Traffic flow of connected and automated vehicles at lane drop on two-lane highway: An optimization-based control algorithm versus a heuristic rules-based algorithm

This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.

Off-farm employment and poverty alleviation in rural China

Two phenomena in the history of China's economic growth during the last four decades are the increase in the share of offfarm employment and the progress in poverty alleviation in rural China.Although both of them have been well documented in the literature,less is known about the linkage between the two.To better understand the role that off-farm employment has played in poverty alleviation in rural China is critically important not only for China but also for those countries that are trying to reduce poverty.Here,we examine the impact of off-farm employment on poverty alleviation in rural China.Using the data from two nationally representative household panel surveys(China National Rural Survey and China Rural Development Survey),this paper provides supporting evidence that off-farm employment contributes to poverty alleviation in rural China.Specifically,if household participation in off-farm employment increases by 10 percentage points,the likelihood for a nonpoor household to fall into poverty will decrease by 0.88 percentage point whereas the likelihood for a poor household to climb out of poverty will increase by 3.5 percentage points.In a word,off-employment can not only prevent rural residents to fall into poverty but also help those already in poverty climb out of it.

Prediction of efficient outputs based on GM(1,N) model and weak DEA efficiency

This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.

Baidu index and predictability of Chinese stock returns

A number of studies have investigated the predictability of Chinese stock returns with economic variables.Given the newly emerged dataset from the Internet,this paper investigates whether the Baidu Index can be employed to predict Chinese stock returns.The empirical results show that 1)the Search Frequency of Baidu Index(SFBI)can predict next day’s price changes;2)the stock prices go up when individual investors pay less attention to the stocks and go down when individual investors pay more attention to the stocks;3)the trading strategy constructed by shorting on the most SFBI and longing on the least SFBI outperforms the corresponding market index returns without consideration of the transaction costs.These results complement the existing literature on the predictability of Chinese stock returns and have potential implications for asset pricing and risk management.

Introduction to the special issue on Impact of COVID‑19 and cryptocurrencies on the global financial market

In the last year,the global outbreak of COVID-19 and the sharply rising price of Bitcoin greatly influence the financial market.Such influences include but are not limited to the trading strategies between different cryptocurrencies,portfolio diversification,foreign exchange markets,and macroeconomic policy.In this 26th issue of Financial Innovation(FIN),Volume 7,No.2(2021),22 researchers from 7 countries have used both traditional statistical methods and the newly developed machine learning techniques to analyze how COVID-19 affects the global financial market and how cryptocurrencies affect portfolio diversification.The research results could be beneficial to governments in making macroeconomic policies and financial investors for making better investment decisions.

Research on Clustering Analysis and Its Application in Customer Data Mining of Enterprise

The paper study improved K-means algorithm and establish indicators to classify customers according to RFM model. Experimental results show that, the new algorithm has good convergence and stability, it has better than single use of FKP algorithms for clustering. Finally the paper study the application of clustering in customer segmentation of mobile communication enterprise. It discusses the basic theory, customer segmentation methods and steps, the customer segmentation model based on consumption behavior psychology, and the segmentation model is successfully applied to the process of marketing decision support.

Empirical study of the dilemma regarding preliminary proof of causality and methods used by victims in China's environmental health litigation

Environmental health incidents have occurred frequently in recent years;in China,however,litigation has not been effective in protecting the rights and interests of victims due to their heavy burden of proof.In order to mitigate the burden of proof for victims,the environmental judicature in China introduced the rule of inversion of burden of proof;this means that the victim only assumes the preliminary burden of proof,but in practice it has not been sufficient.Victims in environmental health litigation still face many difficulties in proving causality.Based on the statistical analysis of judicial big data,this paper demonstrates three dilemmas faced by victims.First,the preliminary burden of proof of causality has a high standard.Second,the victim's ability to produce evidence is low.Third,the casual relationship between pollution behaviors and health damage is difficult to identify.When examining the possible legal instruments,there are three aspects to the causes of these dilemmas:theory,judicial practice,and society.The theoretical aspect manifests as the differences between the rule of inversion of burden of proof and the presumption of causality;the practical aspect manifests as the lack of an identification system for personal injury;and the social aspect manifests as the victim's lack of economic,scientific,technological,and information resources,as well as the absence of assistance from government sectors and social organizations.Combining Chinese law with judicial practice,this paper proposes a solution to the dilemma of victims needing to prove causality in environmental health litigation.On the basis of clarifying the theoretical differences between the inversion of burden of proof and the presumption of causality,China should adhere to the rule of inversion of burden of proof,establish an identification system for personal injuries caused by environmental pollution,and use methods such as epidemiological causality,indirect counterevidence,and prima facie bewies.Furthermore,the full functions of the government and social organizations must be brought into play.This will not only help victims demonstrate causality,it can also help victims achieve equitable relief.

Present Situation,Problems and Countermeasures of Targeted Poverty Alleviation in Shaxi Township of Lichuan City

Poverty is a major factor restricting the economic and social development of all countries in the world.Eliminating poverty and improving people's livelihood have always been the long-cherished goals of mankind.This paper elaborated the targeted poverty alleviation work in Shaxi Township of Lichuan City mainly from three aspects:targeted identification,targeted assistance,and targeted exit.Besides,it analyzed the problems existing in the practice of targeted poverty alleviation in Shaxi Township,and put forward corresponding countermeasures and recommendations.

Research Hotspot and Frontier Analysis of Business School International Accreditation

International accreditation is the only way for the internationalization of colleges and universities.This article takes 380 articles in the field of business schools international accreditation in the Web of Science database as the research object,and uses the method of scientometrics and VOS viewer knowledge map analysis software to perform co-occurrence analysis on keywords,and finally reveals the research hotspot and development trend of business school international accreditation.

The impact of supply chain resilience on customer satisfaction and financial performance:A combination of contingency and configuration approaches

Supply chain resilience(SCR)refers to a supply chain's(SC's)ability to recover from disruptions timely and effectively.This study uses a combination of contingency and configuration approaches to examine the direct and contingent relationships between SCR dimensions(i.e.,internal,supplier,and customer resilience)and performance.It analyzes survey data collected from 206 Chinese manufacturers.The results show that the three SCR dimensions are positively related to customer satisfaction,whereas customer resilience has no direct contribution to financial performance.Internal resilience moderates the relationship between supplier resilience and performance(negative for customer satisfaction and positive for financial performance).A taxonomy for SCR was developed based on internal,supplier,and customer resilience,providing a holistic perspective for examining the performance discrepancies among four different SCR patterns:high externalleaning,high uniform,medium uniform,and low uniform.These findings offer insights for managers in building SCR from the crisis-management process.

The effect of high-involvement human resource management practices on supply chain resilience and operational performance

Supply chain(SC)resilience is an increasingly important topic for practitioners and academics because it is a competitive weapon for firms to cope with sC disruptive risks.This study examines the impact of high-involvement human resource management practices on SC resilience from the ability-motivation-opportunity perspective.It also examines the relationship between the dimensions of sC resilience and operational performance.Based on data collected from 206 Chinese manufacturers,the proposed hypotheses were tested using structural equation modeling.The results indicated that employee participation played the most powerful role in improving supplier,customer,and internal resilience.Moreover,employee skills only facilitate internal and customer resilience but have no significant impact on supplier resilience.By contrast,employee incentives do not influence the dimension of sC resilience.It was also found that both internal and customer resilience have positive effects on operational performance,while supplier resilience has no significant effect.The findings contribute to literature and practice.

Analysis of CO_2 utilization into synthesis gas based on solar thermochemical CH_4-reforming

In this study, the solar thermochemical reactor performance for CO_2 utilization into synthesis gas(H_2+ CO) based on CH_4 reforming process was investigated in the context of carbon capture and utilization(CCU) technologies. The P1 radiation heat transfer model is adopted to establish the heat and mass transfer model coupled with thermochemical reaction kinetics. The reactor thermal behavior with direct heat transfer between gaseous reactant and products evolution and the effects of different structural parameters were evaluated. It was found that the reactor has the potential to utilize by ～60% of CO_2 captured with 40% of CH_4 co-fed into syngas(72.9% of H_2 and 27.1% of CO) at 741.31 k W/mof incident radiation heat flux. However, the solar irradiance heat flux and temperature distribution were found to significantly affect the reactant species conversion efficiency and syngas production. The chemical reaction is mainly driven by the thermal energy and higher species conversion into syngas was observed when the temperature distribution at the inner cavity of the reactor was more uniform. Designed a solar thermochemical reactor able to volumetric store concentrated irradiance could highly improve CCU technologies for producing energy-rich chemicals. Besides, the mixture gas inlet velocity, operating pressure and CO_2/CH_4 feeding ratio were crucial to determining the efficiency of CO_2 utilization to solar fuels. Catalytic CO_2-reforming of CH_4 to chemical energy is a promising strategy for an efficient utilization of CO_2 as a renewable carbon source.

Nonparametric Control Scheme for Monitoring Phase Ⅱ Nonlinear Profiles with Varied Argument Values

Profile monitoring is used to check the stability of the quality of a product over time when the product quality is best represented by a function at each time point.However,most previous monitoring approaches have not considered that the argument values may vary from profile to profile,which is common in practice.A novel nonparametric control scheme based on profile error is proposed for monitoring nonlinear profiles with varied argument values.The proposed scheme uses the metrics of profile error as the statistics to construct the control charts.More details about the design of this nonparametric scheme are also discussed.The monitoring performance of the combined control scheme is compared with that of alternative nonparametric methods via simulation.Simulation studies show that the combined scheme is effective in detecting parameter error and is sensitive to small shifts in the process.In addition,due to the properties of the charting statistics,the out-of-control signal can provide diagnostic information for the users.Finally,the implementation steps of the proposed monitoring scheme are given and applied for monitoring the blade manufacturing process.With the application in blade manufacturing of aircraft engines,the proposed nonparametric control scheme is effective,interpretable,and easy to apply.

Double weight determination method for experts of complex multi-attribute large-group decision-making in interval-valued intuitionistic fuzzy environment

The systematic clustering analysis based weight determination methods are suitable for the experts of complex multi-attribute large-group decision-making (CMALGDM) in interval-valued intuitionistic fuzzy environment. However, these methods mainly have two shortcomings: they do not consider the consistency of the experts in each aggregation; the aggregation weights are often determined simply by the 'majority principle', and neglect the quantity of information provided by the holistic aggregation, leading to decision biases. Hence, a double weight determination method for experts is proposed to solve these problems. As for the first shortcoming, a mathematical programming model is used to solve for the optimal expert weights within each aggregation, ensuring consistency in the overall preferences of the aggregations. As for the second shortcoming, we propose a modification of the aggregation weights based on the information entropy, which fully considers both the number of experts and the amount of information provided by the holistic aggregation. With the proposed method, the final expert weights are determined more rigorously and objectively. The feasibility of the proposed method is investigated through an illustrative example. © 1990-2011 Beijing Institute of Aerospace Information.

Game-theoretic approach to power and admission control in hierarchical wireless sensor networks

Power efficiency and link reliability are of great impor- tance in hierarchical wireless sensor networks （HWSNs）, espe- cially at the key level, which consists of sensor nodes located only one hop away from the sink node called OHS. The power and admission control problem in HWSNs is comsidered to improve its power efficiency and link reliability. This problem is modeled as a non-cooperative game in which the active OHSs are con- sidered as players. By applying a double-pricing scheme in the definition of OHSs＇ utility function, a Nash Equilibrium solution with network properties is derived. Besides, a distributed algorithm is also proposed to show the dynamic processes to achieve Nash Equilibrium. Finally, the simulation results demonstrate the effec- tiveness of the proposed algorithm.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

PRODUCTION INVENTORY SYSTEM WITH RANDOM SUPPLY INTERRUPTIONS STATUE AND RANDOM LEAD TIMES

This article analyzes a continuous-review inventory system with random supply interruptions and random lead time which may be interrupted by a random number of supplier’s OFF periods. The inventory with constant demand rate is managed by a （r; q1, q2, · · · , qm） policy and supplies from an unreliable sole supplier. By renewal theory and matrix Geometric method, the long-run average cost function is obtained and some important properties of the function are proved. Furthermore, performance of the inventory is derived.

Preventing crash in stock market:The role of economic policy uncertainty during COVID‑19

This paper investigates the impact of economic policy uncertainty(EPU)on the crash risk of US stock market during the COVID-19 pandemic.To this end,we use the GARCHS(GARCH with skewness)model to estimate daily skewness as a proxy for the stock market crash risk.The empirical results show the significantly negative correlation between EPU and stock market crash risk,indicating the aggravation of EPU increase the crash risk.Moreover,the negative correlation gets stronger after the global COVID-19 outbreak,which shows the crash risk of the US stock market will be more affected by EPU during the epidemic.

Industrial Engineering Analysis of Chinese Manufacturing Industry in Transition Period Based on Grey Predictions

In order to explore the characteristics and development strategies of Chinese manufacturing production system, the grey forecasting model GM( 1,1) and the grey verhulst dynamic model were built firstly. The prediction results show that Chinese manufacturing productivity would reach $ 32 806 per person in 2018,which indicates rapid development and lays the foundation for China to become the world's manufacturing power since the reform and opening up. However, it is predicted that Chinese manufacturing productivity would peak in 2018 based on the grey verhulst dynamic model,which reveals the resource configuration mode of Chinese manufacturing system could not prop up its increasing manufacturing capability. Furthermore the main reasons of this phenomenon were explored,which could be summarized as the lack of accumulation,integration of industrial engineering( IE)and information technology( IT), promoting mechanism of IE application as well as integration model of management innovation and technology innovation,etc. Finally,a series of strategies based on IE theory to solve these problems were given. This study provides an effective way to deal with the challenges and opportunities facing the Chinese manufacturing industry,meanwhile,it may contribute to the theoretical system of IE.

INVARIANT REPRESENTATION FOR STOCHASTIC DIFFERENTIAL OPERATOR BY BSDES WITH UNIFORMLY CONTINUOUS COEFFICIENTS AND ITS APPLICATIONS

In this paper, we prove that a kind of second order stochastic differential op- erator can be represented by the limit of solutions of BSDEs with uniformly continuous coefficients. This result is a generalization of the representation for the uniformly continuous generator. With the help of this representation, we obtain the corresponding converse comparison theorem for the BSDEs with uniformly continuous coefficients, and get some equivalent relationships between the properties of the generator g and the associated solutions of BSDEs. Moreover, we give a new proof about g-convexity.