Fuzzy Content Mining for Targeted Advertisement

Content-targeted advertising system is becoming an increasingly important part of the funding source of free web services. Highly efficient content analysis is the pivotal key of such a system. This project aims to establish a content analysis engine involving fuzzy logic that is able to automatically analyze real user-posted Web documents such as blog entries. Based on the analysis result, the system matches and retrieves the most appropriate Web advertisements. The focus and complexity is on how to better estimate and acquire the keywords that represent a given Web document. Fuzzy Web mining concept will be applied to synthetically consider multiple factors of Web content. A Fuzzy Ranking System is established based on certain fuzzy (and some crisp) rules, fuzzy sets, and membership functions to get the best candidate keywords. Once it is has obtained the keywords, the system will retrieve corresponding advertisements from certain providers through Web services as matched advertisements, similarly to retrieving a products list from Amazon.com. In 87% of the cases, the results of this system can match the accuracy of the Google Adwords system. Furthermore, this expandable system will also be a solid base for further research and development on this topic

Security of electric power systems : cascading outage analysis, interdiction model and resilience to natural disasters

textSecure electric power system operation is key to social warfare. However, recent years have seen numerous natural disasters and terrorist attacks that threat the grid security. This dissertation summarizes the efforts to develop a model to analyze cascading outages, an interdiction model to analyze worst-case attacks on power grids, and research on grid resilience to natural disasters. The developed cascading outage analysis model uses outage checkers to systematically simulate the system behavior after an initial disturbance, and calculate the potential cascading outage path and electric load shedding. The new interdiction model combines the previously developed medium-term attack-defense model with the short-term cascading outage analysis model to find worst-case terrorist attack. The dissertation also reviews the research on power grid resilience to natural disaster, and develops a framework to simulate the impacts of hurricanes.Electrical and Computer Engineerin

Does default risk matter for investors in REITs

We investigate the relationship between default risk and REIT stock returns. A default risk long-short investment strategy generates a return of 15% per annum. We also evaluate a large number of potential explanations for the negative relationship between default risk and subsequent stock returns. We do not find robust evidence that the default risk premium can be explained by firm size, book-to-market equity, asset growth and idiosyncratic volatility. However, CAPM beta shows some promise in explaining the default risk premium. Our results shed further light on the role of default risk in investment in REITs. First published online 23 September 202

CAROM Air -- Vehicle Localization and Traffic Scene Reconstruction from Aerial Videos

Road traffic scene reconstruction from videos has been desirable by road safety regulators, city planners, researchers, and autonomous driving technology developers. However, it is expensive and unnecessary to cover every mile of the road with cameras mounted on the road infrastructure. This paper presents a method that can process aerial videos to vehicle trajectory data so that a traffic scene can be automatically reconstructed and accurately re-simulated using computers. On average, the vehicle localization error is about 0.1 m to 0.3 m using a consumer-grade drone flying at 120 meters. This project also compiles a dataset of 50 reconstructed road traffic scenes from about 100 hours of aerial videos to enable various downstream traffic analysis applications and facilitate further road traffic related research. The dataset is available at https://github.com/duolu/CAROM.Comment: Accepted to IEEE ICRA 202

The Genetic Associations and Epistatic Effects of the CCR5 Promoter and CCR2-V64I Polymorphisms on Susceptibility to HIV-1 Infection in a Northern Han Chinese Population

The outcome of human immunodeficiency virus (HIV)-1 infection and course to AIDS are variable among individuals. Both chemokine receptor 5 (CCR5) and CCR2 gene polymorphisms play essential roles in the susceptibility of HIV-1 infection. To investigate the main and epistatic effects of the CCR5 promoter and CCR2-V64I polymorphisms on HIV-1 infection in the Northern Han Chinese, subjects of 91 HIV-1-infected patients and 91 health controls were recruited. Single-nucleotide polymorphisms (SNPs) in the CCR5 promoter region and CCR2-V64I variants were genotyped. In the single-locus analysis, CCR5 58755-G and CCR5 59653-T alleles were significantly associated with HIV-1 infection (odds ratio [OR]=0.529, 95% confidence interval [CI]: 0.295-0.948; OR=1.710, 95% CI: 1.039-2.814). After adjustment with age and gender, subjects with the CCR5 59653-CT genotype showed the increased risk of HIV-1 infection compared with those with the wild-type CC genotype (adjusted OR=2.502; 95% CI: 1.332-4.698). No positive association was observed in other SNPs. Haplotype-based association analysis revealed that the haplotype TATGC was associated with the susceptibility to HIV-1 infection (p=0.003). Besides, we found the significant epistatic effects between the CCR5 58755-A/G and CCR5 59029-A/G polymorphisms associated with the lower risk of HIV-1 infection. In addition, we also identified the best three-factor interaction model, including the CCR5 58755-A/G, 59029-A/G, and CCR2-V64I polymorphisms, indicating that there were also strong gene-gene interactions between the CCR5 promoter and CCR2 polymorphisms on the susceptibility of HIV-1 infection. These findings contribute to understanding the genetic mechanism for the susceptibility of HIV-1 infection in Northern Han Chinese