LMP estimation considering the uncertainty of wind power

One of the impediments to large-scale use of wind generation within power system is its variable and uncertain real-time availability. Due to the low marginal cost of wind power, its output will change the merit order of power markets and influence the Locational Marginal Price (LMP). For the large scale of wind power, LMP calculation can't ignore the essential variable and uncertain nature of wind power. This paper proposes an algorithm to estimate LMP. The estimation result of conventional Monte Carlo simulation is taken as benchmark to examine accuracy. Case study is conducted on a simplified SE Australian power system, and the simulation results show the feasibility of proposed method.

A comparison of two commercially available motion capture systems for gait analysis : high end vs low-cost

In 1999 Richards compared the accuracy of commercially available motion capture systems commonly used in biomechanics. Richards identified that in static tests the optical motion capture systems generally produced RMS errors of less than 1.0 mm. During dynamic tests, the RMS error increased to up to 4.2 mm in some systems. In the last 12 years motion capture systems have continued to evolve and now include high-resolution CCD or CMOS image sensors, wireless communication, and high full frame sampling frequencies. In addition to hardware advances, there have also been a number of advances in software, which includes improved calibration and tracking algorithms, real time data streaming, and the introduction of the c3d standard. These advances have allowed the system manufactures to maintain a high retail price in the name of advancement. In areas such as gait analysis and ergonomics many of the advanced features such as high resolution image sensors and high sampling frequencies are not required due to the nature of the task often investigated. Recently Natural Point introduced low cost cameras, which on face value appear to be suitable as at very least a high quality teaching tool in biomechanics and possibly even a research tool when coupled with the correct calibration and tracking software. The aim of the study was therefore to compare both the linear accuracy and quality of angular kinematics from a typical high end motion capture system and a low cost system during a simple task.

An estimate of road accident costs in Singapore

An earlier study by the Asian Development Bank (ADB) showed that the annual cost of road traffic accidents in 2001 was S$699.36 million which was 0.5% of the annual GDP. This paper attempts to update of the cost estimates of road traffic accidents. More precise methods of computing the human cost, lost output and property damage are adopted which grew in an annual cost of S$610.3 million or 0.338% of the annual GDP in 2003. A more conservative estimate of S$878,000 for fatal accident is also obtained, compared to the earlier figure of S$1.4 million. This study has shown that it is necessary to update the annual traffic accident costs regularly, as the figures vary with the number of accidents which change with time.

A framework for life cycle cost estimation of a product family at the early stage of product development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system.

Benefit cost analysis applied to behavioral and engineering safety countermeasures in San Francisco, California

The state of the practice in safety has advanced rapidly in recent years with the emergence of new tools and processes for improving selection of the most cost-effective safety countermeasures. However, many challenges prevent fair and objective comparisons of countermeasures applied across safety disciplines (e.g. engineering, emergency services, and behavioral measures). These countermeasures operate at different spatial scales, are funded often by different financial sources and agencies, and have associated costs and benefits that are difficult to estimate. This research proposes a methodology by which both behavioral and engineering safety investments are considered and compared in a specific local context. The methodology involves a multi-stage process that enables the analyst to select countermeasures that yield high benefits to costs, are targeted for a particular project, and that may involve costs and benefits that accrue over varying spatial and temporal scales. The methodology is illustrated using a case study from the Geary Boulevard Corridor in San Francisco, California. The case study illustrates that: 1) The methodology enables the identification and assessment of a wide range of safety investment types at the project level; 2) The nature of crash histories lend themselves to the selection of both behavioral and engineering investments, requiring cooperation across agencies; and 3) The results of the cost-benefit analysis are highly sensitive to cost and benefit assumptions, and thus listing and justification of all assumptions is required. It is recommended that a sensitivity analyses be conducted when there is large uncertainty surrounding cost and benefit assumptions.

The effect of project information on the accuracy of building price forecasts

A fundamental proposition is that the accuracy of the designer's tender price forecasts is positively correlated with the amount of information available for that project. The paper describes an empirical study of the effects of the quantity of information available on practicing Quantity Surveyors' forecasting accuracy. The methodology involved the surveyors repeatedly revising tender price forecasts on receipt of chunks of project information. Each of twelve surveyors undertook two projects and selected information chunks from a total of sixteen information types. The analysis indicated marked differences in accuracy between different project types and experts/non-experts. The expert surveyors' forecasts were not found to be significantly improved by information other than that of basic building type and size, even after eliminating project type effects. The expert surveyors' forecasts based on the knowledge of building type and size alone were, however, found to be of similar accuracy to that of average practitioners pricing full bills of quantities.

How to improve pupils' literacy? A cost-effectiveness analysis of a French educational project

The Action Lecture program is an innovative teaching method run in some nursery and primary schools in Paris and designed to improve pupils’ literacy. We report the results of an evaluation of this program. We describe the experimental protocol that was built to estimate the program’s impact on several types of indicators. Data were processed following a Differences-in-Differences (DID) method. Then we use the estimation of the impact on academic achievement to conduct a cost-effectiveness analysis and take a reduction of the class size program as a benchmark. The results are positive for the Action Lecture program.

Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments

In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online.

The financial cost of hamstring strain injuries in the Australian Football League

Background/Aim Hamstring strain injuries (HSIs) have remained the most prevalent injury in the Australian football league (AFL) over the past 21 regular seasons. The impact of HSIs in sport is often expressed as regular season games missed due to injury. However the financial cost of athletes missing games due to injury has not been investigated. The aim of this report is to estimate the financial cost of games missed due to HSIs in the AFL. Method Data was collected using publically available information from the AFL’s injury report and the official AFL annual report for the past 10 competitive AFL seasons. Average athlete salary and injury epidemiology data was used to determine the average yearly financial cost of HSIs for AFL clubs and the average financial cost of a single HSI over this time period. Results Across the observed period, average yearly financial cost of HSIs per club increased by 71% compared to a 43% increase in average yearly athlete salary. Over the same time period the average financial cost of a single HSI increased by 56% from $25,603 in 2003 to $40,021 in 2012, despite little change in HSI rates during the period. Conclusion The observed increased financial cost of HSIs was ultimately explained by the failure of teams to decrease HSI rates, but coupled with increases in athlete salaries over the past 10 season. The information presented in this report will highlight the financial cost of HSIs and other sporting injuries, raising greater awareness and the need for further funding for research into injury prevention strategies to maximise economical return for investment in athletes.

Sampling environmental acoustic recordings to determine bird species richness

Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data. Read More: http://www.esajournals.org/doi/abs/10.1890/12-2088.1

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Predicting freeway pavement construction cost using a back-propagation neural network : a case study in Henan, China

The objective of this research was to develop a model to estimate future freeway pavement construction costs in Henan Province, China. A comprehensive set of factors contributing to the cost of freeway pavement construction were included in the model formulation. These factors comprehensively reflect the characteristics of region and topography and altitude variation, the cost of labour, material, and equipment, and time-related variables such as index numbers of labour prices, material prices and equipment prices. An Artificial Neural Network model using the Back-Propagation learning algorithm was developed to estimate the cost of freeway pavement construction. A total of 88 valid freeway cases were obtained from freeway construction projects let by the Henan Transportation Department during the period 1994−2007. Data from a random selection of 81 freeway cases were used to train the Neural Network model and the remaining data were used to test the performance of the Neural Network model. The tested model was used to predict freeway pavement construction costs in 2010 based on predictions of input values. In addition, this paper provides a suggested correction for the prediction of the value for the future freeway pavement construction costs. Since the change in future freeway pavement construction cost is affected by many factors, the predictions obtained by the proposed method, and therefore the model, will need to be tested once actual data are obtained.

Examining the effects of early cost drivers on contingencies

The accuracy of early cost estimates is critical to the success of construction projects. The selected tender price (clients' building cost) is usually seen in previous research as a holistic dependent variable when examining early stage estimates. Unlike other components of construction cost, the amount of contingencies is decided by clients/consultants with consideration of early project information. Cost drivers of contingencies estimates are associated with uncertainty and complexity, and include project size, schedule, ground condition, construction site access, market condition and so on. A path analysis of 133 UK school building contracts was conducted to identify impacts of nine major cost drivers on the determination of contingencies by different clients/cost estimators. This research finds that gross floor area (GFA), schedule and requirement of air conditioning have statistically significant impacts on the contingency determination. The mediating role of schedule between gross floor area and contingencies (GFA→Schedule→Contingencies) was confirmed with the Soble test. The total effects of the three variables on contingencies estimates were obtained with the consideration of this indirect effect. The squared multiple correlation (SMC) of contingencies (=0.624) indicates the identified three variables can explain 62.4% variance of contingencies, and it is comparatively satisfactory considering the heterogeneity among different estimators, unknown estimating techniques and different projects

Improving the accuracy of mine site water balances through improved estimation of runoff volumes

A mine site water balance is important for communicating information to interested stakeholders, for reporting on water performance, and for anticipating and mitigating water-related risks through water use/demand forecasting. Gaining accuracy over the water balance is therefore crucial for sites to achieve best practice water management and to maintain their social license to operate. For sites that are located in high rainfall environments the water received to storage dams through runoff can represent a large proportion of the overall inputs to site; inaccuracies in these flows can therefore lead to inaccuracies in the overall site water balance. Hydrological models that estimate runoff flows are often incorporated into simulation models used for water use/demand forecasting. The Australian Water Balance Model (AWBM) is one example that has been widely applied in the Australian context. However, the calibration of AWBM in a mining context can be challenging. Through a detailed case study, we outline an approach that was used to calibrate and validate AWBM at a mine site. Commencing with a dataset of monitored dam levels, a mass balance approach was used to generate an observed runoff sequence. By incorporating a portion of this observed dataset into the calibration routine, we achieved a closer fit between the observed vs. simulated dataset compared with the base case. We conclude by highlighting opportunities for future research to improve the calibration fit through improving the quality of the input dataset. This will ultimately lead to better models for runoff prediction and thereby improve the accuracy of mine site water balances.