Real-time Bidding for Online Advertising: Measurement and Analysis

The real-time bidding (RTB), aka programmatic buying, has recently become the fastest growing area in online advertising. Instead of bulking buying and inventory-centric buying, RTB mimics stock exchanges and utilises computer algorithms to automatically buy and sell ads in real-time; It uses per impression context and targets the ads to specific people based on data about them, and hence dramatically increases the effectiveness of display advertising. In this paper, we provide an empirical analysis and measurement of a production ad exchange. Using the data sampled from both demand and supply side, we aim to provide first-hand insights into the emerging new impression selling infrastructure and its bidding behaviours, and help identifying research and design issues in such systems. From our study, we observed that periodic patterns occur in various statistics including impressions, clicks, bids, and conversion rates (both post-view and post-click), which suggest time-dependent models would be appropriate for capturing the repeated patterns in RTB. We also found that despite the claimed second price auction, the first price payment in fact is accounted for 55.4% of total cost due to the arrangement of the soft floor price. As such, we argue that the setting of soft floor price in the current RTB systems puts advertisers in a less favourable position. Furthermore, our analysis on the conversation rates shows that the current bidding strategy is far less optimal, indicating the significant needs for optimisation algorithms incorporating the facts such as the temporal behaviours, the frequency and recency of the ad displays, which have not been well considered in the past.Comment: Accepted by ADKDD '13 worksho

A New Historicist Analysis of the Rewriting of Chinese American History in Donald Duk

Frank Chin creates the methods of recovering the lost history of Chinese Americans in his book Donald Duk. He constructs the male heroism through traditional Chinese culture, challenges American education of history through describing the changing process of Donald’s attitudes towards anything about China, and rewrites his version of Chinese American history by analyzing the relation between dreams and reality. Thus Chin achieves his strategy to subvert “History” with “history.” This paper intends to give a new historicist analysis of the rewriting of Chinese American history in Chinese American literature through Donald Duk by Frank Chin

Being Ethical in Instructional Technology Co nsulting

As new technologies merge everyday and become part of our lives, instructional technology consulting that provides professional services to help clients use technologies for learning and performance improvement becomes more popular and important. Being ethical in consulting has been recognized as a crucial and important part of consulting services by many professional organizations, consulting firms, consulting professionals, and their clients. Corresponding to the theme of AECT Convention 2008, professional ethics, the paper examines the meaning of being ethical in instructional technology consulting from the lived experiences of instructional technology consultants and discusses implications for promoting the ethical practice of instructional technology consulting

A Probe Into the Sustainable Development of Petty Loan Companies

The petty loan companies in China have been in good performance since taken the pilot demonstration, which effectively relieves the rural funds and financing difficulties of SMEs. However, the petty loan companies in the business development also face many problems, such as the unreasonable legal status, the limited sources of funding, the heavy tax burden, high cost, and operational risks, and so on. These issues will be restricted to the sustainable development of petty loan companies. This thesis is in-depth analysis of the problems of petty loan companies in terms of sustainable development, and puts forward suggestions to promote the sustainable development of petty loan companies

Carbon Emission Prediction and Clean Industry Transformation Based on Machine Learning: A Case Study of Sichuan Province

This study preprocessed 2000-2019 energy consumption data for 46 key Sichuan industries using matrix normalization. DBSCAN clustering identified 16 feature classes to objectively group industries. Penalized regression models were then applied for their advantages in overfitting control, high-dimensional data processing, and feature selection - well-suited for the complex energy data. Results showed the second cluster around coal had highest emissions due to production needs. Emissions from gasoline-focused and coke-focused clusters were also significant. Based on this, emission reduction suggestions included clean coal technologies, transportation management, coal-electricity replacement in steel, and industry standardization. The research introduced unsupervised learning to objectively select factors and aimed to explore new emission reduction avenues. In summary, the study identified industry groupings, assessed emissions drivers, and proposed scientific reduction strategies to better inform decision-making using algorithms like DBSCAN and penalized regression models.Comment: 21 pages,19 figure

Student Response Systems in Higher Education: Moving Beyond Linear Teaching and Surface Learning

Over the past decade, instructors in colleges and universities increasingly have used Student Response Systems (SRSs)--typically in large classes to increase the level of student engagement and learning. Research shows that both students and instructors perceive SRSs to be beneficial, although evidence of improved learning has been less clear. Experts emphasize that instructors must consider how technology might enhance good pedagogy in order for increases in learning to occur. SRSs do increase student engagement and provide prompt feedback—two key practices that promote learning. However, professional groups propose goals for students in higher education that focus on deep learning rather than the knowledge-centered emphasis of many large classes. Recent research shows that SRSs coupled with pedagogical enhancements can promote deep learning when teaching and questioning strategies center on higher-level thinking skills. A framework integrating the levels of student responses with principles for good pedagogical practice is provided as a guide for using SRSs to foster deep learning

Conformal single-layer encapsulation of PEDOT at low substrate temperature

In this work, we demonstrate a single-layer encapsulation method for poly(3,4-ethylenedioxythiophene) (PEDOT). This method is achieved by initiated chemical vapor deposition (iCVD) process, which is scalable and employs solvent-free and low-substrate temperature conditions. The encapsulant used, poly(divinylbenzene-co-maleic anhydride) (PDVB-MA), was first time synthesized via vapor phase process. This cross-linked iCVD polymer can be rapidly deposited (40 nm min−1) with uniform and conformal morphology. In the test of PEDOT degradation, the encapsulation extended the halflife of PEDOT to 900 h at 30 °C in air, which is more than 10 times of the counterpart without encapsulation.Eni S.p.A. (Firm) (Eni-MIT Solar Frontiers Alliance

Synchronous Communication Technology for Remote Academic Advising at a State University

The use of synchronous communication technology has significantly increased in recent years for communications in online learning and instruction, especially since the COVID-19 pandemic. Synchronous communication technology, such as Zoom, Google Meets, and Microsoft Teams, is widely adopted by academic advisors to continue their advising services as many universities were forced to move their traditional in-person academic advising to remote academic advising (RAA) in an online format. In this context, we explored the knowledge, experiences, and perceptions of students and academic advisors at a state university using synchronous communication technology for RAA during the COVID-19 pandemic. The study includes data collected from 539 sets of data from students and 28 from advisors. Through descriptive data analysis, the study revealed knowledge and a variation of perception gaps among students, in addition to students and academic advisors for RAA. With research results, we discuss the implications for effective RAA, concluding with suggestions for effective uses of synchronous communication technology to conduct RAA for academic advisors

A New Model of Productive Online Discussion and Its Implications for Research and Instruction

We develop a new model of productive online discussion based on a brief review of research literature on online discussion. As compared to previous discussion models, the new model provides a more systematic and comprehensive framework to understand how learning occurs through online discussion. Based on the new model, we propose several directions for research on improving the quality of online discussion and learning