Research on the Internal Talent Training Path and Performance Evaluation Mechanism of New R&D Institutions in Zhejiang Province

New research and development(R&D)institutions are an important part of the national innovation system,playing an important role in promoting the transformation of scientific and technological achievements.In recent years,new R&D institutions have gradually become the driving force of innovation-driven development in China.Taking new R&D institutions in Zhejiang Province as the research object,this paper studies the internal talent training path and performance evaluation mechanism of new R&D institutions in Zhejiang Province by using the literature research method,comparison method,case verification method,and other methods.The investigation results show that there are problems such as lack of material and spiritual support and neglect of the absorption of local talents in the internal talent training,and there are problems such as unclear standards,insufficient data,and opaque processes in the performance evaluation mechanism,which greatly affect the establishment and improvement of the performance evaluation mechanism.Given the above problems,this paper puts forward a forward-looking,oriented,flexible,and compatible talent training path and performance evaluation mechanism,hoping to optimize the effective internal talent training path of new R&D institutions,improve the evaluation performance,and promote healthy development of new R&D institutions in Zhejiang Province.

Carbon materials toward efficient potassium storage:Rational design,performance evaluation and potassium storage mechanism

Potassium-ion batteries(PIBs)are potential“Beyond Li-ion Batteries”candidates for their resource advantage and low standard electrode potential.To date,the research on PIBs is in its early stages,the most urgent task is to develop high-performance electrode materials and reveal their potassium storage mechanism.For PIBs anode materials,carbon with tunable microstructure,excellent electrochemical activity,nontoxicity and low price is considered as one of the most promising anode materials for commercialization.Although some breakthrough works have emerged,the overall electrochemical performance of the reported carbon anode is still far away from practical application.Herein,we carry out a comprehensive overview of PIBs carbon anode in terms of three aspects of rational design of structure,performance evaluation criteria and characterization of potassium storage mechanism.First,the regulation mechanism of key structural features of carbon anode on its potassium storage performance and the representative structural regulation strategies are introduced.Then,in view of the undefined performance evaluation criteria of PIBs carbon anode,a reference principle for evaluating the potassium storage performance of carbon anode is proposed.Finally,the advanced characterization techniques for the potassium storage mechanism of carbon anode are summarize.This review aims to provide guidance for the development of practical PIBs anode.

Performance evaluation of CLM5.0 in simulating liquid soil water in high mountainous area,Northwest China

The model performance in simulating soil water content(SWC) is crucial for successfully modeling earth’s system,especially in high mountainous areas.In this study,the performance of Community Land Model 5.0(CLM5.0) in simulating liquid SWC was evaluated against observations from nine in-situ sites in the upper reach of the Heihe River Watershed(HRW),Northwest China.The CLM5.0 shows reliable performance in the study area with correlation coefficients(R) ranging between 0.79–0.93,root mean standard errors(RMSE)ranging between 0.044–0.097 m^(3)/m^(3),and the mean bias(BIAS) ranging between-0.084–0.061 m^(3)/m^(3).The slightly worse performance of CLM5.0 than CLM4.5 on alpine meadow and grassland is mainly caused by the revised canopy interception parameterization.The CLM5.0 overestimates interception and underestimates evapotranspiration(ET) on both alpine meadow and grassland during the growth period.The systematical overestimations at all the grassland sites indicate that the underestimation of ET is much larger than the overestimation of interception on grassland during growth period,while the errors of simulated interception and ET are partially canceled out on alpine meadow.Moreover,the underestimation of ET is more responsible for the overestimation of SWC than the overestimation of interception in the high mountainous area.It is necessary to estimate reasonable empirical parameter α(proportion of leaf water collection area) in interception parameterization scheme and further improve the dry surface layerbased soil evaporation resistance parameterization introduced in CLM5.0 in future researches.The performance of CLM5.0 is better under completely frozen stage than thawing stage and freezing stage,because of low variations of liquid SWC caused by extremely low hydraulic conductivity of soils.The underestimation of liquid SWC under frozen state is caused by underestimation of soil temperature,which leads to more ice mass and less liquid water in total water content.

Recent Advances in the Rapid Detection and Performance Evaluation Methods of Detergent Additives for Gasoline

Although detergent additives for gasoline have been widely commercialized,their formulas are often kept confidential and there is still no standardized method for quickly detecting the main active ingredients and evaluating their effectiveness,which makes their regulation difficult.An overview of the current state of the development and application of detergent additives for gasoline in China and other regions,as well as a review of the rapid detection and performance evaluation methods available for analyzing detergent additives are given herein.The review focuses on the convenience,cost,efficiency,and feasibility of on-site detection and the evaluation of various methods,and also looks into future research directions,such as detecting and evaluating detergent additives in ethanol gasoline and with advanced engine technologies.

ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

A general evaluation system for optimal selection performance of radar clutter model

The optimal selection of radar clutter model is the premise of target detection,tracking,recognition,and cognitive waveform design in clutter background.Clutter characterization models are usually derived by mathematical simplification or empirical data fitting.However,the lack of standard model labels is a challenge in the optimal selection process.To solve this problem,a general three-level evaluation system for the model selection performance is proposed,including model selection accuracy index based on simulation data,fit goodness indexs based on the optimally selected model,and evaluation index based on the supporting performance to its third-party.The three-level evaluation system can more comprehensively and accurately describe the selection performance of the radar clutter model in different ways,and can be popularized and applied to the evaluation of other similar characterization model selection.

Flow control performance evaluation of a tri-electrode sliding discharge plasma actuator

Tri-electrode sliding discharge(TED)plasma actuators are formed by adding a direct current(DC)exposed electrode to conventional dielectric barrier discharge(DBD)plasma actuators.There are three TED modes depending on the polarity and amplitude of the DC supply:DBD discharge,extended discharge and sliding discharge.This paper evaluates the electrical,aerodynamic and mechanical characteristics of a TED plasma actuator based on energy analysis,particle image velocimetry experiments and calculations using the Navier-Stokes equation.The flow control performances of different discharge modes are quantitatively analyzed based on characteristic parameters.The results show that flow control performance in both extended discharge and sliding discharge is more significant than that of DBD,mainly because of the significantly higher(up to 141%)body force of TED compared with DBD.However,conductivity loss is the primary power loss caused by the DC polarity for TED discharge.Therefore,power consumption can be reduced by optimizing the dielectric material and thickness,thus improving the flow control performance of plasma actuators.

Performance evaluation of ecological compensation policy for cultivated land in China

The paper evaluates the changes in the ecological environment of cultivated land in the major crop-producing areas major crop-producing areas in the past 20 years by constructing an ecological pollution index;and quantitatively analyzes the effects of the existing policies and their main influencing factors by applying the PSM-DID method based on the frequency of policy enactment.The results are as follows:first,the existing ecological compensation policies for cultivated land are effective but not significant in improving the ecological environment in the major crop-producing areas.The economic development level and grain cultivation area of the major crop-producing areas are significantly and positively correlated with the improvement of the arable land ecological environment,while the level of agricultural infrastructure construction is significantly and negatively correlated with the improvement of the arable land ecological environment.Second,the reason for the ineffectiveness of the current arable ecological land compensation policy in protecting the arable land ecological environment in the main grain-producing regions is that the existing arable ecological land compensation policy in China has its own institutional defects and needs to be further improved.At the same time,the level of environmental pollution of cultivated land in the main grain-producing regions is positively correlated with the level of income from cultivated land and cultivated area.

Analysis of Highway Roadbed Performance Evaluation Technology

With the continuous development of China,the requirements for road construction are also increasing.Among them,strengthening the performance of roadbed test can effectively improve road construction.Besides,it is also crucial to perform suitable tests in a timely manner.Therefore,highway inspection technology should be improved for the continuous development of highway construction,which will be explained in this paper,in hopes of improving the construction of highway in China.

Modeling and performance evaluation of QoS-aware job scheduling of computational grids

To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.

Performance Evaluation of Public Bus Transportation by Using DEA Models and Shannon’s Entropy:An Example From a Company in a Large City of China

The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.

Dynamical analysis and performance evaluation of a biped robot under multi-source random disturbances

During bipedal walking,it is critical to detect and adjust the robot postures by feedback control to maintain its normal state amidst multi-source random disturbances arising from some unavoidable uncertain factors.The radical basis function（RBF）neural network model of a five-link biped robot is established,and two certain disturbances and a randomly uncertain disturbance are then mixed with the optimal torques in the network model to study the performance of the biped robot by several evaluation indices and a specific Poincar′e map.In contrast with the simulations,the response varies as desired under optimal inputting while the output is fluctuating in the situation of disturbance driving.Simulation results from noise inputting also show that the dynamics of the robot is less sensitive to the disturbance of knee joint input of the swing leg than those of the other three joints,the response errors of the biped will be increasing with higher disturbance levels,and especially there are larger output fluctuations in the knee and hip joints of the swing leg.

TCP performance evaluation over AODV and DSDV in RW and SN mobility models

This paper presents evaluation and comparison of the TCP performance in different mobile scenarios generated by Random Waypoint (RW) and Social Network (SN) mobility models. To our knowledge, TCP performance in SN mobility is discussed for the first time. The impact of AODV and DSDV routing protocols on the TCP goodput, delay and drop rate per- formance is also discussed. Extensive simulation results and analysis showed that TCP has better performance over AODV than over DSDV and has more stable performance in SN mobility than in RW mobility. We suggest using more mobility models, in particular, such as SN, in the evaluations of the transport layer or routing layer protocols because the mobility patterns have impacts on the protocol performance.

Performance evaluation methods and instrumentation for mine ventilation fans

Ventilation fans are one of the most important pieces of equipment in coal mines. Their performance plays an important role in the safety of staff and production. Given the actual requirements of coal mine production,we instituted a research project on the measurement methods of key performance parameters such as wind pressure,amount of ventilation and power. At the end a virtual instrument for mine ventilation fans performance evaluation was developed using a USB interface. The practical performance and analytical results of our experiments show that it is feasible,reliable and effective to use the proposed instrumentation for mine ventilation performance evaluation.

Total plant performance evaluation based on big data: Visualization analysis of TE process

The performance evaluation of the process industry, which has been a popular topic nowadays, can not only find the weakness and verify the resilience and reliability of the process, but also provide some suggestions to improve the process benefits and efficiency. Nevertheless, the performance assessment principally concentrates upon some parts of the entire system at present, for example the controller assessment. Although some researches focus on the whole process, they aim at discovering the relationships between profit, society, policies and so forth, instead of relations between overall performance and some manipulated variables, that is, the total plant performance. According to the big data of different performance statuses, this paper proposes a hierarchical framework to select some structured logic rules from monitored variables to estimate the current state of the process. The variables related to safety and profits are regarded as key factors to performance evaluation. To better monitor the process state and observe the performance variation trend of the process, a classificationvisualization method based on kernel principal component analysis(KPCA) and self-organizing map(SOM) is established. The dimensions of big data produced by the process are first reduced by KPCA and then the processed data will be mapped into a two-dimensional grid chart by SOM to evaluate the performance status. The monitoring method is applied to the Tennessee Eastman process. Monitoring results indicate that off-line and on-line performance status can be well detected in a two-dimensional diagram.

Performance Evaluation of IEEE 1394b Serial Bus with Deterministic and Stochastic Petri Nets

IEEE 1394b is a high-speed data bus that is widely used in local area networks and consumer electronics. To best utilize this data bus, we need to fully understand its per- formance. To evaluate its performance for both isochronous and asynchronous data transfers, we model the IEEE 1394b bus using Deterministic and Stochastic Pelri Nets （DSPNs）, and conduct simulations using TimeNET 4.0. Using the DSPNs model, we simulate both the average waiting times of isochronous and asynchronous packets. From the simulation results, we determine the factors that influence performance, such as throughput, size of packets, arrival rate of packets, number of isochronous channels, and bus configuration.

PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis （DEA） and analytical hierarchical process （AHP）, a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering （BPR） with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

Cloud service performance evaluation： status, challenges, and opportunities - a survey from the system modeling perspective

With rapid advancement of Cloud computing and networking technologies, a wide spectrum of Cloud services have been developed by various providers and utilized by numerous organizations as indispensable ingredients of their information systems. Cloud service performance has a significant impact on performance of the future information infrastructure. Thorough evaluation on Cloud service performance is crucial and beneficial to both service providers and consumers; thus forming an active research area. Some key technologies for Cloud computing, such as virtualization and the Service-Oriented Architecture （SOA）, bring in special challenges to service performance evaluation. A tremendous amount of effort has been put by the research community to address these challenges and exciting progress has been made. Among the work on Cloud performance analysis, evaluation approaches developed with a system modeling perspective play an important role. However, related works have been reported in different sections of the literature; thus lacking a big picture that shows the latest status of this area. The objectives of this article is to present a survey that reflects the state of the art of Cloud service performance evaluation from the system modeling perspective. This articles also examines open issues and challenges to the surveyed evaluation approaches and identifies possible opportunities for future research in this important field.

Seismic performance evaluation of steel frame-steel plate shear walls system based on the capacity spectrum method

This paper presents some methods that the standard acceleration design response spectra derived from the present China code for seismic design of buildings are transformed into the seismic demand spectra, and that the base shear force-roof displacement curve of structure is converted to the capacity spectrum of an equivalent single-degree-of-freedom （SDOF） system. The capacity spectrum method （CSM） is programmed by means of MATLABT.0 computer language. A dual lateral force resisting system of 10-story steel frame-steel plate shear walls （SPSW） is designed according to the corresponding China design codes. The base shear force-roof displacement curve of structure subjected to the monotonic increasing lateral inverse triangular load is obtained by applying the equivalent strip model to stimulate SPSW and by using the finite element analysis software SAP2000 to make Pushover analysis. The seismic performance of this dual system subjected to three different conditions, i.e. the 8-intensity frequently occurred earthquake, fortification earthquake and seldom occurred earthquake, is evaluated by CSM program. The excessive safety of steel frame-SPSW system designed according to the present China design codes is pointed out and a new design method is suggested.

Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content

Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification.