Charging station planning based on the accumulation prospect theory and dynamic user equilibrium

This study investigates the electric vehicle (EV) traffic equilibrium and optimal deployment of charging locations subject to range limitation. The problem is similar to a network design problem with traffic equilibrium, which is characterized by a bilevel model structure. The upper level objective is to optimally locate charging stations such that the total generalized cost of all users is minimized, where the user’s generalized cost includes two parts, travel time and energy consumption. The total generalized cost is a measure of the total societal cost. The lower level model seeks traffic equilibrium, in which travelers minimize their individual generalized cost. All the utilized paths have identical generalized cost while satisfying the range limitation constraint. In particular, we use origin-based flows to maintain the range limitation constraint at the path level without path enumeration. To obtain the global solution, the optimality condition of the lower level model is added to the upper level problem resulting in a single level model. The nonlinear travel time function is approximated by piecewise linear functions, enabling the problem to be formulated as a mixed integer linear program. We use a modest-sized network to analyze the model and illustrate that it can determine the optimal charging station locations in a planning context while factoring the EV users’ individual path choice behaviours.

Electromagnetic Weaponed Air Robot

This article proposes the integration of mini electromagnetic weapons into an air robot, autonomous targeting of possible targets with an electromagnetic weapon, and features that an electromagnetic armed aircraft robot should have. Unlike traditional user-controlled aerial robot approaches, it targets autonomous movements in the mission area with image processing techniques, so the robot can detect targets and accurately target targets without the need for user control. An autonomous targeting mechanism has been developed with an electromagnetic weapon integrated into the air robot to create a reference route. Various methods are proposed considering the range limitation of electromagnetic weapons and possible targeting errors of the robot user. For target tracking, a control algorithm has been developed to have the most appropriate targeting under the dynamic constraints of the robot and the user. Prototyping and experiments demonstrate the ability of an autonomous electromagnetic armed air robot with autonomous targeting system to address user and targeting problems.

Range limitation of the Peaks of Otter salamander (Plethodon hubrichti) due to competition with the eastern red-backed salamander (Plethodon cinereus) in sympatry

The Peaks of Otter salamander, Plethodon hubrichti, is a montane species found at altitudes above 442 m within a 117 km2 area of the Blue Ridge Mountains in central Virginia, USA. In areas where this species is sympatric with the eastern red-backed salamander (Plethodon cinereus) it seemed likely that P. hubrichti populations were either depressed or eliminated. The habitability of areas beyond the current range boundaries for P. hubrichti is supported by several disjunct populations in areas sympatric with P. cinereus. From 2009 to 2012 we tested whether P. hubrichti was negatively impacted by competition with P. cinereus by removing P. cinereus from treatment plots at three sympatric field locations. The number of surface-active (SA) P. hubrichti increased significantly more on treatment plots than on corresponding reference plots, whereas the number of SA P. cinereus decreased significantly more on treatment plots than on reference plots. The removal of every one P. cinereus from the treatment plots led to an increase of 0.69 P. hubrichti. These results emphasise the importance of conserving mature hardwood forests along the perimeter of the P. hubrichti distribution, where it is sympatric with P. cinereus, so as to prevent future range contraction of this vulnerable species.

Species-energy relationships of indigenous and invasive species may arise in different ways – a demonstration using springtails

Although the relationship between species richness and available energy is well established for a range of spatial scales, exploration of the plausible underlying explanations for this relationship is less common. Speciation, extinction, dispersal and environmental filters all play a role. Here we make use of replicated elevational transects and the insights offered by comparing indigenous and invasive species to test four proximal mechanisms that have been offered to explain relationships between energy availability, abundance and species richness: the sampling mechanism (a null expectation), and the more individuals, dynamic equilibrium and range limitation mechanisms. We also briefly consider the time for speciation mechanism. We do so for springtails on sub-Antarctic Marion Island. Relationships between energy availability and species richness are stronger for invasive than indigenous species, with geometric constraints and area variation playing minor roles. We reject the sampling and more individuals mechanisms, but show that dynamic equilibrium and range limitation are plausible mechanisms underlying these gradients, especially for invasive species. Time for speciation cannot be ruled out as contributing to richness variation in the indigenous species. Differences between the indigenous and invasive species highlight the ways in which deconstruction of richness gradients may usefully inform investigations of the mechanisms underlying them. They also point to the importance of population size-related mechanisms in accounting for such variation. In the context of the sub-Antarctic our findings suggest that warming climates may favour invasive over indigenous species in the context of changes to elevational distributions, a situation found for vascular plants, and predicted for springtails on the basis of smaller-scale manipulative field experiments.

Variable size sampling to support high uniformity confidence in sensor data streams

In order to rapidly process large amounts of sensor stream data, it is effective to extract and use samples that reflect the characteristics and patterns of the data stream well. In this article, we focus on improving the uniformity confidence of KSample, which has the characteristics of random sampling in the stream environment. For this, we first analyze the uniformity confidence of KSample and then derive two uniformity confidence degradation problems: (1) initial degradation, which rapidly decreases the uniformity confidence in the initial stage, and (2) continuous degradation, which gradually decreases the uniformity confidence in the later stages. We note that the initial degradation is caused by the sample range limitation and the past sample invariance, and the continuous degradation by the sampling range increase. For each problem, we present a corresponding solution, that is, we provide the sample range extension for sample range limitation, the past sample change for past sample invariance, and the use of UC-window for sampling range increase. By reflecting these solutions, we then propose a novel sampling method, named UC-KSample, which largely improves the uniformity confidence. Experimental results show that UC-KSample improves the uniformity confidence over KSample by 2.2 times on average, and it always keeps the uniformity confidence higher than the user-specified threshold. We also note that the sampling accuracy of UC-KSample is higher than that of KSample in both numeric sensor data and text data. The uniformity confidence is an important sampling metric in sensor data streams, and this is the first attempt to apply uniformity confidence to KSample. We believe that the proposed UC-KSample is an excellent approach that adopts an advantage of KSample, dynamic sampling over a fixed sampling ratio, while improving the uniformity confidence.