Sleep disturbances and predictors of nondeployability among active-duty army soldiers: an odds ratio analysis of medical healthcare data from fiscal year 2018

Background:The impact of sleep disorders on active-duty soldiers’medical readiness is not currently quantified.Patient data generated at military treatment facilities can be accessed to create research reports and thus can be used to estimate the prevalence of sleep disturbances and the role of sleep on overall health in service members.The current study aimed to quantify sleep-related health issues and their impact on health and nondeployability through the analysis of U.S.military healthcare records from fiscal year 2018(FY2018).Methods:Medical diagnosis information and deployability profiles(e-Profiles)were queried for all active-duty U.S.Army patients with a concurrent sleep disorder diagnosis receiving medical care within FY2018.Nondeployability was predicted from medical reasons for having an e-Profile(categorized as sleep,behavioral health,musculoskeletal,cardiometabolic,injury,or accident)using binomial logistic regression.Sleep e-Profiles were investigated as a moderator between other e-Profile categories and nondeployability.Results:Out of 582,031 soldiers,48.4%(n=281,738)had a sleep-related diagnosis in their healthcare records,9.7%(n=56,247)of soldiers had e-Profiles,and 1.9%(n=10,885)had a sleep e-Profile.Soldiers with sleep e-Profiles were more likely to have had a motor vehicle accident(p OR(prevalence odds ratio)=4.7,95%CI 2.63–8.39,P≤0.001)or work/duty-related injury(p OR=1.6,95%CI 1.32–1.94,P≤0.001).The likelihood of nondeployability was greater in soldiers with a sleep e-Profile and a musculoskeletal e-Profile(p OR=4.25,95%CI 3.75–4.81,P≤0.001)or work/dutyrelated injury(p OR=2.62,95%CI 1.63–4.21,P≤0.001).Conclusion:Nearly half of soldiers had a sleep disorder or sleep-related medical diagnosis in 2018,but their sleep problems are largely not profiled as limitations to medical readiness.Musculoskeletal issues and physical injury predict nondeployability,and nondeployability is more likely to occur in soldiers who have sleep e-Profiles in addition to these issues.Addressing sleep problems may prevent accidents and injuries that could render a soldier nondeployable.

An origami shield with supporting frame structures optimized by a feature-driven topology optimization method

In this paper,the design,manufacture and testing of an origami protective shield with a supporting frame structure are presented.It consists of an origami shield surface and a deployable supporting frame structure that needs to be portable and sufficiently stiff.First,for the design of the shield surface,a threestage origami crease pattern is developed to reduce the shield size in the folded state.The shield surface consists of several stiff modular panels and layered with flexible fabric.The modular panels are made of a multi-layer composite where a ceramic layer is made of small pieces to improve durability as those small pieces enable restriction of crack propagation.Then,the supporting frame structure is designed as a chain-of-bars structure in order to fold into a highly compact state as a bundle of bars and deploy in sequence.Thus,a feature-driven topology structural optimization method preserving component sequence is developed where the inter-dependence of sub-structures is taken into account.A bar with semi-circular ends is used as a basic design feature.The positions of the bar’s end points are treated as design variables and the width of the bars is kept constant.Then,a constraint on the total length of the chain of bars is introduced.Finally,the modular panels made of multi-layer composite and the full-scale prototype of the origami shield are fabricated and tested to verify the bullet-proof performance.

Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.

Deployment of Edge Computing Nodes in IoT:Effective Implementation of Simulated Annealing Method Based on User Location

Edge computing paradigm for 5G architecture has been considered as one of the most effective ways to realize low latency and highly reliable communication,which brings computing tasks and network resources to the edge of network.The deployment of edge computing nodes is a key factor affecting the service performance of edge computing systems.In this paper,we propose a method for deploying edge computing nodes based on user location.Through the combination of Simulation of Urban Mobility(SUMO)and Network Simulator-3(NS-3),a simulation platform is built to generate data of hotspot areas in Io T scenario.By effectively using the data generated by the communication between users in Io T scenario,the location area of the user terminal can be obtained.On this basis,the deployment problem is expressed as a mixed integer linear problem,which can be solved by Simulated Annealing(SA)method.The analysis of the results shows that,compared with the traditional method,the proposed method has faster convergence speed and better performance.

A Combined Antenna Array Deployment with High Positioning Accuracy and Low Angular Measurement Error

In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.

The Determination Method of Product Engineering Features Based on Linguistic Variables

To overcome the problem of imprecise and unclear information in the development of quality functions,a method for determining the priority of engineering features based on mixed linguistic variables is proposed.First,the evaluation member uses the determined linguistic variable to give the correlation strength evaluation matrix of customer requirements and engineering features.Secondly,the relative importance of the evaluation member and customer requirements are aggregated.Finally,the priority of engineering features is obtained by calculating the deviation.The feasibility and practicability of this method are proven by taking the design of a new product of a long bag low-pressure pulse dust collector as an example.

A multi-enterprise quality function deployment paradigm with unstructured decision-making in linguistic contexts

This paper presents an operational framework of unstructured decision-making approach involving quality function deployment(QFD)in an uncertain linguistic context.Firstly,QFD is extended to the multi-enterprise paradigm in a real-world manufacturing environment.Secondly,hesitant fuzzy linguistic term sets(HFLTSs),which facilitate the management and handling of information equivocality,are designed to construct a house of quality(HoQ)in the product planning process.The technique of computing with words is applied to bridge the gap between mechanisms of the human brain and machine processes with fuzzy linguistic term sets.Thirdly,a multi-enterprise QFD pattern is formulated as an unstructured decision-making problem for alternative infrastructure project selection in a manufacturing organization.The inter-relationships of cooperative partners are directly matched with a back propagation neural network(BPNN)to construct the multi-enterprise manufacturing network.The resilience of the manufacturing organization is considered by formulating an outranking method on the basis of HFLTSs to decide on infrastructure project alternatives.Finally,a real-world example,namely,the prototype manufacturing of an automatic transmission for a vehicle,is provided to illustrate the effectiveness of the proposed decision-making approach.

Optimal deployment of swarm positions in cooperative interception of multiple UAV swarms

In order to prevent the attacker from breaking through the blockade of the interception,deploying multiple Unmanned Aerial Vehicle(UAV)swarms on the interception line is a new combat style.To solve the optimal deployment of swarm positions in the cooperative interception,an optimal deployment optimization model is presented by minimizing the penetration zones'area and the analytical expression of the optimal deployment positions is deduced.Firstly,from the view of the attackers breaking through the interception line,the situations of vertical penetration and oblique penetration are analyzed respectively,and the mathematical models of penetration zones are obtained under the condition of a single UAV swarm and multiple UAV swarms.Secondly,based on the optimization goal of minimizing the penetration area,the optimal deployment optimization model for swarm positions is proposed,and the analytical solution of the optimal deployment is solved by using the convex programming theory.Finally,the proposed optimal deployment is compared with the uniform deployment and random deployment to verify the validity of the theoretical analysis.

Watt Linkage–Based Legged Deployable Landing Mechanism for Reusable Launch Vehicle: Principle, Prototype Design, and Experimental Validation

The reusable launch vehicle (RLV) presents a new avenue for reducing cost of space transportation. The landing mechanism, which provides landing support and impact absorption, is a vital component of the RLV at final stage of recovery. This study proposes a novel legged deployable landing mechanism (LDLM) for RLV. The Watt-II six-bar mechanism is adopted to obtain the preferred configuration via the application of the linkage variation approach. To endow the proposed LDLM with advantages of large landing support region, lightweight, and reasonable linkage internal forces, a multi-objective optimization paradigm is developed. Furthermore, the optimal scale parameters for guiding the LDLM prototype design is obtained numerically using the non-dominated sorting genetic algorithm-II (NSGA-II) evolutionary algorithm. A fully-functional scaled RLV prototype is developed by integrating the gravity-governed deploying scheme to facilitate unfolding action to avoid full-range actuation, a dual-backup locking mechanism to enhance reliability of structure stiffening as fully deployed, and a shock absorber (SA) with multistage honeycomb to offer reliable shock absorbing performance. The experimental results demonstrate that the proposed LDLM is capable of providing rapid and smooth deployment (duration less than 1.5 s) with mild posture disturbance to the cabin (yaw and pitch fluctuations less than 6°). In addition, it provides satisfactory impact attenuation (acceleration peak less than 10g (g is the gravitational acceleration)) in the 0.2 m freefall test, which makes the proposed LDLM a potential alternative for developing future RLV archetype.

A Shape-Memory Deployable Subsystem with a Large Folding Ratio in China’s Tianwen-1 Mars Exploration Mission

Once China’s Tianwen-1 Mars probe arrived in a Mars orbit after a seven-month flight in the deep cold space environment,it would be urgently necessary to monitor its state and the surrounding environment.To address this issue,we developed a flexible deployable subsystem based on shape memory polymer composites(SMPC-FDS)with a large folding ratio,which incorporates a camera and two temperature telemetry points for monitoring the local state of the Mars orbiter and the deep space environment.Here,we report on the development,testing,and successful application of the SMPC-FDS.Before reaching its Mars remote-sensing orbit,the SMPC-FDS is designed to be in a folded state with high stiffness;after reaching orbit,it is in a deployed state with a large envelope.The transition from the folded state to the deployed state is achieved by electrically heating the shape memory polymer composites(SMPCs);during this process,the camera on the SMPC-FDS can capture the local state of the orbiter from multiple angles.Moreover,temperature telemetry points on the SMPC-FDS provide feedback on the environment temperature and the temperature change of the SMPCs during the energization process.By simulating a Mars on-orbit space environment,the engineering reliability of the SMPC-FDS was comprehensively verified in terms of the material properties,structural dynamic performance,and thermal vacuum deployment feasibility.Since the launch of Tianwen-1 on 23 July 2020,scientific data on the temperature environment around Tianwen-1 has been successfully acquired from the telemetry points on the SMPCFDS,and the local state of the orbiter has been photographed in orbit,showing the national flag of China fixed on the orbiter.

Mobile Edge Computing Servers Deployment with Improved Genetic Algorithm in Cellular Internet of Things

Mobile edge computing(MEC)provides services to devices and reduces latency in cellular internet of things(IoT)networks.However,the challenging problem is how to deploy MEC servers economically and efficiently.This paper investigates the deployment problem of MEC servers of the real-world road network by employing an improved genetic algorithm(GA)scheme.We first use the threshold-based K-means algorithm to form vehicle clusters according to their locations.We then select base stations(BSs)based on clustering center coordinates as the deployment locations set for potential MEC servers.We further select BSs using a combined simulated annealing(SA)algorithm and GA to minimize the deployment cost.The simulation results show that the improved GA deploys MEC servers effectively.In addition,the proposed algorithm outperforms GA and SA algorithms in terms of convergence speed and solution quality.

Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.

Optimization method of linear barrier coverage deployment for multistatic radar

To address the problem of building linear barrier coverage with the location restriction, an optimization method for deploying multistatic radars is proposed, where the location restriction splits the deployment line into two segments. By proving the characteristics of deployment patterns, an optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment. The types and numbers of deployment patterns are determined by an algorithm that combines the integer linear programming(ILP)and exhaustive method(EM). In addition, to reduce the computation amount, a formula is introduced to calculate the upper threshold of receivers’ number in a deployment pattern. Furthermore, since the objective function is non-convex and non-analytic, the overall model is divided into two layers concerning two suboptimization problems. Subsequently, another algorithm that integrates the segments and layers is proposed to determine the deployment parameters, such as the minimum cost, parameters of the optimal deployment sequence, and the location of the split point. Simulation results demonstrate that the proposed method can effectively determine the optimal deployment parameters under the location restriction.

Configuration Synthesis and Lightweight Networking of Deployable Mechanism Based on a Novel Pyramid Module

Deployable mechanism with preferable deployable performance,strong expansibility,and lightweight has attracted much attention because of their potential in aerospace.A basic deployable pyramid unit with good deployability and expandability is proposed to construct a sizeable deployable mechanism.Firstly,the basic unit folding principle and expansion method is proposed.The configuration synthesis method of adding constraint chains of spatial closed-loop mechanism is used to synthesize the basic unit.Then,the degree of freedom of the basic unit is analyzed using the screw theory and the link dismantling method.Next,the three-dimensional models of the pyramid unit,expansion unit,and array unit are established,and the folding motion simulation analysis is carried out.Based on the number of components,weight reduction rate,and deployable rate,the performance characteristics of the three types of mechanisms are described in detail.Finally,prototypes of the pyramid unit,combination unit,and expansion unit are developed to verify further the correctness of the configuration synthesis based on the pyramid.The proposed deployable mechanism provides aference for the design and application of antennas with a large aperture,high deployable rate,and lightweight.It has a good application prospect in the aerospace field.

Multiusers Parallel Competitive Channel Protocol Based on Unsaturated Service

In order to enhance the area throughput of next generation wireless local area network(WLAN)in high density scenarios,orthogonal frequency division multiple access(OFDMA)has been adopted as one of the key technologies in the next generation WLAN communication standards.However,the performance of the existing media access control(MAC)degrades significantly under unsaturated services.Therefore,this paper proposes a multi-user parallel contention channel MAC(MU-MAC)based on unsaturated services,which can effectively reduce the channel access conflict and improve the OFDMA access efficiency of cluster member nodes.On this basis,MU-MAC is enhanced for the spatial clustering group(SCG)formation protocol and support for the unsaturated service characteristics.Further,the optimal access radius when the service is in a non-saturated state is analyzed to make the relevant theoretical analysis more generally,and the expressions for the throughput and area throughput of the proposed protocol are modeled and derived.The simulation results verify the correctness of the theoretical analysis and the efficiency of the protocol performance.The results show that MU-MAC outperforms IEEE 802.11ax and OMAX protocol in area throughput by 40.72%and 104.15%,respectively.

Research on Human Activity Recognition Algorithm Based on LSTM-1DCNN

With the rapid advancement of wearable devices,Human Activities Recognition(HAR)based on these devices has emerged as a prominent research field.The objective of this study is to enhance the recognition performance of HAR by proposing an LSTM-1DCNN recognition algorithm that utilizes a single triaxial accelerometer.This algorithm comprises two branches:one branch consists of a Long and Short-Term Memory Network(LSTM),while the other parallel branch incorporates a one-dimensional Convolutional Neural Network(1DCNN).The parallel architecture of LSTM-1DCNN initially extracts spatial and temporal features from the accelerometer data separately,which are then concatenated and fed into a fully connected neural network for information fusion.In the LSTM-1DCNN architecture,the 1DCNN branch primarily focuses on extracting spatial features during convolution operations,whereas the LSTM branch mainly captures temporal features.Nine sets of accelerometer data from five publicly available HAR datasets are employed for training and evaluation purposes.The performance of the proposed LSTM-1DCNN model is compared with five other HAR algorithms including Decision Tree,Random Forest,Support Vector Machine,1DCNN,and LSTM on these five public datasets.Experimental results demonstrate that the F1-score achieved by the proposed LSTM-1DCNN ranges from 90.36%to 99.68%,with a mean value of 96.22%and standard deviation of 0.03 across all evaluated metrics on these five public datasets-outperforming other existing HAR algorithms significantly in terms of evaluation metrics used in this study.Finally the proposed LSTM-1DCNN is validated in real-world applications by collecting acceleration data of seven human activities for training and testing purposes.Subsequently,the trained HAR algorithm is deployed on Android phones to evaluate its performance.Experimental results demonstrate that the proposed LSTM-1DCNN algorithm achieves an impressive F1-score of 97.67%on our self-built dataset.In conclusion,the fusion of temporal and spatial information in the measured data contributes to the excellent HAR performance and robustness exhibited by the proposed 1DCNN-LSTM architecture.

Design and dynamic analysis of a scissors hoop-rib truss deployable antenna mechanism

As the support mechanism of space-borne antennas,space deployable antenna mechanism belongs to complex multi-closed-loop coupling mechanism,configuration design and dynamic analysis are more difficult than general parallel mechanism.In this paper,an unequal-length scissors mechanism(ULSM)is proposed by changing the position of the internal rotational joint through a basic scissors mechanism.A scissors hoop-rib truss deployable antenna mechanism(SHRTDAM)is constructed by replacing the parabolic rib with the ULSM.Kinematic analysis of SHRTDAM is conducted,and the degree of freedom(DOF)of the whole antenna mechanism is analyzed based on screw theory,the result showed that it has only one DOF.Velocity and acceleration characteristics of SHRTDAM are obtained by the screw derivative and rotation transformation.Based on Lagrange equation,dynamic model of this mechanism is established,the torque required to drive the mechanism is simulated and verified by Adams and MATLAB software.In addition,a ground experiment prototype of 1.5-m diameter was fabricated and a deployment test is conducted,which demonstrated the mobility and deployment performance of the whole mechanism.The mechanism proposed in this paper can provide a good reference for the design and analysis of large aperture space deployable antennas.

Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems

With the rapid and wide deployment of renewable energy,the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance.The output power of renewable energy is uncertain,and thus flexible regulation for the power balance is highly demanded.Considering the multi-timescale output characteristics of renewable energy,a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper.Through the multi-timescale decomposition algorithm on the basis of mathematical morphology,the multi-timescale components are separated to determine the flexibility requirements on different timescales.Based on the obtained flexibility requirements,a multi-timescale energy resources deployment model based on bi-level optimization is established considering the economic performance and the flexibility of system operation.This optimization model can allocate corresponding flexibility resources according to the economy,flexibility and reliability requirements of the power system,and achieve the trade-off between them.Finally,case studies demonstrate the effectiveness of our model and method.

A simulation-based emergency force planning method for social security events

The occurrence of social security events is uncertain, and the distribution characteristics are highly complex due to a variety of external factors, posing challenges to their rapid and effective handling. The scientific and reasonable requirement evaluation of the emergency force to deal with social security events is very urgent. Based on data analysis, this paper uses the neural network, operational research, modelling and simulation to predict and analyze social security events, studies the usage rule of emergency force and deployment algorithm, and conducts simulation experiments to evaluate and compare the different force deployment schemes for selection.