870 resultados para Maximal Monotone Operators


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Designed for independent living, retirement villages provide either detached or semi-detached residential dwellings with car parking and small private yards. Retirement village developments usually include a mix of independent living units (ILUs) and serviced apartments (SAs) with community facilities providing a shared congregational area for village activities and socialising. Retirement Village assets differ from traditional residential assets due to their operation in accordance with statutory legislation. In Australia, each State and Territory has its own Retirement Village Act and Regulations. In essence, the village operator provides the land and buildings to the residents who pay an amount on entry for the right of occupation. On departure from the units an agreed proportion of either the original purchase price or the sale price is paid to the outgoing resident. The market value of the operator’s interest in the Retirement Village is therefore based upon the estimated future income from Deferred Management Fees and Capital Gain upon roll-over receivable by the operator in accordance with the respective residency agreements. Given the lumpiness of these payments, there is general acceptance that the most appropriate approach to valuation is through Discounted Cash Flow (DCF) analysis. There is however inconsistency between valuers across Australia in how they undertake their DCF analysis, leading to differences in reported values and subsequent confusion among users of valuation services. To give guidance to valuers and enhance confidence from users of valuation services this paper investigates the five major elements of discounted cash flow methodology, namely cash flows, escalation factors, holding period, terminal value and discount rate. Whilst there is dissatisfaction with the financial structuring of the DMF in residency agreements, as long as there are future financial returns receivable by the Village owner/operator, then DCF will continue to be the most appropriate valuation methodology for resident funded retirement villages.

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On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

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This paper presents a modified approach to evaluate access control policy similarity and dissimilarity based on the proposal by Lin et al. (2007). Lin et al.'s policy similarity approach is intended as a filter stage which identifies similar XACML policies that can be analysed further using more computationally demanding techniques based on model checking or logical reasoning. This paper improves the approach of computing similarity of Lin et al. and also proposes a mechanism to calculate a dissimilarity score by identifying related policies that are likely to produce different access decisions. Departing from the original algorithm, the modifications take into account the policy obligation, rule or policy combining algorithm and the operators between attribute name and value. The algorithms are useful in activities involving parties from multiple security domains such as secured collaboration or secured task distribution. The algorithms allow various comparison options for evaluating policies while retaining control over the restriction level via a number of thresholds and weight factors.

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This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a Component-Based Software Engineering approach can address these constraints. The architecture is implemented using Orca – a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the Player software framework in the context of distributed systems.

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Micro-businesses, those with fewer than five employees, have a significant impact on the economy. These very small players represent 89% of all Australian businesses and, collectively, they provide 17% of the nation’s private sector employment. They are ubiquitous in Australia as in many other nations, embedded in local communities and therefore well placed to influence community wellbeing. Surprisingly, very little is known about micro-Business Community Responsibility (mBCR), the micro-business equivalent of Small Business Social Responsibility (SBSR) and Corporate Social Responsibility (CSR). Most national data available on business support for community wellbeing does not separately identify micro-business contributions. In this study an exploratory approach informed by business ethics theory was taken. Data from 36 semi-structured interviews was analysed to examine perceived mBCR approaches, motivations and barriers. The sample for this study was a mix of micro-business owner-operators situated in suburban shopping areas in Brisbane. Three types of mBCR emerged. All types are at least partly driven by enlightened selfinterest (ESI). However of the three mBCR types, two combine ESI with other approaches. One type combines ESI and philanthropic approaches to mBCR, and the other combines ESI with social entrepreneurial approaches to mBCR. The combination of doing business and doing good for many micro-business owneroperators, suggests mBCR may be a significant, yet unrecognised component of the third sector social economy.

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Food microstructure represents the way their elements arrangement and their interaction. Researchers in this field benefit from identifying new methods of examination of the microstructure and analysing the images. Experiments were undertaken to study micro-structural changes of food material during drying. Micro-structural images were obtained for potato samples of cubical shape at different moisture contents during drying using scanning electron microscopy. Physical parameters such as cell wall perimeter, and area were calculated using an image identification algorithm, based on edge detection and morphological operators. The algorithm was developed using Matlab.

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Background Up to one-third of people affected by cancer experience ongoing psychological distress and would benefit from screening followed by an appropriate level of psychological intervention. This rarely occurs in routine clinical practice due to barriers such as lack of time and experience. This study investigated the feasibility of community-based telephone helpline operators screening callers affected by cancer for their level of distress using a brief screening tool (Distress Thermometer), and triaging to the appropriate level of care using a tiered model. Methods Consecutive cancer patients and carers who contacted the helpline from September-December 2006 (n = 341) were invited to participate. Routine screening and triage was conducted by helpline operators at this time. Additional socio-demographic and psychosocial adjustment data were collected by telephone interview by research staff following the initial call. Results The Distress Thermometer had good overall accuracy in detecting general psychosocial morbidity (Hospital Anxiety and Depression Scale cut-off score ≥ 15) for cancer patients (AUC = 0.73) and carers (AUC = 0.70). We found 73% of participants met the Distress Thermometer cut-off for distress caseness according to the Hospital Anxiety and Depression Scale (a score ≥ 4), and optimal sensitivity (83%, 77%) and specificity (51%, 48%) were obtained with cut-offs of ≥ 4 and ≥ 6 in the patient and carer groups respectively. Distress was significantly associated with the Hospital Anxiety and Depression Scale scores (total, as well as anxiety and depression subscales) and level of care in cancer patients, as well as with the Hospital Anxiety and Depression Scale anxiety subscale for carers. There was a trend for more highly distressed callers to be triaged to more intensive care, with patients with distress scores ≥ 4 more likely to receive extended or specialist care. Conclusions Our data suggest that it was feasible for community-based cancer helpline operators to screen callers for distress using a brief screening tool, the Distress Thermometer, and to triage callers to an appropriate level of care using a tiered model. The Distress Thermometer is a rapid and non-invasive alternative to longer psychometric instruments, and may provide part of the solution in ensuring distressed patients and carers affected by cancer are identified and supported appropriately.

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The emergence of Twenty20 cricket at the elite level has been marketed on the excitement of the big hitter, where it seems that winning is a result of the muscular batter hitting boundaries at will. This version of the game has captured the imagination of many young players who all want to score runs with “big hits”. However, in junior cricket, boundary hitting is often more difficult due to size limitations of children and games played on outfields where the ball does not travel quickly. As a result, winning is often achieved via a less spectacular route – by scoring more singles than your opponents. However, most standard coaching texts only describe how to play boundary scoring shots (e.g. the drives, pulls, cuts and sweeps) and defensive shots to protect the wicket. Learning to bat appears to have been reduced to extremes of force production, i.e. maximal force production to hit boundaries or minimal force production to stop the ball from hitting the wicket. Initially, this is not a problem because the typical innings of a young player (<12 years) would be based on the concept of “block” or “bash” – they “block” the good balls and “bash” the short balls. This approach works because there are many opportunities to hit boundaries off the numerous inaccurate deliveries of novice bowlers. Most runs are scored behind the wicket by using the pace of the bowler’s delivery to re-direct the ball, because the intrinsic dynamics (i.e. lack of strength) of most children means that they can only create sufficient power by playing shots where the whole body can contribute to force production. This method works well until the novice player comes up against more accurate bowling when they find they have no way of scoring runs. Once batters begin to face “good” bowlers, batters have to learn to score runs via singles. In cricket coaching manuals (e.g. ECB, n.d), running between the wickets is treated as a separate task to batting, and the “basics” of running, such as how to “back- up”, carry the bat, calling and turning and sliding the bat into the crease are “drilled” into players. This task decomposition strategy focussing on techniques is a common approach to skill acquisition in many highly traditional sports, typified in cricket by activities where players hit balls off tees and receive “throw-downs” from coaches. However, the relative usefulness of these approaches in the acquisition of sporting skills is increasingly being questioned (Pinder, Renshaw & Davids, 2009). We will discuss why this is the case in the next section.

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Venous leg ulceration is a serious condition affecting 1 – 3% of the population. Decline in the function of the calf muscle pump is correlated with venous ulceration. Many previous studies have reported an improvement in the function of the calf muscle pump, endurance of the calf muscle and increased range of ankle motion after structured exercise programs. However, there is a paucity of published research that assesses if these improvements result in an improvement in the healing rates of venous ulcers. The primary purpose of this pilot study was to establish the feasibility of a homebased progressive resistance exercise program and examine if there was any clinical significance or trend toward healing. The secondary aims were to examine the benefit of a home-based progressive resistance exercise program on calf muscle pump function and physical parameters. The methodology used was a randomised controlled trial where eleven participants were randomised into an intervention (n = 6) or control group (n = 5). Participants who were randomised to receive a 12-week home-based progressive resistance exercise program were instructed through weekly face-to-face consultations during their wound clinic appointment by the author. Control group participants received standard wound care and compression therapy. Changes in ulcer parameters were measured fortnightly at the clinic (number healed at 12 weeks, percentage change in area and pressure ulcer score healing score). An air plethysmography test was performed at baseline and following the 12 weeks of training to determine changes in calf muscle pump function. Functional measures included maximum number of heel raises (endurance), maximal isometric plantar flexion (strength) and range of ankle motion (ROAM); these tests were conducted at baseline, week 6 and week 12. The sample for the study was drawn from the Princess Alexandra Hospital in Brisbane, Australia. Participants with venous leg ulceration who met the inclusion criteria were recruited. The participants were screened via duplex scanning and ankle brachial pressure index (ABPI) to ensure they did not have any arterial complications. Participants were excluded if there was evidence of cellulitis. Demographic data were obtained from each participant and details regarding medical history, quality of life and geriatric depression scores were collected at baseline. Both the intervention and control group were required to complete a weekly exercise diary to monitor activity levels between groups. To test for the effect of the intervention over time, a repeated measures analysis of variance was conducted on the major outcome variables. Group (intervention versus control) was the between subject factor and time (baseline, week 6, week 12) was the within subject or repeated measures factor. Due to the small sample size, further tests were conducted to check the assumptions of the statistical test to be used. The results showed that Mauchly.s Test, the Sphericity assumptions of repeated measures for ANOVA were met. Further tests of homogeneity of variance assumptions also confirmed that this assumption was met. Data analysis was conducted using the software package SPSS for Windows Release 17.0. The pilot study proved feasible with all of the intervention (n=6) participants continuing with the resistance program for the 12 week duration and no deleterious effects noted. Clinical significance was observed in the intervention group with a 32% greater change in ulcer size (p= 0.26) than the control group, and a 10% (p = 0.74) greater difference between the numbers healed compared to the control group. Statistical significance was observed for the ejection fraction (p = 0.05), residual volume fraction (p = 0.04) and ROAM (p = 0.01), which all improved significantly in the intervention group over time. These results are encouraging, nevertheless, further investigations seem warranted to examine the effect exercise has on the healing rates of venous leg ulcers, with a multistudy site, larger sample size and longer follow up period.

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In this paper, a comprehensive planning methodology is proposed that can minimize the line loss, maximize the reliability and improve the voltage profile in a distribution network. The injected active and reactive power of Distributed Generators (DG) and the installed capacitor sizes at different buses and for different load levels are optimally controlled. The tap setting of HV/MV transformer along with the line and transformer upgrading is also included in the objective function. A hybrid optimization method, called Hybrid Discrete Particle Swarm Optimization (HDPSO), is introduced to solve this nonlinear and discrete optimization problem. The proposed HDPSO approach is a developed version of DPSO in which the diversity of the optimizing variables is increased using the genetic algorithm operators to avoid trapping in local minima. The objective function is composed of the investment cost of DGs, capacitors, distribution lines and HV/MV transformer, the line loss, and the reliability. All of these elements are converted into genuine dollars. Given this, a single-objective optimization method is sufficient. The bus voltage and the line current as constraints are satisfied during the optimization procedure. The IEEE 18-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate the unavoidable need for optimal control on the DG active and reactive power and capacitors in distribution networks.

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Novel profluorescent nitroxides bearing a triazole linker between the coumarin fluorophore and an isoindoline nitroxide were prepared in good yields using the coppercatalyzed azide�alkyne 1,3-dipolar cycloaddition reaction (CuAAC). Nitroxides containing 7-hydroxy and 7-diethylamino substitution on their coumarin rings displayed significant fluorescence suppression, and upon reaction with methyl radicals, normal fluorescence emission was returned. The fluorescence emission for the 7-hydroxycoumarin nitroxide and its diamagnetic analogue was found to be strongly influenced by pH with maximal fluorescence emission achieved in basic solution. Solvent polarity was also shown to affect fluorescence emission. The significant difference in fluorescence output between the nitroxides and their corresponding diamagnetic analogues makes these compounds ideal tools for monitoring processes involving free-radical species.

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We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical VC dimension, empirical VC entropy, and margin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

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We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.

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In this paper we investigate the heuristic construction of bijective s-boxes that satisfy a wide range of cryptographic criteria including algebraic complexity, high nonlinearity, low autocorrelation and have none of the known weaknesses including linear structures, fixed points or linear redundancy. We demonstrate that the power mappings can be evolved (by iterated mutation operators alone) to generate bijective s-boxes with the best known tradeoffs among the considered criteria. The s-boxes found are suitable for use directly in modern encryption algorithms.

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Skeletal muscle displays enormous plasticity to respond to contractile activity with muscle from strength- (ST) and endurance-trained (ET) athletes representing diverse states of the adaptation continuum. Training adaptation can be viewed as the accumulation of specific proteins. Hence, the altered gene expression that allows for changes in protein concentration is of major importance for any training adaptation. Accordingly, the aim of the present study was to quantify acute subcellular responses in muscle to habitual and unfamiliar exercise. After 24-h diet/exercise control, 13 male subjects (7 ST and 6 ET) performed a random order of either resistance (8 × 5 maximal leg extensions) or endurance exercise (1 h of cycling at 70% peak O2 uptake). Muscle biopsies were taken from vastus lateralis at rest and 3 h after exercise. Gene expression was analyzed using real-time PCR with changes normalized relative to preexercise values. After cycling exercise, peroxisome proliferator-activated receptor-γ coactivator-1α (ET ∼8.5-fold, ST ∼10-fold, P < 0.001), pyruvate dehydrogenase kinase-4 (PDK-4; ET ∼26-fold, ST ∼39-fold), vascular endothelial growth factor (VEGF; ET ∼4.5-fold, ST ∼4-fold), and muscle atrophy F-box protein (MAFbx) (ET ∼2-fold, ST ∼0.4-fold) mRNA increased in both groups, whereas MyoD (∼3-fold), myogenin (∼0.9-fold), and myostatin (∼2-fold) mRNA increased in ET but not in ST (P < 0.05). After resistance exercise PDK-4 (∼7-fold, P < 0.01) and MyoD (∼0.7-fold) increased, whereas MAFbx (∼0.7-fold) and myostatin (∼0.6-fold) decreased in ET but not in ST. We conclude that prior training history can modify the acute gene responses in skeletal muscle to subsequent exercise.