The force exerted during manual tasks is a dominant risk factor for upper-limb musculoskeletal disorders. To identify tasks that may lead to fatigue over a shift, or increase the risk of injury, the demands placed on the hand and forearm system must be quantified and predicted. The purpose of this research was to determine how different ways of simulating manual tasks affected the estimate of demand on the hand and forearm and how well normative data could be used to provide an estimate of that demand. The forces and moments required to perform 20 manual tasks were measured and simulations with three different levels of realism developed, ranging from simple feedback, with real parts, postures and timing to more controlled simulations with simplified parts, standard postures and 5s static exertions. 11 workers hired from a temporary employment agency each performed the simulated tasks and their physical demand was determined using perceived effort, the muscle activity of 8 hand and forearm muscles, and grip (or pinch) force matching. Based on these criteria, the best simulation was that with the same handle size, shape and orientation as the criterion version of the task using simple feedback to match one or two forces. Over the variety of tasks studied here, perceived effort, grip force matching and extensor digitorum activation provided the most similar demand estimate to the criterion task of all measured parameters. The more controlled simulation had the highest correlation compared with normative demand. Overall, the more changes in hand-object interface made between the task of interest and a simulation or normative data, the greater the discrepancy in demand. Normative data tended to underestimate demand, thus underestimating the risk of fatigue and injury. The use of simulations and task specific normative data to estimate hand task demand, with an accuracy useful for field measurements by ergonomists, was supported.

Organizational support for cooperative work has been shifted from using Face-to-Face (FTF) communication in collocated groups to using Communication-Mediated-Communication (CMC) in dispersed groups. This new and growing form of communication has stimulated scholars to study the differences of group performance between FTF and CMC. Task categorization has been the methodology chosen for several empirical research studies. These studies conclude that the effectiveness of a communication medium for a given task depends on the degree to which there is a fit between the richness of information that can be transmitted via a system’s technology and the information richness requirements of that task. However, there are numerous problems associated with using task categorization in such studies. One of these limitations is that categorization forces the researcher to enclose a task situation into a general predetermined category that may not describe the real nature of the activity. For instance, task categorization does not capture the dynamic interaction of groups performing tasks that involve variation. This thesis discusses the weakness and limitations of this approach and, using conclusions drawn from experimental results, propose the adoption of a more systematic approach based on the concept of Ashby’s law of requisite variety. Findings on the differences in performance of FTF groups versus CMC groups of 39 three-person groups of engineering undergraduate students revealed that the group performance was not affected by the communication medium but rather by variation in the task (low and high complexity).

Current methods of robot task teaching and learning have several limitations: highly-trained personnel are usually required to teach robots specific tasks; service-robot systems are limited in learning different types of tasks utilizing the same system; and the teacher’s expertise in the task is not well exploited. A human-inspired robot-task teaching and learning method is developed in this research with the aim of allowing general users to teach different object-manipulation tasks to a service robot, which will be able to adapt its learned tasks to new task setups. The proposed method was developed to be interactive and intuitive to the user. In a closed loop with the robot, the user can intuitively teach the tasks, track the learning states of the robot, direct the robot attention to perceive task-related key state changes, and give timely feedback when the robot is practicing the task, while the robot can reveal its learning progress and refine its knowledge based on the user’s feedback. The human-inspired method consists of six teaching and learning stages: 1) checking and teaching the needed background knowledge of the robot; 2) introduction of the overall task to be taught to the robot: the hierarchical task structure, and the involved objects and robot hand actions; 3) teaching the task step by step, and directing the robot to perceive important state changes; 4) demonstration of the task in whole, and offering vocal subtask-segmentation cues in subtask transitions; 5) robot learning of the taught task using a flexible vote-based algorithm to segment the demonstrated task trajectories, a probabilistic optimization process to assign obtained task trajectory episodes (segments) to the introduced subtasks, and generalization of the taught task trajectories in different reference frames; and 6) robot practicing of the learned task and refinement of its task knowledge according to the teacher’s timely feedback, where the adaptation of the learned task to new task setups is achieved by blending the task trajectories generated from pertinent frames. An agent-based architecture was designed and developed to implement this robot-task teaching and learning method. This system has an interactive human-robot teaching interface subsystem, which is composed of: a) a three-camera stereo vision system to track user hand motion; b) a stereo-camera vision system mounted on the robot end-effector to allow the robot to explore its workspace and identify objects of interest; and c) a speech recognition and text-to-speech system, utilized for the main human-robot interaction. A user study involving ten human subjects was performed using two tasks to evaluate the system based on time spent by the subjects on each teaching stage, efficiency measures of the robot’s understanding of users’ vocal requests, responses, and feedback, and their subjective evaluations. Another set of experiments was done to analyze the ability of the robot to adapt its previously learned tasks to new task setups using measures such as object, target and robot starting-point poses; alignments of objects on targets; and actual robot grasp and release poses relative to the related objects and targets. The results indicate that the system enabled the subjects to naturally and effectively teach the tasks to the robot and give timely feedback on the robot’s practice performance. The robot was able to learn the tasks as expected and adapt its learned tasks to new task setups. The robot properly refined its task knowledge based on the teacher’s feedback and successfully applied the refined task knowledge in subsequent task practices. The robot was able to adapt its learned tasks to new task setups that were considerably different from those in the demonstration. The alignments of objects on the target were quite close to those taught, and the executed grasping and releasing poses of the robot relative to objects and targets were almost identical to the taught poses. The robot-task learning ability was affected by limitations of the vision-based human-robot teleoperation interface used in hand-to-hand teaching and the robot’s capacity to sense its workspace. Future work will investigate robot learning of a variety of different tasks and the use of more robot in-built primitive skills.

Frontal electroencephalographic (EEG) alpha (α) asymmetry may index the activation of lateralized affect and motivation systems in humans. Resting EEG activation was measured and its relationship to Iowa gambling task (IGT) performance was evaluated. No effects were found for α power asymmetry. However, beta (β) power asymmetry, an alternative measure of resting EEG activation, was associated with the number of risky decisions made in the early portion of the task. Additionally, IGT deck selection patterns suggest there are at least three distinct performance styles in healthy individuals. Interestingly, β power asymmetry contradicts performance predictions based on accepted frontal asymmetry affect and motivation models.

Humans have a tendency to engage in economically irrational behaviors such as gambling, which typically leads to long-term financial losses. While there has been much research on human gambling behavior, relatively little work has been done to explore the evolutionary origins of this behavior. To examine the adaptive pressures that may have led to this seemingly irrational behavior in humans, nonhuman primates were tested to explore their reactions to gambling type scenarios. Several experiments based on traditional human economic experiments were adapted for use with a wider variety of primate species including chimpanzees and capuchin monkeys. This allowed for testing multiple species using similar methodologies in order to make more accurate comparisons of species abilities. This series of tasks helps to elucidate risky decision-making behavior in three primate species.

This thesis identifies and analyzes successful movement strategies for the completion of a complex dynamic task. In the past it has been shown that movement strategies correlate well to performance for simple tasks. Therefore, in this thesis I was motivated to find out if motion based metrics correlated well to performance for more complicated motor tasks. First, the Nintendo Wiimote was verified as a suitable gaming interface enabling gross human motion capture through experimental comparisons with other gaming interfaces and precision sensors. Then, a complex motor task was rendered in an open-source gaming environment. This environment enabled the design of a rhythmic task that could be controlled with the Wiimote while data were simultaneously recorded for later analysis. For the task, success and failure could be explained by high correlation between two motion based performance metrics, mean absolute jerk (MAJ) and average frequency (AVF) per trial. A logistic regression analysis revealed that each subject had a range of MAJ and AVF values for being successful, outside of which they were unsuccessful. Therefore, this thesis identifies motion based performance metrics for a novel motor control task that is significantly difficult to master and the techniques used to identify successful movement strategies can be used for predicting success for other such complex dynamic tasks.

Nowadays in the world of mass consumption there is big demand for distributioncenters of bigger size. Managing such a center is a very complex and difficult taskregarding to the different processes and factors in a usual warehouse when we want tominimize the labor costs. Most of the workers’ working time is spent with travelingbetween source and destination points which cause deadheading. Even if a worker knowsthe structure of a warehouse well and because of that he or she can find the shortest pathbetween two points, it is still not guaranteed that there won’t be long traveling timebetween the locations of two consecutive tasks. We need optimal assignments betweentasks and workers.In the scientific literature Generalized Assignment Problem (GAP) is a wellknownproblem which deals with the assignment of m workers to n tasks consideringseveral constraints. The primary purpose of my thesis project was to choose a heuristics(genetic algorithm, tabu search or ant colony optimization) to be implemented into SAPExtended Warehouse Management (SAP EWM) by with task assignment will be moreeffective between tasks and resources.After system analysis I had to realize that due different constraints and businessdemands only 1:1 assingments are allowed in SAP EWM. Because of that I had to use adifferent and simpler approach – instead of the introduced heuristics – which could gainbetter assignments during the test phase in several cases. In the thesis I described indetails what ware the most important questions and problems which emerged during theplanning of my optimized assignment method.

Studiens syfte var att se om känslan glädje leder till att man uppmärksammar en viss typ av information i större utsträckning än annan. I detta fall för positivt belönande ord respektive positivt icke belönande ord. Denna studie är en replikering av Tamir & Robinsons (2007) studie som fick belägg för detta. Deltagarna delades in i två grupper där experimentgruppen som bestod av 9 deltagare fick i uppgift att skriva ner en händelse som gjort och fortfarande gör dem glada för att väcka ett tillstånd av glädje. Kontrollgruppen som bestod av 10 deltagare fick istället i uppgift att minnas och skriva ner hur deras sovrum ser ut för att hamna i ett neutralt tillstånd. Deltagarna slumpades in i respektive grupper och fick 5 minuter på sig att göra denna uppgift. Efter uppgiften fick deltagarna fylla i ett formulär som mäter aktuellt känsloläge, och här skilde sig grupperna signifikant från varandra.Glädje var den känslan som skiljde sig signifikant mellan grupperna. Dot probe task användes för att mäta uppmärksamhetsbias men inga signifikanta skillnader mellan grupperna visades. Detta innebär att glädje i denna studie inte styrde uppmärksamheten mot generellt belönande information. E-prime 2.0 användes som verktyg för att bygga och utföra experimentet.

The process of generating a phonological code from print is widely described as automatic. This claim is tested in Chapter 1 by assessing whether phonological recoding uses central attention in the context of the Psychological Refractory Period (PRP) paradigm. Task 1 was a tone discrimination task and Task 2 was reading aloud. Nonword letter length and grapheme-phoneme complexity yielded additive effects with SOA in Experiments 1 and 2 suggesting that <em>assembled phonology</em> uses central attention. Neighborhood density (N) yielded additive effects with SOA in Experiments 3 and 4, suggesting that one form of lexical contribution to phonological recoding also uses central attention. Taken together, the results of these experiments are <em>inconsistent</em> with the widespread claim that phonological codes are computed automatically. Chapter 2 begins by reconsidering the utility of ?automaticity? as an explanatory framework. It is argued that automaticity should be replaced by accounts that make more specific claims about how processing unfolds. Experiment 5 yielded underadditivity of long-lag word repetition priming with decreasing SOA, suggesting that an early component of the lexical contribution to phonology does not use central attention. There was no evidence of Task 1 slowing with decreasing SOA in Experiments 6 and 7, suggesting that phonological recoding processes are postponed until central attention becomes available. Theoretical development in this field (and others) will be facilitated by abandoning the idea that skilled performance inevitably means that all the underlying processes are automatic.

Three experiments examine how collaboration influences visual search performance. Working with a partner or on their own, participants reported whether a target was present or absent in briefly presented search displays. The search performance of individuals working together (collaborative pairs) was compared to the pooled responses of the individuals working alone (nominal pairs). Collaborative pairs were less likely than nominal pairs to correctly detect a target and they were less likely to make false alarms. Signal detection analyses revealed that collaborative pairs were more sensitive to the presence of the target and had a more conservative response bias than the nominal pairs. This pattern was observed when the search difficulty was increased and when the presence of another individual was matched across pairs. The results are discussed in the context of task sharing, social loafing and current theories of visual search.