190 resultados para Residual-Based Cointegration Test


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To ensure better concrete quality and long-term durability, there has been an increasing focus in recent years on the development of test methods for quality control of concrete. This paper presents a study to evaluate the effect of water accessible porosity and oven-dry unit weight on the resistance of concrete to chloride-ion penetration. Based on the experimental results and regression analyses, empirical relationships of the charge passed (ASTM C 1202) and chloride migration coefficient (NT Build 492) versus the water accessible porosity and oven dry unit weight of the concrete are established. Using basic physical properties of water accessible porosity and oven dry unit weight which can be easily determined, total charge passed and migration coefficient of the concrete can be estimated for quality control and for estimating durability of concrete.

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Residual amplitude modulation (RAM) is an unwanted noise source in electro-optic phase modulators. The analysis presented shows that while the magnitude of the RAM produced by a MgO:LiNbO3 modulator increases with intensity, its associated phase becomes less well defined. This combination results in temporal fluctuations in RAM that increase with intensity. This behaviour is explained by the presented phenomenological model based on gradually evolving photorefractive scattering centres randomly distributed throughout the optically thick medium. This understanding is exploited to show that RAM can be reduced to below the 10-5 level by introducing an intense optical beam to erase the photorefractive scatter.

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STUDY DESIGN: Reliability and case-control injury study. OBJECTIVES: 1) To determine if a novel device, designed to measure eccentric knee flexors strength via the Nordic hamstring exercise (NHE), displays acceptable test-retest reliability; 2) to determine normative values for eccentric knee flexors strength derived from the device in individuals without a history of hamstring strain injury (HSI) and; 3) to determine if the device could detect weakness in elite athletes with a previous history of unilateral HSI. BACKGROUND: HSIs and reinjuries are the most common cause of lost playing time in a number of sports. Eccentric knee flexors weakness is a major modifiable risk factor for future HSIs, however there is a lack of easily accessible equipment to assess this strength quality. METHODS: Thirty recreationally active males without a history of HSI completed NHEs on the device on 2 separate occasions. Intraclass correlation coefficients (ICCs), typical error (TE), typical error as a co-efficient of variation (%TE), and minimum detectable change at a 95% confidence interval (MDC95) were calculated. Normative strength data were determined using the most reliable measurement. An additional 20 elite athletes with a unilateral history of HSI within the previous 12 months performed NHEs on the device to determine if residual eccentric muscle weakness existed in the previously injured limb. RESULTS: The device displayed high to moderate reliability (ICC = 0.83 to 0.90; TE = 21.7 N to 27.5 N; %TE = 5.8 to 8.5; MDC95 = 76.2 to 60.1 N). Mean±SD normative eccentric flexors strength, based on the uninjured group, was 344.7 ± 61.1 N for the left and 361.2 ± 65.1 N for the right side. The previously injured limbs were 15% weaker than the contralateral uninjured limbs (mean difference = 50.3 N; 95% CI = 25.7 to 74.9N; P < .01), 15% weaker than the normative left limb data (mean difference = 50.0 N; 95% CI = 1.4 to 98.5 N; P = .04) and 18% weaker than the normative right limb data (mean difference = 66.5 N; 95% CI = 18.0 to 115.1 N; P < .01). CONCLUSIONS: The experimental device offers a reliable method to determine eccentric knee flexors strength and strength asymmetry and revealed residual weakness in previously injured elite athletes.

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In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.

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In recent years face recognition systems have been applied in various useful applications, such as surveillance, access control, criminal investigations, law enforcement, and others. However face biometric systems can be highly vulnerable to spoofing attacks where an impostor tries to bypass the face recognition system using a photo or video sequence. In this paper a novel liveness detection method, based on the 3D structure of the face, is proposed. Processing the 3D curvature of the acquired data, the proposed approach allows a biometric system to distinguish a real face from a photo, increasing the overall performance of the system and reducing its vulnerability. In order to test the real capability of the methodology a 3D face database has been collected simulating spoofing attacks, therefore using photographs instead of real faces. The experimental results show the effectiveness of the proposed approach.

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OBJECTIVE: The objective of this study was to describe the distribution of conjunctival ultraviolet autofluorescence (UVAF) in an adult population. METHODS: We conducted a cross-sectional, population-based study in the genetic isolate of Norfolk Island, South Pacific Ocean. In all, 641 people, aged 15 to 89 years, were recruited. UVAF and standard (control) photographs were taken of the nasal and temporal interpalpebral regions bilaterally. Differences between the groups for non-normally distributed continuous variables were assessed using the Wilcoxon-Mann-Whitney ranksum test. Trends across categories were assessed using Cuzick's non-parametric test for trend or Kendall's rank correlation τ. RESULTS: Conjunctival UVAF is a non-parametric trait with a positively skewed distribution. Median amount of conjunctival UVAF per person (sum of four measurements; right nasal/temporal and left nasal/temporal) was 28.2 mm(2) (interquartile range 14.5-48.2). There was an inverse, linear relationship between UVAF and advancing age (P<0.001). Males had a higher sum of UVAF compared with females (34.4 mm(2) vs 23.2 mm(2), P<0.0001). There were no statistically significant differences in area of UVAF between right and left eyes or between nasal and temporal regions. CONCLUSION: We have provided the first quantifiable estimates of conjunctival UVAF in an adult population. Further data are required to provide information about the natural history of UVAF and to characterise other potential disease associations with UVAF. UVR protective strategies should be emphasised at an early age to prevent the long-term adverse effects on health associated with excess UVR.

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Geographical market expansion is included in various definitions of entrepreneurship as it entails the opening up of new markets (for example, Davidsson 2003). Expansion into new international markets and launch of new products in international markets are also consistent with definitions of entrepreneurship which center on the pursuit of opportunities {e.g.\Stevenson, 1983 #922;Gartner, 1993 #931}. Accordingly, the decision by managers of small, internationally active businesses to continue to internationalize can be viewed as an entrepreneurial act. In spite of the fact that both start-ups and existing firms can behave entrepreneurially by expanding into new international markets, the attention of entrepreneurship researchers interested in international activities has largely focused on international new ventures (INVs); that is, business organizations that internationalize from inception (Oviatt, and McDougall 1994; Oviatt, and McDougall 1997). Consequently, pursuit of international opportunities by established small and medium-sized enterprises (SMEs) lacks theoretical understanding and empirical investigation through an entrepreneurship lens. This paper contributes to the body of knowledge at the entrepreneurship-internationalization interface by testing whether Stevenson’s opportunity-based conceptualization of entrepreneurial management (Stevenson 1983; Stevenson and Gumpert 1985; Stevenson and Jarillo 1990) can explain the attainment of continued entrepreneurial outcomes by SMEs operating in foreign markets. We choose Stevenson’s conceptualization as it gauges firm-level characteristics that are theorized to facilitate the pursuit of entrepreneurial opportunities, which arguably is at the heart of SMEs’ continued venturing into international markets.

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The inconsistent findings of past board diversity research demand a test of competing linear and curvilinear diversity–performance predictions. This research focuses on board age and gender diversity, and presents a positive linear prediction based on resource dependence theory, a negative linear prediction based on social identity theory, and an inverted U-shaped curvilinear prediction based on the integration of resource dependence theory with social identity theory. The predictions were tested using archival data on 288 large organizations listed on the Australian Securities Exchange, with a 1-year time lag between diversity (age and gender) and performance (employee productivity and return on assets). The results indicate a positive linear relationship between gender diversity and employee productivity, a negative linear relationship between age diversity and return on assets, and an inverted U-shaped curvilinear relationship between age diversity and return on assets. The findings provide additional evidence on the business case for board gender diversity and refine the business case for board age diversity.

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This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

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Incorporating engineering concepts into middle school curriculum is seen as an effective way to improve students’ problem-solving skills. A selection of findings is reported from a science, technology, engineering and mathematics (STEM)-based unit in which students in the second year (grade 8) of a three-year longitudinal study explored engineering concepts and principles pertaining to the functioning of simple machines. The culminating activity, the focus of this paper, required the students to design, construct, test, and evaluate a trebuchet catapult. We consider findings from one of the schools, a co-educational school, where we traced the design process developments of four student groups from two classes. The students’ descriptions and explanations of the simple machines used in their catapult design are examined, together with how they rated various aspects of their engineering designs. Included in the findings are students’ understanding of how their simple machines were simulated by the resources supplied and how the machines interacted in forming a complex machine. An ability to link physical materials with abstract concepts and an awareness of design constraints on their constructions were apparent, although a desire to create a ‘‘perfect’’ catapult despite limitations in the physical materials rather than a prototype for testing concepts was evident. Feedback from teacher interviews added further insights into the students’ developments as well as the teachers’ professional learning. An evolving framework for introducing engineering education in the pre-secondary years is proposed.

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The pull-through/local dimpling failure strength of screwed connections is very important in the design of profiled steel cladding systems to help them resist storms and hurricanes. The current American and European provisions recommend four different test methods for the screwed connections in tension, but the accuracy of these methods in determining the connection strength is not known. It is unlikely that the four test methods are equivalent in all cases and thus it is necessary to reduce the number of methods recommended. This paper presents a review of these test methods based on some laboratory tests on crest- and valley-fixed claddings and then recommends alternative tests methods that reproduce the real behavior of the connections, including the bending and membrane deformations of the cladding around the screw fasteners and the tension load in the fastener.

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The coupling of kurtosis based-indexes and envelope analysis represents one of the most successful and widespread procedures for the diagnostics of incipient faults on rolling element bearings. Kurtosis-based indexes are often used to select the proper demodulation band for the application of envelope-based techniques. Kurtosis itself, in slightly different formulations, is applied for the prognostic and condition monitoring of rolling element bearings, as a standalone tool for a fast indication of the development of faults. This paper shows for the first time the strong analytical connection which holds for these two families of indexes. In particular, analytical identities are shown for the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal. In particular, it is demonstrated how the sum of the peaks in the SES corresponds to the raw 4th order moment. The analytical results show as well a link with an another signal processing technique: the cepstrum pre-whitening, recently used in bearing diagnostics. The analytical results are the basis for the discussion on an optimal indicator for the choice of the demodulation band, the ratio of cyclic content (RCC), which endows the kurtosis with selectivity in the cyclic frequency domain and whose performance is compared with more traditional kurtosis-based indicators such as the protrugram. A benchmark, performed on numerical simulations and experimental data coming from two different test-rigs, proves the superior effectiveness of such an indicator. Finally a short introduction to the potential offered by the newly proposed index in the field of prognostics is given in an additional experimental example. In particular the RCC is tested on experimental data collected on an endurance bearing test-rig, showing its ability to follow the development of the damage with a single numerical index.

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Design of hydraulic turbines has often to deal with hydraulic instability. It is well-known that Francis and Kaplan types present hydraulic instability in their design power range. Even if modern CFD tools may help to define these dangerous operating conditions and optimize runner design, hydraulic instabilities may fortuitously arise during the turbine life and should be timely detected in order to assure a long-lasting operating life. In a previous paper, the authors have considered the phenomenon of helical vortex rope, which happens at low flow rates when a swirling flow, in the draft tube conical inlet, occupies a large portion of the inlet. In this condition, a strong helical vortex rope appears. The vortex rope causes mechanical effects on the runner, on the whole turbine and on the draft tube, which may eventually produce severe damages on the turbine unit and whose most evident symptoms are vibrations. The authors have already shown that vibration analysis is suitable for detecting vortex rope onset, thanks to an experimental test campaign performed during the commissioning of a 23 MW Kaplan hydraulic turbine unit. In this paper, the authors propose a sophisticated data driven approach to detect vortex rope onset at different power load, based on the analysis of the vibration signals in the order domain and introducing the so-called "residual order spectrogram", i.e. an order-rotation representation of the vibration signal. Some experimental test runs are presented and the possibility to detect instability onset, especially in real-time, is discussed.

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Delirium is a significant problem for older hospitalized people and is associated with poor outcomes. It is poorly recognized and evidence suggests that a major reason is lack of education. Nurses, who are educated about delirium, can play a significant role in improving delirium recognition. This study evaluated the impact of a delirium specific educational website. A cluster randomized controlled trial, with a pretest/post-test time series design, was conducted to measure delirium knowledge (DK) and delirium recognition (DR) over three time-points. Statistically significant differences were found between the intervention and non-intervention group. The intervention groups' DK scores were higher and the change over time results were statistically significant [T3 and T1 (t=3.78 p=<0.001) and T2 and T1 baseline (t=5.83 p=<0.001)]. Statistically significant improvements were also seen for DR when comparing T2 and T1 results (t=2.56 p=0.011) between both groups but not for changes in DR scores between T3 and T1 (t=1.80 p=0.074). Participants rated the website highly on the visual, functional and content elements. This study supports the concept that web-based delirium learning is an effective and satisfying method of information delivery for registered nurses. Future research is required to investigate clinical outcomes as a result of this web-based education.

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Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.