Convex Optimization for Linear Query Processing under Approximate Differential Privacy

Differential privacy enables organizations to collect accurate aggregates over sensitive data with strong, rigorous guarantees on individuals' privacy. Previous work has found that under differential privacy, computing multiple correlated aggregates as a batch, using an appropriate \emph{strategy}, may yield higher accuracy than computing each of them independently. However, finding the best strategy that maximizes result accuracy is non-trivial, as it involves solving a complex constrained optimization program that appears to be non-linear and non-convex. Hence, in the past much effort has been devoted in solving this non-convex optimization program. Existing approaches include various sophisticated heuristics and expensive numerical solutions. None of them, however, guarantees to find the optimal solution of this optimization problem. This paper points out that under ($\epsilon$, $\delta$)-differential privacy, the optimal solution of the above constrained optimization problem in search of a suitable strategy can be found, rather surprisingly, by solving a simple and elegant convex optimization program. Then, we propose an efficient algorithm based on Newton's method, which we prove to always converge to the optimal solution with linear global convergence rate and quadratic local convergence rate. Empirical evaluations demonstrate the accuracy and efficiency of the proposed solution.Comment: to appear in ACM SIGKDD 201

Molecular Dynamics Simulation of Strong Shock Waves Propagating in Dense Deuterium With the Effect of Excited Electrons

We present a molecular dynamics simulation of shock waves propagating in dense deuterium with the electron force field method [J. T. Su and W. A. Goddard, Phys. Rev. Lett. 99, 185003 (2007)], which explicitly takes the excitation of electrons into consideration. Non-equilibrium features associated with the excitation of electrons are systematically investigated. We show that chemical bonds in D$_2$ molecules lead to a more complicated shock wave structure near the shock front, compared with the results of classical molecular dynamics simulation. Charge separation can bring about accumulation of net charges on the large scale, instead of the formation of a localized dipole layer, which might cause extra energy for the shock wave to propagate. In addition, the simulations also display that molecular dissociation at the shock front is the major factor corresponding to the "bump" structure in the principal Hugoniot. These results could help to build a more realistic picture of shock wave propagation in fuel materials commonly used in the inertial confinement fusion

Ground-Challenge: A Multi-sensor SLAM Dataset Focusing on Corner Cases for Ground Robots

High-quality datasets can speed up breakthroughs and reveal potential developing directions in SLAM research. To support the research on corner cases of visual SLAM systems, this paper presents Ground-Challenge: a challenging dataset comprising 36 trajectories with diverse corner cases such as aggressive motion, severe occlusion, changing illumination, few textures, pure rotation, motion blur, wheel suspension, etc. The dataset was collected by a ground robot with multiple sensors including an RGB-D camera, an inertial measurement unit (IMU), a wheel odometer and a 3D LiDAR. All of these sensors were well-calibrated and synchronized, and their data were recorded simultaneously. To evaluate the performance of cutting-edge SLAM systems, we tested them on our dataset and demonstrated that these systems are prone to drift and fail on specific sequences. We will release the full dataset and relevant materials upon paper publication to benefit the research community. For more information, visit our project website at https://github.com/sjtuyinjie/Ground-Challenge

Optimizing Batch Linear Queries under Exact and Approximate Differential Privacy

Differential privacy is a promising privacy-preserving paradigm for statistical query processing over sensitive data. It works by injecting random noise into each query result, such that it is provably hard for the adversary to infer the presence or absence of any individual record from the published noisy results. The main objective in differentially private query processing is to maximize the accuracy of the query results, while satisfying the privacy guarantees. Previous work, notably \cite{LHR+10}, has suggested that with an appropriate strategy, processing a batch of correlated queries as a whole achieves considerably higher accuracy than answering them individually. However, to our knowledge there is currently no practical solution to find such a strategy for an arbitrary query batch; existing methods either return strategies of poor quality (often worse than naive methods) or require prohibitively expensive computations for even moderately large domains. Motivated by this, we propose low-rank mechanism (LRM), the first practical differentially private technique for answering batch linear queries with high accuracy. LRM works for both exact (i.e., $\epsilon$-) and approximate (i.e., ($\epsilon$, $\delta$)-) differential privacy definitions. We derive the utility guarantees of LRM, and provide guidance on how to set the privacy parameters given the user's utility expectation. Extensive experiments using real data demonstrate that our proposed method consistently outperforms state-of-the-art query processing solutions under differential privacy, by large margins.Comment: ACM Transactions on Database Systems (ACM TODS). arXiv admin note: text overlap with arXiv:1212.230

Can digital finance drive urban–rural integration?

Financial services are an essential source of capital and play a crucial and significant role in urban–rural integration. We analyse empirically the effect of digital finance on urban–rural integration and its mechanism using provincial panel data in China for 2011–2020. The results indicate that digital finance contributes to urban–rural integration. Moreover, for every 1 standard deviation increase in digital finance development, the degree of urban–rural integration increases by 7.7% on average, and it is more evident in China’s eastern regions, with regional heterogeneity. The level of entrepreneurship can be a vital channel for digital finance to facilitate urban– rural integration. The mechanism of action of digital finance to facilitate urban–rural integration by improving entrepreneurship levels is primarily revealed in the group with lower levels of human capital, which exhibits certain inclusive characteristics. This study is conducive to developing a policy for promoting the free flow of resources between urban and rural areas and advancing urban–rural integration

Heat transfer characteristic analysis of negative pressure type EGR valve based on CFD

The negative pressure valve EGR bears thermal load for a long period, thus its heat transfer characteristics have an important impact on the stability of the engine. The fluid solid coupling method was employed to analyze the contact heat transfer between the inner cavity of the valve and the cooling water as well as the high temperature gas based on CFD. As a result, the characteristics of the internal fluid velocity field, pressure field and temperature field were obtained. Besides, the heat transfer capability of the valve was also improved by adding the annular cooling water channel. The test results showed that the calculation method has a high calculation accuracy providing an important basis for the optimization design of valves