Navigation Features Research Articles

Next level of hospitalisation through smart ICU

Automation technology is developing intelligent health applications to facilitate patients by providing smart health solution. However, plethora of research is required in the autonomous robotics industry to provide smart solutions to hospitals.Hence, the proposed study aims to develop an intelligent automated infrastructure for hospitals, capable of performing several smart tasks in an Intensive Care Unit (ICU). The developed system will make food and medicine approachable by using a robotic arm on an autonomous robot. Furthermore, robotic arm can be locally controlled by the patient paramedic’s staff. The proposed intelligent robot will monitor patient’s condition by automatically monitoring the vitals conditions such as sleeping, stress, discomfort etc. This proposed system is very useful for diseases where close proximity can spread the disease, such as the covid-19 situation. Moreover, the automation will aid ICU patients by controllable bed functionality supported with patient’s EEG signals or remotely by staff. This research proposed LSTM based neural network for EEG classification and compare the results with other machine learning algorithms. The proposed LSTM network achieve 94% accuracy on self generated dataset. The achieved results are also compared with other machine learning models like SVM and Multilayer Perceptron (MLP). The intelligent navigation feature is also introduced which enables the robot to move autonomously in ICU. In addition to this, it can also establish video conference set up between the patient, staff and family members. The robot can automatically alert the staff in an emergency and assist the patient through an intelligent chatbot.

Forming the area of unacceptable values of the parameters of vessels’ movement for the vessels’ divergence at remote control process

Navigation traffic and the danger of collision are steadily increasing. Features of navigation in narrow corridors (water, air, etc.) require the development of modern methods for assessing the situation of convergence and the choice of maneuvering divergence of vessels. A method is proposed for forming the area of inadmissible values of the parameters of the movement of any vehicles (including marine) with remote control of the process of their divergence. Situations are considered when a collision of sea vessels can be avoided only by changing the speed in case such vessels cannot change course. The proposed method can be generalized to any environment of navigation.

Miniaturized Casing Collar Locator for Small Downhole Robots

Despite advances in robotics for many harsh environments, the downhole environment is rarely accessed by robots. Small, autonomous robots for logging oil and gas wells potentially offer significant cost savings over conventional wireline logging tools, but there are some major technical challenges to overcome. Among these is navigation or how the robot can know its own position along the well. Oil and gas wells are lined with steel casing, made up of 40-ft-long pipe joints held together by threaded collars. The collar locations could potentially be used as features for navigation, but conventional magnetic casing collar locator (CCL) sensors are large and must be mechanically stabilized within the casing. This letter investigates the design of CCLs for small, untethered robots with limited energy resources.

Автоматическая маршрутизация судов во льдах: постановка задачи и инструменты решения

Development of the applied solutions to optimize ship path in dynamic ice environment is one of the urgent problems due to the ongoing growth of Arctic shipping. Ice routing makes it possible to increase the efficiency of sea transportation, reduce the risks of ship operation in ice, and minimize the negative anthropogenic impact on the atmosphere. This article describes in a concentrated form the authors’ experience in this area and presents Boreas, the developed research software application for automatic ice routing. Mathematical formulation of ice routing task is based on a universal economic criterion that allows optimizing not only a trajectory, but also the amount of icebreaker assistance, ship operation modes (astern or bow forward), and some other aspects of ice navigation. Functionality and architecture of the Boreas software allow carrying out various studies in the field of ice routing. The application supports alternative ice data sources and various speed regimes of a ship. It allows using different search algorithms (grid, wave-based, and combined) and considers numerous navigation features (predefined fairways, navigation depths, and restricted areas). As an example of using the Boreas software, we compared the route of Norilskiy Nickel containership from Dudinka to Murmansk on March 19—22, 2018 with several automatically generated routes for various speed regimes. Based on our experience and the results of this study, we can state that the development of applied solutions for Arctic routing is significantly complicated by multiple sources of uncertainty and requires further research. The article formulates a list of scientific and technical problems that need to be solved for the comprehensive understanding and further implementation of ice routing technologies in the practice of ship navigation in the Arctic.

Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer\u2019s disease patients

Impairment of navigation is one of the earliest symptoms of Alzheimer’s disease (AD), but to date studies have involved proxy tests of navigation rather than studies of real life behaviour. Here we use GPS tracking to measure ecological outdoor behaviour in AD. The aim was to use data-driven machine learning approaches to explore spatial metrics within real life navigational traces that discriminate AD patients from controls. 15 AD patients and 18 controls underwent tracking of their outdoor navigation over two weeks. Three kinds of spatiotemporal features of segments were extracted, characterising the mobility domain (entropy, segment similarity, distance from home), spatial shape (total turning angle, segment complexity), and temporal characteristics (stop duration). Patients significantly differed from controls on entropy (p-value 0.008), segment similarity (p-value {10}^{-7}), and distance from home (p-value {10}^{-14}). Graph-based analyses yielded preliminary data indicating that topological features assessing the connectivity of visited locations may also differentiate patients from controls. In conclusion, our results show that specific outdoor navigation features discriminate AD patients from controls, which has significant implication for future AD diagnostics, outcome measures and interventions. Furthermore, this work illustrates how wearables-based sensing of everyday behaviour may be used to deliver ecologically-valid digital biomarkers of AD pathophysiology.

Strategi Humas melalui Media Online dalam Membangun Citra MI Miftahul Akhlaqiyah Semarang

MI Miftahul Akhlaqiyah Semarang is a private school located in the beringin region, Ngaliyan. In this environment there are many elementary schools. So that the school needs to introduce the school program to the community. The website is one of the media choices chosen by MI Miftahul Akhlaqiyah in building the image of the school. The focus of the problems taken in this study is: How is the Public Relations Strategy through Online Media in Building the Image of MI Miftahul Akhlaqiyah Semarang? This research uses a type of field research with a descriptive qualitative approach. Collecting data using several methods, namely: observation, interviews and documentation. The results showed that, (1) to facilitate user access, namely the existence of adequate facilities, ease of finding websites, mobile friendly, simple website operation, the presence of the most current and most popular news notifications, and access speed. However, the MI Miftahul Akhlaqiyah website does not have a Navigation feature. (2) The MI Miftahul Akhaqiyah website has a large number of visitors and has a global scope. (3) the MI Miftahul Akhlaqiyah website cannot communicate between visitors, but can only be done between visitors and managers.

Ship Navigation Behavior Prediction Based on AIS Data

Real-time and accurate ship navigation dynamic prediction can effectively improve maritime supervision’s intelligence and precision level and ensure ship navigation safety. To further enhance the accuracy of ship navigation dynamic prediction, this paper uses ship AIS as the data source and proposes an improved LSTM navigation dynamic prediction model based on the attention mechanism. Firstly, a set of pre-processing means, including navigation data extraction, abnormal data processing, and missing data interpolation, is proposed to solve the problems of information loss and inaccuracy in AIS data and incomplete retention of dynamic navigation features; secondly, combining the dynamic characteristics of ship navigation in AIS data with time series, using longitude, latitude, heading, speed, a ship heading and time increment as input to establish a dynamic forecasting model for navigation based on LSTM; The existing navigation sequence coding distortion and space-time data incoherence problem, an optimized Attention-LSTM neural network navigation dynamic prediction method is proposed, and the accuracy and robustness of the model are verified by simulation analysis. The results show that this method can achieve high-precision prediction of the ship’s longitude, latitude, heading, and speed.

GNSS Independent Position Fixing using Multiple Navigational Features Registration

Safe navigation at sea depends on reliable position information. The easy to use and readily available navigation satellite systems are providing round the clock position information for seafarers, but denial of these services by jamming or spoofing techniques have become frequent, and other means are needed to validate critical navigation information. This paper revisits traditional methods to estimate position and heading of a vessel and offers a framework for computerized calculation of these basic observables without the use of radio-borne external information. Using radar and sea chart information, the paper investigates the quality of navigation information based on observed location of beacons, landmarks, coastlines and buoys. The paper demonstrates convincing accuracy in both position and heading estimation.

App Designs and Interactive Features to Increase mHealth Adoption: User Expectation Survey and Experiment.

BackgroundDespite the ubiquity of smartphones, there is little guidance for how to design mobile health apps to increase use. Specifically, knowing what features users expect, grab their attention, encourage use (via predicted use or through positive app evaluations), and signal beneficial action possibilities can guide and focus app development efforts.ObjectiveWe investigated what features users expect and how the design (prototypicality) impacts app adoption.MethodsIn a web-based survey, we elicited expectations, including presence and placement, for 12 app features. Thereafter, participants (n=462) viewed 2 health apps (high prototypicality similar to top downloaded apps vs low prototypicality similar to research interventions) and reported willingness to download, attention, and predicted use of app features. Participants rated both apps (high and low) for aesthetics, ease of use, usefulness, perceived affordances, and intentions to use.ResultsMost participants (425/462, 92%) expected features for navigation or personal settings (eg, menu) in specific regions (eg, top corners). Features with summary graphs or statics were also expected by many (395-396 of 462, 86%), with a center placement expectation. A feature to “share with friends” was least expected among participants (203/462, 44%). Features fell into 4 unique categories based on attention and predicted use, including essential features with high (>50% or >231 of 462) predicted use and attention (eg, calorie trackers), flashy features with high attention but lower predicted use (eg, links to specific diets), functional features with modest attention and low use (eg, settings), and mundane features with low attention and use (eg, discover tabs). When given a choice, 347 of 462 (75%) participants would download the high-prototypicality app. High prototypicality apps (vs low) led to greater aesthetics, ease of use, usefulness, and intentions, (for all, P<.001). Participants thought that high prototypicality apps had more perceived affordances.ConclusionsIntervention designs that fail to meet a threshold of mHealth expectations will be dismissed as less usable or beneficial. Individuals who download health apps have shared expectations for features that should be there, as well as where these features should appear. Meeting these expectations can improve app evaluations and encourage use. Our typology should guide presence and placement of expected app features to signal value and increase use to impact preventive health behaviors. Features that will likely be used and are attention-worthy—essential, flashy, and functional—should be prioritized during app development.

Innovation Diffusion: The Influence of Social Media Affordances on Complexity Reduction for Decision Making.

Social media is a prominent communication platform. Its active usage permeates all generations and it is imperative that the platform be fully optimized for knowledge transfer and innovation diffusion. However, there are several considerations regarding platform usage, including media affordances. Social media affordances enable users to interact with the world around them through features of modality, agency, interactivity, and navigation. Previous studies have indicated that social media affordances significantly influence user behavior and usage. However, research exploring the effect of social media affordances on knowledge acquisition and the reduction of decision-making complexities is limited. Therefore, focusing on 179 paddy farmers in Malaysia, this study examined the effect of social media affordances on information quality, knowledge acquisition, and complexity reduction regarding innovation adoption decisions using a quantitative approach. This study’s findings reveal that social media affordances have a significant effect on perceived information quality, knowledge acquisition, and complexity reduction.

Emotion detection on webpages using biosensors integrated to a window-based dynamic control system

PurposeDetecting emotion on user experience of web applications and browsing is important in many ways. Web designers and developers find such approach quite useful in enhancing navigational features of webpages, and biomedical personnel regularly use computer simulations to monitor and control the behaviour of patients. On the other hand, law enforcement agents rely on human physiological functions to determine the likelihood of falsehood in interrogations. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users' emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors.Design/methodology/approachThe authors propose a novel method-a window dynamic control system that addresses the foregoing issues. Primary data were obtained from laboratory experiments during which forty-four volunteers had their synchronised physiological readings, skin conductance response (SCR), skin temperature (ST), eye movement behaviour and users’ activity attributes taken using biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronised physiological readings and uses them for two purposes. For both detection of optimal emotional responses and users' stress levels. The method's novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage.FindingsResults show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods.Research limitations/implicationsThe paper is limited to using a window control system to detect emotions on webpages, while integrated to biosensors and eye-tracker.Originality/valueThe originality of the proposed model is its resistance to overfitting and its ability to automatically assess human emotion (stress levels) while dealing with specific web contents. The latter is particularly important in that it can be used to predict which contents of webpages cause stress-induced emotions to users when involved in online activities.

Bumble bees strategically use ground level linear features in navigation

Extended ground level structures like roads or field edges can be important cues for navigating animals, seen for example in road-following pigeons. In a landscape devoid of skyline cues but with a rectangular grid of pathways and roads, we used harmonic radar to track free-flying bumble bees, Bombus terrestris. Individual bees consistently used ground level linear features for navigation in a wide range of behavioural contexts. Bee exploration flights, search behaviour and foraging routes were shaped by linear features, with bees frequently flying along and parallel to pathways and roads. Comparisons of flight trajectories across these behavioural contexts show that individuals modulated their use of linear features strategically with respect to their individual goals and experience. Bees searching for a feeder used linear features to target their search, while foragers often followed pathways to return to their hive without overshooting. These findings on a major pollinator have important implications for the placements of bee colonies for agriculture and floral resources for conservation.

Practical and comprehensive formalisms for modelling contemporary graph query languages

The industry-wide adoption of graph databases has been hindered due to the fragmentation in syntax and semantics of available graph query languages. As a result, several projects have been proposed by industry and academia to develop a standard query language by integrating features from existing practical graph query languages. A significant factor that can impact query language integration is the lack of common theoretical language formalisms. We propose common formalisms by extending conjunctive queries and union of conjunctive queries with Tarski’s relation algebra (CQT/UCQT). We use common graph query patterns to compare the expressive power of (CQT/UCQT) with two practical graph query languages - Cypher and PGQL. The query languages are analysed on the core features of graph pattern matching and graph navigation, revealing the common and exclusive characteristics for these languages. Overall, our study serves as a formal basis for comparing existing graph query languages and assists the move towards query language integration and interoperability between available graph database technologies.

IoT Bus Navigation System with Optimized Routing using Machine Learning

As the population in Egypt is ever expanding, it is reflected in the increase of the number of vehicles on the road. Public transportation is the solution and the number of available buses can cover a significant amount of the population demand. However, the outdated state of the transportation infrastructure, the static nature of the lines and indistinct schedules create a confounding and unappealing user experience which prompts the users to stray to cars for their needs. So, an Intelligent Urban Transportation System (IUTS) is a must. IUTS is a multi-layered system which provides the solution for most of these problems. It operates on different layers starting from a real time vehicle tracking for transparent and efficient management of assets, cash-less ticketing done through RFID cards, vehicle health and diagnostic data for creation of automated maintenance schedules and a friendly interactive driver interface. In this paper an approach based on combining all these technologies is discussed where the hardware component is implemented based on System-on-Chip technology with custom hardware to interface with the vehicle. The data collected from the on-board unit is sent to the cloud, and with the help of machine learning algorithms the dynamic responsiveness of the system is guaranteed. The proposed system outperforms other existing ones through the dynamic and optimized routing feature for the bus navigation to optimize the operating cost but still satisfy the passengers’demand.

42‐2: Distinguished Paper: Effects of Luminance Contrast and Font Size on Dual‐Plane HUD Legibility (“The Double 007 Rule for HUDs”)

Head‐up displays (HUDs) can provide important driving information such as speed and navigation directly to a driver within their immediate field of view, and thus improve driving experience. Specifically, a dual‐plane AR‐HUD can provide drivers with larger images with richer information, more intuitive information presentation, and enhanced navigation features. To ensure driver comfort, proper presentation format of the text on the dual‐plane HUD needs to be investigated. A human factors experiment was conducted to explore proper luminance contrast and font size of the text on a HUD. Twenty older and nine mid‐age drivers were instructed to recognize letters in fourteen levels of font size under each of eight levels of luminance contrast (ranging from 1.2:1, to 8:1) on each plane. The best test performance was observed at a luminance contrast of 7:1. We report the minimum and upper bound of 95% confidence interval of legible vertical visual angle for 99.5% of older drivers at each level of luminance contrast. While the typical legibility rule of thumb for font height vs. distance on standard displays is .007 (also known as the Bond rule), our experiment suggests that double that size (0.014) was needed to cover 99.5% of older drivers at a contrast ratio of 1.2:1 on a HUD.

Effects of luminance contrast and font size on dual‐plane head‐up display legibility (“The Double 007 Rule for HUDs”)

AbstractHead‐up displays (HUDs) can provide important driving information such as speed and navigation directly to a driver within their immediate field of view. Specifically, a dual‐plane AR‐HUD can provide drivers with larger images with richer information, more intuitive information presentation, and enhanced navigation features. To ensure driver comfort, proper presentation format of the text on the dual‐plane HUD needs to be investigated. A human factors experiment was conducted to explore proper luminance contrast and font size of the text on a HUD. Twenty older and nine mid‐age drivers were instructed to recognize letters in 14 levels of font size under each of eight levels of luminance contrast (ranging from 1.2:1, to 8:1) on each plane. The best test performance was observed at a luminance contrast of 7:1. We report the minimum and upper bound of 95% confidence interval of legible vertical visual angle for 99.5% of older drivers at each luminance contrast level. Although the typical legibility rule of thumb for font height versus distance on standard displays is 0.007 (known as the Bond rule), our experiment suggests that double that size (0.014) was needed to cover 99.5% of older drivers at a contrast ratio of 1.2:1 on a HUD.

Fighting with “the tyranny of Distance”: History of transport in Australia

Transport plays a vital role in the development of state of Australia. Transport can be compared with arteries of different industries of different types of economy. This infrastructure is especially important for Australia which has a great territory and low density of its population. That’s why the development of transport despite the remoteness of the continent from the Old World went parallel but sometimes even ahead of Europe. For the first time in Ukrainian science, an attempt has been made to investigate at the interdisciplinary level the formation of Australian state with the help of transport. Events are presented in chronological order because the very history of the discovery of the continent began from sailboats. Sailboat transport at the time of the discovery of Australia and the transportation of the first convicts, their supervising soldiers and administration together with free settlers from The Great Britain arrived on sailboats. The use of sailboats in transport along the coast of Australia is also clarified as well as hunting for whales, the future visits to the Pacific Islands and transportation from there valuable species of wood. The transition to steam shipping and later to motor shipping is distinguished, subsequently to motor shipping, innovative port changes of the coast of Australia for better floating and for better placement of cargo on steamers and their uploading taking into account the cost of human labour, of appropriate mechanisms and devices. Features of Australian river navigation are also considered. The development of land transport is studied. It is proved that the development of rail transport in the XIX st. became an important link in the transport system of Australia. Its advantages and obstacles which for many years stood in the way of development are allocated. The problems of different gauge in each Australian state are analysed and the difficulties of overcoming them are emphasized. Road transport and road construction have come out in Australia at a rapid space. It was found that road construction for Australian society was not only economic but also of great social importance because the soldiers who returned to their homeland from the First World War had their jobs on road constructions. The origin and development of aviation on the fifth continent are analysed. The figures of aviation designers are singled out. They pioneered aviation industry in Australia. Conclusions are drawn that this industry became dominant in Australia now.

An exploratory real-world wayfinding experiment: A comparison of drivers’ spatial learning with a paper map vs. turn-by-turn audiovisual route guidance

Turn-by-turn (TBT) route guidance technology installed on mobile phones is very popular among car drivers for wayfinding purposes. Previous studies examined their effect on spatial knowledge predominantly on pedestrians or in virtual environments. Drivers' spatial knowledge was experimentally compared in two random groups: audiovisual route guidance using the TBT navigation feature of the Google Maps app installed on a mobile phone, and a paper map. Participants drove their own vehicles to a predesignated destination in an unfamiliar residential neighborhood. Spatial knowledge tests (orientation, landmark recognition and route recognition) were subsequently administered. The scores of map-assisted drivers were uncorrelated and, on average, higher in orientation (deviation in direction), landmark recognition and route recognition (error percentage). The landmark recognition scores of drivers assisted by TBT route guidance were significantly lower with a very large effect size. The route recognition scores of drivers assisted by route guidance showed strong correlations with orientation and with landmark recognition scores. Results can be attributed to the differences in cognitive effort required to complete the wayfinding task: unlike memorizing a global map survey, passively following TBT audiovisual instructions does not require drivers to actively encode, transform, and continuously monitor their egocentric position in space. Drivers also showed somewhat poorer performance relative to studies with pedestrians which can be explained by the greater mental effort, compared to wandering on foot, involved in wayfinding while safely driving a rapidly moving vehicle. The future implications of the increasing dependence on mobile navigation technologies are further discussed.

Place recognition with deep superpixel features for brain-inspired navigation.

Navigation in primates is generally supported by cognitive maps. Such a map endows an animal with navigational planning capabilities. Numerous methods have been proposed to mimic these natural navigation capabilities in artificial systems. Based on self-navigation and learning strategies in animals, we propose in this work a place recognition strategy for brain-inspired navigation. First, a place recognition algorithm structure based on convolutional neural networks (CNNs) is introduced, which can be applied in the field of intelligent navigation. Second, sufficient images are captured at each landmark and then stored as a reference image library. Simple linear iterative clustering (SLIC) is used to segment each image into superpixels with multi-scale viewpoint-invariant landmarks. Third, highly representative appearance-independent features are extracted from these landmarks through CNNs. In addition, spatial pyramid pooling (SPP) layers are introduced to generate a fixed-length CNN representation, regardless of the image size. This representation boosts the quality of the extracted landmark features. The proposed SLIC-SPP-CNN place recognition algorithm is evaluated on one collected dataset and two public datasets with viewpoint and appearance variations.

Implementation of Smartphone Navigation Features by Combined Forces in Determining the Hazards of Terrorism in Poso

Implementation of Smartphone Navigation Features by Combined Forces in Determining the Hazards of Terrorism in Poso