Radar fast long-time coherent integration via TR-SKT and robust sparse FRFT

Long-time coherent integration(LTCI)is an effective way for radar maneuvering target detection,but it faces the problem of a large number of search parameters and large amount of calculation.Realizing the simultaneous compensation of the range and Doppler migrations in complex clutter back-ground,and at the same time improving the calculation efficiency has become an urgent problem to be solved.The sparse transformation theory is introduced to LTCI in this paper,and a non-parametric searching sparse LTCI(SLTCI)based maneuvering target detection method is proposed.This method performs time reversal(TR)and second-order Keystone transform(SKT)in the range frequency&slow-time data to complete high-order range walk compensation,and achieves the coherent integra-tion of maneuvering target across range and Doppler units via the robust sparse fractional Fourier transform(RSFRFT).It can compensate for the nonlinear range migration caused by high-order motion.S-band and X-band radar data measured in sea clutter background are used to verify the detection performance of the proposed method,which can achieve better detection performance of maneuvering targets with less computational burden compared with several popular integration methods.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

Characteristics of proppant transport and placement within rough hydraulic fractures

A three-dimensional reconstruction of rough fracture surfaces of hydraulically fractured rock outcrops is carried out by casting process,a large-scale experimental setup for visualizing rough fractures is built to perform proppant transport experiments.The typical characteristics of proppant transport and placement in rough fractures and its intrinsic mechanisms are investigated,and the influences of fracture inclination,fracture width and fracturing fluid viscosity on proppant transport and placement in rough fractures are analyzed.The results show that the rough fractures cause variations in the shape of the flow channel and the fluid flow pattern,resulting in the bridging buildup during proppant transport to form unfilled zone,the emergence of multiple complex flow patterns such as channeling,reverse flow and bypassing of sand-carrying fluid,and the influence on the stability of the sand dune.The proppant has a higher placement rate in inclined rough fractures,with a maximum increase of 22.16 percentage points in the experiments compared to vertical fractures,but exhibits poor stability of the sand dune.Reduced fracture width aggravates the bridging of proppant and induces higher pumping pressure.Increasing the viscosity of the fracturing fluid can weaken the proppant bridging phenomenon caused by the rough fractures.

Analysis of the Application Effect of Tracheal Stent Placement in the Nutritional Support Treatment of Tracheoesophageal Fistula

Objective:To evaluate and analyze the application effect of tracheal stent placement in nutritional support therapy for tracheoesophageal fistula.Methods:Clinical data of 32 patients who underwent nutritional support therapy for tracheoesophageal fistula in our hospital from September 2021 to September 2022 were collected,and all patients underwent tracheal silicone stenting,comparing dyspnea classification and Karnofsky score before and after stenting,and conducting post-treatment follow-up.Results:In 32 patients with tracheoesophageal fistula,dyspnea grading improved from grades III and IV to grades 0 to II.Before treatment,10 patients(31.06%)were in grade IV,17 patients(53.12%)were in grade III,and five patients(15.62)were in grade II;after treatment,13 patients(40.63%)were in grade I,12 patients(37.50%)were in grade I,and seven patients(21.87%)were in grade 0(P<0.05);Karnofsky score(37.52±4.86 before treatment)improved significantly to 71.39±8.24 one week after treatment(P<0.05).Nine patients with tracheoesophageal fistula were placed with silicone Y14-10-10 stent,11 with silicone 18-14-14 stent,three with silicone Y15-12-12,and seven with silicone stent 16-13-13.Conclusion:Silicone tracheobronchial stent placement for the treatment of tracheoesophageal fistula is technically feasible,simple,and safe,with reliable near-term efficacy,and is worthy of popularization and application.

Clinical Study on Improving Articulation Clarity in Spastic Cerebral Palsy with 120 Cases of Oral-Facial Acupressure Combined with Oral Placement Therapy

Objective:To observe the efficacy of oral-facial acupressure combined with oral placement therapy(OPT)in improving articulation clarity in 120 children with spastic cerebral palsy,and to explore effective therapeutic solutions for speech disorders associated with spastic cerebral palsy.Methods:A total of 120 children with spastic cerebral palsy and speech disorders,meeting the inclusion criteria,were randomly assigned into two groups:60 cases in the treatment group and 60 cases in the control group.The treatment group received orofacial acupressure combined with OPT,while the control group received only OPT.The Oral Motor Function Assessment Scale(OMFAS),developed by the China Rehabilitation Research Centre(CRRC),was used to evaluate the treatment outcomes before and after the intervention.Results:After the treatment,both the treatment and control groups showed improved mobility of the mandible,lips,and tongue.However,the treatment group exhibited significantly better improvement than the control group,with the difference between the two groups being statistically significant(P<0.05).Conclusion:Oral-facial acupressure combined with OPT can effectively improve articulation clarity in children with spastic cerebral palsy.This combined therapy is recommended for clinical promotion and application.

A Novel Long-Time Coherent Integration Method for Moving Target Detection

Long-time coherent integration(LTCI)can remarkably improve the detection ability of radar for moving target.To increase the processing efficiency,this paper proposes a novel LTCI method based on segment time reversing transform(STRT)and chirp z-transform(CZT).In this method,STRT operation is first presented to estimate the Doppler ambiguity factor,and keystone transform(KT)is used to correct the whole range migration(RM).Then,CZT and non-uniform fast Fourier transform(NUFFT)are used to estimate the parameters as well as correct the second and third order Doppler frequency migration(DFM).Compared with the existing methods,the proposed method can achieve RM correction and DFM correction without repetitive operation.The effectiveness of the proposed method is validated by both simulated and real data.

LONG-TIME CONVERGENCE OF GENERALIZED DIFFERENCE METHOD FOR NAVIER-STOKES EQUATIONS

In this paper, we first provide a generalized difference method for the 2-dimensional Navier-Stokes equations by combing the ideas of staggered scheme m and generalized upwind scheme in space, and by backward Euler time-stepping. Then we apply the abstract framework of to prove its long-time convergence. Finally, a numerical example for solving driven cavity flows is given.

Long-time limit behavior of the solution to an atom's master equation

We study the long-time limit behavior of the solution to an atom＇s master equation. For the first time we derive that the probability of the atom being in the α-th （α = j ＋ 1 -jz, j is the angular momentum quantum number, jz is the z-component of angular momentum） state is {（1 - K/G）/[1 - （K/G）2j＋1]}（K/G）^α-1 as t → ＋∞, which coincides with the fact that when K/G 〉 1, the larger the a is, the larger the probability of the atom being in the α-th state （the lower excited state） is. We also consider the case for some possible generaizations of the atomic master equation.

Long-time evolution of charged grains in plasma under harmonic external force and after being withdrawn

Evolution of the charged grains in a two-dimensional dusty plasma under a spatially harmonic external force,in particular,their long-time behaviors after the force has been withdrawn,is studied by using molecular dynamics simulation.Under an external force and a grain–grain interaction force,initially homogeneously distributed grains can reach a quasistationary state in the form of a disk crystal.After the external force is withdrawn,the disk moves initially with its size and shape nearly unchanged until it rapidly stops moving,and eventually the disk grain rotates like a vortex.The time needed to reach the final state increases with the strength of the initial external force increasing.

LONG-TIME BEHAVIOR OF TRANSIENT SOLUTIONS FOR CELLULAR NEURAL NETWORK SYSTEMS

By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in generalized sense is obtained. This result reported has an important guide to concrete neural network designs.

Long-Time Relaxation and Residual Conductivity in GaP Irradiated by High-Energy Electrons

This paper presents the results of a study of long-time relaxation (LR) and residual conductivity in n-type gallium phosphide (GaP) crystals irradiated by 50 MeV electrons. A manifold increase in photosensitivity and quenching of residual conductivity was found as a result of irradiation. It is shown that LR in GaP is due to disordered regions (generated by electron irradiation) which have conductivity close to self one. The Fermi level in the disordered regions is determined by which is located deep in the forbidden band (Ее - 1.0 eV). LR effect is mainly explained by a spatial separation of electrons and holes, recombination of which is prevented by potential barriers. The observed increase in conductivity is associated with the increase in the concentration of minority carriers as well as with increase of the Hall mobility at the sample illumination.

Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.

Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

In the smart city paradigm, the deployment of Internet of Things(IoT) services and solutions requires extensive communication and computingresources to place and process IoT applications in real time, which consumesa lot of energy and increases operational costs. Usually, IoT applications areplaced in the cloud to provide high-quality services and scalable resources.However, the existing cloud-based approach should consider the above constraintsto efficiently place and process IoT applications. In this paper, anefficient optimization approach for placing IoT applications in a multi-layerfog-cloud environment is proposed using a mathematical model (Mixed-Integer Linear Programming (MILP)). This approach takes into accountIoT application requirements, available resource capacities, and geographicallocations of servers, which would help optimize IoT application placementdecisions, considering multiple objectives such as data transmission, powerconsumption, and cost. Simulation experiments were conducted with variousIoT applications (e.g., augmented reality, infotainment, healthcare, andcompute-intensive) to simulate realistic scenarios. The results showed thatthe proposed approach outperformed the existing cloud-based approach interms of reducing data transmission by 64% and the associated processingand networking power consumption costs by up to 78%. Finally, a heuristicapproach was developed to validate and imitate the presented approach. Itshowed comparable outcomes to the proposed model, with the gap betweenthem reach to a maximum of 5.4% of the total power consumption.

Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows.The individual tasks of a scientific work-flow necessitate a diversified number of large states that are spatially located in different datacenters,thereby resulting in huge delays during data transmis-sion.Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets.Therefore,this fixed storage strategy creates huge amount of bottleneck in its storage capacity.At this juncture,integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and optimizing the energy and time incurred in data transmission across different datacentres remains a challenge.In this paper,Adaptive Cooperative Foraging and Dispersed Foraging Strategies-Improved Harris Hawks Optimization Algorithm(ACF-DFS-HHOA)is proposed for optimizing the energy and data transmission time in the event of placing data for a specific scientific workflow.This ACF-DFS-HHOA considered the factors influencing transmission delay and energy consumption of data centers into account during the process of rationalizing the data placement of scientific workflows.The adaptive cooperative and dispersed foraging strategy is included in HHOA to guide the position updates that improve population diversity and effectively prevent the algorithm from being trapped into local optimality points.The experimental results of ACF-DFS-HHOA confirmed its predominance in minimizing energy and data transmission time incurred during workflow execution.

Different percutaneous transhepatic biliary stent placements and catheter drainage in the treatment of middle and low malignant biliary obstruction

BACKGROUND For cases of middle and low biliary obstruction with left and right hepatic duct dilatation,the type of approach and whether different approaches affect the difficulty of puncture operation and intraoperative and postoperative complications have not been discussed in detail.AIM To compare the efficacy of different percutaneous transhepatic biliary stent placements and catheter drainage in treating middle and low biliary obstruction.METHODS A retrospective analysis was performed on the medical records of 424 patients with middle and low biliary obstruction who underwent percutaneous liver puncture biliary stent placement and catheter drainage at the Department of Interventional Radiology,Shaanxi Provincial People’s Hospital between March 2016 and March 2022.Based on the puncture path,patients were categorized into two groups:Subxiphoid left hepatic lobe approach group(Group A,224 cases)and right intercostal,right hepatic lobe approach group(Group B,200 cases).Liver function improvement,postoperative biliary bleeding incidence,postoperative pain duration,and abdominal effusion leakage around the drainage tube were compared between the two groups at 3 d and 1 wk after the surgery.Patient survival time was recorded during follow-up.RESULTS All 424 surgeries were successful without adverse events.Group A comprised 224 cases,and Group B had 200 cases.There was no statistically significant difference in basic data between Group A and Group B(P>0.05).No significant difference in postoperative biliary bleeding incidence was observed between the groups(P>0.05).The decreased rates for total bilirubin(Group A:69.23±4.50,Group B:63.79±5.65),direct bilirubin(Group A:79.30±11.19,Group B:63.62±5.64),and alkaline phosphatase(Group A:60.51±12.23,Group B:42.68±23.56)in the 1st wk after surgery were significantly faster in Group A than in Group B.The decreased rate of gamma-glutamyl transpeptidase was also significantly faster in Group A at both 3 d(Group A:40.56±10.32,Group B:32.22±5.12)and 1 wk(Group A:73.19±7.05,Group B:58.81±18.98)after surgery(P<0.05).Group A experienced significantly less peritoneal effusion leakage around the drainage tube than Group B(P<0.05).The patient survival rate was higher in Group A compared to Group B(P<0.05).CONCLUSION In treating jaundice patients with middle and low biliary obstruction,a percutaneous left liver puncture demonstrated better clinical efficacy than a percutaneous right liver puncture.

Ruppert's Delaunay Triangulation Refinement Scheme for Optimal RSUs Placement in Vehicle to Infrastructure Communication Network

Road Side Units(RSUs)are the essential component of vehicular communication for the objective of improving safety and mobility in the road transportation.RSUs are generally deployed at the roadside and more specifically at the intersections in order to collect traffic information from the vehicles and disseminate alarms and messages in emergency situations to the neighborhood vehicles cooperating with the network.However,the development of a predominant RSUs placement algorithm for ensuring competent communication in VANETs is a challenging issue due to the hindrance of obstacles like water bodies,trees and buildings.In this paper,Ruppert’s Delaunay Triangulation Refinement Scheme(RDTRS)for optimal RSUs placement is proposed for accurately estimating the optimal number of RSUs that has the possibility of enhancing the area of coverage during data communication.This RDTRS is proposed by considering the maximum number of factors such as global coverage,intersection popularity,vehicle density and obstacles present in the map for optimal RSUs placement,which is considered as the core improvement over the existing RSUs optimal placement strategies.It is contributed for deploying requisite RSUs with essential transmission range for maximal coverage in the convex map such that each position of the map could be effectively covered by at least one RSU in the presence of obstacles.The simulation experiments of the proposed RDTRS are conducted with complex road traffic environments.The results of this proposed RDTRS confirmed its predominance in reducing the end-to-end delay by 21.32%,packet loss by 9.38%with improved packet delivery rate of 10.68%,compared to the benchmarked schemes.

UUV水下动态布放回收流体动力性能数值模拟

UUV与水下对接装置对接的过程中存在双体干扰问题,非线性特征强烈。为了探明UUV在对接过程中流体动力随着对接姿态以及运动距离变化规律,本文借助Fluent软件中的动网格技术开展非定常工况下UUV动态回收过程的数值模拟研究。系统分析UUV运动速度、运动姿态(主要是攻角)对其流体动力性能以及流场结构的影响。本文研究成果可为后续样机试验提供技术指导和理论支撑。

Optimal Placement and Sizing of Distributed Generations for Power Losses Minimization Using PSO-Based Deep Learning Techniques

The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.

双目标优化与生成对抗网络结合的框架结构阻尼器布置方案智能设计方法

为实现框架结构的阻尼器智能化布置,结合减震设计原理和智能算法,采用双目标优化算法和生成对抗网络算法分别进行阻尼器竖向和水平智能布置研究,并将该方法应用到两个框架结构减震设计工程案例中。在框架结构减震设计中,采用双目标优化算法进行阻尼器竖向布置,并与逐层逼近法、工程师设计和非减震设计进行对比,结果表明,采用该优化算法得到的阻尼器竖向布置方案能有效降低层间位移角和楼层加速度,提高结构的抗震性能。在确定各楼层的阻尼器数量后,利用训练好的生成对抗网络生成模型,可快速、自动地选择和确定各楼层阻尼器的平面安装位置,生成的平面布置与工程师设计的平面布置在相似性差异度综合评价指标上小于临界值0.1,说明两者相似度较高,且有利于提高原结构的抗扭能力。将双目标优化算法与生成对抗网络相结合,不仅能满足框架结构的减震性能目标,而且可实现阻尼器布置方案的智能设计,提升减震工程设计效率。