The internal circulations on internal mass transfer rate of a single drop in nonlinear uniaxial extensional flow

The internal flow of a droplet in the nonlinear extensional flow field will exhibit more than two internal circulations with the variation of nonlinear intensity(E).In this paper,the effect of positions and sizes of internal circulations on internal mass transfer rate of a single spherical droplet in a nonlinear extensional flow field is studied and compared with that in a linear extensional flow field.The simulation results show that when E≥0,there are two symmetrical internal circulations in the droplet,which is the same with that in a linear extensional flow.The limit value of mass transfer rate Sh is 15,which is equal to that in a linear extensional flow,no matter how large E is.When E≤-3/7,the number of internal flow circulation of a droplet increase to four and the transfer rate Sh increases.When E=-1,the maximum internal transfer rate Sh equals 30 which is twice of that in a linear extensional flow.The generation of new flow circulations in droplets and the circulation positions will enhance mass transfer when E≤-3/7,which provides a new idea for enhancing the internal mass transfer rate of droplets.

Typhoon Case Comparison Analysis Between Heterogeneous Many-Core and Homogenous Multicore Supercomputing Platforms

In this paper,a typical experiment is carried out based on a high-resolution air-sea coupled model,namely,the coupled ocean-atmosphere-wave-sediment transport(COAWST)model,on both heterogeneous many-core(SW)and homogenous multicore(Intel)supercomputing platforms.We construct a hindcast of Typhoon Lekima on both the SW and Intel platforms,compare the simulation results between these two platforms and compare the key elements of the atmospheric and ocean modules to reanalysis data.The comparative experiment in this typhoon case indicates that the domestic many-core computing platform and general cluster yield almost no differences in the simulated typhoon path and intensity,and the differences in surface pressure(PSFC)in the WRF model and sea surface temperature(SST)in the short-range forecast are very small,whereas a major difference can be identified at high latitudes after the first 10 days.Further heat budget analysis verifies that the differences in SST after 10 days are mainly caused by shortwave radiation variations,as influenced by subsequently generated typhoons in the system.These typhoons generated in the hindcast after the first 10 days attain obviously different trajectories between the two platforms.

Automatic recognition of depression based on audio and video:A review

Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

A novel quantum information hiding protocol based on entanglement swapping of high-level Bell states

Using entanglement swapping of high-level Bell states, we first derive a covert layer between the secret message and the possible output results of the entanglement swapping between any two generalized Bell states, and then propose a novel high-efficiency quantum information hiding protocol based on the covert layer. In the proposed scheme, a covert channel can be built up under the cover of a high-level quantum secure direct communication （QSDC） channel for securely transmitting secret messages without consuming any auxiliary quantum state or any extra communication resource. It is shown that this protocol not only has a high embedding efficiency but also achieves a good imperceptibility as well as a high security.

Primary Exploration of Reliability Evaluation of Computer Live Forensics Model on Physical Memory Analysis

The integrity and fidelity of digital evidence are very important in live forensics. Previous studies have focused the uncertainty of live forensics based on different memory snapshots. However,this kind of method is not effective in practice. In fact,memory images are usually acquired by using forensics tools instead of using snapshots. Therefore,the integrity and fidelity of live evidence should be evaluated during the acquisition process. In this paper,we study the problem in a novel viewpoint. Firstly,several definitions about memory acquisition measure error are introduced to describe the trusty. Then,we analyze the experimental error and propose some suggestions on how to reduce it. A novel method is also developed to calculate the system error in detail. The results of a case study on Windows 7 and VMware virtual machine show that the experimental error has good accuracy and precision,which demonstrate the efficacy of the proposed reducing methods. The system error is also evaluated,that is,it accounts for the whole error from 30% to 50%.

Numerical investigation of the South China Sea deep circulation

Based on a two-level nested model from the global ocean to the western Pacific and then to the South China Sea(SCS),the high-resolution SCS deep circulation is numerically investigated.The SCS deep circulation shows a basin-scale cyclonic structure with a strong southward western boundary current in summer(July),a northeast-southwest through-flow pattern across the deep basin without a western boundary current in winter(January),and a transitional pattern in spring and autumn.The sensitivity model experiments illustrate that the Luzon Strait deep overflow is the main factor controlling the seasonal variation in the SCS deep circulation.The SCS surface wind can significantly influence the SCS deep circulation in winter.The Luzon Strait deep overflow transport from the Pacific into the SCS ranges from 0.68×10^(6) m^(3)/s to 1.83×10^(6) m^(3)/s,reaching its maximum in summer(July,up to 1.83×10^(6) m^(3)/s),less in autumn and winter,and the minimum in spring(May,0.68×10^(6) m^(3)/s).In summer,the strong Luzon Strait deep overflow dominates the SCS deep circulation when the role of the SCS surface wind is small.In winter,the weaker Luzon Strait deep overflow and SCS surface wind jointly drive the SCS deep circulation into a northeast-southwest through-flow pattern.The potential vorticity(PV)dissipation in the SCS deep basin reaches its maximum(−0.122 m^(2)/s^(2))in May and its minimum(−0.380 m^(2)/s^(2))in July.

Shortest Link Scheduling in Wireless Networks with Oblivious Power Control

Link scheduling has always been a fundamental problem in wireless networks for its direct impacts on the performance of wireless networks such as throughput capacity,transmission delay,lifetime,etc.Existing work is mainly established under graphbased models,which are not only impractical but also incorrect due to the essentially fading characteristics of signals.In this paper,we study the shortest link scheduling problem under two more realistic models,namely the signal to interference plus noise ratio(SINR)model and the Rayleigh fading model.We propose a centralized square-based scheduling algorithm(CSSA)with oblivious power control under the SINR model and prove its correctness under both the SINR model and the Rayleigh fading model.Furthermore,we extend CSSA and propose a distributed square-based scheduling algorithm(DSSA).Note that DSSA adopts CSMA/CA so that a wireless node can compete for the wireless channel before starting its communication.We also show theoretical analysis and conduct extensive simulations to exhibit the correctness and efficiency of our algorithms.

External mass transfer from/to a single sphere in a nonlinear uniaxial extensional creeping flow

This work systematically simulates the external mass transfer from/to a spherical drop and solid particle suspended in a nonlinear uniaxial extensional creeping flow.The mass transfer problem is governed by three dimensionless parameters:the viscosity ratio(λ),the Peclet number(Pe),and the nonlinear intensity of the flow(E).The existing mass transfer theory,valid for very large Peclet numbers only,is expanded,by numerical simulations,to include a much larger range of Peclet numbers(1≤Pe≤105).The simulation results show that the dimensionless mass transfer rate,expressed as the Sherwood number(5 h),agrees well with the theoretical results at the convection-dominated regime(Pe>103).Only when E>5/4,the simulated Sh for a solid sphere in the nonlinear uniaxial extensional flow is larger than theoretical results because the theory neglects the effect of the vortex formed outside the particle on the rate of mass transfer.Empirical correlations are proposed to predict the influence of the dimensionless governing parameters(λ,Pe,E)on the Sherwood number(Sh).The maximum deviations of all empirical correlations are less than 15%when compared to the numerical simulated results.

Performance of Resampling Algorithms Based on Particle Filter in Video Target Tracking

Particle filter is a common algorithm in video target tracking.But there are still some shortcomings,for example,particle degradation phenomenon.For solving this problem,the general solution is to introduce resampling step.At present,four kinds of resampling algorithms are widely used:multinomial resampling,residual resampling,stratified resampling and systematic resampling algorithms.In this paper,the performances of these four resampling algorithms were analyzed from realization principle,uniform distribution theory and computational complexity.Finally,through a series of video target tracking experiments,the systematic resampling algorithm had the smallest calculation load,the shortest running time and the maximum number of effective particles.So,it can be concluded that in the field of video target tracking,the systematic resampling algorithm has more advantages than other three algorithms both in the running time and the number of effective particles.

Research on Linux Kernel Version Diversity for Precise Memory Analysis

The diversity of Linux versions brings challenges to Linux memory analysis,which is an established technique in security and forensic investigations.During memory forensics,kernel data structures are essential information.Existing solutions obtain this information by analyzing debugging information or by decompiling kernel functions to handle a certain range of versions.In this paper,by collecting and analyzing a number of Linux versions,we characterize the properties of different Linux kernel versions and how struct offsets change between versions.Furthermore,the Linux kernel provides over 10,000 configurable features,which leads to different kernel structure layouts for the same kernel version.To deal with this problem,we propose a method of identifying kernel struct layout based on brute-force matching.By examining the relationships between kernel structures,common features are extracted and exploited for brute-force matching.The experimental results show that the proposed technology can deduce structure member offsets accurately and efficiently.

An Approach to Analyze Physical Memory Image File of Mac OS X

Memory analysis is one of the key techniques in computer live forensics. Especially,the analysis of a Mac OS X operating system's memory image file plays an important role in identifying the running status of an apple computer. However,how to analyze the image file without using extra"mach-kernel"file is one of the unsolved difficulties. In this paper,we firstly compare several approaches for physical memory acquisition and analyze the effects of each approach on physical memory. Then,we discuss the traditional methods for the physical memory file analysis of Mac OS X. A novel physical memory image file analysis approach without using extra"mach-kernel"file is proposed base on the discussion. We verify the performance of the new approach on Mac OS X 10. 8. 2. The experimental results show that the proposed approach is simpler and more practical than previous ones.

FedIERF: Federated Incremental Extremely Random Forest for Wearable Health Monitoring

Wearable health monitoring is a crucial technical tool that offers early warning for chronic diseases due to its superior portability and low power consumption.However,most wearable health data is distributed across dfferent organizations,such as hospitals,research institutes,and companies,and can only be accessed by the owners of the data in compliance with data privacy regulations.The first challenge addressed in this paper is communicating in a privacy-preserving manner among different organizations.The second technical challenge is handling the dynamic expansion of the federation without model retraining.To address the first challenge,we propose a horizontal federated learning method called Federated Extremely Random Forest(FedERF).Its contribution-based splitting score computing mechanism significantly mitigates the impact of privacy protection constraints on model performance.Based on FedERF,we present a federated incremental learning method called Federated Incremental Extremely Random Forest(FedIERF)to address the second technical challenge.FedIERF introduces a hardness-driven weighting mechanism and an importance-based updating scheme to update the existing federated model incrementally.The experiments show that FedERF achieves comparable performance with non-federated methods,and FedIERF effectively addresses the dynamic expansion of the federation.This opens up opportunities for cooperation between different organizations in wearable health monitoring.

Energy efficiency and area spectral efficiency tradeoff for coexisting wireless body sensor networks

The coexistence of wireless body sensor networks(WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral efficiency are two key performance evaluation metrics for wireless communication networks. In this paper, the fundamental tradeoff between energy efficiency and area spectral efficiency of WBSNs is first investigated under the Poisson point process(PPP) model and Matern hard-core point process(HCPP) model using stochastic geometry. The circuit power consumption is taken into consideration in energy efficiency calculation. The tradeoff judgement coefficient is developed and is shown to serve as a promising complementary measure. In addition, this paper proposes a new nearest neighbour distance power control strategy to improve energy efficiency. We show that there exists an optimal transmit power highly dependant on the density of WBSNs and the nearest neighbour distance. Some important properties are also addressed in the analysis of coexisting WBSNs based on the IEEE 802.15.4 standard, such as the impact of intensity nodes distribution,optimal guard zone, and outage probability. Simulation results show that the proposed power control design can reduce the outage probability and enhance energy efficiency. Energy efficiency and area spectral efficiency of the HCPP model are better than those of the PPP model. In addition, the optimal density of WBSNs coexistence is obtained.

Reliable Data Storage in Heterogeneous Wireless Sensor Networks by Jointly Optimizing Routing and Storage Node Deployment

In the era of big data,sensor networks have been pervasively deployed,producing a large amount of data for various applications.However,because sensor networks are usually placed in hostile environments,managing the huge volume of data is a very challenging issue.In this study,we mainly focus on the data storage reliability problem in heterogeneous wireless sensor networks where robust storage nodes are deployed in sensor networks and data redundancy is utilized through coding techniques.To minimize data delivery and data storage costs,we design an algorithm to jointly optimize data routing and storage node deployment.The problem can be formulated as a binary nonlinear combinatorial optimization problem,and due to its NP-hardness,designing approximation algorithms is highly nontrivial.By leveraging the Markov approximation framework,we elaborately design an efficient algorithm driven by a continuous-time Markov chain to schedule the deployment of the storage node and corresponding routing strategy.We also perform extensive simulations to verify the efficacy of our algorithm.

An Improved Quantum Information Hiding Protocol Based on Entanglement Swapping of χ-type Quantum States

In 2011, Qu et al. proposed a quantum information hiding protocol based on the entanglement swapping of χ-type quantum states. Because a χ-type state can be described by the 4-particle cat states which have good symmetry,the possible output results of the entanglement swapping between a given χ-type state and all of the 16 χ-type states are divided into 8 groups instead of 16 groups of different results when the global phase is not considered. So it is difficult to read out the secret messages since each result occurs twice in each line(column) of the secret messages encoding rule for the original protocol. In fact, a 3-bit instead of a 4-bit secret message can be encoded by performing two unitary transformations on 2 particles of a χ-type quantum state in the original protocol. To overcome this defect, we propose an improved quantum information hiding protocol based on the general term formulas of the entanglement swapping among χ-type states.

A Spatial Domain Quantum Watermarking Scheme

This paper presents a spatial domain quantum watermarking scheme. For a quantum watermarking scheme,a feasible quantum circuit is a key to achieve it. This paper gives a feasible quantum circuit for the presented scheme. In order to give the quantum circuit, a new quantum multi-control rotation gate, which can be achieved with quantum basic gates, is designed. With this quantum circuit, our scheme can arbitrarily control the embedding position of watermark images on carrier images with the aid of auxiliary qubits. Besides reversely acting the given quantum circuit, the paper gives another watermark extracting algorithm based on quantum measurements. Moreover, this paper also gives a new quantum image scrambling method and its quantum circuit. Differ from other quantum watermarking schemes, all given quantum circuits can be implemented with basic quantum gates. Moreover, the scheme is a spatial domain watermarking scheme, and is not based on any transform algorithm on quantum images. Meanwhile, it can make sure the watermark be secure even though the watermark has been found. With the given quantum circuit, this paper implements simulation experiments for the presented scheme. The experimental result shows that the scheme does well in the visual quality and the embedding capacity.

Robust H_(∞)path tracking control of autonomous vehicles with delay and actuator saturation

The path tracking control problem is investigated in this paper for autonomous vehicles(AVs)with time-varying input delay and actuator saturation.Based on the Lyapunov-Krasovskii function and the characteristic of the saturation nonlinearity,a robust H_(∞)state-feedback path tracking controller is presented,and the corresponding control gain can be obtained by solving the linear matrix inequalities(LMIs).The asymptotic stability and prescribed H_(∞)performance conditions are studied for the closed-loop control system.To reduce the cost of control system,a static robust H_(∞)output-feedback controller is also proposed.In addition,the uncertainty effects of the cornering stiffness and external disturbances are included to improve the robustness of the control scheme.Simulation results are given to verify the effectiveness of the proposed theoretical results.

I-sieve: An Inline High Performance Deduplication System Used in Cloud Storage

Data deduplication is an emerging and widely employed method for current storage systems. As this technology is gradually applied in inline scenarios such as with virtual machines and cloud storage systems, this study proposes a novel deduplication architecture called I-sieve. The goal of I-sieve is to realize a high performance data sieve system based on i SCSI in the cloud storage system. We also design the corresponding index and mapping tables and present a multi-level cache using a solid state drive to reduce RAM consumption and to optimize lookup performance. A prototype of I-sieve is implemented based on the open source i SCSI target, and many experiments have been conducted driven by virtual machine images and testing tools. The evaluation results show excellent deduplication and foreground performance. More importantly, I-sieve can co-exist with the existing deduplication systems as long as they support the i SCSI protocol.