Assessment Scheme Research Articles

Understanding an assessment approach in computer-mediated collaborative writing: Learner perceptions and interactions

While much research supports the benefits of computer-mediated collaborative writing (CW) in second language (L2) classrooms, the assessment of CW has received scant attention. This study proposed an assessment scheme considering both the products and processes when assessing online synchronous CW, and explored its effects on learners’ interactions and perceptions of the process-and-product-based assessment approach through qualitative analyses. Through analyzing 21 dyads’ online pair talk and revision histories in CW tasks, post-task reflections, and interviews, this study found that assessment approach impacted patterns of collaboration, as well as the quantity and quality of peer interaction. Also, learners reported multiple advantages of the process-and-product-based assessment approach in computer-mediated CW, including increasing fairness, promoting better performance, and facilitating effective collaboration. Further, the process-and-product-based CW assessment approach raised learners’ awareness of the value of the collaboration process, motivated students to be critical collaborators, and promoted regulated learning. Nevertheless, students expressed concerns that this assessment approach might bring pressure and disrupt idea negotiation. The findings can further our understanding of the role that assessment plays in computer-mediated CW tasks and shed new light on possible ways of implementing CW assessment practices that may facilitate learning and positive learner perceptions in L2 writing classrooms.

A hybrid hydrologic modelling framework with data-driven and conceptual reservoir operation schemes for reservoir impact assessment and predictions

Reservoirs have been built worldwide to address the water-related issues. To fully understand their potential impacts on the hydrologic regime, explicitly parameterizing reservoir operation in hydrologic models is often required. In this study, two data-driven reservoir operation schemes based on extreme gradient boosting (XGBoost) and artificial neural network (ANN) are respectively developed to predict the reservoir release and storage in hydrologic models for reservoirs with historic in-situ inflow, storage, release data. Then, a hybrid modelling framework is proposed by coupling a high-resolution (3 km) hydrologic model with (1) the developed data-driven reservoir operation schemes and (2) a calibration-free conceptual reservoir operation scheme designed for data-scarce reservoirs. This allows quantitative assessment of the cumulative impacts of dam operation on the hydrologic regime under different reservoir data availability. The framework is applied to the Upper Yangtze River Basin (UYRB) in China that is one of the most regulated river basins across the country due to extensive reservoir construction. Results indicate that both data-driven reservoir operation schemes can well reconstruct the reservoir releases and storage in the UYRB (daily NSE of ∼ 0.9), and the XGBoost performs slightly better than ANN. By coupling reservoir operation, the model shows a remarkably improved performance in reconstructing the daily streamflow of the basin. The major reservoirs in the UYRB can redistribute excessive water in the wet season to the dry season and attenuate the high and low flows, leading to enhanced water security along the river. Our approach provides a practical framework for reservoir impact assessment and predictions.

Socio-ecological gap analysis to forecast species range contractions for conservation

Conservation requires both a needs assessment and prioritization scheme for planning and implementation. Range maps are critical for understanding and conserving biodiversity, but current range maps often omit content, negating important metrics of variation in populations and places. Here, we integrate a myriad of conditions that are spatially explicit across distributions of carnivores to identify gaps in capacity necessary for their conservation. Expanding on traditional gap analyses that focus almost exclusively on quantifying discordance in protected area coverage across a species' range, our work aggregates threat layers (e.g., drought, human pressures) with resources layers (e.g., protected areas, cultural diversity) to identify gaps in available conservation capacity (ACC) across ranges for 91 African carnivores. Our model indicated that all species have some portion of their range at risk of contraction, with an average of 15 percentage range loss. We found that the ACC differed based on body size and taxonomy. Results deviated from current perceptions of extinction risks for species with an International Union for Conservation of Nature (IUCN) threat status of Least Concern and yielded insights for species categorized as Data Deficient. Our socio-ecological gap analysis presents a geospatial approach to inform decision-making and resource allocation in conservation. Ultimately, our work advances forecasting dynamics of species' ranges that are increasingly vital in an era of great socio-ecological change to mitigate human-wildlife conflict and promote inclusive carnivore conservation across geographies.

An improved carbon emission calculation framework of precast concrete column in construction stage based on LCA

ABSTRACT The abundant carbon emissions generated by the construction industry have gradually become a significant problem. Rather than employing traditional construction methods, the industrialized building system adopts the efficient on-site assembly of prefabricated components, which provides a new solution for reducing industry carbon emissions. Currently, great differences exist in the life cycle assessment schemes for prefabricated buildings and components, which requires considering many different factors. The accuracy and applicability of the results must therefore be improved. In this study, an improved life cycle calculation framework is proposed to assess the carbon emissions of prefabricated concrete columns in the construction stage. Based on the commonly used calculation methods of carbon emission factors, the framework uses a new calculation method with more considerations for vehicle transportation and uses the consumer lifestyle method to estimate construction workers’ carbon emissions. The framework also fully considers the loss of components in the transportation process. The calculated results are compared with the traditional carbon emission factor calculation methods. Overall, the results for the framework are relatively significant because they more comprehensively consider various factors when compared to results using the traditional calculation methods.

A secure and dependable trust assessment (SDTS) scheme for industrial communication networks

Due to tamper-resistant sensor nodes and wireless media, Industrial Wireless Sensor Networks (WSNs) are susceptible to various security threats that severely affect industrial/business applications. The survival of sensor networks is highly dependent on the flourishing collaboration of sensor nodes. Trust management schemes seem to be realistic and promising techniques to improve security as well as cooperation (dependability) among sensor nodes by estimating the trust level (score) of individual sensor nodes. This research paper presents a well-organized and motivating secure, dependable trust assessment (SDTS) scheme for industrial WSNs to cope with unexpected behavior such as an on–off attack, bad-mouthing attack, garnished attack, etc., by employing robust trust evaluation components based on success ratio and node misbehaviour. SDTS incorporates an interesting trust evaluation function in which the trust range can be adjusted in accordance with the application requirement. SDTS include direct communication trust, indirect communication trust, data trust, and misbehavior-based trust to defend the multiple internal attacks. SDTS works according to the behavior of nodes, i.e., whether the sensor nodes are interacting frequently or not. Moreover, abnormal attenuation and dynamic slide lengths are incorporated in the proposed model (SDTS) to deal with various natural calamities and internal attacks. SDTS is compared against three recent state-of-the-art methods and found efficient in terms of ease of trust assessment, false-positive rate (2.5%), false-negative rate (2%), attack detection rate (90%), detection accuracy (91%), average energy consumption (0.40 J), and throughput (108 Kbps) under the load of 500 sensor nodes with 50% malicious nodes. Investigational results exhibit the potency of the proposed scheme.

Security Study on Freestanding Minigrid with Multiple Rotary Energy Sources

Traditional grid has been extensively studied for system security. For freestanding renewable energy-based minigrid, a three-source stand-alone minigrid is in this study examined for system security under large disturbances. By real-time simulation, rotor responses of the generators and voltage characteristics of the buses are assessed at sudden load change and under fault condition. Post-perturbation behaviour of the system shows synchronism is not compromised by any of the generators and the bus voltage profiles remains within their pre-perturbation statutory limits. This implies that a number of rotating machine-based energy mini-sources could be interconnected into a freestanding minigrid without compromising the stability of the system. The assessment could find use in predictive and corrective compensation for stability issues in mini integrated power systems and serve as simple generic investigative approach that could be integrated into Minigrids Remedial Action Scheme or Minigrids Energy Management System for dynamic security assessment of multi-machine island minigrids.

Application of the global neutron monitor network for assessment of spectra and anisotropy and the related terrestrial effects of strong SEPs

Studies of the characteristic of strong solar energetic particles (SEPs), that is events that can be registered by ground-based instruments such as neutron monitors, allow one to understand their acceleration and propagation in interplanetary space and gives the necessary basis to quantify the related cosmic-ray-induced terrestrial effects. After solar eruptive processes, such as solar flares and/or coronal mass ejections, solar ions are accelerated to the high-energy range. In most cases, the energy of the accelerated solar ions reaches several tens of MeV/n, yet occasionally it exceeds 100 MeV/n or even reaches the GeV/n range. In the latter case, the energy of SEPs is enough, so that they induce an atmospheric particle shower, whose secondary particles reach the ground, eventually registered by ground-based detectors, specifically neutron monitors. This particular class of events is known as ground-level enhancements (GLEs). Here we present a full-chain scheme for assessment of spectra and anisotropy and the related terrestrial effects of GLE causing SEPs. We discuss the application of a method for analysis of GLEs using neutron monitor data and the employment of the derived spectra as a basis to quantify cosmic-ray-induced terrestrial effects during GLEs, specifically atmospheric ionization and exposure to secondary radiation (radiation dose) at cruising aviation altitudes. We present an example study of two GLEs, namely their SEP energy/rigidity spectra derived using records from the global NM network and models for quantification of the atmospheric ionization and exposure to radiation at flight altitudes (ambient dose) during the considered events.

한국형 총식이조사 및 UV/태양광 조사 버섯에서의 비타민 D 분석

This study was conducted to evaluate vitamin D intake of Koreans in a total diet study (TDS) and to determine the effect of irradiation on vitamin D synthesis in mushrooms. For analysis, sample were saponified and extracted with hexane, and vitamin D was quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the validation results, the recovery of the National Institute of Standards and Technology (NIST) standard reference sample (SRM) 1849a was 96.7% and the z-score of −1.6 was obtained by the Food Analysis Performance Assessment Scheme (FAPAS) proficiency test (PT) 21115. Vitamin D2 was not detected in any samples, and the highest level of vitamin D3 was detected in mackerel and anchovies ranging from 24.2 to 120.2 μg/kg. The mean daily intake of vitamin D was 0.99 μg/day, as estimated from the vitamin D contents of the analyzed foods and their corresponding intake. The adequate intake (AI) of vitamin D based on the Dietary reference intakes for Koreans provided by the Ministry of Health and Welfare is 5-15 μg/day for Koreans aged 6 to 75 years. Compared with this AI, vitamin D intake of Koreans estimated in this study was inadequate. For that, the increased vitamin D content in ultraviolet (UV)/sun light irradiated mushrooms warrants further research to increase vitamin D intake of Koreans through diet.

Analysis of Assessment Design in English Language Curriculum 2006 Of Pakistan: A Qualitative Study

Assessment is an essential component of the curriculum. The curriculum is a policy document that guides assessment mechanisms before, during, and after instruction. The curriculum envisioned assessment in standards, benchmarks, and students' learning outcomes (SLOs) by providing action words. assessment is an integral part of the learning process. Language skill development depends on the quality of assessment design and practice during and after instruction. This research study critically analyzes the language skills assessment design intended in Pakistan's language curriculum, 2006. The study aimed to explore the assessment design intended in standards, benchmarks, and students’ learning outcomes SLOs, in the language curriculum of Pakistan 2006 of secondary classes. The study's objective was to investigate the language assessment scheme of LNC, 2006, as well as understand the extent of the assess ment design of the national curriculum, 2006. It is also aimed at to what extent this design supports language assessment and responds to language assessment theories. The document analysis model of "Bowen (2009)" was adopted for this study. The study findings show that the assessment design intended in LNC, 2006 of Pakistan could be more supportive in developing language skills. The level of action verbs used for standards, benchmarks, and SLOs, is very low, almost from Bloom's Taxonomy first three-stage of the cognitive domain. Listening and speaking skills are almost neglected in assessment design. The findings of this study will inform policy developers and curriculum workers to improve the language assessment design. Additionally, the results will guide teachers in understanding language assessment design and implementation accordingly.

Examination of discordant external quality assessment scheme results

An external quality assessment scheme (EQAS) is a form of external quality assurance that provides evaluation of laboratory performance based on the analysis of a collection of samples supplied by an external agency. EQAS performance has been shown to reflect the quality of patient specimen testing in a clinical laboratory.

Quality indicators in laboratory medicine: state-of-the-art, quality specifications and future strategies.

In the last few decades, quality in laboratory medicine has evolved in concert with the transformation and the changes (technological, scientific and organizational) in this sector. Laboratory professionals have faced great challenges, at times being overwhelmed, yetalso involved in this progress. Worldwide, laboratory professionals and scientific societies involved in laboratory medicine have raised awareness concerning the need to identify new quality assurance tools that are effective in reducing the error rate and enhancing patient safety, in addition to Internal Quality Control (IQC) procedures and the participation in the External Quality Assessment Schemes (EQAS). The use of Quality Indicators (QIs), specifically designed for laboratory medicine are effective inassessing and monitoring all critical events occurring inthe different phases of Total Testing Process (TTP), in particular, in the extra-analytical phases. The Model ofQuality Indicators (MQI), proposed by the Working Group "Laboratory Errors and Patient Safety" (WG-LEPS) of the International Federation of Clinical Chemistry andLaboratory Medicine (IFCC) and validated by experts in consensus conferences, is an important window of opportunity for the medical laboratory to demonstrate the use of an effective quality assurance tool fit for this purpose. Aim of this paper is to provide an update of the state-of-the-art concerning the most used QIs data collected in 2021 and the Quality Specifications (QSs) proposed for their evaluation. Moreover, a strategy for the future is proposed in order to improve the MQI and encourage its use in medical laboratories throughout the world.

Methodological scheme of qualimetric assessment of recreational clusters


 
 
 The article deals with the application of qualimetric methods for assessing recreational and tourist potential on the example of an ecotourism cluster developed for natural and geographical and socio-economic conditions and resources of the Ukrainian Black Sea region. The properties of recreational and tourist potential can have different nature, different definitions, and be qualitative-descriptive, verbal, or quantitative (numerical). In qualimetric developments, properties should be comparable in the form of representation and magnitude of evaluation scales. The aim of the study is to develop a methodology for qualimetric assessment of recreational clusters. The theoretical and methodological basis is the fundamental principles and developments of recreational geography, tourism studies and qualimetry, as well as the author’s own developments. In the process of writing, general geographical methods were used, such as descriptive, comparative geographical, and qualimetric assessment methods. Characteristics and properties presented in verbal form can be shown as structural combinations and compounds of simpler indicators. Factors that form the recreational and tourist potential have different weights (significance), which requires an appropriate assessment. The overall assessment of recreational and tourist potential is a weighted average value of all its components, taking into account their weight. The available absolute natural indicators of conditions and resources of recreational and tourist potential are also transformed into qualimetric estimates. The general methodological scheme for assessing recreational clusters, specified according to the conditions and resources of ecotourism of the Black Sea region is represented by seven stages – from structuring a recreational cluster according to its components and levels of hierarchical organization, calculating indicators of the weight of properties and calculating criteria for prop- erties that form the corresponding quality, calculating qualimetric estimates for all primary units of recreational and tourist potential; a meaningful interpretation of the assessment of the recreational and tourist potential of a recreational cluster based on the criteria of properties and scales of the corresponding features and characteristics, as well as indicators of the weight of properties in the formation of recreational and tourist potential. The developed scheme should be considered as a methodological approach for the practical application of qualimetric assessments of recreational and tourist potential in recreational geography and tourism studies.
 
 

Trust assessment for mobile crowdsensing via device fingerprinting

Mobile crowdsensing leverages the ubiquitous sensors of smart devices to facilitate various sensing applications. Users who participate in contributing data usually get rewards from the task requester, while there is a potential risk that someone would preempt the task and provide a forged sensing report for seeking revenue with minimal effort. Thus, trust assessment is essential to identify those irregular sensing reports. The existing methods mainly consider users’ reputations and estimate the trustworthiness upon the difference from the aggregated result. However, they still face a severe problem when a majority of reports are invalid or low-quality caused by the repeated submission, e.g., a user can switch multiple accounts on a single device to repeatedly submit forged reports. To tackle this problem, we design a trust assessment scheme with an enhanced device fingerprinting algorithm. Briefly, to reduce the influence of the repeated sensing reports, we first compute their unique fingerprints derived from the intrinsic characteristics of sensors and assign an initial trust weight for each report. Then, to improve the accuracy of the assessment, we further compute the similarity of the reports to obtain their final trust values. Extensive evaluations are conducted to justify the effectiveness of our proposed design.

Application of Probabilistic Seismic Hazard Assessment to Understand the Earthquake Hazard in Attock City, Pakistan: A Step towards Linking Hazards and Sustainability

Within the last three decades, twelve major earthquakes (Mw > 6.0) have jolted Pakistan and contributed to a heavy death toll and an economic loss of billions of dollars, which is immense for any underdeveloped country. Despite the generalized description of seismic hazards in various regions of Pakistan, densely populated cities still require a detailed and integrated vulnerability analysis to overcome the impact of a significant earthquake. This study aims to integrate seismic hazard assessment schemes to understand the vulnerability of Attock city against an earthquake. It initially evaluates the threat from an earthquake due to tectonic activity in the region, splits the region (about 200 km radius) into six seismic zones and uses area source parameters. The ground motion prediction equations compatible with the study area’s seismotectonic environment are also used in this study. Peak horizontal ground acceleration (PGA) and 5% damped spectral acceleration are critical features of ground motions. The site classification is carried within Attock city, indicating the presence of SB (foundation condition with Vs30 = 760 m/s), SC (foundation condition with Vs30 = 400 m/s) and SD (foundation condition with Vs30 = 300 m/s). The peak ground accelerations for a return period of 475 years at the SB, SC and SD sites are estimated as 0.23 g, 0.28 g and 0.30 g, respectively. Uniform hazard spectra are obtained for each site classification at three return periods (475, 975 and 2475 years). Another possible threat can be the local site conditions of the study area, as Attock city exists on the unlithified sediments of upper Pleistocene to Recent alluvial deposits. That is why microtremor recordings are conducted at 20 sites within Attock city to understand the fundamental frequency (f0), horizontal to vertical spectral amplitude (A0) and Kg parameter, a seismic vulnerability index. The values of f0 are found between 0.6 and 9 Hz and A0 is observed between 2.1 and 5 Hz, whereas the Kg is estimated between 0.24 and 20 Hz. Despite evidence of the seismic vulnerability of Attock city, the current building designs and infrastructure development are not synchronized with the uniform hazard response spectra and the soil amplification, thus enhancing the exposure of the study area to disaster during a major earthquake. This study will be instrumental in pre-disaster mitigation strategies for urban planners and policymakers.

Graph Convolutional Network-Based Interpretable Machine Learning Scheme in Smart Grids

Smart grid is a typical application of industrial cyber-physical systems (ICPS) in the electric power industry. Due to the exposure to different kinds of uncertainties and unpredictable faults, how to reliably assess the short-term voltage stability (SVS) of smart grids to prevent the occurrence of large-scale blackouts is still of primary concern. To tackle this challenging problem, this article develops a novel machine learning scheme to achieve accurate and interpretable online SVS assessment in two steps. First, it utilizes time-series shapelet transform to extract key dynamics and convert the postfault time series into flat features. Second, it designs a graph convolutional network (GCN) to incorporate these features with topology information for SVS assessment. The GCN explores the spatial-temporal dynamics of power system via graph convolution and introduces a system layer to derive the final assessment result. Compared with conventional methods, this novel scheme makes full use of the spatial-temporal information in SVS dynamics, resulting in higher assessment accuracy and stronger adaptability. Besides, it is capable of discovering certain valuable underlying rules and patterns related to SVS. Test results on the IEEE 39-bus system and real-world Guangdong Power Grid in South China verify the effectiveness of the proposed scheme. Note to Practitioners—To achieve accurate and interpretable online short-term voltage stability (SVS) assessment in the challenging environment of smart grids, this article develops a novel machine learning scheme with full consideration of the spatial-temporal information in SVS dynamics. First, it utilizes the time series shapelet transform to convert the postfault time series into flat features. Second, it designs a graph convolutional network (GCN) to incorporate these features with topology information. The full consideration of spatial-temporal information in SVS dynamics can improve the assessment accuracy, and the integration of topology in the scheme can promote its adaptability to topology changes. Apart from the decent performances under changeable environments, the proposed scheme can provide certain valuable underlying rules and patterns related to SVS. Therefore, not only the proposed scheme for SVS assessment can work well in the practical challenging environment of smart grids, but also it helps the dispatchers in smart grids better understand and trust the proposed SVS assessment scheme.

Clinical Practice Guidelines for Management of Suicidal Behaviour.

Clinical Practice Guidelines for Management of Suicidal Behaviour.

Converting to an international unit system improves harmonization of results for SARS-CoV-2 quantification: Results from multiple external quality assessments

The detection of SARS-CoV-2 vRNA in clinical samples has relied almost exclusively on RT-qPCR as the gold standard test. Published results from various external quality assessments ("ring trials") worldwide have shown that there is still a large variability in results reported for the same samples. As reference standards of SARS-CoV-2 RNA are available, we tested whether using standard curves to convert Ct values into copies/mL (cp/mL) improved harmonization. Nine laboratories using 23 test systems (15 of which were unique) prepared standard dilution curves to convert Ct values of 13 SARS-CoV-2 positive samples to cp/mL (hereafter IU/mL). The samples were provided in three rounds of a virus genome detection external quality assessment (EQA) scheme. We tested the precision and accuracy of results reported in IU/mL, and attempted to identify the sources of variability. Reporting results as IU/mL improved the precision of the estimated concentrations of all samples compared to reporting Ct values, although some inaccuracy remained. Variance analysis showed that nearly all variability in data was explained by individual test systems within individual laboratories. When controlling for this effect, there was no significant difference between all other factors tested (test systems, EQA rounds, sample material). Converting results to copies/mL improved precision across laboratory test systems. However, it seems the results are still very specific to test systems within laboratories. Further efforts could be made to improve accuracy and achieve full harmonization across diagnostic laboratories.

A biological integrity framework for describing animal welfare and wellbeing

Ethical treatment of animals is the keystone of livestock production. Assessment of welfare is integral to assurance that animals experience a good life. Underpinning assurance are concepts of what constitutes good welfare, a good life and wellbeing. This review examines the concepts of welfare and wellbeing and the frameworks that have been developed for describing their scope. Historically, the tripartite model of welfare (feeling well, functioning well, leading a natural life) has been translated into the Five Freedoms (FF), Five Domains (FD), Good Life (GL), Welfare through Competence (WtC) and OIE World Organisation for Animal Health Welfare Principles frameworks. These frameworks provide scaffolds for numerous welfare assessment schemes. However, the three-part model of wellbeing (eudaimonia, hedonia, social interaction) lacks an explicit assessment framework, although FD, GL and WtC implicitly address aspects of wellbeing. Whereas positive affective (hedonic) experiences are considered to constitute positive welfare, positive aspects of eudaimonic function and social interaction are considered to be aspects of wellbeing above and beyond any indirect contribution they make to positive affective experiences (i.e. positive welfare). In this view, positive health is more than the absence of ill-health and positive social interactions are more than freedom from social isolation. New phenotypes in farm animals identified through analysis of sensor data are providing new perspectives on the functional integrity of biological processes that align well with concepts of wellbeing. These analyses draw on methods in resilience theory to examine stability in complex dynamic systems, specifically, uniformity of trajectories, periodicity of biorhythms and complexity of networks. A framework is proposed that loosely partitions FF, FD, GL and WtC into inputs, opportunities, and outcomes. The framework positions the outcome of biological integrity within the context of input constraints that can generate harms and deficiencies, and environmental opportunities that can foster acquisition of competencies and flourishing. It combines the eudaimonic, hedonic and social aspects of wellbeing within the tripartite terminology of welfare. It is hoped that the framework can help orientate new descriptions of biological function in farm animals derived from sensor data within the broader literature on welfare and wellbeing.

Constructing symbolic capital to coordinate teaching-focused university-industry collaborations in China: a documentary, videological and empirical analysis

This paper explores how the Chinese government constructs symbolic capital and uses its converted forms to coordinate the relationship between the industry and the higher education sector for implementing teaching-focused university-industry collaboration (UIC). Through videological analysis of thirteen video segments, documentary analysis of three important state policy documents and a special website, and semi-structured interviews with six enterprise representatives and three university representatives, the study reveals that the forms of explicit symbolic capital include linking teaching-focused UIC with national development and rejuvenation, endowing participants with high accolades, and selecting exemplary cases for special recognition. The implicit symbolic capital includes putting teaching-focused UIC within the framework of formal university assessment schemes and untapping participants’ economic capital based upon expanded potential markets. Capital conversion and mobility have led to an education-oriented ecosystem where various stakeholders share a common vision for quality advancement in higher education.

Six Sigma metrics as an indicator for Randox International Quality Assessment Scheme in clinical biochemistry laboratory

Context: Six Sigma methodology represents an evolution in quality assessment and management that has been implemented widely in industry and health sector since the mid-1980s. It consists of five steps: define, measure, analyze, improve, and control (DMAIC). Randox International Quality Assessment Scheme (RIQAS) program Target Score (TS) is a performance indicator, and Sigma metrics is considered as a gold standard for overall performance. Aim: The aim of this study is to present the TS and Sigma metrics observed in clinical chemistry laboratory in SSK Hospital associated with Lady Hardinge Medical College to evaluate the analytical performance of T3, T4, and thyroid-stimulating hormone (TSH) parameters. The study period is from June to August 2022. Materials and Methods: The Sigma metrics for the various analytes was calculated by the following equation: Σ = TEa − bias/CV (TEa—total allowable error, CV—coefficient of variation). Acceptable performance criteria: standard deviation index (SDI) <2; TS >50; the closer a value is to 120, the better the performance, <40 is unacceptable; and %deviation should be less than the defined acceptable limits which is unique to each analyte, the closer the value is to zero, the better is the performance. Results: Our RIQAS results lie in acceptable range except for T3 in the month of August in which TS was unacceptable. Our laboratory Sigma metrics were below three sigmas. The findings of our exercise emphasize the need for a detailed evaluation, and we promote the use of Sigma metrics in quality assurance in the best interest of the patient. Conclusion: Quality check strategies were applied according to the TS and sigma values.