System Performance Assessment Research Articles

Health system performance assessment: embedding resilience through performance intelligence.

Health systems around the world are facing challenges in achieving their goals. In the wake of the coronavirus disease pandemic, the need for resilient health systems has become even more apparent. This article argues that embedding resilience into health system performance assessment (HSPA) frameworks can be a valuable approach for improving health system performance. This perspective examines key challenges threatening health systems and makes a case for the continued relevance of HSPA by embedding resilience-related performance intelligence.

Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer.

Recently, global interest in organizing the functioning of renewable energy resources (RES) through microgrids (MG) has developed, as a unique approach to tackle technical, economic, and environmental difficulties. This study proposes implementing a developed Distributable Resource Management strategy (DRMS) in hybrid Microgrid systems to reduce total net percent cost (TNPC), energy loss (Ploss), and gas emissions (GEM) while taking the cost-benefit index (CBI) and loss of power supply probability (LPSP) as operational constraints. Grey Wolf Optimizer (GWO) was utilized to find the optimal size of the hybrid Microgrid components and calculate the multi-objective function with and without the proposed management method. In addition, a detailed sensitivity analysis of numerous economic and technological parameters was performed to assess system performance. The proposed strategy reduced the system's total net present cost, power loss, and emissions by (1.06%), (8.69%), and (17.19%), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. This study gives a more detailed plan for evaluating the effectiveness of hybrid Microgrid systems from a technical, economic, and environmental perspective.

Smart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management

The integration of fluctuating renewable resources such as wind and solar into existing power systems poses challenges to grid reliability and the seamless incorporation of these resources. To address the inherent variability in renewable generation, direct load control emerges as a promising method for demand-side management. Thermostatically controlled appliances, like air conditioners, hold a significant role in this approach. However, effective direct load control necessitates accurate load magnitude estimation and the potential for load shifting. In this paper, we introduce a smart-agent architecture that employs a mathematical model to forecast aggregated power consumption behavior, even when changes are introduced by the controller. To assess system performance, a numerical simulator was developed, demonstrating the system’s adaptability to changes, its self-retraining capability, and its continuous improvement in predicting aggregated power consumption.

Application Of Rating Scale Method to Design An Employee Performance Assessment System in a Health Equipment Distributor Company

This research aims to find out how to design and build an employee performance assessment information system using the rating scale method. The data collection methods used in this research were observation, interviews, library research, and a literature study. The research utilized the rating scale as the method for assessing employee performance. The author used the Rapid Application Development (RAD) method in system development. The review and analysis confirmed this research's success in developing an employee performance assessment information system using the rating scale method. The successful implementation of this system has had a positive impact by providing a solution to the challenge of performance assessment that is less than objective. With the existence of an employee performance appraisal information system, companies now have tools that can reduce the level of subjectivity in performance appraisals. Using the rating scale method in this system provides consistent evaluation standards, increases assessment accuracy, and presents a higher element of objectivity. In conclusion, implementing the employee performance assessment information system opens up opportunities for continuous improvement in human resource management. With a focus on objectivity and measurability, this system has the potential to become an invaluable tool in achieving company goals and vision.

Insertion of synthetic lesions on patient data: a method for evaluating clinical performance differences between PET systems

BackgroundPerformance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. We have already introduced and experimentally evaluated a simulation method allowing the creation of a controlled ground truth for system performance assessment. In the current study, the goal was to validate the method using patient data and demonstrate its relevance to assess PET performances accuracy in clinical conditions.MethodsTwenty-four patients were recruited and sorted into two groups according to their body mass index (BMI). They were administered with a single dose of 2 MBq/kg 18F-FDG and scanned using clinical protocols consecutively on two PET systems: the Discovery-IQ (DIQ) and the Discovery-MI (DMI). For each BMI group, sixty synthetic lesions were dispatched in three subgroups and inserted at relevant anatomical locations. Insertion of synthetic lesions (ISL) was performed at the same location into the two consecutive exams. Two nuclear medicine physicians evaluated individually and blindly the images by qualitatively and semi-quantitatively reporting each detected lesion and agreed on a consensus. We assessed the inter-system detection rates of synthetic lesions and compared it to an initial estimate of at least 1.7 more targets detected on the DMI and the detection rates of natural lesions. We determined the inter-reader variability, evaluated according to the inter-observer agreement (IOA). Adequate inter-reader variability was found for IOA above 80%. Differences in standardized uptake value (SUV) metrics were also studied.ResultsIn the BMI ≤ 25 group, the relative true positive rate (RTPR) for synthetic and natural lesions was 1.79 and 1.83, respectively. In the BMI > 25 group, the RTPR for synthetic and natural lesions was 2.03 and 2.27, respectively. For each BMI group, the detection rate using ISL was consistent to our estimate and with the detection rate measured on natural lesions. IOA above 80% was verified for any scenario. SUV metrics showed a good agreement between synthetic and natural lesions.ConclusionsISL proved relevant to evaluate performance differences between PET scanners. Using these synthetically modified clinical images, we can produce a controlled ground truth in a realistic anatomical model and exploit the potential of PET scanner for clinical purposes.

Simulating Local Biases in Visual Attention in Neurocognitive Performance.

Typical visual perception includes an attention bias toward right hemisphere mediated global, holistic cortical processing. An atypically local, detail-oriented focus of attention is characteristic of left hemisphere processing and is often observed in patients whose field of attention is restricted by certain types of neurocognitive impairment. We designed the present pair of studies to induce a local attentional focus to observe its consequences on neurocognitive measures of visuospatial processing. In Experiment I, participants wore glasses mimicking simultanagnosia, a disorder of visual attention, to induce a narrowed, atypical attentional style while they completed visual neuropsychological tasks. This simulation impaired participants' capacities to visually synthesize and efficiently reproduce Complex Figure stimuli as measured with the Boston Qualitative Scoring System (BQSS), and it induced an atypical attentional style on Rorschach Performance Assessment System (R-PAS) responses. In Experiment II, participants wore glasses designed to provoke differential hemispheric activation, also hypothesized to influence style of visual attention; but this manipulation did not influence neurocognitive task performance. We discuss implications for the interpretation of BQSS and R-PAS scores and offer directions for future research.

Achievement Prediction and Performance Assessment System for Nations in the Asian Games

The profound impact of deep learning technology is poised to revolutionize various industries, marking the fourth industrial revolution. Thus, we combined efficiency and productivity research (data envelopment analysis, DEA), artificial intelligence and deep learning (artificial neural networks, ANN), a system integrating DEA and ANNs, and simultaneous longitudinal research (time series) to determine comprehensive research trends and create relevant applications. We addressed mega-sports events’ performance assessment systems that predict the efficiency of nations participating in the Asian Games from 1990 to 2023 and analyzed the outcomes, applying them to practical issues of national sports policies and development. Performance assessment systems to diagnose, plan, monitor, and revise the impact of implementing measures in Asian nations represent a step forward. The PAS findings point out future research recommendations by addressing national sports policies and development issues, transforming the predictions of performance assessment systems in mega-sports events into practical management recommendations. In this way, the system for enhanced predictive analytics developed in the study can rapidly analyze large, medium, and small datasets, reveal insights that humans may overlook, and refine the likelihood of predicting future events with greater precision and accuracy.

Comprehensive performance assessment and multi-objective optimization of high-power proton exchange membrane fuel cell system under variable load

Due to the advantages of zero emission, high efficiency and low noise, Proton Exchange Membrane Fuel Cell (PEMFC) has grown to be the spotlight in the field of new energy in recent years. In this work, a high-power PEMFC system model is designed, which consists of the fuel feed Subsystem, the air feed subsystem, the thermal management subsystem and the stack. Among them, the material diffusion in the catalyst layer of the stack is intensively studied and derived. For the comprehensive system performance assessment, the thermodynamic, economic and environmental evaluation models have been developed. The mapping relationships between the operating parameters, the structural parameters and the system comprehensive performance under variable load conditions are obtained. The results of the study prove that increasing the operating temperature and decreasing the membrane thickness under high load current conditions are conducive to increase the system net power output, but at the same time increase the levelized cost of energy and the carbon mass specific emission. In addition, a multi-objective optimization strategy based on the NSGA-Ⅱ is designed to obtain the optimal performance of the system under different operating conditions. The optimized net power, the levelized cost of energy and the carbon mass ratio emission of the system for the final optimal operating point are increased by 40.5 %, 10.3 % and 33.3 % respectively. The aforementioned evidence substantiates the effectiveness of the proposed multi-objective optimization strategy in enhancing the overall performance of the PEMFC system.

Expanding the Interpretive Potential of Eye Tracking for the Rorschach: Replication and Extension of the Findings of Ales et al. (2020)

The present study was undertaken to determine if the findings of Ales et al. (2020) could be replicated and extended, especially in light of the replication crisis in psychology and the social sciences. Ales et al. (2020) found that measures from the engagement and cognitive processing domain of the Rorschach performance assessment system (R-PAS) were associated with Eye Tracking variables that reflect cognitive engagement and effort. Notably, Complexity was associated with the number of fixations participants made while scanning the blots and Vg% was inversely associated with a participant’s average fixation durations. The present study utilized a non-clinical sample of 60 adult participants. The basic findings of Ales et al. (2020) were replicated. In addition, we found that Complexity and Vg% are associated with additional Eye Tracking variables not utilized in the original study. The current findings bolster and extend the interpretation of Ales et al. (2020), indicating that higher levels of Complexity are also associated with scanning more regions of the blot overall, albeit at a slower rate. Similar effect size values were observed in the two different cultural contexts. Higher levels of Vg% are associated with measures indicating shallower and more superficial search strategies, consistent with the interpretation of Vg% as indicative of a vague, impressionistic, and unsophisticated cognitive style.

Accounting academic leaders’ perceptions on New Zealand’s performance-based research funding system

PurposeUniversities globally have faced the introduction of research performance assessment systems that provide monetary and ranking rewards based on publication outputs. This study aims to seek an understanding of the implementation of performance-based research funding (PBRF) and its impact on the heads of departments (HoDs) and accounting academics in New Zealand (NZ) tertiary institutions. The study explores NZ accounting academics’ experiences and their workload; the relationship between teaching and research in the accounting discipline and any issues and concerns affecting new and emerging accounting researchers because of PBRF.Design/methodology/approachApplying an institutional theoretical lens, this paper explores accounting HoDs’ perceptions concerning the PBRF system’s impact on their academic staff. The research used semi-structured interviews to collect data from NZ’s eight universities.FindingsThe key findings posit that many institutional processes, some more coercive in nature, whereas others were normative and mimetic, have been put in place to ensure that academics are able to meet the PBRF requirements. HoDs suggest that their staff understand the importance of research, but that PBRF is a challenge to new and emerging researchers and pose threats to their recruitment. New academics must “hit the ground running” as they must demonstrate not only teaching abilities but also already have a track record of research publications; all in all, a daunting experience for new academics to overcome. There is also a teaching and research disconnect. Furthermore, many areas where improvements can be made in the design of this measurement tool remain.Originality/valueThe PBRF system has significantly impacted on accounting academics. Central university research systems were established that subsequently applied coercive institutional pressures onto line managers to ensure that their staff performed. This finding offers scope for future research to explore a better PBRF that measures and rewards research productivity but without the current system’s unintended negative consequences.

Analytical study and real simulation for improving the safety of ageing nuclear facility using UPFC

This paper aims to increase the performance and improve the safety of an ageing Nuclear Facility (NF). Good power quality extends the life of electrical equipment at NF and thus protects it from premature aging. The first stage of this paper presents a measurement and analysis of various power quality events for a real-world case of a NF under different conditions of operation. In the previous work for this group, a new proposed technique based on partial swarm optimization is presented to find the allocation of the UPFC to enhance the power quality within the specified limit. The technique is tested by IEEE33 bus. This step is to assess system performance and find the best solutions to ensure the normal and safe operation of NF. In this paper, the simulink-matlab programme was used to simulate a real NF based on a new vision of UPFC. The results indicate that the strategy is an effective way to improve the safety of power quality and ageing NF using UPFC.

Machine Learning System Implementation of Education Podcast Recommendations on Spotify Applications Using Content-Based Filtering and TF-IDF

Spotify, this popular music and podcast streaming service, has a fundamental problem in assisting clients in finding podcasts that fit their interests. Thus, the goal of this project is to develop a podcast recommendation system that would enhance users' capacity to identify pertinent content, particularly in the educational genre. By using content-based filtration techniques, this system analyzes the user's listening preferences and interests before recommending educational podcasts. The podcast data source is Spotify, and the suggestions are produced using the TF-IDF and Cosine Similarity techniques. The recommendations provide a list of educational podcasts catered to the user's specific interests. The Confusion Matrix Classification Report was tested to assess system performance during the review phase. Precision values show how accurate the system was at recommending educational podcasts; on average, they range from 0.52 to 0.74. Additionally, the recall value showed a mean of 0.51 and a mean of 0.79, indicating that the algorithm successfully located the relevant content. To put it briefly, this custom recommendation engine enhances the listening experience for Spotify customers by suggesting educational podcasts based on their preferences. The system's ability to match users with material that aligns with their interests was demonstrated by the metrics used to assess its performance. With more user interactions with the system, it was anticipated by Cosine Similarity, a statistic used to determine the quality of recommendations, will continue to improve. To improve user experience and personalize the podcast listening experience on Spotify, this research addresses the challenge of locating suitable podcasts.

Performance assessment of PTSC-driven organic Rankine cycle systems integrated with bottoming Kalina and absorption chiller cycles: A parametric study

It is crucial to evaluate the impact of key parameters of multi-generation systems on their performance characteristics in order to develop efficient systems. The present study conducts parametric analysis of a PTSC-driven trigeneration system with a novel energy distribution based on directfed ORC and bottom-cycled arrangement of double-effect absorption refrigeration cycle and Kalina cycle system. Three different ORC structures (simple, regenerative, and ORC integrated with intermediate heat exchanger ? IHE) are proposed. Effect of key ORC parameters namely ORC evaporator pinch point temperature and pump inlet temperature is examined on the thermodynamic performance of systems. Decrease of pinch point temperature enhances overall efficiencies and heating power in all three configurations, and increases (decreases) the net electrical power for ORC and regenerative ORC (RORC) based systems. This also enhances the cooling power of the RORC based system, though it has no impact on the cooling power of the ORC and ORC-IHE based systems. Reduction of the ORC pump inlet temperature increases overall exergy efficiency in all hybrid systems and overall energy efficiency in the ORC and ORC-IHE based systems, whereas it slightly decreases for the RORC based system. Based on a comparative study, performance of the proposed systems is found to be higher than related solar-driven multi-generation systems in the literature.

Multi-dimensional and multi-level assessment of circular economy strategies in manufacturing systems

A manufacturing system can simultaneously exploit more strategies from the Circular Economy paradigm, such as reduction, reuse, repair, refurbishment, and remanufacturing. These strategies involve finished products, raw materials, and components, and each adopted strategy can unpredictably impact the system performance along one or more dimensions (technical, economic, and environmental) at both the planning and the life cycle levels. This paper deepens the simultaneous measurement of the multi-dimensional and multi-level (strategic and tactical planning and life cycle design) performance of the manufacturing system in the presence of circular economy strategies. The Multi-layer Enterprise Input-Output (MEIO) formalisation method is extended to integrate Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) approaches to perform scenario analyses. The proposed approach is applied to a numerical example to show the impacts of adopting new processes for circular economy strategies in a brownfield context. The considered scenarios combine different circular economic strategies applied to different levels of the Bill of Materials of a multi-product environment. The proposed approach can help practitioners and production managers evaluate adopting circular economy strategies. Moreover, the approach can support the development of methods for simultaneous multi-dimensional performance assessment of manufacturing systems at the operational level.

A comprehensive performance evaluation algorithm for substation secondary equipment: An improved analytic hierarchy process entropy weight and learning vector quantization neural network approach

AbstractThis paper introduces a comprehensive performance evaluation algorithm explicitly designed for secondary equipment in substations, specifically targeting the relay protection system. In contrast to the current evaluation systems, this novel method navigates the complex internal interconnections and mechanisms inherent within secondary system equipment. Such complications have previously impeded the accuracy and breadth of evaluations, thereby limiting the degree of precision and innovation attainable within substations. The proposed approach effectively integrates the improved Analytic Hierarchy Process entropy weight (IAHP‐EW) method with the Learning Vector Quantization (LVQ) neural network. Initially, the IAHP‐EW method identified the comprehensive evaluation indicators and their corresponding weights for relay protection devices. Following weight allocation, these evaluation indicators are scrutinized and computed utilizing the multivariate regression analysis algorithm, resulting in performance evaluation outcomes for the relay protection system. These outcomes are subsequently classified and utilized in training the LVQ neural network, promoting the network's capacity to autonomously evaluate the performance status of the relay protection system. To corroborate the viability and effectiveness of this proposed performance evaluation and prediction algorithm, empirical operating data from a local substation is used. The results suggest a significant improvement in the evaluation accuracy of secondary equipment performance, indicating potential for practical application and a valuable contribution to the field through the introduction of a novel approach to performance assessment of substation relay protection systems.

Explainable Deep Learning Model for Grid-Connected Photovoltaic System Performance Assessment for Improving System Reliability

Explainable Deep Learning Model for Grid-Connected Photovoltaic System Performance Assessment for Improving System Reliability

Developing an ISO 45001-based OHSMS for a Bogotá, Colombia real estate and property development company

Today, many organizations are seeking to implement continuous improvement plans not only to achieve greater economic benefits but also to improve the quality of life for their employees. The importance of reducing and preventing workplace accidents, protecting the health and well-being of employees, and preventing work-related illnesses has increased. This article focuses on the development of an Occupational Health and Safety Management System (OHSMS) for an organization in the real estate and property development services sector in Bogotá. The design of the OHSMS is based on the identification of the deficiencies of the current system and the proposal of continuous improvement, according to the ISO 45001: 2018 standard. The design process included three stages of research: 1. initial diagnosis, 2. hazard and risk assessment, and 3. management system performance assessment with appropriate controls and indicators. This article evaluates working conditions in production and in enclosed spaces, such as offices. The integration of these aspects ensures a comprehensive vision of occupational health and safety in real estate and property development companies. The design of the OHSMS is an essential step towards the continuous improvement of working conditions and the well-being of employees. Compliance with the ISO 45001: 2018 standard aims to ensure a safe and healthy working environment for all members of the organization.

Presenting a Model for Virtual Education Considering Educational Equity with a Phenomenological Approach in Schools of Golestan Province

Purpose: The use of virtual education has seen significant growth compared to the past, making it essential to consider it within the context of educational equity. Consequently, this study aimed to present a model for virtual education considering educational equity with a phenomenological approach in schools of Golestan province. Methodology: This study was applied in terms of its objectives and qualitative in its implementation. The research population consisted of experts and professionals in the field of education in Golestan province, from which 11 individuals were selected as the sample using a purposive sampling method based on the principle of theoretical saturation. The research instruments included a demographic information form and semi-structured interviews, the validity and reliability of which were confirmed. Data were analyzed using thematic analysis. Findings: The findings revealed that virtual education, considering educational equity with a phenomenological approach in schools of Golestan province, comprises 49 sub-categories within 10 main categories including equity-focused virtual education, development of virtual education in rural areas, enhancement of teachers' digital skills, equity in social media, improvement of students' technological skills, culture building for virtual education, a comprehensive monitoring system for virtual education, virtual education performance assessment system, understanding the gaps related to electronic education infrastructure facilities, and strategic planning for virtual education. Eventually, a model for virtual education considering educational equity with a phenomenological approach was designed for schools in Golestan province. Conclusion: The designed model of virtual education, considering educational equity with a phenomenological approach, can have significant practical implications for specialists and educational planners. By focusing on its main and sub-categories, they can create an environment conducive to improving virtual education with an emphasis on educational equity.

Research on the Construction of Intelligent Evaluation System of State-owned Asset Management Performance in Higher Vocational Colleges and Universities Based on Data-Driven Approach

Abstract State-owned assets are an important guarantee for the daily teaching and research activities of higher vocational colleges and universities and serve an important role in ensuring the long-term development of higher vocational colleges and universities while also serving as an important task for talent cultivation and discipline development. In this paper, the construction process of the state-owned assets management performance assessment system is studied in depth, and the state-owned assets management level of higher vocational colleges and universities is analyzed by combining the hierarchical analysis method with the comprehensive fuzzy evaluation method. By constructing the index system and judgment matrix, the weights of “asset security level”, “asset management capacity”, “asset operation efficiency” and “asset management effect” are determined. The weights of “asset security level”, “asset management capacity”, “asset operation efficiency” and “asset management effect” are 0.41, 0.19, 0.18 and 0.22, respectively, and the judgment matrix satisfies the consistency test. The constructed index system is used to assess the management of state-owned assets of a higher vocational college, and the quantitative results show that its fuzzy comprehensive evaluation score is 66.6, reflecting the good level of comprehensive management of the school. The scores of specific level 1 indicators show that the school performs well in “asset management capacity” (70.08 points) but in “asset protection level” (66.72 points), “operational efficiency” (63 points) and “asset management capacity” (63 points), the school’s overall management level is good. However, there is still much room for improvement in “asset security level” (66.72 points), “operational efficiency” (63 points) and “management effectiveness” (66.32 points).

Promoting Core Values with a Values-based Performance Assessment System: Evidence from a Retail Chain

Promoting Core Values with a Values-based Performance Assessment System: Evidence from a Retail Chain