879 resultados para multi-body system
Resumo:
In this contribution, the English commonhold system, which enables the development of freehold units in a multi-unit development, is critically re-visited. Provision is made for the development of freehold apartments on land with a registered commonhold title. At the date of registration, a management body for the scheme, the commonhold association, must be in place. Each purchaser of a unit in the relevant building obtains freehold property on purchase. The property and management of the building housing the units and of the common areas of the scheme are, by contrast, withheld from unit holders and vested in the commonhold association, which is a special kind of body corporate. Since the coming into force of the English legislation, a set of defects have been detected. This contribution re-assesses the main problem areas and makes a number of reform suggestions drawing on material from a number of jurisdictions, notably South Africa, France and Germany. Avoidable problems are likely to arise with any conversions to commonhold from the predominant English long lease system, owing to the narrowness of the conversion rules. The manner in which ownership of units and the common parts are regulated, a key aspect in any such system, merits re-assessment. It seems that here the English rules survive comparison. The rules pertaining to constitution of the commonhold association fail to provide sufficient safeguards for unpaid scheme creditors. The rules relating leasing of commonhold units seem inadequately thought out. There is a conspicuous absence of real remedies for non-payment of assessments by unit holders. The effect of these and other aspects may help to explain why commonhold has had a limited numerical impact. The time for a second generation reforming statute may have come.
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Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset.
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This paper examines biogas innovation system and processes in two farming communities in Davao del Sur, Philippines. Innovation histories were traced through workshops, semi-structured interviews, observations and document analysis. The paper shows that there were diverse innovation actors both from public and private sectors. Restrictive attitudes and practices resulted in weak and limited interactions among actors. Multi-actor interaction was weak, signifying a lack of innovation actors that focus on creating, developing and strengthening linkages, networks and partnerships. The lack of support in the socio-organisational institutions that constitute the enabling environment within which innovation actors operate may lead to systemic failure.
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Current methods and techniques used in designing organisational performance measurement systems do not consider the multiple aspects of business processes or the semantics of data generated during the lifecycle of a product. In this paper, we propose an organisational performance measurement systems design model that is based on the semantics of an organisation, business process and products lifecycle. Organisational performance measurement is examined from academic and practice disciplines. The multi-discipline approach is used as a research tool to explore the weaknesses of current models that are used to design organisational performance measurement systems. This helped in identifying the gaps in research and practice concerning the issues and challenges in designing information systems for measuring the performance of an organisation. The knowledge sources investigated include on-going and completed research project reports; scientific and management literature; and practitioners’ magazines.
Resumo:
The objective of this paper is to show that the group SE(3) with an imposed Lie-Poisson structure can be used to determine the trajectory in a spatial frame of a rigid body in Euclidean space. Identical results for the trajectory are obtained in spherical and hyperbolic space by scaling the linear displacements appropriately since the influence of the moments of inertia on the trajectories tends to zero as the scaling factor increases. The semidirect product of the linear and rotational motions gives the trajectory from a body frame perspective. It is shown that this cannot be used to determine the trajectory in the spatial frame. The body frame trajectory is thus independent of the velocity coupling. In addition, it is shown that the analysis can be greatly simplified by aligning the axes of the spatial frame with the axis of symmetry which is unchanging for a natural system with no forces and rotation about an axis of symmetry.
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Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.
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Forests are a store of carbon and an eco-system that continually removes carbon dioxide from the atmosphere. If they are sustainably managed, the carbon store can be maintained at a constant level, while the trees removed and converted to timber products can form an additional long term carbon store. The total carbon store in the forest and associated ‘wood chain’ therefore increases over time, given appropriate management. This increasing carbon store can be further enhanced with afforestation. The UK’s forest area has increased continually since the early 1900s, although the rate of increase has declined since its peak in the late 1980s, and it is a similar picture in the rest of Europe. The increased sustainable use of timber in construction is a key market incentive for afforestation, which can make a significant contribution to reducing carbon emissions. The case study presented in this paper demonstrates the carbon benefits of a Cross Laminated Timber (CLT) solution for a multi-storey residential building in comparison with a more conventional reinforced concrete solution. The embodied carbon of the building up to completion of construction is considered, together with the stored carbon during the life of the building and the impact of different end of life scenarios. The results of the study show that the total stored carbon in the CLT structural frame is 1215tCO2 (30tCO2 per housing unit). The choice of treatment at end of life has a significant effect on the whole life embodied carbon of the CLT frame, which ranges from -1017 tCO2e for re-use to +153tCO2e for incinerate without energy recovery. All end of life scenarios considered result in lower total CO2e emissions for the CLT frame building compared with the reinforced concrete frame solution.
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We have fabricated a compliant neural interface to record afferent nerve activity. Stretchable gold electrodes were evaporated on a polydimethylsiloxane (PDMS) substrate and were encapsulated using photo-patternable PDMS. The built-in microstructure of the gold film on PDMS allows the electrodes to twist and flex repeatedly, without loss of electrical conductivity. PDMS microchannels (5mm long, 100μm wide, 100μm deep) were then plasma bonded irreversibly on top of the electrode array to define five parallel-conduit implants. The soft gold microelectrodes have a low impedance of ~200kΩ at the 1kHz frequency range. Teased nerves from the L6 dorsal root of an anaesthetized Sprague Dawley rat were threaded through the microchannels. Acute tripolar recordings of cutaneous activity are demonstrated, from multiple nerve rootlets simultaneously. Confinement of the axons within narrow microchannels allows for reliable recordings of low amplitude afferents. This electrode technology promises exciting applications in neuroprosthetic devices including bladder fullness monitors and peripheral nervous system implants.
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To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor–outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier–Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate high-resolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios. Copyright © 2010 Royal Meteorological Society
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Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
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In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.
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Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.
Resumo:
Various fall-detection solutions have been previously proposed to create a reliable surveillance system for elderly people with high requirements on accuracy, sensitivity and specificity. In this paper, an enhanced fall detection system is proposed for elderly person monitoring that is based on smart sensors worn on the body and operating through consumer home networks. With treble thresholds, accidental falls can be detected in the home healthcare environment. By utilizing information gathered from an accelerometer, cardiotachometer and smart sensors, the impacts of falls can be logged and distinguished from normal daily activities. The proposed system has been deployed in a prototype system as detailed in this paper. From a test group of 30 healthy participants, it was found that the proposed fall detection system can achieve a high detection accuracy of 97.5%, while the sensitivity and specificity are 96.8% and 98.1% respectively. Therefore, this system can reliably be developed and deployed into a consumer product for use as an elderly person monitoring device with high accuracy and a low false positive rate.
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The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.
A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture
Resumo:
The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.