Assessment Scheme Research Articles

Formation and Evaluation of Complete Blood Count Proficiency Testing Program.

Introduction: The haematology external quality assessment (EQA) scheme is the most commonly used service of quality assurance. The provision of complete blood count (CBC) materials must meet the quality requirements at a reasonable cost. These requirements are the most significant challenges for EQA organisers in Vietnam. This study’s objective was to evaluate the homogeneity, long-term stability, and peer-group performance of 10-parameter stabilised CBC EQA samples. Methods: The CBC EQA material was prepared using the following steps, including (1) adjusting levels of stabilised erythrocyte, leukocyte, and platelet samples, (2) mixing those cells into batches at three levels, and (3) dispensing and storing them at 2–6 °C. A set of 10 and 30 specimens were randomly chosen from each batch to study the homogeneity and long-term stability following ISO 13528:2015. In total, 166 samples at two levels were randomly distributed to 40 participants, which reported 83 automatic cell counters among six automated analyser models in the CBC EQA program. Results: The 10-parameter stabilised CBC EQA materials at three levels became homogeneous and stable in 12 weeks when preserved at 2–6 °C. Meanwhile, for five parameters (RBC, Hb, MCH, MCV, and MPV), this process was prolonged for up to 16 weeks in stock condition. In terms of peer-group performance, the CV (%) values increased at the low concentration for almost all parameters, especially in platelet counts. Conclusions: The stabilised CBC EQA samples prepared using the partial fixation method with aldehyde and gutaraldehyde in this study meet the ISO 13528:2015 requirements of homogeneity and long-term stability for the CBC EQA scheme. Analytical performance evaluation should categorise participant methods into peer groups.

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement.

Knee osteoarthritis is a degenerative disease, which greatly affects the daily life of patients. Total knee replacement (TKR) is the most common method to treat knee joint disorders and relieve knee pain. Postoperative rehabilitation exercise is the key to restore knee joint function. However, there is a lack of a portable equipment for monitoring knee joint activity and a systematic assessment scheme. We have developed a portable rehabilitation monitoring and evaluation system based on the wearable inertial unit to estimate the knee range of motion (ROM). Ten TKR patients and ten healthy adults are recruited for the experiment, then the system performance is verified by professional rehabilitation equipment Baltimore Therapeutic Equipment (BTE) Primus RS. The average absolute difference between the knee ROM and BTE Primus RS of healthy subjects and patients ranges from 0.16° to 4.94°. In addition, the knee ROM of flexion-extension and gait activity between healthy subjects and patients showed significant differences. The proposed system is reliable and effective in monitoring and evaluating the rehabilitation progress of patients. The system proposed in this work is expected to be used for long-term effective supervision of patients in clinical and dwelling environments.

A fuzzy logic based assessment algorithm for developing a warehouse assessment scheme

A new integrated assessment algorithm is proposed for a warehouse assessment scheme. This new algorithm integrates three paradigms, namely, Grey Relational Analysis (GRA), Data Envelopment Analysis (DEA), and an Interval Type-2 Fuzzy Logic System (IT2FLS). Based on the defined criteria and the various warehouses assessed according to these criteria, the GRA is employed to determine the grey relational grade. The DEA is, then, utilized to estimate the warehouse efficiency scores. Finally, the IT2FLS is developed to map the efficiency scores of the warehouses to the assessed values of the defined criteria. The developed IT2FLS can be used to assess new warehouses without re-performing the calculations of the GRA and the DEA. Validated on several warehouses, the integrated assessment algorithm can assess warehouses successfully, and can tackle the uncertainties during the assessment process. In addition to comparing the warehouses with the best practice, it can also provide managers with a linguistic understanding of the effect of the defined criteria on the warehouse performance.

A deep learning scheme for transient stability assessment in power system with a hierarchical dynamic graph pooling method

To handle more challenging operation security problems in today’s power system, pre-fault transient stability assessment (TSA) is essentially required to promote the awareness of the system stability risks. Fast and analyzable data-driven methods draw much attention in intelligent TSA schemes, but most of them either lack generalization to various operation topologies and fault locations, or fail to operate on developing systems with changeable scales. Some schemes based on graph convolutional networks (GCNs) enjoy promising topology learning but suffer from poor scale reduction, which affects the robustness against system-scale changes. With this in mind, we propose a novel Attention-based Hierarchical Dynamic grAph Pooling nEtwork (AH-DAPE), where a graph-based hierarchical pooling strategy is initiated for effective scale reduction in power systems. The expressive power of hierarchical pooling is enhanced by a spectral unsupervised loss related to power system simplification, while the temporal learning across dynamic coarsened graphs are enabled by integration of inter-graph convolution and mean/maximum operations. Test results on small IEEE 39 Bus system and large IEEE 300 Bus system validate our scheme’s superiority over existing TSA models and robustness against various operation scenarios, especially when applied to new system scales.

The Process of Establishing and Managing a Laboratory Diagnostic Network in the COVID-19 Pandemic in Iran

The COVID-19 pandemic caused by the newly emerged coronavirus was first detected in China in December 2019 and rapidly spread worldwide. The rapid spread of the disease urged all countries involved, in accordance with their capacities, take the necessary measures to diagnose and manage the disease. The first patient was diagnosed with COVID-19 in Iran in February 2020. Considering the significant role of the laboratory services in detection and management of the disease, planning and programming to provide access to these services was considered as a top priority for healthcare system in Iran. Adopting all existing laboratory capacities and providing necessary infrastructures for expanding COVID-19 laboratory diagnostics, resulted in the establishment of a nationwide network of COVID-19 molecular diagnostic laboratories within the shortest possible time. In addition to expanding the capacity of laboratory services, improving the laboratory network’s performance have been taken into serious consideration. Despite the strict sanctions, the COVID-19 molecular diagnostic laboratories scaled up to more than 430 laboratories currently (September 2021), mostly are operating in the private sector. With considerable efforts, COVID-19 molecular laboratory network was established to provide nationwide diagnostic services. Considering the capacity for the SARS-CoV-2 Rapid Antigen test, we can now perform more than 100,000 COVID-19 diagnostic tests per day. However, due to the ongoing pandemic and in accordance with the requirements of the health system, it is necessary to plan and carry out more COVID-19 diagnostic tests. This study aimed to introduce the process of establishing the COVID-19 laboratory diagnostic network to manage the COVID-19 pandemic in Iran.

Rapid damage assessment of 1/3 scaled-down two-story reinforced concrete school building models

ABSTRACT This study presents a damage assessment scheme for seismically excited torsion-coupled nonlinear buildings based on the normalized relative displacement vibration shape (NRDVS). In order to investigate the applicability of the proposed NRDVS, the relative displacements are obtained from a real-time structural response integrator (RTSRI) by integrating the relative accelerations simulated from multiple-degree-of-freedom nonlinear models. As a result, the normalized inter-story drift ratio (NIDR) calculated by differencing the normalized displacements of the two successive floors of NRDVS and dividing by the story height can reveal the damaged floors as well as the location of damaged building members. Furthermore, the proposed damage assessment scheme is validated by observing the experimental measurements of shaking table tests of three 1/3 scaled-down two-story reinforced concrete school building models conducted at the National Center for Research on Earthquake Engineering (NCREE), Taipei, Taiwan.

On Teaching Malware Analysis on Latest Windows

Microsoft Windows operating systems are the most popular desktop operating systems. 83% of malware attacks target Windows. Windows 10 has a market share of 78.45% out of all Windows versions on the market. However, we find security related courses are often taught on Linux or run on older Windows versions. In this paper, we present our practice of teaching malware analysis on the latest Windows (10). We are among the first using the latest Windows (10) for teaching malware analysis. We design the labs and assignments on the pre-configured Windows 10 VM supplemented by the Kali VM. A virtual Cyber Range is created for students to access the two VMs over a cloud. We present our curriculum and learning assessment scheme. Our practice has been validated through surveys on both face-to-face and online classes.

Determination of Sigma metric based on various TEa sources for CBC parameters: the need for Sigma metrics harmonization

Abstract Objectives The application of Sigma metrics can be used for assessing the performance of diagnostic laboratories. Clinical laboratories are confronted with the trouble of having to select the best and suitable quality specifications that are required for quality planning. In this regard, our study aims at evaluating the performance of Sysmex XN-1000 hematology analyzer by using Sigma metrics based on different total allowable error (TEa) source and to determine the effects of these variations in Sigma metric evaluation. Methods Five TEa requirements were selected to calculate Sigma metrics of 11 complete blood count (CBC) parameters. Coefficient of variation (CV) and bias data were supplied from internal quality control (IQC) and External Quality Assessment Scheme (EQAS) respectively. Results According to TEa based on desirable biological variation (BV) database specifications, the highest Sigma value was achieved by white blood cell count for each level, the lowest value was achieved by Red Cell Distribution Width-Standard Deviation parameter. The Sigma calculation based on Spanish TEa showed that seven CBC parameter achieved Sigma value ≥3. Conclusions According to the results of the study, it can be concluded that Sigma scores have a significant fluctuation based on which TEa sources are utilized and the need for Sigma metrics harmonization and standardization is highlighted. Additionally, low Sigma values of most CBC parameters are resulted in the conclusion that the use of performance goals depending on BV data is difficult for common clinical use. Therefore, clear standardized criteria are quite necessary for the selection of TEa goal by laboratories.

Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator.

Procalcitonin (PCT) is a widely used biomarker for rapid sepsis diagnosis and antibiotic stewardship. Variability of results in commercial assays has highlighted the need for standardization of PCT measurements. An antibody-free candidate reference measurement procedure (RMP) based on the isotope dilution mass spectrometry and protein calibration approach was developed and validated to quantify PCT in human serum. The method allows quantification of PCT from 0.25 to 13.74 μg/L (R > 0.998) with extension up to 132 μg/L after dilution of samples with PCT concentration above 13.74 μg/L. Intraday bias was between −3.3 and +5.7%, and interday bias was between −3.0 and −0.7%. Intraday precision was below 5.1%, and interday precision was below 4.0%. The candidate RMP was successfully applied to the absolute quantification of PCT in five frozen human serum pools. A recombinant PCT used as a primary calibrator was characterized by high-resolution mass spectrometry and amino acid analysis to establish traceability of the results to the SI units. This candidate RMP is fit to assign target values to secondary certified reference materials (CRMs) for further use in external quality assessment schemes to monitor the accuracy and comparability of the commercially available immunoassay results and to confirm the need for improving the harmonization of PCT assays. The candidate RMP will also be used to evaluate whether the correlation between the candidate RMP and immunoassays is sufficiently high. Overall, this candidate RMP will support reliable sepsis diagnosis and guide treatment decisions, patient monitoring, and outcomes.

Limning India’s Direct Tax Collection Contractions

Indian direct tax collections have remained sluggish over the period coupled with the lesser tax buoyancy have compelled the government to collect revenues from the untapped or under-tapped sources to finance the galloping expenditure such as the health and defence. To achieve the fixed money value targets the taxmen have been putting excessive pressures on the taxpayers who have created a panic, likely to tantamount to infamous tax terrorism and tax disputes have arisen blocking substantial tax revenues in litigations. Taking this in to cognisance the government has attempted to rationalise the tax system by introducing tax amnesty scheme such as the Vivad-se-Viswas and by launching a Faceless Assessment Scheme (FAS) and tax charter, which is likely to address the tax disputes significantly. To increase the revenue, the best approach for the government is to broadening the tax base, reducing the tax rates, rationalising the tax system, formalising the unorganised sectors and by enhancing the lower household incomes substantially in lieu of serving notices to the non-filers is the need of the hour. JEL Codes: E62, H25

External quality control of microbiological testing in Polish medical diagnostic laboratories in 2020

<br><b>Introduction:</b>The paper presents the course of external quality control programmes organised in 2020 by the Centre of Quality Control in Microbiology (CQCM), including the 27<sup>th</sup> edition of the Polish National External Quality Assessment Scheme in Microbiology POLMICRO.</br> <br><b>Aim:</b>The assessment of the microbiological diagnostics’ quality carried out by Polish laboratories based on results of the POLMICRO, POLMICRO/MIKOLOGIA (MYCOLOGY), and POLMICRO/SSE programmes.</br> <br><b>Material and methods:</b>The participants’ responses from all rounds conducted in 2020 were analysed, i.e. five rounds of the POLMICRO programme, two rounds of the POLMICRO /MIKOLOGIA programme, and one round of POLMICRO/SSE.</br> <br><b>Results:</b>Positive evaluation in all rounds in the annual cycle were obtained by 90,1% of POLMICRO, 92,5% POLMICRO/MIKOLOGIA, and 100% POLMICRO/SSE participants.</br> <br><b>Conclusions:</b> Laboratories participating in the CQCM programmes demonstrated skills in the identification, antimicrobial susceptibility testing, and detection of resistance mechanisms of pathogenic microorganisms. The area of internal quality control of antimicrobial susceptibility testing requires improvement, especially the selection of reference strains.</br>

Applicability of CO-RADS in an Anonymized Cohort Including Earlyand Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America.

Classifications were created to facilitate radiological evaluation of the novel coronavirus disease 2019 (COVID-19) on computed tomography (CT) images. The categorical CT assessment scheme (CO-RADS) categorizes lung parenchymal changes according to their likelihood of being caused by SARS-CoV-2 infection. This study investigates the diagnostic accuracy of diagnosing COVID-19 with CO-RADS compared to the Thoracic Imaging Section of the German Radiological Society (DRG) classification and Radiological Society of North America (RSNA) classification in an anonymized patient cohort. To mimic advanced disease stages, follow-up examinations were included as well. This study includes all patients undergoing chest CT in the case of a suspected SARS-CoV-2 infection or an already confirmed infection between March 13 and November 30, 2020. During the study period, two regional lockdowns occurred due to high incidence values, increasing the pre-test probability of COVID-19. Anonymized CT images were reviewed retrospectively and in consensus by two radiologists applying CO-RADS, DRG, and RSNA classification. Afterwards, CT findings were compared to results of sequential real-time reverse transcriptase polymerase chain reaction (qPCR) test performed during hospitalization to determine statistical analysis for diagnosing COVID-19. 536 CT examinations were included. CO-RADS, DRG and RSNA achieved an NPV of 96 %/94 %/95 % (CO-RADS/DRG/RSNA), PPV of 83 %/80 %/88 %, sensitivity of 86 %/76 %/80 %, and specificity of 96 %/95 %/97 %. The disease prevalence was 20 %. All applied classifications can reliably exclude a SARS-CoV-2 infection even in an anonymous setting. Nevertheless, pre-test probability was high in our study setting and has a great influence on the classifications. Therefore, the applicability of the individual classifications will become apparent in the future with lower prevalence and incidence of COVID-19. · CO-RADS, DRG, and RSNA classifications help to reliably detect infected patients in an anonymized setting. · Pre-test probability has a great influence on the individual classifications. · Difficulties in an anonymized study setting are severe pulmonary changes and residuals.. · Valentin B, Steuwe A, Wienemann T et al. Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society andRadiological Society of North America. Fortschr Röntgenstr 2022; 194: 862 - 872.

Code-quality evaluation scheme for assessment of student contributions to programming projects

Project-based learning is the most common approach to software engineering education, due to its emphasis on the teamwork skills essential to real-world collaborations. This study developed an automated programming assessment system (APAS) featuring a code-quality evaluation scheme to overcome difficulties in assessing the contribution of individual team members. Team participation is visualized on a weekly basis to provide insights pertaining to team dynamics, and metrics based on code quality allow the segmentation of students by level of contribution. Insights provided by the proposed system were also shown to facilitate interventions aimed at improving code quality. Empirical analysis based on submission data from 146 students (41 teams) demonstrated the feasibility of the proposed system in monitoring group-based learning projects at the university level, particularly in detecting free-riders.

Comparison of Risk Assessment Schemes in GHPs and HACCP, FSMA Preventive Controls for Human Food, ISO 22000, and GFSI Recognized Standards with Risk Scoring Guidance in General Use with Fresh Produce

The intention of this qualitative research study was to provide a basic risk concept by comparing food risk assessment schemes and preparing general food risk scoring guidance for developing a simple and reliable practical fruit and vegetable qualitative food safety risk matrices for fresh produce entrepreneurs. These practical food safety risk matrices were verified using FDA fruit and vegetable food safety risk data. The FDA data were converted to a qualitative risk matrix referring to the fruit and vegetable 3 × 3 qualitative food safety risk matrix reference model. Other common qualitative risk matrix models, namely 3 × 3, 4 × 3, and 5 × 5, were constructed based on probability and severity scores for each hazard, as given in the FDA data. These were designated as practical fruit and vegetable 3 × 3, 4 × 3, and 5 × 5 qualitative food safety risk matrix models. The results of these models were compared with the fruit and vegetable 3 × 3 reference model. The two best compatible models are the 5 × 5 and 3 × 3 qualitative food safety risk matrix models. A preference test from focus group containing 12 participants showed good satisfaction overall, indicating that the practical fruit and vegetable 3 × 3, 4 × 3, and 5 × 5 qualitative food safety risk matrix models are useful for entrepreneurs. Understanding of basic risk concepts and verified scientific referencing of food safety risk matrices can improve entrepreneur’s risk assessment. This can be performed by using practical–scientific food safety risk matrices.

An efficient and pragmatic approach for regulatory aquatic mixture risk assessment of pesticides

The current regulatory approach to address aquatic mixture toxicity for pesticides in the EU (EFSA J 11:3290, 2013) is rather complex: in typical cases it requires conducting the entire mixture risk assessment scheme for every exposure scenario separately (e.g. 6–8 ecotoxicological endpoints, for each of the nine exposure scenarios for the European Central Zone with 24 common mitigation measure combinations result in over 1700 sub-scenarios to be assessed). This article discusses the available concepts for a mixture toxicity assessment, the key questions raised and the implementation of these questions in existing risk assessment approaches. Based on this, an alternative, more efficient assessment scheme for aquatic mixture risk assessment (AMiRA) is proposed with the aim of facilitating the practical conduct and interpretation of the assessment while addressing the key questions and preserving the level of protection. The scheme assesses product risk (including a check for non-additive effects), the presence of a risk driver and gains efficiency by the straightforward use of risk quotients (RQ) to calculate mixture risk quotients (RQmix) that are equivalent to the calculation of exposure toxicity ratios for a mixture (ETRmix,CA = Exposure-Toxicity-Ratio for mixtures based on concentration addition) proposed by EFSA (EFSA J 11:3290, 2013). A case study is provided underlining the equivalence of the proposed approach to the EFSA (EFSA J 11:3290, 2013) decision tree.

Development of behavioral patterns in young C57BL/6J mice: a home cage-based study

Evidence exists that behavioral patterns only stabilize once mice reach adulthood. Detailed information about the course of behavioral patterns is of particular relevance for neuroscientific research and for the assessment of cumulative severity in genetically modified mice. The analysis considered five age groups focusing on behavioral assessments in the animals’ familiar home cage environment during the adolescence phase. We confirmed age- and sex-specific differences for several of the behavioral parameters and fecal corticosterone metabolites. Interestingly, an age-dependent decline in saccharin preference was detected in female mice. Regardless of sex, relevant levels of burrowing activity were only observed during later developmental phases. The development of nest complexity following the offer of new material was affected by age in female mice. In female and male mice, an age-dependency was evident for wheel running reaching a peak at P 50. A progressive increase with age was also observed for Open field activity. The data sets provide guidance for behavioral studies and for development of composite measure schemes for evidence-based severity assessment in young mice. Except for the burrowing test, the different behavioral tests can be applied in different age groups during post-weaning development. However, age- and sex-specific characteristics need to be considered.

Positive Animal Welfare: Bridging the Gap or Raising Inequalities Worldwide?

Positive animal welfare (PAW) is a rising topic in animal welfare science, although its construct, definition, and operational approach remain debated. Despite this scientific uncertainty, there is societal interest to include more indicators of positive welfare in legislation, animal welfare assessment and accreditation schemes. Changes in some farming practices seem to be in line with promoting PAW (e.g., free-range housing), providing animals more opportunities for positive experiences such as rewarding natural behaviour, greater autonomy, or choice. Interestingly, some of the ideas underlying PAW are present in extensive production systems or low-input animal management practices that are common in low-income countries, for example free-roaming livestock or village dogs. Nevertheless, welfare challenges such as neglect, diseases, poor nutrition, animal abuse and other forms of suffering remain ubiquitous, especially where resources like veterinary support are limited. Living conditions for animals in low-income countries provide examples of the delicate balance between positive welfare and welfare risks relating to health and survival, with inextricable ethical dilemmas. In our view, the growing focus on PAW could stimulate a more balanced approach to animal welfare worldwide, promoting PAW while simultaneously limiting various forms of welfare challenges. However, this requires accounting for human factors such as societal and cultural location-specific aspects to find flexible solutions that also benefit and respect people whose livelihood may be at stake. Those human factors also modulate the consideration and importance of providing animals with positive welfare states and the role of underlying ethical concepts like happiness and “a good life.”

A high compatibility finger vein image quality assessment system based on deep learning

Finger vein feature recognition has been widely studied due to its high security and stability. However, the systematic errors caused by false and missing information in low-quality finger vein images are still concerns. Recently, researchers have proposed a finger vein image quality assessment scheme to eliminate low-quality images. The major drawback of this strategy is the dependence on limited domain knowledge as the strategy cannot effectively filter out low-quality images and is only adapted to a certain recognition method or database. In this paper, we design a new finger vein image quality evaluation method driven by improving the recognition performance of the recognition system and based on the possibility of the false rejection of low-quality images. The method uses statistical knowledge to analyse the matching of different samples between fingers so as to automatically determine the image quality and classify it. Then, we further design a lightweight convolutional neural network to train the high-quality and low-quality images obtained by the above evaluation criteria and mine the common attributes between low-quality images so as to ensure that the prediction system can judge the image quality quickly and accurately in practical use. The proposed scheme is validated on multiple public datasets and compared with current recognition algorithms. The experimental results show that the quality evaluation standard proposed in this paper has good universality and can be combined with different types of recognition methods and acquisition equipment to well screen out the existing low-quality images. Furthermore, the prediction method proposed in this paper has achieved excellent prediction performance on three public datasets, showing that the proposed method can effectively improve the performance of the original recognition system. Taking the local binary pattern (LBP) algorithm as an example, after using the prediction algorithm proposed in this paper to eliminate low-quality images, the recognition system improves the original recognition performance on the three datasets by 12.670% (SDUMLA), 11.923% (MMCBNU_6000) and 9.940% (FV-USM).

HMM-based models of control room operator's cognition during process abnormalities. 2. Application to operator training

Operator training is critical to ensure safe operation in safety-critical domains such as chemical process industries. Training enhances the operator's understanding of the process, which is then encapsulated as mental models. Typically, the operator's learning in traditional training programs is assessed using expert judgment or in terms of process- and operator action-based metrics. These assessment schemes, however, ignore the cognitive aspects of learning, such as mental model development and cognitive workload. The HMM-based model proposed in Part 1 offers a systematic way to quantify operators' cognition during abnormalities. In this Part 2, we show that the cognitive behaviors displayed by expert operators can be represented as target values on the HMM's state transitions and emission probability distributions. Further, we propose two axioms of learning that can capture the evolution of the operator's mental models as they learn the causal relationships in the process and gain expertise in handling abnormal situations. We validate the proposed axioms by conducting training experiments involving 10 participants performing 486 tasks. Our results reveal that the axioms can accurately assess the progress of operators' learning.

Development of a Quality Index Method Scheme for Sensory Assessment of Chilled Yellowfin Tuna

Background: Quality monitoring and/or assessment are parts of a freshness/quality control system, which is of utmost importance for fresh seafood, especially Scombridae fish. The quality index method (QIM) is a simple, convenient, unique, and reliable tool to determine the sensory status and estimate the remaining shelf life of aqua products. Objective: This study aimed to develop a QIM scheme for chilled stored yellowfin tuna and apply the protocol in the fish quality evaluation and storage time estimation. Method: Eight gutted yellowfin tuna of 20, 30, and 40 kg up were used in the study. Five panelists participated in the QIM development, training and application. Control and/or validation analyses were sensory assessment by a control sheet, total volatile basic nitrogen (TVB-N) quantification, and total viable count (TVC) determination. Chilled storage of tuna was performed in liquid ice and traditional crushed block ice. Partial least square regression (PLS-R) was conducted on quality index (QI) dataset over storage time to find the regression line and prediction accuracy. Results: The established QIM protocol for gutted yellowfin tuna comprised 6 attributes (namely, color of whole fish, odor of whole fish and flesh, eyes, appearance of whole fish, flesh color and flesh texture) and a maximal QI of 15. The PLS-R showed that QI could be used to estimate the remaining time with a precision of ± 2.0 and 1.4 days for fish stored in slurry ice and crushed ice, respectively. The TVB-N content in the fish flesh maintained below the acceptable level of 25 mg N/100 g throughout the storage period, which made the parameter impractical to detect the fish shelf life. The TVC overreached the allowable level of 107 CFU/g around the time of fish rejection by the sensory method. Conclusion: The developed QIM scheme for yellowfin tuna showed to be more advantageous in detecting fish quality changes compared to the control sensory method and could be used to estimate the fish's remaining shelf life.