449 resultados para Robot applications


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Background Maintenance of communication is important for people with dementia living in long-term care. The purpose of this study was to assess the feasibility of using “Giraff”, a telepresence robot to enhance engagement between family and a person with dementia living in long-term care. Methods A mixed-methods approach involving semi-structured interviews, call records and video observational data was used. Five people with dementia and their family member participated in a discussion via the Giraff robot for a minimum of six times over a six-week period. A feasibility framework was used to assess feasibility and included video analysis of emotional response and engagement. Results Twenty-six calls with an average duration of 23 mins took place. Residents showed a general state of positive emotions across the calls with a high level of engagement and a minimal level of negative emotions. Participants enjoyed the experience and families reported that the Giraff robot offered the opportunity to reduce social isolation. A number of software and hardware challenges were encountered. Conclusions Participants perceived this novel approach to engage families and people with dementia as a feasible option. Participants were observed and also reported to enjoy the experience. The technical challenges identified have been improved in a newer version of the robot. Future research should include a feasibility trial of longer duration, with a larger sample and a cost analysis.

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BACKGROUND: Over the past 10 years, the use of saliva as a diagnostic fluid has gained attention and has become a translational research success story. Some of the current nanotechnologies have been demonstrated to have the analytical sensitivity required for the use of saliva as a diagnostic medium to detect and predict disease progression. However, these technologies have not yet been integrated into current clinical practice and work flow. CONTENT: As a diagnostic fluid, saliva offers advantages over serum because it can be collected noninvasively by individuals with modest training, and it offers a cost-effective approach for the screening of large populations. Gland-specific saliva can also be used for diagnosis of pathology specific to one of the major salivary glands. There is minimal risk of contracting infections during saliva collection, and saliva can be used in clinically challenging situations, such as obtaining samples from children or handicapped or anxious patients, in whom blood sampling could be a difficult act to perform. In this review we highlight the production of and secretion of saliva, the salivary proteome, transportation of biomolecules from blood capillaries to salivary glands, and the diagnostic potential of saliva for use in detection of cardiovascular disease and oral and breast cancers. We also highlight the barriers to application of saliva testing and its advancement in clinical settings. SUMMARY: Saliva has the potential to become a first-line diagnostic sample of choice owing to the advancements in detection technologies coupled with combinations of biomolecules with clinical relevance. (C) 2011 American Association for Clinical Chemistry

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Over the past 10 years, the use of saliva as a diagnostic fluid has gained attention and has become a translational research success story. Some of the current nanotechnologies have been demonstrated to have the analytical sensitivity required for the use of saliva as a diagnostic medium to detect and predict disease progression. However, these technologies have not yet been integrated into current clinical practice and work flow. As a diagnostic fluid, saliva offers advantages over serum because it can be collected noninvasively by individuals with modest training, and it offers a cost-effective approach for the screening of large populations. Gland-specific saliva can also be used for diagnosis of pathology specific to one of the major salivary glands. There is minimal risk of contracting infections during saliva collection, and saliva can be used in clinically challenging situations, such as obtaining samples from children or handicapped or anxious patients, in whom blood sampling could be a difficult act to perform. In this review we highlight the production of and secretion of saliva, the salivary proteome, transportation of biomolecules from blood capillaries to salivary glands, and the diagnostic potential of saliva for use in detection of cardiovascular disease and oral and breast cancers. We also highlight the barriers to application of saliva testing and its advancement in clinical settings. Saliva has the potential to become a first-line diagnostic sample of choice owing to the advancements in detection technologies coupled with combinations of biomolecules with clinical relevance.

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Saliva as a biological fluid is gaining wider acceptance for diagnosing diseases. The growing interest in saliva as a biological fluid is due to its noninvasiveness, ease of use, cost-effectiveness, and multiple sample collection possibilities as well as minimal risk to health care professionals of contracting infectious organisms such as HIV and Hep B. However, the clinical translation of saliva is hampered by our lack of understanding of the biomolecular transportation from blood into saliva, the diurnal variations of biomolecules present in saliva, and relatively low levels of analytes (100th to a 1000th fold less than in blood). We provide information on the current status of salivary research, salivary diagnostics empowered by nanotechnology, and future prospects in this emerging field of saliva diagnostics.

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This chapter examines how the methods, outcomes and transformative potentials of my new media arts praxis have been understood by a range of critical commentators from disciplinary perspectives outside of my own ‘home territory’ of media arts. By drawing upon perspectives from Human Computer Interface Design, Engineering, Sustainability Design, Tertiary Education, Communication Design and Public Librarianship I demonstrate how ideas from my arts disciplines have had tangible ‘external’ significance and application.

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Locomotion and autonomy in humanoid robots is of utmost importance in integrating them into social and community service type roles. However, the limited range and speed of these robots severely limits their ability to be deployed in situations where fast response is necessary. While the ability for a humanoid to drive a vehicle would aide in increasing their overall mobility, the ability to mount and dismount a vehicle designed for human occupants is a non-trivial problem. To address this issue, this paper presents an innovative approach to enabling a humanoid robot to mount and dismount a vehicle by proposing a simple mounting bracket involving no moving parts. In conjunction with a purpose built robotic vehicle, the mounting bracket successfully allowed a humanoid Nao robot to mount, dismount and drive the vehicle.

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This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

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As one of the transition metal oxides, niobium pentoxide (Nb2O5) offers a broad variety of properties that make it a potentially useful and highly applicable material in many different areas. In comparison to many other transition metal oxides, Nb2O5 has received relatively little attention, which presents a significant opportunity for future investigations aimed at fundamentally understanding this material and finding new and interesting applications for it. In this article, a general overview of Nb2O5 is presented which focuses on its fundamental properties, synthesis methods and recent applications, along with a discussion on future research directions relevant to this material.

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Cool roof coatings are identified by their solar reflectance index. They have been reported to have multiple benefits, the extent of which are strongly dependent on the peculiarities of the local climate, building stock and electricity network. This paper presents measured and simulated data from residential, educational and commercial buildings involved in recent field trials in Australia. The purpose of the field trials was to evaluate the impact of such coatings on electricity demand and load and to assess their potential application to improve comfort whilst avoiding the need for air conditioners. Measured reductions in temperature, power (kW) and energy (kWh) were used to develop a predictive model that correlates ambient temperature distribution profiles, building demand reduction profiles and electricity network peak demand times. Combined with simulated data, the study indicates the types of buildings that could be targeted in Demand Management programs for the mutual benefit of electricity networks and building occupants.

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This paper presents a low-bandwidth multi-robot communication system designed to serve as a backup communication channel in the event a robot suffers a network device fault. While much research has been performed in the area of distributing network communication across multiple robots within a system, individual robots are still susceptible to hardware failure. In the past, such robots would simply be removed from service, and their tasks re-allocated to other members. However, there are times when a faulty robot might be crucial to a mission, or be able to contribute in a less communication intensive area. By allowing robots to encode and decode messages into unique sequences of DTMF symbols, called words, our system is able to facilitate continued low-bandwidth communication between robots without access to network communication. Our results have shown that the system is capable of permitting robots to negotiate task initiation and termination, and is flexible enough to permit a pair of robots to perform a simple turn taking task.

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Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

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Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.

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We demonstrate potential applications for unusual dendrite like Au–Ag alloy nanoparticles formed via a galvanic replacement reaction in the ionic liquid [BMIM][BF4]. In comparison to Au–Ag alloy nanoshells synthesised via a similar reaction in water, the unusual branched structure of the dendritic materials led to increased electrocatalytic activity for the oxidation of both formaldehyde and hydrazine, and increased sensitivity and spectral resolution for the surface enhanced Raman scattering (SERS) of 4,4-bipyridal.

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Techniques are presented for enhancing weak Raman scattering signals for rapid yet accurate substance detection. Novel surfaces that allow signal enhancement quantification are described as are eye-safe methodologies that maximize the stand-off Raman detection range.

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This thesis demonstrates that robots can learn about how the world changes, and can use this information to recognise where they are, even when the appearance of the environment has changed a great deal. The ability to localise in highly dynamic environments using vision only is a key tool for achieving long-term, autonomous navigation in unstructured outdoor environments. The proposed learning algorithms are designed to be unsupervised, and can be generated by the robot online in response to its observations of the world, without requiring information from a human operator or other external source.