Cloaking locations for anonymous location based services: a hybrid approach

An important privacy issue in Location Based Services is to hide a user’s identity while still provide quality location based services. Previous work has addressed the problem of locational -anonymity either based on centralized or decentralized schemes. However, a centralized scheme relies on an anonymizing server (AS) for location cloaking, which may become the performance bottleneck when there are large number of clients. More importantly, holding information in a centralized place is more vulnerable to malicious attacks. A decentralized scheme depends on peer communication to cloak locations and is more scalable. However, it may pose too much computation and communication overhead to the clients. The service fulfillment rate may also be unsatisfied especially when there are not enough peers nearby. This paper proposes a new hybrid framework called HiSC that balances the load between the AS and mobile clients. HiSC partitions the space into base cells and a mobile client claims a surrounding area consisting of base cells. The number of mobile clients in the surrounding cells is kept and updated at both client and AS sides. A mobile client can either request cloaking service from the centralized AS or use a peer-to-peer approach for spatial cloaking based on personalized privacy, response time, and service quality requirements. HiSC can elegantly distribute the work load between the AS and the mobile clients by tuning one system parameter base cell size and two client parameters - surrounding cell size and tolerance count. By integrating salient features of two schemes, HiSC successfully preserves query anonymity and provides more scalable and consistent service. Both the AS and the clients can enjoy much less work load. Additionally, we propose a simple yet effective random range shifting algorithm to prevent possible privacy leakage that would exist in the original P2P approach. Our experiments show that HiSC can elegantly balance the work load based on privacy requirements and client distribution. HiSC provides close to optimal service quality. Meanwhile, it reduces the response time by more than an order of magnitude from both the P2P scheme and the centralized scheme when anonymity level(value of ) or number of clients is large. It also reduces the update message cost of the AS by nearly 6 times and the peer searching message cost of the clients by more than an order of magnitude.

Mobile local search with noisy locations

The deep penetration of mobile devices have led to the emergence of multiple mobile applications that seek to harness the positioning capabilities embedded in such devices. One of the most functional of these applications is local search. Local search is similar to a regular web search, yet is more powerful in a mobile setting since results are ranked both by prominence and locality. Undoubtedly popular, the current design of local search applications fails to cater equally to a privacy-aware user who desires finer controls in her location disclosure. Towards this end, we propose the design for a private local search (PriLS) application that enables a user to first learn the geographic variation in local search results and then use it to determine a noisy location that has little or no affect on the search results. Parametric studies and real-world evaluations show that PriLS can help identify geographic locations that would produce similar search results (compared to when the user’s location is used) with no noticeable delays in user experience. They also reveal that large areas typically exist where there is no change in the result of a local search query, and can be exploited to provide spatial privacy guarantees to a user.     

Robust design considering highly nonlinear structural behavior

The optimization of structures subject to highly nonlinear behavior, particularly crash structures, requires observance of all design-significant scatterings. This paper presents a time-saving method to generate structures satisfying robust design demands. A vital aspect of robust design from the aircraft industries’ point of view is the consideration of fail-safe approaches accounting for possible structural failure from previous loading or manufacturing inaccuracies. Additional structural elements are utilized to prevent (after failure occurred) the structure from deforming out of bounds. This paper presents an approach on how to include this in the robust design process.     

Identifying locations from geospatial trajectories

Harnessing the latent knowledge present in geospatial trajectories allows for the potential to revolutionise our understanding of behaviour. This paper discusses one component of such analysis, namely the extraction of significant locations. Specifically, we: (i) present the Gradient-based Visit Extractor (GVE) algorithm capable of extracting periods of low mobility from geospatial data, while maintaining resilience to noise, and addressing the drawbacks of existing techniques, (ii) provide a comprehensive analysis of the properties of these visits and consequent locations, extracted through clustering, and (iii) demonstrate the applicability of GVE to the problem of visit extraction with respect to representative use-cases.     

Using gravity models for the evaluation of new university site locations: A case study

A fundamental aspect of competitive spatial models is the choice behaviour of potential customers to patronize a facility. Most of the models used to describe this phenomenon are essentially based on the adaptation of Newton's law of gravitation to the economic case (gravity model).     

Robust counterparts of errors-in-variables problems

Linear data fitting problems with uncertain data which lie in a given uncertainty set are considered. A robust counterpart of such a problem may be interpreted as the problem of finding a solution which is best over all possible perturbations of the data which lie in the set. In particular, robust counterparts of total least squares problems have been studied and good algorithms are available. Robust counterparts of the problems considered as errors-in-variables problems are considered, when it is appropriate to work directly with the uncertain variable values. It is shown how the original problems can be replaced by convex optimization problems in fewer variables for which standard software may be applied.     

SISO系统的鲁棒性能设计

本文讨论了ＳＩＳＯ系统的鲁棒性能设计问题。根据具有乘性不确定性ＳＩＳＯ系统鲁棒性能指标μ的显式表达式,分析了μ综合中权函数的选择,文中还配有例题进行说明。     

Robust control techniques for general dynamic systems

Lyapunov techniques are used to design robust controllers for nonlinear systems. The objective is to use the system structure to simplify the controller as far as possible. A general robust control scheme is developed that applies to systems described by a class of second-order nonlinear equations. Applications to a mobile robot and a chemical stirred tank reactor are given.     

WebPass：一种通过Web页面作定向广播的方法

Web页面目前主要被作为信息广播工具,但在信息保密、隐私和产权保护方面存在不足。提出一种简单而新颖方法,利用Web页面实现了限制性定向广播。已经成功应用于教师教案定向广播和同学会照片散发。     

Robust detection and tracking of annotations for outdoor augmented reality browsing

A common goal of outdoor augmented reality (AR) is the presentation of annotations that are registered to anchor points in the real world. We present an enhanced approach for registering and tracking such anchor points, which is suitable for current generation mobile phones and can also successfully deal with the wide variety of viewing conditions encountered in real life outdoor use. The approach is based on on-the-fly generation of panoramic images by sweeping the camera over the scene. The panoramas are then used for stable orientation tracking, while the user is performing only rotational movements. This basic approach is improved by several new techniques for the re-detection and tracking of anchor points. For the re-detection, specifically after temporal variations, we first compute a panoramic image with extended dynamic range, which can better represent varying illumination conditions. The panorama is then searched for known anchor points, while orientation tracking continues uninterrupted. We then use information from an internal orientation sensor to prime an active search scheme for the anchor points, which improves matching results. Finally, global consistency is enhanced by statistical estimation of a global rotation that minimizes the overall position error of anchor points when transforming them from the source panorama in which they were created, to the current view represented by a new panorama. Once the anchor points are redetected, we track the user's movement using a novel 3-degree-of-freedom orientation tracking approach that combines vision tracking with the absolute orientation from inertial and magnetic sensors. We tested our system using an AR campus guide as an example application and provide detailed results for our approach using an off-the-shelf smartphone. Results show that the re-detection rate is improved by a factor of 2 compared to previous work and reaches almost 90% for a wide variety of test cases while still keeping the ability to run at interactive frame rates.     

Robust performance assessment of feedback control systems

The proper measure of closed-loop performance variation in the presence of model-plant mismatch is discussed in this paper. A generalized closed-loop error transfer function, which is a special representation of the dual Youla parameter and has a close relationship with the pointwise ν-gap metric, is proposed as the suitable means of representing closed-loop performance variation in case of plant perturbation, and the closed-loop performance variation measure is accordingly defined as its maximum singular value frequency by frequency. It is shown that this measure is essential and informative in characterizing closed-loop performance variation. This measure is also shown to be readily applicable to on-line closed-loop performance assessment or monitoring, even without the explicit model of the plant. Its variant, defined as the η-function, which features the relative performance variation as well as generalized stability margin variation with respect to the nominal plant, is also discussed.     

Robust controller design for a class of nonlinear uncertain chemical processes

This article considers the issue of designing robust controllers for single-input/single-output nonlinear chemical processes whose uncertainties satisfy the so-called generalized matching condition. The nominal system (mathematical model) is assumed to be input–output linearizable and the only assumption on uncertainties is that they are bounded. A design methodology of combining the techniques of the differential geometric feedback linearization, the sliding mode control strategy and the adaptive state feedback is presented. Based on the nominal system and the related bounds of uncertainties, a hybrid nonlinear controller, which is more practicable and easily implemented than many other existing ones in the literature, is proposed. A Lyapunov-based approach is utilized to guarantee the robust stability and behavior of the closed-loop system. For demonstrating the effectiveness and applicability of the proposed scheme, we applied it to the control of a continuously stirred tank reactor (CSTR) in the presence of uncertainties including unmodeled side reaction, measuring error, and/or extra unmeasured disturbances. The potential use of a sliding observer along with the proposed scheme is also investigated in this work. Extensive simulation results reveal that the proposed scheme appears to be a practical and promising approach to the robust control of nonlinear uncertain chemical processes.     

Robust edge detection

Edge detection is an important issue in computer vision and image understanding systems. Most conventional techniques have assumed Gaussian noise, and their performance could decrease with the departure of noise distribution from normality. In this paper, we present an edge detection approach using robust statistics. The edge structure is first detected by a robust one-way design model, and then localized by a robust contrast test. Finally, hysteresis thresholding is applied to yield the output edge map. To evaluate its performance, experiments were carried out on synthetic and real images corrupted with both Gaussian noise and a mixture of Gaussian and impulsive noise. The results show that the performance of the proposed edge detector is stable and reliable under severe impulsive noise conditions.     

Robust optimal decisions with imprecise forecasts

A robust minimax approach for optimal investment decisions with imprecise return forecasts and risk estimations in financial portfolio management is considered. Single-period and multi-period mean-variance optimization models are extended to worst-case design with multiple rival risk estimations and return forecasts. In multi-period stochastic formulation of classical mean-variance portfolio optimization problem, an investor makes an investment decision based on expectations and/or scenarios up to some intermediate times prior to the horizon and, consequently, rebalances or restructures the portfolio. Multi-period portfolio optimization entails the construction of a scenario tree representing a discretized estimate of uncertainties and associated probabilities in future stages. It is well known that return forecasts and risk estimations are inherently inaccurate and there are different rival estimates, or scenario trees. Robust optimization models are presented and imprecise nature of moment forecasts to reduce the risk of making a decision based on the wrong scenario is addressed. The worst-case performance is guaranteed in view of all rival risk and return scenarios and will only improve when any scenario other than the worst-case is realized. The ex-ante performance of minimax models is tested using historical data and backtesting results are presented.     

Robust investment decisions under supply disruption in petroleum markets

Energy-dependent economies and energy security strategies need to cope with oil and gas supply disruptions that are rare but persistent and can be financially catastrophic. This paper proposes a tractable approach for determining robust investment strategies in petroleum markets under the risk of supply disruption when asset prices follow geometric mean-reverting jump processes. The robust counterpart of the portfolio management problem under supply disruption is derived for several symmetric and asymmetric representations of the uncertainties in the problem. Computational experiments with real market data indicate that the robust optimization approach using uncertainty sets tailored to the characteristics of the data results in strategies with superior worst-case performance.     

参数空间中鲁棒稳定性问题

本文研究了单输入多输出(SIMO)和多输入单输出(MISO)线性定常控制系统在对象参数扰动下的鲁棒稳定性问题,并对一给定的控制器,系统在标称参数P°下闭环渐稳的情况,提出了在参数空间中构造比中心位于P°的最大稳定超球还要大的稳定超球的方法,从而改善了鲁棒稳定性判据.     

Robust image-based visual servoing using invariant visual information

This paper deals with the use of invariant visual features for visual servoing. New features are proposed to control the 6 degrees of freedom of a robotic system with better linearizing properties and robustness to noise than the state of the art in image-based visual servoing. We show in this paper that by using these features the behavior of image-based visual servoing in task space can be significantly improved. Several experimental results are provided and validate our proposal.