Online Navigation Research Articles

The Sea Route Planning for Survey Vessel Intelligently Navigating to the Survey Lines.

Marine surveying is an important part of marine environment monitoring systems. In order to improve the accuracy of marine surveying and reduce investment in artificial stations, it is necessary to use high-precision GNSS for shipborne navigation measurements. The basic measurement is based on the survey lines that are already planned by surveyors. In response to the needs of survey vessels sailing to the survey line, a method framework for the shortest route planning is proposed. Then an intelligent navigation system for survey vessels is established, which can be applied to online navigation of survey vessels. The essence of the framework is that the vessel can travel along the shortest route to the designated survey line under the limitation of its own minimum turning radius. Comparison and analysis of experiments show that the framework achieves better optimization. The experimental results show that our proposed method can enable the vessel to sail along a shorter path and reach the starting point of the survey line at the specified angle.

Fi-Vi: Large-Area Indoor Localization Scheme Combining ML/DL-Based Wireless Fingerprinting and Visual Positioning

Due to recent technological developments such as online navigation, augmented reality (AR), virtual reality (VR), and digital twins, and the high demand from users for various location-based services (LBS), research on location estimation techniques is being actively conducted. As a result, there is an increasing demand for effective localization technologies that can be used in places where the use of Global Positioning System (GPS) is limited, especially in indoor spaces with very large areas. In this paper, a new structure for an indoor localization system in which wireless fingerprinting and visual-based positioning are hierarchically combined—the so-called Fi-Vi system—is proposed. This scheme consists of two steps: fingerprint-based localization (FBL) followed by visual-based localization (VBL). In the first positioning step (i.e., the FBL stage), the entire area of a significantly broad range for localization is divided into multiple regions, the size and the number of which depend on the target accuracy of this step. Moreover, a machine-learning (ML) or deep-learning (DL) model trained on a Wi-Fi fingerprint radio map selects suitable candidate regions among these multiple regions. In the second positioning step (i.e., the VBL stage), the final location is precisely estimated through visual-based positioning based on the received information regarding the candidate regions. The FBL stage uses a sparse radio map (SRM) for fingerprinting, which can be constructed with relatively little effort and cost compared to radio maps used in conventional fingerprinting methods. As a result, it can be easily combined with existing visual-based positioning methods with almost negligible implementation complexity. Because of the hierarchical structure and SRM, the proposed scheme shows a significant performance improvement in terms of computational load and time required for indoor localization compared to the use of the existing visual-based indoor positioning method alone. In addition, it provides high accuracy and robustness even in a dynamically changing indoor wireless environment where conventional wireless fingerprinting methods show significant performance degradation. Finally, the performance analysis of the proposed scheme was performed using the UJIIndoorLoc dataset. Experiments and theoretical analysis have shown that when the estimation accuracy of the candidate region for the test dataset was achieved at about 99% through the FBL stage, the average computational amount of the VBL stage for the final position estimation was only about 16% of that in cases where the visual-based positioning method was used alone.

ФОРМУВАННЯ ЕЛЕКТРОННИХ ЛОГІСТИЧНИХ МАРШРУТІВ ДОСТАВКИ СІЛЬСЬКОГОСПОДАРСЬКОЇ ПРОДУКЦІЇ ВІД ВИРОБНИКА ДО СПОЖИВАЧА У СИСТЕМІ БЮДЖЕТУВАННЯ ДІЯЛЬНОСТІ СУБ’ЄКТІВ ГОСПОДАРЮВАННЯ

Problematic issues related to the sale of products by local landowners and owners have been identified. At the same time, a significant share of imports of consumer products is justified. Opportunities for import substitution of products of the agricultural sector of the economy with the simultaneous establishment of the business sector in rural integrated territorial communities are outlined. It is investigated that several weaknesses are currently clearly identified for the established mechanism of sales of agricultural products in the chain from producer to final consumer. In addition to low financial literacy, lack of implementation of marketing principles, involvement of technological renewal of production processes, motivational factor, lack of consulting measures, etc., small agricultural producers need to be integrated into a modernized logistics system. The research presents a thesis about the key problem that exists today for the construction of electronic routes of product delivery – the lack of an address database of end users of products. Such a database was not formed by world leaders in trading platforms such as alibaba. com, aliexpress.com, domestic –, Silpo, ATB and others. Their position is well-established and understandable for conservative reasons. However, we pursue a social goal – to establish the necessary components to motivate the development of entrepreneurship in rural communities. This, in turn, should minimize the existing multiple trade margins. It is determined that the starting point (manufacturer's address), online navigation and off-line navigation system such as google.maps and route endpoint (consumer address) are required to build an electronic route. The difficulty arises in reducing to a single accepted orderly and pre-approved classification of the address of all potential end users and producers. Such unification will provide an opportunity not only to optimize electronic routes, but also the opportunity to find a manufacturer, a service provider in a territory optimally distant from the customer. The first steps towards the digitalization of such processes are laid down in our developed online platform perehid-4.com.ua.

Spatial navigation performance in people with multiple sclerosis-a large-scale online study

ObjectiveSpatial navigation has a crucial function in daily life activities, and is therefore strongly linked to quality of life, autonomy, and mobility. Navigation has been shown to be frequently impaired after forms of acquired brain injury, but the impact of MS on navigation ability has yet to be studied. A better understanding of potential navigation problems in this population could improve patient care. Therefore the aim of the current study was to measure objective and subjective navigation performance in people with MS. MethodsPerformance of a large sample of people with MS (N = 359) was compared to a group of matched controls. Additionally, the impact of ambulation and self-reported cognitive performance was studied within the MS sample. Participants filled out the Wayfinding Questionnaire, the patient-reported Expanded Disability Status Scale and the Multiple Sclerosis Neuropsychological Screening Questionnaire for self-report measures. Objective navigation performance was measured with an online navigation test using a virtual environment. ResultsResults indicate a lower subjective as well as objective performance in people with MS compared to healthy controls, and a substantial contribution of self-reported cognitive performance on navigation ability. ConclusionsThese findings indicate that spatial navigation can be a significant problem in people with MS, especially in people with MS with other cognitive impairments.

Generation of Realistic Navigation Paths for Web Site Testing Using RNN and GAN

For applications that have not yet been launched, a reliable way for creating online navigation logs may be crucial, enabling developers to test their products as though they were being used by real users. This might lead to faster and lower-cost program testing and enhancement, especially in terms of usability and interaction. In this work we propose a method for using deep learning approaches such as recurrent neural networks (RNN) and generative adversarial neural networks (GANN) to produce high-quality weblogs. Eventually, we can utilize the created data for automated testing and improvement of Web sites prior to their release with the aid of model-driven development tools such as IFML Editor.

A customized deep learning approach to integrate network-scale online traffic data imputation and prediction

Online data imputation and traffic prediction based on real-time data streams are essential for the intelligent transportation systems, particularly online navigation applications based on the real-time traffic information. However, the inevitable data missing problem caused by various disturbances undermines the information contained in such real-time data, thereby threatening the reliability of data acquisition as well as the prediction results. Such scenarios raise a strong need for integrating the tasks of network-scale online data imputation and traffic prediction, because the existing two-step approaches that separate the above procedures cannot be implemented in an online manner. In this paper, we propose a customized spatiotemporal deep learning architecture, named the graph convolutional bidirectional recurrent neural network (GCBRNN), to combine network-scale online data imputation and traffic prediction into an integrated task. The imputation mechanism and bidirectional framework are developed to cooperatively estimate missing entries and infer future values. We further design a network-scale graph convolutional gated recurrent unit (NGC-GRU) within the GCBRNN, which applies the graph convolution operation and 1×1 convolution module to capture the spatiotemporal dependencies in the traffic data. Experiments are carried out on two real-world traffic networks, including traffic speed and flow datasets. The comparison results demonstrate that our approach significantly outperforms several classical benchmark models with respect to both the imputation and prediction tasks on two datasets under various missing data rates.

Modeling earthmoving operations in real time using hybrid fuzzy simulation

Predicting and optimizing performance in earthmoving operations is critical, because they are essential to many construction projects. The complexity of modeling earthmoving operations remains challenging, even with several modeling techniques available, including simulation. This paper advances the state-of-the-art of modeling earthmoving operations by introducing a hybrid fuzzy system dynamics–discrete event simulation framework with the capacity to: capture the dynamism of performance in earthmoving operations; capture subjective uncertainty of several factors affecting them; model their sequential nature and resource constraints; and determine actual travel time, in real time, using online navigation systems. Findings from this research confirm the proposed framework (i) extends the application of simulation techniques for modeling construction processes involving dynamic input variables and subjective uncertainty, through its ability to capture the non-probabilistic uncertainty of construction systems, and (ii) when combined with the use of online navigation systems to assess trucks’ travel time, improves the accuracy of earthmoving operation models.

The Impact of Social Network Sites on Students’ Psychological Problems

Students in recent years spend a considerable amount of time on social networking web-sites. They have made online access and navigation through these sites part of their daily activities. The impact of social network sites in particular has become a major subject of discussion among various studies, because some of them see these pages as a threat or obstacle, while the rest argue that them affects positively the age of adolescence. A quantitative, descriptive and exploratory survey was conducted to identify the impact of this involvement on adolescents’ behaviour that affect their psychological development. The research sample consisted of 893 students, between the ages 10-15 years, users of the social network sites. This champion has been taken from middle school institutions from different cities of Albania. The analysis of the study results confirmed that students are using social network sites for a long time during the day. They have become addicted to them and they already display some behaviour patterns. As a conclusion, the study found that the inclusion in social network sites, if students spend a considerable amount of time on them, has a negative impact in their psychological problems. Parents, teachers and students need to communicate with each other in order to identify and avoid the risks of social network sites and also other studies should be done in this field and suggest different strategies to manage the psychological problems caused by the use of social networking sites.

Navigation ability in patients with acquired brain injury: A population-wide online study

ABSTRACT The ability to travel independently is a vital part of an autonomous life. It is important to investigate to what degree people with acquired brain injuries (ABI) suffer from navigation impairments. The aim of this study was to investigate the prevalence and characteristics of objective and subjective navigation impairments in the population of ABI patients. A large-scale online navigation study was conducted with 435 ABI patients and 7474 healthy controls. Participants studied a route through a virtual environment and completed 5 navigation tasks that assessed distinct functional components of navigation ability. Subjective navigation abilities were assessed using the Wayfinding questionnaire. Patients were matched to controls using propensity score matching. Overall, performance on objective navigation tasks was significantly lower in the ABI population compared to the healthy controls. The landmark recognition, route continuation and allocentric location knowledge tasks were most vulnerable to brain injury. The prevalence of subjective navigation impairments was higher in the ABI population compared to the healthy controls. In conclusion, a substantial proportion (39.1%) of the ABI population reports navigation impairments. We advocate the evaluation of objective and subjective navigation ability in neuropsychological assessments of ABI patients.

Cooperative Intelligent Transport Systems: Choreography-Based Urban Traffic Coordination

With the emerging connected automated vehicles, 5G and Internet of Things (IoT), vehicles and road infrastructure become connected and cooperative, enabling Cooperative Intelligent Transport Systems (C-ITS). C-ITS are transport system of systems that involves many stakeholders from different sectors. While running their own systems and providing services independently, stakeholders cooperate with each other for improving the overall transport performance such as safety, efficiency and sustainability. Massive information on road and traffic is already available and provided through standard services with different protocols. By reusing and composing the available heterogeneous services, novel value-added applications can be developed. This paper introduces a choreography-based service composition platform, i.e. the CHOReVOLUTION Integrated Development and Runtime Environment (IDRE), and it reports on how the IDRE has been successfully exploited to accelerate the reuse-based development of a choreography-based Urban Traffic Coordination (UTC) application. The UTC application takes the shape of eco-driving services that through real-time eco-route evaluation assist the drivers for the most eco-friendly and comfortable driving experience. The eco-driving services are realized through choreography and they are exploited through a mobile app for online navigation. From specification to deployment to execution, the CHOReVOLUTION IDRE has been exploited to support the realization of the UTC application by automatizing the generation of the distributed logic to properly bind, coordinate and adapt the interactions of the involved parties. The benefits brought by CHOReVOLUTION IDRE have been assessed through the evaluation of a set of Key Performance Indicators (KPIs).

Oncology Patient Navigation Training: Results of a Pilot Study in Nigeria.

The purpose of this pilot study was to test the efficacy of an online navigation training designed to improve trainee confidence in performing core patient navigation tasks among Nigerian nurses, patient advocates, and cancer survivors. The online training originally designed for US patient navigators was supplemented by a Nigerian health system interactive session. Nurses, advocates, and cancer survivors (n = 36) were recruited to take a patient navigation training from May–June 2020 that consisted of approximately 10 h of online content and a 2-h online session. Trainees enrolled in the no-cost training and completed all 20 lessons. Post-intervention interviews (n = 10) were conducted to garner feedback from trainees. Trainees reported statistically significant improvements in confidence in performing core competencies for cancer patient navigation across all lessons. Feedback was generally positive with trainees expressing satisfaction and appreciation for the training. Challenges included lack of free, broadband Internet access leading to data streaming costs on the part of trainees. Trainees who were oncology nurses indicated that funding, time, and staffing constraints could impede implementation of patient navigation in practice; but these trainees also expressed new ideas for patient support and advocacy to alleviate some barriers to care for their patients as a result of the training. This study provided preliminary data that supports the feasibility and utility of using the GW Cancer Center online patient navigation training in non-US settings. Small adaptations to training content and technological delivery could improve access to the training experience. Implementation science approaches are needed to inform sustainable patient navigation in low-resource settings.

Self-Balancing Robot Navigation

Human activity has been increasing, to support the activity, people in the modern era create robots to replace some human activities. The interest in two-wheeled balance robots has continued to increase, this is because it is highly maneuverable, making it efficient for use in various areas. In this study, the online navigation of a two-wheeled self-balancing robot is done. The connection between the robot and online navigation is using a Wi-Fi connection. The world model base on the real room is created by Gazebo and then visualized in RVIZ. The map creation and navigation process are handled by the package provided by ROS. The results of the simulation and real tracking show that the robot can move from the starting point to the destination point in either a straight or a curved path. The difference of the final position of the robot between simulation and real tracking is only (15.4 cm, 4 cm) and (9.6 cm, 43 cm) for the straight and curved path. This result proved that online navigation can be used to navigate an autonomous robot without real navigation sensors.

Going remote: Implementing digital research methods at an academic medical center during COVID-19.

COVID-19 has forced medical research institutions to conduct clinical research remotely. Here, we describe how a university's mHealth Research Core helped facilitate the shift to remote research during the COVID-19 pandemic. In 2019 (pre-pandemic), we conducted stakeholder interviews and leadership group sessions to identify, create, and implement resources and core functions to support investigator-initiated mHealth research. Between April 2019 and February 2020, we identified four investigator needs: 1) a seminar series on trends in mHealth research, 2) mHealth case consultation services, 3) liaison services with institutional regulatory compliance groups, and 4) online navigation tools for implementation of mHealth methods (e.g., eConsent) and for building partnerships with technology vendors. To date, the mHealth Research Core has held seven seminars, completed 71 case consultations, assisted four COVID-related clinical studies, advised the IRB on shifting to remote research, and widely disseminated eConsent navigation tools. Although pre-pandemic stakeholder and investigator needs led to the creation of the mHealth Research Core, this institutional resource played a critical role in continuing clinical research during the pandemic by assisting investigators in rapidly shifting to remote study methodology.

Spatial and dosimetric evaluation of residual distortions of prostate and seminal vesicle bed after image-guided definitive and postoperative radiotherapy of prostate cancer with endorectal balloon.

PurposeTo quantify daily residual deviations from the planned geometry after image‐guided prostate radiotherapy with endorectal balloon and to evaluate their effect on the delivered dose distribution.MethodsDaily kV‐CBCT imaging was used for online setup‐correction in six degrees of freedom (6‐dof) for 24 patients receiving definitive (12 RTdef patients) or postoperative (12 RTpostop patients) radiotherapy with endorectal balloon (overall 739 CBCTs). Residual deviations were evaluated using several spatial and dosimetric variables, including: (a) posterior Hausdorff distance HDpost (=maximum distance between planned and daily CTV contour), (b) point Pworst with largest HDpost over all fractions, (c) equivalent uniform dose using a cell survival model (EUDSF) and the generalized EUD concept (gEUDa with parameter a = −7 and a = −20). EUD values were determined for planned (EUDSFplan), daily (EUDSFind), and delivered dose distributions (EUDSFaccum) for plans with 6 mm (=clinical plans) and 2 mm CTV‐to‐PTV margin. Time series analyses of interfractional spatial and dosimetric deviations were conducted.ResultsLarge HDpost values ≥ 12.5 mm (≥15 mm) were observed in 20/739 (5/739) fractions distributed across 7 (3) patients. Points Pworst were predominantly located at the posterior CTV boundary in the seminal vesicle region (16/24 patients, 6/7 patients with HDpost ≥ 12.5 mm). Time series analyses revealed a stationary white noise characteristic of HDpost and relative dose at Pworst. The EUDSF difference between planned and accumulated dose distributions was < 5.4% for all 6‐mm plans. Evaluating 2‐mm plans, EUDSF deteriorated by < 10% (<5%) in 75% (58.5%) of the patients. EUDSFaccum was well described by the median value of the EUDSFind distribution. PTV margin calculation at Pworst yielded 8.8 mm.ConclusionsAccumulated dose distributions in prostate radiotherapy with endorectal balloon are forgiving of considerable residual distortions after 6‐dof patient setup if they are observed in a minority of fractions and the median value of EUDSFind determined per fraction stays within 95% of prescribed dose. Common PTV margin calculations are overly conservative because after online correction of translational and rotational errors only residual deformations need to be included. These results provide guidelines regarding online navigation, margin optimization, and treatment adaptation strategies.

Narratives and Their Impact on Students’ Information Seeking and Critical Online Reasoning in Higher Education Economics and Medicine

The digital and information age has fundamentally transformed the way in which students learn and the study material they have at their disposal, especially in higher education. Students need to possess a number of higher-order cognitive and metacognitive skills, including effective information processing and critical reasoning to be able to navigate the Internet and use online sources, even those found outside of academically curated domains and in the depths of the Internet, and to solve (domain-specific) problems. Linking qualitative and quantitative research and connecting the humanities to empirical educational science studies, this paper investigates the role of narratives and their impact on university students’ information seeking and their critical online reasoning (COR). This study focuses on the link between students’ online navigation skills, information seeking behavior and critical reasoning with regard to the specific domains: economics and medicine. For the empirical analysis in this paper, we draw on a study that assesses the critical online reasoning (COR) skills of undergraduate students of economics and medicine at two German universities. To measure COR skills, we used five tasks from the computer-based assessment “Critical Online Reasoning Assessment” (CORA), which assesses students’ skills in critically evaluating online sources and reasoning using evidence on contentious issues. The conceptual framework of this study is based on an existing methodology – narrative economics and medicine – and discusses its instructional potential and how it can be used to develop a new tool of ’wise interventions’ to enhance students’ COR in higher education. Based on qualitative content analyses of the students’ written responses, i.e. short essays, three distinct patterns of information seeking behavior among students have been identified. These three patterns – “Unambiguous Fact-Checking”, “Perspective-Taking without Fact-Checking”, and “Web Credibility-Evaluating” – differ substantially in their potential connection to underlying narratives of information used by students to solve the CORA tasks. This analysis suggests that training university students in narrative analysis can strongly contribute to enhancing their critical online reasoning.

Navegação em ambientes digitais

Este trabalho apresenta um estudo do processo de apropriação do letramento digital experenciado por alunos de cursos de graduação a distância da Universidade Federal de Minas Gerais (UFMG). O objetivo é investigar as práticas de leitura on-line utilizadas pelos alunos, por meio dos diversos am-bientes digitais disponíveis para os estudos acadêmicos. Em sua metodologia, embora essencialmente interpretativa e qualitativa, em momentos específicos de tratamento dos dados, a pesquisa envolve também a abordagem quantitativa. A coleta de dados foi realizada a partir de questionário on-linee de simulação de navegação. Os resultados evidenciam que os alunos realizam habilidades e estratégias de navegação e de leitura on-line eficientemente, apesar de perceber uma carência desses alunos em fazer uma pesquisa investigativa mais apurada. Percebemos que a nova sala de aula e o novo caderno são desafios que reque-rem velhas e novas práticas e que trazem uma nova textualidade na qual a tela rompe a superficialidade do texto impresso em uma concepção mais ampla e atual de leitura, provocando não só mudanças materiais, assim como a maneira pela qual as informações são apresentadas.

A proactive route planning approach to navigation errors

ABSTRACT Online navigation systems assume a person can follow a given route from origin to destination. Nonetheless, spatial cognition studies show that wayfinding is a complex, highly adaptive process and that route planning is incremental rather than prescriptive. Indeed, people may deviate from their originally chosen route for a number of reasons including navigation errors, especially when the environment is unfamiliar. Even in familiar places, certainty in wayfinding is highly unlikely to be completely achieved. Consequently, when people make a wrong turn or miss an exit, even the best reroute to the destination may add several minutes to the originally planned travel time. This work formally defines the novel problem of finding a path such that, when navigation errors occur, recovering is not as costly. We call this approach the most recoverable path. This subtle change in the route planning problem – i.e., considering error recovery costs – invalidates using dynamic programming, such as in shortest path algorithm solutions. We therefore introduce a novel, readily applicable, fast heuristic to this NP-hard problem. The benefits of the most recoverable path are manifold: long detours are avoided, actual travel time is reduced, and it is comparable to its shortest counterpart in terms of length.

VOC Monitoring and Ozone Generation Potential Analysis Based on a Single-Photon Ionization Time-of-Flight Mass Spectrometer

The single-photon ionization time-of-flight mass spectrometer (SPI-TOFMS), which has high sensitivity, high accuracy, and a short response time, is effective for the real-time monitoring of volatile organic compounds (VOCs). In this study, the theory and structural composition of the SPI-TOFMS are described. Its detection limit can reach parts per billion by volume (ppbv), the dynamic range is better than three orders of magnitude, and the response speed can reach milliseconds. The distribution of VOCs and the ozone generation contribution rate in the Hefei Economic Development Zone are analyzed using this instrument with a vehicle platform for online navigation detection. The experimental results showed that aromatics were the primary components of the total volatile organic compounds (TVOCs), and aromatics and alkenes contributed more to ozone formation in an industrial manufacturing area. This research indicates that the SPI-TOFMS can rapidly and accurately conduct online monitoring of VOCs in industrial development zones. In addition, it has been applied in the fields of atmospheric composition observation, environmental monitoring, and industrial VOC leakage monitoring.

A Hybrid Controller for Multi-Agent Collision Avoidance via a Differential Game Formulation

We consider the multi-agent collision avoidance problem for a team of wheeled mobile robots. Recently, a local solution to this problem, based on a game-theoretic formulation, has been provided and validated via numerical simulations. Due to its local nature, the result is not well-suited for online applications. In this article, we propose a novel hybrid implementation of the control inputs that yields a control strategy suited for the online navigation of mobile robots. Moreover, subject to a certain dwell time condition, the resulting trajectories are globally convergent. The control design is demonstrated both via simulations and experiments.

Radar-Updated Inertial Landing Navigation With Online Initialization

This article focuses on the employment of an inertial measurement unit (IMU) and a radar altimeter and velocimeter as navigation sensors for Mars landing navigation. At the beginning of the parachute descent phase, high dynamic oscillatory motion may saturate the gyroscope and produce large attitude estimation errors, thereby producing a high landing risk. To address this problem, an online navigation initialization algorithm is presented by combining data from the IMU and the radar. By defining a new inertial frame, attitude, and Mars-related velocity are conveniently initialized. A key contribution of this article is the computation of gravitational acceleration using IMU and velocimeter's measurements for the approximation of the nadir vector. Given the nadir vector, the inertial position is initialized in conjunction with the altimeter's measurement, the gravitational acceleration is modeled such that the inertial navigation equation can be propagated and the propagated altitude and velocity can be corrected by radar radar-derived measurements.