A software-defined networking approach for handover management with real-time video in WLANs

To achieve high performance and reliability in video streaming over wireless local area networks （WLANs）, one must jointly consider both optimized association to access points （APs） and handover management based on dynamic scanning of alternate APs. In this article, we propose a new architecture within the software-defined networking （SDN） framework, which allows stations to be connected to several APs simultaneously and to switch fast between them. We evaluate our system in a real-time testbed and demonstrate that our SDN-based handover mechanism significantly reduces the number and duration of video freeze events and allows for smaller playout buffers.

Dimensional Measurement of Complete-connective Network under the Condition of Particle’s Fission and Growth at a Constant Rate

We construct a complete-connective regular network based on Self-replication Space and the structural principles of cantor set and Koch curve. A new definition of dimension is proposed in the paper, and we also investigate a simplified method to calculate the dimension of two regular networks. By the study results, we can get a extension: the formation of Euclidean space may be built by the process of the Big Bang's continuously growing at a constant rate of three times.

Injections Attacks Efficient and Secure Techniques Based on Bidirectional Long Short Time Memory Model

E-commerce,online ticketing,online banking,and other web-based applications that handle sensitive data,such as passwords,payment information,and financial information,are widely used.Various web developers may have varying levels of understanding when it comes to securing an online application.Structured Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the OpenWeb Application Security Project(OWASP)for its 2017 Top Ten List Cross Site Scripting(XSS).An attacker can exploit these two flaws and launch malicious web-based actions as a result of these flaws.Many published articles focused on these attacks’binary classification.This article described a novel deep-learning approach for detecting SQL injection and XSS attacks.The datasets for SQL injection and XSS payloads are combined into a single dataset.The dataset is labeledmanually into three labels,each representing a kind of attack.This work implements some pre-processing algorithms,including Porter stemming,one-hot encoding,and the word-embedding method to convert a word’s text into a vector.Our model used bidirectional long short-term memory(BiLSTM)to extract features automatically,train,and test the payload dataset.The payloads were classified into three types by BiLSTM:XSS,SQL injection attacks,and normal.The outcomes demonstrated excellent performance in classifying payloads into XSS attacks,injection attacks,and non-malicious payloads.BiLSTM’s high performance was demonstrated by its accuracy of 99.26%.

Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

Removal of Ocular Artifacts from Electroencephalo-Graph by Improving Variational Mode Decomposition

Ocular artifacts in Electroencephalography(EEG)recordings lead to inaccurate results in signal analysis and process.Variational Mode Decomposition(VMD)is an adaptive and completely nonrecursive signal processing method.There are two parameters in VMD that have a great influence on the result of signal decomposition.Thus,this paper studies a signal decomposition by improving VMD based on squirrel search algorithm(SSA).It’s improved with abilities of global optimal guidance and opposition based learning.The original seasonal monitoring condition in SSA is modified.The feedback of whether the optimal solution is successfully updated is used to establish new seasonal monitoring conditions.Opposition-based learning is introduced to reposition the position of the population in this stage.It is applied to optimize the important parameters of VMD.GOSSA-VMD model is established to remove ocular artifacts from EEG recording.We have verified the effectiveness of our proposal in a public dataset compared with other methods.The proposed method improves the SNR of the dataset from-2.03 to 2.30.

A Study on the Evolution of Mechanism of Infectious Disease Analysis Model of Event Using Micro-Blog Platform

After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.

New Characteristics of Active Life Expectancy of the Elderly in China

Life expectancy of the elderly is a significant problem in China, and it changes not only the health care, but also the pension. This study used tracking data from the Chinese Urban and Rural Elderly Population Survey to calculate the age-specific Active Life Expectancy (ALE) of the Chinese elderly population aged 60 years and over. For analysis, this population was divided into different sub-populations according to gender, census register and region. The main conclusions of our study are as follows: 1) The quality of life for elderly males may be greater than that for elderly females;2) There were significant differences in Active Life Expectancy (ALE) and Inactive Life Expectancy (ILE) between urban and rural elderly;3) The differences in ALE between the eastern, central and western regions of China were not significant;and 4) The increased remaining life expectancy of the elderly was mainly attributed to the extended ALE in the lower age group and the expanded ILE in the higher age group. This study expands the knowledge of Chinese elderly’s life expectancy in different health status.

Structural Dimensions Analysis of Service Employees' Innovation Behavior Based on Structural Equation Model

In order to know about the essence of service employees' innovation behavior, the service employees' innovation behavior scale based on their unique characteristics is designed. Data were collected from high-star hospitalities. Through the issuance and the collection of questionnaires, the scale is verified to have good reliability and validity by SPSS software analysis. Meanwhile,the structural equation model( SEM) is suited for testing structural dimensions of service employees' innovation behavior. The results showed that service employees' innovation behavior could be decomposed into a four-dimensional structure,namely innovation orientation, ideas generation, innovation implementation and innovation practice. In addition,there are significant differences in service employees' innovation behavior about subjects' gender,position,education background and years of working.

A closed-loop Supply Chain Network Equilibrium Model with Fuzzy Demand under Production Capacity Constraints and Price Rigidities

A closed-loop supply chain network equilibrium problem is examined,which consists of mutual competitive manufacturers with production capacity constraints and retailers with fuzzy market demands,mutual competitive collectors as well as a binding price ceiling of the commodities.By utilizing the credibility measure of fuzzy event,variational inequality and Lagrange dual theory,the optimum behaviors of manufactures,retailers,collectors and consumers are described.Therefore,the supply chain network equilibrium model is established.Numerical examples were given to illustrate the impact of production capacity constraints and price ceiling on the network equilibrium pattern.The results show that the shortage of commodities in consumer market will be more serious,the wholesale price of product and purchase price of waste products rise,the profits of retailers decrease,the profits of manufacturers and collectors increase as the government gradually reduce the binding price ceiling on competitive markets,and the trend will be more obvious in the existence of production capacity constraints at same time.

Linear operators and positive semidefiniteness of symmetric tensor spaces

We study symmetric tensor spaces and cones arising from polynomial optimization and physical sciences.We prove a decomposition invariance theorem for linear operators over the symmetric tensor space,which leads to several other interesting properties in symmetric tensor spaces.We then consider the positive semidefiniteness of linear operators which deduces the convexity of the Frobenius norm function of a symmetric tensor.Furthermore,we characterize the symmetric positive semidefinite tensor(SDT)cone by employing the properties of linear operators,design some face structures of its dual cone,and analyze its relationship to many other tensor cones.In particular,we show that the cone is self-dual if and only if the polynomial is quadratic,give specific characterizations of tensors that are in the primal cone but not in the dual for higher order cases,and develop a complete relationship map among the tensor cones appeared in the literature.

PIECEWISE LINEAR NCP FUNCTION FOR QP FREE FEASIBLE METHOD

在这篇论文，明智的 NCP 功能为非线性的不平等被建议的有片的一个 QP 免费的可行方法抑制了优化问题。新 NCP 功能 arepiece 明智的线性合理的、常规伪 smooth 并且有好性质。这个方法是 KKT optimality 条件的方程重新阐述的线性系统的基于的在解决方案，由使用 thepiecewise NCP 函数。这个方法是没有假定严格的补充条件能、全球性会聚的工具，累积的孤立的海角指。而且，活跃限制的坡度没被请求线性地独立。可以被伪获得的次矩阵 -- 牛顿方法，没被请求一致地积极明确。初步的数字结果显示这个新 QP 免费的方法是相当有希望的。

Impacts of building information modeling(BIM) implementation on design and construction performance: a resource dependence theory perspective

Drawing on resource dependence theory, this paper develops and empirically tests a model for understanding how the implementation of building information modeling(BIM) in construction projects impacts the performance of different project participating organizations through improving their interorganizational collaboration capabilities. Based on two sets of survey data collected from designers and general contractors in BIMbased construction projects in China, the results from partial least squares analysis and bootstrapping mediation test provide clear evidence that BIM-enabled capabilities of information sharing and collaborative decision-making as a whole play a significant role in determining BIMenabled efficiency and effectiveness benefits for both designers and general contractors. The results further reveal that designers and general contractors benefit from project BIM implementation activities significantly nonequivalently, and that this non-equivalence closely relates to the different roles played by designers and general contractors in BIM-enabled interorganizational resource exchange processes. The findings validate the resource dependence theory perspective of BIM as a boundary spanning tool to manage interorganizational resource dependence in construction projects, and contribute todeepened understandings of how and why project participating organizations benefit differently from the implementation of interorganizational information technologies like BIM.

An improved proximal-based decomposition method for structured monotone variational inequalities

The proximal-based decomposition method was originally proposed by Chen and Teboulle （Math. Programming, 1994, 64：81-101 for solving corrvex minimization problems. This paper extends it to solving monotone variational inequalities associated with separable structures with the improvements that the restrictive assumptions on the involved parameters are much relaxed, and thus makes it practical to solve the subproblems easily. Without additional assumptions, global convergence of the new method is proved under the same mild assumptions on the problem＇s data as the original method.

Decentralized estimation of sensor systematic error and target state vector

An accurate estimation of the sensor systematic error is significant for improving the performance of target tracking system. The existing methods usually append the bias states directly to the variable states to form augmented state vectors and utilize the conventional Kalman estimator to achieve state vectors estimate. So doing is expensive in computation, and much work is devoted to decoupling variable states and systematic error. But the decentralied estimation of systematic errors and reduction of the amount of computation as well as decentralied track fusion are far from being realized. This paper addresses distributed track fusion problem in multi-sensor tracking system in the presence of sensor bias. By this method, variable states and systematic error is decoupled. Decentralized systematic error estimation and track fusion are achieved. Simulation results verify that this method can get accurate estimation of systematic error and state vector.

Optimal restructuring strategies under various dynamic factors

Corporate restructuring was identified as a new industrial force that has great impact on economic values and that therefore has become central in daily financial decision making. This article investigates the optimal restructuring strategies under different dynamic factors and their numerous impacts on firm value. The concept of quasi-leverage is introduced and valuation models are built for corporate debt and equity under imperfect market conditions. The model’s input variables include the quasi-leverage and other firm-specific parameters, the output variables include multiple corporate security values. The restruc- turing cost is formulated in the form of exponential function, which allows us to observe the sensitivity of the variation in security values. The unified model and its analytical solution developed in this research allow us to examine the continuous changes of security values by dynamically changing the coupon rates, riskless interest rate, bankruptcy cost, quasi-leverage, personal tax rate, corporate taxes rate, transaction cost, firm risk, etc., so that the solutions provide useful guidance for financing and restructuring decisions.

How do Normal Traders and Sharp Traders Make Profits in the Chinese Security Market?

In this paper,we consider the strategic interaction between the normal and sharp traders in a dynamic limit-order security market and its impact on the Chinese security market at different market volatility levels.We find that when the proportion of sharp traders is less than a threshold in an orderdriven market,the sharp traders who submit limit orders will get more returns than the normal traders.The participation of sharp traders in the market can increase the total social welfare of all the traders.In addition,we show that:(1)when the market volatility level is generally low,the short-term sharp traders benefit from larger volatility;(2)when the market volatility level is generally high,the insider/cheating sharp traders with high-frequent trading rather than the short-term sharp traders benefit from extreme high volatility;(3)when the market volatility level is moderate,the sharp traders can increase market liquidity.

Optimal Inspection and Replacement Strategy for Systems Subject to Two Types of Failures with Adjustable Inspection Intervals

The inspection activities are often carried out to detect possible indication of failures in plant systems.This paper considers a single unit system subject to two types of failures, where one failure mode is the traditional0-1 logic failure and the other failure mode is described by a two-stage failure process. Adjustable inspections are used to detect the defective stage of the latter. We assume that the inspection duration gets shorter and shorter with a constant ratio. At the same time, preventive replacement is used to avoid the possible failure due to the former failure mode. The renewal process of this system is analyzed and the expected long-run cost per unit time(ELRCUT) is derived. The optimal inspection period and the preventive replacement interval to minimize ELRCUT are studied. At last, a numerical example is presented to illustrate the proposed model.

Optimization and Operations Research in Mitigation of a Pandemic

The pandemic of COVID-19 initiated in 2019 and spread all over the world in 2020 has caused significant damages to the human society,making troubles to all aspects of our daily life.Facing the serious outbreak of the virus,we consider possible solutions from the perspectives of both governments and enterprises.Particularly,this paper discusses several applications of supply chain management,public resource allocation,and pandemic prevention using optimization and machine learning methods.Some useful insights in mitigating the pandemic and economy reopening are provided at the end of this paper.These insights might help governments to reduce the severity of the current pandemic and prevent the next round of outbreak.They may also improve companies'reactions to the increasing uncertainties appearing in the business operations.Although the coronavirus imposes challenges to the entire society at the moment,we are confident to develop new techniques to prevent and eradicate the disease.

Intelligent data analytics is here to change engineering management

A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it's needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.