Deployment Characteristics Research Articles

Notch Flexure as Kirigami Cut for Tunable Mechanical Stretchability towards Metamaterial Application

ABSTRACT Kirigami is an art of paper cutting, which can be used in mechanical metamaterials, actuators, and energy absorption based on its deployable and load-deflection characteristics. Traditional cuts with zero width produce undesirable plastic deformation or even tear fracture due to stress concentration in stretching. This study proposes to enlarge the cut width into a notch flexure, which is applied to an orthogonality-cutted kirigami sheet, which buckles out of plane into a 3D configuration patterns under uniaxial tension. The use of compliant beam as the notch makes the stress distribution around the cuts more uniform in both elastic and elastoplastic regime. The experimental and numerical results show that by tuning the geometric parameters of cuts and material properties of the sheets, the trigger condition of 3D patterns can be adjusted. Potential capability of tunable phononic wave propagation in this kirigami-inspired metamaterial is demonstrated. This design methodology offers a theoretical guide for kirigami-based structures.

A Current Sharing State Estimation Method of Redundant Switched-Mode Power Supply Based on LSTM Neural Network

Redundant Switched-mode Power supplies (SMPSs) are commonly used to improve electronic systems’ reliability, and accurate estimation of the current sharing state is significant for evaluating the system’s health. Currently, the current sharing state estimation is mainly realized by using current sensors to detect each branch’s current, and the deployment and maintenance costs are high. In this paper, a method for power supply current sharing state estimation based on LSTM recurrent neural network is proposed. By taking advantage of subtle differences in the inherent spectral characteristics of SMPSs, this method only needs to detect the voltage ripple at the switching frequency of the load terminal to estimate the output current of each power supply branch. The verification experiment on the three-power redundant experimental platform shows that the estimation error is less than 10%. The method has the characteristics of simple structure, non-invasion, convenient deployment and maintenance, so it has high application and promotion value.

On the nonlinear dynamics of a Kresling-pattern origami under harmonic force excitation

Kresling origami-inspired cylindrical structures have received considerable attention due to their effective deployment characteristics, programmable dual-directional and multifunctional properties, along with their ability to support loads. The Kresling origami investigations to date have focused mostly on their geometry, kinematics, and quasi-static mechanics. While recent works have started to uncover the Kresling origami’s transient deployment dynamics and linear vibration/wave propagation features, the rich nonlinear dynamics of Kresling origami-inspired structures under consistent external excitations have yet to be examined and understood. Given that Kresling origami elements are highly nonlinear so their dynamic responses can be extremely complex under external disturbances, and the fact that in many applications they are embedded in mechanical systems that are continuously excited, such as in robotics, air and ground vehicles, and impact, noise, and vibration isolation structures, this is an important and nontrivial research issue that needs to be addressed.To advance the state of the art, the goal of this research is to explore and uncover the nonlinear dynamics of Kresling origami-inspired tubular structures under consistent forced excitations, in particular harmonic loadings. Time and frequency domain analyses are performed and bifurcation diagrams are developed and analyzed for a range of forcing amplitudes and frequencies. This research reveals the complex responses of Kresling origami-inspired systems, i.e., existence of multiple period-1 attractors, period-n (n>1) attractors, jump from one attractor (limit-cycle) to another attractor, and presence of chaotic attractors for a range of input forcing parameters. The noteworthy result of this study also concerns a synchronization of the origami cylinder’s steady-state axial and rotational (twist) displacements. Without such a forced nonlinear dynamic analysis, these findings have not been and cannot be discovered in previous studies. The insights and knowledge uncovered in this investigation are valuable in raising awareness and providing guidance in the design and control of Kresling origami-based structures for realistic engineering operations, where external dynamic disturbances are often unavoidable.

Stochastic Geometry-Based Analysis of Cache-Enabled Hybrid Satellite-Aerial-Terrestrial Networks With Non-Orthogonal Multiple Access

Due to the emergence of non-terrestrial platforms with extensive coverage, flexible deployment, and reconfigurable characteristics, the hybrid satellite-aerial-terrestrial networks (HSATNs) can accommodate a great variety of wireless access services in different applications. To effectively reduce the transmission latency and facilitate the frequent update of files with improved spectrum efficiency, we investigate the performance of cache-enabled HSATN, where the user retrieves the required content files from the cache-enabled aerial node (AN) or the satellite with the non-orthogonal multiple access (NOMA) scheme. If the required content files of the user are cached in the AN, the cache-enabled node would serve directly. Otherwise, the user would retrieve the content file from the satellite system, where the satellite system seeks opportunities for proactive content pushing to ANs during the user content delivery phase. Specifically, taking into account the uncertainty of the number and location of ANs, along with the channel fading of terrestrial users, the outage probability and hit probability of the considered network are, respectively, derived based on stochastic geometry. Numerical results unveil the effectiveness of the cache-enabled HSATN with the NOMA scheme and proclaim the influence of key factors on the system performance. The realistic, tractable, and expandable framework, as well as associated methodology, provide both useful guidance and a solid foundation for evolved networks with advanced configurations in the performance of cache-enabled HSATN.

Remote Arrhythmia Detection for Eldercare in Malaysia.

Cardiovascular disease continues to be one of the most prevalent medical conditions in modern society, especially among elderly citizens. As the leading cause of deaths worldwide, further improvements to the early detection and prevention of these cardiovascular diseases is of the utmost importance for reducing the death toll. In particular, the remote and continuous monitoring of vital signs such as electrocardiograms are critical for improving the detection rates and speed of abnormalities while improving accessibility for elderly individuals. In this paper, we consider the design and deployment characteristics of a remote patient monitoring system for arrhythmia detection in elderly individuals. Thus, we developed a scalable system architecture to support remote streaming of ECG signals at near real-time. Additionally, a two-phase classification scheme is proposed to improve the performance of existing ECG classification algorithms. A prototype of the system was deployed at the Sarawak General Hospital, remotely collecting data from 27 unique patients. Evaluations indicate that the two-phase classification scheme improves algorithm performance when applied to the MIT-BIH Arrhythmia Database and the remotely collected single-lead ECG recordings.

Digitalisation and sustainable energy transitions in Africa: assessing the impact of policy and regulatory environments on the energy sector in Nigeria and South Africa

BackgroundDigital technologies have unique characteristics for achieving radically disruptive transitions within the energy sector. They provide opportunities for new production and consumption models between micro-producers and consumers of electricity within communities in a way that transforms the traditional energy generation and consumption model. The study critically assessed the digitalisation of energy systems in Africa within the context of existing policy frameworks in the quest to achieve sustainable energy transitions in Africa. It investigated how digital technologies such as blockchain, digital platforms and smart grids were adopted and implemented within the energy sector to achieve new energy production and consumption models that are both environmentally sustainable and socially inclusive. This assessment was done within the context of existing policy and regulatory frameworks of the society where the use cases were domiciled.MethodsThe aim of the research was to investigate how sustainable energy transitions are being achieved in Nigeria and South Africa through the digitalisation of energy systems. A qualitative methodological approach was done in three stages—a document analysis that reviewed relevant literature on the energy sector policies in Nigeria and South Africa; the next step involved a comparative case study conducted to assess the characteristics of digital technology deployment in each country’s energy transition. Finally, outcomes of the comparative case studies were then situated within the context of existing policies within the countries covered by the study.ResultsResults from the research indicate that Africa is still in the early stages of adoption and application of digital technologies such as blockchain and smart grids within the energy sector. The results also showed a disconnect between the policy environment and industry efforts at achieving this. The current applications as exemplified in the use cases by the three companies covered in this study indicates that Africa's sustainable energy transition is in a rudimentary or early adoption stage, and they are not currently aided by the policy environments in which such projects are domiciled.ConclusionsThe research provides deep insights into the current state and developments within the energy sector especially in relation to how digital technologies are being adopted and implemented in solving the energy poverty prevalent across sub-Saharan Africa.

An eco-friendly and efficient trigeneration system for dual-fuel marine engine considering heat storage and energy deployment

Under the background of energy and environmental crisis, to achieve energy-conservation and emission-reduction, we urgently need efficient and sustainable technologies to improve the energy efficiency and reduce emissions of the shipping industry. For this purpose, an eco-friendly and efficient trigeneration system is proposed. Initially, the mathematical model of the trigeneration system is established, and the fidelity is verified by comparing with the relevant investigation. Subsequently, the influence of fluid types and sensitivity parameters on the performance is discussed. Then, the conversion factor is introduced to quantify the contribution of each subsystem to the trigeneration system, and the optimal design parameters are obtained through the three-objective optimization. After determining the optimal design parameters, the change rule of the performance under working conditions is analyzed. Ultimately, the positive effect of heat storage and energy deployment characteristics in accumulator on dynamic-energy-demand is explored. The calculation results present that the power, thermal-efficiency, exergy-efficiency, the emission-reduction of the system, under the maximum working condition, reach 347.08 kW, 23.65%, 49.29% and 2210.04 t/year, and the recovery-time is only 7.35 years. The results prove that the system not only has excellent thermodynamic performance, economic and environmental benefits, but also can meet the dynamic-energy-demand of the marine. It provides theoretical guidance for researchers who are committed to overcoming the low-efficiency of waste-heat utilization, and brings enlightenment to enterprises for the research and innovation of waste heat recovery technology.

Point-of-care 3D printing: a low-cost approach to teaching carotid artery stenting

BackgroundCarotid Artery Stenting (CAS) is increasingly being used in selected patients as a minimal invasive approach to carotid endarterectomy. Despite the long standing tradition of endovascular treatments, visual feedback during stent-deployment is impossible to obtain as deployment is performed under fluoroscopic imaging. Furthermore, the concept of stent-placement is often still unclear to patients. 3D Printing allows to replicate patient-specific anatomies and deploy stents inside them to simulate procedures. As such these models are being used for endovascular training as well as patient education.PurposeTo our knowledge, this study reports the first use of a low-cost patient-specific 3D printed model for teaching CAS deployment under direct visualization, without fluoroscopy.MethodologyA CT-angiogram was segmented and converted to STL format using Mimics inPrint™ software. The carotid arteries were bilaterally truncated to fit the whole model on a Formlabs 2 printer without omitting the internal vessel diameter. Next, this model was offset using a 1 mm margin. A ridge was modelled on the original vessel anatomy which was subsequently subtracted from the offset model in order to obtain a deroofed 3D model. All vessels were truncated to facilitate post-processing, flow and guide wire placement.ResultsCarotid artery stents were successfully deployed inside the vessel. The deroofing allows for clear visualization of the bottlenecks and characteristics of CAS deployment and positioning, including stent foreshortening, tapering and recoil. This low-cost 3D model provides visual insights in stent deployment and positioning, and can allow for patient-specific procedure planning.ConclusionsThe presented approach demonstrates the use of low-cost 3D Printed CAS models in teaching complex stent behavior as observed during deployment. Two main findings are illustrated. On one hand, the feasibility of low-cost in-hospital model production is shown. On the other hand, the teaching of CAS deployment bottlenecks at the carotid level without the need for fluoroscopic guidance, is illustrated. The observed stent characteristics as shown during deployment are difficult to assess in radiologic models. Furthermore, printing patient-specific 3D models preoperatively could possibly assist in accurate patient selection, preoperative planning, case-specific training and patient education.

Brain-Immune Interactions as the Basis of Gulf War Illness: Clinical Assessment and Deployment Profile of 1990-1991 Gulf War Veterans in the Gulf War Illness Consortium (GWIC) Multisite Case-Control Study.

The Boston University-based Gulf War Illness Consortium (GWIC) is a multidisciplinary initiative developed to provide detailed understanding of brain and immune alterations that underlie Gulf War illness (GWI), the persistent multisymptom disorder associated with military service in the 1990–1991 Gulf War. The core GWIC case-control clinical study conducted in-depth brain and immune evaluation of 269 Gulf War veterans (223 GWI cases, 46 controls) at three U.S. sites that included clinical assessments, brain imaging, neuropsychological testing, and analyses of a broad range of immune and immunogenetic parameters. GWI cases were similar to controls on most demographic, military, and deployment characteristics although on average were two years younger, with a higher proportion of enlisted personnel vs. officers. Results of physical evaluation and routine clinical lab tests were largely normal, with few differences between GWI cases and healthy controls. However, veterans with GWI scored significantly worse than controls on standardized assessments of general health, pain, fatigue, and sleep quality and had higher rates of diagnosed conditions that included hypertension, respiratory and sinus conditions, gastrointestinal conditions, and current or lifetime depression and post-traumatic stress disorder. Among multiple deployment experiences/exposures reported by veterans, multivariable logistic regression identified just two significant GWI risk factors: extended use of skin pesticides in theater (adjusted OR = 3.25, p = 0.005) and experiencing mild traumatic brain injury during deployment (OR = 7.39, p = 0.009). Gulf War experiences associated with intense stress or trauma (e.g., participation in ground combat) were not associated with GWI. Data and samples from the GWIC project are now stored in a repository for use by GWI researchers. Future reports will present detailed findings on brain structure and function, immune function, and association of neuroimmune measures with characteristics of GWI and Gulf War service.

Numerical Analysis for Non-Uniformity of Balloon-Expandable Stent Deployment Driven by Dogboning and Foreshortening.

Stenting is the most common intervention for arteriosclerosis treatment; however, the success of the treatment depends on the incidence of in-stent restenosis (ISR). Stent deployment characteristics are major influencers of ISR and can be measured in terms of dogboning, asymmetry, and foreshortening. This study aimed to analyse the implications of balloon and stent-catheter assembly parameters on the stent deployment characteristics. Experimental approach to analyse the impact of the balloon and stent-catheter assembly parameters on stent deployment characteristics is a time-consuming and complex task, whereas numerical methods prove to be quick, efficient, and reliable. In this study, eleven finite element models were employed to analyse non-uniform balloon stent expansion pattern, comprised of variation in, stent axial position on balloon, balloon length, balloon folding pattern, and balloon wall thickness. Obtained results suggest that the axially noncentral position of the stent on balloon and variable balloon thickness lead to non-uniform stent deployment pattern. Also, it was proved that variation in balloon length and balloon folding pattern influence deployment process. Improved positional accuracies, uniform balloon wall thickness, and selection of the appropriate length of a balloon for selected stent configuration will help to minimize dogboning, asymmetry, and foreshortening during non-uniform stent expansion, thereby reducing the risk of restenosis. The stated numerical approach will be helpful to optimize stent catheter assembly parameters thus minimizing in-vitro tests and product development time.

Trajectory-aware spatio-temporal range query processing for unmanned aerial vehicle networks

Unmanned aerial vehicle (UAV) network is widely used in environmental monitoring, target searching and rescuing, logistics, and other fields due to its characteristics of large-scale coverage, rapid deployment and strong resistance to destruction. When users are interested in sensory data in certain areas covered by UAV networks, they can send a spatio-temporal range query with time and geography constraints through the ground station. For example, obtaining the temperature information around fire points in the forest within an hour before the fire bursts out. Then, UAVs that carry the query results will return the data to the ground station through multi-hop routing. However, most of the existing spatio-temporal range query algorithms are designed for static networks. How to conduct spatio-temporal range queries in the UAV networks is still an open problem. In this paper, we propose a Trajectory-Aware Spatio-Temporal range query processing algorithm (TAST) for UAV networks. The ground station takes advantage of the pre-planned trajectory information of UAVs to build the topology change model of the UAV network, which can reflect the changes of UAVs’ communication links and neighbors. Furthermore, the static topology change graph (TCG) is proposed for optimizing the routing of query results in the spatio-temporal query processing. Next, we propose a Trajectory-Aware Spatio-Temporal range query processing algorithm based on packet Splitting (TASTS), which is used to split large query results into multiple small packets called unit packets, and each unit packet is transmitted back to the ground station independently and efficiently. Finally, we evaluated our algorithms through simulation experiments. The simulation results show that TAST and TASTS perform well in terms of query success rate, query efficiency and overhead ratio.

Veteran help-seeking behaviour for mental health issues: a systematic review

IntroductionServing military personnel and veterans have been identified to have a high prevalence of mental health disorders. Despite this, only a significantly small number seek mental healthcare. With the UK...

Physical Simulation Experimental Technology and Mechanism of Water Invasion in Fractured-Porous Gas Reservoir: A Review

In the development process for a fractured-porous gas reservoir with developed fracture and active water, edge water or bottom water easily bursts rapidly along the fracture to the production well, and the reservoir matrix will absorb water, reducing the gas percolation channel and increasing the gas phase percolation resistance of the reservoir matrix, therefor reducing the stable production capacity and recovery efficiency of the gas reservoir. For this reason, this paper investigates physical simulation experimental technology and mechanisms as reported by both domestic and foreign scholars regarding water invasion in fractured-porous gas reservoirs. In this paper, it is considered that the future trend and focus of water invasion experiments will be to establish a more realistic three-dimensional physical model on the basis of fine geological description, combined with gas reservoir well pattern deployment and production characteristics, and to fully consider the difference between horizontal and vertical water invasion along the reservoir side; at the same time, dynamic parameters such as model pressure field and water saturation field can be obtained in real time. Based on this understanding of the water invasion mechanism of fractured-porous gas reservoirs, we propose the next research direction and the development countermeasures such as water controls, drainage, and dissolved water seals and water locks to combat water invasion in reservoirs, along with the injection of gas to replenish formation energy, etc., so as to slow down and control the influence of water invasion.

Prevalence of Potentially Morally Injurious Events in Operationally Deployed Canadian Armed Forces Members.

As moral injury is a still-emerging concept within the area of military mental health, prevalence estimates for moral injury and its precursor, potentially morally injurious events (PMIEs), remain unknown for many of the world's militaries. The present study sought to estimate the prevalence of PMIEs in the Canadian Armed Forces (CAF), using data collected from CAF personnel deployed to Afghanistan, via logistic regressions controlling for relevant sociodemographic, military, and deployment characteristics. Analyses revealed that over 65% of CAF members reported exposure to at least one event that would be considered a PMIE. The most commonly PMIEs individuals reported included seeing ill or injured women and children they were unable to help (48.4%), being unable to distinguish between combatants and noncombatants (43.6%), and finding themselves in a threatening situation where they were unable to respond due to the rules of engagement under which they were required to operate (35.4%). These findings provide support for both the presence of exposure to PMIEs in CAF members and the need for formal longitudinal data collection regarding PMIE exposure and moral injury development.

Using an Improved PSO-SVM Model to Recognize and Classify the Image Signals

Image recognition is an important field of artificial intelligence. Its basic idea is to use computers to automatically classify different scenes in the acquired images, instead of traditional manual classification tasks. In this paper, through the analysis of rough set theory and artificial intelligence network, as well as the role of the two in image recognition, the rough set theory and artificial intelligence network are organically combined, and a network based on rough set theory and artificial intelligence network is proposed. Using BP artificial intelligence network model, improved BP artificial intelligence network model, and improved PSO-SVM model to identify and classify the extracted characteristic signals and compare the results, all reached 85% correct rate. The PCA and SVM are combined and applied to the MNIST handwritten digit collection for recognition and classification. At the data level, dimensionality reduction is performed on high-dimensional image data to compress the data. This greatly improves the performance of the algorithm, the recognition accuracy rate is as high as 98%, and the running time is shortened by about 90%. The model first preprocesses the original image data and then uses rough set theory to select features, which reduces the input dimension of the artificial intelligence network, improves the learning and recognition speed of the artificial intelligence network, and further improves the accuracy of recognition. The paper applies the model to handwritten digital image recognition, and the experimental results show that the model is effective and feasible. The system has the characteristics of easy deployment and easy maintenance and integration. Experiments show that the system has good time characteristics in the process of multialgorithm parallel image fusion processing.

Semiquantitative Chest Computed Tomography Assessment Identifies Expiratory Central Airway Collapse in Symptomatic Military Personnel Deployed to Iraq and Afghanistan.

Purpose:We noted incidental findings on chest computed tomography (CT) imaging of expiratory central airway collapse (ECAC) in dyspneic patients after military deployment to southwest Asia (mainly Iraq and Afghanistan). We developed a standardized chest CT protocol with dynamic expiration to enhance diagnostic reliability and investigated demographic, clinical, and deployment characteristics possibly associated with ECAC.Materials and Methods:We calculated ECAC in 62 consecutive post-9/11 deployers with dyspnea who underwent multi-detector chest CT acquisition. ECAC was defined as ≥70% reduction in the cross-sectional tracheal area at dynamic expiration. We compared demographics (age, smoking, body mass index), comorbid conditions (gastroesophageal reflux, obstructive sleep apnea [OSA]), and clinical findings (air trapping, forced expiratory volume in 1 second percent predicted) in deployers with and without ECAC. We examined associations between ECAC and forced expiratory volume in 1 second percent predicted, air trapping, OSA, deployment duration, and blast exposure.Results:Among 62 consecutive deployers with persistent dyspnea, 37% had ECAC. Three had severe (>85%) collapse. Those with ECAC were older (mean age 46 vs. 40 y, P=0.02), but no other demographic or clinical characteristics were statistically different among the groups. Although not statistically significant, ECAC odds were 1.5 times higher (95% confidence interval: 0.9, 2.5) for each additional year of southwest Asia deployment. Deployers with ECAC had 1.6 times greater odds (95% confidence interval: 0.5, 4.8) of OSA.Conclusions:Findings suggest that ECAC is common in symptomatic southwest Asia deployers. Chest high-resolution CT with dynamic expiration may provide an insight into the causes of dyspnea in this population, although risk factors for ECAC remain to be determined. A standardized semiquantitative approach to CT-based assessment of ECAC should improve reliable diagnosis in dyspneic patients.

Individual and experiential predictors of character development across the deployment cycle

How soldiers adapt to and change in response to the deployment experience has received a great deal of attention. What predicts which soldiers are resilient and which soldiers decline in character strengths across the deployment transition? We examined this question in two analyses drawing from the same data source of soldiers deploying for the first time (Analysis 1: N = 179,026; Analysis 2: N = 85,285; Mage = 24.6–24.7 years old, SD = 4.87; 66.5–66.9% White). Specifically, we examined how individual (e.g. sociodemographic, military) and deployment (e.g. stressful experiences) characteristics predict character development across the deployment cycle. Character strengths were assessed once before and up to three times after soldiers’ return from deployment. Reproducing previous work, we found evidence for two classes of change—a resilient class (“stable high”) and a recovery class (“persistent low”). The strongest predictor of high, resilient character strength levels was better self-rated health at baseline. The findings are discussed in the context of the mechanisms that drive character development, evidence for post-traumatic growth, and practical implications for the U.S. Army.

Exposure to Civilian Casualties Is Related to Guilt and Suicidality in Post 9/11 Veterans of Iraq and Afghanistan

The nature of America’s Post 9/11 wars has often placed service members in close proximity to not only enemy and friendly forces, but also civilian noncombatants. The unique psychological consequences of witnessing, attempting to save, or feeling responsible for causing harm to noncombatants are relatively understudied. However, guilt has been shown to be both a direct predictor of suicidal ideation and also to act as a moderator and mediator in the relationship between trauma exposure and suicidality. Despite its established importance, there are few studies attempting to quantitatively explain the specific sources of guilt for combat veterans who may have been exposed to multiple and varied traumas. This study used a hierarchical multiple regression of self-report online survey data from Post 9/11 veterans of Iraq and/or Afghanistan (n = 184) to test the hypothesis that combat experiences with civilian casualties would predict guilt above and beyond other personal, military, and deployment characteristics and experiences. The results show a strong correlation between guilt and suicide and a moderate association between experiences involving civilian casualties and guilt. Additionally, feeling personally responsible for killing or wounding civilian noncombatants results in stronger feelings of guilt than either witnessing or providing medical assistance to them. The outcome of this study offers insights for tailoring interventions for veterans who report having combat experiences involving civilian casualties in order to improve how we address guilt and suicide risk. In doing so, the field may provide more comprehensive and relevant mental health support to combat veterans.

Covert Communication in UAV-Assisted Air-Ground Networks

Unmanned aerial vehicle (UAV) assisted communication is a promising technique for future wireless networks due to its characteristics of low cost and flexible deployment. However, the high possibility of line-of-sight (LoS) air-ground channels may result in a great risk of being attacked by malicious users. Especially compared to the encryption and physical layer security that prevent eavesdropping, covert communication aims at hiding the existence of transmission, which is able to satisfy the more critical requirement of security. Thus, in this article, we focus on the covert communication issues of UAV-assisted wireless networks. First, the preliminaries of secure communications including encryption, physical layer security and covert communication are discussed. Then, current works and typical applications of UAV in covert communications are demonstrated. We then propose two schemes to enhance the covertness of UAV-assisted networks for some typical scenarios. Specifically, to improve the covert rate in UAV-assisted data dissemination, an iterative algorithm is proposed to jointly optimize the time slot, transmit power and trajectory. For the covertness of ground-air communication, a friendly jammer is employed to confuse the wardens, where the location of the jammer, the jamming power and the legitimate transmit power are jointly optimized. Numerical results are presented to validate the performance of these two proposed schemes. Finally, several challenges and promising directions are pointed out.

Research on failure rate of self-service payment terminal of power supply company based on cloud computing

With the continuous development of power companies, the load on the user side continues to diversify, the traditional payment methods in the power system are constantly updated, and the scale of self-service payment terminals has been fully expanded. However, as the scale of self-service payment terminals becomes larger and terminal equipment functions become more abundant, the failure rate of terminal equipment is also on the rise. Cloud computing can provide a large number of low-cost computing and storage resources, and has the characteristics of easy deployment and strong scalability, which can meet the software and hardware needs of big data analysis. Therefore, the effective integration of cloud computing and big data technology and the use of their respective advantages have important practical significance in the big data analysis of equipment failure. Completing the prediction of the failure rate of the terminal equipment according to the designed big data analysis framework will help to arrange the maintenance plan of the terminal equipment reasonably and improve the reliability of the power self-service payment terminal.