Space Navigation Research Articles

Pentecostalism and the (de)construction of ‘Otherness’: Experiences of black African students at a South African University

AbstractDrawing on fieldwork conducted at a South African University, this qualitative study examines the lived experiences of black foreign students studying and living in South Africa. The study sought to understand the role that Pentecostalism plays in mediating the everyday experiences of black foreign students within and beyond the university campus spaces. A total of 30 student patrons from two Pentecostal churches were purposively sampled for the study. Data were collected using qualitative methods, including in‐depth interviews, participant observation, and informal conversations. Data were recorded, transcribed, and thematically analysed. The study findings revealed that for many African foreign students in South Africa, Pentecostalism mediated their sense of being on campus and allowed them to deal with the real and perceived social disarticulation fashioned by xenophobic terrains and attendant socio‐material anxieties. I assert that Pentecostal communities helped African foreign students to embed themselves and adjust to life on campus. These communities allowed them to forge convivial relationships and mutuality with fellow students and other Church members. Building on extant scholarly arguments and debates on Pentecostalism and student mobilities, I argue that Pentecostalism play(ed) a central role in the (de)construction of a sense of ‘Otherness’ through socio‐spiritual rituals including, sermons (the word), proselytisation and other social practices, albeit with varying degrees of success. Although Pentecostal networks strongly mediated black African foreign students' everyday navigation in precarious social spaces, the anxiety and the feeling of otherness are not completely removed.

Next-generation materials for space electronics: A conceptual review

Space electronics play a pivotal role in enabling modern space missions, facilitating communication, navigation, remote sensing, and scientific exploration. However, the extreme conditions of space, including temperature variations, radiation exposure, and mechanical stresses, pose significant challenges for the materials used in electronic components. This conceptual review explores the next-generation materials for space electronics, aiming to address these challenges and push the boundaries of performance and reliability. The review begins by outlining the fundamental requirements for space electronics materials, emphasizing the need for extreme temperature resistance, radiation shielding, mechanical strength, and thermal conductivity. It then surveys the current state-of-the-art materials, including silicon-based materials, compound semiconductors, polymers, ceramics, and composites, highlighting their strengths and limitations in space applications. Furthermore, the review discusses emerging materials and technologies, such as 2D materials, organic electronics, quantum materials, and metamaterials, which hold promise for revolutionizing space electronics. Implementation strategies are proposed, considering factors like integration with existing systems, scalability, cost-effectiveness, environmental impact, and regulatory compliance. Through this conceptual review, insights are provided into the potential applications of next-generation materials in satellites, space probes, exploration missions, and beyond. The conclusion summarizes key findings, underscores potential implications for the future of space electronics, and offers recommendations for further research and development. By advancing the state of materials science for space electronics, this review aims to contribute to the ongoing exploration and utilization of space for the benefit of humanity.

Innovating Deterrence Strategies in the New Space Age

In recent decades, space has become a crucial arena in international relations, reshaping geopolitical dynamics due to the increased reliance on satellite technology and strategic space assets. Nations globally recognize the economic and strategic advantages of space, leading to cooperation and competition. The expanding use of space for communication, navigation, surveillance, and exploration has become integral to modern societies. The commercial space industry, driven by private entities, contributes significantly to space endeavors. This heightened reliance on space assets necessitates robust space security policies to protect critical systems and maintain technological advantages. Traditionally, deterrence theories focused on terrestrial domains, but the unique characteristics of space demand a paradigm shift. The article introduces a novel perspective on space deterrence, emphasizing strategic capabilities, alliances, and a nuanced understanding of potential aggressors. Core components include denial, resilience, and cost imposition strategies. Military strength, alliances, and space-based nuclear assets play roles in conventional and nuclear space deterrence. Dissuading military aggression involves operational concepts, resilience, and strategic costs. Shaping aggressor thinking requires perception management, confidence-building, and norms. Crafting denial and punishment strategies involves arms control initiatives. Understanding potential aggressors involves assessing motives, aligning interests, and evaluating orbital escalation. The multidimensional nature of space deterrence converges to create a robust framework for dissuading aggression, ensuring a stable and secure celestial environment.

Deceiving Humans and Machines Alike: Search-based Test Input Generation for DNNs Using Variational Autoencoders

Due to the rapid adoption of Deep Neural Networks (DNNs) into larger software systems, testing of DNN-based systems has received much attention recently. While many different test adequacy criteria have been suggested, we lack effective test input generation techniques. Inputs such as images of real-world objects and scenes are not only expensive to collect but also difficult to randomly sample. Consequently, current testing techniques for DNNs tend to apply small local perturbations to existing inputs to generate new inputs. We propose SINVAD (Search-based Input space Navigation using Variational AutoencoDers), a way to sample from, and navigate over, a space of realistic inputs that resembles the true distribution in the training data. Our input space is constructed using Variational Autoencoders (VAEs), and navigated through their latent vector space. Our analysis shows that the VAE-based input space is well-aligned with human perception of what constitutes realistic inputs. Further, we show that this space can be effectively searched to achieve various testing scenarios, such as boundary testing of two different DNNs or analyzing class labels that are difficult for the given DNN to distinguish. Guidelines on how to design VAE architectures are presented as well. Our results have the potential to open the field to meaningful exploration through the space of highly structured images.

Individual differences in knowledge network navigation

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants’ performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation.

Designs of Optomechanical Acceleration Sensors with the Natural Frequency from 5 Hz to 50 kHz

In many applications, such as space navigation, metrology, testing, and geodesy, it is necessary to measure accelerations with frequencies ranging from fractions of a hertz to several kilohertz. For this purpose, optomechanical sensors are used. The natural frequency of such sensors should be approximately ten times greater than the frequency of the measured acceleration. In the case of triaxial acceleration measurements, a planar design with two sensors that measure accelerations in two perpendicular in-plane directions and a third sensor that measures out-of-plane acceleration is effective. The mechanical characteristics of the existing designs of both in-plane and out-of-plane types of sensors were analyzed, and the improved designs were elaborated. Using numerical simulation, the dependencies of the natural frequency level in the range from several hertz to tens of kilohertz on the designs and geometric parameters of opto-mechanical accelerometers were modeled. This allows one to select the accelerometer design and its parameters to measure the acceleration at the assigned frequency. It is shown that the opto-mechanical accelerometers of the proposed designs have reduced dissipation losses and crosstalk.

Space classification for indoor pedestrian navigation with morphological and functional characteristics

AbstractIndoor navigation networks serve as the foundation for indoor pedestrian navigation services. However, current graph‐based topological network models cannot easily represent complex indoor structures in a manner consistent with user behaviour and cognitive patterns, and thus cannot support fine‐grained indoor navigation analysis services. To enhance the rationality of the model, we considered the influences of morphological and functional characteristics of indoor spaces on pedestrian movement and proposed a method for classifying navigation spaces. This method, based on convex space segmentation, defines morphological and functional characteristic functions, classifying indoor navigation spaces as either corridors or open spaces, which suitable for representing as median axis models or visual graphs, respectively. These categories supported the creation of topological network models for route planning analysis. Indoor map experiments confirmed the effectiveness of our method in identifying various types of corridors and open spaces, that addressing the limitations of width‐based parameters, even in complex indoor settings.

93 Investigating the minimal requirements for startup procurement by healthcare institutions in Ontario, Canada

OBJECTIVES/GOALS: The primarygoal is to understand the challenges and barriers associated with the procurement of innovative technologies.Specifically, our research will answer the following question: what are the minimal requirements for a startup’s solution to beprocuredby anOntariohealthcare institution? METHODS/STUDY POPULATION: Participants will include procurement professionals at startups, healthcare institutions, and procurement facilitating agencies. Semi-structured interviews will be conducted in order to understand different procurement pathways and the possible procurement related gaps or barriers that startups face. Through qualitative ethnographic methods, participant interviews will characterize existing relationships and examine the rationale behind startup procurement decision-making. Data collection will include recordings, verbatim transcripts, and researcher field notes. Through inductive qualitative analysis, the data will be examined to build an intervention to assist in startup procurement. RESULTS/ANTICIPATED RESULTS: Our investigation will yield insight into expectations between hospital procurement requirements and startup procurement. The qualitative analysis will identify targets for engagement, and appropriate actors that can bridge gaps. Our results will identify pathways for procurement and the minimal procurement requirements to aid startup procurement planning. Our research will support innovators by delivering an intervention that will enable easier implementation of market ready solutions in a Canadian context. In line with principles from the National Center for Advancing Translational Sciences, this research can be used towards enhancing efficiency, speed of translation, and innovation. DISCUSSION/SIGNIFICANCE: We will contextualize the needs of start-ups and empower them to understand their procurement ecosystem. Facilitating better navigation of the procurement space allows for innovators to present solutions that healthcare organizations can adopt, resulting in improved clinical and patient outcomes.

Towards Efficient Coordination in Multi-Agent Reinforcement Learning through Hybrid Information-Driven Approaches

Abstract: This paper introduces a novel framework to enhance coordination in multi-agent reinforcement learning (MARL) systems by integrating mutual information (MMI) principles with information-driven strategies. Firstly, we propose a variational approach leveraging MMI to promote coordinated behaviors among agents by regulating the cumulative return alongside the simultaneous mutual information between multi-agent actions. Through the introduction of a latent variable inducing nonzero mutual information and the application of a variational bound, a tractable lower bound is derived for the MMI-regularized objective function. This bound combines maximum entropy reinforcement learning with reducing uncertainty in other agents' actions. Subsequently, we present a practical algorithm, Variational Maximum Mutual Information Multi-Agent Actor-Critic (VM3-AC), utilizing policy iteration to maximize the derived lower bound, following a centralized learning with decentralized execution (CTDE) paradigm. Secondly, we explore the challenges of large state spaces and limited computational resources in distributed multi-agent systems, proposing a hybrid information-driven MARL approach. This approach integrates informationtheoretic models as heuristics to aid navigation in sparse state spaces, complemented by information-based rewards within an RL framework to learn higher-level policies efficiently. Our preliminary findings suggest that this hybrid approach could enhance exploration efficiency significantly, demonstrating approximately three orders of magnitude improvement over naive baseline metrics. Although still in its early stages, this work presents a promising direction for future research in achieving efficient coordination in MARL systems

SOCIALGYM 2.0: Simulator for Multi-Robot Learning and Navigation in Shared Human Spaces

We present Social Gym 2.0, a simulator for multi-agent navigation research. Our simulator enables navigation for multiple autonomous agents, replicating real-world dynamics in complex indoor environments, including doorways, hallways, intersections, and roundabouts. Unlike current simulators that concentrate on single robots in open spaces, Social Gym 2.0 employs multi-agent reinforcement learning (MARL) to develop optimal navigation policies for multiple robots with diverse, dynamic constraints in complex environments. Social Gym 2.0 also departs from the accepted software design standards by employing a configuration-over-convention paradigm providing the capability to benchmark different MARL algorithms, as well as customize observation and reward functions. Users can additionally create their own environments and evaluate various algorithms, based on both deep reinforcement learning as well as classical navigation, using a broad range of social navigation metrics.

Main directions of implementing research results of artificial intelligence systems into domestic production

Speaking about the need to create technological sovereignty in the sphere of the domestic economy production, we realize how multidimensional and costly in all types of resources is the activity that has critical time constraints. In addition to sovereignty as a concept in the broad sense, technological sovereignty is created to increase the efficiency of Russian economic activity. One of the directions of increasing the production activities efficiency is the so-called production digitalization. This notion is fundamentally different from the production processes automation of the 1970s and 1980s. With the advent of the Internet and space navigation capabilities of modern astronautics, the approach and level of tasks in organizing human life have completely changed. Wireless communication, the Internet of Things, unmanned vehicle including aircraft are the terms of the XXI century. The purpose of the study is to define the theoretical principles of digitalization in the manufacturing process for those who are interested in this issue. The authors also attempt to provide a summary of popular classifications of digital technologies by functionality and application sectors. Based on the theoretical principles of digitalization and the given classification, we identify the main directions of production digitalization.

Time transfer over 113 km free space laser communication channel.

The space time frequency transfer plays a crucial role in applications such as space optical clock networks, navigation, satellite ranging, and space quantum communication. Here, we propose a high-precision space time frequency transfer and time synchronization scheme based on a simple intensity modulation/direct detection (IM/DD) laser communication system, which occupies a communication bandwidth of approximately 0.2%. Furthermore, utilizing an optical-frequency comb time frequency transfer system as an out-of-loop reference, experimental verification was conducted on a 113 km horizontal atmospheric link, with a long-term stability approximately 8.3 × 10-16 over a duration of 7800 seconds. Over an 11-hour period, the peak-to-peak wander is approximately 100 ps. Our work establishes the foundation of the time frequency transfer, based on the space laser communication channel, for future ground-to-space and inter-satellite links.

X-ray pulsar observation signals simulation method at the spacecraft in near-Earth space

The near-Earth space holds significant strategic value, and X-ray pulsar-based navigation in this region can diversify navigation methods, enhancing the safety and autonomy of spacecraft. Due to the challenges and high costs associated with obtaining actual measurements of pulsars in near-Earth space, the simulation technology for X-ray pulsar signals in this region can provide input for demonstrating the feasibility of technical solutions and experiments related to the application of X-ray pulsar-based navigation in near-Earth space. Therefore, this paper proposes a method for simulating X-ray signals in near-Earth space. Firstly, a scale transforming method is employed to generate a photon arrival time sequence at the spacecraft that includes energy information. Subsequently, the atmospheric transmittance model is utilized for photon selection, obtaining a sequence of photons that have passed through the atmosphere after absorption. Finally, experimental validation of the proposed algorithm is conducted using Crab pulsar data measured by the Insight-HXMT. The similarity between the simulated data and the measured data is evaluated in terms of profiles, phases, and energy spectra. Simulation experiments demonstrate that the time delay estimation error caused by the simulation algorithm is less than 17.17 us. When the observation tangent point altitude is in the range of 160 km to 180 km, the Pearson correlation coefficient of the profiles between simulated and measured data is 73.74 %. The Pearson residuals of the energy spectra are evenly distributed between −0.2 and 0.2, indicating a good level of similarity between the two.

A Survey of PAPR Techniques Based on Machine Learning.

Orthogonal Frequency Division Multiplexing (OFDM) is the modulation technology used in Fourth Generation (4G) and Fifth Generation (5G) wireless communication systems, and it will likely be essential to Sixth Generation (6G) wireless communication systems. However, OFDM introduces a high Peak to Average Power Ratio (PAPR) in the time domain due to constructive interference among multiple subcarriers, increasing the complexity and cost of the amplifiers and, consequently, the cost and complexity of 6G networks. Therefore, the development of new solutions to reduce the PAPR in OFDM systems is crucial to 6G networks. The application of Machine Learning (ML) has emerged as a promising avenue for tackling PAPR issues. Along this line, this paper presents a comprehensive review of PAPR optimization techniques with a focus on ML approaches. From this survey, it becomes clear that ML solutions offer customized optimization, effective search space navigation, and real-time adaptability. In light of the demands of evolving 6G networks, integration of ML is a necessity to propel advancements and meet increasing prerequisites. This integration not only presents possibilities for PAPR reduction but also calls for continued exploration to harness its potential and ensure efficient and reliable communication within 6G networks.

Recent Advances in Preparing Transparent Phosphor Ceramics for High-Index Color Rendering and High-Power Lighting.

In recent years, high-power white light-emitting diode (wLED)/laser diode (wLD) lighting sources based on transparent phosphor ceramic (TPC) materials have attracted increasing application interest in automotive headlights, projection displays, and space navigation lighting due to their superior brightness, lighting distance, compactness, lifespan, and environmental resistance compared with the widely used phosphor-converted wLEDs. However, preparing TPC-converted wLEDs/wLDs with high color rendering index (CRI) remains a huge challenge, which limits their widespread application. In this review, we summarize the recently adopted strategies for constructing TPCs to develop high-power wLEDs/wLDs with high CRI values (>75). The construction protocols were categorized into four groups: host regulation, red-emitter doping, host regulation/red-emitter doping combination, and composite structure design. A comprehensive discussion was conducted on the design principles, photoluminescent properties, and device performances for each strategy. The challenges and future trends of high-power and high-CRI wLEDs/wLDs based on TPCs are also discussed toward the end of this review.

Overview of Bridge Crane Control

This paper summarizes the research hotspot of underactuated mechanical system in nonlinear control field, and emphasizes its wide application in practical engineering, including space vehicle, inverted pendulum and navigation system. The Chinese government has supported the construction crane industry through a series of policies and regulations, providing guidance for its safe production and technical specifications. In the context of social development, the application demand of bridge gantry cranes in narrow environments is increasing, and the future development trend will focus on the direction of intelligence, science and technology and humanization. In recent decades, the research results on the positioning and pendulum of bridge crane at home and abroad are divided into open loop and closed loop control methods, and the control methods are described in detail in this paper.

A review study of space perception and navigation of people with low vision: is simulated low vision a reliable methodology?

The inclusion of visually impaired participants in research protocols concerning their perception of space and navigation is essential for the reliability of the results, given the strategies developed by the people concerned in everyday life. However, the diversity of visual impairments, the scarcity of participants and possible safety issues due to obstacles in the physical space induce limitations and prompt researchers to look into alternative methodologies. Simulated low vision is seen as an option. This method involves sighted participants wearing goggles with customized filters or watching processed images in virtual environments. The objective of this study is to investigate the reliability of simulated low vision as a research method to describe the space perception and navigation of people with visual impairment. We conducted a literature review and identified 36 quantitative studies on low vision spatial performance involving multiple user groups. Simulated low vision proved effective in small-scale spatial ability evaluation, such as object detection and distance estimation, but remained challenging regarding large-scale capacity, such as navigation with mobility requirement. Advances in virtual environments suggest that they are a good alternative to goggles and screen displays because of their precision in mimicking ocular problems in simulation settings. Finally, the use of head-mounted-display (HMD) by people with real low vision could open up the possibility of greater testing in safer and controlled conditions, but requires confirmation of the validity of the protocols.

Fast surface signal extraction method for photon point clouds with strong background noise without prior altitude information.

It is extremely challenging to rapidly and accurately extract target echo photon signals from massive photon point clouds with strong background noise without any prior geographic information. Herein, we propose a fast surface detection method realized by combining the improved density-dimension algorithm (DDA) and Kalman filtering (KF), termed the DDA-KF algorithm, for photon signals with a high background noise rate (BNR) to improve the extraction of surface photon signals from spacecraft platforms. The results showed that the algorithm exhibited good adaptability to strong background noise and terrain slope variations, and had real-time processing capabilities for massive photon point clouds in large-scale detection range without prior altitude information of target. Our research provides a practical technical solution for single-photon lidar applications in deep space navigation and can help improve the performance in environments characterized by strong background noise.

Assessing Human Spatial Navigation in a Virtual Space and its Sensitivity to Exercise.

Spatial navigation (SN) is the ability to locomote through the environment, which requires an understanding of where one is located in time and space. This capacity is known to rely on the sequential firing of place cells within the hippocampus. SN is an important behavior to investigate as this process deteriorates with age, especially in neurodegenerative disorders. However, the investigation of SN is limited by the lack of sophisticated behavioral techniques to assess this hippocampal-dependent task. Therefore, the goal of this protocol was to develop a novel, real-world approach to studying SN in humans. Specifically, an active virtual SN task was developed using a cross-platform game engine. During the encoding phase, participants navigated their way through a virtual city to locate landmarks. During the remembering phase, participants remembered where these reward locations were and delivered items to these locations. Time to find each location was captured and episodic memory was assessed by a free recall phase, including aspects of place, order, item, and association. Movement behavior (x, y, and z coordinates) was assessed through an asset available in the game engine. Importantly, results from this task demonstrate that it accurately captures both spatial learning and memory abilities as well as episodic memory. Further, findings indicate that this task is sensitive to exercise, which improves hippocampal functioning. Overall, the findings suggest a novel way to track human hippocampal functioning over the course of time, with this behavior being sensitive to physical activity training paradigms.

Signals of opportunity for space navigation: An application-oriented review

Space navigation using X-Ray pulsars is known as opportunistic navigation, where we rely on signals of opportunity from natural phenomena to determine navigation solutions for spacecraft. However, this definition becomes too small or shallow, as it doesn't include other forms of navigation using natural beacons reported over the last two decades. Since a classification or review of all opportunistic techniques is still missing, this article presents the first survey on the field of signals of opportunity (SOOP), and introduces a framework for this scientific area, where natural beacons could be associated to stars, distant planets or natural phenomena, and signals could come with distinct characteristics and wavelengths. The new classification groups dozens of existing technologies of navigation using natural beacons, making easier for newcomers to interpret quickly a variety of works and mathematical formalisms. In addition, we deepen into an engineering perspective on the ongoing status of SOOP-based navigation, highlighting what is required to achieve the level of readiness on the methods that still on theory. We also give answer to a number of open questions, such as e.g. what criterion defines if a signal from a given natural beacon could be used or not for navigational purposes, as well as what is the minimum intersatellite distance that we can detect using an opportunistic signal, what type of signal characteristics we need from natural phenomena to generate navigation solutions or how far apart natural beacons preferentially need to be. These results enrich the field and become fundamental with an increasing interest of the space industry to bring novel forms of navigation into low-cost spacecraft of limited hardware capabilities (such as Cubesats).Furthermore, using results from past remote sensing missions, we preliminary found that Earth's lightning is a natural resource available in large scale and in sufficient variability that can be potentially used for relative opportunistic navigation. The physics of the problem is introduced, where at least theoretically, multiple lightning events can be used to map the arrival times to cooperating spacecraft, fixing their positions relative to each other independently from ground.