Mission-critical Tasks Research Articles

Smart IoRT Networks: AI-Powered Swarm Robotics, Time-Sensitive Networking, LiDAR-Enhanced Environment Mapping, Energy-Efficient Microcontrollers, and Thermal Imaging Cameras

The smart Internet of Robotic Things (IoRT) networks integrate swarm robotics, Time-Sensitive Networking (TSN), Light Detection and Ranging (LiDAR) mapping, microcontrollers, and thermal imaging, producing adaptive and efficient ecosystems. The proposed study addresses a real-life problem across most industries, offering an autonomous, scalable, and optimized resource solution. It integrates swarm robotics for task coordination, TSN for low-latency communication, LiDAR for environmental mapping, and microcontrollers for energy efficiency along with thermal imaging capabilities for anomaly detection. Combining all these components a comprehensive AI architecture was developed to improve the performance in complex scenarios of IoRT. The research aims to develop scalable IoRT solutions that incorporate swarm robotics for coordination, TSN for deterministic communication, LiDAR for accurate mapping, energy-efficient microcontrollers for sustainability, and thermal imaging for anomaly detection in mission-critical tasks while being adaptable, reliable, and efficient. The proposed system attains 93% accuracy, 91% scalability, 94% F1 score, 95% efficiency, and 93% anomaly detection, which is beyond traditional methods. It addresses IoRT challenges with enhanced real-time adaptability, energy efficiency, and scalability to ensure optimal performance in applications like healthcare and disaster response. The integrated IoRT framework employs cutting-edge technologies and thus tackles dynamic challenges with precision and accuracy. Since it outperforms the traditional methods in different metrics, it establishes scalable, sustainable solutions for various real-time IoRT applications. The adaptability towards resources gets improved in more complex ecosystems.

A gradient descent algorithm for SNN with time-varying weights for reliable multiclass interpretation

Interpretation of the prediction is vital for mission critical tasks. Accurate interpretation relies upon the generalization accuracy of the model. In this paper, we propose a modified gradient descent learning algorithm to improve the generalization ability of a Spiking Neural Network with time-varying weights (SNN-t). This algorithm is referred to as GradST, can help towards improving the interpretation of multiclass classification problems. We have transformed the SNN-t to a Generalized Additive Model (GAM) to provide interpretation. The resultant Spiking Additive Model (SAM) has the generalization ability of SNN-t and the interpretable characteristics of GAM for multiclass problems. We also propose a post-processing method to enable better visualization of multiple shape functions of GAMs, towards better relative interpretation for multiclass classification problems. The post-processing method utilizes the properties of multiclass GAMs to visually modify the shape functions to establish the importance of the feature in multiclass setting. We first evaluate the performance of SNN-t, trained with GradST and the SAM generated from it, on large public datasets. The SNN-t trained with GradST has better generalization accuracy than other SNN-t classifier and consequently, the SAM generated from it has better generalization accuracy than other state-of-the-art multiclass GAMs. Improved accuracy in SAM implies more reliable interpretation. Then, we evaluate the proposed post-processing method for multiclass GAMs to provide relative interpretation. It is observed that relative interpretation of multiclass GAM is more meaningful and reliable.

Cold Habituation Does Not Alter Thermal Responses or Manual Dexterity During Prolonged Cold Air Exposure

Background: Habituation is a pattern of cold acclimatization characterized by attenuated cold defense responses, including a reduction in peripheral vasoconstriction and subsequent increase in skin temperature (TSk) as well as a decrease in shivering thermogenesis. Habituation is achieved through repeated reductions in TSk, rather than deep body core temperature (TC), via exposure to prolonged cold air or brief cold-water immersion. Due to improvements in TSk, enhanced manual dexterity and peripheral cold injury risk reduction are purported benefits of cold habituation. Warfighters frequently operate in cold climates and experience decrements in manual dexterity and strength. These functional losses can negatively impact mission critical tasks and training exercises; however, the effectiveness of cold habituation as a potential countermeasure to alleviate the deleterious effects of prolonged cold exposure on peripheral temperatures, thermal comfort, and hand function is unclear. Purpose: To evaluate the influence of eight consecutive cold air exposures on the thermal (TC and TSk), perceptual (thermal comfort and sensation), and functional (manual dexterity and strength) responses to cold air. We hypothesized that TSk would be higher and perceptual responses and manual dexterity improved, following repeated cold exposure. Methods: Eight young adults (6 M/1 F/1 FTM; 21 ± 2 years; %BF 24.5 ± 7.0) underwent a 2-h cold air exposure (8 °C, ~50% RH) on 8 consecutive days wearing minimal clothing. On Day 0 (baseline exposure ~1 week prior) and Days 1 and 8 of repeated exposure, TC was recorded continuously via a telemetry pill used as a rectal suppository. Extremity (Thand and Tfinger) and mean weighted TSk (MWTSk) from 8 skin sites were recorded continuously. Thermal comfort (TC) and thermal sensation (TS) were recorded at 20 min intervals. Expired gases were collected at 20 min intervals and used to calculate metabolic heat production (MHP). Manual dexterity was assessed using the Purdue Pegboard and Minnesota Manual Dexterity Test (MMDT), and hand strength were measured before and at the end of cold exposure. Results: TC changed across time ( p < 0.05) but did not differ between days ( p > 0.05). MWTSk, Thand, and Tfinger decreased across time ( p < 0.05) but also did not differ between days ( p > 0.05). Mean and minimum whole-body TS and TC were not different between days ( p > 0.05). MHP increased across time ( p < 0.05) but did not differ between days ( p > 0.05). Purdue Pegboard, MMDT task performance, and hand strength did not differ between days ( p > 0.05). Conclusion: Eight consecutive days of cold air exposure does not augment extremity skin temperature, thermal comfort, or manual performance during prolonged cold conditions. Supported by U.S. Army Medical Research and Development Command, Military Operational Medicine Research Program; author views not offcial US Army or DoD policy. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Efficient Malware Analysis Using Metric Embeddings

Real-world malware analysis consists of a complex pipeline of classifiers and data analysis—from detection to classification of capabilities to retrieval of unique training samples from user systems. In this article, we aim to reduce the complexity of these pipelines through the use of low-dimensional metric embeddings of Windows PE files, which can be used in a variety of downstream applications, including malware detection, family classification, and malware attribute tagging. Specifically, we enrich labeling of malicious and benign PE files with computationally-expensive, disassembly-based malicious capabilities information. Using this enhanced labeling, we derive several different types of efficient metric embeddings utilizing an embedding neural network trained via contrastive loss, Spearman rank correlation, and combinations thereof. Our evaluation examines performance on a variety of transfer tasks performed on the EMBER and SOREL datasets, demonstrating that low-dimensional, computationally-efficient metric embeddings maintain performance with little decay. This offers the potential to quickly retrain for a variety of transfer tasks at significantly reduced overhead and complexity. We conclude with an examination of practical considerations for the use of our proposed embedding approach, such as robustness to adversarial evasion and introduction of task-specific auxiliary objectives to improve performance on mission critical tasks.

Comparing Hypothermic and Thermal Neutral Conditions to Induce Metabolic Suppression.

Suppressing metabolism in astronauts could decrease CO2 production. It is unknown whether active cooling is required to suppress metabolism in sedated patients. We hypothesized that hypothermia would have an additive effect with dexmedetomidine on suppressing metabolism. This is a randomized crossover trial of healthy subjects receiving sedation with dexmedetomidine and exposure to a cold (20°C) or thermal neutral (31°C) environment for 3 hours. We measured heart rate, blood pressure, core temperature, resting oxygen consumption (VO2), resting carbon dioxide production (VCO2), and resting energy expenditure (REE) at baseline and each hour of exposure to either environment. We also evaluated components of the Defense Automated Neurobehavioral Assessment (DANA) Brief to evaluate the effect of metabolic suppression on cognition. Six subjects completed the study. Heart rate and core temperature were lower during the cold (56 bpm) condition than the thermal neutral condition (67 bpm). VO2, VCO2, and REE decreased between baseline and the 3-hour measurement in the cold condition (Δ = 0.9 mL/min, 56.94 mL/min, 487.9 Kcal/D, respectively). DANA simple response time increased between baseline and start of recovery in both conditions (20°C 136.9 cognitive efficiency [CE] and 31°C 87.83 CE). DANA procedural reaction time increased between baseline and start of recovery in the cold condition (220.6 CE) but not in the thermal neutral condition. DANA Go/No-Go time increased between baseline and start of recovery in both conditions (20°C 222.1 CE and 31°C 122.3 CE). Sedation and cold environments are required for metabolic suppression. Subjects experienced decrements in cognitive performance in both conditions. A significant recovery period may be required after metabolic suppression before completing mission critical tasks.

An Augmented Reality Hand-Eye Sensorimotor Impairment Assessment for Spaceflight Operations.

INTRODUCTION: Following a transition from microgravity to a gravity-rich environment (e.g., Earth, Moon, or Mars), astronauts experience sensorimotor impairment, primarily from a reinterpretation of vestibular cues, which can impact their ability to perform mission-critical tasks. To enable future exploration-class missions, the development of lightweight, space-conscious assessments for astronauts transitioning between gravity environments without expert assistance is needed.METHODS: We examined differences in performance during a two-dimensional (2D) hand-eye multidirectional tapping task, implemented in augmented reality in subjects (N = 20) with and without the presence of a vestibular-dominated sensorimotor impairment paradigm: the binaural bipolar application of a pseudorandom galvanic vestibular stimulation (GVS) signal. Metrics associated with both the impairment paradigm and task performance were assessed.RESULTS: Medial-lateral sway during balance on an anterior-posterior sway-referenced platform with eyes closed was most affected by GVS (effect size: 1.2), in addition to anterior-posterior sway (effect size: 0.63) and the vestibular index (effect size: 0.65). During the augmented reality task, an increase in time to completion (effect size: 0.63), number of misses (effect size: 0.52), and head linear accelerations (effect size: 0.30) were found in the presence of the selected GVS waveform.DISCUSSION: Findings indicate that this multidirectional tapping task may detect emergent vestibular-dominated impairment (near landing day performance) in astronauts. Decrements in speed and accuracy indicate this impairment may hinder crews' ability to acquire known target locations while in a static standing posture. The ability to track these decrements can support mission operations decisions.Allred AR, Weiss H, Clark TK, Stirling L. An augmented reality hand-eye sensorimotor impairment assessment for spaceflight operations. Aerosp Med Hum Perform. 2024; 95(2):69-78.

OROS: Online Operation and Orchestration of Collaborative Robots Using 5G

The 5G mobile networks extend the capability for supporting collaborative robot operations in outdoor scenarios. However, the restricted battery life of robots still poses a major obstacle to their effective implementation and utilization in real scenarios. One of the most challenging situations is the execution of mission-critical tasks that require the use of various onboard sensors to perform simultaneous localization and mapping (SLAM) of unexplored environments. Given the time-sensitive nature of these tasks, completing them in the shortest possible time is of the highest importance. In this paper, we analyze the benefits of 5G-enabled collaborative robots by enhancing the intelligence of the robot operation through joint orchestration of Robot Operating System (ROS) and 5G resources for energysaving goals, addressing the problem from both offline and online manners. We propose OROS, a novel orchestration approach that minimizes mission-critical task completion times as well as overall energy consumption of 5G-connected robots by jointly optimizing robotic navigation and sensing together with infrastructure resources. We validate our 5G-enabled collaborative framework by means of Matlab/Simulink, ROS software and Gazebo simulator. Our results show an improvement between 3.65in exploration task by exploiting 5G orchestration features for battery savings when using 3 robots.

Duty-cycle-aware low-thrust trajectory optimization using embedded homotopy

In space mission design, an important operational constraint is planned periodic coast arcs during which various mission-critical tasks such as navigation or ground communications are performed. These constraints, typically implemented as thruster duty cycles, can be characterized as discrete coast arcs enforced periodically during intervals of deterministic thrusting. A typical approach to incorporate duty cycles is by enforcing maximum thrust levels that are less than a nominal value. This work presents an embedded homotopy indirect optimization method for a smooth enforcement of discrete duty-cycle constraints for low-thrust trajectory optimization. The complexity of enforcing such discrete constraints is two-fold: (1) a precise event-detection strategy is needed to determine the beginning of deterministic thrust arcs, which must be successively updated along the trajectory and (2) a smooth modeling of the discrete coast events occurring on the order of 10s or even 100s depending on the duration of deterministic thrust arcs. Duty cycle constraints are enforced at the level of the Hamiltonian using a Composite Smooth Control (CSC) method, producing high-resolution optimal control solutions conscious of planned duty cycle coast arcs. Numerical solutions are presented for the heliocentric transfer phases of three space missions. The results are then validated against the Evolutionary Mission Trajectory Generator (EMTG), one of NASA’s global trajectory optimization tools used for interplanetary mission design and capable of the explicit enforcement of periodic duty cycle coasting. The proposed indirect method is suitable for obtaining high-resolution trajectory solutions with realistically enforced thruster duty cycle, which could then be used as high-quality initial guesses in flight-fidelity mission planning tools. The proposed smooth modeling of discrete coast arcs can also be customized to enforce periodic and non-periodic thrust shutdown constraints.

Control-Oriented Power Allocation for Integrated Satellite-UAV Networks

This letter presents a sensing-communication-computing-control (SC3) integrated satellite unmanned aerial vehicle (UAV) network, where UAVs are equipped with sensors, mobile edge computing (MEC) servers, base stations and satellite communication modules. Like a nervous system, this integrated network is capable of organizing multiple field robots in remote areas, so as to perform mission-critical tasks which are dangerous for humans. Aiming at activating this nervous system with multiple SC3 loops, we present a control-oriented optimization problem. Different from traditional studies which mainly focused on communication metrics, we address the power allocation issue to minimize the sum linear quadratic regulator (LQR) control cost of all SC3 loops. Specifically, we show the convexity of the problem and reveal the relationship between the optimal transmit power and intrinsic entropy rates of different SC3 loops. For the assure-to-be-stable case, we derive a closed-form solution for ease of practical applications. After demonstrating the superiority of the control-oriented power allocation, we further highlight its difference from the classic capacity-oriented water-filling method.

Human movement in simulated hypogravity-Bridging the gap between space research and terrestrial rehabilitation.

Human movement is optimized to Earth's gravity and based on highly complex interactions between sensory and neuro-muscular systems. Yet, humans are able to adapt-at least partially-to extreme environments upon and beyond Earth's surface. With upcoming Lunar Gateway and Artemis missions, it is crucial to increase our understanding of the impact of hypogravity-i.e., reduced vertical loading-on physiological and sensory-motor performances to improve countermeasure programs, and define crewmember's readiness to perform mission critical tasks. Several methodologies designed to reduce vertical loading are used to simulate hypogravity on Earth, including body weight support (BWS) devices. Countering gravity and offloading the human body is also used in various rehabilitation scenarios to improve motor recovery in neurological and orthopedic impairments. Thus, BWS-devices have the potential of advancing theory and practice of both space exploration and terrestrial rehabilitation by improving our understanding of physiological and sensory-motor adaptations to reduced vertical loading and sensory input. However, lack of standardization of BWS-related research protocols and reporting hinders the exchange of key findings and new advancements in both areas. The aim of this introduction paper is to review the role of BWS in understanding human movement in simulated hypogravity and the use of BWS in terrestrial rehabilitation, and to identify relevant research areas contributing to the optimization of human spaceflight and terrestrial rehabilitation. One of the main aims of this research topic is to facilitate standardization of hypogravity-related research protocols and outcome reporting, aimed at optimizing knowledge transfer between space research and BWS-related rehabilitation sciences.

URLLC-Based Cooperative Industrial IoT Networks With Nonlinear Energy Harvesting

The efficient and effective framework for next-generation (5G and beyond 5G) wireless networks should include mission-critical aspects such as ultralow latency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\leq \!\!1$</tex-math></inline-formula> ms), ultrahigh reliability (99.999%), and enhanced data rate. Billions of ubiquitously connected devices are expected to serve various industrial applications in upcoming industry standards such as Industry 5.0. These industrial applications include mission-critical tasks such as smart grids, remote surgery, and intelligent transportation systems. This article considers an industrial Internet of Things (IIoT) environment in mission-critical ultrareliable low latency communication (URLLC) application where the main industrial unit or industrial control node (CN) sends messages to the target device (TD) with the aid of a cooperative device (CD). We investigate a novel transmission protocol and analyze the network’s performance. Considering the nonlinear energy harvesting (EH) mechanism at power-constrained nodes and direct and cooperative phase transmissions, the outage probability (OP) and block error rate (BLER) performances are evaluated for Rayleigh distributed fading channels. The analytical results are validated through Monte–Carlo simulations.

Dynamic visual acuity as a biometric for astronaut performance and safety

Astronauts are exposed to an austere and constantly changing environment during space travel. To respond to these rapid environmental changes, high levels of dynamic visual acuity (DVA) are required. DVA is the ability to visualize objects that are in motion, or with head movement and has previously been shown to decrease significantly following spaceflight. Decreased DVA can potentially impact astronauts while performing mission critical tasks and drive space motion sickness. In this paper, we suggest that DVA assessment during spaceflight and during G-transitions should be considered to help further understand the vestibulo-ocular impacts of interplanetary spaceflight and ensure mission performance including potential manned missions to Mars.

Minified Augmented Reality as a Terrestrial Analog for G-Transitions Effects in Lunar and Interplanetary Spaceflight

Brief periods of extreme gravitational transition are anticipated during interplanetary spaceflight, including transitions between microgravity, hypogravity, and hypergravity. Rapid sensorimotor adaptation will occur following these G-transitions which may affect astronaut performance including gaze control and dynamic visual acuity. Significant decrements in dynamic visual acuity could lead to mission compromise or failure (e.g., impairing mission critical tasks or spacecraft maneuvering). It is crucial to provide astronauts with the training necessary to overcome these physiological barriers they are bound to encounter during spaceflight missions. Minifying lenses in augmented reality may serve as an easily applicable, low-cost, method to simulate vestibulo-ocular dysfunction that occurs during gravitational transitions. In this paper, we review the effects of G-transitions on the vestibulo-ocular system and report on the novel development of minified augmented reality as a potential simulator and training tool for future spaceflight. We also report the results from an early validation study with a mean decrease in DVA (0.370 LogMAR) with 80% minifying effect, as well as a mean increase of DVA post-minifying (0.030 LogMAR). These early results suggest that minified augmented reality may serve as an accessible terrestrial analog for G-transitions, thus having potential for pre-mission training, particularly for lunar and interplanetary spaceflight.

Mission-critical tasks for assessing risks from vestibular and sensorimotor adaptation during space exploration.

To properly assess the risk induced by vestibular and sensorimotor adaptation during exploration missions, we examined how long-duration stays on the International Space Station affect functional performance after gravity transitions. Mission-critical tasks that challenge the balance and the locomotion control systems were assessed: i.e., sit-to-stand, recovery-from-fall, tandem-walk, and walk-and-turn. We assessed 19 astronauts, including 7 first-time flyers and 12 experienced flyers, before their flight, a few hours after landing, and then 1day and 6-11days later. Results show that adaptation to long-term weightlessness causes deficits in functional performance immediately after landing that can last for up to 1week. No differences were observed between first-time and experienced astronaut groups. These data suggest that additional sensorimotor-based countermeasures may be necessary to maintain functional performance at preflight levels when landing on planetary surfaces after a long period in weightlessness.

Multidimensional ground reaction forces and moments from wearable sensor accelerations via deep learning

Introduction: Military task performance is dependent upon the coherent and effective collaboration of its component parts. These are comprised of individuals working in coordinated teams performing tasks that are naturally variable and have physical and cognitive elements, the relative contribution being dependent upon the task. Furthermore, the battlefield is non-linear, and dynamic with human, task, environmental and informational constraints. Complexity is added to team performance assessment by the fact that there is considerable redundancy within military teams. This redundancy is critical and affords the ability for team performance to be protected even when individual performance is degraded by fatigue. The purpose of this work is to propose a conceptual framework for the assessment of military team dynamics, based upon analytical models used in sport in addition to emergent sensor technologies and Artificial Intelligence (AI). Methods: A review of the scientific literature and the developments in team performance assessment, AI and emerging sensor technologies was conducted to inform a conceptual framework designed to assess team dynamics and redundancy in the presence of individual fatigue. Results: Current assessment of team dynamics during mission-critical tasks, the contribution of each individual, and the emergent team behaviours whilst subject to fatigue are typically limited to subjective ratings and post-activity reports. Indeed, there seems to be an institutional belief that the military already assess teams effectively and retrospective After Action Review is key to this success. As such, the ability to reliably monitor and objectively assess military team dynamics and redundancy remains a challenge. In addition, despite advancements in technology, the opportunity to conduct real-time or near real-time observations with which to provide rapid insights is yet to be taken up by the military. Discussion/conclusions: Improvements in analytical methods, sensor technologies, and the maturity of AI tools provide the opportunity to progress from simply describing individual and team performance to understanding the team dynamics by the integration of novel sensors and AI-assisted analytical tools. Devices to rapidly acquire and process data continue to evolve along with wearable, and stand-off sensors and AI-assisted tools. A peer-reviewed, conceptual, interdisciplinary framework for objectively assessing team dynamics is proposed. With careful collaboration, we suggest that the potential to enhance the understanding of team dynamics and redundancy is boundless. Notwithstanding, it is critical that defence organisations have an endorsed strategy for the acceptance and implementation of such analytical tools that would provide a clear operational benefit.

Rapid loss of fine motor skills after low dose space radiation exposure

Sensorimotor function, motivation, and attentional processes are fundamental aspects of behavioral organization during skilled tasks. NASA’s planned expedition to Mars will expose astronauts to space radiation (SR) that has the potential to impair performance in mission critical tasks. Impairments in task accuracy and movement kinematics have been previously reported during string-pulling behavior ~7 months after SR exposure. If similar SR-induced sensorimotor deficits emerge at earlier times, then astronauts may have compromised in-flight performance disruptions while performing skilled tasks in critical situations, such as when manipulating controls or performing seat egress. Due to the possibility that such performance losses may compromise mission success, it is critical to determine if sensorimotor, motivation, or attentional deficits occur acutely after SR exposure at a time point that corresponds to in-flight performance. Male Wistar rats were thus exposed to either 10 cGy simplified galactic cosmic radiation (GCRsim), 10 cGy 4Helium (4He), or no radiation at all (Sham), and string-pulling behavior was assessed approximately 72 h later. Following exposure to SR, rats (4He) took more time to approach the string to initiate string-pulling behavior and to pull in the string to reach the Cheerio (4He and GCRsim) relative to Sham rats. 4He-exposed rats also exhibited a greater number of misses and less contacts relative to both Sham and GCRsim-exposed rats. Further, rats exposed to 4He demonstrated less concentrated reach endpoints with both the left and right hands compared to GCR-exposed rats. This work suggests that sensorimotor function and motivation and/or attentional processes were impaired 72 h after 4He-radiation exposure.

Cortical thickness of primary motor and vestibular brain regions predicts recovery from fall and balance directly after spaceflight.

Motor adaptations to the microgravity environment during spaceflight allow astronauts to perform adequately in this unique environment. Upon return to Earth, this adaptation is no longer appropriate and can be disruptive for mission critical tasks. Here, we measured if metrics derived from MRI scans collected from astronauts can predict motor performance post-flight. Structural and diffusion MRI scans from 14 astronauts collected before launch, and motor measures (balance performance, speed of recovery from fall, and tandem walk step accuracy) collected pre-flight and post-flight were analyzed. Regional measures of gray matter volume (motor cortex, paracentral lobule, cerebellum), myelin density (motor cortex, paracentral lobule, corticospinal tract), and white matter microstructure (corticospinal tract) were derived as a-priori predictors. Additional whole-brain analyses of cortical thickness, cerebellar gray matter, and cortical myelin were also tested for associations with post-flight and pre-to-post-flight motor performance. The pre-selected regional measures were not significantly associated with motor behavior. However, whole-brain analyses showed that paracentral and precentral gyri thickness significantly predicted recovery from fall post-spaceflight. Thickness of vestibular and sensorimotor regions, including the posterior insula and the superior temporal gyrus, predicted balance performance post-flight and pre-to-post-flight decrements. Greater cortical thickness pre-flight predicted better performance post-flight. Regional thickness of somatosensory, motor, and vestibular brain regions has some predictive value for post-flight motor performance in astronauts, which may be used for the identification of training and countermeasure strategies targeted for maintaining operational task performance.

High-precision time synchronization chip design for industrial sensor and actuator network

Mission-critical (MC) sensor and actuator networks (SANs) are being applied widely for multiaxis motion control of robotic manipulators , particularly for performing MC tasks in smart manufacturing. One of the most challenging tasks in MC-SANs is the development of a precision time synchronization (PTS) protocol. A conventional precision time system uses the IEEE 1588 v2 standard [1] ; however, in MC-SANs, many factors need to be considered when designing an IoT computing system, such as robustness, cost-effectiveness, interoperability and scalability. This study proposes a high-precision time synchronization protocol based on Modbus sensors and actuator networks for an industrial fieldbus network. The PTS protocol design and hardware synthesis are conducted with a consistent and systematic design methodology. GRAFCET is used to model the individual functional modules and hierarchical behavior of the system. The behavior of each module is represented as a sequential–concurrent hybrid discrete event system . We apply high-level synthesis rules to design PTS hardware for a complex PTS system based on the VHSIC hardware description language (VHDL). The PTS hardware module has an embedded PTS algorithm with a proportional error correction model, and the time synchronization accuracy of the precision time protocol (PTP) chip is up to 42 ns. Experimental results demonstrate that our high-performance PTS controller chip can satisfy the requirements of multiaxis motion control and that it is more efficient than other protocols and products designed for similar industrial manufacturing applications.

Secure and Energy Efficient Data Transaction in WSN through SSCHS Routing Protocol

Abstract: Wireless sensor networks are widely used due to its usage and advantages because it can utilize in mission critical tasks. One of the major issues in WSN is reliable data delivery without any loss and to increase network lifetime by utilizing energy efficient process. The objective of this work is to increase network lifetime at the same time ensuring high packet delivery ratio. Clustering is one of the best methods to increase network lifetime, however election process of cluster head will consume energy and reduces network performance. Therefore in proposed work, energy efficient cluster based routing protocol has been implemented which includes residual energy and distance as major parameter to form cluster. Cluster head selection will be a static process, once cluster is formed cluster head will be selected through election process after transaction the residual energy in CH will be checked with the threshold value and same CH will again act as head this reduces cluster formation and election process. In addition to provide secure data transaction MD5 algorithm has been implemented. Attack based data loss is also reduced and concentrated in proposed work to achieve objective of this work. Keywords: (SSCHS) Secure static cluster head selection, network lifetime, cluster, MD5 and Static cluster head.

Differential organization of open field behavior in mice following acute or chronic simulated GCR exposure

Astronauts undertaking deep space travel will receive chronic exposure to the mixed spectrum of particles that comprise Galactic Cosmic Radiation (GCR). Exposure to the different charged particles of varied fluence and energy that characterize GCR may impact neural systems that support performance on mission critical tasks. Indeed, growing evidence derived from years of terrestrial-based simulations of the space radiation environment using rodents has indicated that a variety of exposure scenarios can result in significant and long-lasting decrements to CNS functionality. Many of the behavioral tasks used to quantify radiation effects on the CNS depend on neural systems that support maintaining spatial orientation and organization of rodent open field behavior. The current study examined the effects of acute or chronic exposure to simulated GCR on the organization of open field behavior under conditions with varied access to environmental cues in male and female C57BL/6 J mice. In general, groups exhibited similar organization of open field behavior under dark and light conditions. Two exceptions were noted: the acute exposure group exhibited significantly slower and more circuitous homeward progressions relative to the chronic group under light conditions. These results demonstrate the potential of open field behavior organization to discriminate between the effects of select GCR exposure paradigms.