From electronic navigational chart data to sea-bottom models: Kriging approaches for the Bay of Pozzuoli

<p class="Abstract">Electronic Navigational Charts (ENCs), official databases created by a national hydrographic office and included in Electronic Chart Display and Information System (ECDIS), supply, among essential indications for safe navigation, data about sea-bottom morphology in terms of depth points and isolines. Those data are very useful to build bathymetric 3D models: applying interpolation methods, it is possible to produce a continuous representation of the seafloor for supporting studies concerning different aspects of a marine area, such as directions and intensity of currents, sensitivity of habitats and species, etc. Many interpolation methods are available in literature for bathymetric data modelling: among them kriging ones are extremely performing, but require deep analysis to define input parameters, i.e. semi-variogram models. This paper aims to analyze kriging approaches for depth data concerning the Bay of Pozzuoli. The attention is focused on the role of semi-variogram models for Ordinary and Universal kriging. Depth data included in two ENCs, namely IT400129 and IT400130, are processed using Geostatistical Analyst, an extension of ArcGIS 10.3.1 (ESRI). The results testify the relevance of the choice of the mathematical functions of the semi-variogram: Stable Model supplies, for this case study, the best performance in terms of depth accuracy for both Ordinary and Universal kriging.</p>

Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism

Satellite navigation has become ubiquitous to plan and track travelling. Having access to a vehicle’s position enables the prediction of its destination. This opens the possibility to various benefits, such as early warnings of potential hazards, route diversions to pass traffic congestion, and optimizing fuel consumption for hybrid vehicles. Thus, reliably predicting destinations can bring benefits to the transportation industry. This paper investigates using deep learning methods for predicting a vehicle’s destination based on its journey history. With this aim, Dense Neural Networks (DNNs), Long Short-Term Memory (LSTM) networks, Bidirectional LSTM (BiLSTM), and networks with and without attention mechanisms are tested. Especially, LSTM and BiLSTM models with attention mechanism are commonly used for natural language processing and text-classification-related applications. On the other hand, this paper demonstrates the viability of these techniques in the automotive and associated industrial domain, aimed at generating industrial impact. The results of using satellite navigation data show that the BiLSTM with an attention mechanism exhibits better prediction performance destination, achieving an average accuracy of 96% against the test set (4% higher than the average accuracy of the standard BiLSTM) and consistently outperforming the other models by maintaining robustness and stability during forecasting.

Predictive Course Control and Guidance of Autonomous Unmanned Sailboat Based on Efficient Sampled Gaussian Process

In view of the vulnerability of ocean unmanned sailboats to the large lateral velocities due to wind and waves during navigation, this paper proposes a Gaussian Process Model Predictive Control (GPMPC) method based on data-driven learning technique to improve the navigation tracking accuracy of unmanned sailboats. The feature model of the sailing course change subject to the wind and waves is learned from the efficient sampling data. It is then combined with the model predictive control to form the course controller. To reduce the influence of wind and waves disturbances, an adaptive weight term is designed in the object function to improve the tracking accuracy of the model predictive control. The guidance commands received by the model predictive controller take into account the path deviation caused by the current and lateral motion of the ship. The results show that GPMPC has the advantages of fast response time and less overshoot; the unmanned sailboat can better achieve waypoint tracking by learning navigation data.

Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction

Travellers use the term waymarking to define the action of posting signs, or waymarks, along a route. These marks are intended to be points of reference during navigation for the environment. In this research, we will define waymarking as the skill of a robot to signal the environment or generate information to facilitate localization and navigation, both for its own use and for other robots as well. We present an automated environment signaling system using human–robot interaction and radio frequency identification (RFID) technology. The goal is for the robot, through human–robot interaction, to obtain information from the environment and use this information to carry out the signaling or waymarking process. HRI will play a key role in the signaling process since this type of communication makes it possible to exchange more specific and enriching information. The robot uses common phrases such as “Where am I?” and “Where can I go?”, just as we humans do when we ask other people for information about the environment. It is also possible to guide the robot and “show” it the environment to carry out the task of writing the signs. The robot will use the information received to create, update, or improve the navigation data in the RFID signals. In this paper, the signaling process will be described, how the robot acquires the information for signals, writing and updating process and finally, the implementation and integration in a real social robot in a real indoor environment.

Integrity as an Aspect of Information Security: an Overview of Modern Apрroaches

There are three main aspects of the information security: • confidentiality; • availability; • integrity. Nowadays ensuring the confidentiality has ceased to be the dominant requirement, but privacy as an element of confidentiality (or as an independent aspect) attracts, perhaps, the greatest attention both at the legislative (personal data protection) and at the technical (depersonalization of big data) levels. The Internet of Things has defined a new level of accessibility requirements. Network access has come to the fore, without it a (too) smart kettle will not boil water. (Attempts to block some Internet resources led to similar everyday problems.) The number of entities whose integrity needs to be ensured has grown. These are data flows, hardware configurations, logistics chains, and much more. Integrity began to be understood not only as security against unauthorized modification, but also as the quality of data, their completeness and validity. This was the reason for writing this article. In our opinion, there is no systematic presentation of modern approaches to ensuring integrity in the literature and therefore it would be appropriate. It makes no sense to rank the aspects of information security according to their importance, but we would like to emphasize the role of integrity. Integrity turns out to be the most important aspect of information security in those cases when information is a "guide to action" and serves to make decisions. The prescription of medicines, prescribed medical procedures, the set and characteristics of components, the course of the technological process — all these are examples of information, the violation of the integrity of which can literally be fatal. It is also unpleasant to distort official information, whether it is the text of the law or the page of the website of a government organization. Compromising the integrity of the electronic voting process casts doubt on the legitimacy of the authorities. Unauthorized influence on financial flows leads to material losses. Distortion of navigation data can lead to accidents. The article is an overview of modern approaches to ensuring integrity as an aspect of information security. An attempt is made to analyze the relevant models, policies and security mechanisms, as well as their application in different subject areas.

Efficient and Unique learning of the Complex Receiver Structure of Galileo E5 AltBOC using an Educational Software in Matlab

This paper presents an efficient and unique method to learn the complex receiver structure of Galileo E5 AltBOC (Alternative Binary Offset Carrier). The software application is designed in Matlab to present each step involved in the design of software receiver of Galileo E5 signal. This software application contains the fundamental concepts of the Galileo E5 signal in the form of signal acquisition, signal tracking, extraction of the navigation data, power spectral density (PSD) of the AltBOC (15, 10), Fast Fourier Transform (FFT) of the E5a and E5b signal and implementation of the subcarrier used for the AltBOC (15,10). This paper also presents the extraction of navigation data by a novel based approach using the prompt channel of carrier tracking from the code loop discriminator.

A Brief Review on Challenges in Design and Development of Nanorobots for Medical Applications

Robotics is a rapidly growing field, and the innovative idea to scale down the size of robots to the nanometer level has paved a new way of treating human health. Nanorobots have become the focus of many researchers aiming to explore their many potential applications in medicine. This paper focuses on manufacturing techniques involved in the fabrication of nanorobots and their associated challenges in terms of design architecture, sensors, actuators, powering, navigation, data transmission, followed by challenges in applications. In addition, an overview of various nanorobotic systems addresses different architectures of a nanorobot. Moreover, multiple medical applications, such as oncology, drug delivery, and surgery, are reviewed and summarized.

SIMULATION OF EGNOS SATELLITE NAVIGATION SIGNAL USAGE FOR AIRCRAFT LPV PRECISION INSTRUMENT APPROACH

Satellite navigation has become a very important topic in the air transport industry along with its application in instrument approach procedures. Recently, extracted statistical characteristics of the European Geostationary Navigation Overlay Service (EGNOS) satellite signal have been made available from real measurements in the Czech Republic. The numerical modeling approach is taken for a feasibility study of automatic aircraft control during the Localizer Performance with Vertical Guidance (LPV) precision approach based on such navigation data. The model incorporates Kalman filtering of the stochastic navigation signal, feed-back control of L-410 aircraft dynamics and the calculation of approach progress along the predefined procedure. Evaluation of the performance of the system prototype is performed using the scenarios developed with a strong interest in altitude control. The specific scenario is focused on a curved approach which offers a huge advantage of the approaches based on the Satellite-based Augmentation System (SBAS) compared to ones with the Instrument Landing System (ILS). Outputs of simulation executions are statistically analyzed and assessed against predefined navigation performance goals equivalent to ILS categories with a positive outcome.

Creation of Ship Navigation Data Using Simulation Technology in Training Module

All ships need navigation data to ensure they stay on track during course-changing maneuvers. Navigation data are usually obtained by shipyards while conducting turning trials at sea. The aim of this research was to generate navigation data for warships, such as the Leander Class Frigate (LCF). The research was conducted using the Ship Bridge Simulator (SBS) simulation technology at the Maritime Centre of the National Defence University of Malaysia (NDUM). Turning trials were conducted at various speeds, rudder angels, and heading changes. Distance to new course, advance and transfer have been tabulated for LCF navigation data. Navigation experts validated the data by nautical chart plotting. The data were found to be highly reliable for the training module. The research was successfully conducted and generated LCF navigation data. The navigation data collected are highly accurate and effective for the naval cadet navigation training module at the NDUM. The SBS software is highly suitable for turning trials and navigation data generation.