790 resultados para fund performance evaluation


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Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

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Approximately half of the houses in Northern Ireland were built before any form of minimum thermal specification or energy efficiency standard was enforced. Furthermore, 44% of households are categorised as being in fuel poverty; spending more than 10% of the household income to heat the house to bring it to an acceptable level of thermal comfort. To bring existing housing stock up to an acceptable standard, retrofitting for improving the energy efficiency is essential and it is also necessary to study the effectiveness of such improvements in future climate scenarios. This paper presents the results from a year-long performance monitoring of two houses that have undergone retrofits to improve energy efficiency. Using wireless sensor technology internal temperature, humidity, external weather, household gas and electricity usage were monitored for a year. Simulations using IES-VE dynamic building modelling software were calibrated using the monitoring data to ASHARE Guideline 14 standards. The energy performance and the internal environment of the houses were then assessed for current and future climate scenarios and the results show that there is a need for a holistic balanced strategy for retrofitting.

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Currently, no standard mix design procedure is available for CIR-emulsion in Iowa. The CIR-foam mix design process developed during the previous phase is applied for CIR-emulsion mixtures with varying emulsified asphalt contents. Dynamic modulus test, dynamic creep test, static creep test and raveling test were conducted to evaluate the short- and long-term performance of CIR-emulsion mixtures at various testing temperatures and loading conditions. A potential benefit of this research is a better understanding of CIR-emulsion material properties in comparison with those of CIR-foam material that would allow for the selection of the most appropriate CIR technology and the type and amount of the optimum stabilization material. Dynamic modulus, flow number and flow time of CIR-emulsion mixtures using CSS-1h were generally higher than those of HFMS-2p. Flow number and flow time of CIR-emulsion using RAP materials from Story County was higher than those from Clayton County. Flow number and flow time of CIR-emulsion with 0.5% emulsified asphalt was higher than CIR-emulsion with 1.0% or 1.5%. Raveling loss of CIR-emulsion with 1.5% emulsified was significantly less than those with 0.5% and 1.0%. Test results in terms of dynamic modulus, flow number, flow time and raveling loss of CIR-foam mixtures are generally better than those of CIR-emulsion mixtures. Given the limited RAP sources used for this study, it is recommended that the CIR-emulsion mix design procedure should be validated against several RAP sources and emulsion types.

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We investigate whether Real Estate Investment Trust (REIT) managers actively manipulate performance measures in spite of the strict regulation under the REIT regime. We provide empirical evidence that is consistent with this hypothesis. Specifically, manipulation strategies may rely on the opportunistic use of leverage. However, manipulation does not appear to be uniform across REIT sectors and seems to become more common as the level of competition in the underlying property sector increases. We employ a set of commonly used traditional performance measures and a recently developed manipulation-proof measure (MPPM, Goetzmann, Ingersoll, Spiegel, and Welch (2007)) to evaluate the performance of 147 REITs from seven different property sectors over the period 1991-2009. Our findings suggest that the existing REIT regulation may fail to mitigate a substantial agency conflict and that investors can benefit from evaluating return information carefully in order to avoid potentially manipulative funds.

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The Millennium Challenge Corporation (MCC) contracted the Technology & Social Change group (TASCHA) at the University of Washington to conduct a performance evaluation of the Namibia Regional Study and Resource Centers (RSRC) Activity. This evaluation has been designed to serve the needs of two major stakeholders, MCC and the Namibia Library and Archives Service (NLAS). The evaluation comprises a set of quantitative and qualitative data collection efforts divided into two categories: Component 1 and Component 2. This report presents the findings for Component 1 only, focusing on evaluating the RSRC planning and implementation activities leading up to the end of the MCA-Namibia Compact in September 2014.

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The mixing performance of three passive milli-scale reactors with different geometries was investigated at different Reynolds numbers. The effects of design and operating characteristics such as mixing channel shape and volume flow rate were investigated. The main objective of this work was to demonstrate a process design method that uses on Computational Fluid Dynamics (CFD) for modeling and Additive Manufacturing (AM) technology for manufacture. The reactors were designed and simulated using SolidWorks and Fluent 15.0 software, respectively. Manufacturing of the devices was performed with an EOS M-series AM system. Step response experiments with distilled Millipore water and sodium hydroxide solution provided time-dependent concentration profiles. Villermaux-Dushman reaction experiments were also conducted for additional verification of CFD results and for mixing efficiency evaluation of the different geometries. Time-dependent concentration data and reaction evaluation showed that the performance of the AM-manufactured reactors matched the CFD results reasonably well. The proposed design method allows the implementation of new and innovative solutions, especially in the process design phase, for industrial scale reactor technologies. In addition, rapid implementation is another advantage due to the virtual flow design and due to the fast manufacturing which uses the same geometric file formats.

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Malicious users try to compromise systems using new techniques. One of the recent techniques used by the attacker is to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These compromised machines are said to be infected with malicious software termed a “bot”. In this paper, we investigate the correlation of behavioural attributes such as keylogging and packet flooding behaviour to detect the existence of a single bot on a compromised machine by applying (1) Spearman’s rank correlation (SRC) algorithm and (2) the Dendritic Cell Algorithm (DCA). We also compare the output results generated from these two methods to the detection of a single bot. The results show that the DCA has a better performance in detecting malicious activities.

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This paper evaluates the performance of a survivorship bias-free data set of Portuguese funds investing in Euro-denominated bonds by using conditional models that consider the public information available to investors when the returns are generated. We find that bond funds underperform the market significantly and by an economically relevant magnitude. This underperformance cannot be explained by the expenses they charge. Our findings support the use of conditional performance evaluation models, since we find strong evidence of both time-varying risk and performance, dependent on the slope of the term structure and the inverse relative wealth variables. We also show that survivorship bias has a significant impact on performance estimates. Furthermore, during the European debt crisis, bond fund managers performed significantly better than in non-crisis periods and were able to achieve neutral performance. This improved performance throughout the crisis seems to be related to changes in funds’ investment styles.

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The functional and structural performance of a 5 cm synthetic small diameter vascular graft (SDVG) produced by the copolymerization of polyvinyl alcohol hydrogel with low molecular weight dextran (PVA/Dx graft) associated to mesenchymal stem cells (MSCs)-based therapies and anticoagulant treatment with heparin, clopidogrel and warfarin was tested using the ovine model during the healing period of 24 weeks. The results were compared to the ones obtained with standard expanded polyetetrafluoroethylene grafts (ePTFE graft). Blood flow, vessel and graft diameter measurements, graft appearance and patency rate (PR), thrombus, stenosis and collateral vessel formation were evaluated by B-mode ultrasound, audio and color flow Doppler. Graft and regenerated vessels morphologic evaluation was performed by scanning electronic microscopy (SEM), histopathological and immunohistochemical analysis. All PVA/Dx grafts could maintain a similar or higher PR and systolic / diastolic laminar blood flow velocities were similar to ePTFE grafts. CD14 (macrophages) and α-actin (smooth muscle) staining presented similar results in PVA/Dx/MSCs and ePTFE graft groups. Fibrosis layer was lower and endothelial cells were only detected at graft-artery transitions where it was added the MSCs. In conclusion, PVA/Dx graft can be an excellent scaffold candidate for vascular reconstruction, including clinic mechanically challenging applications, such as SDVGs, especially when associated to MSCs-based therapies to promote higher endothelialization and lower fibrosis of the vascular prosthesis, but also higher PR values.

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This report fully summarises a project designed to enhance commercial real estate performance within both operational and investment contexts through the development of a model aimed at supporting improved decision-making. The model is based on a risk adjusted discounted cash flow, providing a valuable toolkit for building managers, owners, and potential investors for evaluating individual building performance in terms of financial, social and environmental criteria over the complete life-cycle of the asset. The ‘triple bottom line’ approach to the evaluation of commercial property has much significance for the administrators of public property portfolios in particular. It also has applications more generally for the wider real estate industry given that the advent of ‘green’ construction requires new methods for evaluating both new and existing building stocks. The research is unique in that it focuses on the accuracy of the input variables required for the model. These key variables were largely determined by market-based research and an extensive literature review, and have been fine-tuned with extensive testing. In essence, the project has considered probability-based risk analysis techniques that required market-based assessment. The projections listed in the partner engineers’ building audit reports of the four case study buildings were fed into the property evaluation model developed by the research team. The results are strongly consistent with previously existing, less robust evaluation techniques. And importantly, this model pioneers an approach for taking full account of the triple bottom line, establishing a benchmark for related research to follow. The project’s industry partners expressed a high degree of satisfaction with the project outcomes at a recent demonstration seminar. The project in its existing form has not been geared towards commercial applications but it is anticipated that QDPW and other industry partners will benefit greatly by using this tool for the performance evaluation of property assets. The project met the objectives of the original proposal as well as all the specified milestones. The project has been completed within budget and on time. This research project has achieved the objective by establishing research foci on the model structure, the key input variable identification, the drivers of the relevant property markets, the determinants of the key variables (Research Engine no.1), the examination of risk measurement, the incorporation of risk simulation exercises (Research Engine no.2), the importance of both environmental and social factors and, finally the impact of the triple bottom line measures on the asset (Research Engine no. 3).

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This letter presents a technique to assess the overall network performance of sampled value process buses based on IEC 61850-9-2 using measurements from a single location in the network. The method is based upon the use of Ethernet cards with externally synchronized time stamping, and characteristics of the process bus protocol. The application and utility of the method is demonstrated by measuring latency introduced by Ethernet switches. Network latency can be measured from a single set of captures, rather than comparing source and destination captures. Absolute latency measures will greatly assist the design testing, commissioning and maintenance of these critical data networks.

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The dynamic capabilities view (DCV) focuses on renewal of firms’ strategic knowledge resources so as to sustain competitive advantage within turbulent markets. Within the context of the DCV, the focus of knowledge management (KM) is to develop the KMC through deploying knowledge governance mechanisms that are conducive to facilitating knowledge processes so as to produce superior business performance over time. The essence of KM performance evaluation is to assess how well the KMC is configured with knowledge governance mechanisms and processes that enable a firm to achieve superior performance through matching its knowledge base with market needs. However, little research has been undertaken to evaluate KM performance from the DCV perspective. This study employed a survey study design and adopted hypothesis-testing approaches to develop a capability-based KM evaluation framework (CKMEF) that upholds the basic assertions of the DCV. Under the governance of the framework, a KM index (KMI) and a KM maturity model (KMMM) were derived not only to indicate the extent to which a firm’s KM implementations fulfill its strategic objectives, and to identify the evolutionary phase of its KMC, but also to bench-mark the KMC in the research population. The research design ensured that the evaluation framework and instruments have statistical significance and good generalizabilty to be applied in the research population, namely construction firms operating in the dynamic Hong Kong construction market. The study demonstrated the feasibility of quantitatively evaluating the development of the KMC and revealing the performance heterogeneity associated with the development.

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Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

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In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.