Mobility Model Research Articles

Enhanced Authentication Scheme for Mobility Model in Medical Wireless Sensor Networks

The advent of wireless sensor networks has brought significant advancements in healthcare, enabling remote interactions between medical professionals and patients. However, ensuring the security of communication in Medical Wireless Sensor Networks (WSNs) poses different challenges. To address this, this paper introduces a novel authentication framework designed for doctors and patients. The proposed mechanism incorporates essential features such as mutual authentication, anonymity, and data integrity, safeguarding the Medical Wireless Sensor Networks (MWSN). Symmetric encryption techniques are employed to maintain the overall security of the system.

Mobilization Of Political Protest In The Russian Segment Of Social Media (2021): Triggers, Audience, Communication Channels

The article presents the results of applied political research, the purpose of which is to determine the scale, mobilization potential, social base, and digital communication technologies of protest-oriented information flow in the Russian segment of social media on the eve of the Single Voting Day of 2021. The cognitive mapping implemented in the study made it possible to identify the meaningful characteristics of the information flow. The social media analysis made it possible to determine the dynamic and structural characteristics of the information flow, the gender and age specifics of the users involved in it, as well as quantitative characteristics of the activity of key communities forming protest information flows. The method of social graphs revealed the structure of interaction between the opposition and protest communities of Telegram in 2021. The event analysis carried out during the study made it possible to fix the key peaks of growth in the dynamics of user activity around protest events and discourses. On this basis, it was possible to identify the triggers used to involve users in protest information flows (elections, law enforcement agencies, vaccination, socio-economic problems), typologize the communities forming the protest information flow (protest aggregator communities, news aggregator communities, local analytics communities), and model of mass protest mobilization (primary trigger — secondary trigger — offline protest).

UAV‐SHUTTLE‐MMM: UAV‐shuttle‐enabled mobility management model in sparsely deployed flying ad hoc networks

SummaryThe reliable surveillance of a large region typically needs a large number of unmanned aerial vehicles (UAVs), which leads to high operational costs in flying ad hoc networks (FANETs). Therefore, the UAV mobility model plays an important role that affecting the performance of FANET. This research paper comes up with a novel UAV‐shuttle‐enabled mobility management model (US‐MMM) that is a crucial attribute for the large and highly sparse network. The proposed mobility model uses UAV shuttles. A relatively lesser number of UAVs are used than comparative approaches to enhance the connectivity among the UAVs in a sparse network. UAV shuttle is the special self‐governing node, which traverses the network and collects the data to deliver to the base station (BS). The main strength of the proposed mobility model is the self‐governing ability of the UAV shuttle, which leads to high connectivity in the network. The UAV shuttle executes the proposed dynamic path planning algorithm and uses the adaptive ranking algorithm to determine its target. The main contribution of this research work is to develop a subnet scan and Number of Neighbor and Distance‐based Adaptive Ranking of Targets (NN‐DART) algorithm for dynamic route planning of UAV shuttle. The proposed mobility model is used with various routing schemes to check the difference in the performance of various routing schemes. The proposed mobility model is simulated in NS‐2.35, and the results have shown an improvement in the packet delivery ratio, routing overhead, and end‐to‐end delay.

Statistical inference for complete and incomplete mobility trajectories under the flight-pause model.

We formulate a statistical flight-pause model (FPM) for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. We develop the statistical machinery for parameter inference and trajectory imputation under various forms of missing data. We show that common assumptions about the missing data mechanism for MPT are not valid for the mechanism governing the random motions underlying the FPM, representing an understudied missing data phenomenon. We demonstrate the consequences of missing data and our proposed adjustments in both simulations and real data, outlining implications for MPT data collection and design.

Moving far or moving often? A neglected axis of variation in hunter-gatherer mobility

As one of the hallmarks of a hunting and gathering lifestyle, mobility is a primary concern for both archaeologists and ethnographers studying hunter-gatherer settlement systems. Most research considering hunter-gatherer mobility, however, concentrates primarily on the total distance moved by a group per annum. This paper develops a novel metric, the Distance/Frequency Index (DFI), which describes a continuum between relatively frequent, short moves and relatively infrequent, long moves, and is derived to be orthogonal to total distance moved per annum. Multiple regressions of the DFI on a series of important demographic, social, and economic variables demonstrate that it correlates positively with population density and negatively with group size, percentage hunting in the diet, mean annual precipitation, and effective temperature. Analyses of a more recently collated subset of these data suggest that the correlations with group size and effective temperature are particularly robust. The DFI can also be related to a number of measures of occupation intensity and duration derived from archaeological assemblages, and to existing models of residential and logistical mobility. The DFI thus provides a valuable second axis of variation in hunter-gatherer mobility.

Cognitive-Radio-Based Resource Management for Smart Transportation: A Sliding Mode Control Approach

Smart transportation is one of the key components of the smart city. A significant amount of data is produced by the numerous vehicles connected via wireless networks. This demands smart spectrum management for efficient data communication. The optimal bandwidth usage can be obtained by opportunistically sharing the spectrum among high-priority class primary and low-priority class secondary users’ vehicles. In this study, we develop a mathematical model to ensure effective resource allocation in Cognitive Radio based Smart Transportation Networks (CR-STN) considering the mobility, bandwidth constraint and interference models. Robust sliding mode control is synthesized using an exponential reaching law to avoid data packet congestion in CR-STN to ensure smart spectrum management. In addition, a dynamic event-triggered mechanism is incorporated with the sliding mode controller to reduce computational complexity and energy expenses. The effectiveness of the suggested controller has been validated by simulation results.

Resource allocation and OFDM system transmission for 5G cellular communications

Cellular communication technology has been developed for over a hundred years and has reached its fifth generation in mobile. 5G, as a new generation of communication technology, has comprehensively changed the mobile network application model with its ability of high-speed transmission, low network latency, and large-scale connectivity. It has brought a new impetus to the development of various industries. Cellular communication uses cellular wireless networking to connect terminals and network devices through wireless channels so that users can communicate with each other during their activities, with the main feature being the mobility of the terminals and the automatic roaming process across local networks. The use of OFDM in 5G communications can significantly improve the efficiency and capacity of wireless signal transmission. This paper provides a detailed introduction to the use of OFDM in cellular communications through frequency division multiplexing and OFDM.

Meet the authors: Yong Chen, Xiqun (Michael) Chen, and Ziyou Gao

In their recent publication in Patterns, the authors proposed a novel multi-scale unified mobility model to capture the universal-scale laws of individual and population movement within urban agglomerations. This People of Data highlights the contributions of their work to the field and the critical role data science plays in research and the research community.

Changes in mobility patterns during the COVID-19 pandemic in Zambia: Implications for the effectiveness of NPIs in Sub-Saharan Africa.

The COVID-19 pandemic has impacted many facets of human behavior, including human mobility partially driven by the implementation of non-pharmaceutical interventions (NPIs) such as stay at home orders, travel restrictions, and workplace and school closures. Given the importance of human mobility in the transmission of SARS-CoV-2, there have been an increase in analyses of mobility data to understand the COVID-19 pandemic to date. However, despite an abundance of these analyses, few have focused on Sub-Saharan Africa (SSA). Here, we use mobile phone calling data to provide a spatially refined analysis of sub-national human mobility patterns during the COVID-19 pandemic from March 2020-July 2021 in Zambia using transmission and mobility models. Overall, among highly trafficked intra-province routes, mobility decreased up to 52% during the time of the strictest NPIs (March-May 2020) compared to baseline. However, despite dips in mobility during the first wave of COVID-19 cases, mobility returned to baseline levels and did not drop again suggesting COVID-19 cases did not influence mobility in subsequent waves.

Examination of Wireless Body Area Network Using Mobile Sinks

In the last few years, postural mobility has been seen as a significant barrier to the successful deployment of Wireless Body Area Networks (WBAN), and several mobility models have been put out to overcome this problem. Due to the sink node's fixed location in such topologies, WBAN performance was declining. The domains of other wireless networks including MANET, VANET, and FANET have successfully used Mobile Sink as a solution. The network lifespan and other QoS metrics like average end-to-end latency, PDR, throughput and energy consumption are significantly influenced by sink mobility. The random movement of the sink node is taken into account in this study effort to cope with the heterogeneity of network nodes and their movement pattern. Static and mobile sinks (Controlled and Random movements) are used to test both mobility models using Network Simulator NS2.35, and it was shown that mobile sinks improved WBAN performance for all QoS criteria.

An analytical model and experimental validation of annular heat source during scanning electron beam treatment

In this investigation, the maximum depth of penetration and power density coefficient are calculated by simulating the motion trajectories of electrons in surface layer of 5CrNiMo steel using Monte Carlo method, and the number of electrons is 500,000 in simulation. Then tomographic calculation is used to determine the distribution of power density coefficient on the section perpendicular to electron incidence direction, and a Gaussian columnar heat source model that matches the properties of electron beam is established. Finally, a mobile annular heat source model of scanning electron beam is then derived, combining it with the real operating mode. The temperature field during surface modification is simulated by using the mobile annular heat source model, and the simulation findings are compared to experimental data. The findings of Monte Carlo simulation demonstrate that the power density coefficient is Gaussian distributed on the section perpendicular to the depth of electron incidence and the peak power density at the center of each section changes with depth. The thickness and microstructure of re-melting layer predicted from the temperature field simulation is very close to the one from experimental findings. In our investigation, on top of deriving a model for the heat source of a single beam spot, we have also solved the problem of mathematical representation of the beam spot when it is doing high-speed rotational and linear composite motions. The aforementioned findings demonstrate that our study can provide methodological references for the construction of heat source models for different materials during electron beam treatment.

Specific Absorption Rate and Temperature Distributions in the Human Head with Implanted Deep Brain Stimulation Subjected to Mobile Phone Electromagnetic Radiation

Deep Brain Stimulation (DBS), also known as the brain pacemaker, has gradually evolved from a scientific experiment into an effective clinical treatment for movement disorders as a method of improving movement disorders. At present, there are few studies on the effects of 5G mobile phone antenna radiation on the heads of adult patients implanted with DBS. In this study, COMSOL Multiphysics was used to establish a mobile phone model with a 5G/4G patch antenna, a real human head, and the DBS models. Then, we calculated the specific absorption rate (SAR) of various layers of the head tissues with the mobile phone at different distances from the human head, as well as the temperature change rule of the head and the DBS irradiated by the antenna for 30 min. The simulation results showed that when the frequency is 3500 MHz, the electromagnetic radiation of the phone to the patient’s head is generally greater than that of the 2400 MHz. When at 3500 MHz, the distance between the phone and the head is inversely proportional to the SAR value; thus, when the distance between the phone and the head is 1 cm, the maximum SAR value—which is 1.132 W/kg—appeared in the skin layer of the head with implanted DBS. But it is worth noting that the largest temperature rise appeared in the brain layer at 2400 MHz and at a distance of 1 cm, which is 0.2148 °C. Although the SAR values and temperature rise obtained from all simulations are below the limits of 2 W/kg and +1 °C specified by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), we still recommend that patients with implanted DBS maintain a distance when using the phones.

Transforming transnational intercultural sensitivity for midwifery students through an inclusive mobility model (TOTEMM)

Transforming transnational intercultural sensitivity for midwifery students through an inclusive mobility model (TOTEMM)

Identifying the Components of Mobile Value-Added Services in Health: A Qualitative Approach

Background. Considering the widespread influence of mobile phones in life and its various features, it is necessary to use value-added services of mobile phones in the field of treatment and health. This study aimed to identify and categorize the factors affecting the use of mobile value-added services in the field of health. Methods. This qualitative research was conducted using thematic analysis. A total of 74 articles were extracted from scientific databases. Next, 51 related articles were fully reviewed using thematic analysis method. After that, basic, organizing, and inclusive themes were extracted, and the model was implemented. Validity of the research was confirmed by experts according to the degree of connection between the components and the mobile value-added services model in the field of health. The reliability coefficient was 97%, which indicated a high reliability. Results. Based on the review and analysis of the articles, the final model consisted of 64 basic themes, 16 organizing themes (understanding benefits, understanding well-being, user values, customer outcomes, community outcomes, organizational outcomes, technology infrastructure, reducing fear of technology, learning and development, occupational factors, support and incentives, technical reliability, human reliability, risk reduction, attitude, and expectation), and six global themes (user understanding, effects and consequences, technology development, environmental influencing conditions, reliability, and mindset and expectations). Conclusion. According to the factors identified in this research, policy makers and health managers can have the right planning for the use of mobile value-added services in the field of health.

Assisted Car Platooning and Congestion Control at Road Intersections

Enhancing road safety and traffic efficiency are the important aspects and goals that automakers and researchers trying to achieve in recent years. The autonomous vehicle technology has been identified as a solution to achieve these goals. However, the adoption of fully autonomous vehicles in the current market is still in the very early stages of deployment. The objective of this paper is to develop a Cooperative Adaptive Cruise Control (CACC) model at a road intersection using platooning car-following mobility models, object detection at traffic light units, and Vehicle-to-Everything (V2X) communication through vehicular ad hoc networks (VANETs). The mobility model considers traffic simulation using the SUMO-PLEXE-VEINS platforms integration. Next, a prototype of an assisted car platooning system consisting of roadside unit (RSU) and on-board units (OBU) is developed using artificial intelligence (AI)-based smart traffic light for obstruction detection at an intersection and modified remote-control cars with V2X communication equipped with in-vehicle alert notification, respectively. The results show accurate detection of obstruction by the proposed assisted car platooning system, and an optimised smart traffic light operation that can reduce congestion and fuel consumption, improve traffic flow, and enhance road safety. The findings from this paper can be used as a baseline for the framework of CACC implementation by legislators, policymakers, infrastructure providers, and vehicle manufacturers.

Internet of Vehicles Based On Cellular-Vehicle-To-Everything (C-V2X)

In line with the development of automotive and traffic systems, high mobility and density in different road topologies cause scalability and delay issues due to frequent disconnection between communication nodes. From a safety aspect, Cellular-V2X (C-V2X) wireless technology was introduced by the Third Generation Partnership Project Organization (3GPP) to realise the transmission of emergency messages at critical times, anywhere. Specifically, Mode 4 C-V2X supports side-link communication without relying on a base station to provide network coverage. However, Mode 4 is susceptible to several limitations, which include half-duplex transmission, packet collision, and propagation errors that will cause intermittent connectivity issues. It is also difficult to determine appropriate parameter configurations that can increase the spectrum efficiency of dense networks to facilitate reliable and low-latency networks. The objective of this paper is to investigate the effectiveness of a Mode 4 C-V2X system under different road topologies and traffic scenarios. The study adopts a Krauss vehicular mobility model based on SUMO software to model normal and dense networks in a highway and a road intersection scenario, then perform simulation using OMNET++ software to analyse the impact of different physical layer (PHY) configurations such as modulation and coding scheme, packet size, number of resource block allocation, as well as the probability of resource reservation. The results show that the optimal configuration of parameters depends on the scenario. For highway scenarios, a lower MCS and a higher number of RBs are recommended. For road intersection scenarios, a higher MCS and a lower number of RBs are recommended. The packet size should also be in accordance with the requirements of the application used. The findings of this study can be used to assist in the design of an optimal intelligent transportation system using adaptive C-V2X parameters that can be automatically adjusted under different scenarios and network conditions.

Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks.

The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.

A multi-scale unified model of human mobility in urban agglomerations

Understanding human mobility patterns is vital for the coordinated development of cities in urban agglomerations. Existing mobility models can capture single-scale travel behavior within or between cities, but the unified modeling of multi-scale human mobility in urban agglomerations is still analytically and computationally intractable. In this study, by simulating people's mental representations of physical space, we decompose and model the human travel choice process as a cascaded multi-class classification problem. Our multi-scale unified model, built upon cascaded deep neural networks, can predict human mobility in world-class urban agglomerations with thousands of regions. By incorporating individual memory features and population attractiveness features extracted by a graph generative adversarial network, our model can simultaneously predict multi-scale individual and population mobility patterns within urban agglomerations. Our model serves as an exemplar framework for reproducing universal-scale laws of human mobility across various spatial scales, providing vital decision support for urban settings of urban agglomerations.

Conformational particularities of beta-amyloid peptide 25-35

In Alzheimer's disease, beta-amyloid peptide (Ав) plays an important role in the mechanism of neurodegeneration. A small fragment of Лв(25-35) (with the sequence GSNKGAIIGLLM) is regarded to be the functional domain of Лв, responsible for its neurotoxic properties and represents the biological active region of Лв. Conformational analysis of each C-terminal segment of the peptide by the method of molecular mechanics revealed a limited number of most probable conformations and quite clearly helped to clarify what forces stabilize the structures. The obtained results showed that Лв(25-35) energetically has a propensity for adopting alpha-helix conformation of the C-terminal octapeptide segment. A molecular dynamics method was used to build a model of intramolecular mobility in the Лв(25-35) molecule. It was demonstrated that in low-energy conformations, Лв(25-35), the orientation of flexible structures of the N-terminal region with respect to the structures of the C-terminal region is different.

Revving up VNDN: Efficient caching and forwarding by expanding content popularity perspective and mobility

Network caching in Vehicular Named Data Networks (VNDN) has the potential to support latency-sensitive services, though given the massive amount of content generated by vehicles in a VNDN, it is challenging to cache sufficiently diverse content across the network for an acceptable hit ratio. Redundant interest transmissions can negatively impact network overhead, wasting network resources when retrieving duplicate content. In the literature, a caching decision is typically based on ongoing popularity, computed from a vehicle’s experience with requests received for individual content. This leads to each vehicle caching the most popular content. Instead, we group content into different categories. All content in a popular category of vehicular service (e.g., tourist information category) is cached equally, not just the most popular content within a category (e.g., information relating to a particular museum). This increases content diversity in the cache. Further, we posit that a service requester from a particular location at a specific time would be interested in the same category of service/application as other users from the same location/time. Leveraging this observation, we consider both forthcoming spatial/temporal and ongoing popularity of vehicular services when ranking their popularity. We also address network overhead with a mobility model that captures the communication duration between vehicles. This parameter, which has been overlooked in existing literature, enables the selection of an appropriate forwarder for content requests. We use ndnSIM VNDN with a mobility trace of Luxembourg city for simulation. Compared to an approach where individual content-wise popularity is computed, our scheme shows more than 100% improvement in cache hit ratio where the number of contents in the network varied between 104 and 105. Simultaneously, we also enhanced the diversity of content caching, while considering the trade-off between cache hit ratio and network overhead.