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Exploring and articulating novel marketing concepts are essential for developing new marketing theories. Conceptual papers enhance the marketing field by reviewing current knowledge, identifying inconsistencies, highlighting gaps, offering insights, and proposing future research agendas. We investigate how scholars can transform conceptual ideas into robust articles by providing a guide for marketing researchers with five key strategies or beacons for overcoming challenges in conceptual writing. This year, winners of the 2024 AMS Review–Sheth Foundation Doctoral Competition for Conceptual Articles (DoCCA) are presented. [ABSTRACT FROM AUTHOR]

Current safety-critical applications, found in domains such as automotive networking, automated industries, and control systems, require deterministic and latency-bounded end-to-end communication, currently not supported by best-effort networks. Time-Sensitive Networking (TSN) is the most feasible approach to fulfill such requirements. Originating from the wired domain, their application to the wireless domain is now attracting attention. Besides some advances in time synchronization and scheduling, essential policies such as association with a wireless TSN (W-TSN), have not been explored. This paper analyses the necessary tools for a prospective client to accomplish association with the W-TSN without affecting ongoing time-sensitive traffic. We introduce three beacon-based methods to pre-synchronize and pre-schedule nodes willing to associate with the network. On top of the first full-stack Software Defined Radio (SDR) based IEEE802.11/Wi-Fi design, the proposed approaches are developed and tested in a real-world environment. A delay analysis shows a worst-case association delay of up to 1.8 s, and high accuracy synchronization on prospective clients' association frame receptions, with 100% of on-time arrivals, even with challenging scheduling timeslots as short as 128 μ s. [ABSTRACT FROM AUTHOR]

The performance of long baseline (LBL) positioning systems is significantly impacted by the distribution and positional calibration accuracy of underwater acoustic beacon arrays. In previous calibration methods for beacon arrays based on autonomous underwater vehicle (AUV) platforms, the slant range information of each beacon was processed independently, and each beacon was calibrated one at a time. This approach not only decreases the calibration efficiency but also leaves the positional calibration accuracy of each beacon highly susceptible to the navigation trajectory of the AUV. To overcome these limitations, an equivalent virtual LBL (EVLBL) positioning model is introduced in this paper. This model operates by adjusting the positions of each beacon according to the dead reckoning increments computed during the AUV's reception of positioning signals, effectively forming a virtual beacon array. Consequently, the AUV is capable of mitigating LBL positioning errors that arise from its motion by simultaneously receiving positioning signals from all beacons. Additionally, an overall calibration method for beacon arrays based on particle swarm optimization (PSO) is proposed. In this approach, the minimization of the deviation between the EVLBL trajectory and the dead reckoning trajectory is set as the optimization objective, and the coordinates of each beacon are iteratively optimized. The simulation results demonstrate that the proposed EVLBL-based PSO algorithm (EVPSO) significantly enhanced the calibration efficiency and positional accuracy of the beacon array. Compared with conventional methods, the estimation error of the beacon positions was reduced from 6.40 m to within 1.00 m. After compensating for the beacon array positions, the positioning error of the LBL system decreased from approximately 5.00 m (with conventional methods) to around 1.00 m (with EVPSO), demonstrating the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Birds and social insects represent excellent systems for understanding visually guided navigation. Both animal groups use surrounding visual cues for homing and foraging. Ants extract sufficient spatial information from panoramic views, which naturally embed all near and far spatial information, for successful homing. Although egocentric panoramic views allow for parsimonious explanations of navigational behaviors, this potential source of spatial information has been mostly neglected during studies of vertebrates. Here we investigate how distinct landmarks, a beacon, and panoramic views influence the reorientation behavior in pigeons (Columba livia). Pigeons were trained to search for a location characterized by a beacon and several distinct landmarks. Transformation tests manipulated aspects of the landmark configuration, allowing for a dissociation among navigational strategies. Quantitative image and path analyses provided support that the panoramic view was used by the pigeons. Although the results from some individuals support the use of beaconing, overall the pigeons relied predominantly on the panoramic view when spatial cues provided conflicting information regarding the goal location. Reorientation based on vector and bearing information derived from distinct landmarks as well as environmental geometry failed to account fully for the results. Thus, the results of our study support that pigeons can use panoramic views for reorientation in familiar environments. Given that the current model for landmark use by pigeons posits the use of different vectors from an object, a global panorama-matching strategy suggests a fundamental change in the theory of how pigeons use surrounding visual cues for localization. [ABSTRACT FROM AUTHOR]

This paper introduces collaborative localization algorithms for wireless sensor networks (WSNs) in outdoor environments without GPS. Using a limited number of beacons and anchor nodes, the proposed approach leverages machine learning techniques, specifically Random Forest Regression (RFR) enhanced by Smell Agent Optimization (SAO) and Golden Jackal Optimization Algorithm (GJOA), to optimize network performance and minimize localization errors. The scheme employs up to three beacon nodes to accurately determine ordinary nodes' positions. Evaluation shows that employing three beacon nodes reduces the average localization error (ALE) by up to 40% compared to using two. Moreover, the proposed model, RFGJ, exhibits resilience to increased node density, maintaining accuracy even with higher node densities. The RFGJ model outperforms the other evaluated models, consistently achieving lower ALE values and faster localization times than both the RFSA and RF models. This is evident from the RFGJ model's superior performance metrics during training, including the highest R2 value of 0.996 and the lowest Root Mean Squared Error (RMSE) value of 0.028. These findings establish the RFGJ model as a promising tool for optimizing collaborative localization in WSNs, enabling more efficient and reliable localization across various applications. [ABSTRACT FROM AUTHOR]

Icebergs and ice islands (large, tabular icebergs) present a significant hazard to marine vessels and infrastructure at a time when demand for access to Arctic waters is increasing. There is a growing demand for in situ iceberg tracking data to monitor their drift trajectories and improve models used for operational forecasting of ice hazards, yet the high cost of commercial tracking devices often prevents monitoring at optimal spatial and temporal resolutions. Here, we provide a detailed description of the Cryologger Ice Tracking Beacon (ITB), a low-cost, robust, and user-friendly data logger and telemeter for tracking icebergs and ice islands based on the Arduino open-source electronics platform. Designed for deployments of at least 2 years with an hourly sampling interval that is remotely modifiable by the end user, the Cryologger ITB provides long-term measurements of position, temperature, pressure, pitch, roll, heading, and battery voltage. Data are transmitted via the Iridium satellite network at user-specified intervals. We present the results of field campaigns in 2018 and 2019, which saw the deployment of 16 ITBs along the coasts of Greenland and Ellesmere and Baffin islands. The overall success of these ITB deployments has demonstrated that inexpensive, open-source hardware and software can provide a reliable and cost-effective method of monitoring icebergs and ice islands in the polar regions. [ABSTRACT FROM AUTHOR]

The mediation of cultural heritage is a significant concern in the field of history and culture valorization. Technologies such as HBIM (Historic Building Information Modeling), XR (Extended Reality), and Beacons offer highly promising solutions that have demonstrated their value in various heritage-related applications, namely 3D reconstruction, documentation, restoration, preservation, and mediation. The primary objective of this paper is to propose an approach that combines HBIM () and XR (), integrating Beacon sensors to create a rich cultural mediation experience. Our approach is based on an HBIM model of the site, enriched with multi-source semantic information stored in a NoSQL database. It also leverages Beacon sensors to deliver historical content related to the study site (Mosque Al-Quaraouiyine) based on the user's position, thereby providing a cultural mediation experience within an XR environment. This study resulted in the creation of an HBIM model of the study site, the integration of a MongoDB database for storing semantic data, the utilization of the Unity SDK to retrieve this data, and the deployment of Beacons for user position detection within the XR environment. These advancements led to the display of contextual historical and multimedia information through interactive panels, offering a rich and interactive experience. The added value of this project lies in its innovative combination of several modern technologies to provide an educational and immersive experience to users, while also paving the way for future developments towards the dissemination of cultural information based on new technologies. [ABSTRACT FROM AUTHOR]

Human marine activities are becoming increasingly frequent. The adverse marine environment has led to an increase in man overboard incidents, resulting in significant losses of life and property. After a drowning accident, the accurate location information of the drowning victim can help improve the success rate of rescue. In this paper, we explore a LoRa-based Maritime Position-Indicating Beacon System (LR-MPIBS). A low-power drowning detection circuit is designed in LR-MPIBS to detect drowning accidents in a timely manner after a person falls into the water. The instantaneous high current of the LoRa RF can lower the supply voltage and cause other modules to work abnormally. A fast current transient response circuit is proposed to solve the problem. LR-MPIBS includes a power ripple suppression circuit that can reduce the measurement errors and operational abnormalities caused by power ripple interference. We explore the impedance matching law of LoRa RF circuits through simulation experiments to improve the quality of LoRa communication. A data processing algorithm for personnel drift trajectory is proposed to alleviate the challenges caused by the raw positioning data with large deviations and high communication cost. The experimental results show that LR-MPIBS can automatically start and actively alarm within 3 s after a person falls into the water. The positioning cold start time is less than 50 s. The performance of communication distance is more than 5 km. The endurance of LR-MPIBS is 25 h (with a 30 s communication cycle). [ABSTRACT FROM AUTHOR]

This paper demonstrates how the complex interaction of a number of intrinsic and extrinsic taphonomic factors have differentially affected the relative preservation of the skeletal remains recovered from Beacon Island. These include: local geology and hydrology; flora and fauna; human interactions; and burial type (e.g. body position and number). The latter function to demonstrate that contemporary burials dating to 1629 can present markedly divergent taphonomic 'alterations', even those buried within close proximity to one-another. It is evident that alterations can arise in a very short-time frame (months to a few years) and their recognition in a modern context is thus of forensic relevance. These are accordingly illustrated and described relative to their potential to inform forensic interpretations in a modern case-work context. [ABSTRACT FROM AUTHOR]

safety beacon message (SBM) plays a pivotal role in the Internet of Vehicles (IoV), broadcasting crucial events and road conditions to nearby vehicles. Given the sensitive nature of the data, such as vehicle identity and location, ensuring privacy is paramount. The significance of this research lies in addressing the pressing need for comprehensive privacy protection in the IoV, especially as most existing schemes focus on safeguarding either vehicle identity or location data during exchanges with core servers. The primary objective of this article is to introduce an SBM separation algorithm, termed SBM-SA, designed to holistically protect both identity and location data. Utilising correlation analysis, the SBM-SA stands as an innovative anonymisation privacy algorithm. Through a simulated IoV environment, the accuracy and efficacy of an SBM-SA are meticulously analysed and juxtaposed against prevailing privacy protection schemes. The findings underscore the SBM-SA's potential to significantly enhance privacy measures in the IoV. Implications of this research extend to shaping future privacy protection strategies of the SBM, emphasising the need for holistic and robust solutions in an increasingly interconnected vehicular landscape. [ABSTRACT FROM AUTHOR]

Functional asymmetries of the avian visual system can be studied in monocularly occluded birds, as their hemispheres are largely independent. Right and left monocularly occluded homing pigeons and control birds under binocular view have been trained in a food localisation task in an octagonal outdoor arena provided with one coloured beacon on each wall. The three groups were tested after the removal of the visual beacons, so to assess their sun compass learning abilities. Pigeons using the left eye/right hemisphere system exhibited slower learning compared to the other monocular group. During the test in the arena void of visual beacons, the three groups of birds, regardless of their visual condition, were generally able to identify the training sector by exclusively relying on sun compass information. However, the directional choices of the pigeons with the left eye/right hemisphere in use were significantly affected by the removal of the beacons, while both control pigeons and birds with the right eye/left hemisphere in use displayed unaltered performances during the test. A subsample of pigeons of each group were re-trained in the octagonal arena with visual beacons present and tested after the removal of visual beacons after a 6 h fast clock-shift treatment. All birds displayed the expected deflection consistent to the sun compass use. While birds using either the left or the right visual systems were equally able to learn a sun compass-mediated spatial task, the left eye/right hemisphere visual system displayed an advantage in relying on visual beacons. [ABSTRACT FROM AUTHOR]

Biosensors are becoming more common in the healthcare industry, but battery life is a significant barrier to broader adoption. Another concern is that these sensors heavily rely on radio frequency technology, which is dangerous to the human body and the environment. This research presents an optical wireless communication (OWC) based battery-efficient adaptive superframe for real-time biosensors. To begin, OWC uses visible light for downlink and infrared for uplink, making it human-safe. Second, our retrofit technique makes sensor transmission delays and energy usage more efficient. Third, as we look into wearable sensors, we see that the one-of-a-kind continuous superframe structure saves energy and allows for emergency data handling via the deployment of an emergency beacon. Fourthly, we compare the simulation results to the IEEE 802.15.7 standard superframe timeline to evaluate the practicality of our suggested technique. Analytical expressions are formulated to predict and analyze endto-end delays, average energy consumption, and savings. The results show a significant improvement in energy savings and delays without incurring any additional overheads. [ABSTRACT FROM AUTHOR]

A rectangular rapid flashing beacon (RRFB) is a pedestrian crosswalk countermeasure system that cautions drivers by providing them with real-time warning about the presence of pedestrians in an upcoming crosswalk. This paper investigated the safety effectiveness of existing RRFBs installed in the state of Florida between 2013 and 2018. Additionally, traffic volume, roadway characteristics, and land-use mix were included as explanatory variables. The study evaluated 154 treated sites with RRFB installations and 158 control sites with similar characteristics. Safety performance functions (SPF) were developed, and crash modification factors (CMF) were calculated using the empirical Bayes (EB) methodology for various crash types. A CMF of 0.31 for total pedestrian crashes was estimated, showing that RRFBs have the potential to reduce 69% of total pedestrian-involved crashes. CMF for total vehicular crashes and rear-end crashes were also investigated to ascertain whether RRFBs have adverse effects on rear-end crashes. CMF for total vehicular crashes was found to be 1.14, showing that RRFBs do not have positive effect in reducing total vehicular crashes. Similarly, it was observed that CMF for the rear-end crashes was 1.11, indicating RRFBs might have adverse effect on rear-end crashes because vehicles needs to slow down or stop due to the presence of pedestrians. CMFunctions for significant variables for pedestrian, rear-end, and total crash models were also estimated in this study. An economic analysis indicated that the implementation of RRFBs will yield a benefit to cost ratio (calculated over 3 years) of approximately 85.5 with a 4% discount rate. [ABSTRACT FROM AUTHOR]

VANET is a special paradigm of high mobility ad hoc network that promotes communication among the vehicles to enhance traffic safety. Cooperative awareness is the basic principle of VANETs that is accomplished by periodic exchange of beacons/ WSMs between vehicles. Due to highly dynamic topology and irregular distribution of vehicles, there is a necessity of a flexible beaconing mechanism that maintains a balance between the required level of cooperative awareness and network load and overcomes the limitations of periodic beaconing scheme of IEEE 802.11p. We proposed a context-aware hybrid beaconing algorithm that piggybacks driver status in beacon and disseminates it to the neighboring vehicles to enhance safety. The complete context has been considered to get the value of driver status and initial network status using SBN. The proposed technique considers real-time network congestion status and dynamically adapts the transmission range and power parameters at PHY layer, and beacon interval and CW at MAC layer using EDCA mechanism. The performance of the proposed algorithm has been evaluated using SUMO and NS-3 based on PDR, WSM PDR, goodput, and EED. The proposed algorithm demonstrates comparable WSM PDR to the benchmark scheme of LIMERIC and outperforms periodic beaconing scheme by exhibiting 35% improvement in WSM PDR on CCH and 15% improvement in PDR on SCH. Further, our proposed approach depicts more realistic scenario by considering the complete context; and maintains balance between transmission of safety and non-safety messages, thus, preventing starvation of non-safety applications as compared to the techniques in the existing literature. [ABSTRACT FROM AUTHOR]

Logistics sustainability practices in industrial cases gain more attention recently especially when transportation efficiency becomes a bottleneck. The research of smart parking develops rapidly especially the thriving of Internet of Things (IoT). In this research, the industrial hazardous chemical vehicle (IHCV) consists of tractor and trailer. The vehicle coupling and decoupling occur frequently in order to fulfil logistics missions. The real-time dynamic indoor location information of both tractors and trailers are of great significance among users. Excessive time and human effort consumed in locating the vehicles lead to the transportation delay and disorderly parking exacerbate congestion inside the indoor parking garage. In this paper, we propose an IoT-enabled smart indoor parking system for logistics vehicles. A self-learning genetic tracking algorithm is developed to ensure the tracking performance. The feasibility and effectiveness of this solution architecture and algorithm are verified in a real-life chemical logistics company. The results show that the proposed algorithm not only performs constant improving location accuracy up to 96.7% after learning but also ensure the long-term use compared to the triangulation method. Moreover, disorderly parking can be identified by location cell partition as to eliminate potential risks. Improved logistics efficiency and lowered congestion situation contribute to the sustainable logistics. [ABSTRACT FROM AUTHOR]

The announcement of beacon technology in 2013 created a wave of excitement among pioneering retailers and marketing leaders, allowing them to send location-based messages to customers in-store. However, until present, the technology has not yet established a strong foothold in retailing. The present paper adopts a multi-method approach with the objective to 1) detail its main challenges in the market and 2) enlighten scholars and practitioners on smart use cases for in-store location-based marketing. The findings of the multiple data sources (i.e. review of academic and practitioner literature, in-depth interviews with retail technology experts and focus groups with consumers) allowed the authors to infer valid conclusions, along with recommendations for future research and actionable managerial advice. [ABSTRACT FROM AUTHOR]

The baseband signal of the 406 MHz COSPAS-SARSAT emergency beacon is a 144-bit or 112-bit data with 0 and 1 code, including the information bits and error correcting check bits. In order to improve the coding efficiency of the baseband signal for the 406 MHz transmitter in the STM32 micro-controller, this paper proposes a calculation method for the first BCH error correcting code (BCH-1) and the second BCH error correcting code (BCH-2) of the COSPAS-SARAST transmitter. First, conduct the data coding process by 64-bit integral data; then, compute the BCH (127, 106) code and the BCH (63, 51) code to obtain the respective error correcting codes for improving coding rate; next, generate the baseband signal according to the GB 14391-2021 coding format; finally, modulate the baseband signal into a 406 MHz-RF signal, send it out and complete the task of distress alerting. The experimental results show that the proposed STM32 microcontroller-based baseband signal generation method is effective, and the EPIRB (Emergency Position Indicating Radio Beacon) designed based on this method has reached the industry standard. [ABSTRACT FROM AUTHOR]

When performing indoor tasks, miniature swarm robots are suffered from their small size, poor on-board computing power, and electromagnetic shielding of buildings, which means that some traditional localization methods, such as global positioning system (GPS), simultaneous localization and mapping (SLAM), and ultra-wideband (UWB), cannot be employed. In this paper, a minimalist indoor self-localization approach for swarm robots is proposed based on active optical beacons. A robotic navigator is introduced into a swarm of robots to provide locally localization services by actively projecting a customized optical beacon on the indoor ceiling, which contains the origin and the reference direction of localization coordinates. The swarm robots observe the optical beacon on the ceiling via a bottom-up-view monocular camera, and extract the beacon information on-board to localize their positions and headings. The uniqueness of this strategy is that it uses the flat, smooth, and well-reflective ceiling in the indoor environment as a ubiquitous plane for displaying the optical beacon; meanwhile, the bottom-up view of swarm robots is not easily blocked. Real robotic experiments are conducted to validate and analyze the localization performance of the proposed minimalist self-localization approach. The results show that our approach is feasible and effective, and can meet the needs of swarm robots to coordinate their motion. Specifically, for the stationary robots, the average position error and heading error are 2.41 cm and 1.44°; when the robots are moving, the average position error and heading error are less than 2.40 cm and 2.66°. [ABSTRACT FROM AUTHOR]

Summary: In a vehicular ad hoc network (VANET) each node is required to transmit periodic and event‐driven messages. The periodic messages are also known as beacons and consist of the basic vehicle status, such as position, speed, direction, and any additional information required by a safety application. One of the main concerns faced with this technology is channel congestion, which often happens in scenarios with a high vehicular density like traffic jams. When the channel is congested, there are no guarantees for a reliable message delivery. For this purpose, several protocols have been proposed to resolve this issue. In this work we propose neighbor congestion avoidance protocol (NCAP) as a novel solution employing a proactive strategy with vehicle position prediction using Kalman filter and an efficient event‐driven message delivery scheme. When compared with other strategies in congested scenarios, NCAP was able to significantly decrease the number of beacons by 49%, while also reducing the number of event‐driven message retransmissions by approximately 81%. NCAP also presented better performance in regard to the number of collisions between messages and channel busy ratio. [ABSTRACT FROM AUTHOR]

The integration of human-centric approaches has gained more attention recently due to more automated systems being introduced into our built environments (buildings, roads, vehicles, etc.), which requires a correct understanding of how humans perceive such systems and respond to them. This paper introduces an Immersive Virtual Environment-based method to evaluate the infrastructure design with psycho-physiological and behavioral responses from the vulnerable road users, especially for pedestrians. A case study of pedestrian mid-block crossings with three crossing infrastructure designs (painted crosswalk, crosswalk with flashing beacons, and a smartphone app for connected vehicles) are tested. Results from 51 participants indicate there are differences between the subjective and objective measurement. A higher subjective safety rating is reported for the flashing beacon design, while the psychophysiological and behavioral data indicate that the flashing beacon and smartphone app are similar in terms of crossing behaviors, eye tracking measurements, and heart rate. In addition, the smartphone app scenario appears to have a lower stress level as indicated by eye tracking data, although many participants do not have prior experience with it. Suggestions are made for the implementation of new technologies, which can increase public acceptance of new technologies and pedestrian safety in the future. [ABSTRACT FROM AUTHOR]

Navigation is often regarded as one of the most-exciting use cases for Augmented Reality (AR). Current AR Head-Mounted Displays (HMDs) are rather bulky and cumbersome to use and, therefore, do not offer a satisfactory user experience for the mass market yet. However, the latest-generation smartphones offer AR capabilities out of the box, with sometimes even pre-installed apps. Apple's framework ARKit is available on iOS devices, free to use for developers. Android similarly features a counterpart, ARCore. Both systems work well for small spatially confined applications, but lack global positional awareness. This is a direct result of one limitation in current mobile technology. Global Navigation Satellite Systems (GNSSs) are relatively inaccurate and often cannot work indoors due to the restriction of the signal to penetrate through solid objects, such as walls. In this paper, we present the Pedestrian Augmented Reality Navigator (PAReNt) iOS app as a solution to this problem. The app implements a data fusion technique to increase accuracy in global positioning and showcases AR navigation as one use case for the improved data. ARKit provides data about the smartphone's motion, which is fused with GNSS data and a Bluetooth indoor positioning system via a Kalman Filter (KF). Four different KFs with different underlying models have been implemented and independently evaluated to find the best filter. The evaluation measures the app's accuracy against a ground truth under controlled circumstances. Two main testing methods were introduced and applied to determine which KF works best. Depending on the evaluation method, this novel approach improved the accuracy by 57% (when GPS and AR were used) or 32% (when Bluetooth and AR were used) over the raw sensor data. [ABSTRACT FROM AUTHOR]

Subsea navigation by autonomous underwater vehicles (AUVs) is a demanding task that involves the integration of inertial sensors, gyrocompasses, Doppler velocity loggers, and reference from acoustic beacons. In this paper, we propose to augment this information by providing an external measurement of heading change. We rely on the direction of sand ripples, which are abundant on the seabed near the shore and whose direction is, locally, constant. Thus, any apparent change in their directivity, as detected by the AUV, would reflect as a change in the vehicle's heading. Considering this, we developed a mechanism that detects regions of interest (ROIs) containing sand ripples within a synthetic aperture sonar (SAS) image, segments the ROI into highlight and shadow, and evaluates the angle difference between ROIs within two consecutive SAS images. For detection of sand ripples and estimation of angle difference, we employ two deep neural networks, while for segmentation we formulate a fuzzy-logic clustering. Taking advantage of a transfer learning approach, we trained the deep networks on simulated SAS images and on a large database of 2088 real SAS images, which we share for reproducibility. Results from real SAS images from three different sites show a good trade-off between precision and recall for sand-ripple detection, and an error of a few degrees in the heading change estimation, which well exceeds a geometrical-based benchmark. We also show performance from a real-time experiment for which we implemented our method on an AUV and estimated its heading change on-the-fly. [ABSTRACT FROM AUTHOR]

Summary: Vehicular safety applications are based on broadcasting periodic safety beacons on the IEE802.11p control channel. The CSMA MAC scheme adopted in the IEE802.11p cannot ensure the strict timeline and the high reliability when broadcasting these real time and critical messages since it does not consider the high mobility of vehicles, the limited network resources, and the variant traffic densities. Therefore, the design of an effective MAC scheme that takes in consideration these parameters represents a challenging task. Furthermore, the fixed beaconing rate results an overload on the commination channel and collisions especially in dense situations that delay beacons broadcast. In this paper, we propose a novel hybrid MAC scheme for fast and reliable broadcast of safety beacons. At first, it relies on a time slot reuse policy that considers the mobility features of vehicles while reducing transmission collisions. In addition, it adapts mathematically the beaconing rate to the traffic density based on vehicular velocity at the aim of optimizing the performance of the wireless channel. Simulation results show that our proposal outperforms significantly the IEEE802.11p CSMA MAC scheme and upgrades the performance of vehicular networks in broadcasting periodic safety beacons. [ABSTRACT FROM AUTHOR]

Protected wetlands such as deltas, lakes or rivers provide a sanctuary for many endangered species. In order to protect these areas from illegal human interventions, it is necessary to monitor the unauthorized entrance of motor boats. In order to mitigate such an impact, we have developed a network of floating beacons for underwater acoustic monitoring, using LoRa communication modules operating at 433 MHz. Such beacons should be equipped with compact antennas. In this paper, we use a genetic algorithm approach to design the compact, monopole antennas required for the beacons; size constraints would apply not only to the radiating element but also to the ground plane. Although the antenna input is unbalanced, such a small ground plane may yield common mode currents on the antenna feeder, which distort the radiation pattern of the antenna. In order to investigate the effect of the common mode currents, we developed a distance averaging method, while, for characterizing the antenna, we used a single-antenna method. For the experimental validation of the system in real conditions, a continuous monitoring of the lake was carried out. During the monitoring, multiple events generated by incursions of motor boats were successfully detected and recorded. [ABSTRACT FROM AUTHOR]

Nowadays, one of the most important objectives in health research is the improvement of the living conditions and well-being of the elderly, especially those who live alone. These people may experience undesired or dangerous situations in their daily life at home due to physical, sensorial or cognitive limitations, such as forgetting their medication or wrong eating habits. This work focuses on the development of a database in a home, through non-intrusive technology, where several users are residing by combining: a set of non-intrusive sensors which captures events that occur in the house, a positioning system through triangulation using beacons and a system for monitoring the user's state through activity wristbands. Two months of uninterrupted measurements were obtained on the daily habits of 2 people who live with a pet and receive sporadic visits, in which 18 different types of activities were labelled. In order to validate the data, a system for the real-time recognition of the activities carried out by these residents was developed using different current Deep Learning (DL) techniques based on neural networks, such as Recurrent Neural Networks (RNN), Long Short-Term Memory networks (LSTM) or Gated Recurrent Unit networks (GRU). A personalised prediction model was developed for each user, resulting in hit rates ranging from 88.29% to 90.91%. Finally, a data sharing algorithm has been developed to improve the generalisability of the model and to avoid overtraining the neural network. [ABSTRACT FROM AUTHOR]

COVID-19 has brought new hybrid learning environments with some students in the classroom and some others online, synchronously, due to the needs of social distancing. These new hybrid learning environments pose new challenges, for example for group collaboration. This paper presents Smart Groups, a system aimed at helping teachers to orchestrate collaboration in hybrid learning environments and assesses its usability and usefulness through a simulation study. Smart Groups identifies the students that are in the classroom and online, automates the creation of groups (recommending collaborative learning flow patterns to teachers and considering the previous work done by students), supports the communication among students and the use of additional tools and resources for collaboration, and helps maintain the safety distance among the students who are in the classroom. The usability of Smart Groups has been assessed through a mock-up by 60 users (41 students and 19 teachers) with the system usability scale (SUS) obtaining good results (mean = 75.47, standard deviation = 14.95, median = 76.25). A subgroup (10 teachers out of 19) carried out follow-up interviews using the technology acceptance model (TAM) and highlighted the usefulness of Smart Groups to orchestrate collaboration in hybrid learning environments. Implications for practice or policy:. • Smart Groups supports teachers in the orchestration of groups in hybrid learning environments. • Smart Groups facilitates group coordination and communication among students. • Smart Groups helps maintain the safety distance. [ABSTRACT FROM AUTHOR]

This research presents a vehicle ID-based congestion aware message (CAM) for beacon signals on the vehicle environment. At the MAC protocol of the vehicle environment, enhanced vehicle ID-based analysis model is given first. With the automobile ID embedded in their separate CAMs, the model weights the randomized back-off numbers chosen by cars engaging in the back-off procedure. This leads to identifying a car ID-based randomized back-off code, which reduces the likelihood of a collision due to the identical back-off number. A traffic density based-congestion control algorithm (TDCCA) is suggested in this research. The revised mathematical approach surpasses previous work's overall packet latency because just one-fourth of the congestion window is employed during the experiment. The research includes a congestion management method that adjusts the rate of CAM transmitted over the host controller to improve the efficiency of the model parameters. The method considers various circumstances, from nonsaturated to substantially saturated networks (in terms of congestion probability) and sparsely dispersed and teemed networks (in the form of vehicular intensity). The technique is run across various automobile ID-based back-off values for high-standard results analysis. The simulation outcomes in terms of packet delivery ratio, energy consumption, delay, success rate, and collision ensure the effectiveness of the TDCCA method. Even at high traffic densities, the automobile ID-based CAM following information method outperforms the typical fixed CAM frequency IEEE 802.11p, according to simulation findings for all back-off figures. [ABSTRACT FROM AUTHOR]

Visual recognition and localization of underwater optical beacons is an important step in autonomous underwater vehicle (AUV) docking. The main issues that restrict the use of underwater monocular vision range are the attenuation of light in water, the mirror image between the water surface and the light source, and the small size of the optical beacon. In this study, a fast monocular camera localization method for small 4-light beacons is proposed. A YOLO V5 (You Only Look Once) model with coordinated attention (CA) mechanisms is constructed. Compared with the original model and the model with convolutional block attention mechanisms (CBAM), and our model improves the prediction accuracy to 96.1% and the recall to 95.1%. A sub-pixel light source centroid localization method combining super-resolution generative adversarial networks (SRGAN) image enhancement and Zernike moments is proposed. The detection range of small optical beacons is increased from 7 m to 10 m. In the laboratory self-made pool and anechoic pool experiments, the average relative distance error of our method is 1.04 percent, and the average detection speed is 0.088 s (11.36 FPS). This study offers a solution for the long-distance fast and accurate positioning of underwater small optical beacons due to their fast recognition, accurate ranging, and wide detection range characteristics. [ABSTRACT FROM AUTHOR]

Free space optical (FSO) communication can support various unmanned aerial vehicles' (UAVs) applications that require large capacity data transmission. In order to perform FSO communication between two terminals, it is essential to employ a pointing, acquisition, and tracking (PAT) system with an efficient and optimal performance. We report on the development of a common optical-path-based FSO communication system, tailored for applications in UAVs. The proposed system is equipped with a quadrant photodiode (QPD)-based PAT system without an additional beacon beam subsystem. The presented approach reduced the structural complexity and improved the tracking efficiency for the same size, weight, and power (SWaP). To achieve a robust FSO link in a dynamic UAV environment, the observability and controllability were obtained based on the linearized control according to the incident beam size on the QPD, which was verified by optical simulation and experiments. As a result, the QPD-based PAT system for implementing FSO links demonstrated an up to 4.25 times faster tracking performance. Moreover, the FSO link experimentally confirmed the 1.25 Gbps full-duplex error-free communication at a 50 m distance. [ABSTRACT FROM AUTHOR]

Singe-beacon localization technology can help Autonomous Underwater Vehicles (AUVs) to obtain precise positions by deploying only one beacon. It is considered as a promising way, benefiting from saving much time and labor compared with traditional Long-Baseline Localization (LBL). A typical single-beacon localization scheme contains two essential questions: the initial observability problem and long-endurance trajectory tracking problem. Aiming at these core problems, a comprehensive solution for single-beacon localization is described in this paper. An multi-hypothesis initial position discriminant method is proposed firstly, which helps to achieve accurate initial location based on observability analysis. Then, an Adaptive Network Fuzzy Inference System (ANFIS)-improved Extended Kalman Filter (EKF) method is proposed, in which single-beacon measuring information is fused with off-the-shelf sensors, including DVL, Compass, etc. ANFIS-EKF can help to improve trajectory tracking precisions by restraining the heavy loss of linearization in conventional EKF. Both simulation and field tests are conducted to verify the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation. [ABSTRACT FROM AUTHOR]

Phaeocystis globosa is a marine-bloom-forming haptophyte with a polymorphic life cycle alternating between free-living cells and a colonial morphotype, that produces high biomass and impacts ecological structure and function. The mechanisms of P. globosa bloom formation have been extensively studied, and various environmental factors are believed to trigger these events. However, little is known about the intrinsic biological processes that drive the bloom process, and the mechanisms underlying P. globosa bloom formation remain enigmatic. Here, we investigated a P. globosa bloom occurring along the Chinese coast and compared the proteomes of in situ P. globosa colonies from bloom and dissipation phases using a tandem mass tag (TMT)-based quantitative proteomic approach. Among the 5540 proteins identified, 191 and 109 proteins displayed higher abundances in the bloom and dissipation phases, respectively. The levels of proteins involved in photosynthesis, pigment metabolism, nitrogen metabolism, and matrix substrate biosynthesis were distinctly different between these two phases. Ambient nitrate is a key trigger of P. globosa bloom formation, while the enhanced light harvest and multiple inorganic carbon-concentrating mechanisms support the prosperousness of colonies in the bloom phase. Additionally, colonies in the bloom phase have greater carbon fixation potential, with more carbon and energy being fixed and flowing toward the colonial matrix biosynthesis. Our study revealed the key biological processes underlying P. globosa blooms and provides new insights into the mechanisms behind bloom formation. [ABSTRACT FROM AUTHOR]

A systematic oceanographic monitoring and management requires an effective marine tracking system. It helps the localization of different marine assets, their border control and in encountering emergency situations. Thus, a reliable marine tracking system is always required to ensure a safe marine environment for shippers, fishers, sailors and other marine assets. Nowadays due to the evolution in wireless sensor network (WSN) technology, their easy and inexpensive deployment can be seen in different fields such as agriculture, medical, industries and IoT. The implementation of WSN in the marine environment comes with various issues due to the complex behavior of the marine environment and thus affects the reliability of the system. In this paper, a WSN-based marine tracking protocol sailing is presented, which identifies the location of marine assets reliably through the genetic firefly (GEFIR) algorithm. The system comprises sensor nodes, sink nodes, server-client terminals and a base station. The protocol uses the application and contact layers to create a group of beacon nodes (boats) based on the geographical location to conserve energy and increase data reliability. GEFIR algorithm is implemented to give a precise and more convenient data to the WSN for the mariners. The results show a better performance for latency calculation through the WSN- and GEFIR-based sailing protocol. The system generates the alert to nodes (sailors) in case they are moving out from a specified region and sends their location for further communication. [ABSTRACT FROM AUTHOR]

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Autonomous underwater vehicle networks is a significant resource for aquatic life maintenance and monitoring underwater pollution. It is necessary to study the underwater localization algorithms which self-localize themselves. The proposed work concentrates only on the range-free localization model with a goal is to use only very few sensing nodes in the network with low cost and high battery power to self-localize themselves. Few beacon nodes have been used to localize the sensor nodes in the definite position of the network. Compressive sensing theory based on hop count information for localizing the sensor nodes has also been used for localization. This research aims to collect the connectivity information of all the nodes in the network with compressive sensing theory and improve the localization accuracy. The analysis presents that the proposed method works well with location accuracy. Compressive Sensing Node Localization reduces cost and enhances sensors' energy efficiency compared to other underwater localization algorithms. [ABSTRACT FROM AUTHOR]

Emergency fire situations in tunnels can be especially dangerous when occurring in long underground or subsea tunnels, particularly when evacuation on foot is the only alternative. This paper presents the results from a study comparing different visual and acoustic measures to facilitate efficient and safe emergency evacuation and their effect on people's self-rescue behaviour in response to a tunnel fire. Eighty-one participants evaluated seven different scenarios in virtual reality with or without visual and acoustic supporting measures (i.e. signs, lights, acoustic beacons) to find their way to emergency doors. Objective behavioural data, such as orientation, and walking speed, were collected. The results suggest that the distance between the emergency doors increases uncertainty and affects the time to self-rescue significantly, with four times longer times for 500 m than 250 m between doors. Additionally, the use of continuous guiding lights positively supported orientation and walking speed, with 97 % of the participants finding their way and showing a reduction of time to reach the emergency door of 10–20 s. The study underscores the importance in the proper visual and acoustic evacuation measures for the wayfinding of emergency exits, improving self-rescue of people. • Visual and acoustic measures to support self-evacuation were tested. • The study examines the impact of different measures on users' behaviour during evacuation. • Virtual Reality was used as method for evaluating measures due to ethical issues. • Black smoke simulation was developed for the VR scenarios. • Both type, position and distance between measures highly impacted time to escape. [ABSTRACT FROM AUTHOR]