572 resultados para multiple objective programming


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This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

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Objective Hallux valgus has been linked to functional disability and increased falls risk, but mechanisms underpinning functional disability are unclear. This study investigated functional performance, muscle strength and plantar pressures in adults with mild, moderate, and severe HV compared to controls, while considering the influence of foot pain. Methods Sixty adults with hallux valgus (classified as mild, moderate and severe on dorsalplantar radiographs) and 30 controls participated. Measures included: hallux plantarflexion and abduction strength, walking performance, postural sway and forefoot plantar pressures. Multiple analysis of covariance and pairwise comparisons (p<0.05, Bonferroni adjustment) were used to investigate differences between groups, adjusting for age, sex, body mass index and foot pain. Results Hallux plantarflexion and abduction strength was significantly reduced in those with moderate (mean differences: plantarflexion -45.8N, abduction -12.3N, p<0.001) and severe hallux valgus (plantarflexion -50.1N, p<0.001; abduction -11.2N, p=0.01) compared to controls. A significant reduction in hallux peak pressure and pressure-time integral was evident in moderate (peak pressure -90.8kPa, p<0.001) and severe hallux valgus (peak pressure -106.2kPa, p<0.001) compared to controls. Those with severe hallux valgus also demonstrated increased mediolateral postural sway in single leg stance compared to controls (3.5cm, p=0.01). Conclusion Moderate to severe hallux valgus is associated with reduced hallux plantar pressures and strength measures, while relatively normal function compared to controls was found in those with mild deformity. Greater understanding of specific functional deficits associated with different stages of hallux valgus will help inform clinical management and future research.

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NLS is a stream cipher which was submitted to the eSTREAM project. A linear distinguishing attack against NLS was presented by Cho and Pieprzyk, which was called Crossword Puzzle (CP) attack. NLSv2 is a tweak version of NLS which aims mainly at avoiding the CP attack. In this paper, a new distinguishing attack against NLSv2 is presented. The attack exploits high correlation amongst neighboring bits of the cipher. The paper first shows that the modular addition preserves pairwise correlations as demonstrated by existence of linear approximations with large biases. Next, it shows how to combine these results with the existence of high correlation between bits 29 and 30 of the S-box to obtain a distinguisher whose bias is around 2^−37. Consequently, we claim that NLSv2 is distinguishable from a random cipher after observing around 2^74 keystream words.

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The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.

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The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

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This chapter reports on a study that reveals the essence of participation in urban spaces by ten children who live with various physical conditions: Muscular Dystrophy, Cerebral Palsy, and Autoimmune Rheumatic Diseases. These conditions affect muscle and movement differently resulting in diverse ways in which children move through space (personal mobility). The children at the time of the research were 9-12 years of age residing in South-east Queensland, Australia. The approach and methods selected for this study, interpretive phenomenological inquiry and grounded theory, were chosen for their capacity to capture the complexity and multiple interactions of the child’s urban living. The confronting and poignant accounts by children and their families of their experiences produced a new way of understanding the concept of participation, as a ‘journey of becoming involved.’ Their accounts of performing everyday routines (e.g. leaving home, getting in and out of the car, and entering places) in urban spaces (neighbourhood streets, schools, open spaces, shopping centres, and hospitals) revealed differences in the way settings were experienced. These differences were associated with the interplay between the body, space and context. Where interplays were problematic, explicit decisions about children’s involvement were made. These decisions were described in terms of ‘avoid going’, ‘pick and choose’, ‘discontinue’, ‘accept’, or ‘contest.’ What these decisions mean is some spaces are avoided, some journeys are discontinued, and some barriers encountered in journeys are normalised as everyday experiences, i.e. ‘tolerable discrimination’. These actions resulted in experiences of non-participation or partial–tokenistic participation. The key substantive contribution of the research lies in the identification of points in children’s journeys that shape participation experience. These points identify where future interventions in policy, programming and design can be made to make real and sustaining changes to lives of children and their families in geographies crucial to urban living.

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This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

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Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

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This study explores the idea of video games where the players are not just allowed to express themselves creatively, but are challenged to do so and are judged based on the quality of their creative expression. The outcome of the research is a series of six games which comment on this idea. The study also raises further questions regarding how current video games are constructed and designed in comparison with non-computer games, and invites a further evolution of the craft of video game design in a direction that focuses more on interpreting and reacting to what the player is doing.

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Abstract - Enterprise Resource Planning (ERP) software has become the dominant strategic platform for supporting enterprise-wide business processes. However, single vendor ERP software systems have been criticised for not meeting specific organisation and industry requirements. An alternative approach ‘Best of Breed (BoB)’, integrates components of software from multiple standard package vendors, and in some cases custom components. The objective is to develop enterprise systems that are more closely aligned with the requirements of an organisation. Although this approach may not be common at present it is likely to grow in importance due to business needs and technology advances such as the componentisation of ERP software. A case study analysis of a BoB implementation at a global entertainment's company is used as a platform for the discussion of the issues associated with this strategy and a comparison is made with the single vendor ERP alternative. The analysis centres on the complexity of implementation, the differences in the levels of functionality and business fit and the maintenance requirements.

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Background Despite the importance of an effective health system response to various disasters, relevant research is still in its infancy, especially in middle- and low-income countries. Objective This paper provides an overview of the status of disaster health management in China, with its aim to promote the effectiveness of the health response for reducing disaster-related mortality and morbidity. Design A scoping review method was used to address the recent progress of and challenges to disaster health management in China. Major health electronic databases were searched to identify English and Chinese literature that were relevant to the research aims. Results The review found that since 2003 considerable progress has been achieved in the health disaster response system in China. However, there remain challenges that hinder effective health disaster responses, including low standards of disaster-resistant infrastructure safety, the lack of specific disaster plans, poor emergency coordination between hospitals, lack of portable diagnostic equipment and underdeveloped triage skills, surge capacity, and psychological interventions. Additional challenges include the fragmentation of the emergency health service system, a lack of specific legislation for emergencies, disparities in the distribution of funding, and inadequate cost-effective considerations for disaster rescue. Conclusions One solution identified to address these challenges appears to be through corresponding policy strategies at multiple levels (e.g. community, hospital, and healthcare system level).

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This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

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Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

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This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; downloading the program to the Spartan-3E board using version 14.7 of the Xilinx ISE; and simulating the program using the iSim Simulator.