A network tomography approach for traffic monitoring in smart cities

Various urban planning and managing activities required by a Smart City are feasible because of traffic monitoring. As such, the thesis proposes a network tomography-based approach that can be applied to road networks to achieve a cost-efficient, flexible, and scalable monitor deployment. Due to the algebraic approach of network tomography, the selection of monitoring intersections can be solved through the use of matrices, with its rows representing paths between two intersections, and its columns representing links in the road network. Because the goal of the algorithm is to provide a cost-efficient, minimum error, and high coverage monitor set, this problem can be translated into an optimization problem over a matroid, which can be solved efficiently by a greedy algorithm. Also as supplementary, the approach is capable of handling noisy measurements and a measurement-to-path matching. The approach proves a low error and a 90% coverage with only 20% nodes selected as monitors in a downtown San Francisco, CA topology --Abstract, page iv

Justifying a privacy guardian in discourse and behaviour : the People’s Republic of China’s strategic framing in data governance

The People’s Republic of China’s (PRC) approach to data governance, centred on data sovereignty, is much debated in academic literature. However, it remains unclear how the PRC’s different state actors justify this approach. Based on an analysis of the discourse and behaviour of the PRC’s state actors through strategic framing theory, their role as a privacy guardian can arguably be described as strategically constructed. The Chinese government and legislative bodies have tailored their communications to present themselves as champions of individual privacy, aiming to secure support for state policies. This strategic framing encompasses four mechanisms: the reframing of privacy threats through political narratives; legal ambiguities; selective framing; and the implementation of censorship to influence public discourse. An examination of how the Chinese government responded differently to data breaches in the cases of Didi and the Shanghai National Police Database leak highlights the Chinese government’s efforts in maintaining framing consistency to construct itself as a guardian, rather than a violator, of individual privacy.Peer reviewe

Watertightization of Trimmed Surfaces at Intersection Boundary

This paper introduces a watertight technique to deal with the boundary representation of surface-surface intersection in CAD. Surfaces play an important role in today's geometric design. The mathematical model of non-uniform rational B-spline surfaces (NURBS) is the mainstream and ISO standard. In the situation of surface-surface intersection, things are a little complicated, for some parts of surfaces may be cut-off, so called trimmed surfaces occur, which is the central topic in the past decades in CAD community of both academia and industry. The main problem is that the parametric domain of the trimmed surface generally is not the standard square or rectangle, and rather, typically, bounded by curves, based on point inverse of the intersection points and interpolated. The existence of gaps or overlaps at the intersection boundary makes hard the preprocessing of CAE and other downstream applications. The NURBS are in this case hard to keep a closed form. In common, a special data structure of intersection curves must be affiliated to support downstream applications, while the data structure of the whole CAD system is not unified, and the calculation is not efficient. In terms of Bezier surface, a special case of NURBS, this paper designs a reparameterization or normalization to transform the trimmed surface into a group of Bezier surface patches in standard parametric domain [0,1]X[0,1]. And then the boundary curve of normalized Bezier surface patch can be replaced by the intersection curve to realize watertight along the boundary. In this way, the trimmed surface is wiped out, the "gap" between CAD and CAE is closed.Comment: 10 pages,6 figure

Just Fine-tune Twice: Selective Differential Privacy for Large Language Models

With the increasing adoption of NLP models in real-world products, it becomes more and more important to protect these models from privacy leakage. Because private information in language data is sparse, previous research formalized a Selective-Differential-Privacy (SDP) notion to provide protection for sensitive tokens detected by policy functions, and prove its effectiveness on RNN-based models. But the previous mechanism requires separating the private and public model parameters and thus cannot be applied on large attention-based models. In this paper, we propose a simple yet effective just-fine-tune-twice privacy mechanism to first fine-tune on in-domain redacted data and then on in-domain private data, to achieve SDP for large Transformer-based language models. We also design explicit and contextual policy functions to provide protections at different levels. Experiments show that our models achieve strong performance while staying robust to the canary insertion attack. We further show that even under low-resource settings with a small amount of in-domain data, SDP can still improve the model utility. We will release the code, data and models to facilitate future research

Characterization of behaviour and hazards of fire and deflagration for high-energy Li-ion cells by over-heating

Fire and deflagration are extreme manifestation of thermal runaway (TR) of Li-ion cells, and they are characterized for fully charged LiNiCoAlO2 (LNCA) 18650 cells in this investigation. The cells are over-heated using a cone calorimeter under different incident heat fluxes. When the cells are exposed to the incident heat flux larger than 35 kW m−2, both fire and deflagration present. The pressure valve opens when the temperature of the cell is higher than 132 °C. The fire occurs with the valve opening when the concentration of the venting vapour in the air is higher than the lower flammability limit. The deflagration happens after the cell temperature arrives about 200 °C, and is mainly arising from the cathode decomposition, the combustion of solvents and the anode relevant thermal reactions. The extreme temperatures of the cell and the flame during deflagration are over than 820 and 1035 °C, respectively. The production of COx, mass loss, heat release rate (HRR) are quantitative identified, and are found increase as the increasing incident heat flux. Based on revised oxygen consumption method, the HRR and liberated heat during the fire and deflagration for the cells are up to 11.8 ± 0.05 kW and 163.1 ± 1.5 kJ, respectively

Towards Efficient Data Valuation Based on the Shapley Value

"How much is my data worth?" is an increasingly common question posed by organizations and individuals alike. An answer to this question could allow, for instance, fairly distributing profits among multiple data contributors and determining prospective compensation when data breaches happen. In this paper, we study the problem of data valuation by utilizing the Shapley value, a popular notion of value which originated in coopoerative game theory. The Shapley value defines a unique payoff scheme that satisfies many desiderata for the notion of data value. However, the Shapley value often requires exponential time to compute. To meet this challenge, we propose a repertoire of efficient algorithms for approximating the Shapley value. We also demonstrate the value of each training instance for various benchmark datasets