Path Approach Research Articles

Quantifying the Landscape of Decision Making From Spiking Neural Networks.

The decision making function is governed by the complex coupled neural circuit in the brain. The underlying energy landscape provides a global picture for the dynamics of the neural decision making system and has been described extensively in the literature, but often as illustrations. In this work, we explicitly quantified the landscape for perceptual decision making based on biophysically-realistic cortical network with spiking neurons to mimic a two-alternative visual motion discrimination task. Under certain parameter regions, the underlying landscape displays bistable or tristable attractor states, which quantify the transition dynamics between different decision states. We identified two intermediate states: the spontaneous state which increases the plasticity and robustness of changes of minds and the “double-up” state which facilitates the state transitions. The irreversibility of the bistable and tristable switches due to the probabilistic curl flux demonstrates the inherent non-equilibrium characteristics of the neural decision system. The results of global stability of decision-making quantified by barrier height inferred from landscape topography and mean first passage time are in line with experimental observations. These results advance our understanding of the stochastic and dynamical transition mechanism of decision-making function, and the landscape and kinetic path approach can be applied to other cognitive function related problems (such as working memory) in brain networks.

Reliable trajectory-adaptive routing strategies in stochastic, time-varying networks with generalized correlations

This paper focuses on the problem of finding optimal trajectory-adaptive routing strategies in stochastic time-varying networks with generalized spatio-temporal correlations. A representation for jointly distributed continuous link travel times across the entire network with time-varying distributions and correlation structures is presented, and the crucial characteristics and methodological difficulties of the problem are discussed. The paper presents a generalized 2-stage path and strategy finding solution approach that can serve for finding both exact and approximate solutions with the tuning of a risk-level tolerance parameter. The first stage of the solution approach generates eligible paths, where the risk-level parameter is used to eliminate paths that are likely to be inefficient. The second stage finds reliable trajectory-adaptive strategies, using the eligible paths only, based on one or multiple reliability-based optimality conditions. Thus, the approach allows the user to determine the optimal strategy for one or multiple groups of travelers with different reliability preferences. Numerical experiments show that the average running time of the algorithm reduces super-linearly with the increase of the risk-tolerance parameter ∊, while incurring some loss to the objective function relative to the exact solution. Thus, the heuristic can offer significant benefits in reducing the run time of the solution algorithm, while finding adaptive strategy solutions that consistently maintain better objective function values compared to the a priori (i.e., non-adaptive) solutions.

A discrete optimisation approach for target path planning whilst evading sensors

In this paper we deal with a practical problem that arises in military mission planning. The problem is to plan a path for one, or more, agents to reach a target without being detected by enemy sensors.Agents are not passive, rather they can initiate actions which aid evasion. They can knockout sensors. Here to knockout a sensor means to completely disable the sensor. They can also confuse sensors. Here to confuse a sensor means to reduce the probability that the sensor can detect an agent.Agent actions are path dependent and time limited. By path dependent we mean that an agent needs to be sufficiently close to a sensor to knock it out. By time limited we mean that a limit is imposed on how long a sensor is knocked out or confused before it reverts back to its original operating state.The approach adopted breaks the continuous space in which agents move into a discrete space. This enables the problem to be formulated as a zero–one integer program with linear constraints. The advantage of representing the problem in this manner is that powerful commercial software optimisation packages exist to solve the problem to proven global optimality. A heuristic for the problem based on successive shortest paths is also presented.Computational results are presented for a number of randomly generated test problems that are made publicly available.

Thermal Resistance of Insulated Precast Concrete Sandwich Panels

Many nations are already working toward full implementation of energy efficiency in buildings known as Green Building. In line with this perspective, this paper aims to develop a thermally efficient precast concrete sandwich panels (PCSP) for structural applications. Therefore, an experimental investigation was carried out to determine the thermal resistance of the proposed PCSP using Hotbox method and the results were validated using finite element method (FEM) in COMSOL Multiphysics Software. The PCSP were designed with staggered shear connectors to avoid thermal bridges between the successive layers. The staggered connectors are spaced at 200 mm, 300 mm and 400 mm on each concrete layer, while the control panel is designed with 200 mm direct shear connection. In the experimental test, four (4) panels of 500 mm × 500 mm and 150 mm thick were subjected to Hotbox Test to determine the thermal resistance. The result shows that thermal resistance of the PCSP with staggered shear connection increases with increase in spacing. The PCSP with 400 mm staggered shear connectors indicates the best thermal efficiency with a thermal resistance (R value) of 2.48 m2K/W. The thermal performance was verified by FEA which shows less than 5% error coupled with a precise prediction of surface temperature gradient. This indicates that, with conventional materials, thermal path approach can be used to develop a precast concrete building with better thermal resistant properties. Hopefully, stakeholders in the green building industry would find this proposed PCSP as an alternative energy efficient load bearing panel towards sustainable and greener buildings.

A Multi-Objective Optimization Approach for Multi-Vehicle Path Planning Problems Considering Human–Robot Interactions

Abstract There has been unprecedented development in the field of unmanned ground vehicles (UGVs) over the past few years. UGVs have been used in many fields including civilian and military with applications such as military reconnaissance, transportation, and search and research missions. This is due to their increasing capabilities in terms of performance, power, and tackling risky missions. The level of autonomy given to these UGVs is a critical factor to consider. In many applications of multirobotic systems like “search-and-rescue” missions, teamwork between human and robots is essential. In this article, given a team of manned ground vehicles (MGVs) and UGVs, the objective is to develop a model that can minimize the number of teams and total distance traveled while considering human–robot interaction (HRI) studies. The human costs of managing a team of UGVs by a MGV are based on human–robot interaction (HRI) studies. In this research, we introduce a combinatorial, multi-objective ground vehicle path planning problem that takes human–robot interactions into consideration. The objective of the problem is to find: ideal number of teams of MGVs-UGVs that follow a leader–follower framework where a set of UGVs follow an MGV and path for each team such that the missions are completed efficiently.

Optimal path planning of autonomous navigation in outdoor environment via heuristic technique

Path planning for automated guided vehicles (AGVs) operating in an outdoor environment is a key task in logistic applications. This paper highlights a new approach for finding collision-free path for AGVs in an outdoor environment using satellite images. Satellite images are transformed into occupancy grids that divide the environment, obstacles (building, trees and pedestrian path etc.,) as black grids and free routes as white grids in order to find an obstacle free path. The proposed navigation control strategy is to localise the AGVs vehicle route until any approaching obstacle is detected and to turn to the safest area before continuing its path. The navigational model was developed in the MATLAB/Simulink 2D virtual environment to visualise the path navigation. Particle swarm optimization and its five variants were used to obtain the obstacle free path. Experiments were conducted in various environments to verify the efficiency and performance of the algorithm. Validation with a bench mark instance ensures that the proposed algorithm found a shorter path with less computation time.

A Framework for Optimizing Green Infrastructure Networks Based on Landscape Connectivity and Ecosystem Services

Optimizing the layout of green infrastructure (GI) is an effective way to alleviate the fragmentation of urban landscapes, coordinate the relationship between urban development and urban ecosystem services, and ensure the sustainable development of cities. This study provides a new technical framework for optimizing GI networks based on a case study of Kaifeng, an exemplar of many ancient cities along the Yellow River in China. To do this, we used a morphological spatial pattern analysis (MSPA) methodology and combined it with Procedure for mAthematical aNalysis of lanDscape evOlution and equilibRium scenarios Assessment (PANDORA) model to determine the hubs of the GI network. Then we employed a least-cost path approach to simulate potential corridors linking the hubs. We further identify the key ‘pinch points’ of the GI network that need priority protection based on circuit theory. Altogether, this framework takes patches that have a high level of ecosystem services and are more important in maintaining overall connectivity as hubs, thereby improving the accuracy of hub identification. Moreover, it establishes a direct connection between GI construction and ecosystem services, and improves biodiversity conservation by optimizing the network structure of GI. The results of the case study show that this framework is suitable for GI planning and construction, and can provide effective technical support for the formulation of urban sustainable development strategies.

Polynomial-Time Construction of Contraction Hierarchies for Multi-Criteria Objectives

In this paper we consider a variant of the multi-criteria shortest path problem where the different criteria are combined in an arbitrary conic combination at query time. We show that contraction hierarchies (CH) — a very powerful speed-up technique originally developed for standard shortest path queries (Geisberger et al. 2008) — can be adapted to this scenario and lead - after moderate preprocessing effort - to query times that are orders of magnitudes faster than standard shortest path approaches. On the theory side we prove via some polyhedral considerations that the crucial node contraction operation during the CH construction can be performed in polynomial-time, while on the more practical side we complement our theoretical results with experiments on real-world data. Our approach extends previous results (Geisberger, Kobitzsch, and Sanders 2010) which only considered the bicriteria case. This is an extended abstract of the full paper published in (Funke and Storandt 2013).

Water diplomacy paths – An approach to recognise water diplomacy actions in shared waters

Water diplomacy is gaining increasing attention among both researchers and policy-makers. The interest is understandable, given that the concept brings together themes such as shifting geopolitics, new types of diplomacy and increasing water scarcity. Yet, there is no common definition for water diplomacy and actual water diplomacy actions typically vary across multiple tracks and scales.In this article, we seek to contribute to the practice of water diplomacy by introducing a step-wise Water Diplomacy Paths approach for analysing different water diplomacy contexts and related water diplomacy actions. To facilitate this, we recognise five key aspects for water diplomacy (Political; Preventive; Integrative; Cooperative; Technical) and propose a general definition for water diplomacy. We also discuss the possible distinctions between the related concepts of water diplomacy and transboundary water cooperation. The use of the Water Diplomacy Paths approach is demonstrated with brief case studies focusing on Central Asia, the Mekong Region, and the Finnish-Russian water cooperation. The work builds on an extensive literature review and comparative analysis of water diplomacy approaches as well as on a series of workshops and interviews among selected water diplomacy actors, including career diplomats.The suggested Water Diplomacy Paths approach envisions possible ways forward through four main steps: 1) identification of key themes and related actors; 2) analysis of the current state, 3) recognition of (undesired) drivers and related scenarios; and 4) identification of possible water diplomacy actions. We see that the approach has potential to support water diplomacy processes with the help of the distinction it makes between water- and diplomacy-focused activities as well as its consideration of tensions and related actions. Such characteristics also emphasise the complementarity that water diplomacy actions have with more traditional transboundary water cooperation arrangements. We argue that water diplomacy as a concept and as a practical approach provides an example of the future of foreign policy and diplomacy, where the use of shared waters is likely to be of increasing importance.

En route to the North: modelling crested porcupine habitat suitability and dispersal flows across a highly anthropized area in northern Italy

The crested porcupine (Hystrix cristata) underwent a rapid and widespread range expansion in Italy. Nowadays the species is moving towards the northernmost regions of the country and its occurrence is increasing in the highly anthropized Po Plain. Our objectives were to evaluate the suitability of the Po Plain for the species, as well as to identify dispersal corridors connecting the northern Apennines occurrence areas and the Prealps. We modelled the species home-range scale habitat suitability based on an ensemble modelling approach. Additionally, a habitat suitability prediction carried out at a finer scale was used to parametrize the landscape resistance, based on which we modelled the potential dispersal corridors for the species using a factorial least-cost path approach. The ensemble prediction estimated a potential occurrence of the crested porcupine in 27.4% of the study area. The species occurrence probability was mainly driven by the distribution of extensive cultivations, woodlands and shrublands, and water courses and by the annual mean temperature. Conversely, the movements of the species resulted mainly sustained by woodlands and shrublands and highly hindered by simple arable lands and rice paddies. The connectivity prediction showed that three main dispersal routes are likely to connect crested porcupine occurrence areas in the northern Apennines to currently unoccupied but highly suitable areas in the Prealps. The study allowed us to identify the areas in the Prealps with the highest probability to be colonized by the crested porcupine in the near future and provided important insights for the conservation of a strictly protected species in a human-dominated landscape.

Electrical transport properties of liquid Pb-Li alloys

It is generally observed that electrical transport properties of simple liquid metal based alloys can be explained well in terms of Faber-Ziman theory, 2kF scattering model and finite mean free path approach. However, these approaches give poor description for materials, which show departure from nearly free electron (NFE) model. Taking Pb-Li as a test case of a system showing departure from NFE (which also exhibit compound formation tendency and disparate mass system), a new technique is proposed to compute electrical transport properties using model potential formalism coupled with t-matrix formulation. We have treated valence number of Pb & Li as a parameter in determining phase shifts. Further, rather than calculating phase shift in terms of Muffin-Tin potential, we have used model potential formalism. Present results suggest that compared to other three theoretical approaches mentioned above, present coupling scheme reproduce qualitative features of electrical transport properties of liquid Pb-Li alloys, which can be used further to study electrical transport properties of similar systems.

Deterministic, random, or in between? Inferring the randomness level of wildlife movements

BackgroundWhen assessing connectivity, it is crucial to rely on accurate modeling frameworks that consider species movement preferences and patterns. One important aspect is the level of randomness or unpredictability in the route selection. In this respect, traditional approaches (based on least-cost path or circuit theory) consider species movements unrealistically as totally deterministic or as totally random. A recent approach (randomized shortest path) advocates for choosing intermediate levels of randomness through a single parameter. This parameter may be optimized by validating connectivity surfaces developed from different levels of randomness against observed movement data. However, connectivity models are seldom validated, and it is still unclear how to approach this task. To address this knowledge gap, this paper aims at comparing different validation methods to infer the optimal randomness level in connectivity studies. Additionally, we aimed to disentangle the practical consequences of applying traditional connectivity approaches versus using an optimized level of movement randomness when delineating corridors.MethodsThese objectives were accomplished through the study case of the Iberian lynx, an endangered species whose maintenance and recovery depend on the current connectivity among its population nuclei. We firstly determined a conductance surface based on point selection functions accounting for the behavioral state (territorial or exploratory) of individuals. Secondly, we identified the level of randomness that better fits lynxes’ movements with independent GPS locations and different validation techniques. Lastly, we delineated corridors between lynx population nuclei through a) the randomized shortest path approach and the extreme and optimal levels of randomness of each validation method, and b) the traditional connectivity approaches.ResultsAccording to all used validation methodologies, models with intermediate levels of randomness outperformed those with extreme randomness levels representing totally deterministic or random movements. We found differences in the optimal randomness level among validation methods but similar results in the delineation of corridors. Our results also revealed that models with extreme randomness levels (deterministic and random walk) of the randomized path approach provided equivalent corridor networks to those from traditional approaches. Moreover, these corridor networks calculated with traditional approaches showed notable differences in patterns from the corridor network calculated with an optimized randomness level.ConclusionsHere we presented a connectivity model with a solid biological basis that calibrates the level of movement randomness and is supported by comprehensive validation methods. It is thus a step forward in the search and evaluation of connectivity approaches that lead to improved, efficient, and successful management actions.

Finding evacuation routes using traffic and network structure information

• Evacuation framework using topology and space-time traffic information is proposed. • The proposed algorithm greatly improves network clearance time during peak times. • Proposed routes ensure seamless evacuations but evacuees must cover long distances. • Properly maintaining central links and boosting connectivity in networks is vital. Given the unpredictable nature of transportation networks, a strategic disaster evacuation plan involving taking detours, which avoids congested and less connected links, is of practical importance. It guarantees the seamless evacuation of evacuees to safe exits while reducing the chance that their safety is jeopardized. This study develops a vehicle evacuation algorithm that employs a link-based centrality metric to dynamically identify agile evacuation paths based on the topological features and the changing spatio-temporal traffic concentration on links within the network. By employing real traffic volume data corresponding to the Yeouido Island’s transport network in Seoul, Korea, we demonstrate that, relative to the conventional shortest path approach, considering the structural and operational features of transport networks using a link-based betweenness centrality measure has a better evacuation performance during high evacuation demand periods by lowering network clearance time. Extensive experimental results, pertinent findings, and recommendations for developing effective evacuation plans are discussed.

Capitalising on water soft paths: new futures for urban communities

ABSTRACT As social artefacts born out of social and economic aspirations and ideologies, the design and application of critical infrastructures can meaningfully engage or alienate the everyday user; be complicit to the extractive economy or facilitate its sustainable extraction and regeneration; and generate outcomes that are productive for local human capital and community development or otherwise. This study applies a “soft path” interpretation of the sociality of water infrastructures in local community contexts. It examines how “water soft paths” – water infrastructures and shared systems intentionally designed to promote sustainable water consumption and production – can be delivered with and through local community participation, and in turn, facilitate community development as well as other socially productive and just outcomes. From a cross-case analysis of five global cases of water soft path implementations, numerous far-reaching benefits of the water soft path approach were discovered. Accruing to it were the attainment of pro-ecological outcomes, human capital creation, community identity building, improved social equity and justice; and multi-agency partnerships. The study thus prompts critical reconsideration of dominant planning philosophies and practice, and proposes a practical approach for instituting creative, user-centric forms of community-level urban planning.

Research on Cold Chain Logistics Distribution Route Based on Ant Colony Optimization Algorithm

The cold chain logistics distribution industry not only demands all goods can be timely distribution but also requires to reduce the entire logistics transportation cost as far as possible, and distribution vehicle route optimization is the key problem of cold chain logistics transportation cost calculation. The traditional optimization method spends a lot of time to search so that it is tough to find the globally optimal path approach, which results in higher distribution costs and lower efficiency. To solve the abovementioned problems, a cold logistics distribution path optimization solution, ground on an improved ant colony optimization algorithm (IACO) is formulated. Specially, other constraints, e.g., the transport time factor, transport cooling factor, and mean road patency factor, can be added to the unified IACO. Meanwhile, the updating mode of traditional pheromone is improved to limit the maximum and minimum pheromone concentration on the road and change the path selection transfer probability. The simulation results and experiment make clear that the IACO algorithm is lower than the chaotic-simulated annealing ant colony algorithm (CSAACO) and the traditional ACO algorithm in terms of convergence speed, logistics transportation distance, and logistics delivery time. At the same time, we have successfully obtained the optimal logistics distribution path, which can provide valuable reference information for improving the economic benefits of cold chain logistics enterprises.

Option pricing models without probability: a rough paths approach

AbstractWe describe the pricing and hedging of financial options without the use of probability using rough paths. By encoding the volatility of assets in an enhancement of the price trajectory, we give a pathwise presentation of the replication of European options. The continuity properties of rough‐paths allow us to generalize the so‐called fundamental theorem of derivative trading, showing that a small misspecification of the model will yield only a small excess profit or loss of the replication strategy. Our hedging strategy is an enhanced version of classical delta hedging where we use volatility swaps to hedge the second‐order terms arising in rough‐path integrals, resulting in improved robustness.

Online flight path planning with flight time constraints for fixed-wing UAVs in dynamic environments

PurposeA major challenge for mission planning of aircraft is to generate flight paths in highly dynamic environments. This paper presents a new approach for online flight path planning with flight time constraints for fixed-wing UAVs. The flight paths must take into account the kinematic restrictions of the vehicle and be collision-free with terrain, obstacles and no-fly areas. Moreover, the flight paths are subject to time constraints such as predetermined time of arrival at the target or arrival within a specified time interval.Design/methodology/approachThe proposed flight path planning algorithm is an evolution of the well-known RRT* algorithm. It uses three-dimensional Dubins paths to reflect the flight capabilities of the air vehicle. Requirements for the flight time are realized by skillfully concatenating two rapidly exploring random trees rooted in the start and target point, respectively.FindingsThe approach allows to consider static obstacles, obstacles which might pop up unexpectedly, as well as moving obstacles. Targets might be static or moving with constantly changing course. Even a change of the target during flight, a change of the target approach direction or a change of the requested time of arrival is included.Originality/valueThe capability of the flight path algorithm is demonstrated by simulation results. Response times of fractions of a second qualify the algorithm for real-time applications in highly dynamic scenarios.

Educational reconstructions of quantum physics using the sum over paths approach with energy dependent propagators

Moving from the research tradition on the use of Feynman’s sum over paths approach in education, we have developed an educational reconstruction of elementary quantum physics which uses Feynman paths at fixed energy and is capable of a simple conceptual explanation of discrete energy levels in bound systems. The reconstruction has been found to offer several educational advantages, may help students think of quantum physics in a way more akin to how the subject is used by scientists, and allows to shed light on the relationship between energy and time.

A Convergence Analysis on the Investment Development Path Approach

Gelişmiş ve gelişmekte olan ülkelere ait yatırım gelişme yolu eğrilerinin 1970-2018 döneminde yakınsama davranışı gösterip göstermediğinin incelendiği bu çalışmanın iki temel amacı bulunmaktadır. Bunlardan birincisi, yatırım gelişme yolu yaklaşımından hareketle küreselleşme sürecinin temel araçlarından olan doğrudan yabancı sermaye yatırımlarının ülkeler arasındaki gelişmişlik farklılıklarını ortadan kaldırıp kaldırmadığını analiz etmektir. İkincisi ise, son dönemlerde geliştirilen doğrusal olmayan birim kök testlerini kullanarak, yatırım gelişme yolu eğrilerinin yakınsama davranışının ortaya çıkan makroekonomik şoklardan etkilenip etkilenmediğini araştırmaktır. Elde edilen bulgular, söz konusu ülkelerin yatırım gelişme yolu eğrilerinin doğrusal olmayan bir yapıda yakınsama davranışı sergilediğini ve dolayısıyla yakınsama sürecinin makroekonomik şoklardan etkilendiğini göstermektedir.

On Solving Transportation Problem – Linear Path Approach

Aim of this study is to determine the optimal cost for the given rectangular (or) square grid corresponding transportation problem along with balanced and unbalanced manner. We proposed the algorithmic way to provide cost from supply to the corresponding demand of the transportation problem in graph theoretical way to obtain minimum cost than the existed method in Operation Research. The proposed research brings out anoptimal basic feasible solution derived through graph theoretical method. It provides more than hundred percentage matching with so called existed method’s optimal basic feasible solution.