Performance Assessment Method Research Articles

An updated multi-criteria decision-making method for the sustainable renovation of buildings including environmental, economic and social life-cycle metrics

The ambitious targets of carbon emission reduction set worldwide for the coming years entail the commitment of structural engineers towards the sustainable renovation of existing buildings. The life cycle thinking (LCT) approach offers a holistic perspective for the design of sustainable retrofitting strategies. It envisages the reduction of the environmental impact at all building life cycle phases, while also addressing economic and social issues. Multi-criteria decision-making (MCDM) approaches support the choice of optimal retrofitting solutions, thus being relevant tools for boosting the actual adoption of LCT in current practices. In this study, a previously proposed MCDM approach is enriched with additional LCT-inspired decision parameters (module D beyond-life impacts, environmental payback period, invasiveness), and is then scrutinised and discussed through its application to a case-study building. Four integrated retrofitting scenarios are investigated using state-of-art seismic loss and energy performance assessment methods, including four different types of exoskeletons, made of timber, steel, and concrete. The end-to-end integrated assessment shows that the inclusion of additional LCT-inspired decision criteria effectively favours LCT-based retrofitting interventions over more traditional ones.

Uncertainty quantification: For an IAQ and energy performance assessment method for smart ventilation strategies

In new low-energy buildings or buildings after thermal refurbishment, the envelope high airtightness could have an impact on air renewal and could decrease the indoor air quality (IAQ). In this context smart-ventilation systems with variable airflows could play a role in providing better IAQ without compromising the energy performance.However, smart-ventilation strategies are quite recent, and their benefits need to be clearly quantified. This article, proposes to quantify the uncertainty of a recent multi-criteria performance assessment method, using global RBD-FAST sensitivity analysis. The impact of the pollutant emissions scenarios, model input parameters and ventilation strategies is assessed.Five ventilation systems were studied: two constant airflow, one humidity-controlled and two humidity/CO2 controlled, applied on a French low-energy house. 2500 simulations were performed to calculate 504 sensitivity indices across 12 input variables and 9 output performance indicators. The sensitivity analysis shows that occupant bio-effluent, formaldehyde and PM2.5 emissions rates are responsible for 11 %–87 % of the uncertainty for the IAQ performance indicators. The PM2.5 deposition velocity parameter is responsible for 50 % of the uncertainty on the PM2.5 indicator, which was an unknown impact. In addition, the benefits of humidity-controlled ventilation were highlighted regarding energy performance, with, in average, 20 % lower heat-loss compared to constant airflow ventilation. Moreover, smart-ventilation provides clear IAQ benefits without drastically increasing the energy demand. This work demonstrates the potential of the proposed evaluation method for ventilation performance assessment.

Circles of port sustainability: A novel method combining global comparability and local relatability in performance assessment

Ports are increasingly ‘greening’ operations to protect their ‘license to operate’ by integrating social-environmental considerations into their management and reporting on their sustainability performance. In this research, we develop a novel method for port sustainability performance (PSP) assessment that combines science-based knowledge with place-based contextualisation. Specifically, we address a recognised challenge of combining global (‘top-down’) techno-scientifically oriented indicators with place-based locally relatable (‘bottom-up’) contexts in sustainability performance, in addition to addressing limitations encountered in empirical verification. First, a critical evaluation of the international literature on port sustainability assessments is undertaken to distil commonalities in global performance indicators, and to identify typical frames used in the design of sustainability performance indices. We apply this learning, together with place-based experiential knowledge, to develop a science-based framework for a Port Sustainability Performance (PSP) Index that is explicitly aligned with the Sustainability Development Goals (SDGs). We then apply a co-design process to demonstrate local customisation of the index to derive place-based quantifiable measures and targets. Further, for easy-to-use empirical verification, a simple spreadsheet is applied to develop a flexible weighted scoring matrix. The matrix uses place-based rating systems for selected measures and associated targets, and aggregates allocated scores into informative outputs. Finally, the concept of Circles of Sustainability is adapted for ports to visually display sustainability performance, in alignment with related SDGs. This research contributes to bridging the science-practice divide in reporting on port sustainability performance.

How can exposure assessment for pesticides in epidemiological studies be improved? Insights from the IMPRESS project

The IMPRoving Exposure aSSessment Methodologies for Epidemiological Studies on Pesticides (IMPRESS) project (http://www.impress-project.org/) aimed to further the understanding of the performance of pesticide exposure assessment methods (EAMs). To achieve this the IMPRESS project used two approaches to assess EAM performance, using existing and newly collected data from five studies from three different countries and use of published secondary data to undertake three meta-analyses for selected chronic health outcomes. Based on the findings of the IMPRESS project we provide in this paper insights on the overarching research question “How can exposure assessments for pesticides in epidemiological studies be improved”? Exposure assessment is a critical component of pesticide epidemiological studies. EAMs used and epidemiological practices employed need to reflect the changing nature and complexities of pesticide exposure in various occupational settings. To properly assess the association between exposure and selected health outcomes, the choice of EAM should provide a clear exposure contrast within the study population. Acquiring a practical understanding of the pesticide use practices is crucial to determine whether factors such as frequency or intensity of exposure have to be considered in planned analyses. Biomonitoring may be more beneficially applied intensively in a focussed exposure assessment analysis of a particular cohort, which can be used to determine the most relevant exposure factors within that cohort-specific context. Overall, improving pesticide exposure assessment in epidemiological studies requires a multi-disciplinary approach. A next step for the wider scientific community may be to consider the development of a decision tree to aid the selection of suitable EAMs. Such a decision tree would need to consider and be based on multiple parameters including, but not limited to, study type, health endpoint, socio-demographic context, farming system, pesticide used, and application methods.

Integrated multi-dimensional assessment of red mud recycling technologies: Insights from industrial waste treatment and life-cycle management

A large stock of red mud (RM), with certain resource values and potential environmental hazards, places higher requirements on the selection and optimization of recycling technology. A multi-dimensional performance assessment method combined with life cycle assessment was established to address this issue. In this study, eight typical RM recycling technologies were screened and sorted into three categories, 18 assessment indicators covering technological, resource, environmental, economic, and social dimensions were defined, and the integrated performance assessments of different categories and technologies were analyzed and compared. For the building material preparation category, the environmental dimension mainly focused on reducing the consumption of chemical reagents and sintering temperatures. In the material adsorption and modification category, improvements primarily targeted the technological and societal dimensions by increasing technological readiness and social feasibility. For the metal extraction category, the technology dimension focused on improving applicability and competitiveness and optimizing process parameters. Electricity, the primary energy source, significantly affected environmental performance and constrained industrial scalability. Thus, integrated performance assessment method for RM recycling technologies offers a methodology for researchers, provides a scientific basis and guidance for technology selection for industrialized applications, and promotes the optimal management of industrial solid waste for governments.

A novel class of non-Gaussian system performance assessment and controller parameter tuning methods

Traditional variance-based control performance assessment (CPA) and controller parameter tuning (CPT) methods tend to ignore non-Gaussian external disturbances. To address this limitation, this study proposes a novel class of CPA and CPT methods for non-Gaussian single-input single-output systems, denoted as data Gaussianization (inverse) transformation methods. The idea of quantile transformation is used to transform the non-Gaussian data with the goal of maximizing mutual information into virtual Gaussian data. In addition, optimal system data for the virtual loop are mapped back to the actual non-Gaussian system using quantile inverse transformation. Furthermore, a CARMA model-based recursive extended least square algorithm and a CARMA model-based least absolute deviation iterative algorithm are used to identify virtual Gaussian and non-Gaussian system process models, respectively, while implementing the CPT. Finally, a unified framework is proposed for the CPA and CPT of a non-Gaussian control system. The simulation results demonstrate that the proposed strategy can provide a consistent benchmark judgment criterion (threshold) for different non-Gaussian noises, and the tuned controller parameters have good performance.

Evacuation safety assessment in corridor-type high-rise building under fires

This study aims to elucidate the characteristics of personnel evacuation in corridor-type high-rise building under fires and to assess their evacuation performance. Utilizing Building EXODUS software, the study simulated the evacuation behavior of occupants, particularly focusing on the impact of corridor structures on the building's fire evacuation capabilities. A performance evaluation model was developed, which incorporates factors such as building conditions and natural environments. This model employs an enhanced Analytic Hierarchy Process (AHP) combined with Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) analysis for more accurate assessment. The findings reveal that traditional evacuation performance assessment methods, which often overlook the impacts of corridor location, time of day, and illumination conditions, are not adequately suited for the evaluation of evacuation performance in corridor-type high-rise building under fires. Under similar external conditions, the evacuation time for buildings with connecting corridors is significantly shorter than that for conventional high-rise buildings, showing reductions of 25.0 %–34.0 % at the same time of day and 26.0 %–37.8 % under the same illumination conditions. Additionally, nighttime evacuations are 29.4 % longer than those conducted during daytime. The implementation of a layered evacuation strategy reduces evacuation time by 9.7 % compared with free evacuation methods. The enhanced model proposed in this study provides a more effective framework for assessing the evacuation performance of corridor-type high-rise buildings.

Development of a theory-monitoring integrated structure joints assessment method of prefabricated underground stations

Prefabricated assembly structures have been extensively applied for the construction of low carbon and cost effective underground subway stations in China. Engineers faced significant challenges in dealing with the assessment of mechanical performance of structures joints within prefabricated underground station (PUS) structures during construction process. Manual assembly of large-scale prefabricated structures may lead to significant disturbance of structures joints, resulting in structures joints failure in construction process or even water leakage in maintenance of underground stations. To address these issues, this study proposed an integrated theory-monitoring method for joint performance assessment. The initial step involved the establishment of a fiber optical sensors (FOS) monitoring system for PUS joints. A joint performance assessment module was then developed utilizing the Joint Interfaces Contact Model (JICM) and was subsequently integrated into monitoring system, forming a joint performance assessment method, namely FOS-JICM (FOJI). A case study was finally conducted on a Shenzhen pipe jacking PUS to evaluate the effectiveness of FOJI. Main research findings of this study include (a) FOS monitoring system demonstrated excellent adaptability, accuracy, and real-time performance in practical applications; (b) FOS monitoring system effectively captured joint deformation and stress evolution throughout the entire construction process, providing insights into the impact of complex geological conditions and box culverts on joint behavior; (c) FOJI, with its integration of the JICM module, enabled safety assessment of joint performance during pipe jacking process; (d) FOJI successfully identified joint damage, offering valuable guidance for engineering restoration and protective measures. It facilitated prompt updates and adjustments based on the actual construction conditions, establishing a cycle mechanism for safety protection. These achievements not only establish a theoretical foundation for ensuring the construction safety of PUS joints but also present substantial practical application value.

Quasi-static tests of full-scale precast canopy beam-column joints with UHPC-filled grouted corrugated ducts connection

The traditional reinforced concrete canopy using cast-in-place (CIP) technology, is associated with problems such as long construction period, high environmental pollution, and low construction quality. Prefabricated assembly technology, due to its modern and highly industrialized characteristics, provides a promising solution to address the mentioned challenges. In this study, an innovative Ultra High-Performance concrete (UHPC)-filled grouted corrugated duct connection (UGCDC) approach was introduced for prefabricated canopy beam-column joints, considering the structural characteristics of the canopy. To evaluate the seismic behavior of canopy beam-column joints utilizing the UGCDC method, three comprehensive full-scale quasi-static experiments were conducted. Meanwhile, relevant seismic behavior indexes were extracted from the hysteresis curve, and the seismic performance of canopy joints was assessed by analyzing the effects of different research parameters on seismic behavior indicators. In addition, based on the OpenSees platform, a fiber finite element model (FEM) was established that incorporated the bond-slip behavior at the UGCDC joint. The research results indicated that the seismic behavior of canopy beam-column joints using UGCDC is basically consistent with that of CIP joints, and setting a shear key in UGCDC joints can improve ductility by 22.4 %. In terms of bearing capacity, there is not much difference among the three specimens, but in terms of initial stiffness, the specimen using UGCDC and shear key and the specimen using UGCDC have increased by 6.0 % and 9.6 % compared to CIP specimen, respectively. The developed FEM can predict the hysteresis characteristic of canopy joints using UGCDC. UGCDC method is a reliable connection form for canopy beam-column connection joint, which is suitable for medium to high intensity earthquake areas. Finally, a seismic performance assessment method of prefabricated canopy beam-column joints using UGCDC was proposed.

Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath

enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system. We now provide three diverse data sets, covering microbial biotransformation in different environments and under different experimental conditions. This also enabled developing a pathway prediction model that is applicable to a more diverse set of chemicals. In the prediction engine, we implemented a new evaluation tailored towards pathway prediction, which returns a more honest and holistic view on the performance. We also implemented a novel applicability domain algorithm, which allows the user to estimate how well the model will perform on their data. Finally, we improved the implementation to speed up the overall system and provide new functionality via a plugin system.Scientific contributionThe main scientific contributions are the development of a pathway prediction model applicable to diverse chemicals, a specialized evaluation method for holistic performance assessment, and a novel applicability domain algorithm for user-specific performance estimation. The introduction of two new data sets, and the creation of links to EC classes make enviPath a unique resource in microbial biotransformation research.

Evaluation of Environmental and Social Safeguards Performance Assessment Method using Corrective Action Plan Compliance Rate in Financing and Investment

This study evaluates the environmental and social safeguards (ESS) performance assessment method of PT Sarana Multi Infrastruktur (Persero) (PT SMI), focusing on the corrective action plan (CAP) compliance rate in financing and investment. Despite the utility of the compliance rate in monitoring adherence to financing agreements, it often inaccurately reflect actual environmental and social performance due to its inherent ambiguities. This research employed a qualitative method, employing observations of 146 active financing facilities and equity investment, surveys, and discussions with PT SMI’s ESS personnel. The study reveals that projects with higher CAP compliance rates may still have unresolved issues, while projects with fewer CAPs can be unfairly categorized as underperforming. To address these limitations, the study proposes a new, comprehensive framework that incorporates multiple variables to better capture ESS performance. This approach aligns with sustainable practices, enhances legitimacy, and meets stakeholder expectations more effectively. In addition, the proposed framework offers opportunities for incentives or disincentives based on ESS performance. Future research should focus on developing and validating this new framework to ensure accurate assessments of ESS performance in financing and investment activities.

EVALUATION OF TIME AND COST PERFORMANCE ON THE GX OFFICE & CO WORKING BALI PROJECT USING THE EARNED VALUE METHOD

In rapid construction developments, delays still occur frequently and have not been resolved, as experienced by the GX Office & Co Working Bali project. The project will be completed in 42 weeks, but in the 27th week, there is an indication of a delay of -4.31% from the initial plan. Earned Value Method (EVM) is a time and cost performance assessment method that can be used to develop strategies to minimize delays. This research aims to evaluate the time and cost performance of the GX Office & Co Working Bali project using the EVM method. A quantitative approach is used to collect and analyze project schedules, actual costs, and progress reports. EVM key indicators such as Planned Value (PV), Earned Value (EV), and Actual Cost (AC) are analyzed to determine Schedule Variance (SV), Cost Variance (CV), Schedule Performance Index (SPI), and Cost Performance Index (CPI). The results showed that the project experienced delays, especially from week 1 to week 14 and week 19 to week 27, with SPI values mostly below 1. However, the project showed increased efficiency in cost management with values CPI above one after week 14 to week 27, indicating that the actual costs incurred are lower than the value of the work completed. These findings highlight the need for corrective actions and more effective management strategies to address delays efficiently in terms of costs.

An integrated performance assessment method for SMEs fruit processing sustainability in Indonesia

An integrated performance assessment method for SMEs fruit processing sustainability in Indonesia

Penerapan Metode Kooperatif Tipe Learning Together Untuk Meningkatkan Hasil Belajar Seni Budaya di SMAN 8 Denpasar

After conducting initial observations at SMK Negeri 8 Denpasar, it was discovered that the students' learning outcomes in cultural arts subjects were relatively low. Therefore, the researcher decided to conduct further study using the PTK (Classroom Action Research) approach method. The aim of implementing the PTK method was to enhance students' understanding of the cultural arts subject through a cooperative learning model known as "learning together," with the goal of improving student learning outcomes. The PTK method involved 2 cycles, with each cycle consisting of 4 stages. The research subjects were the 35 students of class XII Mipa-4 at SMA Negeri 8 Denpasar. Data was collected using performance assessment and observation methods. The collected data was analyzed using a qualitative descriptive method, which aimed to examine the entire cultural arts learning process. Additionally, a qualitative method was applied to analyze the results of the assessment of student performance by comparing the average value of the completeness of learning outcomes. Following the analysis, it was observed that in cycle I, the highest and lowest scores for students of SMA Negeri 8 Denpasar class XII Mipa-4 were 85 and 60, respectively, with a class average score of 71. However, in cycle II, the highest and lowest scores increased to 95 and 80, and the class average score rose to 88. Furthermore, in cycle II, all students achieved scores above the minimum completeness level. This indicated a significant improvement in student scores from cycle I to cycle II.

Spatial correlation in building seismic performance for regional resilience assessment

Probabilistic seismic performance assessment method for buildings offers a valuable approach to simulate the broader regional impacts: economic losses, downtime, and casualties. A crucial aspect of this process entails accounting for the spatial correlation of building performances, aiming for an accurate estimation of the probability of extreme regional losses, such as the simultaneous collapse of buildings with similar structural characteristics. In this study, a correlation model based on a Gaussian random field is employed, and several key challenges associated with its application are addressed. In addition, efficiency of five different methods of selecting station records from the same earthquake scenario is compared. The minimum number of earthquake records necessary to achieve a stable correlation result is determined. Additionally, spatial correlations derived from different history earthquake events are compared. By addressing these critical issues, this research contributes to refining the reliability of probabilistic methods for regional resilience assessment.

Evaluating student performance assessment methods in Objective Structured Clinical Exam: perspectives and comparisons.

This study aims to evaluate how student performance and perspectives changed when the Objective Structured Clinical Exam (OSCE) assessment system was changed from a composite score to discipline-specific grading at the Harvard School of Dental Medicine. The retrospective study population consisted of all students (n=349) who completed three OSCEs (OSCE 1, 2, and 3) as part of the predoctoral program during the years 2014-2023. Data on the students' OSCE scores were obtained from the Office of Dental Education, and data on students' race/ethnicity and gender were obtained from their admissions data. The likelihood of a student failing the OSCE after the assessment system change significantly increased with an adjusted odds ratio of 20.12. After the change, the number of failed subjects per student decreased with an adjusted mean ratio of 0.48. Students perceived the OSCE as being less useful after the change. Independent of the grading change, OSCEs 1 and 2 were seen as more useful compared to OSCE 3, which is administered in the last year of the Doctor of Dental Medicine program. The discipline-specific nature of the new assessment system helps focus on specific areas of remediation, rather than blanket remediation used previously, in order to isolate the actual areas of deficiency and to focus remediation efforts so that students can align their learning needs appropriately.Therefore, although the actual number of fails identified increased for the course, the assessment change has allowed for more directed, actionable information to be gained from the OSCE to prepare students to work toward competency standards.

A BWM-TOPSIS Linear Programming Model for Evaluating the Performance of Health-Promoting Hospitals with McKinsey 7s Framework in Organizational Management

This research addresses the critical aspect of evaluating operational performance in health promotion hospitals, which play a vital role in providing medical services to local communities. The research proposes an integrated method for performance assessment, utilizing the Best-Worst Method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) linear programming model. Taking the case of health promotion hospitals in Maha Sarakham province, Thailand, and considering the McKinsey 7s framework's seven criteria, BWM is employed to determine the criteria weights. Subsequently, the TOPSIS linear programming model selects the ideal health promotion hospital based on these weights. The BWM analysis reveals criteria weights in the following order: system, staff, skill, style, structure, strategy, and shared value. The TOPSIS linear programming model identifies SH12 as the top-performing health promotion hospital with a closeness coefficient value of 0.8821. Additionally, a Spearman's rank correlation test validates this proposed method against the original TOPSIS approach, yielding a correlation value of 1.0. These findings provide valuable guidance for organizations, particularly in shaping strategic policies and resource allocation within medical service units, medical equipment, and personnel management in organizational settings. This study offers that the proposed method is simpler and will aid in the ongoing analysis of strengths and weaknesses in the improvement of organizations and development, helping organizations adapt to changes.

The Impact of the Implementation of the Government's Digital Direct Expenditure Program to Improve MSME Performance

This study aims to analyze and assess the impact of the procurement defense program on the performance of MSMEs in Gorontalo Province. The locus of research on MSME business actors who are members of the procurement defense program, especially through market place applications, both MbizMarketpalce and brliUMKM market place totaling 85 MSMEs with a sample of 10 MSMEs. The performance assessment method for MSMEs is used by Balance Scorecard analysis to analyze the financial and non-financial impacts of MSME businesses. The results showed that the Gorontalo Provincial government's procurement defense program had a relatively good impact on financial and non-financial performance. On average, there is an increase in operating profits, number of workers, production volume and marketing area. The procurement defense program is very helpful for MSME business actors in increasing public reputation and trust in their products and services so that business productivity and performance increase.

A spatiotemporal synergetic operating performance assessment based on reconstructed correlation matrix and dissimilarity analytics for plant-wide hot strip mill process

Operating performance assessment (OPA) of process industries plays a significant role in improving the product quality and pursuing the best economic benefits. With the continuous improvement of industrial intelligence, massive data has been collected. Variable time-delay issue is brought by the different spatial and temporal distributions of production units, which affects the actual causal relationship of collected data and assessment accuracy. Therefore, a spatiotemporal synergetic operating performance assessment (SSOPA) method is proposed in this paper. First, a reconstructed correlation matrix is carefully crafted in both time and space, leveraging the intricate multi-correlated spatiotemporal-delay (MCSD) parameters. To precisely quantify the multi-correlated relationships, a mixed gray relation analysis (MGRA) is employed. Subsequently, a predatory search-based genetic algorithm (PSGA) is utilized to meticulously search for the optimal MCSD parameters. Once these parameters are determined, an OPA model is formulated for each subsystem, drawing upon aligned process data and a distributed dissimilarity analysis (DISSIM). Finally, based on the subsystem-level OPA, a comprehensive assessment of the global operating performance level is conducted. The feasibility and effectiveness of the proposed method are verified by the plant-wide hot strip mill process (PHSMP).

Balance diagnostics in propensity score analysis following multiple imputation: A new method.

The combination of propensity score analysis and multiple imputation has been prominent in epidemiological research in recent years. However, studies on the evaluation of balance in this combination are limited. In this paper, we propose a new method for assessing balance in propensity score analysis following multiple imputation. A simulation study was conducted to evaluate the performance of balance assessment methods (Leyrat's, Leite's, and new method). Simulated scenarios varied regarding the presence of missing data in the control or treatment and control group, and the imputation model with/without outcome. Leyrat's method was more biased in all the studied scenarios. Leite's method and the combine method yielded balanced results with lower mean absolute difference, regardless of whether the outcome was included in the imputation model or not. Leyrat's method had a higher false positive ratio and Leite's and combine method had higher specificity and accuracy, especially when the outcome was not included in the imputation model. According to simulation results, most of time, Leyrat's method and Leite's method contradict with each other on appraising the balance. This discrepancy can be solved using new combine method.