Online korean skincare decision support system

Despite the explosive growth of electronic commerce and the rapidly increasing number of consumers who use interactive media for pre-purchase information search and online shopping, very little is known about how consumers make purchase decisions in such settings. One desirable form of interactivity from a consumer perspective is the implementation of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment to their individual preferences

Least Present Value of Net Revenue: a new auction-mechanism for highway concessions

This paper presents a new mechanism for awarding tolled-highways, based on the variable-term concept proposed by Engel et al (1997). These authors claim that a mechanism based on bids for least-present-value of revenue (LPVR) eliminates the risk of demand and simplifies renegotiations. However, if maintenance and operation costs are non-negligible, it is proven that, under LPVR, bidders need to estimate future traffic to make their offers, so the risk of demand is still present. Moreover, LPVR does not guarantee the selection of the best concessionaire. An alternative mechanism (least-present-value of net revenue, LPVNR) is proposed. The idea is to use bids that do not force firms to estimate future traffic. Under LPVNR, firms must make offers on: (i) total amount of revenue, net of maintenance costs; (ii) annual operation and routine-maintenance costs; and (iii) cost of road re-pavement. The concession is awarded to the firm with the lowest total expected cost, and the selection rule is adapted to the information available. The new mechanism is simple, does not impose additional efforts from firms, and eliminates the risk of demand more effectively. Although initially conceived for the road sector, the idea of LPVNR could easily be extended to other infrastructure sectors.Highways, roads, concessions, auctions

Effect of Proportion of Missing Data on Application of Data Imputation in Pavement Management Systems

Missing data are commonly found in pavement condition/performance databases. A common practice today is to apply statistical imputation methods to replace the missing data with imputed values. It is thus important for pavement management decision makers to know the uncertainty and errors involved in the use of datasets with imputed values in their analysis. An equally important information of practical significance is the maximum allowable proportion of missing data (i.e. level of data missingness in the pavement condition/performance records) that will still produce results with acceptable magnitude of error or risk when using imputed data. This paper proposes a procedure for determining such useful information. A numerical example analyzing pavement roughness data is presented to demonstrate the procedure through evaluating the error and reliability characteristics of imputed data. The roughness data of three road sections were obtained from the LTPP database. From these data records, datasets with different proportions of missing data were randomly generated to study the effect of level of data missingness. The analysis shows that the errors of imputed data increased with the level of data missingness, and their magnitudes are significantly affected by the effect of pavement rehabilitation. On the application of data imputation in PMS, the study suggests that at 95% confidence level, 25% of missing data appears to be a reasonable allowable maximum limit for analyzing pavement roughness time series data not involving rehabilitation within the analysis period. When pavement rehabilitation occurs within the analysis period, the maximum proportion of imputed data should be limited to 15%

Updating, Upgrading, Refining, Calibration and Implementation of Trade-Off Analysis Methodology Developed for INDOT

As part of the ongoing evolution towards integrated highway asset management, the Indiana Department of Transportation (INDOT), through SPR studies in 2004 and 2010, sponsored research that developed an overall framework for asset management. This was intended to foster decision support for alternative investments across the program areas on the basis of a broad range of performance measures and against the background of the various alternative actions or spending amounts that could be applied to the several different asset types in the different program areas. The 2010 study also developed theoretical constructs for scaling and amalgamating the different performance measures, and for analyzing the different kinds of trade-offs. The research products from the present study include this technical report which shows how theoretical underpinnings of the methodology developed for INDOT in 2010 have been updated, upgraded, and refined. The report also includes a case study that shows how the trade-off analysis framework has been calibrated using available data. Supplemental to the report is Trade-IN Version 1.0, a set of flexible and easy-to-use spreadsheets that implement the tradeoff framework. With this framework and using data at the current time or in the future, INDOT’s asset managers are placed in a better position to quantify and comprehend the relationships between budget levels and system-wide performance, the relationships between different pairs of conflicting or non-conflicting performance measures under a given budget limit, and the consequences, in terms of system-wide performance, of funding shifts across the management systems or program areas

Evaluating the Need to Seal Thermal Cracks in Alaska’s Asphalt Concrete Pavements

INE/AUTC 12.2

Improving Displacement Measurement for Evaluating Longitudinal Road Profiles

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper introduces a half-wavelength peak matching (HWPM) model, which improves the accuracy of vehicle based longitudinal road profilers used in evaluating road unevenness and mega-textures. In this application, the HWPM model is designed for profilers which utilize a laser displacement sensor with an accelerometer for detecting surface irregularities. The process of converting acceleration to displacement by double integration (which is used in most rofilers) is error-prone, and although there are techniques to minimize the effect of this error, this paper proposes a novel approach for improving the generated road profile results. The technique amends the vertical displacement derived from the accelerometer samples, by using data from the laser displacement sensor as a reference. The vehicle based profiler developed for this experiment (which uses the HWPM model) shows a huge improvement in detected longitudinal irregularities when compared with pre-processed results, and uses a 3-m rolling straight edge as a benchmark.Peer reviewe

Quantifying road roughness: multiresolution and near real-time analysis

Road roughness is a key parameter for road construction and for assessing ride quality during the life of paved and unpaved road systems. The quarter-car model (QC model), is a standard mathematical tool for estimating suspension responses and can be used for summative or pointwise analysis of vehicle response to road geometry. In fact, transportation agencies specify roughness requirements as summative values for pavement projects that affect construction practices and contractor pay factors. The International Roughness Index (IRI), a summative statistic of quarter-car suspension response, is widely used to characterize overall roughness profiles of pavement stretches but does not provide sufficient detail about the frequency or spatial distribution of roughness features. This research focuses on two pointwise approaches, continuous roughness maps and wavelets analysis, that both characterize overall roughness and identify localized features and compares these findings with IRI results. Automated algorithms were developed to preform finite difference analysis of point cloud data collected by three-dimensional (3D) stationary terrestrial laser scans of paved and unpaved roads. This resulted in continuous roughness maps that characterized both spatial roughness and localized features. However, to address the computational limitations of finite difference analysis, Fourier and wavelets (discrete and continuous wavelet transform) analyses were conducted on sample profiles from the federal highway administration (FHWA) Long Term Pavement Performance data base. The Fourier analysis was performed by transforming profiles into frequency domain and applying the QC filter to the transformed profile. The filtered profiles are transformed back to spatial domain to inspect the location of high amplitudes in the suspension rate profiles. Finite difference analysis provides suspension responses in spatial domain, on the other hand Fourier analysis can be performed in either frequency or spatial domains only. To describe the location and frequency content of localized features in a profile, wavelet filters were customized to separate the suspension response profiles into sub profiles with known frequency bands. Other advantages of wavelets analysis includes data compression, making inferences from compressed data, and analyzing short profiles (\u3c 7.6 m). The proposed approaches present the basis for developing real-time autonomous algorithms for smoothness based quality control and maintenance

Rheological Properties of Modified Crumb Rubber Asphalt Binder and Selecting the Best Modified Binder Using AHP Method

Crumb rubber modifier (CRM) is one of the most popular asphalt binder modifiers due to the economic benefits and desired physical and rheological properties of asphalt binders and asphalt mixes. This research focuses on evaluating the properties of rubber-modified asphalt binders and selecting the best modified binder. The modified binders were produced by blending virgin binders with CRM at various contents of different gradations, and different methods of grinding. CRM made through ambient and cryogenic grinding methods with two gradation sizes were produced and tested. Three different virgin binders from two sources were obtained and used. The Analytic Hierarchy Process (AHP) method was used to determine the best combination of virgin binder and CRM, based on the rheological properties and their importance in Nevada’s construction code. Based on AHP analysis, ambient CRM obtained the highest priority. CRM contents of 10% and 15% were ranked higher than 20% depending on the grade of the virgin binder. Both mesh 20 and 40 CRM sizes were favorable

Road Work Ahead: Holding Government Accountable for Fixing America's Crumbling Roads and Bridges

Examines the poor maintenance of roads and bridges; their consequences, including costs; and underlying causes, including pressure from special interest groups and untargeted transportation policies. Recommends fixing existing infrastructure first

SUP&R DSS: A sustainability-based decision support system for road pavements

Road pavement community members are increasingly becoming aware of the need to incorporating the principles of sustainable development into the sector. Policies are also going in this direction and as a consequence in the recent years researchers and practitioners are coming up with new materials, technologies and practices designed to reduce the negative impacts of their activities in the surroundings. Within this framework the road pavements sector is witnessing a paradigm shift towards the development of pavement technologies incorporating high-content of recycled materials, as well as best practices to decrease the overall carbon footprint. These are all promising solutions that to the most can sound as sustainable practices. However the whole road pavement community is still investigating methodologies and tools to define what actually sustainable means and thereby performing a sustainable decision-making. It is within this context that the need of a sustainability-based decision support system (DSS) that could help road pavement engineers at the design stage was identified and is here presented. The Sustainable Pavements & Railways DSS (SUP&R DSS) relies on a multi-criteria decision analysis (MCDA) method to rank the sustainability of alternatives. It applies life cycle-based approaches to quantify the values of a set of indicators purposely and methodologically selected to capture the cause- effect link between the general concepts of the three wellbeing dimensions of sustainability, i.e., environmental, economic and social, and the infrastructure construction and maintenance practice. Furthermore, the system allows selecting different weighting for the indicators but offers also a default set of values derived from a survey conducted with over 50 stakeholders in Europe and beyond. Together with the development, structure and features of the SUP&R DSS, this paper present its applicability by means of a case study aiming at identifying the most sustainable asphalt mixture for wearing courses. Several promising options for flexible road pavements were selected, ranging from low to hot temperature asphalt. The results show that a foamed warm mix asphalt mixture with a reclaimed asphalt pavement content of 50% is the most sustainable among the competing alternatives. Furthermore, a sensitivity analysis conducted to investigate the influence of the indicators weights, the parameters of the MCDA method and the long-term performance of the alternative asphalt mixtures on the stability of the ranking showed that its first position in the ranking remained unaffected