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.

Diverging Diamond Interchange Performance Measures Using Connected Vehicle Data

Since the first Diverging Diamond Interchange (DDI) implementation in 2009, most of the performance studies developed for this type of interchange have been based on simulations and historical crash data, with a small number of studies using Automated Traffic Signal Performance Measures (ATSPM). Simulation models require considerable effort to collect volumes and to model actual controller operations. Safety studies based on historical crashes usually require from 3 to 5 years of data collection. ATSPMs rely on sensing equipment. This study describes the use of connected vehicle trajectory data to analyze the performance of a DDI located in the metropolitan area of Fort Wayne, IN. An extension of the Purdue Probe Diagram (PPD) is proposed to assess the levels of delay, progression, and saturation. Further, an additional PPD variation is presented that provides a convenient visualization to qualitatively understand progression patterns and to evaluate queue length for spillback in the critical interior crossover. Over 7000 trajectories and 130,000 GPS points were analyzed between the 7th and the 11th of June 2021 from 5:00 AM to 10:00 PM to estimate the DDI’s arrivals on green, level of service, split failures, and downstream blockage. Although this technique was demonstrated for weekdays, the ubiquity of connected vehicle data makes it very easy to adapt these techniques to analysis during special events, winter storms, and weekends. Furthermore, the methodologies presented in this paper can be applied by any agency wanting to assess the performance of any DDI in their jurisdiction.

Workflow logs analysis system for enterprise performance measurement

Workflow logs that record the execution of business processes offer very valuable data resource for real-time enterprise performance measurement. In this paper, a novel scheme that uses the technology of data warehouse and OLAP to explore workflow logs and create complex analysis reports for enterprise performance measurement is proposed. Three key points of this scheme are studied: 1) the measure set; 2) the open and flexible architecture for workflow logs analysis system; 3) the data models in WFMS and data warehouse. A case study that shows the validity of the scheme is also provided.

Test Rig Effect on Performance Measurement for Low Loaded Large-Diameter Fan for Automotive Application

Large diameter fans with low solidity are widely used in automotive application for engine cooling. Their designs with small chord length help reducing the torque on the electrical motor and providing a good aerodynamic compromise between several operating conditions, some of these being at high flow rate. Their global performances are measured according to the ISO standard DP 5801, which allows comparison of results from different facilities. However, some variations in global performances are observed when considering results from two different test rigs. On a fan selected for the purpose of this study, up to 6 % of efficiency is lost on the worst case. As efficiency is more than ever a key factor to select a component, some experimental and numerical investigations were conducted to analyze the fan behavior on each facility. Two sets of measurement and simulation are performed and compared. Geometries considered for the domain of computation include the test rig plenum, the torquemeter, the ground and a large domain for the atmospheric conditions. The exact fan geometry with tip clearance and under-hub ribs is also considered. Numerical results show a good agreement with experiment in both cases when convergence is reached and for low flow rate when computations are switched to unsteady mode. Comparisons show that simulations are able to capture the different fan behaviors depending on the confguration and those efficiency losses previously observed are correctly predicted. These results are further analyzed to perform some post-processing. Blade loading remains identical for both cases but disparities appear in the wake and its interaction with the surrounding. Tiny details that are often neglected during experiment and/or simulation appear to be the cause of slight variations. Position of the torquemeter and shape of the plenum are among the parameters that various and that have cumulative effects. Efficiency being a ration of pressure and torque, variations are rather important. Finally, these results are discussed in terms of rules for conception and a new geometry less sensible to loss of efficiency is proposed.

Diamond Interchange Performance Measures Using Connected Vehicle Data

Diamond interchanges are frequently used where a freeway intersects a two-way surface street. Most of the techniques to evaluate the performance of diamond interchanges rely on the Highway Capacity Manual (HCM), simulation, Automated Traffic Signal Performance Measures (ATSPMs), and historical crash data. HCM and simulation techniques require on-site data collection to obtain models’ inputs. ATSPMs need high-resolution controller event data acquired from roadway sensing equipment. Safety studies typically need 3 to 5 years of crash data to provide statistically significant results. This study utilizes commercially available connected vehicle (CV) data to assess the performance and operation of a three- and four-phase diamond interchange located in Indianapolis, Indiana, and Dallas, Texas, respectively. Over 92,000 trajectories and 1,400,000 GPS points are analyzed from August 2020 weekdays CV data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) from which arrivals on green (AOG), split failures, downstream blockage, and movement-based control delay are estimated. In addition, an extension of the PPD is presented that characterizes the complete journey of a vehicle travelling through both signals of the diamond interchange. This enhanced PPD is a significant contribution as it provides an analytical framework and graphical summary of the operational characteristics of how the external movements traverse the entire system. The four-phase control showed high internal progression (99% AOG) compared to the moderate internal progression of the three-phase operation (64% AOG). This is consistent with the design objectives of three- and four-phase control models, but historically these quantitative AOG measures were not possible to obtain with just detector data. Additionally, a graphical summary that illustrates the spatial distribution of hard-braking and hard-acceleration events is also provided. The presented techniques can be used by any agency to evaluate the performance of their diamond interchanges without on-site data collection or capital investments in sensing infrastructure.

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.

Can composite performance measures predict survival of patients with colorectal cancer?

AIM: To assess the relationship between long-term colorectal patient survival and methods of calculating composite performance scores.

Using fuzzy cognitive maps to model performance measurement system of Internet-based supply chain

Fuzzy cognitive maps （FCM） is a well-established artificial intelligence technique, which can be effectively applied in the domains of performance measurement, decision making and other management science. FCM can be a useful tool in a group decision-making environment by using scientifically integrated expert knowledge. The theories of FCM and balance scorecard （BSC） both emphasize cause-and-effect relationships among indicators in a complex system, but few reports have been published addressing the combined application of these two techniques. In this paper we propose a FCM simulation model for the sample performance measurement system of Intemet-based supply chain, which is constructed by BSC theory. We gave examples to explain how FCM can be adapted to execute the causal mechanism of BSC, and also how FCM can support group decision-making and forecasting in performance measurement.

Functional safety verification and performance measurement of train-train communication link

The short-range wireless communication technology has advanced considerably and provides the feasibility of train-train(T2T)communication link in the communication-based train control system.The introduction of the T2T link would reduce the headway and improve operational efficiency.Formal methods are system design techniques that use rigorously specified mathematical models to ensure all behaviors work as expected.And it is exactly the functional safety verification needed.Therefore,to deal with the functional safety verification of the T2T link,an untimed colored petri net model is first constructed.Secondly,the verification process is performed.Conclusions can be drawn from the state space report and the computation tree logic queries.Lastly,the model is parameterized,and then data log files are obtained for further performance measurement.Results show that the proposed criteria are satisfied and there are no defects in the basic design requirements.The transmission delay has considered the reconnection,transmission errors and the interruption.The probability of the delay lower than 150 ms accounts for 98.106%,which meets the specification and the previous field test.

Structure analysis and performance measurement of Chinese health de-livery system

Objective:Although evidence has already demonstrated that the performance of Health Deliv- ery System(HDS) varies widely across nations,relatively little is known about the factors that give rise to these variations and the key point to improve the performance besides adjusting system structure.By setup of HDS performance measurement system on the base of association of financial,social,and environmental characteristics,we construct system dynamic model of HDS to simulate the invention policies.Methods: Performance measures were collected from HDS in 31 regions of China and combined with secondary data sources.Multivariate,linear,nonlinear regression and factor analysis models were used to estimate associ- ations between system characteristics and the performance.Results:Performance varied significantly with the size,financial resources and organizational structure of HDS.Performance measurement system of health delivery system was developed to give the rank of all Chinese regions.Conclusion:Performance measurement system of HDS is the basic of HDS modeling by system dynamic.

Determinants of international joint venture performance measurement： A theoretical framework

International joint ventures （IJVs） have increasingly their role in business world and also in research field of international business. There have been a lot of studies related to determinant factors of IJV performance. However, there are very few studies focusing on the measurement of I Jr performance. Especially, researchers have ignored how foreign parent firms really choose their measures in the evaluation of their IJV performance. This research investigates determinant factors of performance measures of 1JVs. Determinant factors of IJV performance measures include motives for establishment, establishment mode, location of IJVs, distribution of ownership in IJVs, cultural background of parent firms, and trust between partners, IJV life stages, parent firms＇ international experience, and relatedness of the IJVs to their parents. Performance measures are divided into financial measures and non-financial measures. The paper shows how different determinant factors are expected to lead foreign parent firms preferring one kind of measure over the other.

Congruity of Multiple Performance Measures

In multi-action situation, there are losses of efficiency due to noise effect and incongruity effect. To isolate noise effect, we prove that the loss of efficiency is zero if and only if the objective of the principal is a linear representation of the performance measures when the performance measures are noiseless. Using this result, several definitions of incongruity are given. Our definitions extend the single performance definition given in Feltham and Xie （1994） to multiple performance measures situation, and reconcile the conflict between the definition given in Datar et al. （2001） and that in Feltham and Xie （1994）. A numeric example is analyzed to show the way that the variances of measures and correlation coefficient between measures affect the utility of the principal.

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.

Continuous Flow Intersection Performance Measures Using Connected Vehicle Data

Continuous flow intersections (CFIs), also known as displaced left turns (DLTs), are a type of alternative intersection designed to improve operations at locations with heavy left-turn movements by reallocating these vehicles to the left side of opposing traffic. Currently, simulation is commonly used to evaluate operational performance of CFIs. However, this approach requires significant on-site data collection and is highly dependent on the analyst’s ability to correctly model the intersection and driver behavior. Recently, connected vehicle (CV) trajectory data has become widely available and presents opportunities for the direct measurement of traffic signal performance measures. This study utilizes CV trajectory data to analyze the performance of a CFI located in West Valley City, UT. Over 4500 trajectories and 105,000 GPS points are analyzed from August 2021 weekday data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) and extended PPDs to estimate split failures (SF), arrivals on green (AOG), traditional Highway Capacity Manual (HCM) level of service (LOS), and the distribution of stops. The estimated operational performance showed effective progression during the PM peak period at all the critical internal storage areas with AOG levels at exit traffic signals between 83% and 100%. In contrast, all external approaches with longer queue storage areas had AOG values ranging from 2% to 81% during the same time period. The presented analytical techniques and summary graphics provide practitioners with tools to evaluate the performance of any CFI where CV trajectories are available without the need for on-site data collection.

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.

Performance Measurement Based on Balanced Scorecard

Balanced scorecard is a strategic information system and a performance measurement system. It integrates almost all the interests of stakeholders and mainly comprises four perspectives： management, operational, marketing, and knowledge.

Research on Performance Measurement System of Knowledge Strategy for Firms

Knowledge has become the most important strategic resource of firms, and the competition among firms is more based on knowledge than before. To deal with this challenge, some firms are trying to develop knowledge strategies to direct their knowledge management activities, but current strategic performance measurement systems can＇t evaluate the performance of knowledge strategies appropriately. This article develops a performance measurement system for knowledge strategies based on Balanced Scorecard, and simulates the system with an improved Data Envelopment Analysis （DEA） model.

Measuring Raters' Scoring Performance and Their Scoring Results in Terms of Writing Performance Measures

This explorative study investigates 1） whether and how quantitative measures of writing can be applied in finding out about scoring raters＇ specific tendency in their scoring of EFL writing; 2） how the knowledge of raters＇ tendency and scoring results would help verify the best way of combining raters＇ scores; and 3） how the prediction of the writing scores of EFL writing obtained by quantitative writing performance measures would match the real scores given by raters. Based on a tentative CAF framework of writing measures, raters＇ performance or tendency in their scoring was observed and certain patterns of similarities as well as differences were found among the raters. The resuks of multiple linear regressions indicate that all raters give prior attention to the aspect of accuracy in their scoring. Differences among raters are also obvious. When it comes to the combination of different raters＇ scores, the study also finds that weighted average is the best of the three ways of combining scores for this group of raters because it has yielded the best predicting scores than the ＂pure average＂. It is even slightly better than the results obtained by facet analysis in terms of some important indices such as R square and Durbin-Watson value. The matching of the predicted scores with the real scores is well over 50 percent. The results of the study are further discussed in relation to the application of wpm and the possible improvement of wpm framework. The methodological, theoretical and practical implications of the study have also been touched upon in the relevant part of the article.

Performance Measurement and Faculty Pay

In classic agency models, first best efficiency can′t be achieved due to the trade-off between risk and incentives except that agency is risk neutral. Whereas if the principal′s objective is not contractible, an alternative objective performance measurement which is contractible is always proposed. However, if the reaction of this objective performance measurement to agency′s effort differs from that of the principal′s objective, the agent would game performance measures, which leads to loss of efficiency, even if agency is risk neutral. By adding subjective weights on objective measures, or combination of subjective performance measurement with objective performance measurement, efficiency can be regained. Implications for faculty pay are also discussed.

Performance measures in evaluating machine learning based bioinformatics predictors for classifications

Many existing bioinformatics predictors are based on machine learning technology. When applying these predictors in practical studies, their predictive performances should be well understood. Different performance measures are applied in various studies as well as different evaluation methods. Even for the same performance measure, different terms, nomenclatures or notations may appear in different context. Results： We carried out a review on the most commonly used performance measures and the evaluation methods for bioinformatics predictors. Conclusions： It is important in bioinformatics to correctly understand and interpret the performance, as it is the key to rigorously compare performances of different predictors and to choose the right predictor.