A 2D based Partition Strategy for Solving Ranking under Team Context (RTP)

In this paper, we propose a 2D based partition method for solving the problem of Ranking under Team Context(RTC) on datasets without a priori. We first map the data into 2D space using its minimum and maximum value among all dimensions. Then we construct window queries with consideration of current team context. Besides, during the query mapping procedure, we can pre-prune some tuples which are not top ranked ones. This pre-classified step will defer processing those tuples and can save cost while providing solutions for the problem. Experiments show that our algorithm performs well especially on large datasets with correctness

The application of international law principle in practice of the delimitation on continental shelf

The dissertation is based on the characteristics and development of geology and geography to starts the analysis of international conventions such as ‘UNCLOS” and other legal documents concerning delimitation of the continental shelf in the legal system with combining various theories from both China and international scholars, and will have a systematically study over origins and current legal status of continental shelf, as well as its basic principles of delimitation method in practice. Meanwhile, by illustration the effectiveness brought by international political, diplomatic, economic development to the natural resource exploitation, and discussion of Chinese continental shelf delimitation practice, the article will finally form some rational suggestions as the reference and theoretical support for the settlement of the controversial problem between China and her neighbors

Bio-inspired log-polar based color image pattern analysis in multiple frequency channels

The main topic addressed in this thesis is to implement color image pattern recognition based on the lateral inhibition subtraction phenomenon combined with a complex log-polar mapping in multiple spatial frequency channels. It is shown that the individual red, green and blue channels have different recognition performances when put in the context of former work done by Dragan Vidacic. It is observed that the green channel performs better than the other two channels, with the blue channel having the poorest performance. Following the application of a contrast stretching function the object recognition performance is improved in all channels. Multiple spatial frequency filters were designed to simulate the filtering channels that occur in the human visual system. Following these preprocessing steps Dragan Vidacic\u27s methodology is followed in order to determine the benefits that are obtained from the preprocessing steps being investigated. It is shown that performance gains are realized by using such preprocessing steps

QEBA: Query-Efficient Boundary-Based Blackbox Attack

Machine learning (ML), especially deep neural networks (DNNs) have been widely used in various applications, including several safety-critical ones (e.g. autonomous driving). As a result, recent research about adversarial examples has raised great concerns. Such adversarial attacks can be achieved by adding a small magnitude of perturbation to the input to mislead model prediction. While several whitebox attacks have demonstrated their effectiveness, which assume that the attackers have full access to the machine learning models; blackbox attacks are more realistic in practice. In this paper, we propose a Query-Efficient Boundary-based blackbox Attack (QEBA) based only on model's final prediction labels. We theoretically show why previous boundary-based attack with gradient estimation on the whole gradient space is not efficient in terms of query numbers, and provide optimality analysis for our dimension reduction-based gradient estimation. On the other hand, we conducted extensive experiments on ImageNet and CelebA datasets to evaluate QEBA. We show that compared with the state-of-the-art blackbox attacks, QEBA is able to use a smaller number of queries to achieve a lower magnitude of perturbation with 100% attack success rate. We also show case studies of attacks on real-world APIs including MEGVII Face++ and Microsoft Azure.Comment: Accepted by CVPR 202

Review on Quantitative Assessment of Corporate Governance

Recently a lot of different institutions and research centers around the world gradually launch their corporate governance assessment system, making each interested party to get to know the corporate governance level and making reasonable decisions. This essay is based upon corporate governance and assessment connotation, summarizes and concludes the research progress of domestic and overseas corporate governance quantitative assessment, finding that corporate governance quantitative assessment mainly relies on composite indicator assessment, but there is still big difference in the starting point, targeted object and assessment indicator of assessment indicator system, so some people question the validity and applicability of this assessment indicator system. Based on this, this essay points out that the existent literature review has some problems such as assessment subject is vague, missing out some key indicators, weighting subjectively and failing to abide the principle of “ substance over form”, thus bringing up corresponding suggestion.Recently a lot of different institutions and research centers around the world gradually launch their corporate governance assessment system, making each interested party to get to know the corporate governance level and making reasonable decisions. This essay is based upon corporate governance and assessment connotation, summarizes and concludes the research progress of domestic and overseas corporate governance quantitative assessment, finding that corporate governance quantitative assessment mainly relies on composite indicator assessment, but there is still big difference in the starting point, targeted object and assessment indicator of assessment indicator system, so some people question the validity and applicability of this assessment indicator system. Based on this, this essay points out that the existent literature review has some problems such as assessment subject is vague, missing out some key indicators, weighting subjectively and failing to abide the principle of “ substance over form”, thus bringing up corresponding suggestion

Study of the Influence of Corporate Governance Level on Investors’ Confidence

Stock market investment has the Sheep-Flock Effect, so investors’ confidence relates to the stability and healthy development of the stock market. The functional mechanism of investors’ confidence is complicated with many influential factors. This paper selects the factor of corporate governance level to investigate and study the great effect of corporate governance level evaluation on maintaining and increasing investors’ confidence from the perspective of investors. In this paper, the method to measure investors’ confidence and corporate governance level is improved, and the data of A-share companies listed in Shanghai Stock Exchange of China in 2011-2013 is selected as the sample to analyze the panel data. The results show that, the higher the corporate governance level is, the stronger investors’ confidence is; investors’ confidence is also influenced by the macro level of the market and the nature of various industries is different, so significances of influences of corporate governance level in different industries on investors’ confidence are not the same. At the same time, the empirical results show that investors’ confidence has a positive lag effect

Substitution between CSR Activities: Evidence from Hiring and Mistreating Unauthorized Workers and Pollution

We argue substitution exists among CSR investments and exogenously increasing one CSR investment could lead to a decrease in another CSR investment. We provide evidence using the U.S. states’ staggered adoptions of E-Verify mandates, which curtails a labor-related social bad by reducing the hiring of unauthorized workers and related workplace abuses. We find the mandate leads to an increase in plant-level pollution, an environmental social bad, and the effect is stronger when the mandate applies to more employers, for plants in states with more unauthorized workers in the labor force, and for plants with jobs that are inherently more hazardous

Forward modeling of tree-climate relations across the Northern Hemisphere

University of Minnesota M.A. thesis. December 2014. Major: Geography. Advisor: Dr. Scott St. George. 1 computer file (PDF); v, 28 pages.This thesis uses the Vaganov-Shashkin model of tree ring formation, a multivariate, nonlinear, mechanistic model that directly predicts tree-ring growth using climate data, to simulate tree-ring formation across the Northern Hemisphere. Previous research has shown the model has skill in reproducing ring-width variability and climate sensitivity at local and regional scales, but its ability to simulate the major geographical differences in tree-climate relationships at a hemispheric scale has not yet been tested. In this study, we ran the model at over 7,000 locations across the Northern Hemisphere, and compared the seasonal climate responses of the simulations against a network of nearly 2,200 real tree-ring width records. We also calculated the predicted dominant factor at each location and used relative growth rates to explain these patterns. Simulated tree-ring chronologies are consistent with the real ones in the seasonality and relative strength of the encoded climate signals, demonstrating that the model has skill in reproducing tree-ring growth response to climate variability across the Northern Hemisphere. Because the simulations were produced using only climate records and the same set of parameters, the fact that the model was able to reproduce major geographical differences in the observations suggests that climate is the primary factor in determining large-scale tree-climate relationships. We also used relative growth rates to show the sequence of events during the growing season and the possible mechanism of the climate response of tree rings. We found that temperature dominates growth at temperature-sensitive sites during most of the growing season and that at stations where temperature dominates growth at the end of growing season, summer precipitation generally has a strong positive influence on tree-ring formations, while at locations where soil moisture limits growth at the end of growing season, ring widths usually have a positive correlation with winter precipitation. Because the model has skill in reproducing ring widths and tree-climate relationships at local, regional and hemispheric scales, we suggest VSM can potentially be used as a low-cost estimator to predict tree-ring response to climate prior to sampling and to forecast long-term changes in tree-climate relationships