Online Performance Assessment Research Articles

Differences in source selection and their effect on the quality of written statements during a critical online reasoning performance assessment

The importance of researching information on the Internet is ever increasing. While ease of use and accessibility are advantages, there is a risk of not being able to adequately assess the relevance and reliability of online sources. With data from the BRIDGE-project (N = 143) we assess the online movements of respondents and track how they researched digitally to answer a task on a generic, accessible topic. We then draw conclusions about their search behavior during this open online performance assessment. The controlled and monitored environment allowed to identify differences in their source selection and how those had an impact on the quality of their written statements respective to the given task.

Online performance and proactive maintenance assessment of data driven prediction models

Online performance and proactive maintenance assessment of data driven prediction models

Online Bridge Structural Condition Assessment Based on the Gaussian Process: A Representative Data Selection and Performance Warning Strategy

Data-driven methods have now been widely used in structural health monitoring of civil infrastructures thanks to the rapid development of sensor technologies with massive structural and operational condition data. One main issue of data-driven methods is that the computational time increases with the number of monitoring data used, which limits their applications for online structural condition assessment. Focusing on bridge structural health monitoring, this paper proposes a representative data selection strategy for online performance assessment based on Gaussian process models. The proposed method can effectively reduce the required monitoring data size for training, allowing the bridge performance assessment to be conducted in a real-time manner. The method is developed in a probabilistic manner, allowing associated uncertainty of bridge monitoring data to be rigorously considered. A probabilistic warning index is proposed for bridge condition assessment and anomaly detection. The proposed method is validated using synthetic data and applied to structural condition assessment of two full-scale bridges, illustrating the feasibility for real implementations.

Internet-based Technologies are the Tools for Promoting Sportsmanship in Pakistan

In today's digital era, the sports industry is going through a remarkable transformation. It's no longer just a game; the integration of technology in sport is reshaping how teams operate, athletes train themselves, and fans like to engage. Various tools, platforms, and applications for online coaching, performance assessment, smart apparel, and footwear have been created. Thus, it can be inferred that a network of well-organized devices and sensors has emerged to revolutionize sports industry as a whole. However, in Pakistan, technological adoption is often neglected and prejudiced. In the context of sports, Pakistan exhibits a restricted range of diverse athletic activities, mostly adhering to traditional practices and displaying little integration of technology advancements. The primary objective of this research is to examine the impact of internet technology on the promotion of sportsmanship within the context of Pakistan. The researchers have conducted in-depth interviews with athletes and sports professionals, using theme analysis to transcribe and evaluate the participants' comments in a comprehensive manner. The results indicate that technology plays a crucial role in upholding the integrity of the game, and the incorporation of technology in sports may enhance Pakistan's overall performance index.

Countering vaccine hesitancy: a systematic review of interventions to strengthen healthcare professionals' action.

Vaccine hesitancy is relevant for healthcare professionals (HCPs) who face challenges in building trusting relationships with patients. Accordingly, the VAX-TRUST project has been developed to improve experiences of HCPs and patients dealing with vaccinations. To support VAX-TRUST, this work aimed to identify latest interventions targeted at HCPs to address hesitancy and increase vaccine uptake. A systematic review was conducted according to PRISMA by searching PubMed, Scopus and Embase. The protocol was registered on PROSPERO. Articles were eligible if evaluated interventions directly targeted at HCPs/healthcare students. The search was run on 26 January 2022. Articles published in 2016 or after were included. A total of 17 492 records were identified; 139 articles were selected. Most articles were set in USA (n = 110). Over half had a pre-post design without a control group (n = 78). A total of 41 articles focused on single-component interventions, 60 on multi-component interventions involving only HCPs and/or students and 38 on multi-component interventions involving also other professionals. Main components were in-person education (n = 76), synchronous (n = 10) and asynchronous (n = 23) online learning, educational materials (n = 26), performance assessment and feedback (n = 33), electronic record changes (n = 30), role play/simulation (n = 21) and online games/apps (n = 5). Educational sessions were mainly about scientific update or communication. Outcomes of interventions were grouped in: vaccination rates (n = 69), knowledge (n = 32), attitudes (n = 26), confidence in counselling (n = 30) and acceptability (n = 16). Apps, gaming, role play/simulations could represent innovative interventions. This review highlighted the need of delving into communication strategies and using more robust evaluations, longer follow-up and standardized measurements.

Leveraging Online Tutorials and Performance Assessment to Improve Information Literacy Instruction

Leveraging the campus Learning Management System (LMS) and rapid e-learning development software such as Articulate Storyline allows educators to develop and deploy interactive tutorials for performance assessment of student's knowledge. This quick hit chronicles the development, deployment, and assessment of a suite of tutorials for information literacy instruction. Opportunities and challenges will be highlighted as well as how working with a dash boarding tool like PowLeveraging the campus learning management system and rapid e-learning development software such as Articulate Storyline allows educators to develop and deploy interactive tutorials for performance assessment of students’ knowledge. This quick hit chronicles the development, deployment, and assessment of a suite of tutorials for information literacy instruction. Opportunities and challenges are highlighted as well as how working with a dashboarding tool such as Power BI can unlock hidden insights in the data and cultivate new collaborations. Visit the project GitHub (https://marquetterml.github.io/information-literacy-modules/) to utilize the tutorials at your own institution and add your input to the project.er BI can unlock hidden insights in the data and cultivate new collaborations. Visit the project GitHub to utilize the tutorials at your own institution and add your input to the project - https://marquetterml.github.io/information-literacy-modules/.

Performance evaluation strategy for battery pack of electric vehicles: Online estimation and offline evaluation

Electric vehicles are powered by battery packs, which are usually composed of hundreds of units in series or in parallel. For power battery pack performance evaluation, many literatures have been published, including online performance assessment, life prediction and offline performance evaluation. Nevertheless, performance evaluation strategies that include both online and offline have not attracted sufficient attention. In this paper, we propose a performance evaluation method based on MCPE-DEKF, which can solve the problem of consistency analysis and sort of battery cells offline, as well as, implementing battery pack state estimation online. MCPE-DEKF is designed to enhanced the accuracy and adaptability for power battery pack SOC estimation. The pack SOC online estimation value from cells means model and the standard deviation of SOC estimation are combined with MCPE to determine their aggregation weights. An offline evaluation framework for cells grading and sorting problem is solved by MCPE methods. As the results show that, the RMSE of the online estimation for the battery pack is less than 2% and 7 mV for the SOC and the terminal voltage, respectively. The RMSE of the cell estimation is less than 0.3% and 6 mV, respectively. In terms of offline evaluation approaches for cells, we propose an approach with a fusion method to improve the reliability of sorting by integrating method 1 and method 4 (the second-best sorting method).

Concentration measurement of a mixture using an infrared transceiver

Microreaction technologies are employed in various applications like space propulsion, atomization, drug delivery and in lab-on-chip applications. Mixing index measurement in micro reactors is essential to assess the performance of the proposed micro mixer. A major roadblock in the design of a micromixer is its assessment and determination of mixing index during the operation due to the complex flow characteristics and mass transfer that occur during the mixing of fluids or reactants. Sensor design is thus vital in analyzing the performance of micro mixers during operation. Infrared sensing is a versatile flow visualization technique which has been effectively used previously to characterize two phase flows in conventional macro channels. The present work develops a robust multiphysics simulation framework and provides a comprehensive characterization of an infrared sensor to perform online assessment of micromixers during their operation. This study considers the case of an optimized passive micromixer described in several literatures and models the microfluidic mixing between silica nanoparticles and distilled water at various concentrations. Further coupling was done by applying the physics of ray optics to understand the performance of an infrared sensor. The variation in infrared sensor output with the mixing index is presented based on the multiphysics coupling. With this analysis, the characteristic output of an infrared sensor can be inferred for any practical microfluidic mixing and microreactor application, thus helping the instrumentation design for online performance assessment of micromixers.

Controlling the AP Controller: Controller Performance Assessment and Modification.

Despite recent advances in closed-loop control of blood glucose concentration (BGC) in people with type 1 diabetes (T1D), online performance assessment and modification of artificial pancreas (AP) control systems remain a challenge as the metabolic characteristics of users change over time. A controller performance assessment and modification system (CPAMS) analyzes the glucose concentration variations and controller behavior, and modifies the parameters of the control system used in the multivariable AP system. Various indices are defined to quantitatively evaluate the controller performance in real time. Controller performance assessment and modification system also incorporates online learning from historical data to anticipate impending disturbances and proactively counteract their effects. Using a multivariable simulation platform for T1D, the CPAMS is used to enhance the BGC regulation in people with T1D by means of automated insulin delivery with an adaptive learning predictive controller. Controller performance assessment and modification system increases the percentage of time in the target range (70-180) mg/dL by 52.3% without causing any hypoglycemia and hyperglycemia events. The results demonstrate a significant improvement in the multivariable AP controller performance by using CPAMS.

Online assessment of sand filter performance for bacterial removal in a full-scale drinking water treatment plant

Microbiological risks associated with drinking water can be minimized by providing enhanced integrity monitoring of bacterial removal by water treatment processes. This study aimed to evaluate the efficacy of real-time bacteriological counters for continuously assessing the performance of a full-scale sand filter to remove bacteria. Over the course of an 8-day evaluation, online counting of bacteria was successfully performed, providing continuous bacterial counts in the sand filter influent and effluent over approximate ranges from 17 × 104 to 94 × 104 and from 0.2 × 104 to 1.3 × 104 counts/mL, respectively. Periodic variations were observed with online bacterial counts in the sand filter influent because of the changes in the performance of flocculation and sedimentation processes. Overall, online removal rates of bacteria determined during the full-scale test were 95.2–99.3% (i.e., 1.3–2.2-log), indicating that online bacterial counting can continuously demonstrate over 1.3-log removal in the sand filter. Real-time bacteriological counting technology can be a useful tool for assessing variability and detecting bacterial breakthrough. It can be integrated with other online water quality measurements to evaluate underlying trends and the performance of sand filters for bacterial removal, which can enhance the safety of drinking water.

Fusion of Online Assessment Methods for Gynecological Examination Training: a Feasibility Study

The objective of this paper was to determine if a fusion of online assessment methods is a feasible methodology for online assessment of performance of users inside virtual reality simulators. Three different forms of the Fuzzy Naive Bayes method based  on statistical distributions were used to assess specific tasks and the fusion of information was performed by a Weighted Majority Voting system. Data was compiled representing a portion of the Gynecological Exam, which is a checkup examination that is routinely performed for women and is paramount in finding earlier cases of cervical cancer. Confusion matrices and Kappa coefficients were obtained using a Monte Carlo simulation for this method. From the analysis of these results, it is possible to confirm that this method performed well, with a substantial agreement degree.

Online complex nonlinear industrial process operating optimality assessment using modified robust total kernel partial M-regression

Abstract Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc . Thus, it is necessary to develop efficacious strategies or procedure to assess the process performance online. In this paper, we explore the issue of operating optimality assessment for complex industrial processes based on performance-similarity considering nonlinearities and outliers simultaneously, and a general enforced online performance assessment framework is proposed. In the offline part, a new and modified total robust kernel projection to latent structures algorithm, T-KPRM, is proposed and used to evaluate the complex nonlinear industrial process, which can effectively extract the optimal-index-related process variation information from process data and establish assessment models for each performance grades overcoming the effects of outlier. In the online part, the online assessment results can be obtained by calculating the similarity between the online data from a sliding window and each of the performance grades. Furthermore, in order to improve the accuracy of online assessment, we propose an online assessment strategy taking account of the effects of noise and process uncertainties. The Euclidean distance between the sliding data window and the optimal evaluation level is employed to measure the contribution rates of variables, which indicate the possible reason for the non-optimal operating performance. The proposed framework is tested on a real industrial case: dense medium coal preparation process, and the results shows the efficiency of the proposed method comparing to the existing method.

Data‐driven fault diagnosis and robust control: Application to PEM fuel cell systems

SummaryA data‐driven methodology that includes the unfalsified control concept in the framework of fault diagnosis and isolation (FDI) and fault‐tolerant control (FTC) is presented. The selection of the appropriate controller from a bank of controllers in a switching supervisory control setting is performed by using an adequate FDI outcome. By combining simultaneous online performance assessment of multiple controllers with the fault diagnosis decision from structured hypothesis tests, a diagnosis statement regarding what controller is most suitable to deal with the current (nominal or faulty) mode of the plant is obtained. Switching strategies that use the diagnosis statement are also proposed. This approach is applied to a nonlinear experimentally validated model of the breathing system of a polymer electrolyte membrane fuel cell. The results show the effectiveness of this FDI–fault‐tolerant control data‐driven methodology. Copyright © 2017 John Wiley & Sons, Ltd.

Online Performance Assessment System for Urban Water Supply and Sanitation Services in India

Access to water and sanitation services in urban India is widespread, but little is known about the levels of service provision, quality of water supplied and equity of coverage. A key challenge in the urban water supply and sanitation sector in India is the lack of adequate and reliable information. This paper describes the journeys of 400 plus cities in two western states of India from a rudimentary paper-based system to an online performance assessment system. It is prepared under the Performance Assessment System (PAS) research project at CEPT University, funded by the Bill and Melinda Gates Foundation. These 400 plus cities are of various sizes, ranging from 5,000 to 5 million population.

ON-LINE PERFORMANCE ASSESSMENT AND FAULT DIAGNOSIS OF MECHANICAL SYSTEMS

This study integrates sensors, signal capture equipment, industrial computers and machinery health check-up software to develop an On-line Performance Assessment and Fault Diagnosis of Mechanical System, helping engineers predict mechanical conditions. Physical quantities captured by the sensors is utilized to process physical signals, and the Wavelet Packet Energy method is used for the feature extraction of non-stationary signals in coordination with the Principal Component Analysis for feature selection. This study establishes On-line Performance Assessment and Fault Diagnosis of Mechanical System based on Discriminant Analysis which is able to immediately determine the mechanical performance. When abnormal mechanical conditions occur, Bayesian Network will be activated to construct error diagnostic model and determine possible causes of error or malfunction of the machinery. Finally, the system is applied to the fan motor, high-speed spindle motor and AC motor of the machine tool. Experimental results show that the theory can effectively diagnose mechanical performance remarkable with an accuracy rate of 92.50% or higher.

Technology-Driven Online Marketing Performance Measurement

Although the measurement of offline and online marketing is extensively researched, the literature on online performance measurement still has a number of limitations such as slow theory advancement and predominance of technology- and practitioner-driven measurement approaches. By focusing on the widely employed but under-researched affiliate marketing channel, this study addresses these limitations and evaluates the effectiveness of practitioner-led online performance assessment. The paper offers a comprehensive review of extant performance measurement research across traditional, online and affiliate marketing and, employing grounded theory, presents a qualitative in-depth analysis of 72 online forum discussions and 37 semi-structured interviews with the major affiliate marketing stakeholders. As a result, the research identifies a growing need for change in the technology-pushed measurement approaches in affiliate marketing, and proposes actionable improvement recommendations for affiliate and online marketing managers.

A computational framework for life-cycle management of wind turbines incorporating structural health monitoring

The integration of structural health monitoring into life-cycle management strategies can help facilitating a reliable operation of wind turbines and reducing the life-cycle costs significantly. This article presents a life-cycle management framework for online monitoring and performance assessment of wind turbines, enabling optimum maintenance and inspection planning at minimum associated life-cycle costs. Incorporating continuously updated monitoring data (i.e. structural, environmental, and operational data), the framework allows capturing and understanding the actual wind turbine condition and, hence, reduces uncertainty in structural responses as well as load effects acting on the structure. As will be shown in this article, the framework integrates a variety of heterogeneous hardware and software components, including sensors and data acquisition units, server systems, Internet-enabled user interfaces as well as finite element models for system identification, and a multiagent system for self-detecting sensor malfunctions. To validate its capabilities and to demonstrate its practicability, the framework is deployed for continuous monitoring and life-cycle management of a 500-kW wind turbine. Remote life-cycle analyses of the monitored wind turbine are conducted, and case studies are presented investigating both the structural performance and the operational efficiency of the wind turbine.

Factors Affecting the Use of an E-Learning Portal at University

Electronic learning (e-learning) portals can be defined as websites that store and present materials for online learning, training, performance assessment, and certification. Few, if any, studies have investigated the factors that might contribute to the integration or implementation of e-learning portals in universities. With the development of this article, we intend to address the following questions: Does availability of ICT imply the use of e-learning portals? How is ICT being used by students? This article examines the relative importance and significance of three types of ICT (Internet, Groupware, and Collective systems) relating to the use of e-learning portal through an empirical investigation of 210 students in a Spanish university using a multinomial logistic regression. The results support that by effectively developing higher levels of Groupware systems, teachers empower students to make better, more informed decisions—and facilitate the utilization of e-learning portals.

On-Line Monitoring of Run-to-Run Control Performance in a Discrete Microelectronics Manufacturing

Semiconductor manufacturing is challenged by strategy development for ensuring the yield of defect-free products. In this paper, an on-line performance assessment strategy is proposed to evaluate the EWMA-based run-to-run (RtR) controllers in a discrete microelectronics fabrication. Expressions of minimum variance performance (MVP) and best achievable performance (BAP) are derived in a rigorous way. Technologies such as close loop identification and numerical optimization are employed in order to carry out on-line monitoring. Case studies of the chemical mechanical polishing (CMP) unit operation show the efficacy and the attractiveness the strategy.

Assessment of a peer review process among interns at an Australian hospital

This study considered how a peer review process could work in an Australian public hospital setting. Up to 229 medical personnel completed an online performance assessment of 52 Junior Medical Officers (JMOs) during the last quarter of 2008. Results indicated that the registrar was the most suitable person to assess interns, although other professionals, including interns themselves, were identified as capable of playing a role in a more holistic appraisal system. Significant sex differences were also found, which may be worthy of further study. Also, the affirmative rather than the formative aspect of the assessment results suggested that the criteria and questions posed in peer review be re-examined. A peer review process was able to be readily implemented in a large institution, and respondents were positive towards peer review generally as a valuable tool in the development of junior medical staff.