A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications.

Generative Semantics 4: The Collapse

This chapter traces the collapse of Generative Semantics, which ultimately became a movement away from Noam Chomsky’s view of linguistics, more than a movement toward a unifying vision of language or linguistics. The leaders all went in various directions. Paul Postal and Jim McCawley retained their commitments to formal modeling, but Postal developed a new, non-Transformational framework with David Perlmutter, Relational Grammar, while McCawley continued to ply an increasingly idiosyncratic Transformational model he eventually called Unsyntax. Robin Lakoff led the expansion of linguistic pragmatics and founded feminist linguistics. George Lakoff and Haj Ross took overlapping but distinct forays into non-discrete linguistics. Meanwhile, the Generative Semantics ethos was losing whatever appeal it may have had. Linguists outside the movement, and some within, found the style irritating. Meanwhile, too, Chomsky’s innovations were proving very fruitful and attracting adherents under the label, the Extended Standard Theory. Chomsky’s framework emerged from the brief Generative Semantics eclipse and now seemed the clear winner of the Linguistics Wars.

The Drunk Utilitarian Revisited: Does Alcohol Really Increase Utilitarianism in Moral Judgment?

The “drunk utilitarian” phenomenon suggests that people are more likely to accept harm for the greater good when they are under the influence of alcohol. This phenomenon conflicts with the ideas that (a) acceptance of pro-sacrificial harm requires inhibitory control of automatic emotional responses to the idea of causing harm and (b) alcohol impairs inhibitory control. This preregistered experiment aimed to provide deeper insights into the effects of alcohol on moral judgments by using a formal modeling approach to disentangle three factors in moral dilemma judgments and by distinguishing between instrumental harm and impartial beneficence as two distinct dimensions of utilitarian psychology. Despite the use of a substantially larger sample and higher doses of alcohol compared with the ones in prior studies, alcohol had no significant effect on moral judgments. The results pose a challenge to the idea that alcohol increases utilitarianism in moral judgments.

Modeling unmanned aerial vehicle system for identifying foci of arboviral disease with monitoring system

People who live in low-income and hard-to-reach regions are usually the most affected ones by high incidences of arboviral diseases, increasing morbidity and mortality rates, and public health costs. We present the modeling of hardware and software components of an unmanned aerial vehicle (UAV) system by mathematical tools, focusing on monitoring foci of arboviral diseases transmitted by Aedes aegypti mosquito, e.g., Zika, Chikungunya, and Dengue. We used restriction equations and the colored Petri nets formal modeling language to represent the flight dynamics and the software components of the system, respectively. We evaluated the specification of desired behaviors of the monitoring system using simulations and the model checking technique. The results showed the completeness and correctness of the specification. The design of such a system is challenging due to the potential risks to people and the environment. Therefore, this study provides insights into the development of an UAV system for such an application scenario. The monitoring system has the potential of improving the efficiency in identifying foci of arboviral diseases.