Green Up Pavement Rehabilitation Design Tool

While designers produce pavement rehabilitation recommendations every day, for projects of all sizes, most designers have little information on the environmental impact of their recommendations. This research developed a new decision tool, called the “Green Up Pavement Rehabilitation Design Tool,” to allow the comparison of different rehabilitation solutions in terms of greenhouse gas emissions and to encourage sustainable practices such as materials recycling and the use of permeable, cool, and quiet pavement surfaces. The project aligns with the major goal of California Senate Bill 1, which is “to address deferred maintenance on the state highway system and the local street and road system,” by providing a rehabilitation strategy selection tool as well as an educational tool to promote sustainable pavement practices. The Green Up graphic and the overall methodology were finalized in consultation with representatives of the portland cement concrete and asphalt industries in California. For designers interested in learning more, the tool includes fact sheets about sustainable pavement rehabilitation strategies and links to additional online resources

Giving in Numbers: 2013 Edition

Developed by CECP in association with The Conference Board, "Giving in Numbers: 2013 Edition" is based on data from 2companies including 60 of the largest 100 companies in the Fortune 500. The sum of contributions across all respondents of the 2012 Corporate Giving Survey (CGS), from which the data is pulled, totaled more than $20 billion in cash and in-kind giving. This report not only presents a profile of corporate philanthropy in 2012, but also pinpoints how corporate giving is evolving and becoming more focused since before the recession of 2008 and 2009. This is the ninth annual report on trends in corporate giving

OpenML: networked science in machine learning

Many sciences have made significant breakthroughs by adopting online tools that help organize, structure and mine information that is too detailed to be printed in journals. In this paper, we introduce OpenML, a place for machine learning researchers to share and organize data in fine detail, so that they can work more effectively, be more visible, and collaborate with others to tackle harder problems. We discuss how OpenML relates to other examples of networked science and what benefits it brings for machine learning research, individual scientists, as well as students and practitioners.Comment: 12 pages, 10 figure

Exploring Image Virality in Google Plus

Reactions to posts in an online social network show different dynamics depending on several textual features of the corresponding content. Do similar dynamics exist when images are posted? Exploiting a novel dataset of posts, gathered from the most popular Google+ users, we try to give an answer to such a question. We describe several virality phenomena that emerge when taking into account visual characteristics of images (such as orientation, mean saturation, etc.). We also provide hypotheses and potential explanations for the dynamics behind them, and include cases for which common-sense expectations do not hold true in our experiments.Comment: 8 pages, 8 figures. IEEE/ASE SocialCom 201

A Benchmark for Image Retrieval using Distributed Systems over the Internet: BIRDS-I

The performance of CBIR algorithms is usually measured on an isolated workstation. In a real-world environment the algorithms would only constitute a minor component among the many interacting components. The Internet dramati-cally changes many of the usual assumptions about measuring CBIR performance. Any CBIR benchmark should be designed from a networked systems standpoint. These benchmarks typically introduce communication overhead because the real systems they model are distributed applications. We present our implementation of a client/server benchmark called BIRDS-I to measure image retrieval performance over the Internet. It has been designed with the trend toward the use of small personalized wireless systems in mind. Web-based CBIR implies the use of heteroge-neous image sets, imposing certain constraints on how the images are organized and the type of performance metrics applicable. BIRDS-I only requires controlled human intervention for the compilation of the image collection and none for the generation of ground truth in the measurement of retrieval accuracy. Benchmark image collections need to be evolved incrementally toward the storage of millions of images and that scaleup can only be achieved through the use of computer-aided compilation. Finally, our scoring metric introduces a tightly optimized image-ranking window.Comment: 24 pages, To appear in the Proc. SPIE Internet Imaging Conference 200

Public Bikesharing in North America During a Period of Rapid Expansion: Understanding Business Models, Industry Trends & User Impacts, MTI Report 12-29

Public bikesharing—the shared use of a bicycle fleet—is an innovative transportation strategy that has recently emerged in major cities around the world, including North America. Information technology (IT)-based bikesharing systems typically position bicycles throughout an urban environment, among a network of docking stations, for immediate access. Trips can be one-way, round-trip, or both, depending on the operator. Bikesharing can serve as a first-and-last mile connector to other modes, as well as for both short and long distance destinations. In 2012, 22 IT-based public bikesharing systems were operating in the United States, with a total of 884,442 users and 7,549 bicycles. Four IT-based programs in Canada had a total of 197,419 users and 6,115 bicycles. Two IT-based programs in Mexico had a total of 71,611 users and 3,680 bicycles. (Membership numbers reflect the total number of short- and long-term users.) This study evaluates public bikesharing in North America, reviewing the change in travel behavior exhibited by members of different programs in the context of their business models and operational environment. This Phase II research builds on data collected during our Phase I research conducted in 2012. During the 2012 research (Phase I), researchers conducted 14 expert interviews with industry experts and public officials in the United States and Canada, as well as 19 interviews with the manager and/or key staff of IT-based bikesharing organizations. For more information on the Phase I research, please see the Shaheen et al., 2012 report Public Bikesharing in North America: Early Operator and User Understanding. For this Phase II study, an additional 23 interviews were conducted with IT-based bikesharing organizations in the United States, Canada, and Mexico in Spring 2013. Notable developments during this period include the ongoing expansion of public bikesharing in North America, including the recent launches of multiple large bikesharing programs in the United States (i.e., Citi Bike in New York City, Divvy in Chicago, and Bay Area Bike Share in the San Francisco Bay Area). In addition to expert interviews, the authors conducted two kinds of surveys with bikesharing users. One was the online member survey. This survey was sent to all people for whom the operator had an email address.The population of this survey was mainly annual members of the bikesharing system, and the members took the survey via a URL link sent to them from the operator. The second survey was an on-street survey. This survey was designed for anyone, including casual users (i.e., those who are not members of the system and use it on a short-term basis), to take “on-street” via a smartphone. The member survey was deployed in five cities: Montreal, Toronto, Salt Lake City, Minneapolis-Saint Paul, and Mexico City. The on-street survey was implemented in three cities: Boston, Salt Lake City, and San Antonio

Improving waiting times in the Emergency Department

Waiting times in the Emergency Department cause considerable delays in care and in patient satisfaction. There are many moving parts to the ED visit with multiple providers delivering care for a single patient. Factors that have been shown to delay care in the ED have been broken down into input factors such as triaging, throughput factors during the visit, and output factors, which include discharge planning and available inpatient beds for admitted patients. Research has shown that throughput factors are an area of interest to decrease time spent in the ED that will lead to decrease waiting room times. In this Quality Improvement project, we will develop a systematic check in system with ED providers that will allow providers to identify any outstanding issues that may be delaying care or discharge. We hypothesize that this system will increase throughput in the ED by resolving any lab, radiology, or treatments that were overlooked. Reviewing the results of this QI project will allow us to see if we were effective in our timing of scheduled check-ins. Ultimately, this will reduce time spent in the waiting room by allowing more patients to be seen. In the era of the Affordable Care Act, more patients have access to affordable healthcare and will increase volume in the ED. This check-in system will allow more patients to be seen smoothly and in a timely manner that will improve and increase patient care and satisfaction in the ED

Uncovering the Hidden Co-Evolution in the Work History of Software Projects

The monitoring of project-oriented business processes is difficult because their state is fragmented and represented by the progress of different documents and artifacts being worked on. This observation holds in particular for software development projects in which various developers work on different parts of the software concurrently. Prior contributions in this area have proposed a plethora of techniques to analyze and visualize the current state of the software artifact as a product. It is surprising that these techniques are missing to provide insights into what types of work are conducted at different stages of the project and how they are dependent upon another. In this paper, we address this research gap and present a technique for mining the software process including dependencies between artifacts. Our evaluation of various open-source projects demonstrates the applicability of our technique