Realizing Interspecies Democracy

Sue Donaldson, Janneke Vink, and Jean-Paul Gagnon discuss the problem of anthropocentric democratic theory and the preconditions needed to realize a (corrective) interspecies democracy. Donaldson proposes the formal involvement of nonhuman animals in political institutions—a revolutionary task; Vink argues for changes to the law that would cover nonhuman animals with inviolable political rights; and Gagnon advises a personal change to dietary choices (veganism) and ethical orientations (do no harm). Together, the three proposals point to a future position where humans can participate in a multispecies world in which nonhuman others are freed from our tyrannical grasp.

A new approach for predicting the future position of a moving object: Hurricanes case study

Nowadays, huge amounts of tracking data related to moving objects are being generated and collected in suitable repositories thanks to GPS devices, RFIDsensors, satellites and wireless communication technologies. Tracked moving objects could be pedestrians, cars, vessels, planes, animals, natural disasters. Those letters generate trajectory data that contain a great deal of knowledge. For this reason, these trajectory data sets need an urgent and an effective analysis process and constitute a rich source for inferring mobility patterns. Predicting the future position of a given moving object is one of the important tasks we can find in the knowledge discovery process. In fact, being able to predict a moving object’s future position related to natural phenomena, would allow decision makers to take strategic decisions in order to help the humanity, and prevent or avoid the propagation of natural catastrophes. The aim of this paper is to propose a new approach to predict the future position of a moving object, especially a moving region based on mobility patterns. To achieve this aim, we experiment our approach on a real case study related to hurricanes as moving regions. The proposed approach is composed of three phases. The first phase allows generating object mobility patterns. In the second phase, spatio-tempoal mobility rules are extracted from the generated patterns. In the third and last phase, hurricane future position prediction is accomplished by using the extracted rules.

Mapping post-Brexit environmental law

The UK’s withdrawal from the EU will not bring about immediate changes to the substance of environmental law in the UK, but that law will become easier to change. The future position is complicated by devolution within the UK, where differing policy objectives on continuing alignment with the EU and weaknesses in the inter-governmental structures are causing problems. Environmental principles are being given legal recognition and new structures for environmental governance being created for each nation. These include environmental watchdogs that go some of the way to making up for the loss of the oversight provided by the EU institutions.

‘Brexit’ and the Scots in England: A diaspora facing uncertainty?

Brexit has brought many uncertainties, including the future position of UK-based EU migrants. Our concern is with a much less studied group, albeit one of the largest socio-political sub-groups within England – the Scots. These are migrants who live in a different country but within the same state and recent constitutional decision making has not been kind to them. In 2014, English based Scots had no vote in the independence referendum and in the EU referendum they witnessed Scotland voting significantly differently to England, resulting in ongoing tensions between the UK and Scottish Governments. If Brexit leads to another independence referendum, what are the implications for Scots in England, in terms of their citizenship, identity, and residence in a very different (r)UK? We explore their status in a (r)UK outside the EU, we speculate on whether some might move back or whether, if they remain, they would experience hostility within post-Brexit England. Might the current position of the English Scots tell us something about the future relationship between England and Scotland?

Efficient Geo-Textual Hybrid Indexing Techniques for Moving Objects and Queries

Advancements of various Geographic Information Technologies have resulted in huge growth in Geo-Textual data. Many Indexing and searching algorithms are developed to handle this Geo-Textual data which contains spatial, textual and temporal information. In past, Indexing and searching algorithms are developed for the applications in which the object trajectory or velocity vector is known in advance and hence we can predict the future position of the objects. There are real time applications like emergency management systems, traffic monitoring, where the objects movements are unpredictable and hence future position of the objects cannot be predicted. Techniques are required to answer the geo-textual kNN query where the velocity vectors or trajectories of moving and moving queries are not known. In case of moving objects, capturing current position of the object and maintaining spatial index optimally is very much essential. The hybrid indexing techniques used earlier are based on R-tree spatial index. The nodes of the R-tree index structure are split or merged to maintain the locations of continuously moving objects, increasing the maintenance cost as compared to the grid index. In this paper a solution is proposed for creating and maintaining hybrid index for moving objects and queries based on grid and inverted list hybrid indexing techniques. The method is also proposed for finding Geo-Textual nearest neighbours for static and moving queries using hybrid index and conceptual partitioning of the grid. The overall gain reported by the experimental work using hybrid index over the non- hybrid index is 30 to 40 percent depending on the grid size chosen for mapping the data space and on the parameters of queries.

Using Real-Time Dynamic Prediction to Implement IoV-Based Collision Avoidance

For some IoV-based collision-avoidance architectures, it is not necessary that all vehicles have communication abilities. Hence, they need some particular designs and extra components. In the literature, one of them uses a camera mounted onto the infrastructure at an intersection to realize collision detection. Consequently, technologies for real-time object detection and dynamic prediction are required for the purposes of collision avoidance. In this paper, we propose an interesting method to predict the future position of a vehicle based on a well-known, real-time object detection project, YOLOv3. Our algorithm utilizes the concept of vehicle dynamics and the confidence region to predict the future position on vehicles. This will help us to realize real-time dynamic prediction and Internet of Vehicles (IoV)-based collision detection. Lastly, in accordance with the experimental results, our design shows the performance for predicting the future position of a vehicle.