial tasks. Research in areas of self-driving cars, intimate collaboration with humans in manipulation tasks, human control of humanoid robots for hazardous environments, and social interaction with robots is at initial stages. The efficacy of humanoid general-purpose robots has yet to be proven. HRI is now applied in almost all robot tasks, including manufacturing, space, aviation, undersea, surgery, rehabilitation, agriculture, education, package fetch and delivery, policing, and military operations. © 2016, Human Factors and Ergonomics Society.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

OpenAIRE

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive cha...

Interaction in Spoken Word Recognition Models: Feedback Helps

Science.gov (United States)

Magnuson, James S.; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D.

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis. PMID:29666593

Interaction in Spoken Word Recognition Models: Feedback Helps.

Science.gov (United States)

Magnuson, James S; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Interaction in Spoken Word Recognition Models: Feedback Helps

Directory of Open Access Journals (Sweden)

James S. Magnuson

2018-04-01

Full Text Available Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Why E-Business Must Evolve beyond Market Orientation: Applying Human Interaction Models to Computer-Mediated Corporate Communications.

Science.gov (United States)

Johnston, Kevin McCullough

2001-01-01

Considers the design of corporate communications for electronic business and discusses the increasing importance of corporate interaction as companies work in virtual environments. Compares sociological and psychological theories of human interaction and relationship formation with organizational interaction theories of corporate relationship…

Human-Bat Interactions in Rural West Africa.

Science.gov (United States)

Anti, Priscilla; Owusu, Michael; Agbenyega, Olivia; Annan, Augustina; Badu, Ebenezer Kofi; Nkrumah, Evans Ewald; Tschapka, Marco; Oppong, Samuel; Adu-Sarkodie, Yaw; Drosten, Christian

2015-08-01

Because some bats host viruses with zoonotic potential, we investigated human-bat interactions in rural Ghana during 2011-2012. Nearly half (46.6%) of respondents regularly visited bat caves; 37.4% had been bitten, scratched, or exposed to bat urine; and 45.6% ate bat meat. Human-bat interactions in rural Ghana are frequent and diverse.

A Budyko-type Model for Human Water Consumption

Science.gov (United States)

Lei, X.; Zhao, J.; Wang, D.; Sivapalan, M.

2017-12-01

With the expansion of human water footprint, water crisis is no longer only a conflict or competition for water between different economic sectors, but also increasingly between human and the environment. In order to describe the emergent dynamics and patterns of the interaction, a theoretical framework that encapsulates the physical and societal controls impacting human water consumption is needed. In traditional hydrology, Budyko-type models are simple but efficient descriptions of vegetation-mediated hydrologic cycle in catchments, i.e., the partitioning of mean annual precipitation into runoff and evapotranspiration. Plant water consumption plays a crucial role in the process. Hypothesized similarities between human-water and vegetation-water interactions, including water demand, constraints and system functioning, give the idea of corresponding Budyko-type framework for human water consumption at the catchment scale. Analogous to variables of Budyko-type models for hydrologic cycle, water demand, water consumption, environmental water use and available water are corresponding to potential evaporation, actual evaporation, runoff and precipitation respectively. Human water consumption data, economic and hydro-meteorological data for 51 human-impacted catchments and 10 major river basins in China are assembled to look for the existence of a Budyko-type relationship for human water consumption, and to seek explanations for the spread in the observed relationship. Guided by this, a Budyko-type analytical model is derived based on application of an optimality principle, that of maximum water benefit. The model derived has the same functional form and mathematical features as those that apply for the original Budyko model. Parameters of the new Budyko-type model for human consumption are linked to economic and social factors. The results of this paper suggest that the functioning of both social and hydrologic subsystems within catchment systems can be explored within

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

Science.gov (United States)

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

Science.gov (United States)

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

The Evolution of Integrated Assessment and Emerging Challenges in the Assessment of Human and Natural System Interactions

Science.gov (United States)

Clarke, L.

2017-12-01

Integrated assessment (IA) modeling and research has a long history, spanning over 30 years since its inception and addressing a wide range of contemporary issues along the way. Over the last decade, IA modeling and research has emerged as one of the primary analytical methods for understanding the complex interactions between human and natural systems, from the interactions between energy, water, and land/food systems to the interplay between health, climate, and air pollution. IA modeling and research is particularly well-suited for the analysis of these interactions because it is a discipline that strives to integrate representations of multiple systems into consistent computational platforms or frameworks. In doing so, it explicitly confronts the many tradeoffs that are frequently necessary to manage complexity and computational cost while still representing the most important interactions and overall, coupled system behavior. This talk explores the history of IA modeling and research as a means to better understand its role in the assessment of contemporary issues at the confluence of human and natural systems. It traces the evolution of IA modeling and research from initial exploration of long-term emissions pathways, to the role of technology in the global evolution of the energy system, to the key linkages between land and energy systems and, more recently, the linkages with water, air pollution, and other key systems and issues. It discusses the advances in modeling that have emerged over this evolution and the biggest challenges that still present themselves as we strive to better understand the most important interactions between human and natural systems and the implications of these interactions for human welfare and decision making.

Quantifying human-environment interactions using videography in the context of infectious disease transmission

Directory of Open Access Journals (Sweden)

Timothy R. Julian

2018-05-01

Full Text Available Quantitative data on human-environment interactions are needed to fully understand infectious disease transmission processes and conduct accurate risk assessments. Interaction events occur during an individual’s movement through, and contact with, the environment, and can be quantified using diverse methodologies. Methods that utilize videography, coupled with specialized software, can provide a permanent record of events, collect detailed interactions in high resolution, be reviewed for accuracy, capture events difficult to observe in real-time, and gather multiple concurrent phenomena. In the accompanying video, the use of specialized software to capture humanenvironment interactions for human exposure and disease transmission is highlighted. Use of videography, combined with specialized software, allows for the collection of accurate quantitative representations of human-environment interactions in high resolution. Two specialized programs include the Virtual Timing Device for the Personal Computer, which collects sequential microlevel activity time series of contact events and interactions, and LiveTrak, which is optimized to facilitate annotation of events in real-time. Opportunities to annotate behaviors at high resolution using these tools are promising, permitting detailed records that can be summarized to gain information on infectious disease transmission and incorporated into more complex models of human exposure and risk.

Pantomimic gestures for human-robot interaction

CSIR Research Space (South Africa)

Burke, Michael G

2015-10-01

Full Text Available -1 IEEE TRANSACTIONS ON ROBOTICS 1 Pantomimic Gestures for Human-Robot Interaction Michael Burke, Student Member, IEEE, and Joan Lasenby Abstract This work introduces a pantomimic gesture interface, which classifies human hand gestures using...

Human Work Interaction Design

DEFF Research Database (Denmark)

Lopes, Arminda; Ørngreen, Rikke

This book constitutes the thoroughly refereed post-conference proceedings of the Third IFIP WG 13.6 Working Conference on Human Work Interaction Design, HWID 2012, held in Copenhagen, Denmark, in December 2012. The 16 revised papers presented were carefully selected for inclusion in this volume...

Control of a Robot Dancer for Enhancing Haptic Human-Robot Interaction in Waltz.

Science.gov (United States)

Hongbo Wang; Kosuge, K

2012-01-01

Haptic interaction between a human leader and a robot follower in waltz is studied in this paper. An inverted pendulum model is used to approximate the human's body dynamics. With the feedbacks from the force sensor and laser range finders, the robot is able to estimate the human leader's state by using an extended Kalman filter (EKF). To reduce interaction force, two robot controllers, namely, admittance with virtual force controller, and inverted pendulum controller, are proposed and evaluated in experiments. The former controller failed the experiment; reasons for the failure are explained. At the same time, the use of the latter controller is validated by experiment results.

A componential model of human interaction with graphs: 1. Linear regression modeling

Science.gov (United States)

Gillan, Douglas J.; Lewis, Robert

1994-01-01

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Interactive Exploration Robots: Human-Robotic Collaboration and Interactions

Science.gov (United States)

Fong, Terry

2017-01-01

For decades, NASA has employed different operational approaches for human and robotic missions. Human spaceflight missions to the Moon and in low Earth orbit have relied upon near-continuous communication with minimal time delays. During these missions, astronauts and mission control communicate interactively to perform tasks and resolve problems in real-time. In contrast, deep-space robotic missions are designed for operations in the presence of significant communication delay - from tens of minutes to hours. Consequently, robotic missions typically employ meticulously scripted and validated command sequences that are intermittently uplinked to the robot for independent execution over long periods. Over the next few years, however, we will see increasing use of robots that blend these two operational approaches. These interactive exploration robots will be remotely operated by humans on Earth or from a spacecraft. These robots will be used to support astronauts on the International Space Station (ISS), to conduct new missions to the Moon, and potentially to enable remote exploration of planetary surfaces in real-time. In this talk, I will discuss the technical challenges associated with building and operating robots in this manner, along with lessons learned from research conducted with the ISS and in the field.

A Systems Model for Teaching Human Resource Management

Directory of Open Access Journals (Sweden)

George R. Greene

2013-07-01

Full Text Available Efficient and effective human resource management is a complex, involved, and interactive process. This article presents and discusses a unique systems approach model for teaching human resource (people management processes, and the important inter-relationships within that process. The model contains two unique components related to key sub-processes: incentives management and performance evaluation. We have not observed a model applying a systems thinking paradigm presented in any textbook, journal article, business publication, or other literature addressing the topic. For nearly three decades, the model has been used in teaching a comprehensive, meaningful understanding of the human resource management process that can be effectively implemented in both corporate and academic learning venues.

Human-structure Interaction and Implications

DEFF Research Database (Denmark)

Pedersen, Lars

2016-01-01

On civil engineering structures human occupancy is often modeled as a static load. Modeling humans as a static load is a simplification of matters, as will be demonstrated in the paper. The paper addresses the complexity of having both passive humans (sitting or standing) as well as active humans...

The relevance of non-human primate and rodent malaria models for humans

Directory of Open Access Journals (Sweden)

Riley Eleanor

2011-02-01

Full Text Available Abstract At the 2010 Keystone Symposium on "Malaria: new approaches to understanding Host-Parasite interactions", an extra scientific session to discuss animal models in malaria research was convened at the request of participants. This was prompted by the concern of investigators that skepticism in the malaria community about the use and relevance of animal models, particularly rodent models of severe malaria, has impacted on funding decisions and publication of research using animal models. Several speakers took the opportunity to demonstrate the similarities between findings in rodent models and human severe disease, as well as points of difference. The variety of malaria presentations in the different experimental models parallels the wide diversity of human malaria disease and, therefore, might be viewed as a strength. Many of the key features of human malaria can be replicated in a variety of nonhuman primate models, which are very under-utilized. The importance of animal models in the discovery of new anti-malarial drugs was emphasized. The major conclusions of the session were that experimental and human studies should be more closely linked so that they inform each other, and that there should be wider access to relevant clinical material.

Enhancing Human-Computer Interaction Design Education: Teaching Affordance Design for Emerging Mobile Devices

Science.gov (United States)

Faiola, Anthony; Matei, Sorin Adam

2010-01-01

The evolution of human-computer interaction design (HCID) over the last 20 years suggests that there is a growing need for educational scholars to consider new and more applicable theoretical models of interactive product design. The authors suggest that such paradigms would call for an approach that would equip HCID students with a better…

Gaze-and-brain-controlled interfaces for human-computer and human-robot interaction

Directory of Open Access Journals (Sweden)

Shishkin S. L.

2017-09-01

Full Text Available Background. Human-machine interaction technology has greatly evolved during the last decades, but manual and speech modalities remain single output channels with their typical constraints imposed by the motor system’s information transfer limits. Will brain-computer interfaces (BCIs and gaze-based control be able to convey human commands or even intentions to machines in the near future? We provide an overview of basic approaches in this new area of applied cognitive research. Objective. We test the hypothesis that the use of communication paradigms and a combination of eye tracking with unobtrusive forms of registering brain activity can improve human-machine interaction. Methods and Results. Three groups of ongoing experiments at the Kurchatov Institute are reported. First, we discuss the communicative nature of human-robot interaction, and approaches to building a more e cient technology. Specifically, “communicative” patterns of interaction can be based on joint attention paradigms from developmental psychology, including a mutual “eye-to-eye” exchange of looks between human and robot. Further, we provide an example of “eye mouse” superiority over the computer mouse, here in emulating the task of selecting a moving robot from a swarm. Finally, we demonstrate a passive, noninvasive BCI that uses EEG correlates of expectation. This may become an important lter to separate intentional gaze dwells from non-intentional ones. Conclusion. The current noninvasive BCIs are not well suited for human-robot interaction, and their performance, when they are employed by healthy users, is critically dependent on the impact of the gaze on selection of spatial locations. The new approaches discussed show a high potential for creating alternative output pathways for the human brain. When support from passive BCIs becomes mature, the hybrid technology of the eye-brain-computer (EBCI interface will have a chance to enable natural, fluent, and the

Human-Robot Interaction Directed Research Project

Science.gov (United States)

Rochlis, Jennifer; Ezer, Neta; Sandor, Aniko

2011-01-01

Human-robot interaction (HRI) is about understanding and shaping the interactions between humans and robots (Goodrich & Schultz, 2007). It is important to evaluate how the design of interfaces and command modalities affect the human s ability to perform tasks accurately, efficiently, and effectively (Crandall, Goodrich, Olsen Jr., & Nielsen, 2005) It is also critical to evaluate the effects of human-robot interfaces and command modalities on operator mental workload (Sheridan, 1992) and situation awareness (Endsley, Bolt , & Jones, 2003). By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed that support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for design. Because the factors associated with interfaces and command modalities in HRI are too numerous to address in 3 years of research, the proposed research concentrates on three manageable areas applicable to National Aeronautics and Space Administration (NASA) robot systems. These topic areas emerged from the Fiscal Year (FY) 2011 work that included extensive literature reviews and observations of NASA systems. The three topic areas are: 1) video overlays, 2) camera views, and 3) command modalities. Each area is described in detail below, along with relevance to existing NASA human-robot systems. In addition to studies in these three topic areas, a workshop is proposed for FY12. The workshop will bring together experts in human-robot interaction and robotics to discuss the state of the practice as applicable to research in space robotics. Studies proposed in the area of video overlays consider two factors in the implementation of augmented reality (AR) for operator displays during teleoperation. The first of these factors is the type of navigational guidance provided by AR symbology. In the proposed

Human Work Interaction Design

DEFF Research Database (Denmark)

Gonçalves, Frederica; Campos, Pedro; Clemmensen, Torkil

2015-01-01

In this paper, we review research in the emerging practice and research field of Human Work Interaction Design (HWID). We present a HWID frame-work, and a sample of 54 papers from workshops, conferences and journals from the period 2009-2014. We group the papers into six topical groups, and then ...

Mechanical Impedance Modeling of Human Arm: A survey

Science.gov (United States)

Puzi, A. Ahmad; Sidek, S. N.; Sado, F.

2017-03-01

Human arm mechanical impedance plays a vital role in describing motion ability of the upper limb. One of the impedance parameters is stiffness which is defined as the ratio of an applied force to the measured deformation of the muscle. The arm mechanical impedance modeling is useful in order to develop a better controller for system that interacts with human as such an automated robot-assisted platform for automated rehabilitation training. The aim of the survey is to summarize the existing mechanical impedance models of human upper limb so to justify the need to have an improved version of the arm model in order to facilitate the development of better controller of such systems with ever increase in complexity. In particular, the paper will address the following issue: Human motor control and motor learning, constant and variable impedance models, methods for measuring mechanical impedance and mechanical impedance modeling techniques.

Social Psychology Of Persuasion Applied To Human-agent Interaction

Directory of Open Access Journals (Sweden)

Shenghua Liu

2008-01-01

Full Text Available This paper discusses and evaluates the application of a social psychologically enriched, user-centered approach to agent architecture design. The major aim is to facilitate human-agent interaction (HAI by making agents not only algorithmically more intelligent but also socially more skillful in communicating with the user. A decision-making model and communicative argumentation strategies have been incorporated into the agent architecture. In the presented content resource management experiments, enhancement of human task performance is demonstrated for users that are supported by a persuasive agent. This superior performance seems to be rooted in a more trusting collaborative relationship between the user and the agent, rather than in the appropriateness of the agent's decision-making suggestions alone. In particular, the second experiment demonstrated that interface interaction design should follow the principles of task-orientation and implicitness. Making the influence of the agent too salient can trigger counterintentional effects, such as users' discomfort and psychological reactance.

Immune Cell-Supplemented Human Skin Model for Studying Fungal Infections.

Science.gov (United States)

Kühbacher, Andreas; Sohn, Kai; Burger-Kentischer, Anke; Rupp, Steffen

2017-01-01

Human skin is a niche for various fungal species which either colonize the surface of this tissue as commensals or, primarily under conditions of immunosuppression, invade the skin and cause infection. Here we present a method for generation of a human in vitro skin model supplemented with immune cells of choice. This model represents a complex yet amenable tool to study molecular mechanisms of host-fungi interactions at human skin.

Integrating social science into empirical models of coupled human and natural systems

Science.gov (United States)

Jeffrey D. Kline; Eric M. White; A Paige Fischer; Michelle M. Steen-Adams; Susan Charnley; Christine S. Olsen; Thomas A. Spies; John D. Bailey

2017-01-01

Coupled human and natural systems (CHANS) research highlights reciprocal interactions (or feedbacks) between biophysical and socioeconomic variables to explain system dynamics and resilience. Empirical models often are used to test hypotheses and apply theory that represent human behavior. Parameterizing reciprocal interactions presents two challenges for social...

Social interactions through the eyes of macaques and humans.

Directory of Open Access Journals (Sweden)

Richard McFarland

Full Text Available Group-living primates frequently interact with each other to maintain social bonds as well as to compete for valuable resources. Observing such social interactions between group members provides individuals with essential information (e.g. on the fighting ability or altruistic attitude of group companions to guide their social tactics and choice of social partners. This process requires individuals to selectively attend to the most informative content within a social scene. It is unclear how non-human primates allocate attention to social interactions in different contexts, and whether they share similar patterns of social attention to humans. Here we compared the gaze behaviour of rhesus macaques and humans when free-viewing the same set of naturalistic images. The images contained positive or negative social interactions between two conspecifics of different phylogenetic distance from the observer; i.e. affiliation or aggression exchanged by two humans, rhesus macaques, Barbary macaques, baboons or lions. Monkeys directed a variable amount of gaze at the two conspecific individuals in the images according to their roles in the interaction (i.e. giver or receiver of affiliation/aggression. Their gaze distribution to non-conspecific individuals was systematically varied according to the viewed species and the nature of interactions, suggesting a contribution of both prior experience and innate bias in guiding social attention. Furthermore, the monkeys' gaze behavior was qualitatively similar to that of humans, especially when viewing negative interactions. Detailed analysis revealed that both species directed more gaze at the face than the body region when inspecting individuals, and attended more to the body region in negative than in positive social interactions. Our study suggests that monkeys and humans share a similar pattern of role-sensitive, species- and context-dependent social attention, implying a homologous cognitive mechanism of

Human mini-guts: new insights into intestinal physiology and host-pathogen interactions.

Science.gov (United States)

In, Julie G; Foulke-Abel, Jennifer; Estes, Mary K; Zachos, Nicholas C; Kovbasnjuk, Olga; Donowitz, Mark

2016-11-01

The development of indefinitely propagating human 'mini-guts' has led to a rapid advance in gastrointestinal research related to transport physiology, developmental biology, pharmacology, and pathophysiology. These mini-guts, also called enteroids or colonoids, are derived from LGR5 + intestinal stem cells isolated from the small intestine or colon. Addition of WNT3A and other growth factors promotes stemness and results in viable, physiologically functional human intestinal or colonic cultures that develop a crypt-villus axis and can be differentiated into all intestinal epithelial cell types. The success of research using human enteroids has highlighted the limitations of using animals or in vitro, cancer-derived cell lines to model transport physiology and pathophysiology. For example, curative or preventive therapies for acute enteric infections have been limited, mostly due to the lack of a physiological human intestinal model. However, the human enteroid model enables specific functional studies of secretion and absorption in each intestinal segment as well as observations of the earliest molecular events that occur during enteric infections. This Review describes studies characterizing these human mini-guts as a physiological model to investigate intestinal transport and host-pathogen interactions.

Neural correlate of human reciprocity in social interactions.

Science.gov (United States)

Sakaiya, Shiro; Shiraito, Yuki; Kato, Junko; Ide, Hiroko; Okada, Kensuke; Takano, Kouji; Kansaku, Kenji

2013-01-01

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoner's dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions.

Neural correlate of human reciprocity in social interactions

Directory of Open Access Journals (Sweden)

Shiro eSakaiya

2013-12-01

Full Text Available Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human and strategy (random, tit-for-tat in repeated prisoner’s dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate and theory of mind (ToM regions (i.e., ventromedial prefrontal cortex [VMPFC] and precuneus. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (deactivation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during

Measuring the genetic influence on human life span: gene-environment interaction and sex-specific genetic effects

DEFF Research Database (Denmark)

Tan, Qihua; De Benedictis, G; Yashin, Annatoli

2001-01-01

New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographicinf......New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic...

A QCM-D study of the concentration- and time-dependent interactions of human LL37 with model mammalian lipid bilayers.

Science.gov (United States)

Lozeau, Lindsay D; Rolle, Marsha W; Camesano, Terri A

2018-07-01

The human antimicrobial peptide LL37 is promising as an alternative to antibiotics due to its biophysical interactions with charged bacterial lipids. However, its clinical potential is limited due to its interactions with zwitterionic mammalian lipids leading to cytotoxicity. Mechanistic insight into the LL37 interactions with mammalian lipids may enable rational design of less toxic LL37-based therapeutics. To this end, we studied concentration- and time-dependent interactions of LL37 with zwitterionic model phosphatidylcholine (PC) bilayers with quartz crystal microbalance with dissipation (QCM-D). LL37 mass adsorption and PC bilayer viscoelasticity changes were monitored by measuring changes in frequency (Δf) and dissipation (ΔD), respectively. The Voigt-Kelvin viscoelastic model was applied to Δf and ΔD to study changes in bilayer thickness and density with LL37 concentration. At low concentrations (0.10-1.00 μM), LL37 adsorbed onto bilayers in a concentration-dependent manner. Further analyses of Δf, ΔD and thickness revealed that peptide saturation on the bilayers was a threshold for interactions observed above 2.00 μM, interactions that were rapid, multi-step, and reached equilibrium in a concentration- and time-dependent manner. Based on these data, we proposed a model of stable transmembrane pore formation at 2.00-10.0 μM, or transition from a primarily lipid to a primarily protein film with a transmembrane pore formation intermediate state at concentrations of LL37 > 10 μM. The concentration-dependent interactions between LL37 and PC bilayers correlated with the observed concentration-dependent biological activities of LL37 (antimicrobial, immunomodulatory and non-cytotoxic at 0.1-1.0 μM, hemolytic and some cytotoxicity at 2.0-13 μM and cytotoxic at >13 μM). Copyright © 2018 Elsevier B.V. All rights reserved.

A physical model of sensorimotor interactions during locomotion

Science.gov (United States)

Klein, Theresa J.; Lewis, M. Anthony

2012-08-01

In this paper, we describe the development of a bipedal robot that models the neuromuscular architecture of human walking. The body is based on principles derived from human muscular architecture, using muscles on straps to mimic agonist/antagonist muscle action as well as bifunctional muscles. Load sensors in the straps model Golgi tendon organs. The neural architecture is a central pattern generator (CPG) composed of a half-center oscillator combined with phase-modulated reflexes that is simulated using a spiking neural network. We show that the interaction between the reflex system, body dynamics and CPG results in a walking cycle that is entrained to the dynamics of the system. We also show that the CPG helped stabilize the gait against perturbations relative to a purely reflexive system, and compared the joint trajectories to human walking data. This robot represents a complete physical, or ‘neurorobotic’, model of the system, demonstrating the usefulness of this type of robotics research for investigating the neurophysiological processes underlying walking in humans and animals.

Human-Interaction Challenges in UAV-Based Autonomous Surveillance

Science.gov (United States)

Freed, Michael; Harris, Robert; Shafto, Michael G.

2004-01-01

Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We describe a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this framework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then describes human-interaction challenges arising from this approach that we have identified and begun to address.

Towards a Model of Human Resource Solutions for Achieving Intergenerational Interaction in Organisations

Science.gov (United States)

McGuire, David; By, Rune Todnem; Hutchings, Kate

2007-01-01

Purpose: Achieving intergenerational interaction and avoiding conflict is becoming increasingly difficult in a workplace populated by three generations--Baby Boomers, Generation X-ers and Generation Y-ers. This paper presents a model and proposes HR solutions towards achieving co-operative generational interaction. Design/methodology/approach:…

A Physical Interaction Network of Dengue Virus and Human Proteins*

Science.gov (United States)

Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

2011-01-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

A physical interaction network of dengue virus and human proteins.

Science.gov (United States)

Khadka, Sudip; Vangeloff, Abbey D; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J; Perera, Rushika; LaCount, Douglas J

2011-12-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection.

The interaction of 2-mercaptobenzimidazole with human serum albumin as determined by spectroscopy, atomic force microscopy and molecular modeling.

Science.gov (United States)

Li, Yuqin; Jia, Baoxiu; Wang, Hao; Li, Nana; Chen, Gaopan; Lin, Yuejuan; Gao, Wenhua

2013-04-01

The interaction of 2-mercaptobenzimidazole (MBI) with human serum albumin (HSA) was studied in vitro by equilibrium dialysis under normal physiological conditions. This study used fluorescence, ultraviolet-visible spectroscopy (UV-vis), Fourier transform infrared (FT-IR), circular dichroism (CD) and Raman spectroscopy, atomic force microscopy (AFM) and molecular modeling techniques. Association constants, the number of binding sites and basic thermodynamic parameters were used to investigate the quenching mechanism. Based on the fluorescence resonance energy transfer, the distance between the HSA and MBI was 2.495 nm. The ΔG(0), ΔH(0), and ΔS(0) values across temperature indicated that the hydrophobic interaction was the predominant binding Force. The UV, FT-IR, CD and Raman spectra confirmed that the HSA secondary structure was altered in the presence of MBI. In addition, the molecular modeling showed that the MBI-HSA complex was stabilized by hydrophobic forces, which resulted from amino acid residues. The AFM results revealed that the individual HSA molecule dimensions were larger after interaction with MBI. Overall, this study suggested a method for characterizing the weak intermolecular interaction. In addition, this method is potentially useful for elucidating the toxigenicity of MBI when it is combined with the biomolecular function effect, transmembrane transport, toxicological testing and other experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

Humans, computers and wizards human (simulated) computer interaction

CERN Document Server

Fraser, Norman; McGlashan, Scott; Wooffitt, Robin

2013-01-01

Using data taken from a major European Union funded project on speech understanding, the SunDial project, this book considers current perspectives on human computer interaction and argues for the value of an approach taken from sociology which is based on conversation analysis.

A Perspective on Computational Human Performance Models as Design Tools

Science.gov (United States)

Jones, Patricia M.

2010-01-01

The design of interactive systems, including levels of automation, displays, and controls, is usually based on design guidelines and iterative empirical prototyping. A complementary approach is to use computational human performance models to evaluate designs. An integrated strategy of model-based and empirical test and evaluation activities is particularly attractive as a methodology for verification and validation of human-rated systems for commercial space. This talk will review several computational human performance modeling approaches and their applicability to design of display and control requirements.

A Culture-Behavior-Brain Loop Model of Human Development.

Science.gov (United States)

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Proxemics models for human-aware navigation in robotics: Grounding interaction and personal space models in experimental data from psychology

OpenAIRE

Barnaud , Marie-Lou; Morgado , Nicolas; Palluel-Germain , Richard; Diard , Julien; Spalanzani , Anne

2014-01-01

International audience; In order to navigate in a social environment, a robot must be aware of social spaces, which include proximity and interaction-based constraints. Previous models of interaction and personal spaces have been inspired by studies in social psychology but not systematically grounded and validated with respect to experimental data. We propose to implement personal and interaction space models in order to replicate a classical psychology experiment. Our robotic simulations ca...

The antiprogesterone Org 31710 inhibits human blastocyst-endometrial interactions in vitro

DEFF Research Database (Denmark)

Petersen, Astrid; Bentin-Ley, Ursula; Ravn, Vibeke

2005-01-01

OBJECTIVE: To investigate the effect of the anti-P Org 31710 on human blastocyst attachment to cultured endometrial epithelial cells. DESIGN: Experimental in vitro study. SETTING: University hospital. PATIENT(S): Eleven fertile endometrial donors. INTERVENTION(S): Timed endometrial biopsy for cell...... statistical significance. The presence of swollen microvilli, precursors of endometrial pinopodes, was significantly reduced on cultures with Org 31710 (P=.03). CONCLUSION(S): The study presents a model for human blastocyst-endometrial interactions responding to an anti-P drug. The exact mechanism...

A Novel Bioinspired Vision System: A Step toward Real-Time Human-Robot Interactions

Directory of Open Access Journals (Sweden)

Abdul Rahman Hafiz

2011-01-01

Full Text Available Building a human-like robot that could be involved in our daily lives is a dream of many scientists. Achieving a sophisticated robot's vision system, which can enhance the robot's real-time interaction ability with the human, is one of the main keys toward realizing such an autonomous robot. In this work, we are suggesting a bioinspired vision system that helps to develop an advanced human-robot interaction in an autonomous humanoid robot. First, we enhance the robot's vision accuracy online by applying a novel dynamic edge detection algorithm abstracted from the rules that the horizontal cells play in the mammalian retina. Second, in order to support the first algorithm, we improve the robot's tracking ability by designing a variant photoreceptors distribution corresponding to what exists in the human vision system. The experimental results verified the validity of the model. The robot could have a clear vision in real time and build a mental map that assisted it to be aware of the frontal users and to develop a positive interaction with them.

What Can Human Geography Offer Climate Change Modelling?

DEFF Research Database (Denmark)

Grindsted, Thomas Skou

2014-01-01

behaviour to economic rationality when construed in sophisticated climate models and sometimes in nongeographical representations. The need to comprehensively take into consideration methodological approaches concerning the interface of society-environment interactions seems highly relevant to contemporary...... regularities, rationalities, and pre-analytic assumptions. Lastly we discuss challenges of constructing nature(s) and how we better understand the (geo) politics of climate change modeling.......The discipline of Geography may be one of the most prominent and oldest disciplines in the conceptualization of human–environment interactions that integrates elements from both natural and social sciences. Yet, much research on society–environment interactions on climate change reduces human...

A Probabilistic Model of Social Working Memory for Information Retrieval in Social Interactions.

Science.gov (United States)

Li, Liyuan; Xu, Qianli; Gan, Tian; Tan, Cheston; Lim, Joo-Hwee

2018-05-01

Social working memory (SWM) plays an important role in navigating social interactions. Inspired by studies in psychology, neuroscience, cognitive science, and machine learning, we propose a probabilistic model of SWM to mimic human social intelligence for personal information retrieval (IR) in social interactions. First, we establish a semantic hierarchy as social long-term memory to encode personal information. Next, we propose a semantic Bayesian network as the SWM, which integrates the cognitive functions of accessibility and self-regulation. One subgraphical model implements the accessibility function to learn the social consensus about IR-based on social information concept, clustering, social context, and similarity between persons. Beyond accessibility, one more layer is added to simulate the function of self-regulation to perform the personal adaptation to the consensus based on human personality. Two learning algorithms are proposed to train the probabilistic SWM model on a raw dataset of high uncertainty and incompleteness. One is an efficient learning algorithm of Newton's method, and the other is a genetic algorithm. Systematic evaluations show that the proposed SWM model is able to learn human social intelligence effectively and outperforms the baseline Bayesian cognitive model. Toward real-world applications, we implement our model on Google Glass as a wearable assistant for social interaction.

Human-Computer Interaction in Smart Environments

Science.gov (United States)

Paravati, Gianluca; Gatteschi, Valentina

2015-01-01

Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

A topological multilayer model of the human body.

Science.gov (United States)

Barbeito, Antonio; Painho, Marco; Cabral, Pedro; O'Neill, João

2015-11-04

Geographical information systems deal with spatial databases in which topological models are described with alphanumeric information. Its graphical interfaces implement the multilayer concept and provide powerful interaction tools. In this study, we apply these concepts to the human body creating a representation that would allow an interactive, precise, and detailed anatomical study. A vector surface component of the human body is built using a three-dimensional (3-D) reconstruction methodology. This multilayer concept is implemented by associating raster components with the corresponding vector surfaces, which include neighbourhood topology enabling spatial analysis. A root mean square error of 0.18 mm validated the three-dimensional reconstruction technique of internal anatomical structures. The expansion of the identification and the development of a neighbourhood analysis function are the new tools provided in this model.

Human interactions with sirenians (manatees and dugongs)

Science.gov (United States)

Bonde, Robert K.; Flint, Mark

2017-01-01

There are three extant sirenian species of the Trichechidae family and one living Dugongidae family member. Given their close ties to coastal and often urbanized habitats, sirenians are exposed to many types of anthropogenic activities that result in challenges to their well-being, poor health, and even death. In the wild, they are exposed to direct and indirect local pressures as well as subject to large-scale stressors such as global climate change acting on regions or entire genetic stocks. In captivity, they are subject to husbandry and management practices based on our collective knowledge, or in some cases lack thereof, of their needs and welfare. It is therefore reasonable to consider that their current imperiled status is very closely linked to our actions. In this chapter, we identify and define human interactions that may impact dugongs and manatees, including hunting, fisheries, boat interactions, negative interactions with man-made structures, disease and contaminants, and global climate change. We examine techniques used to investigate these impacts and the influence of sirenian biology and of changing human behaviors on potential outcomes. We examine how this differs for dugongs and manatees in the wild and for those held in captivity. Finally, we provide possible mitigation strategies and ways to assess the efforts we are making to improve the welfare of individuals and to conserve these species. This chapter identifies how the welfare of these species is intrinsically linked to the human interactions these animals experience, and how the nature of these interactions has changed with societal shifts. We proffer suggested ways to minimize negative impacts. Current knowledge should be used to minimize negative human interactions and impacts, to promote positive impacts, and to protect these animals for the future.

Visual exploration and analysis of human-robot interaction rules

Science.gov (United States)

Zhang, Hui; Boyles, Michael J.

2013-01-01

We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming

Enantiomeric metabolic interactions and stereoselective human methadone metabolism.

Science.gov (United States)

Totah, Rheem A; Allen, Kyle E; Sheffels, Pamela; Whittington, Dale; Kharasch, Evan D

2007-04-01

Methadone is administered as a racemate, although opioid activity resides in the R-enantiomer. Methadone disposition is stereoselective, with considerable unexplained variability in clearance and plasma R/S ratios. N-Demethylation of methadone in vitro is predominantly mediated by cytochrome P450 CYP3A4 and CYP2B6 and somewhat by CYP2C19. This investigation evaluated stereoselectivity, models, and kinetic parameters for methadone N-demethylation by recombinant CYP2B6, CYP3A4, and CYP2C19, and the potential for interactions between enantiomers during racemate metabolism. CYP2B6 metabolism was stereoselective. CYP2C19 was less active, and stereoselectivity was opposite that for CYP2B6. CYP3A4 was not stereoselective. With all three isoforms, enantiomer N-dealkylation rates in the racemate were lower than those of (R)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (R-methadone) or (S)-(6-dimethyamino-4,4-diphenyl-heptan-3-one) hydrochloride (S-methadone) alone, suggesting an enantiomeric interaction and mutual metabolic inhibition. For CYP2B6, the interaction between enantiomers was stereoselective, with S-methadone as a more potent inhibitor of R-methadone N-demethylation than R-of S-methadone. In contrast, enantiomer interactions were not stereoselective with CYP2C19 or CYP3A4. For all three cytochromes P450, methadone N-demethylation was best described by two-site enzyme models with competitive inhibition. There were minor model differences between cytochromes P450 to account for stereoselectivity of metabolism and enantiomeric interactions. Changes in plasma R/S methadone ratios observed after rifampin or troleandomycin pretreatment in humans in vivo were successfully predicted by CYP2B6- but not CYP3A4-catalyzed methadone N-demethylation. CYP2B6 is a predominant catalyst of stereoselective methadone metabolism in vitro. In vivo, CYP2B6 may be a major determinant of methadone metabolism and disposition, and CYP2B6 activity and stereoselective metabolic

Human immune system mouse models of Ebola virus infection.

Science.gov (United States)

Spengler, Jessica R; Prescott, Joseph; Feldmann, Heinz; Spiropoulou, Christina F

2017-08-01

Human immune system (HIS) mice, immunodeficient mice engrafted with human cells (with or without donor-matched tissue), offer a unique opportunity to study pathogens that cause disease predominantly or exclusively in humans. Several HIS mouse models have recently been used to study Ebola virus (EBOV) infection and disease. The results of these studies are encouraging and support further development and use of these models in Ebola research. HIS mice provide a small animal model to study EBOV isolates, investigate early viral interactions with human immune cells, screen vaccines and therapeutics that modulate the immune system, and investigate sequelae in survivors. Here we review existing models, discuss their use in pathogenesis studies and therapeutic screening, and highlight considerations for study design and analysis. Finally, we point out caveats to current models, and recommend future efforts for modeling EBOV infection in HIS mice. Published by Elsevier B.V.

Human-Computer Interaction in Smart Environments

Directory of Open Access Journals (Sweden)

Gianluca Paravati

2015-08-01

Full Text Available Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

Science.gov (United States)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

A scored human protein-protein interaction network to catalyze genomic interpretation

DEFF Research Database (Denmark)

Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

2017-01-01

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

Structural Insight into the interaction of Flavonoids with Human Telomeric Sequence

Science.gov (United States)

Tawani, Arpita; Kumar, Amit

2015-01-01

Flavonoids are a group of naturally available compounds that are an attractive source for drug discovery. Their potential to act as anti-tumourigenic and anti-proliferative agents has been reported previously but is not yet fully understood. Targeting human telomeric G-quadruplex DNA could be one of the mechanisms by which these flavonoids exert anticancer activity. We have performed detailed biophysical studies for the interaction of four representative flavonoids, Luteolin, Quercetin, Rutin and Genistein, with the human telomeric G-quadruplex sequence tetramolecular d-(T2AG3T) (Tel7). In addition, we used NMR spectroscopy to derive the first model for the complex formed between Quercetin and G-quadruplex sequence. The model showed that Quercetin stabilises the G-quadruplex structure and does not open the G-tetrad. It interacts with the telomeric sequence through π-stacking at two sites: between T1pT2 and between G6pT7. Based on our findings, we suggest that Quercetin could be a potent candidate for targeting the telomere and thus, act as a potent anti-cancer agent. PMID:26627543

Human-machine interaction in nuclear power plants

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu

2005-01-01

Advanced nuclear power plants are generally large complex systems automated by computers. Whenever a rate plant emergency occurs the plant operators must cope with the emergency under severe mental stress without committing any fatal errors. Furthermore, the operators must train to improve and maintain their ability to cope with every conceivable situation, though it is almost impossible to be fully prepared for an infinite variety of situations. In view of the limited capability of operators in emergency situations, there has been a new approach to preventing the human error caused by improper human-machine interaction. The new approach has been triggered by the introduction of advanced information systems that help operators recognize and counteract plant emergencies. In this paper, the adverse effect of automation in human-machine systems is explained. The discussion then focuses on how to configure a joint human-machine system for ideal human-machine interaction. Finally, there is a new proposal on how to organize technologies that recognize the different states of such a joint human-machine system

A feature-based approach to modeling protein-DNA interactions.

Directory of Open Access Journals (Sweden)

Eilon Sharon

Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.

Application of equivalent electrodes method to analysis of interaction between ELF-LF electric fields and human body

International Nuclear Information System (INIS)

Ceselkoska, Vesna C.; Velickovic, Dragutin M.

2002-01-01

This paper presents the use of equivalent electrodes method, numerical method, based on surface-charge equation to quantify the interaction of low frequencies electric fields with various models of human body. The evaluation of the electric field intensity on the body surface is performed for a realistic model of the human body. Several examples for different postures of the model are given. (Author)

The Past, Present and Future of Human Computer Interaction

KAUST Repository

Churchill, Elizabeth

2018-01-16

Human Computer Interaction (HCI) focuses on how people interact with, and are transformed by computation. Our current technology landscape is changing rapidly. Interactive applications, devices and services are increasingly becoming embedded into our environments. From our homes to the urban and rural spaces, we traverse everyday. We are increasingly able toﾖoften required toﾖmanage and configure multiple, interconnected devices and program their interactions. Artificial intelligence (AI) techniques are being used to create dynamic services that learn about us and others, that make conclusions about our intents and affiliations, and that mould our digital interactions based in predictions about our actions and needs, nudging us toward certain behaviors. Computation is also increasingly embedded into our bodies. Understanding human interactions in the everyday digital and physical context. During this lecture, Elizabeth Churchill -Director of User Experience at Google- will talk about how an emerging landscape invites us to revisit old methods and tactics for understanding how people interact with computers and computation, and how it challenges us to think about new methods and frameworks for understanding the future of human-centered computation.

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

Science.gov (United States)

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

Probing cocaine-antibody interactions in buffer and human serum.

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Muthu Ramakrishnan

Full Text Available Despite progress in cocaine immunotherapy, the kinetic and thermodynamic properties of antibodies which bind to cocaine and its metabolites are not well understood. It is also not clear how the interactions between them differ in a complex matrix such as the serum present in the human body. In the present study, we have used microscale thermophoresis (MST, isothermal titration calorimetry (ITC, and surface plasmon resonance (SPR we have evaluated the affinity properties of a representative mouse monoclonal (mAb08 as well as those of polyclonal antibodies purified from vaccinated mouse and human patient serum.MST analysis of fluorescently tagged mAb08 binding to cocaine reveals an approximately 15 fold decrease in its equilibrium dissociation constant in 20-50% human serum compared with that in saline buffer. A similar trend was also found using enriched polyclonal antibodies purified from vaccinated mice and patient serum, for which we have used fluorescently tagged bovine serum albumin conjugated to succinyl norcocaine (BSA-SNC. This conjugate closely mimics both cocaine and the hapten used to raise these antibodies. The ITC data also revealed that cocaine has a moderate affinity of about 2 µM to 20% human serum and very little interaction with human serum albumin or nonspecific human IgG at that concentration range. In a SPR inhibition experiment, the binding of mAb08 to immobilized BSA-SNC was inhibited by cocaine and benzoylecgonine in a highly competitive manner, whereas the purified polyclonal antibodies from vaccinated humans and mice, revealed preferential selectivity to pharmacologically active cocaine but not to the inactive metabolite benzoylecgonine. We have also developed a simple binding model to simulate the challenges associated with cocaine immunotherapy using the variable quantitative and kinetic properties of the antibodies.High sensitivity calorimetric determination of antibody binding to cocaine and its metabolites provide

Kinetic Models for Topological Nearest-Neighbor Interactions

Science.gov (United States)

Blanchet, Adrien; Degond, Pierre

2017-12-01

We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Human-Computer Interaction The Agency Perspective

CERN Document Server

Oliveira, José

2012-01-01

Agent-centric theories, approaches and technologies are contributing to enrich interactions between users and computers. This book aims at highlighting the influence of the agency perspective in Human-Computer Interaction through a careful selection of research contributions. Split into five sections; Users as Agents, Agents and Accessibility, Agents and Interactions, Agent-centric Paradigms and Approaches, and Collective Agents, the book covers a wealth of novel, original and fully updated material, offering:   ü  To provide a coherent, in depth, and timely material on the agency perspective in HCI ü  To offer an authoritative treatment of the subject matter presented by carefully selected authors ü  To offer a balanced and broad coverage of the subject area, including, human, organizational, social, as well as technological concerns. ü  To offer a hands-on-experience by covering representative case studies and offering essential design guidelines   The book will appeal to a broad audience of resea...

Interaction of an atypical Plasmodium falciparum ETRAMP with human apolipoproteins

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Sahasrabudhe Sudhir

2008-10-01

Full Text Available Abstract Background In order to establish a successful infection in the human host, the malaria parasite Plasmodium falciparum must establish interactions with a variety of human proteins on the surface of different cell types, as well as with proteins inside the host cells. To better understand this aspect of malaria pathogenesis, a study was conducted with the goal of identifying interactions between proteins of the parasite and those of its human host. Methods A modified yeast two-hybrid methodology that preferentially selects protein fragments that can be expressed in yeast was used to conduct high-throughput screens with P. falciparum protein fragments against human liver and cerebellum libraries. The resulting dataset was analyzed to exclude interactions that are not likely to occur in the human host during infection. Results An initial set of 2,200 interactions was curated to remove proteins that are unlikely to play a role in pathogenesis based on their annotation or localization, and proteins that behave promiscuously in the two-hybrid assay, resulting in a final dataset of 456 interactions. A cluster that implicates binding between P. falciparum PFE1590w/ETRAMP5, a putative parasitophorous vacuole membrane protein, and human apolipoproteins ApoA, ApoB and ApoE was selected for further analysis. Different isoforms of ApoE, which are associated with different outcomes of malaria infection, were shown to display differential interactions with PFE1590w. Conclusion A dataset of interactions between proteins of P. falciparum and those of its human host was generated. The preferential interaction of the P. falciparum PFE1590w protein with the human ApoE ε3 and ApoE ε4 isoforms, but not the ApoE ε2 isoform, supports the hypothesis that ApoE genotype affects risk of malaria infection. The dataset contains other interactions of potential relevance to disease that may identify possible vaccine candidates and drug targets.

Human work interaction design meets international development

DEFF Research Database (Denmark)

Campos, P.; Clemmensen, T.; Barricelli, B.R.

2017-01-01

opportunity to observe technology-mediated innovative work practices in informal settings that may be related to the notion of International Development. In this unique context, this workshop proposes to analyze findings related to opportunities for design research in this type of work domains: a) human......Over the last decade, empirical relationships between work domain analysis and HCI design have been identified by much research in the field of Human Work Interaction Design (HWID) across five continents. Since this workshop takes place at the Interact Conference in Mumbai, there is a unique...

Dynamic Human Body Modeling Using a Single RGB Camera.

Science.gov (United States)

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-03-18

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

Science.gov (United States)

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Metabolic interaction between toluene, trichloroethylene and n-hexane in humans

DEFF Research Database (Denmark)

Bælum, Jesper; Mølhave, Lars; Hansen, S H

1998-01-01

This human experimental study describes the mutual metabolic interaction between toluene, trichloroethylene, and n-hexane.......This human experimental study describes the mutual metabolic interaction between toluene, trichloroethylene, and n-hexane....

Testing odorant-receptor interaction theories in humans through discrimination of isotopomers

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Mara Andrione

2017-12-01

Full Text Available Odour reception takes place on the olfactory receptor neuron membrane, where molecular receptors interact with volatile odorant molecules. This interaction is classically thought to rely on chemical and structural features of the odorant, e.g. size, shape, functional groups. However, this model does not allow formulating a correct prediction for the smell of an odorant, suggesting that other molecular properties may play a role in the odour transduction process. An alternative model of olfaction maintains that odorant receptors can probe not only the structural and chemical features, but also the molecular vibration spectrum of the odorants. This constitutes the so-called vibration model of olfaction. According to this model, two isotopomers of the same molecule, i.e. two forms of the same molecule, one unaltered and one in which one or more hydrogen atoms are substituted with deuterium – which are therefore structurally and chemically identical, but with different molecular vibration spectra – would interact differently with an olfactory receptor, producing different olfactory perceptions in the brain. Here, we report on a duo-trio discrimination experiment conducted on human subjects, testing isotopomer pairs that have recently been shown to be differentially encoded in the honeybee brain.

Eye Tracking Based Control System for Natural Human-Computer Interaction

Directory of Open Access Journals (Sweden)

Xuebai Zhang

2017-01-01

Full Text Available Eye movement can be regarded as a pivotal real-time input medium for human-computer communication, which is especially important for people with physical disability. In order to improve the reliability, mobility, and usability of eye tracking technique in user-computer dialogue, a novel eye control system with integrating both mouse and keyboard functions is proposed in this paper. The proposed system focuses on providing a simple and convenient interactive mode by only using user’s eye. The usage flow of the proposed system is designed to perfectly follow human natural habits. Additionally, a magnifier module is proposed to allow the accurate operation. In the experiment, two interactive tasks with different difficulty (searching article and browsing multimedia web were done to compare the proposed eye control tool with an existing system. The Technology Acceptance Model (TAM measures are used to evaluate the perceived effectiveness of our system. It is demonstrated that the proposed system is very effective with regard to usability and interface design.

Eye Tracking Based Control System for Natural Human-Computer Interaction.

Science.gov (United States)

Zhang, Xuebai; Liu, Xiaolong; Yuan, Shyan-Ming; Lin, Shu-Fan

2017-01-01

Eye movement can be regarded as a pivotal real-time input medium for human-computer communication, which is especially important for people with physical disability. In order to improve the reliability, mobility, and usability of eye tracking technique in user-computer dialogue, a novel eye control system with integrating both mouse and keyboard functions is proposed in this paper. The proposed system focuses on providing a simple and convenient interactive mode by only using user's eye. The usage flow of the proposed system is designed to perfectly follow human natural habits. Additionally, a magnifier module is proposed to allow the accurate operation. In the experiment, two interactive tasks with different difficulty (searching article and browsing multimedia web) were done to compare the proposed eye control tool with an existing system. The Technology Acceptance Model (TAM) measures are used to evaluate the perceived effectiveness of our system. It is demonstrated that the proposed system is very effective with regard to usability and interface design.

Advancing coupled human-earth system models: The integrated Earth System Model Project

Science.gov (United States)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems

Neural Signatures of Trust During Human-Automation Interactions

Science.gov (United States)

2016-04-01

also automated devices such as a Global Positioning System. For instance, to provide advanced safety measures, the Transportation Safety...AFRL-AFOSR-VA-TR-2016-0160 Neural Signatures of Trust during Human- Automation Interactions Frank Krueger GEORGE MASON UNIVERSITY Final Report 04/01...SUBTITLE Neural Signatures of Trust during Human- Automation Interactions 5a. CONTRACT NUMBER FA9550-13-1-0017 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

Using hydraulic modeling to simulate human interactions with water resources in an Omani irrigation system

Science.gov (United States)

Xanthopoulou, Themis; Ertsen, Maurits; Düring, Bleda; Kolen, Jan

2017-04-01

In the dry Southern Oman, more than a thousand years ago, a large water system that connected the mountain mass with the coastal region was constructed. Its length (up to 30 km) and the fact that the coastal region has a rich groundwater aquifer create confusion as to why the system was initially built. Nonetheless, it was abandoned a couple of centuries later only to be partially revived by small farming communities in the 17th to 18th century. The focus of our research is one of the irrigation systems that used the water conveyed from the large water system. Not much is known about these small irrigation systems functioning in the Wadi Al Jizzi of the greater Sohar region. There are no written records and we can only make guesses about the way the systems were managed based on ethnographical studies and the traditional Omani techniques. On the other hand, the good preservation state of the canals offers a great opportunity for hydraulic reconstruction of irrigation events. More than that, the material remains suggest and at the same time limit the ways in which humans interacted with the system and the water resources of the region. All irrigation activities and some daily activities had to be realized through the canal system and only if the canal system permits it these actions would have been feasible. We created a conceptual model of irrigation that includes the human agent and feedback mechanisms through hydraulics and then we simulated irrigation events using the Sobek software. Scenarios and sensibility analysis were used to address the unknown aspects of the system. Our research yielded insights about the way the farming community interacted with the larger water system, the levels of co-ordination and co-operation required for successful irrigation and the predisposition of conflict and power relations.

Advances and perspectives in in vitro human gut fermentation modeling.

Science.gov (United States)

Payne, Amanda N; Zihler, Annina; Chassard, Christophe; Lacroix, Christophe

2012-01-01

The gut microbiota is a highly specialized organ containing host-specific assemblages of microbes whereby metabolic activity directly impacts human health and disease. In vitro gut fermentation models present an unmatched opportunity of performing studies frequently challenged in humans and animals owing to ethical concerns. Multidisciplinary systems biology analyses supported by '-omics' platforms remain widely neglected in the field of in vitro gut fermentation modeling but are key to advancing the significance of these models. Model-driven experimentation using a combination of in vitro gut fermentation and in vitro human cell models represent an advanced approach in identifying complex host-microbe interactions and niches central to gut fermentation processes. The aim of this review is to highlight the advances and challenges exhibited by in vitro human gut fermentation modeling. Copyright © 2011 Elsevier Ltd. All rights reserved.

From 'automation' to 'autonomy': the importance of trust repair in human-machine interaction.

Science.gov (United States)

de Visser, Ewart J; Pak, Richard; Shaw, Tyler H

2018-04-09

Modern interactions with technology are increasingly moving away from simple human use of computers as tools to the establishment of human relationships with autonomous entities that carry out actions on our behalf. In a recent commentary, Peter Hancock issued a stark warning to the field of human factors that attention must be focused on the appropriate design of a new class of technology: highly autonomous systems. In this article, we heed the warning and propose a human-centred approach directly aimed at ensuring that future human-autonomy interactions remain focused on the user's needs and preferences. By adapting literature from industrial psychology, we propose a framework to infuse a unique human-like ability, building and actively repairing trust, into autonomous systems. We conclude by proposing a model to guide the design of future autonomy and a research agenda to explore current challenges in repairing trust between humans and autonomous systems. Practitioner Summary: This paper is a call to practitioners to re-cast our connection to technology as akin to a relationship between two humans rather than between a human and their tools. To that end, designing autonomy with trust repair abilities will ensure future technology maintains and repairs relationships with their human partners.

Advancements in Violin-Related Human-Computer Interaction

DEFF Research Database (Denmark)

Overholt, Daniel

2014-01-01

of human intelligence and emotion is at the core of the Musical Interface Technology Design Space, MITDS. This is a framework that endeavors to retain and enhance such traits of traditional instruments in the design of interactive live performance interfaces. Utilizing the MITDS, advanced Human...

Human-wildlife interaction in Serengeti and Ngorongoro districts

African Journals Online (AJOL)

Mgina

animals for reptile farms, ecologically focused small mammal management ... Magige - Human-wildlife interaction in Serengeti and Ngorongoro districts of Tanzania … 96 ... Information about attitudes of ..... interface: Interactions around Tilden.

Inferring high-confidence human protein-protein interactions

Directory of Open Access Journals (Sweden)

Yu Xueping

2012-05-01

Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

Humor in Human-Computer Interaction : A Short Survey

NARCIS (Netherlands)

Nijholt, Anton; Niculescu, Andreea; Valitutti, Alessandro; Banchs, Rafael E.; Joshi, Anirudha; Balkrishan, Devanuj K.; Dalvi, Girish; Winckler, Marco

2017-01-01

This paper is a short survey on humor in human-computer interaction. It describes how humor is designed and interacted with in social media, virtual agents, social robots and smart environments. Benefits and future use of humor in interactions with artificial entities are discussed based on

Haptic Human-Human Interaction Through a Compliant Connection Does Not Improve Motor Learning in a Force Field

NARCIS (Netherlands)

Beckers, Niek; Keemink, Arvid; van Asseldonk, Edwin; van der Kooij, Herman; Prattichizzo, Domenico; Shinoda, Hiroyuki; Tan, Hong Z.; Ruffaldi, Emanuele; Frisoli, Antonio

2018-01-01

Humans have a natural ability to haptically interact with other humans, for instance during physically assisting a child to learn how to ride a bicycle. A recent study has shown that haptic human-human interaction can improve individual motor performance and motor learning rate while learning to

Minimal mobile human computer interaction

NARCIS (Netherlands)

el Ali, A.

2013-01-01

In the last 20 years, the widespread adoption of personal, mobile computing devices in everyday life, has allowed entry into a new technological era in Human Computer Interaction (HCI). The constant change of the physical and social context in a user's situation made possible by the portability of

Incorporating human-water dynamics in a hyper-resolution land surface model

Science.gov (United States)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in

Systematic Three-Dimensional Coculture Rapidly Recapitulates Interactions between Human Neurons and Astrocytes

Directory of Open Access Journals (Sweden)

Robert Krencik

2017-12-01

Full Text Available Summary: Human astrocytes network with neurons in dynamic ways that are still poorly defined. Our ability to model this relationship is hampered by the lack of relevant and convenient tools to recapitulate this complex interaction. To address this barrier, we have devised efficient coculture systems utilizing 3D organoid-like spheres, termed asteroids, containing pre-differentiated human pluripotent stem cell (hPSC-derived astrocytes (hAstros combined with neurons generated from hPSC-derived neural stem cells (hNeurons or directly induced via Neurogenin 2 overexpression (iNeurons. Our systematic methods rapidly produce structurally complex hAstros and synapses in high-density coculture with iNeurons in precise numbers, allowing for improved studies of neural circuit function, disease modeling, and drug screening. We conclude that these bioengineered neural circuit model systems are reliable and scalable tools to accurately study aspects of human astrocyte-neuron functional properties while being easily accessible for cell-type-specific manipulations and observations. : In this article, Krencik and colleagues show that high-density cocultures of pre-differentiated human astrocytes with induced neurons, from pluripotent stem cells, elicit mature characteristics by 3–5 weeks. This provides a faster and more defined alternative method to organoid cultures for investigating human neural circuit function. Keywords: human pluripotent stem cells, neurons, astrocytes, synapses, coculture, three-dimensional spheres, organoids, disease modeling

Compliance control based on PSO algorithm to improve the feeling during physical human-robot interaction.

Science.gov (United States)

Jiang, Zhongliang; Sun, Yu; Gao, Peng; Hu, Ying; Zhang, Jianwei

2016-01-01

Robots play more important roles in daily life and bring us a lot of convenience. But when people work with robots, there remain some significant differences in human-human interactions and human-robot interaction. It is our goal to make robots look even more human-like. We design a controller which can sense the force acting on any point of a robot and ensure the robot can move according to the force. First, a spring-mass-dashpot system was used to describe the physical model, and the second-order system is the kernel of the controller. Then, we can establish the state space equations of the system. In addition, the particle swarm optimization algorithm had been used to obtain the system parameters. In order to test the stability of system, the root-locus diagram had been shown in the paper. Ultimately, some experiments had been carried out on the robotic spinal surgery system, which is developed by our team, and the result shows that the new controller performs better during human-robot interaction.

Physical Forces between Humans and How Humans Attract and Repel Each Other Based on Their Social Interactions in an Online World.

Directory of Open Access Journals (Sweden)

Stefan Thurner

Full Text Available Physical interactions between particles are the result of the exchange of gauge bosons. Human interactions are mediated by the exchange of messages, goods, money, promises, hostilities, etc. While in the physical world interactions and their associated forces have immediate dynamical consequences (Newton's laws the situation is not clear for human interactions. Here we quantify the relative acceleration between humans who interact through the exchange of messages, goods and hostilities in a massive multiplayer online game. For this game we have complete information about all interactions (exchange events between about 430,000 players, and about their trajectories (movements in the metric space of the game universe at any point in time. We use this information to derive "interaction potentials" for communication, trade and attacks and show that they are harmonic in nature. Individuals who exchange messages and trade goods generally attract each other and start to separate immediately after exchange events end. The form of the interaction potential for attacks mirrors the usual "hit-and-run" tactics of aggressive players. By measuring interaction intensities as a function of distance, velocity and acceleration, we show that "forces" between players are directly related to the number of exchange events. We find an approximate power-law decay of the likelihood for interactions as a function of distance, which is in accordance with previous real world empirical work. We show that the obtained potentials can be understood with a simple model assuming an exchange-driven force in combination with a distance-dependent exchange rate.

Holistic Modeling for Human-Autonomous System Interaction

Science.gov (United States)

2015-01-01

piloting ...2012).  18X   Pilots  Learn  RPAs  First.      Retrieved  April  7,  2013,  from   http://www.holloman.af.mil/news/story.asp...human  processor  (QN-­‐ MHP):  a  computational  architecture  for   multitask  performance  in  human-­‐machine  

Modeling human behaviors and reactions under dangerous environment.

Science.gov (United States)

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

Science.gov (United States)

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

Human agency beliefs influence behaviour during virtual social interactions.

Science.gov (United States)

Caruana, Nathan; Spirou, Dean; Brock, Jon

2017-01-01

In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an "intentional stance" by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants' behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative "joint attention" game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other's eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm ("Computer" condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room ("Human" condition). Those in the "Human" condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the "Computer" condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement of the application's goals.

Fused cerebral organoids model interactions between brain regions.

Science.gov (United States)

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human-Robot Interaction.

Science.gov (United States)

Abubshait, Abdulaziz; Wiese, Eva

2017-01-01

Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like robots, as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human-robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human-robot interaction. We examine this question by manipulating agent appearance (human vs. robot) and behavior (reliable vs. random) within the same paradigm and examine how congruent (human/reliable vs. robot/random) versus incongruent (human/random vs. robot/reliable) combinations of these triggers affect performance (i.e., gaze following) and attitudes (i.e., agent ratings) in human-robot interaction. The results show that both appearance and behavior affect human-robot interaction but that the two triggers seem to operate in isolation, with appearance more strongly impacting attitudes, and behavior more strongly affecting performance. The implications of these findings for human-robot interaction are discussed.

Lessons learned from HRA and human-system modeling efforts

International Nuclear Information System (INIS)

Hallbert, B.P.

1993-01-01

Human-System modeling is not unique to the field of Human Reliability Analysis (HRA). Since human factors professionals first began their explorations of human activities, they have done so with the concept of open-quotes systemclose quotes in mind. Though the two - human and system - are distinct, they can be properly understood only in terms of each other: the system provides a context in which goals and objectives for work are defined, and the human plays either a pre-defined or ad hoc role in meeting these goals. In this sense, every intervention which attempts to evaluate or improve upon some system parameter requires that an understanding of human-system interactions be developed. It is too often the case, however, that somewhere between the inception of a system and its implementation, the human-system relationships are overlooked, misunderstood, or inadequately framed. This results in mismatches between demands versus capabilities of human operators, systems which are difficult to operate, and the obvious end product-human error. The lessons learned from human system modeling provide a valuable feedback mechanism to the process of HRA, and the technologies which employ this form of modeling

Modelling the basic error tendencies of human operators

Energy Technology Data Exchange (ETDEWEB)

Reason, J.

1988-01-01

The paper outlines the primary structural features of human cognition: a limited, serial workspace interacting with a parallel distributed knowledge base. It is argued that the essential computational features of human cognition - to be captured by an adequate operator model - reside in the mechanisms by which stored knowledge structures are selected and brought into play. Two such computational 'primitives' are identified: similarity-matching and frequency-gambling. These two retrieval heuristics, it is argued, shape both the overall character of human performance (i.e. its heavy reliance on pattern-matching) and its basic error tendencies ('strong-but-wrong' responses, confirmation, similarity and frequency biases, and cognitive 'lock-up'). The various features of human cognition are integrated with a dynamic operator model capable of being represented in software form. This computer model, when run repeatedly with a variety of problem configurations, should produce a distribution of behaviours which, in toto, simulate the general character of operator performance.

Modelling the basic error tendencies of human operators

International Nuclear Information System (INIS)

Reason, J.

1988-01-01

The paper outlines the primary structural features of human cognition: a limited, serial workspace interacting with a parallel distributed knowledge base. It is argued that the essential computational features of human cognition - to be captured by an adequate operator model - reside in the mechanisms by which stored knowledge structures are selected and brought into play. Two such computational 'primitives' are identified: similarity-matching and frequency-gambling. These two retrieval heuristics, it is argued, shape both the overall character of human performance (i.e. its heavy reliance on pattern-matching) and its basic error tendencies ('strong-but-wrong' responses, confirmation, similarity and frequency biases, and cognitive 'lock-up'). The various features of human cognition are integrated with a dynamic operator model capable of being represented in software form. This computer model, when run repeatedly with a variety of problem configurations, should produce a distribution of behaviours which, in total, simulate the general character of operator performance. (author)

Modelling the basic error tendencies of human operators

International Nuclear Information System (INIS)

Reason, James

1988-01-01

The paper outlines the primary structural features of human cognition: a limited, serial workspace interacting with a parallel distributed knowledge base. It is argued that the essential computational features of human cognition - to be captured by an adequate operator model - reside in the mechanisms by which stored knowledge structures are selected and brought into play. Two such computational 'primitives' are identified: similarity-matching and frequency-gambling. These two retrieval heuristics, it is argued, shape both the overall character of human performance (i.e. its heavy reliance on pattern-matching) and its basic error tendencies ('strong-but-wrong' responses, confirmation, similarity and frequency biases, and cognitive 'lock-up'). The various features of human cognition are integrated with a dynamic operator model capable of being represented in software form. This computer model, when run repeatedly with a variety of problem configurations, should produce a distribution of behaviours which, in toto, simulate the general character of operator performance. (author)

When Humanoid Robots Become Human-Like Interaction Partners: Corepresentation of Robotic Actions

Science.gov (United States)

Stenzel, Anna; Chinellato, Eris; Bou, Maria A. Tirado; del Pobil, Angel P.; Lappe, Markus; Liepelt, Roman

2012-01-01

In human-human interactions, corepresenting a partner's actions is crucial to successfully adjust and coordinate actions with others. Current research suggests that action corepresentation is restricted to interactions between human agents facilitating social interaction with conspecifics. In this study, we investigated whether action…

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Science.gov (United States)

Kirlik, Alex

1991-01-01

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Ghost-in-the-Machine reveals human social signals for human-robot interaction.

Science.gov (United States)

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P

2015-01-01

We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer's requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human-robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience.

Human-robot interaction assessment using dynamic engagement profiles

DEFF Research Database (Denmark)

Drimus, Alin; Poltorak, Nicole

2017-01-01

-1] interval, where 0 represents disengaged and 1 fully engaged. The network shows a good accuracy at recognizing the engagement state of humans given positive emotions. A time based analysis of interaction experiments between small humanoid robots and humans provides time series of engagement estimates, which...... and is applicable to humanoid robotics as well as other related contexts.......This paper addresses the use of convolutional neural networks for image analysis resulting in an engagement metric that can be used to assess the quality of human robot interactions. We propose a method based on a pretrained convolutional network able to map emotions onto a continuous [0...

Synchronization in human musical rhythms and mutually interacting complex systems.

Science.gov (United States)

Hennig, Holger

2014-09-09

Though the music produced by an ensemble is influenced by multiple factors, including musical genre, musician skill, and individual interpretation, rhythmic synchronization is at the foundation of musical interaction. Here, we study the statistical nature of the mutual interaction between two humans synchronizing rhythms. We find that the interbeat intervals of both laypeople and professional musicians exhibit scale-free (power law) cross-correlations. Surprisingly, the next beat to be played by one person is dependent on the entire history of the other person's interbeat intervals on timescales up to several minutes. To understand this finding, we propose a general stochastic model for mutually interacting complex systems, which suggests a physiologically motivated explanation for the occurrence of scale-free cross-correlations. We show that the observed long-term memory phenomenon in rhythmic synchronization can be imitated by fractal coupling of separately recorded or synthesized audio tracks and thus applied in electronic music. Though this study provides an understanding of fundamental characteristics of timing and synchronization at the interbrain level, the mutually interacting complex systems model may also be applied to study the dynamics of other complex systems where scale-free cross-correlations have been observed, including econophysics, physiological time series, and collective behavior of animal flocks.

Human-technology interaction for standoff IED detection

Science.gov (United States)

Zhang, Evan; Zou, Yiyang; Zachrich, Liping; Fulton, Jack

2011-03-01

IEDs kill our soldiers and innocent people every day. Lessons learned from Iraq and Afghanistan clearly indicated that IEDs cannot be detected/defeated by technology alone; human-technology interaction must be engaged. In most cases, eye is the best detector, brain is the best computer, and technologies are tools, they must be used by human being properly then can achieve full functionality. In this paper, a UV Raman/fluorescence, CCD and LWIR 3 sensor fusion system for standoff IED detection and a handheld fusion system for close range IED detection are developed and demonstrated. We must train solders using their eyes or CCD/LWIR cameras to do wide area search while on the move to find small suspected area first then use the spectrometer because the laser spot is too small, to scan a one-mile long and 2-meter wide road needs 185 days although our fusion system can detect the IED in 30m with 1s interrogating time. Even if the small suspected area (e.g., 0.5mx0.5m) is found, human eyes still cannot detect the IED, soldiers must use or interact with the technology - laser based spectrometer to scan the area then they are able to detect and identify the IED in 10 minutes not 185 days. Therefore, the human-technology interaction approach will be the best solution for IED detection.

Computational modeling of blast wave interaction with a human body and assessment of traumatic brain injury

Science.gov (United States)

Tan, X. G.; Przekwas, A. J.; Gupta, R. K.

2017-11-01

The modeling of human body biomechanics resulting from blast exposure poses great challenges because of the complex geometry and the substantial material heterogeneity. We developed a detailed human body finite element model representing both the geometry and the materials realistically. The model includes the detailed head (face, skull, brain and spinal cord), the neck, the skeleton, air cavities (lungs) and the tissues. Hence, it can be used to properly model the stress wave propagation in the human body subjected to blast loading. The blast loading on the human was generated from a simulated C4 explosion. We used the highly scalable solvers in the multi-physics code CoBi for both the blast simulation and the human body biomechanics. The meshes generated for these simulations are of good quality so that relatively large time-step sizes can be used without resorting to artificial time scaling treatments. The coupled gas dynamics and biomechanics solutions were validated against the shock tube test data. The human body models were used to conduct parametric simulations to find the biomechanical response and the brain injury mechanism due to blasts impacting the human body. Under the same blast loading condition, we showed the importance of inclusion of the whole body.

Investigation of the Interaction between Patulin and Human Serum Albumin by a Spectroscopic Method, Atomic Force Microscopy, and Molecular Modeling

Directory of Open Access Journals (Sweden)

Li Yuqin

2014-01-01

Full Text Available The interaction of patulin with human serum albumin (HSA was studied in vitro under normal physiological conditions. The study was performed using fluorescence, ultraviolet-visible spectroscopy (UV-Vis, circular dichroism (CD, atomic force microscopy (AFM, and molecular modeling techniques. The quenching mechanism was investigated using the association constants, the number of binding sites, and basic thermodynamic parameters. A dynamic quenching mechanism occurred between HSA and patulin, and the binding constants (K were 2.60 × 104, 4.59 × 104, and 7.01 × 104 M−1 at 288, 300, and 310 K, respectively. Based on fluorescence resonance energy transfer, the distance between the HSA and patulin was determined to be 2.847 nm. The ΔG0, ΔH0, and ΔS0 values across various temperatures indicated that hydrophobic interaction was the predominant binding force. The UV-Vis and CD results confirmed that the secondary structure of HSA was altered in the presence of patulin. The AFM results revealed that the individual HSA molecule dimensions were larger after interaction with patulin. In addition, molecular modeling showed that the patulin-HSA complex was stabilized by hydrophobic and hydrogen bond forces. The study results suggested that a weak intermolecular interaction occurred between patulin and HSA. Overall, the results are potentially useful for elucidating the toxigenicity of patulin when it is combined with the biomolecular function effect, transmembrane transport, toxicological, testing and other experiments.

Comparison of dogs and humans in visual scanning of social interaction.

Science.gov (United States)

Törnqvist, Heini; Somppi, Sanni; Koskela, Aija; Krause, Christina M; Vainio, Outi; Kujala, Miiamaaria V

2015-09-01

Previous studies have demonstrated similarities in gazing behaviour of dogs and humans, but comparisons under similar conditions are rare, and little is known about dogs' visual attention to social scenes. Here, we recorded the eye gaze of dogs while they viewed images containing two humans or dogs either interacting socially or facing away: the results were compared with equivalent data measured from humans. Furthermore, we compared the gazing behaviour of two dog and two human populations with different social experiences: family and kennel dogs; dog experts and non-experts. Dogs' gazing behaviour was similar to humans: both species gazed longer at the actors in social interaction than in non-social images. However, humans gazed longer at the actors in dog than human social interaction images, whereas dogs gazed longer at the actors in human than dog social interaction images. Both species also made more saccades between actors in images representing non-conspecifics, which could indicate that processing social interaction of non-conspecifics may be more demanding. Dog experts and non-experts viewed the images very similarly. Kennel dogs viewed images less than family dogs, but otherwise their gazing behaviour did not differ, indicating that the basic processing of social stimuli remains similar regardless of social experiences.

Dynamic perceptions of human-likeness while interacting with a social robot

NARCIS (Netherlands)

Ruijten, P.A.M.; Cuijpers, R.H.

2017-01-01

In human-robot interaction research, much attention is given to the development of socially assistive robots that can have natural interactions with their users. One crucial aspect of such natural interactions is that the robot is perceived as human-like. Much research already exists that

Human-Computer Interaction, Tourism and Cultural Heritage

Science.gov (United States)

Cipolla Ficarra, Francisco V.

We present a state of the art of the human-computer interaction aimed at tourism and cultural heritage in some cities of the European Mediterranean. In the work an analysis is made of the main problems deriving from training understood as business and which can derail the continuous growth of the HCI, the new technologies and tourism industry. Through a semiotic and epistemological study the current mistakes in the context of the interrelations of the formal and factual sciences will be detected and also the human factors that have an influence on the professionals devoted to the development of interactive systems in order to safeguard and boost cultural heritage.

Role of frameworks, models, data, and judgment in human reliability analysis

Energy Technology Data Exchange (ETDEWEB)

Hannaman, G W

1986-05-01

Many advancements in the methods for treating human interactions in PRA studies have occurred in the last decade. These advancements appear to increase the capability of PRAs to extend beyond just the assessment of the human's importance to safety. However, variations in the application of these advanced models, data, and judgements in recent PRAs make quantitative comparisons among studies extremely difficult. This uncertainty in the analysis diminishes the usefulness of the PRA study for upgrading procedures, enhancing traning, simulator design, technical specification guidance, and for aid in designing the man-machine interface. Hence, there is a need for a framework to guide analysts in incorporating human interactions into the PRA systems analyses so that future users of a PRA study will have a clear understanding of the approaches, models, data, and assumptions which were employed in the initial study. This paper describes the role of the systematic human action reliability procedure (SHARP) in providing a road map through the complex terrain of human reliability that promises to improve the reproducibility of such analysis in the areas of selecting the models, data, representations, and assumptions. Also described is the role that a human cognitive reliability model can have in collecting data from simulators and helping analysts assign human reliability parameters in a PRA study. Use of these systematic approaches to perform or upgrade existing PRAs promises to make PRA studies more useful as risk management tools.

Human-computer systems interaction backgrounds and applications 3

CERN Document Server

Kulikowski, Juliusz; Mroczek, Teresa; Wtorek, Jerzy

2014-01-01

This book contains an interesting and state-of the art collection of papers on the recent progress in Human-Computer System Interaction (H-CSI). It contributes the profound description of the actual status of the H-CSI field and also provides a solid base for further development and research in the discussed area. The contents of the book are divided into the following parts: I. General human-system interaction problems; II. Health monitoring and disabled people helping systems; and III. Various information processing systems. This book is intended for a wide audience of readers who are not necessarily experts in computer science, machine learning or knowledge engineering, but are interested in Human-Computer Systems Interaction. The level of particular papers and specific spreading-out into particular parts is a reason why this volume makes fascinating reading. This gives the reader a much deeper insight than he/she might glean from research papers or talks at conferences. It touches on all deep issues that ...

Mobile human-computer interaction perspective on mobile learning

CSIR Research Space (South Africa)

Botha, Adèle

2010-10-01

Full Text Available Applying a Mobile Human Computer Interaction (MHCI) view to the domain of education using Mobile Learning (Mlearning), the research outlines its understanding of the influences and effects of different interactions on the use of mobile technology...

The Science of Human Interaction and Teaching

Science.gov (United States)

Yano, Kazuo

2013-01-01

There is a missing link between our understanding of teaching as high-level social phenomenon and teaching as a physiological phenomenon of brain activity. We suggest that the science of human interaction is the missing link. Using over one-million days of human-behavior data, we have discovered that "collective activenes" (CA), which indicates…

Functionalized anatomical models for EM-neuron Interaction modeling

Science.gov (United States)

Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

2016-06-01

The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.

2013-07-12

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about experimentally and computationally detected human PPIs as well as their corresponding annotation data. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://biotools.ceid.upatras.gr/hint-kb/), a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, cal-culatesasetoffeaturesofinterest and computesaconfidence score for every candidate protein interaction. This confidence score is essential for filtering the false positive interactions which are present in existing databases, predicting new protein interactions and measuring the frequency of each true protein interaction. For this reason, a novel machine learning hybrid methodology, called (Evolutionary Kalman Mathematical Modelling—EvoKalMaModel), was used to achieve an accurate and interpretable scoring methodology. The experimental results indicated that the proposed scoring scheme outperforms existing computational methods for the prediction of PPIs.

Pose Estimation and Adaptive Robot Behaviour for Human-Robot Interaction

DEFF Research Database (Denmark)

Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen

2009-01-01

Abstract—This paper introduces a new method to determine a person’s pose based on laser range measurements. Such estimates are typically a prerequisite for any human-aware robot navigation, which is the basis for effective and timeextended interaction between a mobile robot and a human. The robot......’s pose. The resulting pose estimates are used to identify humans who wish to be approached and interacted with. The interaction motion of the robot is based on adaptive potential functions centered around the person that respect the persons social spaces. The method is tested in experiments...

Structural model for the interaction of a designed Ankyrin Repeat Protein with the human epidermal growth factor receptor 2.

Directory of Open Access Journals (Sweden)

V Chandana Epa

Full Text Available Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2. HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84-1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions.

Modeling Child–Nature Interaction in a Nature Preschool: A Proof of Concept

Directory of Open Access Journals (Sweden)

Peter H. Kahn

2018-05-01

Full Text Available This article provides a proof of concept for an approach to modeling child–nature interaction based on the idea of interaction patterns: characterizations of essential features of interaction between humans and nature, specified abstractly enough such that countless different instantiations of each one can occur – in more domestic or wild forms – given different types of nature, people, and purposes. The model draws from constructivist psychology, ecological psychology, and evolutionary psychology, and is grounded in observational data collected through a time-sampling methodology at a nature preschool. Through using a nature language that emphasizes ontogenetic and phylogenetic significance, seven keystone interaction patterns are described for this nature preschool: using one’s body vigorously in nature, striking wood on wood, constructing shelter, being in solitude in nature, lying on earth, cohabiting with a wild animal, and being outside in weather. These 7 interactions patterns are then brought together with 13 other patterns published elsewhere to provide a total of 20 keystone interaction patterns that begin to fill out the model, and to show its promise. Discussion focuses on what the model aims to be in terms of both product and process, on what work the model can currently do, and how to further develop the model.

Gene expression profiles of human dendritic cells interacting with Aspergillus fumigatus in a bilayer model of the alveolar epithelium/endothelium interface.

Directory of Open Access Journals (Sweden)

Charles Oliver Morton

Full Text Available The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549 and endothelium (human pulmonary artery epithelial cells, HPAEC on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC, monocyte-derived DC (moDC and myeloid DC (mDC, were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA.

Application of postured human model for SAR measurements

Science.gov (United States)

Vuchkovikj, M.; Munteanu, I.; Weiland, T.

2013-07-01

In the last two decades, the increasing number of electronic devices used in day-to-day life led to a growing interest in the study of the electromagnetic field interaction with biological tissues. The design of medical devices and wireless communication devices such as mobile phones benefits a lot from the bio-electromagnetic simulations in which digital human models are used. The digital human models currently available have an upright position which limits the research activities in realistic scenarios, where postured human bodies must be considered. For this reason, a software application called "BodyFlex for CST STUDIO SUITE" was developed. In its current version, this application can deform the voxel-based human model named HUGO (Dipp GmbH, 2010) to allow the generation of common postures that people use in normal life, ensuring the continuity of tissues and conserving the mass to an acceptable level. This paper describes the enhancement of the "BodyFlex" application, which is related to the movements of the forearm and the wrist of a digital human model. One of the electromagnetic applications in which the forearm and the wrist movement of a voxel based human model has a significant meaning is the measurement of the specific absorption rate (SAR) when a model is exposed to a radio frequency electromagnetic field produced by a mobile phone. Current SAR measurements of the exposure from mobile phones are performed with the SAM (Specific Anthropomorphic Mannequin) phantom which is filled with a dispersive but homogeneous material. We are interested what happens with the SAR values if a realistic inhomogeneous human model is used. To this aim, two human models, a homogeneous and an inhomogeneous one, in two simulation scenarios are used, in order to examine and observe the differences in the results for the SAR values.

Human-Computer Interaction and Information Management Research Needs

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — In a visionary future, Human-Computer Interaction HCI and Information Management IM have the potential to enable humans to better manage their lives through the use...

A Simple Model for Human and Nature Interaction

Science.gov (United States)

Motesharrei, S.; Rivas, J.; Kalnay, E.

2012-12-01

There are widespread concerns that current trends in population and resource-use are unsustainable, but the possibilities of an overshoot and collapse remain unclear and controversial. Collapses of civilizations have occurred many times in the past 5000 years, often followed by centuries of economic, intellectual, and population decline. Many different natural and social phenomena have been invoked to explain specific collapses, but a general explanation remains elusive. Two important features seem to appear across societies that have collapsed: Ecological Strain and Economic Stratification. Our new model (Human And Nature DYnamics, HANDY) has just four equations that describe the evolution of Elites, Commoners, Nature, and Wealth. Mechanisms leading to collapse are discussed and the measure "Carrying Capacity" is developed and defined. The model shows that societal collapse can happen due to either one of two independent factors: (1) over-consumption of natural resources, and/or (2) deep inequity between Elites and Commoners. The model also portrays two distinct types of collapse: (i) collapse followed by recovery of nature, and (ii) full collapse. The model suggests that the estimation of Carrying Capacity is a practical means for early detection of a collapse. Collapse can be avoided, and population can reach a sustainable equilibrium, if the rate of depletion of nature is reduced to a sustainable level, and if resources are distributed in a reasonably equitable fashion.; A type-ii (full) collapse is shown in this figure. With high inequality and high depletion, societies are doomed to collapse. Wealth starts to decrease when population rises above the carrying capacity. The large gap between carrying capacity and its maximum is a result of depletion factor being much larger than the sustainable limit. ; It is possible to overshoot, oscillate, and eventually converge to an equilibrium, even in an inequitable society. However, it requires policies that control

A systems model for immune cell interactions unravels the mechanism of inflammation in human skin.

Science.gov (United States)

Valeyev, Najl V; Hundhausen, Christian; Umezawa, Yoshinori; Kotov, Nikolay V; Williams, Gareth; Clop, Alex; Ainali, Crysanthi; Ouzounis, Christos; Tsoka, Sophia; Nestle, Frank O

2010-12-02

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.

A systems model for immune cell interactions unravels the mechanism of inflammation in human skin.

Directory of Open Access Journals (Sweden)

Najl V Valeyev

2010-12-01

Full Text Available Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.

Modeling and prediction of human word search behavior in interactive machine translation

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Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

2017-12-01

As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles

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Hwisoo Eom

2015-06-01

Full Text Available A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles.

Science.gov (United States)

Eom, Hwisoo; Lee, Sang Hun

2015-06-12

A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC) and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

Human-robot interaction modeling and simulation of supervisory control and situational awareness during field experimentation with military manned and unmanned ground vehicles

Science.gov (United States)

Johnson, Tony; Metcalfe, Jason; Brewster, Benjamin; Manteuffel, Christopher; Jaswa, Matthew; Tierney, Terrance

2010-04-01

The proliferation of intelligent systems in today's military demands increased focus on the optimization of human-robot interactions. Traditional studies in this domain involve large-scale field tests that require humans to operate semiautomated systems under varying conditions within military-relevant scenarios. However, provided that adequate constraints are employed, modeling and simulation can be a cost-effective alternative and supplement. The current presentation discusses a simulation effort that was executed in parallel with a field test with Soldiers operating military vehicles in an environment that represented key elements of the true operational context. In this study, "constructive" human operators were designed to represent average Soldiers executing supervisory control over an intelligent ground system. The constructive Soldiers were simulated performing the same tasks as those performed by real Soldiers during a directly analogous field test. Exercising the models in a high-fidelity virtual environment provided predictive results that represented actual performance in certain aspects, such as situational awareness, but diverged in others. These findings largely reflected the quality of modeling assumptions used to design behaviors and the quality of information available on which to articulate principles of operation. Ultimately, predictive analyses partially supported expectations, with deficiencies explicable via Soldier surveys, experimenter observations, and previously-identified knowledge gaps.

Mathematical Analysis for Non-reciprocal-interaction-based Model of Collective Behavior

Science.gov (United States)

Kano, Takeshi; Osuka, Koichi; Kawakatsu, Toshihiro; Ishiguro, Akio

2017-12-01

In many natural and social systems, collective behaviors emerge as a consequence of non-reciprocal interaction between their constituents. As a first step towards understanding the core principle that underlies these phenomena, we previously proposed a minimal model of collective behavior based on non-reciprocal interactions by drawing inspiration from friendship formation in human society, and demonstrated via simulations that various non-trivial patterns emerge by changing parameters. In this study, a mathematical analysis of the proposed model wherein the system size is small is performed. Through the analysis, the mechanism of the transition between several patterns is elucidated.

The epistemology and ontology of human-computer interaction

NARCIS (Netherlands)

Brey, Philip A.E.

2005-01-01

This paper analyzes epistemological and ontological dimensions of Human-Computer Interaction (HCI) through an analysis of the functions of computer systems in relation to their users. It is argued that the primary relation between humans and computer systems has historically been epistemic:

Singularity now: using the ventricular assist device as a model for future human-robotic physiology.

Science.gov (United States)

Martin, Archer K

2016-04-01

In our 21 st century world, human-robotic interactions are far more complicated than Asimov predicted in 1942. The future of human-robotic interactions includes human-robotic machine hybrids with an integrated physiology, working together to achieve an enhanced level of baseline human physiological performance. This achievement can be described as a biological Singularity. I argue that this time of Singularity cannot be met by current biological technologies, and that human-robotic physiology must be integrated for the Singularity to occur. In order to conquer the challenges we face regarding human-robotic physiology, we first need to identify a working model in today's world. Once identified, this model can form the basis for the study, creation, expansion, and optimization of human-robotic hybrid physiology. In this paper, I present and defend the line of argument that currently this kind of model (proposed to be named "IshBot") can best be studied in ventricular assist devices - VAD.

Young Investigator Program (8.5): Preventing Complex Failures of Human Interactive Systems with Erroneous Behavior Generation and Robust Human Task Behavior Patterns

Science.gov (United States)

2017-11-13

Chairman, Subcommittee on Oversight and Investigations, Conmittee on Energy and Commerce , House of Representatives. Technical Report GAO/OSI-93-4, 1993...Bolton & E . J. Bass. Formally verifying human-automation interaction as part of a system model: Limitations and tradeoffs. Innovations in Systems and...Software Engineering: A NASA Journal, 6(3):219–231, 2010. [5] M. L. Bolton & E . J. Bass. Using task analytic models to visualize model checker

Identification of Molecular Fingerprints in Human Heat Pain Thresholds by Use of an Interactive Mixture Model R Toolbox (AdaptGauss).

Science.gov (United States)

Ultsch, Alfred; Thrun, Michael C; Hansen-Goos, Onno; Lötsch, Jörn

2015-10-28

Biomedical data obtained during cell experiments, laboratory animal research, or human studies often display a complex distribution. Statistical identification of subgroups in research data poses an analytical challenge. Here were introduce an interactive R-based bioinformatics tool, called "AdaptGauss". It enables a valid identification of a biologically-meaningful multimodal structure in the data by fitting a Gaussian mixture model (GMM) to the data. The interface allows a supervised selection of the number of subgroups. This enables the expectation maximization (EM) algorithm to adapt more complex GMM than usually observed with a noninteractive approach. Interactively fitting a GMM to heat pain threshold data acquired from human volunteers revealed a distribution pattern with four Gaussian modes located at temperatures of 32.3, 37.2, 41.4, and 45.4 °C. Noninteractive fitting was unable to identify a meaningful data structure. Obtained results are compatible with known activity temperatures of different TRP ion channels suggesting the mechanistic contribution of different heat sensors to the perception of thermal pain. Thus, sophisticated analysis of the modal structure of biomedical data provides a basis for the mechanistic interpretation of the observations. As it may reflect the involvement of different TRP thermosensory ion channels, the analysis provides a starting point for hypothesis-driven laboratory experiments.

In our own image? Emotional and neural processing differences when observing human-human vs human-robot interactions.

Science.gov (United States)

Wang, Yin; Quadflieg, Susanne

2015-11-01

Notwithstanding the significant role that human-robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human-human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal-parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. © The Author (2015). Published by Oxford University Press.

Exhaustive Genome-Wide Search for SNP-SNP Interactions Across 10 Human Diseases

Directory of Open Access Journals (Sweden)

William Murk

2016-07-01

Full Text Available The identification of statistical SNP-SNP interactions may help explain the genetic etiology of many human diseases, but exhaustive genome-wide searches for these interactions have been difficult, due to a lack of power in most datasets. We aimed to use data from the Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA study to search for SNP-SNP interactions associated with 10 common diseases. FastEpistasis and BOOST were used to evaluate all pairwise interactions among approximately N = 300,000 single nucleotide polymorphisms (SNPs with minor allele frequency (MAF ≥ 0.15, for the dichotomous outcomes of allergic rhinitis, asthma, cardiac disease, depression, dermatophytosis, type 2 diabetes, dyslipidemia, hemorrhoids, hypertensive disease, and osteoarthritis. A total of N = 45,171 subjects were included after quality control steps were applied. These data were divided into discovery and replication subsets; the discovery subset had > 80% power, under selected models, to detect genome-wide significant interactions (P < 10−12. Interactions were also evaluated for enrichment in particular SNP features, including functionality, prior disease relevancy, and marginal effects. No interaction in any disease was significant in both the discovery and replication subsets. Enrichment analysis suggested that, for some outcomes, interactions involving SNPs with marginal effects were more likely to be nominally replicated, compared to interactions without marginal effects. If SNP-SNP interactions play a role in the etiology of the studied conditions, they likely have weak effect sizes, involve lower-frequency variants, and/or involve complex models of interaction that are not captured well by the methods that were utilized.

More-Realistic Digital Modeling of a Human Body

Science.gov (United States)

Rogge, Renee

2010-01-01

A MATLAB computer program has been written to enable improved (relative to an older program) modeling of a human body for purposes of designing space suits and other hardware with which an astronaut must interact. The older program implements a kinematic model based on traditional anthropometric measurements that do provide important volume and surface information. The present program generates a three-dimensional (3D) whole-body model from 3D body-scan data. The program utilizes thin-plate spline theory to reposition the model without need for additional scans.

Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling.

Directory of Open Access Journals (Sweden)

Lulla Opatowski

2018-02-01

Full Text Available Evidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, which have become critical in public health decision-making. Yet models usually focus on influenza virus acquisition and infection alone, thereby making broad oversimplifications of pathogen ecology. Herein, we report evidence of influenza virus interactions with bacteria and viruses and systematically review the modelling studies that have incorporated interactions. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitidis, respiratory syncytial virus (RSV, human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. The notable exception is the pneumococcus-influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approach to test biological hypotheses on interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and possible misinterpretation, and we illustrate the impact of interactions on public health surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures. Finally, we identify the public health, surveillance, modelling, and biological challenges and propose avenues of research for the coming years.

Quantifying Engagement: Measuring Player Involvement in Human-Avatar Interactions

Science.gov (United States)

Norris, Anne E.; Weger, Harry; Bullinger, Cory; Bowers, Alyssa

2014-01-01

This research investigated the merits of using an established system for rating behavioral cues of involvement in human dyadic interactions (i.e., face-to-face conversation) to measure involvement in human-avatar interactions. Gameplay audio-video and self-report data from a Feasibility Trial and Free Choice study of an effective peer resistance skill building simulation game (DRAMA-RAMA™) were used to evaluate reliability and validity of the rating system when applied to human-avatar interactions. The Free Choice study used a revised game prototype that was altered to be more engaging. Both studies involved girls enrolled in a public middle school in Central Florida that served a predominately Hispanic (greater than 80%), low-income student population. Audio-video data were coded by two raters, trained in the rating system. Self-report data were generated using measures of perceived realism, predictability and flow administered immediately after game play. Hypotheses for reliability and validity were supported: Reliability values mirrored those found in the human dyadic interaction literature. Validity was supported by factor analysis, significantly higher levels of involvement in Free Choice as compared to Feasibility Trial players, and correlations between involvement dimension sub scores and self-report measures. Results have implications for the science of both skill-training intervention research and game design. PMID:24748718

Interaction of an antiepileptic drug, lamotrigine with human serum albumin (HSA): Application of spectroscopic techniques and molecular modeling methods.

Science.gov (United States)

Poureshghi, Fatemeh; Ghandforoushan, Parisa; Safarnejad, Azam; Soltani, Somaieh

2017-01-01

Lamotrigine (an epileptic drug) interaction with human serum albumin (HSA) was investigated by fluorescence, UV-Vis, FTIR, CD spectroscopic techniques, and molecular modeling methods. Binding constant (K b ) of 5.74×10 3 and number of binding site of 0.97 showed that there is a slight interaction between lamotrigine and HSA. Thermodynamic studies was constructed using the flourimetric titrations in three different temperatures and the resulted data used to calculate the parameters using Vant Hoff equation. Decreased Stern Volmer quenching constant by enhanced temperature revealed the static quenching mechanism. Negative standard enthalpy (ΔH) and standard entropy (ΔS) changes indicated that van der Waals interactions and hydrogen bonds were dominant forces which facilitate the binding of Lamotrigine to HSA, the results were confirmed by molecular docking studies which showed no hydrogen binding. The FRET studies showed that there is a possibility of energy transfer between Trp214 and lamotrigine. Also the binding of lamotrigine to HSA in the studied concentrations was not as much as many other drugs, but the secondary structure of the HSA was significantly changed following the interaction in a way that α-helix percentage was reduced from 67% to 57% after the addition of lamotrigine in the molar ratio of 4:1 to HSA. According to the docking studies, lamotrigine binds to IB site preferably. Copyright © 2016. Published by Elsevier B.V.

Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

Science.gov (United States)

Nath, Abhigyan; Kumari, Priyanka; Chaube, Radha

2018-01-01

Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug targets and their interactions can be very useful for drug repurposing. Supervised machine learning methods have been very useful in drug target prediction and in prediction of drug target interactions. Here, we describe the details for developing prediction models using supervised learning techniques for human drug target prediction and their interactions.

An Integrated Human System Interaction (HSI) Framework for Human-Agent Team Collaboration, Phase I

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National Aeronautics and Space Administration — The NASA commitment to a human presence in space exploration results in the interaction of humans with challenging environments in space, on lunar, and on planetary...

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

Science.gov (United States)

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Velocity-curvature patterns limit human-robot physical interaction.

Science.gov (United States)

Maurice, Pauline; Huber, Meghan E; Hogan, Neville; Sternad, Dagmar

2018-01-01

Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

OpenAIRE

Mavridis, Nikolaos

2014-01-01

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-lookin...

A motivation model for interaction between parent and child based on the need for relatedness

Directory of Open Access Journals (Sweden)

Masaki eOgino

2013-09-01

Full Text Available In communication between parents and children, various kinds of intrinsic and extrinsic motivations affect the emotions that encourage actions to promote more interactions. This paper presents a motivation model for the interaction between an infant and a caregiver which models relatedness, one of the most important basic psychological needs, as a variable that increases with experiences of emotion sharing. Relatedness is not only an important factor of pleasure but also a meta-factor which affects other factors such as stress and emotion mirroring. In the simulation experiment, two agents, each of which has the proposed motivation model, show emotional communication depending on the relatedness level that is similar to actual human communication. Especially, the proposed model can reproduce a finding described by the "still-face paradigm", in which an infant shows unpleasant emotion when a caregiver suddenly stops facial expressions. The proposed model is implemented in an artificial agent with a recognition system for gestures and facial expressions. The baby-like agent successfully interacts with an actual human and shows reactions comparable to the "still-face paradigm".

Human-computer interaction handbook fundamentals, evolving technologies and emerging applications

CERN Document Server

Sears, Andrew

2007-01-01

This second edition of The Human-Computer Interaction Handbook provides an updated, comprehensive overview of the most important research in the field, including insights that are directly applicable throughout the process of developing effective interactive information technologies. It features cutting-edge advances to the scientific knowledge base, as well as visionary perspectives and developments that fundamentally transform the way in which researchers and practitioners view the discipline. As the seminal volume of HCI research and practice, The Human-Computer Interaction Handbook feature

Experimental and mathematical modeling methods for the investigation of toxicological interactions

International Nuclear Information System (INIS)

El-Masri, Hisham A.

2007-01-01

While procedures have been developed and used for many years to assess risk and determine acceptable exposure levels to individual chemicals, most cases of environmental contamination can result in concurrent or sequential exposure to more than one chemical. Toxicological predictions of such combinations must be based on an understanding of the mechanisms of action and interaction of the components of the mixtures. Statistical and experimental methods test the existence of toxicological interactions in a mixture. However, these methods are limited to experimental data ranges for which they are derived, in addition to limitations caused by response differences from experimental animals to humans. Empirical methods such as isobolograms, median-effect principle and response surface methodology (RSM) are based on statistical experimental design and regression of data. For that reason, the predicted response surfaces can be used for extrapolation across dose regions where interaction mechanisms are not anticipated to change. In general, using these methods for predictions can be problematic without including biologically based mechanistic descriptions that can account for dose and species differences. Mechanistically based models, such as physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, include explicit descriptions of interaction mechanisms which are related to target tissues levels. These models include dose-dependent mechanistic hypotheses of toxicological interactions which can be tested by model-directed experimental design and used to identify dose regions where interactions are not significant

Exploring cultural factors in human-robot interaction : A matter of personality?

NARCIS (Netherlands)

Weiss, Astrid; Evers, Vanessa

2011-01-01

This paper proposes an experimental study to investigate task-dependence and cultural-background dependence of the personality trait attribution on humanoid robots. In Human-Robot Interaction, as well as in Human-Agent Interaction research, the attribution of personality traits towards intelligent

Benefits of Subliminal Feedback Loops in Human-Computer Interaction

OpenAIRE

Walter Ritter

2011-01-01

A lot of efforts have been directed to enriching human-computer interaction to make the user experience more pleasing or efficient. In this paper, we briefly present work in the fields of subliminal perception and affective computing, before we outline a new approach to add analog communication channels to the human-computer interaction experience. In this approach, in addition to symbolic predefined mappings of input to output, a subliminal feedback loop is used that provides feedback in evo...

Review on modeling heat transfer and thermoregulatory responses in human body.

Science.gov (United States)

Fu, Ming; Weng, Wenguo; Chen, Weiwang; Luo, Na

2016-12-01

Several mathematical models of human thermoregulation have been developed, contributing to a deep understanding of thermal responses in different thermal conditions and applications. In these models, the human body is represented by two interacting systems of thermoregulation: the controlling active system and the controlled passive system. This paper reviews the recent research of human thermoregulation models. The accuracy and scope of the thermal models are improved, for the consideration of individual differences, integration to clothing models, exposure to cold and hot conditions, and the changes of physiological responses for the elders. The experimental validated methods for human subjects and manikin are compared. The coupled method is provided for the manikin, controlled by the thermal model as an active system. Computational Fluid Dynamics (CFD) is also used along with the manikin or/and the thermal model, to evaluate the thermal responses of human body in various applications, such as evaluation of thermal comfort to increase the energy efficiency, prediction of tolerance limits and thermal acceptability exposed to hostile environments, indoor air quality assessment in the car and aerospace industry, and design protective equipment to improve function of the human activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Preliminary Study of Peer-to-Peer Human-Robot Interaction

Science.gov (United States)

Fong, Terrence; Flueckiger, Lorenzo; Kunz, Clayton; Lees, David; Schreiner, John; Siegel, Michael; Hiatt, Laura M.; Nourbakhsh, Illah; Simmons, Reid; Ambrose, Robert

2006-01-01

The Peer-to-Peer Human-Robot Interaction (P2P-HRI) project is developing techniques to improve task coordination and collaboration between human and robot partners. Our work is motivated by the need to develop effective human-robot teams for space mission operations. A central element of our approach is creating dialogue and interaction tools that enable humans and robots to flexibly support one another. In order to understand how this approach can influence task performance, we recently conducted a series of tests simulating a lunar construction task with a human-robot team. In this paper, we describe the tests performed, discuss our initial results, and analyze the effect of intervention on task performance.

Computing the stresses and deformations of the human eye components due to a high explosive detonation using fluid-structure interaction model.

Science.gov (United States)

Karimi, Alireza; Razaghi, Reza; Navidbakhsh, Mahdi; Sera, Toshihiro; Kudo, Susumu

2016-05-01

In spite the fact that a very small human body surface area is comprised by the eye, its wounds due to detonation have recently been dramatically amplified. Although many efforts have been devoted to measure injury of the globe, there is still a lack of knowledge on the injury mechanism due to Primary Blast Wave (PBW). The goal of this study was to determine the stresses and deformations of the human eye components, including the cornea, aqueous, iris, ciliary body, lens, vitreous, retina, sclera, optic nerve, and muscles, attributed to PBW induced by trinitrotoluene (TNT) explosion via a Lagrangian-Eulerian computational coupling model. Magnetic Resonance Imaging (MRI) was employed to establish a Finite Element (FE) model of the human eye according to a normal human eye. The solid components of the eye were modelled as Lagrangian mesh, while an explosive TNT, air domain, and aqueous were modelled using Arbitrary Lagrangian-Eulerian (ALE) mesh. Nonlinear dynamic FE simulations were accomplished using the explicit FE code, namely LS-DYNA. In order to simulate the blast wave generation, propagation, and interaction with the eye, the ALE formulation with Jones-Wilkins-Lee (JWL) equation defining the explosive material were employed. The results revealed a peak stress of 135.70kPa brought about by detonation upsurge on the cornea at the distance of 25cm. The highest von Mises stresses were observed on the sclera (267.3kPa), whereas the lowest one was seen on the vitreous body (0.002kPa). The results also showed a relatively high resultant displacement for the macula as well as a high variation for the radius of curvature for the cornea and lens, which can result in both macular holes, optic nerve damage and, consequently, vision loss. These results may have implications not only for understanding the value of stresses and strains in the human eye components but also giving an outlook about the process of PBW triggers damage to the eye. Copyright © 2016 Elsevier Ltd

Human-Robot Interaction Directed Research Project

Science.gov (United States)

Sandor, Aniko; Cross, Ernest V., II; Chang, Mai Lee

2014-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces and command modalities affect the human's ability to perform tasks accurately, efficiently, and effectively when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. This DRP concentrates on three areas associated with interfaces and command modalities in HRI which are applicable to NASA robot systems: 1) Video Overlays, 2) Camera Views, and 3) Command Modalities. The first study focused on video overlays that investigated how Augmented Reality (AR) symbology can be added to the human-robot interface to improve teleoperation performance. Three types of AR symbology were explored in this study, command guidance (CG), situation guidance (SG), and both (SCG). CG symbology gives operators explicit instructions on what commands to input, whereas SG symbology gives operators implicit cues so that operators can infer the input commands. The combination of CG and SG provided operators with explicit and implicit cues allowing the operator to choose which symbology to utilize. The objective of the study was to understand how AR symbology affects the human operator's ability to align a robot arm to a target using a flight stick and the ability to allocate attention between the symbology and external views of the world. The study evaluated the effects type of symbology (CG and SG) has on operator tasks performance and attention allocation during teleoperation of a robot arm. The second study expanded on the first study by evaluating the effects of the type of

Modelling human eye under blast loading.

Science.gov (United States)

Esposito, L; Clemente, C; Bonora, N; Rossi, T

2015-01-01

Primary blast injury (PBI) is the general term that refers to injuries resulting from the mere interaction of a blast wave with the body. Although few instances of primary ocular blast injury, without a concomitant secondary blast injury from debris, are documented, some experimental studies demonstrate its occurrence. In order to investigate PBI to the eye, a finite element model of the human eye using simple constitutive models was developed. The material parameters were calibrated by a multi-objective optimisation performed on available eye impact test data. The behaviour of the human eye and the dynamics of mechanisms occurring under PBI loading conditions were modelled. For the generation of the blast waves, different combinations of explosive (trinitrotoluene) mass charge and distance from the eye were analysed. An interpretation of the resulting pressure, based on the propagation and reflection of the waves inside the eye bulb and orbit, is proposed. The peculiar geometry of the bony orbit (similar to a frustum cone) can induce a resonance cavity effect and generate a pressure standing wave potentially hurtful for eye tissues.

Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

International Nuclear Information System (INIS)

Druce, C.H.; Moszkowski, S.A.

1986-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested

Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

Energy Technology Data Exchange (ETDEWEB)

Druce, C.H.; Moszkowski, S.A.

1986-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested.

Characterization of human-dog social interaction using owner report.

Science.gov (United States)

Lit, Lisa; Schweitzer, Julie B; Oberbauer, Anita M

2010-07-01

Dog owners were surveyed for observations of social behaviors in their dogs, using questions adapted from the human Autism Diagnostic Observation Schedule (ADOS) pre-verbal module. Using 939 responses for purebred and mixed-breed dogs, three factors were identified: initiation of reciprocal social behaviors (INIT), response to social interactions (RSPNS), and communication (COMM). There were small or no effects of sex, age, breed group or training. For six breeds with more than 35 responses (Border Collie, Rough Collie, German Shepherd, Golden Retriever, Labrador Retriever, Standard Poodle), the behaviors eye contact with humans, enjoyment in interactions with human interaction, and name recognition demonstrated little variability across breeds, while asking for objects, giving/showing objects to humans, and attempts to direct humans' attention showed higher variability across these breeds. Breeds with genetically similar backgrounds had similar response distributions for owner reports of dog response to pointing. When considering these breeds according to the broad categories of "herders" and "retrievers," owners reported that the "herders" used more eye contact and vocalization, while the "retrievers" used more body contact. Information regarding social cognitive abilities in dogs provided by owner report suggest that there is variability across many social cognitive abilities in dogs and offers direction for further experimental investigations. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Interactive Dimensioning of Parametric Models

KAUST Repository

Kelly, T.

2015-06-22

We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.

Comparison of Experimental Models for Predicting Laser Tissue Interaction from 3.8-Micron Lasers

National Research Council Canada - National Science Library

Williams, Charles Melville

2004-01-01

The purpose of this study was to compare and contrast the effects of single 3.8-micron laser pulses in an in-vitro and in-vivo model of human skin and to demonstrate the efficacy of in-vitro laser tissue interaction models...

Human Work Interaction Design

DEFF Research Database (Denmark)

Lopes, Arminda; Ørngreen, Rikke

. The papers reflect many different areas and address many complex and diverse work domains, ranging from medical user interfaces, work and speech interactions at elderly care facilities, greenhouse climate control, navigating through large oil industry engineering models, crisis management, library usability...

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

Directory of Open Access Journals (Sweden)

Prashanthi Karyala

2016-09-01

Full Text Available Dengue virus (DENV is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/.

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

Science.gov (United States)

Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma

2016-09-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).

Interacting boson model with surface delta interaction between nucleons

International Nuclear Information System (INIS)

Druce, C.; Moszkowski, S.A.

1984-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. The authors have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson proton-boson interaction for the case of degenerate orbits

Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.

Directory of Open Access Journals (Sweden)

Suyu Mei

Full Text Available Reconstruction of host-pathogen protein interaction networks is of great significance to reveal the underlying microbic pathogenesis. However, the current experimentally-derived networks are generally small and should be augmented by computational methods for less-biased biological inference. From the point of view of computational modelling, data scarcity, data unavailability and negative data sampling are the three major problems for host-pathogen protein interaction networks reconstruction. In this work, we are motivated to address the three concerns and propose a probability weighted ensemble transfer learning model for HIV-human protein interaction prediction (PWEN-TLM, where support vector machine (SVM is adopted as the individual classifier of the ensemble model. In the model, data scarcity and data unavailability are tackled by homolog knowledge transfer. The importance of homolog knowledge is measured by the ROC-AUC metric of the individual classifiers, whose outputs are probability weighted to yield the final decision. In addition, we further validate the assumption that only the homolog knowledge is sufficient to train a satisfactory model for host-pathogen protein interaction prediction. Thus the model is more robust against data unavailability with less demanding data constraint. As regards with negative data construction, experiments show that exclusiveness of subcellular co-localized proteins is unbiased and more reliable than random sampling. Last, we conduct analysis of overlapped predictions between our model and the existing models, and apply the model to novel host-pathogen PPIs recognition for further biological research.

Social interaction enhances motor resonance for observed human actions.

Science.gov (United States)

Hogeveen, Jeremy; Obhi, Sukhvinder S

2012-04-25

Understanding the neural basis of social behavior has become an important goal for cognitive neuroscience and a key aim is to link neural processes observed in the laboratory to more naturalistic social behaviors in real-world contexts. Although it is accepted that mirror mechanisms contribute to the occurrence of motor resonance (MR) and are common to action execution, observation, and imitation, questions remain about mirror (and MR) involvement in real social behavior and in processing nonhuman actions. To determine whether social interaction primes the MR system, groups of participants engaged or did not engage in a social interaction before observing human or robotic actions. During observation, MR was assessed via motor-evoked potentials elicited with transcranial magnetic stimulation. Compared with participants who did not engage in a prior social interaction, participants who engaged in the social interaction showed a significant increase in MR for human actions. In contrast, social interaction did not increase MR for robot actions. Thus, naturalistic social interaction and laboratory action observation tasks appear to involve common MR mechanisms, and recent experience tunes the system to particular agent types.

Proceedings of the topical meeting on advances in human factors research on man/computer interactions

International Nuclear Information System (INIS)

Anon.

1990-01-01

This book discusses the following topics: expert systems and knowledge engineering-I; verification and validation of software; methods for modeling UMAN/computer performance; MAN/computer interaction problems in producing procedures -1-2; progress and problems with automation-1-2; experience with electronic presentation of procedures-2; intelligent displays and monitors; modeling user/computer interface; and computer-based human decision-making aids

The Interaction between Human and Organizational Capital in Strategic Human Resource Management (P.49-62)

OpenAIRE

Audia Junita

2017-01-01

Studies in strategic human resource management emphasize the contribution of human and human resource management to organizational performance achievement. Human and organizational capitals are strategic capability and mechanism to create value in an organization.This paper seeks to identify an interactive relationship between human and organizational capital in strategic human resource management theoretically, which so far, have not got adequate attention, particularly in a systemic relatio...

Human agency beliefs influence behaviour during virtual social interactions

Directory of Open Access Journals (Sweden)

Nathan Caruana

2017-09-01

Full Text Available In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an “intentional stance” by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants’ behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative “joint attention” game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other’s eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm (“Computer” condition. The other half were misled into believing that the virtual character was controlled by a second participant in another room (“Human” condition. Those in the “Human” condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the “Computer” condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect

A Functional Analysis on the Interspecies Interaction between Mouse LFA-1 and Human Intercellular Adhesion Molecule-1 at the Cell Level

Directory of Open Access Journals (Sweden)

David Núñez

2017-12-01

Full Text Available The interaction between intercellular adhesion molecules (ICAM and the integrin leukocyte function-associated antigen-1 (LFA-1 is crucial for the regulation of several physiological and pathophysiological processes like cell-mediated elimination of tumor or virus infected cells, cancer metastasis, or inflammatory and autoimmune processes. Using purified proteins it was reported a species restriction for the interaction of ICAM-1 and LFA-1, being mouse ICAM-1 able to interact with human LFA-1 but not human ICAM-1 with mouse LFA-1. However, in vivo results employing tumor cells transfected with human ICAM-1 suggest that functionally mouse LFA-1 can recognize human ICAM-1. In order to clarify the interspecies cross-reactivity of the ICAM-1/LFA-1 interaction, we have performed functional studies analyzing the ability of human soluble ICAM-1 and human/mouse LFA-1 derived peptides to inhibit cell aggregation and adhesion as well as cell-mediated cytotoxicity in both mouse and human systems. In parallel, the affinity of the interaction between mouse LFA-1-derived peptides and human ICAM-1 was determined by calorimetry assays. According to the results obtained, it seems that human ICAM-1 is able to interact with mouse LFA-1 on intact cells, which should be taking into account when using humanized mice and xenograft models for the study of immune-related processes.

A Functional Analysis on the Interspecies Interaction between Mouse LFA-1 and Human Intercellular Adhesion Molecule-1 at the Cell Level.

Science.gov (United States)

Núñez, David; Comas, Laura; Lanuza, Pilar M; Sánchez-Martinez, Diego; Pérez-Hernández, Marta; Catalán, Elena; Domingo, María Pilar; Velázquez-Campoy, Adrián; Pardo, Julián; Gálvez, Eva M

2017-01-01

The interaction between intercellular adhesion molecules (ICAM) and the integrin leukocyte function-associated antigen-1 (LFA-1) is crucial for the regulation of several physiological and pathophysiological processes like cell-mediated elimination of tumor or virus infected cells, cancer metastasis, or inflammatory and autoimmune processes. Using purified proteins it was reported a species restriction for the interaction of ICAM-1 and LFA-1, being mouse ICAM-1 able to interact with human LFA-1 but not human ICAM-1 with mouse LFA-1. However, in vivo results employing tumor cells transfected with human ICAM-1 suggest that functionally mouse LFA-1 can recognize human ICAM-1. In order to clarify the interspecies cross-reactivity of the ICAM-1/LFA-1 interaction, we have performed functional studies analyzing the ability of human soluble ICAM-1 and human/mouse LFA-1 derived peptides to inhibit cell aggregation and adhesion as well as cell-mediated cytotoxicity in both mouse and human systems. In parallel, the affinity of the interaction between mouse LFA-1-derived peptides and human ICAM-1 was determined by calorimetry assays. According to the results obtained, it seems that human ICAM-1 is able to interact with mouse LFA-1 on intact cells, which should be taking into account when using humanized mice and xenograft models for the study of immune-related processes.

Are Children with Autism More Responsive to Animated Characters? A Study of Interactions with Humans and Human-Controlled Avatars

Science.gov (United States)

Carter, Elizabeth J.; Williams, Diane L.; Hodgins, Jessica K.; Lehman, Jill F.

2014-01-01

Few direct comparisons have been made between the responsiveness of children with autism to computer-generated or animated characters and their responsiveness to humans. Twelve 4-to 8-year-old children with autism interacted with a human therapist; a human-controlled, interactive avatar in a theme park; a human actor speaking like the avatar; and…

A review of the models for evaluating organizational factors in human reliability analysis

International Nuclear Information System (INIS)

Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da; Melo, Paulo Fernando Ferreira Frutuoso e

2009-01-01

Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

A review of the models for evaluating organizational factors in human reliability analysis

Energy Technology Data Exchange (ETDEWEB)

Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)], e-mail: bayout@cnen.gov.br, e-mail: rfonseca@cnen.gov.br; Melo, Paulo Fernando Ferreira Frutuoso e [Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear], e-mail: frutuoso@con.ufrj.br

2009-07-01

Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

A Multiscale Survival Process for Modeling Human Activity Patterns.

Science.gov (United States)

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Mathematical models of human behavior

DEFF Research Database (Denmark)

Møllgaard, Anders Edsberg

at the Technical University of Denmark. The data set includes face-to-face interaction (Bluetooth), communication (calls and texts), mobility (GPS), social network (Facebook), and general background information including a psychological profile (questionnaire). This thesis presents my work on the Social Fabric...... data set, along with work on other behavioral data. The overall goal is to contribute to a quantitative understanding of human behavior using big data and mathematical models. Central to the thesis is the determination of the predictability of different human activities. Upper limits are derived....... Evidence is provided, which implies that the asymmetry is caused by a self-enhancement in the initiation dynamics. These results have implications for the formation of social networks and the dynamics of the links. It is shown that the Big Five Inventory (BFI) representing a psychological profile only...

Laser interaction with biological material mathematical modeling

CERN Document Server

Kulikov, Kirill

2014-01-01

This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains.

Science.gov (United States)

Ron, Gil; Globerson, Yuval; Moran, Dror; Kaplan, Tommy

2017-12-21

Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA-DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA-DNA interaction data.

Modeling Human Leukemia Immunotherapy in Humanized Mice

Directory of Open Access Journals (Sweden)

Jinxing Xia

2016-08-01

Full Text Available The currently available human tumor xenograft models permit modeling of human cancers in vivo, but in immunocompromised hosts. Here we report a humanized mouse (hu-mouse model made by transplantation of human fetal thymic tissue plus hematopoietic stem cells transduced with a leukemia-associated fusion gene MLL-AF9. In addition to normal human lymphohematopoietic reconstitution as seen in non-leukemic hu-mice, these hu-mice showed spontaneous development of B-cell acute lymphoblastic leukemia (B-ALL, which was transplantable to secondary recipients with an autologous human immune system. Using this model, we show that lymphopenia markedly improves the antitumor efficacy of recipient leukocyte infusion (RLI, a GVHD-free immunotherapy that induces antitumor responses in association with rejection of donor chimerism in mixed allogeneic chimeras. Our data demonstrate the potential of this leukemic hu-mouse model in modeling leukemia immunotherapy, and suggest that RLI may offer a safe treatment option for leukemia patients with severe lymphopenia.

Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

Science.gov (United States)

Lee, Seungcheol Austin; Liang, Yuhua Jake

2015-04-01

Individuals often apply social rules when they interact with computers, and this is known as the Computers Are Social Actors (CASA) effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain human compliance (e.g., completing a pattern recognition task). The current study focuses on three key factors frequently cited to influence traditional notions of compliance: evaluations toward the source (competence and warmth), normative influence (reciprocity), and affective influence (mood). Structural equation modeling assessed the effects of these factors on human compliance with computer request. The final model shows that norm-based influence (reciprocity) increased the likelihood of compliance, while evaluations toward the computer agent did not significantly influence compliance.

Workshop on cultural usability and human work interaction design

DEFF Research Database (Denmark)

Clemmensen, Torkil; Ørngreen, Rikke; Roese, Kerstin

2008-01-01

it into interaction design. The workshop will present current research into cultural usability and human work interaction design. Cultural usability is a comprehensive concept, which adheres to all kinds of contexts in which humans are involved (private family, work, public and private organizations, nature......, Workplace observation, Think-Aloud Usability Test, etc. These techniques often give - seemingly - similar results when applied in diverse cultural settings, but experience shows that we need a deep understanding of the cultural, social and organizational context to interpret the results, and to transform...

Toward a unified method for analysing and teaching Human Robot Interaction

DEFF Research Database (Denmark)

Dinesen, Jens Vilhelm

, drawing on key theories and methods from both communications- and interaction-theory. The aim is to provide a single unified method for analysing interaction, through means of video analysis and then applying theories, with proven mutual compatibility, to reach a desired granularity of study.......This abstract aims to present key aspect of a future paper, which outlines the ongoing development ofa unified method for analysing and teaching Human-Robot-Interaction. The paper will propose a novel method for analysing both HRI, interaction with other forms of technologies and fellow humans...

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Science.gov (United States)

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Audio Technology and Mobile Human Computer Interaction

DEFF Research Database (Denmark)

Chamberlain, Alan; Bødker, Mads; Hazzard, Adrian

2017-01-01

Audio-based mobile technology is opening up a range of new interactive possibilities. This paper brings some of those possibilities to light by offering a range of perspectives based in this area. It is not only the technical systems that are developing, but novel approaches to the design...... and understanding of audio-based mobile systems are evolving to offer new perspectives on interaction and design and support such systems to be applied in areas, such as the humanities....

Vision-based interaction

CERN Document Server

Turk, Matthew

2013-01-01

In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, there has been an increasing interest in computer vision as an input modality in the context of human-computer interaction. Such vision-based interaction can endow interactive systems with visual capabilities similar to those important to human-human interaction, in order to perceive non-verbal cues and incorporate this information in applications such

Development of an interactive anatomical three-dimensional eye model.

Science.gov (United States)

Allen, Lauren K; Bhattacharyya, Siddhartha; Wilson, Timothy D

2015-01-01

The discrete anatomy of the eye's intricate oculomotor system is conceptually difficult for novice students to grasp. This is problematic given that this group of muscles represents one of the most common sites of clinical intervention in the treatment of ocular motility disorders and other eye disorders. This project was designed to develop a digital, interactive, three-dimensional (3D) model of the muscles and cranial nerves of the oculomotor system. Development of the 3D model utilized data from the Visible Human Project (VHP) dataset that was refined using multiple forms of 3D software. The model was then paired with a virtual user interface in order to create a novel 3D learning tool for the human oculomotor system. Development of the virtual eye model was done while attempting to adhere to the principles of cognitive load theory (CLT) and the reduction of extraneous load in particular. The detailed approach, digital tools employed, and the CLT guidelines are described herein. © 2014 American Association of Anatomists.

Modeling human-machine interactions for operations room layouts

Science.gov (United States)

Hendy, Keith C.; Edwards, Jack L.; Beevis, David

2000-11-01

The LOCATE layout analysis tool was used to analyze three preliminary configurations for the Integrated Command Environment (ICE) of a future USN platform. LOCATE develops a cost function reflecting the quality of all human-human and human-machine communications within a workspace. This proof- of-concept study showed little difference between the efficacy of the preliminary designs selected for comparison. This was thought to be due to the limitations of the study, which included the assumption of similar size for each layout and a lack of accurate measurement data for various objects in the designs, due largely to their notional nature. Based on these results, the USN offered an opportunity to conduct a LOCATE analysis using more appropriate assumptions. A standard crew was assumed, and subject matter experts agreed on the communications patterns for the analysis. Eight layouts were evaluated with the concepts of coordination and command factored into the analysis. Clear differences between the layouts emerged. The most promising design was refined further by the USN, and a working mock-up built for human-in-the-loop evaluation. LOCATE was applied to this configuration for comparison with the earlier analyses.

Centrality of Social Interaction in Human Brain Function.

Science.gov (United States)

Hari, Riitta; Henriksson, Linda; Malinen, Sanna; Parkkonen, Lauri

2015-10-07

People are embedded in social interaction that shapes their brains throughout lifetime. Instead of emerging from lower-level cognitive functions, social interaction could be the default mode via which humans communicate with their environment. Should this hypothesis be true, it would have profound implications on how we think about brain functions and how we dissect and simulate them. We suggest that the research on the brain basis of social cognition and interaction should move from passive spectator science to studies including engaged participants and simultaneous recordings from the brains of the interacting persons. Copyright © 2015 Elsevier Inc. All rights reserved.

Human and Virtual Agents Interacting in the Virtuality Continuum

NARCIS (Netherlands)

Nijholt, Antinus; Miyares Bermúdez, E.; Ruiz Miyares, L.

2006-01-01

We introduce several of our projects in an overview that makes it possible to compare research approaches on interaction modeling in virtual, mixed-reality and real (physical) environments. For these environments, interaction modeling means multimodal (verbal and nonverbal) interaction modeling

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

OpenAIRE

Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

OpenAIRE

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

Science.gov (United States)

Wilson, Alex; Blunsom, Phil; Ker, Andrew D.

2014-02-01

This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.

Association with humans and seasonality interact to reverse predictions for animal space use.

Science.gov (United States)

Laver, Peter N; Alexander, Kathleen A

2018-01-01

Variation in animal space use reflects fitness trade-offs associated with ecological constraints. Associated theories such as the metabolic theory of ecology and the resource dispersion hypothesis generate predictions about what drives variation in animal space use. But, metabolic theory is usually tested in macro-ecological studies and is seldom invoked explicitly in within-species studies. Full evaluation of the resource dispersion hypothesis requires testing in more species. Neither have been evaluated in the context of anthropogenic landscape change. In this study, we used data for banded mongooses ( Mungos mungo ) in northeastern Botswana, along a gradient of association with humans, to test for effects of space use drivers predicted by these theories. We used Bayesian parameter estimation and inference from linear models to test for seasonal differences in space use metrics and to model seasonal effects of space use drivers. Results suggest that space use is strongly associated with variation in the level of overlap that mongoose groups have with humans. Seasonality influences this association, reversing seasonal space use predictions historically-accepted by ecologists. We found support for predictions of the metabolic theory when moderated by seasonality, by association with humans and by their interaction. Space use of mongooses living in association with humans was more concentrated in the dry season than the wet season, when historically-accepted ecological theory predicted more dispersed space use. Resource richness factors such as building density were associated with space use only during the dry season. We found negligible support for predictions of the resource dispersion hypothesis in general or for metabolic theory where seasonality and association with humans were not included. For mongooses living in association with humans, space use was not associated with patch dispersion or group size over both seasons. In our study, living in association

Interaction of lipid nanoparticles with human epidermis and an organotypic cell culture model

DEFF Research Database (Denmark)

Kuntsche, Judith; Bunjes, Heike; Fahr, Alfred

2008-01-01

Various lipid nanoparticle formulations were investigated with respect to (trans)dermal drug delivery with special regard to the mechanism of their effects on human and an organotypic cell culture epidermis. Potential alterations of stratum corneum lipid domains were studied using fluorescence...... assays with labeled liposomes and thermal analysis of isolated stratum corneum. Influences on the permeation of corticosterone were investigated and the occlusive properties of the nanoparticles were determined by measurements of the transepidermal water loss (TEWL). The penetration of a fluorescence dye...... studies and thermal analysis of human and cell culture epidermis indicate that surface lipids, which are not present to the same extent in the cell culture model than in human epidermis, seem to play an important role....

Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

Science.gov (United States)

Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

2014-01-01

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans. PMID:24752212

Multimodal Information Presentation for High-Load Human Computer Interaction

NARCIS (Netherlands)

Cao, Y.

2011-01-01

This dissertation addresses multimodal information presentation in human computer interaction. Information presentation refers to the manner in which computer systems/interfaces present information to human users. More specifically, the focus of our work is not on which information to present, but

Probing the interaction of a therapeutic flavonoid, pinostrobin with human serum albumin: multiple spectroscopic and molecular modeling investigations.

Directory of Open Access Journals (Sweden)

Shevin R Feroz

Full Text Available Interaction of a pharmacologically important flavonoid, pinostrobin (PS with the major transport protein of human blood circulation, human serum albumin (HSA has been examined using a multitude of spectroscopic techniques and molecular docking studies. Analysis of the fluorescence quenching data showed a moderate binding affinity (1.03 × 10(5 M(-1 at 25°C between PS and HSA with a 1∶1 stoichiometry. Thermodynamic analysis of the binding data (ΔS = +44.06 J mol(-1 K(-1 and ΔH = -15.48 kJ mol(-1 and molecular simulation results suggested the involvement of hydrophobic and van der Waals forces, as well as hydrogen bonding in the complex formation. Both secondary and tertiary structural perturbations in HSA were observed upon PS binding, as revealed by intrinsic, synchronous, and three-dimensional fluorescence results. Far-UV circular dichroism data revealed increased thermal stability of the protein upon complexation with PS. Competitive drug displacement results suggested the binding site of PS on HSA as Sudlow's site I, located at subdomain IIA, and was well supported by the molecular modelling data.

[Investigation on the interaction between pentadecafluorooctanoic acid and human serum albumin by capillary electrophoresis].

Science.gov (United States)

Gu, Yi; Guo, Ming; Lü, Da; Hou, Ping; Yin, Xinxin

2018-01-08

Capillary electrophoresis (CE) has been used to establish the analytical method of interaction between pentadecafluorooctanoic acid (PFOA) and human serum albumin (HSA). Under the physiological conditions, the interaction model of PFOA and HSA were constructed. Mobility method, plug-plug kinetic (PPK) method and simplified Hummel-Dreyer method were used to determine the interaction between derivatives and HSA. Non-linear regression, Scatchard equation and Klotz equation were adopted to obtain the interaction parameters. The results showed that all the three methods can be used to analyze the interaction of PFOA-HSA system. According to the interaction parameters, the most suitable CE method is simplified Hummel-Dreyer method while the most suitable theoretical equation is non-linear regression. The binding parameters indicated that the interaction of PFOA-HSA system has only one type of binding sites and the binding is stable. The research results have illustrated the interaction between HSA and PFOA, and provided a beneficial reference for in-depth research of the toxic mechanism of PFOA.

Molecular modeling of interactions in electronic nose sensors for environmental monitoring

Science.gov (United States)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Yen, S. -P. S.; Zhou, H.; Manatt, K.

2002-01-01

We report a study aimed at understanding analyte interactions with sensors made from polymer-carbon black composite films. The sensors are used in an Electronic Nose (ENose) which is used for monitoring the breathing air quality in human habitats. The model mimics the experimental conditions of the composite film deposition and formation and was developed using molecular modeling and simulation tools. The Dreiding 2.21 Force Field was used for the polymer and analyte molecules while graphite parameters were assigned to the carbon black atoms. The polymer considered for this work is methyl vinyl ether / maleic acid copolymer. The target analytes include both inorganic (NH3) and organic (methanol) types of compound. Results indicate different composite-analyte interaction behavior.

Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

Science.gov (United States)

Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

2017-12-14

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

Sense of presence and anxiety during virtual social interactions between a human and virtual humans

OpenAIRE

Morina, Nexhmedin; Brinkman, Willem-Paul; Hartanto, Dwi; Emmelkamp, Paul M.G.

2014-01-01

Virtual reality exposure therapy (VRET) has been shown to be effective in treatment of anxiety disorders. Yet, there is lack of research on the extent to which interaction between the individual and virtual humans can be successfully implanted to increase levels of anxiety for therapeutic purposes. This proof-of-concept pilot study aimed at examining levels of the sense of presence and anxiety during exposure to virtual environments involving social interaction with virtual humans and using d...

Human Metabolism and Interactions of Deployment-Related Chemicals

National Research Council Canada - National Science Library

Hodgson, Ernest

2003-01-01

This study examines the human-metabolism and metabolic interactions of a subset of deployment-related chemicals, including chlorpyrifos, DEET, permethrin, pyridostigmine bromide, and sulfur mustard metabolites...

Haptic communication between humans is tuned by the hard or soft mechanics of interaction

Science.gov (United States)

Usai, Francesco; Ganesh, Gowrishankar; Sanguineti, Vittorio; Burdet, Etienne

2018-01-01

To move a hard table together, humans may coordinate by following the dominant partner’s motion [1–4], but this strategy is unsuitable for a soft mattress where the perceived forces are small. How do partners readily coordinate in such differing interaction dynamics? To address this, we investigated how pairs tracked a target using flexion-extension of their wrists, which were coupled by a hard, medium or soft virtual elastic band. Tracking performance monotonically increased with a stiffer band for the worse partner, who had higher tracking error, at the cost of the skilled partner’s muscular effort. This suggests that the worse partner followed the skilled one’s lead, but simulations show that the results are better explained by a model where partners share movement goals through the forces, whilst the coupling dynamics determine the capacity of communicable information. This model elucidates the versatile mechanism by which humans can coordinate during both hard and soft physical interactions to ensure maximum performance with minimal effort. PMID:29565966

See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction.

Science.gov (United States)

Xu, Tian Linger; Zhang, Hui; Yu, Chen

2016-05-01

We focus on a fundamental looking behavior in human-robot interactions - gazing at each other's face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user's face as a response to the human's gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot's gaze toward the human partner's face in real time and then analyzed the human's gaze behavior as a response to the robot's gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot's face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained.

Tactile interactions activate mirror system regions in the human brain.

Science.gov (United States)

McKyton, Ayelet

2011-12-07

Communicating with others is essential for the development of a society. Although types of communications, such as language and visual gestures, were thoroughly investigated in the past, little research has been done to investigate interactions through touch. To study this we used functional magnetic resonance imaging. Twelve participants were scanned with their eyes covered while stroking four kinds of items, representing different somatosensory stimuli: a human hand, a realistic rubber hand, an object, and a simple texture. Although the human and the rubber hands had the same overall shape, in three regions there was significantly more blood oxygen level dependent activation when touching the real hand: the anterior medial prefrontal cortex, the ventral premotor cortex, and the posterior superior temporal cortex. The last two regions are part of the mirror network and are known to be activated through visual interactions such as gestures. Interestingly, in this study, these areas were activated through a somatosensory interaction. A control experiment was performed to eliminate confounds of temperature, texture, and imagery, suggesting that the activation in these areas was correlated with the touch of a human hand. These results reveal the neuronal network working behind human tactile interactions, and highlight the participation of the mirror system in such functions.

Formation of Human Subjectivity in Psychological Interactions with Nature

Directory of Open Access Journals (Sweden)

S A Mudrak

2014-12-01

Full Text Available The article outlines the current trends in the environmental psychological research of the peculiarities of developing the subject-subjective human relationship with nature: considering human habitat environment as a set of natural objects; studying certain natural sites as psychologically attributive elements of the environment; determining the psychological meaning of the «Human Habitat Environment»; giving the analysis of the problem of the subjectivity development in human interaction with the natural objects.

Proceedings of the Third International Conference on Intelligent Human Computer Interaction

CERN Document Server

Pokorný, Jaroslav; Snášel, Václav; Abraham, Ajith

2013-01-01

The Third International Conference on Intelligent Human Computer Interaction 2011 (IHCI 2011) was held at Charles University, Prague, Czech Republic from August 29 - August 31, 2011. This conference was third in the series, following IHCI 2009 and IHCI 2010 held in January at IIIT Allahabad, India. Human computer interaction is a fast growing research area and an attractive subject of interest for both academia and industry. There are many interesting and challenging topics that need to be researched and discussed. This book aims to provide excellent opportunities for the dissemination of interesting new research and discussion about presented topics. It can be useful for researchers working on various aspects of human computer interaction. Topics covered in this book include user interface and interaction, theoretical background and applications of HCI and also data mining and knowledge discovery as a support of HCI applications.

Human reconstructed skin xenografts on mice to model skin physiology.

Science.gov (United States)

Salgado, Giorgiana; Ng, Yi Zhen; Koh, Li Fang; Goh, Christabelle S M; Common, John E

Xenograft models to study skin physiology have been popular for scientific use since the 1970s, with various developments and improvements to the techniques over the decades. Xenograft models are particularly useful and sought after due to the lack of clinically relevant animal models in predicting drug effectiveness in humans. Such predictions could in turn boost the process of drug discovery, since novel drug compounds have an estimated 8% chance of FDA approval despite years of rigorous preclinical testing and evaluation, albeit mostly in non-human models. In the case of skin research, the mouse persists as the most popular animal model of choice, despite its well-known anatomical differences with human skin. Differences in skin biology are especially evident when trying to dissect more complex skin conditions, such as psoriasis and eczema, where interactions between the immune system, epidermis and the environment likely occur. While the use of animal models are still considered the gold standard for systemic toxicity studies under controlled environments, there are now alternative models that have been approved for certain applications. To overcome the biological limitations of the mouse model, research efforts have also focused on "humanizing" the mice model to better recapitulate human skin physiology. In this review, we outline the different approaches undertaken thus far to study skin biology using human tissue xenografts in mice and the technical challenges involved. We also describe more recent developments to generate humanized multi-tissue compartment mice that carry both a functioning human immune system and skin xenografts. Such composite animal models provide promising opportunities to study drugs, disease and differentiation with greater clinical relevance. Copyright © 2017 International Society of Differentiation. Published by Elsevier B.V. All rights reserved.

Study on intelligent processing system of man-machine interactive garment frame model

Science.gov (United States)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

Semantic models for adaptive interactive systems

CERN Document Server

Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

2013-01-01

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

Human-nature interactions and the consequences and drivers of provisioning wildlife.

Science.gov (United States)

Cox, Daniel T C; Gaston, Kevin J

2018-05-05

Many human populations are undergoing an extinction of experience, with a progressive decline in interactions with nature. This is a consequence both of a loss of opportunity for, and orientation towards, such experiences. The trend is of concern in part because interactions with nature can be good for human health and wellbeing. One potential means of redressing these losses is through the intentional provision of resources to increase wildlife populations in close proximity to people, thereby increasing the potential for positive human-nature experiences, and thence the array of benefits that can result. In this paper, we review the evidence that these resource subsidies have such a cascade of effects. In some Westernized countries, the scale of provision is extraordinarily high, and doubtless leads to both positive and negative impacts for wildlife. In turn, these impacts often lead to more frequent, reliable and closer human-nature interactions, with a greater variety of species. The consequences for human wellbeing remain poorly understood, although benefits documented in the context of human-nature interactions more broadly seem likely to apply. There are also some important feedback loops that need to be better characterized if resource provisioning is to contribute effectively towards averting the extinction of experience.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Authors.

Interactive domains in the molecular chaperone human alphaB crystallin modulate microtubule assembly and disassembly.

Directory of Open Access Journals (Sweden)

Joy G Ghosh

2007-06-01

Full Text Available Small heat shock proteins regulate microtubule assembly during cell proliferation and in response to stress through interactions that are poorly understood.Novel functions for five interactive sequences in the small heat shock protein and molecular chaperone, human alphaB crystallin, were investigated in the assembly/disassembly of microtubules and aggregation of tubulin using synthetic peptides and mutants of human alphaB crystallin.The interactive sequence (113FISREFHR(120 exposed on the surface of alphaB crystallin decreased microtubule assembly by approximately 45%. In contrast, the interactive sequences, (131LTITSSLSSDGV(142 and (156ERTIPITRE(164, corresponding to the beta8 strand and the C-terminal extension respectively, which are involved in complex formation, increased microtubule assembly by approximately 34-45%. The alphaB crystallin peptides, (113FISREFHR(120 and (156ERTIPITRE(164, inhibited microtubule disassembly by approximately 26-36%, and the peptides (113FISREFHR(120 and (131LTITSSLSSDGV(142 decreased the thermal aggregation of tubulin by approximately 42-44%. The (131LTITSSLSSDGV(142 and (156ERTIPITRE(164 peptides were more effective than the widely used anti-cancer drug, Paclitaxel, in modulating tubulinmicrotubule dynamics. Mutagenesis of these interactive sequences in wt human alphaB crystallin confirmed the effects of the alphaB crystallin peptides on microtubule assembly/disassembly and tubulin aggregation. The regulation of microtubule assembly by alphaB crystallin varied over a narrow range of concentrations. The assembly of microtubules was maximal at alphaB crystallin to tubulin molar ratios between 1:4 and 2:1, while molar ratios >2:1 inhibited microtubule assembly.Interactive sequences on the surface of human alphaB crystallin collectively modulate microtubule assembly through a dynamic subunit exchange mechanism that depends on the concentration and ratio of alphaB crystallin to tubulin. These are the first

Modeling Leadership Styles in Human-Robot Team Dynamics

Science.gov (United States)

Cruz, Gerardo E.

2005-01-01

The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

The Human-Computer Interaction of Cross-Cultural Gaming Strategy

Science.gov (United States)

Chakraborty, Joyram; Norcio, Anthony F.; Van Der Veer, Jacob J.; Andre, Charles F.; Miller, Zachary; Regelsberger, Alexander

2015-01-01

This article explores the cultural dimensions of the human-computer interaction that underlies gaming strategies. The article is a desktop study of existing literature and is organized into five sections. The first examines the cultural aspects of knowledge processing. The social constructs technology interaction is discussed. Following this, the…

Towards a model for egocentric interaction with physical and virtual objects

DEFF Research Database (Denmark)

Pederson, Thomas; Janlert, Lars-Erik; Surie, Dipak

2010-01-01

Designers of mobile context-aware systems are struggling with the problem of conceptually incorporating the real world into the system design. We present a body-centric modeling framework (as opposed to device-centric) that incorporates physical and virtual objects of interest on the basis...... of proximity and human perception, framed in the context of an emerging "egocentric" interaction paradigm....

Drug interactions at the human placenta: what is the evidence?

Directory of Open Access Journals (Sweden)

Miriam eRubinchik-Stern

2012-07-01

Full Text Available Pregnant women (and their fetuses are treated with a significant number of prescription and nonprescription medications. Interactions among those drugs may affect their efficacy and toxicity in both mother and fetus. Whereas interactions that result in altered drug concentrations in maternal plasma are detectable, those involving modulation of placental transfer mechanisms are rarely reflected by altered drug concentrations in maternal plasma. Therefore, they are often overlooked. Placental-mediated interactions are possible because the placenta is not only a passive diffusional barrier, but also expresses a variety of influx and efflux transporters and drug metabolizing enzymes. Current data on placental-mediated drug interactions are limited. In rodents, pharmacological or genetic manipulations of placental transporters significantly affect fetal drug exposure. In contrast, studies in human placentae suggest that the magnitude of such interactions is modest in most cases. Nevertheless, under certain circumstances, such interactions may be of clinical significance. This review describes currently known mechanisms of placental-mediated drug interactions and the potential implications of such interactions in humans. Better understanding of those mechanisms is important for minimizing fetal toxicity from drugs while improving their efficacy when directed to treat the fetus.

Interaction Modeling at PROS Research Center

OpenAIRE

Panach , José ,; Aquino , Nathalie; PASTOR , Oscar

2011-01-01

Part 1: Long and Short Papers; International audience; This paper describes how the PROS Research Center deals with interaction in the context of a model-driven approach for the development of information systems. Interaction is specified in a conceptual model together with the structure and behavior of the system. Major achievements and current research challenges of PROS in the field of interaction modeling are presented.

Soft Electronics Enabled Ergonomic Human-Computer Interaction for Swallowing Training

Science.gov (United States)

Lee, Yongkuk; Nicholls, Benjamin; Sup Lee, Dong; Chen, Yanfei; Chun, Youngjae; Siang Ang, Chee; Yeo, Woon-Hong

2017-04-01

We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant (“skin-like”) electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders.

A Social Cognitive Neuroscience Stance on Human-Robot Interactions

Directory of Open Access Journals (Sweden)

Chaminade Thierry

2011-12-01

Full Text Available Robotic devices, thanks to the controlled variations in their appearance and behaviors, provide useful tools to test hypotheses pertaining to social interactions. These agents were used to investigate one theoretical framework, resonance, which is defined, at the behavioral and neural levels, as an overlap between first- and third- person representations of mental states such as motor intentions or emotions. Behaviorally, we found a reduced, but significant, resonance towards a humanoid robot displaying biological motion, compared to a human. Using neuroimaging, we've reported that while perceptual processes in the human occipital and temporal lobe are more strongly engaged when perceiving a humanoid robot than a human action, activity in areas involved in motor resonance depends on attentional modulation for artificial agent more strongly than for human agents. Altogether, these studies using artificial agents offer valuable insights into the interaction of bottom-up and top-down processes in the perception of artificial agents.

The scaling of human interactions with city size.

Science.gov (United States)

Schläpfer, Markus; Bettencourt, Luís M A; Grauwin, Sébastian; Raschke, Mathias; Claxton, Rob; Smoreda, Zbigniew; West, Geoffrey B; Ratti, Carlo

2014-09-06

The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

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He Weiming

2010-07-01

Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Incorporating the gut microbiota into models of human and non-human primate ecology and evolution.

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Amato, Katherine R

2016-01-01

The mammalian gut is home to a diverse community of microbes. Advances in technology over the past two decades have allowed us to examine this community, the gut microbiota, in more detail, revealing a wide range of influences on host nutrition, health, and behavior. These host-gut microbe interactions appear to shape host plasticity and fitness in a variety of contexts, and therefore represent a key factor missing from existing models of human and non-human primate ecology and evolution. However, current studies of the gut microbiota tend to include limited contextual data or are clinical, making it difficult to directly test broad anthropological hypotheses. Here, I review what is known about the animal gut microbiota and provide examples of how gut microbiota research can be integrated into the study of human and non-human primate ecology and evolution with targeted data collection. Specifically, I examine how the gut microbiota may impact primate diet, energetics, disease resistance, and cognition. While gut microbiota research is proliferating rapidly, especially in the context of humans, there remain important gaps in our understanding of host-gut microbe interactions that will require an anthropological perspective to fill. Likewise, gut microbiota research will be an important tool for filling remaining gaps in anthropological research. © 2016 Wiley Periodicals, Inc.

Real-time face and gesture analysis for human-robot interaction

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Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

2010-05-01

Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

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Matthew D Dyer

2010-08-01

Full Text Available Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.