Mobile Path Research Articles

IMOC: Optimization Technique for Drone-Assisted VANET (DAV) Based on Moth Flame Optimization

Technology advancement in the field of vehicular ad hoc networks (VANETs) improves smart transportation along with its many other applications. Routing in VANETs is difficult as compared to mobile ad hoc networks (MANETs); topological constraints such as high mobility, node density, and frequent path failure make the VANET routing more challenging. To scale complex routing problems, where static and dynamic routings do not work well, AI-based clustering techniques are introduced. Evolutionary algorithm-based clustering techniques are used to solve such routing problems; moth flame optimization is one of them. In this work, an intelligent moth flame optimization-based clustering (IMOC) for a drone-assisted vehicular network is proposed. This technique is used to provide maximum coverage for the vehicular node with minimum cluster heads (CHs) required for routing. Delivering optimal route by providing end-to-end connectivity with minimum overhead is the core issue addressed in this article. Node density, grid size, and transmission ranges are the performance metrics used for comparative analysis. These parameters were varied during simulations for each algorithm, and the results were recorded. A comparison was done with state-of-the-art clustering algorithms for routing such as Ant Colony Optimization (ACO), Comprehensive Learning Particle Swarm Optimization (CLPSO), and Gray Wolf Optimization (GWO). Experimental outcomes for IMOC consistently outperformed the state-of-the-art techniques for each scenario. A framework is also proposed with the support of a commercial Unmanned Aerial Vehicle (UAV) to improve routing by minimizing path creation overhead in VANETs. UAV support for clustering improved end-to-end connectivity by keeping the routing cost constant for intercluster communication in the same grid.

An interference-tolerant fast convergence zeroing neural network for dynamic matrix inversion and its application to mobile manipulator path tracking

In this paper, a new interference-tolerant fast convergence zeroing neural network (ITFCZNN) using a novel activation function (NAF) for solving dynamic matrix inversion (DMI) is presented and investigated. Compared with the original zeroing neural network (OZNN) models, the proposed ITFCZNN not only has the ability to converge to 0 within a fixed-time, but also resist different types of interference and noises in solving DMI problems. Besides, detailed mathematical analysis of convergence and robustness of the ITFCZNN are provided. Comparative numerical simulation verifications of the new ITFCZNN and the OZNN activated by other commonly used activation functions (AF) are also provided to demonstrate the better robustness, effectiveness and fixed-time convergence of the ITFCZNN. In addition, a mobile manipulator path tracking application example is given to verify the applicability and feasibility of the ITFCZNN with interference and noises. Both of the theoretical analysis and numerical simulation results verify the effectiveness and robustness of the ITFCZNN model.

Structural, optical and electrical transport properties of Sn doped In2O3

Present study focuses on the structural, morphological, optical and electrical transport properties of Sn substituted In2O3 (In2-x SnxO3; 0.0 ≤ x ≤ 0.25) synthesized by solid state reaction method. X-ray diffraction patterns and selected area electron diffraction from high resolution transmission electron microscopy substantiated the pure cubic bixbyite structure with high crystallinity. Raman analysis confirmed the cubic like phonon modes in each sample and their noticeable phase was revealed by the presence of tin doping. The band gap widening of all nanocrystalline samples were well explained by Burstein-Moss model, due to the filling of the strongly dispersing conduction band by doped electrons and the decrease in oxygen vacancies were confirmed by deconvoluted emission spectra. Hall measurements showed the n-type conductivity with low electrical resistivity (1.3011×10−4Ω-cm) along with high carrier concentration (7.523×1020cm−3), mobility (63.85 cm2/V-s) and electron mean free path (11.183 nm) for x = 0.1, optimizing it as a suitable candidate for optoelectronic applications.

A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks.

Decoding the Hidden Curriculum: Latino/a First-Generation College Students’ Influence on Younger Siblings’ Educational Trajectory

ABSTRACT Past research demonstrates that familial and community support can aid the academic success of Latino/a students. However, few studies explore how older siblings influence their younger siblings’ education trajectory including primary, secondary, and post-secondary education. Drawing on 25 in-depth interviews with Latino/a first-generation college students at a large research university in Southern California, I find that older siblings assist their younger family members by (a) choosing schools, (b) assisting with reading comprehension, (c) helping with homework assignments, and (d) post-high school preparation. In doing do, they demystify norms and rules about education and attempt to position their loved ones on a path of upward mobility. I capture the labor Latino/a children of immigrants provide to their families and how these contributions can result in tensions between parents and children. Findings advance scholarship on intra-immigrant family brokering, Latino/a families, and education.

Time-space constraints to HIV treatment engagement among women who use heroin in Dar es Salaam, Tanzania: A time geography perspective.

Timely initiation and sustained adherence to antiretroviral therapy (ART) are essential to improving the health outcomes of people living with HIV and preventing onward HIV transmission. However, women who use heroin often face challenges to initiating and adhering to ART. In this paper we identify spatial, temporal, and social factors that affect HIV treatment engagement among women who use heroin, drawing from a time geography framework. We conducted in-depth interviews with 30 heroin-using women living with HIV in Dar es Salaam, Tanzania between January and March 2019. We found that unstable housing, high mobility, HIV-related stigma, and unpredictable daily paths due to heroin use and involvement in sex work spatially and temporally constrained women who use heroin from incorporating HIV treatment behaviors into daily routines. Some women, however, were able to overcome these time-space constraints to HIV treatment engagement through social support and social role performance. Time geography, including concepts of time-space constraints and daily paths, is a useful framework for identifying barriers to ART engagement. Structural, relational, and individual interventions aimed at eliminating time-space constraints hold the potential to improve HIV treatment engagement among particularly vulnerable and mobile populations.

Health equity considerations in COVID-19: geospatial network analysis of the COVID-19 outbreak in the migrant population in Singapore.

BackgroundLow-wage dormitory-dwelling migrant workers in Singapore were disproportionately affected by coronavirus disease 2019 (COVID-19) infection. This was attributed to communal living in high-density and unhygienic dormitory settings and a lack of inclusive protection systems. However, little is known about the roles of social and geospatial networks in COVID-19 transmission. The study examined the networks of non-work–related activities among migrant workers to inform the development of lockdown exit strategies and future pandemic preparedness.MethodsA population-based survey was conducted with 509 migrant workers across the nation, and it assessed dormitory attributes, social ties, physical and mental health status, COVID-19-related variables and mobility patterns using a grid-based network questionnaire. Mobility paths from dormitories were presented based on purposes of visit. Two-mode social networks examined the structures and positions of networks between workers and visit areas with individual attributes.ResultsCOVID-19 risk exposure was associated with the density of dormitory, social ties and visit areas. The migrant worker hub in the city centre was the most frequently visited for essential services of grocery shopping and remittance, followed by south central areas mainly for social gathering. The hub was positioned as the core with the highest degree of centrality with a cluster of workers exposed to COVID-19.ConclusionsSocial and geospatial networks of migrant workers should be considered in the implementation of lockdown exit strategies while addressing the improvement of living conditions and monitoring systems. Essential services, like remittance and grocery shopping at affordable prices, need to be provided near to dormitories to minimize excess gatherings.

GHG emissions from the transport sector in Oman: Trends and potential decarbonization pathways

The Gulf Cooperation Council, despite being the home for the world's largest oil and gas reserves and the highest per capita GDP, the Greenhouse Gas emissions from transportation remain poorly understood, and a missing piece in the puzzle of reduction policies. This paper uses Oman as a Gulf Cooperation Council Countries representative model, with a transport-fuel policy to reveal carbon growth from the transportation sector and to examine feasible paths for carbon-neutral mobility. This study uses IPCC guidelines and methodology of 2006 for the assessment of the GHG emissions trends of transportations modes from 2000 to 2015. The results of the analysis indicating that the share of transport emissions in Oman's total GHG emissions has doubled from 8.1% in 2000 to 16.3% in 2015. Transportation emissions became the third larger contributor to overall greenhouse gas emissions in Oman, after the oil and natural gas (26%) and energy industries (20%). Road transport is the biggest contributor to transport sector emissions, and their contribution to total transport emissions increased from 66% in 2000 to 92% in 2015. Carbon emission from the transportation sector will continue to grow steadily due to the high demand for transportation by a growing population. The cheap availability of fuel and affordable car costs, given the limited public transport, will persist as driving factors of the ongoing rise in carbon emission from transportation. Therefore, curbing emission from the Omani transportation system should take place in the socio-economic context of the country through phasing out the fuel subsidies system, developing a reliable public transport system, planning for the electrification of road transportation, and using rail for freight transportation.

Path Tracking Simulation of a Wheeled Mobile Robot with Three Mecanum Wheels

This paper presents a study of wheeled mobile robot WMR path tracking by presenting the kinematic model of holonomic wheeled mobile robot with three mecanum controlled wheels. The advantage of mecanum wheels usage is to make the mobile robot movement in lateral and longitudinal directions smooth and to improve the tracking ability to travel in every direction under any orientation. This proposed type of WMR has three actuated input coordinates (angular velocities of the mecanum wheels) and three generalized output coordinates (robot linear translation along x, y axes and the robot orientation). The kinematic models of the WMR are based on a functional relation among configuration variables and their derivatives. It is a known fact that the WMR poses can be achieved in the configuration space but the path to reach these poses has complex step in the consideration. The mobility capability in the proposed design of WMR makes it suitable for different types of applications. The contribution in this work is the initiative to obtain the mathematical models of inverse and forward kinematics in order to analyze a new design of WMR with three mecanum wheels to simplify the task implementation of the robot by obtaining the suitable path to reach the mobile robot target. It has been taken in consideration that, the WMR motion is assumed as a pure rolling without any slipping. Simulation example results presented in this work show the proposed control algorithm applied on two different cases of path tracking (circular path, infinity path) and the effect of WMR wheels angular velocities on the robot body velocities and robot position errors. The results show a good performance in minimizing the positioning errors during the implementation of its task.

A Hierarchical Motion Planning for Mobile Manipulator

This paper focuses on motion planning for mobile manipulators that can be used to plan both the base and the manipulator. An Optimized Hierarchical Mobile Manipulator Planner (OHMP) is proposed, which consists of two phases: two‐dimensional mobile base path planning and three‐dimensional manipulator trajectory planning. In the two‐dimensional mobile base path planning phase, a hybrid sampling strategy combining bridge test and uniform sampling is adopted to optimize Probabilistic Roadmap‐based basic planning and improve the efficiency of overall planning. In the three‐dimensional manipulator trajectory planning phase, if the current manipulator configuration is in a collision state, then a secure configuration is searched, and the trajectory between them is planned. Given start and goal configurations, the OHMP can efficiently produce a collision‐free path in complex environments. The estimates are backed up by the experiment result. It proves the validity and rationality of the planner, and it is effective for motion planning in complex static environments. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

GeoHash tag based mobility detection and prediction for traffic management

User mobility detection and prediction can help in many ways for planning and monitoring a population distribution and displacement in a specific area or location. It also helps in planning for resource distribution and allocation. In this paper, we present a study on the mobility of the population which can be monitored by sensors, GPS devices through location detection. All the public transports like buses, taxis, etc. have GPS devices posted that can provide movement of a vehicle in city traffic. For experimental analysis, the T-Drive Taxi Trajectories dataset was selected, in which taxi location data are collected with the information of taxi ID, timestamp, latitude, and longitude. GeoHash tags were generated for the location of a taxi based on latitude and longitude. A graph was built based on vertices as GeoHash tag and edges as a direct link between the GeoHash tags. Graph-Based data analysis was applied to identify the importance of GeoHash tag based on the in-degree and PageRank of the vertices. The mobility path and movement of traffic can be predicted that can be used for disaster management and urban development for city planning.

Edge Computing through Virtual Force for Detecting Trustworthy Values

As the advancement of IoT (Internet of Things) and other emerging mobile application continues, it is an accepted fact that Edge Computing paradigm is considered to be the best fit in terms of fulfilling the resource requirements. Moreover, it is a fact that the data collected by the sensor networks serves as the base for the IoT applications as well as the systems. However, due to advancement in cybercrimes, there is a possibility that the data collected through the sensor networks are vulnerable to attacks which may result in serious consequences. The proposed work focuses on a new model which is used to gather trustworthy data using edge computing in IoT. In order to get the accurately quantified trust values, the sensor nodes are analyzed and found from different dimensions. Moreover, with the help of trust value obtained, it is possible to find the best mobility path which carries the highest value of trust. This data is gathered from the sensors with the help of mobile edge data collector. This analysis shows that for a trustworthy data collection model of IoT, there is noticeable improvement in terms of energy conservation and system security, thereby improving the performance of the system.

Diálogo con el 'Manifiesto por una pedagogía post-crítica' desde la esperanza como acción social transformadora

El objetivo de este artículo es el análisis del Manifiesto por una Pedagogía Post-crítica, publicado por Hodgson, Vlieghe y Zamojski en el año 2017. Este manifiesto anuncia cinco principios que impulsan a la pedagogía post-crítica hacia una redefinición de los marcos de la educación y la formación. Presentamos acuerdos y desacuerdos respecto a estos cinco principios en base a la siguiente creencia: resulta necesario superar la reducción de la educación a una vía de adaptación y/o movilidad social, ya que la finalidad última de la pedagogía post-crítica debe ser profundizar en el desarrollo del sujeto pedagógico. El resultado de la investigación nos permite abogar por una pedagogía que, sujeta a la realidad y a lo que las cosas son, se erija en «una meta-en-sí», habilitada para analizar y reubicar las posibles instrumentalizaciones. Esto nos lleva a demandar una reformulación de lo social y lo político en tanto reclamo y revelación de ciertas distorsiones existentes, pero también en tanto intersección que aglutina los retos de la pedagogía. Se llega a la conclusión de que, a partir de una hermenéutica que vaya más allá del contraste entre comprensión y explicación, la esperanza puede brindarnos la oportunidad de conseguir que ciertas oportunidades y algunos retos sociales conviertan a las utopías en compromisos. Y lo hacemos porque concebimos la esperanza como una actitud generadora de transformaciones y como una aspiración articuladora de acciones humanas, no como un recurso quimérico que pretenda evitar la concreción de las directrices profesionales normativas que atañen a la pedagogía.

A mobile sink path planning for wireless sensor networks based on priority‐ordered dependent nonparametric trees

SummaryThe professional design of the routing protocols with mobile sink(s) in wireless sensor networks (WSNs) is important for many purposes such as maximizing energy efficiency, increasing network life, and evenly distributing load balance across the network. Moreover, mobile sinks ought to first collect data from nodes which have very important and dense data so that packet collision and loss can be prevented at an advanced level. For these purposes, the present paper proposes a new mobile path planning protocol by introducing priority‐ordered dependent nonparametric trees (PoDNTs) for WSNs. Unlike traditional clustered or swarm intelligence topology‐based routing methods, a topology which has hierarchical and dependent infinite tree structure provides a robust link connection between nodes, making it easier to reselect ancestor nodes (ANs). The proposed priority‐ordered infinite trees are sampled in the specific time frames by introducing new equations and hierarchically associated with their child nodes starting from the root node. Hence, the nodes with the highest priority and energy that belong to the constructed tree family are selected as ANs with an opportunistic approach. A mobile sink simply visits these ANs to acquire data from all nodes in the network and return to where it started. As a result, the route traveled is assigned as the mobile path for the current round. We have performed comprehensive performance analysis to illustrate the effectiveness of the present study using NS‐2 simulation environment. The present routing protocol has achieved better results than the other algorithms over various performance metrics.

Edge-Computing-Based Trustworthy Data Collection Model in the Internet of Things

It is generally accepted that the edge computing paradigm is regarded as capable of satisfying the resource requirements for the emerging mobile applications such as the Internet of Things (IoT) ones. Undoubtedly, the data collected by underlying sensor networks are the foundation of both the IoT systems and IoT applications. However, due to the weakness and vulnerability to attacks of underlying sensor networks, the data collected are usually untrustworthy, which may cause disastrous consequences. In this article, a new model is proposed to collect trustworthy data on the basis of edge computing in the IoT. In this model, the sensor nodes are evaluated from multiple dimensions to obtain accurately quantified trust values. Besides, by mapping the trust value of a node onto a force for the mobile data collector, the best mobility path is generated with high trust. Moreover, a mobile edge data collector is used to visit both the sensors with quantified trust values and collect trustworthy data. The extensive experiment validates that the IoT systems based on trustworthy data collection model gain a significant improvement in their performance, in terms of both system security and energy conservation.

Generating optimal path by level set approach for a mobile robot moving in static/dynamic environments

According to the analogy between the mobile robot navigation path and the heat transferring path under steady state, the robot path planning problem during navigation is converted into identify the heat transferring path that minimizes the thermal compliance across the analysis domain. A new path planning approach which combines the concept of growth simulation and level set based heat conduction topology optimization framework is adopted to determine the heat transferring path. By introducing the concept of growth simulation, the proposed approach could calculate a few steps of the navigation path, which is of great significance for online reactive navigation. The proposed approach could avoid local minima and search for the optimal growth orientation freely without constraints from background mesh since the inherent characteristics of heat conduction and the level set approach, respectively. A new reactive navigation algorithm based on the proposed path planning approach and the concept of temporarily safe path is proposed to navigate the mobile robot from the start point to the goal point in unknown dynamic environment with static and dynamic obstacles. Diverse simulation cases are carried to illustrate the effectiveness of the reactive navigation algorithm.

Data Collection Method of Large Scale WSNS Mobile Node Based on Compressed Sensing and Intelligent Optimization

Aiming at the defects of large-scale large scale wireless sensor network data processing network traffic and high task latency, a data collection scheme of mobile node based on discrete elastic collision optimization algorithm and adaptive block compression sensing is proposed. Firstly, by analyzing the relationship between the network partitioning and the node deployment, an adaptive block compressed sensing data collection strategy is proposed to realize sensor node based on adaptive network block compressed sensing data collection. Designing mobile node data acquisition path planning strategy and multiple mobile nodes The collaborative computer system adopts the fitness value constraint transformation processing technology and the parallel discrete elastic collision optimization algorithm to achieve the purpose of balancing network node energy consumption and reducing data processing task delay. Finally, the simulation results show that the data collection scheme can effectively realize high-efficiency processing of large-scale sensor network data, and reduce network traffic and network task delay, and better balance network node energy consumption.

Trayectorias de movilidad residencial y cuidado en casa de ancianos pobres urbanos

El objetivo es identificar los tipos de movilidad residencial entre los ancianos pobres urbanos con base en los espacios de cuidado en la casa donde residen. Los datos provienen de dos estudios etnográficos en Guadalajara, México, con 40 ancianos pobres urbanos. Se analiza la casa como un espacio de cuidado a partir de las características físicas y el uso del espacio doméstico, y las relaciones familiares en su interior para identificar los tipos de movilidad residencial. Cuatro trayectorias de movilidad residencial muestran las circunstancias para la inclusión o exclusión del cuidado en casa y la movilidad residencial entre la casa y el asilo.

Random waypoint mobility and two-ray path loss model to analyse multiple routing protocols in mobile ad hoc networks

Random waypoint mobility and two-ray path loss model to analyse multiple routing protocols in mobile ad hoc networks

Assessing multimodal mobility trends using heterogeneous data sources: a case study for supporting sustainable policy goals within the region of Algarve

This paper is built around a research project developed with the support of the Regional Planning Authority of the Algarve Region in Portugal which assessed mobility patterns covering all modes of transport using heterogeneous data sources (time-series data). Data mining techniques helped to identify limitations in some data sets. The econometric analysis showed that integrated autoregressive models and moving averages for series with seasonality were successful in the prediction of passenger flows using time-series data gathered by the regional authority from transport operators and other entities.Results from the analysis are useful to support a strategy to reverse current trends on continued car growth (along with public transport decrease) and to devise policy measures to enable a sustainable mobility path towards decarbonisation and social equity goals until 2030.