No / PURPOSE. To determine the influence of refractive blur on postural stability during somatosensory and vestibular system perturbation and dual tasking. METHODS. Fifteen healthy, elderly subjects (mean age, 71 ± 5 years), who had no history of falls and had normal vision, were recruited. Postural stability during standing was assessed using a force platform, and was determined as the root mean square (RMS) of the center of pressure (COP) signal in the anterior-posterior (A-P) and medial-lateral directions collected over a 30-second period. Data were collected under normal standing conditions and with somatosensory and vestibular system perturbations. Measurements were repeated with an additional physical and/or cognitive task. Postural stability was measured under conditions of binocular refractive blur of 0, 1, 2, 4, and 8 D and with eyes closed. The data were analyzed with a population-averaged linear model. RESULTS. The greatest increases in postural instability were due to disruptions of the somatosensory and vestibular systems. Increasing refractive blur caused increasing postural instability, and its effect was greater when the input from the other sensory systems was disrupted. Performing an additional cognitive and physical task increased A-P RMS COP further. All these detrimental effects on postural stability were cumulative. CONCLUSIONS. The findings highlight the multifactorial nature of postural stability and indicate why the elderly, many of whom have poor vision and musculoskeletal and central nervous system degeneration, are at greater risk of falling. The findings also highlight that standing instability in both normal and perturbed conditions was significantly increased with refractive blur. Correcting visual impairment caused by uncorrected refractive error could be a useful intervention strategy to help prevent falls and fall-related injuries in the elderly.

No description available.

Ph.D. / Computer Science and Electrical Engineering / We envision that next-generation spoken dialogue systems will be supporting a complex user goal and multiple parallel tasks, which requires the system and the user to jointly direct the flow of conversation. The problem, however, is that there lacks an effective model of directing the flow of conversation. This thesis research aims to develop such a model for next-generation spoken dialogue systems. We started with conventions actually used in human-human dialogue, which are natural for users to follow and probably also efficient in problem-solving. An annotation framework, DialogueView, was established to allow for the investigation of complex interaction in dialogue. A series of empirical studies on two corpora, the Trains and the MTD, were then conducted to understand people's initiative behavior of directing the conversation flow. We first examined people's initiative behavior in decomposing a complex goal into sub-goals and achieving each of them in the Trains domain. We found that initiative is subservient to discourse goal. We next examined people's initiative behavior in switching the conversation to a more urgent task. We found that conversants strive to switch tasks at a less disruptive place; but where they cannot, they exert additional effort to signal the task switching, such as increasing pitch. We finally examined people's behavior on initiative conflicts, where both conversants try to direct the conversation at the same time. We found that conversants try to avoid initiative conflicts; but when initiative conflicts occur, they are efficiently resolved with simple linguistic devices such as volume. Computer simulation experiments were also conducted to better understand the underlying benefits of using the human conventions. Our findings on human-human dialogues have important implication for building next-generation spoken dialogue systems by (1) guiding the system when to show initiative, and when to let the user show initiative; (2) guiding the system when and how to switch to a more urgent task, and to understand the user's switch; and (3) guiding the system how to resolve and repair initiative conflicts.

A large proportion of the farming in Kenya and Eastern Africa is performed by smallholding farmers. At the same time, consumers are expecting to find foodstuff more close by and in a more convenient way than most smallholding farmers can provide. Crowdsourcing can efficiently be applied to many problems where many small producers need to collaborate to create the complete product, without exposing much of the complex process to the end consumers. Using semi structured interviews, systematic literature review and prototyping, the application of crowdsourcing to reach and empower smallholding farmers was explored. The findings were used to create recommendations in the form of guidelines that are expected to serve as ground work and background to future studies within the area. In general, a mobile based platform for crowdsourcing was found to be viable while still having some problems with the intended target market. Three primary factors which affects the potential success were identified; The generally low availability of internet to smallholding farmers (limited by high prices), lacking education which can limit comprehension of more complicated processes, and smartphones with limited capacity for advanced applications. / En stor del av jordbruket i Kenya och östra Afrika utförs av småbönder. Samtidigt förväntar sig konsumenter att kunna hitta matprodukter närmare och på ett mer bekvämt sätt än de flesta småbönder kan erbjuda. Crowdsourcing kan effektivt tillämpas på många problem där flera små producenter behöver samarbeta för att skapa den kompletta produkten utan att utsätta slutkonsumenten för den komplexa processen. Med hjälp av semi-trukturerade intervjuer, systematisk litteratur studie och prototyping, undersöktes tillämpningen av crowdsourcing för att nå och förstärka småbönder. Resultaten användes för att skapa rekommendationer i form av riktlinjer som förväntas fungera som grundarbete och bakgrund till framtida studier inom området. I allmänhet visade sig en mobilbaserad plattform för crowdsourcing vara realistisk, samtidigt som den fortfarande hade några problem med den avsedda målmarknaden. Tre primära faktorer som påverkar den potentiella framgången identifierades. Dessa var den generellt låga tillgängligheten av internet till småbönder (begränsad av höga priser), avsaknad av utbildning som kan begränsa förståelsen av mer komplicerade processer, och smartphones med begränsad kapacitet för avancerade applikationer.

Approved for public release, distribution is unlimited / Unmanned vehicles (UVs) are expected to be an integral part of the U.S. Navy's expeditionary and carrier strike groups and are quickly being integrated into maritime operations. Command and control issues must be resolved, however, in order to utilize unmanned systems as intelligence, surveillance, and reconnaissance assets. The purpose of this research was to assess the current doctrine of mission tasking with respect to tactical unmanned vehicles (UVs) and determine a method for effectively tasking these systems. The problem was analyzed by applying the factors of METT-T: mission, enemy, terrain and weather, troops and support available, and time available to UV-enabled maritime missions. The analysis identified specific implications for unmanned vehicles and emphasized important considerations for tasking and allocating UVs. METT-T analyses generally result in courses of action, however, tasking is a command and control issue, and therefore, four organizational structures emerge for tasking UVs A significant finding of this study is that the current doctrinal framework of the composite warfare commander's concept can support tasking unmanned vehicles, but requires revision to effectively address UV allocation issues. / Ensign, United States Navy

This thesis investigated the effect of visuomotor and working memory 1) task difficulty and 2) multitasking on dynamic functional connectivity in the brain. Studies have only recently begun to investigate functional connectivity within the scope of concurrent dual task or varying task difficulty conditions (Cocchi, Zalesky, et al. 2011; Rietschel et al. 2012). A series of EEG recordings were conducted during execution of visuomotor or working memory tasks within a novel paradigm using BCI2VR custom MATLAB toolbox. Functional connectivity was correlated with task-related coherence (TRCoh) analysis between two task conditions involving either variation in task difficulty or concurrent execution during multitasking within the delta (0 – 4 Hz), theta (4 – 8 Hz), alpha (8 – 12 Hz), beta1 (12-16 Hz), beta2 (16 – 20 Hz) and beta3 (20 – 24 Hz) frequency bands. An increase in coherence was observed with increased cognitive load, during both increased task difficulty and multitasking, in all frequency bands except beta1 and beta2. This may suggest that the psychomotor efficiency hypothesis also applies to multitasking as well as task difficulty. Decreases in beta coherence were observed with increased performance error, indicating that interregional beta coherence may not follow the PEH trend. The increased coherence between brain regions in the alpha, delta and theta bands contributes to the growing volume of research on quantifying cognitive workload and may serve as a future basis on increasing multitasking efficiency during high stress environments. Further research recording multitasking effects on individuals over regular intervals during an extended period of time (months or years) will be required to better understand changes in functional connectivity within the brain.

In this work, sensor tasking refers to assigning the times and pointing directions for a sensor to collect observations of cataloged objects, in order to maintain the accuracy of the orbit estimates. Sensor tasking must consider the dynamics of the objects and uncertainty in their positions, the coordinate frame in which the sensor tasking is defined, the timing requirements for observations, the sensor capabilities, the local visibility, and constraints on the information processing and communication. This research focuses on finding efficient ways to solve the sensor tasking optimization problem. First, different coordinate frames are investigated, and it is shown that the observer fixed Local Meridian Equatorial (ground-based) and Satellite Meridian Equatorial (space-based) coordinate frames provide consistent sets of pointing directions and accurate representations of orbit uncertainty for use by the optimizers in solving the sensor tasking problem. Next, two classical optimizers (greedy and Weapon-Target Assignment) which rely on convexity are compared with two Machine Learning optimizers (Ant Colony Optimization and Distributed Q-learning) which attempt to learn about the solution space in order to approximate a global optimal solution. It is shown that the learning optimizers are able to generate better solutions, while the classical optimizers are more efficient to run and require less tuning to implement. Finally, the realistic scenario where the optimization algorithm receives no feedback before it must make the next decision is introduced. The Predicted Measurement Probability (PMP) is developed, and employed in a two sensor optimization framework. The PMP is shown to provide effective feedback to the optimization algorithm regarding the observations of each sensor.<br>

Abstract is available through the Abstracts of the Association for Research in Otolaryngology.

In recent years, evolving technology has provided a wide range of resources for Military forces. However, that wideness also caused resource management difficulties in combat missions. Air Tasking Order (ATO) is prepared for various missions of air combats in order to reach objectives by an optimized resource management. Considering combinatorial military aspects with dynamic objectives and various constraints / computer support became inevitable for optimizing the resource management in air force operations. In this thesis, we study different optimization approaches for resource allocation problem of ATO preparation and analyze their performance. We proposed a genetic algorithm formulation with customized encoding, crossover and fitness calculation mechanisms by using the domain knowledge. A linear programming formulation of the problem is developed by integer decision variables and it is used for effectivity and efficiency analysis of genetic algorithm formulations.

As wearable computers become more ubiquitous in society and work environments, there are concerns that their use could be negatively impactful in some settings. Previous research indicates that mobile phone and wearable computer use can impair walking and driving performance, but as these technologies are adopted into hazardous work environments it is less clear what the impact will be. The current research investigated the effects that head mounted display use has on high angle climbing, a task representative of the extreme physical demands of some hazardous occupations (such as firefighting or search and rescue work). We explored the effect that introducing a secondary word reading and later recall task has on both climbing performance (holds per meter climbed and distance covered), and word reading and recall (dual-task effects). We found a decrease in both climbing performance and word recall under dual task conditions. Further, we examined participant climbing motion around word presentation and non-word presentation times during the climbing traverse. We found that participants slowed around word presentations, relative to periods without word presentation. Finally, we compared our results to those found in previous research using similar dual-tasking paradigms. These comparisons indicated that physical tasks may be more detrimental to word recall than seated tasks, and that visual stimuli might hinder climbing performance more than audible stimuli. This research has important theoretical implications for the dual-tasking paradigm, as well at important practical implications for emergency response operations and other hazardous working environments.