Information Conductivity:Universal Performance Measure for Semantic Communications

As a novel paradigm,semantic communication provides an effective solution for breaking through the future development dilemma of classical communication systems.However,it remains an unsolved problem of how to measure the information transmission capability for a given semantic communication method and subsequently compare it with the classical communication method.In this paper,we first present a review of the semantic communication system,including its system model and the two typical coding and transmission methods for its implementations.To address the unsolved issue of the information transmission capability measure for semantic communication methods,we propose a new universal performance measure called Information Conductivity.We provide the definition and the physical significance to state its effectiveness in representing the information transmission capabilities of the semantic communication systems and present elaborations including its measure methods,degrees of freedom,and progressive analysis.Experimental results in image transmission scenarios validate its practical applicability.

Comparative Performance Measurement of the Pareto Optimal Combination and Multi-Objective Combination Models for Controller Placement in Software-Defined Networks

The evolution of the current network has challenges of programmability, maintainability and manageability, due to network ossification. This challenge led to the concept of software-defined networking (SDN), to decouple the control system from the infrastructure plane caused by ossification. The innovation created a problem with controller placement. That is how to effectively place controllers within a network topology to manage the network of data plane devices from the control plane. The study was designed to empirically evaluate and compare the functionalities of two controller placement algorithms: the POCO and MOCO. The methodology adopted in the study is the explorative and comparative investigation techniques. The study evaluated the performances of the Pareto optimal combination (POCO) and multi-objective combination (MOCO) algorithms in relation to calibrated positions of the controller within a software-defined network. The network environment and measurement metrics were held constant for both the POCO and MOCO models during the evaluation. The strengths and weaknesses of the POCO and MOCO models were justified. The results showed that the latencies of the two algorithms in relation to the GoodNet network are 3100 ms and 2500 ms for POCO and MOCO respectively. In Switch to Controller Average Case latency, the performance gives 2598 ms and 2769 ms for POCO and MOCO respectively. In Worst Case Switch to Controller latency, the performance shows 2776 ms and 2987 ms for POCO and MOCO respectively. The latencies of the two algorithms evaluated in relation to the Savvis network, compared as follows: 2912 ms and 2784 ms for POCO and MOCO respectively in Switch to Controller Average Case latency, 3129 ms and 3017 ms for POCO and MOCO respectively in Worst Case Switch to Controller latency, 2789 ms and 2693 ms for POCO and MOCO respectively in Average Case Controller to Controller latency, and 2873 ms and 2756 ms for POCO and MOCO in Worst Case Switch to Controller latency respectively. The latencies of the two algorithms evaluated in relation to the AARNet, network compared as follows: 2473 ms and 2129 ms for POCO and MOCO respectively, in Switch to Controller Average Case latency, 2198 ms and 2268 ms for POCO and MOCO respectively, in Worst Case Switch to Controller latency, 2598 ms and 2471 ms for POCO and MOCO respectively, in Average Case Controller to Controller latency, 2689 ms and 2814 ms for POCO and MOCO respectively Worst Case Controller to Controller latency. The Average Case and Worst-Case latencies for Switch to Controller and Controller to Controller are minimal, and favourable to the POCO model as against the MOCO model when evaluated in the Goodnet, Savvis, and the Aanet networks. This simply indicates that the POCO model has a speed advantage as against the MOCO model, which appears to be more resilient than the POCO model.

Research and Analysis on the Application of Strategic Performance Management in Enterprises

In today’s competitive business environment,strategic performance management(SPM)is crucial for continuous growth and innovation.Therefore,it is important to realize the advantages of SPM in enterprise applications.This paper analyzes the theoretical basis,implementation framework,and application effects of SPM in enterprises by examining actual cases from different industries.It reveals the core elements of an effective performance management system,including clear goal setting,reasonable performance indicators,and periodic performance evaluations.Additionally,the paper examines the impact of China’s specific economic policy environment on the implementation of SPM and proposes strategies to optimize performance management practices,ultimately promoting the achievement of strategic goals.This paper provides specific and personalized practical guidance for enterprises.

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.

PerfMon: Measuring Application-Level Performance in a Large-Scale Campus Wireless Network

WiFi has become one of the most popular ways to access the Internet.However,in large-scale campus wireless networks,it is challenging for network administrators to provide optimized access quality without knowledge on fine-grained traffic characteristics and real network performance.In this paper,we implement PerfMon,a network performance measurement and diagnosis system,which integrates collected multi-source datasets and analysis methods.Based on PerfMon,we first conduct a comprehensive measurement on application-level traffic patterns and behaviors from multiple dimensions in the wireless network of T university(TWLAN),which is one of the largest campus wireless networks.Then we systematically study the application-level network performance.We observe that the application-level traffic behaviors and performance vary greatly across different locations and device types.The performance is far from satisfactory in some cases.To diagnose these problems,we distinguish locations and device types,and further locate the most crucial factors that affect the performance.The results of case studies show that the influential factors can effectively characterize performance changes and explain for performance degradation.

Traffic Incident Management Performance Measures: Ranking Agencies on Roadway Clearance Time

This study develops a procedure to rank agencies based on their incident responses using roadway clearance times for crashes. This analysis is not intended to grade agencies but to assist in identifying agencies requiring more training or resources for incident management. Previous NCHRP reports discussed usage of different factors including incident severity, roadway characteristics, number of lanes involved and time of incident separately for estimating the performance. However, it does not tell us how to incorporate all the factors at the same time. Thus, this study aims to account for multiple factors to ensure fair comparisons. This study used 149,174 crashes from Iowa that occurred from 2018 to 2021. A Tobit regression model was used to find the effect of different variables on roadway clearance time. Variables that cannot be controlled directly by agencies such as crash severity, roadway type, weather conditions, lighting conditions, etc., were included in the analysis as it helps to reduce bias in the ranking procedure. Then clearance time of each crash is normalized into a base condition using the regression coefficients. The normalization makes the process more efficient as the effect of uncontrollable factors has already been mitigated. Finally, the agencies were ranked by their average normalized roadway clearance time. This ranking process allows agencies to track their performance of previous crashes, can be used in identifying low performing agencies that could use additional resources and training, and can be used to identify high performing agencies to recognize for their efforts and performance.

Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

A Nationwide Evaluation of the State of Practice of Performance Measurements for Intelligent Transportation Systems

State departments of transportation’s (DOTs) decisions to invest resources to expand or implement intelligent transportation systems (ITS) programs or even retire existing infrastructure need to be based on performance evaluations. Nonetheless, an apparent gap exists between the need for ITS performance measurements and the actual implementation. The evidence available points to challenges in the ITS performance measurement processes. This paper evaluated the state of practice of performance measurement for ITS across the US and provided insights. A comprehensive literature review assessed the use of performance measures by DOTs for monitoring implemented ITS programs. Based on the gaps identified through the literature review, a nationwide qualitative survey was used to gather insights from key stakeholders on the subject matter and presented in this paper. From the data gathered, performance measurement of ITS is fairly integrated into ITS programs by DOTs, with most agencies considering the process beneficial. There, however, exist reasons that prevent agencies from measuring ITS performance to greater detail and quality. These include lack of data, fragmented or incomparable data formats, the complexity of the endeavor, lack of data scientists, and difficulty assigning responsibilities when inter-agency collaboration is required. Additionally, DOTs do not benchmark or compare their ITS performance with others for reasons that include lack of data, lack of guidance or best practices, and incomparable data formats. This paper is relevant as it provides insights expected to guide DOTs and other agencies in developing or reevaluating their ITS performance measurement processes.

Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement

Emerging connected vehicle (CV) data sets have recently become commercially available, enabling analysts to develop a variety of powerful performance measures without deploying any field infrastructure. This paper presents several tools using CV data to evaluate traffic progression quality along a signalized corridor. These include both performance measures for high-level analysis as well as visualizations to examine details of the coordinated operation. With the use of CV data, it is possible to assess not only the movement of traffic on the corridor but also to consider its origin-destination (O-D) path through the corridor. Results for the real-world operation of an eight-intersection signalized arterial are presented. A series of high-level performance measures are used to evaluate overall performance by time of day, with differing results by metric. Next, the details of the operation are examined with the use of two visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon progression diagram (PPD). Comparing flow visualizations developed with different included O-D paths reveals several features, such as the presence of secondary and tertiary platoons on certain sections that cannot be seen when only end-to-end journeys are included. In addition, speed heat maps are generated, providing both speed performance along the corridor and locations and the extent of the queue. The proposed visualization tools portray the corridor’s performance holistically instead of combining individual signal performance metrics. The techniques exhibited in this study are compelling for identifying locations where engineering solutions such as access management or timing plan change are required. The recent progress in infrastructure-free sensing technology has significantly increased the scope of CV data-based traffic management systems, enhancing the significance of this study. The study demonstrates the utility of CV trajectory data for obtaining high-level details of the corridor performance as well as drilling down into the minute specifics.

Research on the Effect of R&D Investment Intensity and Sales Expense on the Performance of Biomedical Enterprises

Objective To explore the influence of new drug R&D investment and sales expense on the performance of biomedical enterprises.Methods The financial statements of 76 listed biomedical enterprises for 5 consecutive years were selected,and the data were modeled to study the effect of R&D investment and sales expense on the performance of biomedical enterprises by using financial indicators as tools and statistical methods of multiple linear regression.Results and Conclusion Under the premise that the weak related factors such as enterprise scale,life cycle and asset-liability ratio are set as unrelated variables,the R&D investment intensity of biomedical enterprises is negatively correlated with the current performance,which also shows that the R&D of biomedical enterprises has the characteristics of high risk.Besides,the influence of early R&D investment is delayed.However,the sales expense of leading biomedical enterprises with large scales have higher proportion.Meanwhile the greater sales expense of the same enterprise in different periods,the better the enterprise performance is.Biomedical enterprises should consider their own development stage to develop more patented drugs.Besides,they must formulate plans for allocating reasonable sales personnel and cost expense to ensure that enterprises can obtain better benefits.

Research on the Impact of Independent R&D and Collaborative Innovation on Economic Performance in China’s pharmaceutical Industry

Objective To study the impact of independent R&D and collaborative innovation on economic performance in the pharmaceutical industry.Methods A panel regression model was established by selecting the panel data of China’s pharmaceutical industry from 2009 to 2019.Results and Conclusion Independent R&D and collaborative innovation of the pharmaceutical industry in eastern,central and western regions of China had a positive effect on economic performance.Besides,the promotion effect of independent R&D was greater than that of collaborative innovation.The positive driving effect of economic performance is the largest among the three regions,followed by the central and western regions.The collaborative innovation has the greatest positive effect on economic performance in the central region,followed by the eastern and western regions.

Fabrication and performance evaluation of the thermoelectric generation and performance measuring system

A novel thennoelectric generating and performance measuring system （TGPMS） was designed and fabricated. TGPMS can not only achieve the function of thennoelectric generation, but also measure the thennoelectric performance parameters of the bismuth-telluride-based thennoelectric device accurately. These thennoelectric performance parameters mainly include the dependence of the Seebeck coefficient of the thennoelectric device on the device＇s temperature in the low temperature range （about 40 ~ 190~C ）, and the dependence of the power output and thermoelectric conversion efficiency on the temperature dif- ference or output load. With the optimum load, the optimal value of the power output is 3.39W when the temperature difference reaches 231.2~C, and the optimal value of the conversion efficiency is 3.22% when the temperature difference reaches 208.9~C. TGPMS provides an experimental foundation for the application of the thennoelectric generators in the space field.

Monitoring and Measuring Event Decision-Making Process Using Key Performance Indicators： Evidence From Italian Cruise Terminals

This paper investigates the control systems and coordination mechanisms applied in the relationships between cruise line companies and terminal concessionaires in the cruise events management when the ships are stopping on the quay. Using a case study methodology and focusing on the Italian context, this exploratory study, through a qualitative approach, interviewed two main cruise terminal concessionaires and indirectly observed events planned by cruise companies in sea ports selected for outlining the role of control systems, coordination, and knowledge sharing between the players in cruise events decision-making processes. The first results show that the cruise event management processes on ship berthing and on terminal are separated. The cruise companies don＇t involve terminal concessionaires in the event organization considering them only service suppliers Also, the concessionaires conceive the events planned in the cruise infrastructures as a business unit to optimize the space use, without any forms of coordination or control with cruise companies. Knowledge sharing, coordination, and control among the two players could support the planning, and management of ＂new cruise events＂ in which the visitors may be led from the infrastructure to the ships stopped on the quay. This study offers a set of key performance indicators to support the management, control, and coordination of each inter-organizational relationship identified. Managerial implications and suggestions for improving cruise events management have been provided.

New Measurement Method for Spline Shaft Rolling Performance Evaluation using Laser Displacement Sensor

In order to control the quality of spline shaft in rolling process, an efficient measurement method for rolling performance evaluation is essential. Here, a newly developed on-machine non-contact measurement prototype based on laser displacement sensor and rotary encoder is proposed. The prototype is intended for the automated evaluation of the spline shaft rolling performance by measuring the dimensional change of tooth root, which is correlated with the surface residual stress and micro-hardness. Laser displacement sensor and rotary encoder are used to record the polar radius and polar angle of each point on measuring section. Data are displayed in a polar coordinate system and fitted in a gear. Through multipoint curvature method, the roots of spline shaft are recognized automatically. Then, the dimensional change can be calculated by fitting the radius of the tooth root circle before and after rolling. Systematic error covering offset error is also analyzed and calibrated. At last, measurement test results show that the system has advantages of simple structure, high measurement precision(radius error < 0.6 μm), high measurement efficiency(measuring time < 2 s) and automatic control ability, providing a new opportunity for the efficient evaluation of various spline shafts in high-precision mechanical processing.

Dynamic response limit of high-speed railway bridge under earthquake considering running safety performance of train

Due to the wide railway network and different characteristics of many earthquake zones in China,considering the running safety performance of trains(RSPT)in the design of high-speed railway bridge structures is very necessary.In this study,in order to provide the seismic design and evaluation measure of the bridge structure based on the RSPT,a calculation model of RSPT on bridge under earthquake was established,and the track surface response measure when the derailment coefficient reaches the limit value was calculated by referring to 15 commonly used ground motion(GM)intensity measures.Based on the coefficient of variation of the limit value obtained from multiple GM samples,the optimal measures were selected.Finally,the limit value of bridge seismic response based on RSPT with different train speeds and structural periods was determined.

基于同位素稀释液相色谱串联质谱技术检测血清25(OH)D3的候选参考测量程序的建立及性能评价

目的建立基于同位素稀释液相色谱串联质谱技术(liquid phase chromatography tandem mass spectrometry,LC-MS/MS)的血清25羟维生素D3[25-hydroxy vitamin D3,25(OH)D3]的候选参考测量程序。方法采用同位素标准溶液为内标,液液萃取进行前处理,正离子电喷雾模式进行监测。参照美国临床实验室标准化协会(Clinical and Laboratory Standards Institute,CLSI)C62-A和EP15-A3等文件,对方法的正确度、精密度、线性范围、定量限、检测下限、相对基质效应等进行验证。采用候选参考测量程序和质谱常规程序检测40份临床血清样本,评价两种方法的一致性。结果候选方法的分析时间为15 min,通过色谱的等度洗脱可有效分离同分异构体3-epi-25(OH)D3,特异度好。测定参考实验室室间比对(RELA)样本,偏倚低于1.5%。批内精密度和批间精密度分别为0.75%~2.31%和1.28%~2.01%。定量限和检测下限分别为0.85 ng/ml和1.84 ng/ml。在2.5~220ng/ml浓度范围内线性良好。无相对基质效应和携带污染。质谱常规程序与候选参考程序的相关性较好(r=0.982),但低浓度样本处的偏差超出卫健委临检中心室间质评的允许总误差±25%。结论成功建立了基于LC-MS/MS技术的血清25(OH)D3的候选参考测量程序,分析性能符合要求,可用于临床常规方法的量值溯源。

Study of the seismic performance of hybrid A-frame micropile/MSE (mechanically stabilized earth) wall

The Hybrid A-Frame Micropile/MSE （mechanically stabilized earth） Wall suitable for mountain roadways is put forward in this study： a pair of vertical and inclined micropiles goes through the backfill region of a highway MSE Wall from the road surface and are then anchored into the foundation. The pile cap and grade beam are placed on the pile tops, and then a road barrier is connected to the grade beam by connecting pieces. The MSE wall＇s global stability, local stability and impact resistance of the road barrier can be enhanced simultaneously by this design. In order to validate the serviceability of the hybrid A-frame micropile/MSE wall and the reliability of the numerical method, scale model tests and a corresponding numerical simulation were conducted. Then, the seismic performance of the MSE walls before and after reinforcement with micropiles was studied comparatively through numerical methods. The results indicate that the hybrid A-frame micropile/ MSE wall can effectively control earthquake-induced deformation, differential settlement at the road surface, bearing pressure on the bottom and acceleration by means of a rigid-soft combination of micropiles and MSE. The accumulated displacement under earthquakes with amplitude of 0.1-0.5 g is reduced by 36.3%-46.5%, and the acceleration amplification factor on the top of the wall is reduced by 13.4%, 15.7% and 19.3% based on 0.1, 0.3 and 0.5 g input earthquake loading, respectively, In addition, the earthquake-induced failure mode of the MSE wall in steep terrain is the sliding of the MSE region along the backslope, while the micropiles effectively control the sliding trend. The maximum earthquake-induced pile bending moment is in the interface between MSE and slope foundation, so it is necessary to strengthen the reinforcement of the pile body in the interface. Hence, it is proven that the hybrid A-frame micropile/MSE wall system has good seismic performance.

Rates of surgical site infection as a performance measure:Are we ready?

With the introduction of quality assurance in health care delivery,there has been a proliferation of research studies that compare patient outcomes for similar conditions among many health care delivery facilities.Since the 1990s,increasing interest has been placed in the incorporation of clinical adverse events as quality indicators in hospital quality assurance programs.Adverse post-operative events,and very especially surgical site infection(SSI) rates after specif ic procedures,gained popularity as hospital quality indicators in the 1980s.For a SSI rate to be considered a valid indicator of the quality of care,it is essential that a proper adjustment for patient case mix be performed,so that meaningful comparisons of SSI rates can be made among surgeons,institutions,or over time.So far,a signif icant impediment to developing meaningful hospital-acquired infection rates that can be used for intra-and inter-hospital comparisons has been the lack of an adequate means of adjusting for case mix.This paper discusses what we have learned in the last years regarding risk adjustment of SSI rates for provider performance assessment,and identif ies areas in which signif icant improvement is still needed.

Detection performance and inversion processing of logging-while-drilling extra-deep azimuthal resistivity measurements

We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.

Effect of Measurement Error on the Multivariate CUSUM Control Chart for Compositional Data

Control charts(CCs)are one of the main tools in Statistical Process Control that have been widely adopted in manufacturing sectors as an effective strategy for malfunction detection throughout the previous decades.Measurement errors(M.E’s)are involved in the quality characteristic of interest,which can effect the CC’s performance.The authors explored the impact of a linearmodel with additive covariate M.E on the multivariate cumulative sum(CUSUM)CC for a specific kind of data known as compositional data(CoDa).The average run length(ARL)is used to assess the performance of the proposed chart.The results indicate that M.E’s significantly affects themultivariate CUSUM-CoDaCCs.The authors haveused theMarkov chainmethod to study the impact of different involved parameters using six different cases for the variance-covariance matrix(VCM)(i.e.,uncorrelated with equal variances,uncorrelated with unequal variances,positively correlated with equal variances,positively correlated with unequal variances,negatively correlatedwith equal variances and negatively correlated with unequal variances).The authors concluded that the error VCM has a negative impact on the performance of themultivariate CUSUM-CoDa CC,as the ARL increases with an increase in the value of the error VCM.The subgroup size m and powering operator b positively impact the proposed CC,as the ARL decreases with an increase in m or b.The number of variables p also has a negative impact on the performance of the proposed CC,as the values of ARL increase with an increase in p.For the implementation of the proposal,two illustrated examples have been reported formultivariate CUSUM-CoDaCCs inthe presence ofM.E’s.Onedealswith themanufacturingprocessof uncoated aspirin tablets,and the other is based on monitoring the machines involved in the muesli manufacturing process.