854 resultados para software performance evaluation


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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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Recent advancement in wearable technologies, particularly smart watches embedded with powerful processors, memory subsystems with various built-in sensors such as ac-celerometer, gyroscope and optical sensor in one single package has opened a whole new application space. One of the main applications of interest is the monitoring of movement patterns, heart rate, ECG and PPG particularly for longer duration's in natural environments. In this study, we conducted a performance evaluation on the optical heart rate sensor of the smartwatch with respect to the commonly used ECG and PPG devices. Results have shown that the heart rate acquired from the smartwatch is reasonably accurate with a high degree of correlation. Further, we conducted a preliminary exerise to evaluate sleep quality using the heart rate readings and accelerometer readings captured from the smartwatch and compared with a commercially available and clinically used non-contact sleep sensor, RESMED S+.

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The popularity of Twitter attracts more and more spammers. Spammers send unwanted tweets to Twitter users to promote websites or services, which are harmful to normal users. In order to stop spammers, researchers have proposed a number of mechanisms. The focus of recent works is on the application of machine learning techniques into Twitter spam detection. However, tweets are retrieved in a streaming way, and Twitter provides the Streaming API for developers and researchers to access public tweets in real time. There lacks a performance evaluation of existing machine learning-based streaming spam detection methods. In this paper, we bridged the gap by carrying out a performance evaluation, which was from three different aspects of data, feature, and model. A big ground-truth of over 600 million public tweets was created by using a commercial URL-based security tool. For real-time spam detection, we further extracted 12 lightweight features for tweet representation. Spam detection was then transformed to a binary classification problem in the feature space and can be solved by conventional machine learning algorithms. We evaluated the impact of different factors to the spam detection performance, which included spam to nonspam ratio, feature discretization, training data size, data sampling, time-related data, and machine learning algorithms. The results show the streaming spam tweet detection is still a big challenge and a robust detection technique should take into account the three aspects of data, feature, and model.

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As a renewable and non-polluting energy source, wind is used to produce electricity via large-diameter horizontal or vertical axis wind turbines. Such large wind turbines have been well designed and widely applied in industry. However, little attention has been paid to the design and development of miniature wind energy harvesters, which have great potential to be applied to the HVAC (heating, ventilating and air conditions) ventilation exhaust systems and household personal properties. In this work, 10 air-driven electromagnetic energy harvesters are fabricated using 3D printing technology. Parametric measurements are then conducted to study the effects of (1) the blade number, (2) its geometric size, (3) aspect ratio, presence or absence of (4) solid central shaft, (5) end plates, and (6) blade orientation. The maximum electrical power is 0.305 W. To demonstrate its practical application, the electricity generated is used to power 4 LED (light-emitting diode) lights. The maximum overall efficiency ηmax is approximately 6.59%. The cut-in and minimum operating Reynolds numbers are measured. The present study reveals that the 3D printed miniature energy harvesters provide a more efficient platform for harnessing ‘wind power’.

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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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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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Deliberating on Enterprise Resource Planning (ERP) software sourcing and provision, this paper contrasts the corporate environment with the small business environment. The paper is about Enterprise Resource Planning client (ERPc) expectations and Enterprise Resource Planning vendor (ERPv) value propositions as a mutually compatible process for achieving acceptable standards of ERP software performance. It is suggested that a less-than-equitable vendor–client relationship would not contribute to the implementation of the optimum solution. Adapting selected theoretical concepts and models, the researchers analyse ERPv to ERPc relationship. This analysis is designed to discover if the provision of the very large ERP vendors who market systems such as SAP, and the provision of the smaller ERP vendors (in this instance Eshbel Technologies Ltd who market an ERP software solution called Priority) when framed as a value proposition (Walters, D. (2002) Operations Strategy. Hampshire, UK: Palgrave), is at all comparable or distinctive.

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Performance is a crucial attribute for most software, making performance analysis an important software engineering task. The difficulty is that modern applications are challenging to analyse for performance. Many profiling techniques used in real-world software development struggle to provide useful results when applied to large-scale object-oriented applications. There is a substantial body of research into software performance generally but currently there exists no survey of this research that would help identify approaches useful for object-oriented software. To provide such a review we performed a systematic mapping study of empirical performance analysis approaches that are applicable to object-oriented software. Using keyword searches against leading software engineering research databases and manual searches of relevant venues we identified over 5,000 related articles published since January 2000. From these we systematically selected 253 applicable articles and categorised them according to ten facets that capture the intent, implementation and evaluation of the approaches. Our mapping study results allow us to highlight the main contributions of the existing literature and identify areas where there are interesting opportunities. We also find that, despite the research including approaches specifically aimed at object-oriented software, there are significant challenges in providing actionable feedback on the performance of large-scale object-oriented applications.

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The aim of this letter is to propose an analytical model to study the performance of Software-Defined Network (SDN) switches. Here, SDN switch performance is defined as the time that an SDN switch needs to process packet without the interaction of controller. We exploit the capabilities of queueing theory based M/Geo/1 model to analyze the key factors, flowtable size, packet arrival rate, number of rules, and position of rules. The analytical model is validated using extensive simulations. Our study reveals that these factors have significant influence on the performance of an SDN switch.

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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.