Variation In Quality Research Articles

Academic service quality, student satisfaction and loyalty: a study at higher education legal entities in Indonesia

PurposeThis study aims to explore the influence of academic service quality on student satisfaction and loyalty, based on a study at Higher Education Legal Entities (HELE) in Indonesia. HELE is a policy in higher education that empowers these institutions to become autonomous in management. Academic service quality (ASQ) is an essential aspect of fostering the satisfaction and loyalty of students.Design/methodology/approachThis study uses the descriptive quantitative and regressive survey approach to examine the influence of academic service quality on student satisfaction and loyalty. The population in this study encompassed all students from HELE. Meanwhile, 750 students were purposefully selected from 16 HELE in Indonesia. Data were collected using validated and reliable questionnaires. The garnered data were analyzed using a structural equation model through Smart PLS 3.FindingsThis study finds that (1) there is a significant direct influence of academic service quality on student satisfaction in HELE, (2) there is a reasonably direct influence of student satisfaction on student loyalty in HELE. (3) ASQ of HELE has a feeble direct influence on student loyalty and (4) there is a moderate indirect impact of academic service quality on student loyalty, mediated by student satisfaction at HELE in Indonesia.Research limitations/implicationsThe research was conducted across 16 HELEs in Indonesia. Many other universities do services and of course impact on satisfaction and loyalty for students, but are not included in this research. Besides that, other aspects are not included in this research either. Based on that condition, this result cannot cover all aspects of others in all universities in Indonesia.Practical implicationsThe practical implication of this study’s results for the leaders of HELES is to commit to student-centered, service-oriented tactics and actions for establishing student loyalty. Besides, these institutions must prioritize developing and maintaining profitable customer relationships in this changing world and offer an agenda for the future research.Social implicationsThe social implication will be indicated by higher universities to always improve the service quality of academics, with continuous improvement in the future. It has to do with every university so that student satisfaction improves, and student loyalty improves too. Exiting HELE in the future depends on the variables of service quality for stakeholders in the community around. If the community gets satisfaction, in the future, they will be back to support the HELE in the future.Originality/valueThe results of this study are original and novel, and strengthen the findings of previous research that there is an effect of academic service quality on student satisfaction. It confirms the effects of satisfaction on loyalty, along with the effects of academic service quality on loyalty mediated by satisfaction. These results rejected previous results that there are effects of academic service quality on student loyalty in HELE as organizations.

Assessment of rarity and ecological preferences of the non-marine ostracods (Crustacea) in Çanakkale Province (Türkiye)

Rarity as a multidimensional concept has not been discussed for the ostracods along with the effects of physicochemical factors and sedimentation rates of waters on their distribution. We randomly sampled 91 aquatic sites including eight habitat types in the Çanakkale Province to study ostracod species rarity, commonness, and ecological preferences, and to test the relationships between the rarity index (average of geographic range, habitat specificity, and population size indices) and environmental factors. A total of 44 ostracod taxa (25 living) were reported from 75 sites. Among the species, Candonocypris caledonica was recorded for the first time in Türkiye. Sixty percent of 25 living species exhibited cosmopolitan characteristics, making significant contributions to the diversity of ostracods. The well-known cosmopolitan species, Heterocypris salina (rr = 0.268), Cypridopsis vidua (rr = 0.289), Limnocythere inopinata (rr = 0.330), Ilyocypris bradyi (rr = 0.370), and Psychrodromus olivaceus (rr = 0.390), were identified as common species based on the rarity index (rr) values. Of the environmental variables, only sediment grain sizes (×2000, ×500, and ×63 μm) were found to be effective on the distribution of ostracod species. The Shannon index exhibited a positively significant association with ×2000, while the population size index displayed a linear relationship with ×63 μm grain size, indicating a small population size and rarity. Associations among index values, sediment grain size, and water quality variables showed that comprehensive studies on ostracods, analyzing both water and sediment, can provide a clearer and more precise information for evaluating the rarity and ecological preferences of species.

Effects of Performance Appraisal Quality on Employee Performance in Homa Construction PLC Company Addis Ababa City Administration, Ethiopia

The objective of this study was to examine Effects of Performance Appraisal Quality on Employee Performance in Homa Construction PLC Company, Addis Ababa, Ethiopia. The study was used descriptive and which incorporated both qualitative and quantitative research approaches. The researcher was employed Stratified Random Sampling Technique techniques to distribute the questionnaire to the respondents. Data was collected by using both closed and open ended self-administered questionnaires and a total of two hundred (200) questionnaires were returned. The results were analyzed and interpreted using SPSS software version 20. The scores are interpreted quantitatively and open-ended suggestions are interpreted qualitatively. The research finding of Correlation analysis was indicated there is positive, strong and significant relationships were existed between (Performance Appraisal Quality and Feedback, Feedback and Employee Performance, and Performance Appraisal Quality and Employee Performance) at r =.896, p < 0.01, r =.851 p < 0.01, and r =.799 p < 0.01 respectively. Linear regression analysis also indicated that at 72.8% variance in Employee Performance can be predicted from the combination of all Performance Appraisal Quality and its Feedback Dimensions. The result also shows that at F=267.047, p<0.05 statistically significant. This indicates that combination of the predictors significantly combined together to predict Employee Performance. In meantime the result from the analysis of an independent-sample t-test was approved that most variables of performance appraisal quality were significantly differentiated in score variance for males and females while the finding result of ANOVA analysis explores there was no a statistically significant difference at the p>.05 level in mean scores between groups in Performance Appraisal Quality [F (1, 198) = 1.189, p=.277]. However, there was statistically significant difference at the p>.05 level in mean scores between groups for both Feedback and Employee Performance based on the Age of Respondents. Furthermore, as the result of finding obtained from descriptive statistical analysis Employee Performance was stated low in all attributes. This also proved for unsatisfactory practice of performance appraisals and its feedback that had seen in most Company projects. Finally, the researcher believes that this paper was not exhaustive that could provide all lists of topic researched. However, it gives a bird-eye view on topic and it is open for further discussion and/or critics.

Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow

PurposeAI-assisted techniques for lesion registration and segmentation have the potential to make CT-based tumor follow-up assessment faster and less reader-dependent. However, empirical evidence on the advantages of AI-assisted volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans is lacking. The aim of this study was to assess the efficiency, quality, and inter-reader variability of an AI-assisted workflow for volumetric segmentation of lymph node and soft tissue metastases in follow-up CT scans. Three hypotheses were tested: (H1) Assessment time for follow-up lesion segmentation is reduced using an AI-assisted workflow. (H2) The quality of the AI-assisted segmentation is non-inferior to the quality of fully manual segmentation. (H3) The inter-reader variability of the resulting segmentations is reduced with AI assistance.Materials and methodsThe study retrospectively analyzed 126 lymph nodes and 135 soft tissue metastases from 55 patients with stage IV melanoma. Three radiologists from two institutions performed both AI-assisted and manual segmentation, and the results were statistically analyzed and compared to a manual segmentation reference standard.ResultsAI-assisted segmentation reduced user interaction time significantly by 33% (222 s vs. 336 s), achieved similar Dice scores (0.80–0.84 vs. 0.81–0.82) and decreased inter-reader variability (median Dice 0.85–1.0 vs. 0.80–0.82; ICC 0.84 vs. 0.80), compared to manual segmentation.ConclusionThe findings of this study support the use of AI-assisted registration and volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans. The AI-assisted workflow achieved significant time savings, similar segmentation quality, and reduced inter-reader variability compared to manual segmentation.

PENGARUH KUALITAS PELAYANAN DAN FASILITAS TERHADAP KEPUASAN KONSUMEN PADA RUMAH MAKAN ASIDO KHAS BATAK JALAN BUNGA TEROMPET NO.16 KOTA MEDAN

The aim of this research is to find out whether customer satisfaction at the Asido Khas Batak Restaurant on Jalan Terompet Bunga No. 16 Medan City is influenced by facilities and service quality. A total of 31,416 people constituted the population of this study, which used a quantitative approach. Using nonprobability sampling, a sample of 100 respondents who met the predetermined criteria was collected. Validity, reliability and classical assumption tests were used to test the data before the t test, F test and coefficient of determination were used in the research data collection method. Customer satisfaction is proven to be significantly influenced by facilities and service quality. Customer satisfaction is greatly influenced by facilities and service quality simultaneously. Service and facility quality variables can influence customer satisfaction by 63.6%, according to the adjusted coefficient of determination (Adjusted R2) of 0.636, with other variables outside the scope of this research model determining the remaining 36.4%. This indicates that the reasons behind customer happiness may still be caused by other factors.

Effect of exogenous sperm capacitation inducers on stallion sperm

Although under appropriate laboratory conditions, sperm from different mammalian species can be capacitated in vitro, the optimal conditions for sperm capacitation in the stallion have been elusive. This study evaluated the effect of different capacitating inducers in Whitten and Tyrode media and assessed their impact on capacitation-related factors. Stallion sperm were incubated with different combinations of capacitating inducers at 38.5 °C in an air atmosphere. Sperm quality variables such as motility, mitochondrial membrane potential, and lipid peroxidation were assessed. Membrane fluidity and intracellular calcium levels were evaluated as early markers of capacitation, while tyrosine phosphorylation events and the sperm's ability to perform acrosomal exocytosis were used as late capacitation markers. Finally, these sperm were evaluated using a heterologous zona pellucida binding assay. The findings confirm that capacitating conditions evaluated increase intracellular calcium levels and membrane fluidity in both media. Similarly, including 2 or 3 inducers in both media increased tyrosine phosphorylation levels and acrosomal exocytosis after exposure to progesterone, confirming that stallion sperm incubated in these conditions shows cellular and molecular changes consistent with sperm capacitation. Furthermore, the zona pellucida binding assay confirmed the binding capacity of sperm incubated in capacitation conditions, a key step for stallion in vitro fertilization success. Further studies are needed to evaluate the effect of these conditions on in vitro fertilization in the horse.

Establishing the Preface for a Unified Otolaryngology Residency Curriculum: Implications and Considerations.

Otolaryngology residency training, along with the world of online medical education, has been continuously evolving and refining methods to educate and produce competent otolaryngologists. Numerous resources have been developed to assist otolaryngology residents in enhancing their clinical training. Although these resources greatly enhance clinical training, the growing volume of material presents a challenge within the constrained schedule of otolaryngology residents. This challenge is compounded by the variability in quality among resources which lack standardization or validation. Recently, the American Academy of Otolaryngology-Head and Neck Surgery Foundation has proposed a unified otolaryngology curriculum designed to address these issues. This curriculum aims to incorporate high-quality educational materials, evidence-based adult learning principles, accessible learning sources, and diverse instructional methods within a structured program. Such a curriculum promises a significant positive impact, mirroring successes observed in various other surgical specialties.

A Decision-Making Model for Fast-Track High-Rise Buildings Using Structural Equation Modelling

Fast-track is a project management technique used to address time constraints and schedule overrun on construction projects. One of the major impediments in the application of fast-track technique in Pakistan’s construction industry is the lack of a comprehensive decision-making model. The aim of this research is to develop a comprehensive decision-making model for fast-track high-rise buildings which can highlight the impact of each decision-making aspect on its relevant project success indicator i.e., time variance(TV), cost variance(CV), quality variance(QV) or scope variance(SV) and the impact of cost, quality, and scope variances on time variance. Structural equation modelling (SEM) was used to develop this model. Questionnaire based on 5-point Likert’s scale was used to collect data from 159 construction industry professionals. Data was analysed using smart PLS-4 software. Results showed that on fast-track projects, scope variance has the greatest impact on time variance whereas quality variance has the least impact. Early scope freeze, early involvement of the contractor in design phase and early procurement of long-lead-time items are the most important decisions on fast-track projects whereas quality optimization decisions have an adverse impact on project duration. The proposed model has high out-of-sample predictive ability making it a universally applicable decision-making model. DOI: https://doi.org/10.52783/pst.434

Influence of epinephrine reactivity to stress on meat quality in goats.

The magnitude of physiological responses to a stressor can vary among individual goats within a herd; however, whether these differences can differentially affect meat quality is not known. This study was conducted to determine the influence of the magnitude of epinephrine response (ER) to acute stress on muscle metabolome and meat quality in goats. Male Spanish goats (6 mo old) were transported for 180min. (N = 75 goats; 25 goats/d) to impose stress. Blood samples were obtained after transport for analysis of physiological responses. Goats were slaughtered using humane procedures and samples were collected for muscle metabolomics and meat quality analyses. The data obtained from blood and muscle/meat analysis were then categorized based on epinephrine concentrations into low (LE), medium (ME), and high (HE) ER groups (n = 12/ER group). The physiological and meat quality variables were analyzed as a Completely Randomized Design in SAS, and metabolomics data were analyzed using R software. Plasma glucose concentrations were significantly high in the HE group, low in the LE group, and intermediate in the ME group (P < 0.05). However, leukocyte counts and cortisol, norepinephrine, blood urea nitrogen, and creatine concentrations were not different among the ER groups. Muscle (Longissimus dorsi) glycogen concentrations (15min postmortem) were significantly higher (P < 0.05) in the ME and LE groups than in the HE group. However, postmortem Longissimus muscle pH and temperature (15min and 24h), 24h calpastatin and desmin levels, and rib chop color (L*, a*, and b*), cooking loss, and Warner-Bratzler shear force values were unaffected by ER. Targeted metabolomics analysis of Longissimus muscle (15min) revealed that diacyl phosphatidylcholines (C38:0; 40:6) and sphingomyelin (C20:2) were significantly different (P < 0.05) among the ER groups, with the concentrations of these metabolites being consistently high in the LE group. These differential muscle metabolite concentrations suggest that ER can influence biochemical pathways associated with cell membrane integrity and signaling. ER had a significant effect on dopamine concentrations, with the levels increasing with increasing levels of ER. The results indicate that differences in epinephrine reactivity can influence selected physiological responses and muscle metabolites; however, it does not significantly influence meat quality attributes.

Physical and physiological quality of oat (Avena sativa L. cv. Turquesa) seeds

bjective: The objective of this study was to determine the physical and physiological quality of a batch of oat (Avena sativa L. cv. Turquesa) seeds. Design/Methodology/Approach: The following physical quality variables were evaluated: seed purity, weight of a thousand seeds, volumetric weight, and moisture content. Physiological quality was evaluated through a germination and emergence speed test, which also was used to measure seed vigor. A completely randomized experimental design, with factorial arrangement, and four repetitions was used. The factors analyzed were seed size (small and large) and aging (with and without aging). Results: The following results were recorded: 99.52% seed purity; 34.31 g weight of a thousand seeds; 54.80 kg hl-1 volumetric weight; and 6.50% moisture content. Regarding treatment germination, no significant differences were found between the seed size and the size × aging interaction (P = 0.422). The aging treatment reduced germination from 96.50% (unaged seeds) to 89.25% (aged seeds). The emergence speed did not show significant differences regarding seed size (P = 0.066) and size × aging interaction (P = 0.868). The aging treatment had a negative impact on the emergence rate. The aged seeds emerged at a 15.55 plants d-1 speed, while unaged seeds reached a 17.88 plants d-1 speed. Study Limitations/Implications: This study only evaluated one batch of oat seeds. Findings/Conclusions: The seeds have an adequate physical and physiological quality to establish oat crops. In addition, the seed batch was highly vigorous, because it maintained &gt;80% germination rate after the aging treatment.

Evaluation of Water and Sediment Quality in Lake Mogan, Türkiye

The wetlands, with their delicate ecosystems, play a crucial role in regulating water regimes and supporting diverse plant and animal communities, particularly those associated with water habitats. Mogan Lake, located within the Gölbaşı Special Environmental Protection Area, stands out as a unique habitat, hosting over 200 bird species. This study aimed to assess the current water quality of Mogan Lake by analysing various water quality variables. Three sampling sites, representing the northern, middle, and southern parts of the lake, were selected to examine both surface water and bottom sludge characteristics through the analysis of 29 pollutant variables. Water samples were collected from 30 cm beneath the water surface and 50 cm above the bottom of the lake. Sediment samples were collected from the sludge at the lake basin. Additionally, to understand their impact on the lake’s water quality, 26 pollutants were also measured in water samples taken from the five main streams that feed the lake. The results reveal a significant level of organic pollution in the lake, along with elevated nitrogen levels indicating hypertrophic conditions. Although organic pollutants were detected in the lake bottom sediment through analysis, they are considered non-hazardous in terms of heavy metals and other inorganic variables.

Analysis of the spatiotemporal dynamics and driving factors of ecosystem quality in Inner Mongolia from 2005 to 2020

Enhancing ecosystem quality is a necessary part of establishing of ecological civilization. The study of ecosystem quality requires the development of comprehensive evaluation indices. The existing simple remote sensing ecological indices are insufficient for achieving a comprehensive and systematic evaluation of the ecosystem quality. Therefore, we constructed an ecosystem quality index based on the landscape pattern, ecosystem stability, and ecosystem services. The spatiotemporal dynamics of the ecosystem quality in Inner Mongolia were analyzed over the period from 2005 to 2020. Moreover, a geographically weighted regression model was used to investigate the factors influencing the spatiotemporal variations in the ecosystem quality. The main results are as follows. (1) The spatial distribution of ecosystem quality in Inner Mongolia exhibited a gradual decline from the northeast to the southwest. In contrast, temporal analysis revealed a general increase in ecosystem quality from 2005 to 2020. (2) Climate was a significant factor influencing the spatial heterogeneity and temporal variability of the ecosystem quality. Socioeconomic factors, population density and livestock numbers had notable impacts on the spatial heterogeneity and temporal variability of ecosystem quality, respectively. (3) In Inner Mongolia, temperature and ecosystem quality showed a positive correlation in the northeastern region, but a negative correlation in the central and western regions. The findings offer valuable support for local policymakers in making informed decisions regarding targeted ecosystem management. Furthermore, our results provide local governments with valuable insights for enhancing the quality of regional ecosystems by taking into account the specific conditions of the area.

Rollout of a statewide Australian telestroke network including virtual reality training is associated with improved hyperacute stroke workflow metrics and thrombolysis rate

BackgroundTelestroke networks aim to address variability in both quality and access to stroke care in rural areas, by providing remote access to expert stroke neurologists. Implementation of telestroke requires adaptation of workflow processes and education. We previously developed virtual reality (VR) workflow training and documented acceptability, utility and feasibility. The effects on acute stroke treatment metrics have not been previously described.AimsThe overall aim was to improve hyperacute stroke metrics and shorten the time-to-reperfusion therapy administration in rural settings.MethodsThis study applies a natural experiment approach, collecting stroke metric data during transition from a pre-existing pilot to a statewide telestroke service at five rural hospitals. Pre- and post-intervention data included baseline patient demographics and assessment, diagnosis, and treatment delivery metrics. The primary study outcome was door-to-decision time (thrombolysis and endovascular thrombectomy). Secondary outcomes included door-to-computerized tomography time, door-to-thrombolysis time and proportion of patients receiving thrombolysis or thrombectomy treatment. Usage data relating to the VR stroke workflow training of interprofessional healthcare professionals was automatically captured via Wi-Fi. Statistical comparisons of clinical metrics between the pre- and post-intervention time periods, defined as the timeframes before and after VR deployment, were performed.ResultsA total of 2,683 patients were included (April 2013–December 2022); 1910 pre- and 773 post-intervention. All acute stroke time metrics significantly improved post-intervention. The primary outcome, door-to-decision time, decreased from 80 min [56–118] to 54 min [40–76; P &amp;lt; 0.001]. Secondary outcomes also improved, including door-to-thrombolysis time (90 min [68–114] vs. 68.5 min [54–90]; P &amp;lt; 0.001) and proportion of patients thrombolysed (11 vs. 16%; P &amp;lt; 0.001). The proportion of patients transferred for thrombectomy was unchanged (6 vs. 7%; P = 0.69). Seventy VR sessions totaling 15 h 39 min of training time were logged. VR training usage varied across sites (3–31 sessions per site).ConclusionsDelivery of a multi-factorial intervention including infrastructure, funding, education and training (with VR workflow training) as part of a state-wide telestroke rollout was associated with improved acute stroke treatment metrics. Additional work is required to identify the contribution of each intervention component on clinical outcomes and to increase training uptake and sustainment.

The Influence Of Perceived Product Quality, Perceived Marketing Quality And Social Media Marketing On Consumer Buying Interest

This research was conducted with the aim of finding out how much influence product quality, service quality and social media marketing have on consumer buying interest at the Batik Gallery of the East Java Province Cooperative and SME Service, partially and simultaneously and how much influence they have. This research data was obtained from primary data through interviews and distributing questionnaires to consumers who had purchased products at the Batik Gallery of the East Java Province UKM Service. In this study, researchers used the Lemeshow formula to obtain the population size and obtained 96 data samples for processing. In this research the author used quantitative descriptive methods. The analysis used is multiple linear regression analysis, t test, F test, classical assumption test, and coefficient of determination test using the SPSS version 23 application. The questionnaire in this research has also passed the validity and reliability testing stage. The results of the partial test (t-test) between the product quality variable (X1) and purchasing interest (Y), can be concluded that the product quality variables (X1) and (Y) have no partial influence. The service quality and social media marketing variables have a partial influence. Meanwhile, the results of simultaneous testing (F-test) can be concluded that there is a significant simultaneous influence between the variables product quality (X1), service quality (X2) and social media marketing (X3) on consumer buying interest (Y).

Groundwater solutes influence the adsorption of short-chain perfluoroalkyl acids (PFAA) to colloidal activated carbon and impact performance for in situ groundwater remediation

Subsurface injection of colloidal activated carbon (CAC) is an in situ remediation strategy for perfluoroalkyl acids (PFAA), but the influence of groundwater solutes on longevity is uncertain, particularly for short-chain PFAA. We quantify the impact of inorganic anions, dissolved organic matter (DOM), and stabilizing polymer on PFAA adsorption to a commercial CAC. Surface characterization supported PFAA chain-length dependent adsorption results and mechanisms are provided. Inorganic anions decreased adsorption for short-chain PFAA (<7 perfluorinated carbons) due to competitive effects, while long-chain PFAA (≥ 7 perfluorinated carbons) were less impacted. DOM decreased adsorption of all PFAA in a chain-length dependent manner. High DOM concentrations (10 mg/L, ∼5 mg OC/L) decreased PFOA adsorption by a factor of 2, PFPeA by one order of magnitude, and completely hindered PFBA adsorption. High MW DOM has less impact on short-chain PFAA than low MW DOM, possibly due to differences in the ability to access CAC micropores. Low DOM concentrations (1 mg/L, ∼0.5 mg OC/L) did not impact adsorption. CMC (90 kDa average MW) had negligible impact on PFAA adsorption likely due to minimal CAC surface coverage. Longevity modeling demonstrated that groundwater solutes limit the capacity for PFAA in a CAC barrier, particularly for short-chain PFAA.

A Smirk of Satisfaction: Study on Panama Cafe Consumers

Aims: The success of a business cannot be separated from customer satisfaction. Consumer satisfaction or customer satisfaction is also an important factor in building a business. Satisfied consumers will certainly increase sales from the company. Consumer satisfaction is the level of consumer feelings after comparing what he received with what he expected. The purpose of this study is to find solutions to problems among product quality, service quality, and price on customer satisfaction. Study Design: Quantitative descriptive. Place and Duration of Study: The sample used in this study were consumers who made purchases at Panama Cafe in Makassar City during the period January to March 2024. Methodology: This research is a descriptive quantitative study conducted from January to March 2024. Sampling using purposive sampling method. The total sample in this research are 50 customers (22 male, 22 female, age range 15-35 years) who made more than two purchases. Data collection uses a questionnaire, which will be tested for validity and reliability, with the help of SPSS to processing data. Results: The Product Quality variable has a T count of 0.471 and a significant value obtained of 0.640&gt; 0.05. Thus it can be said that the product quality variable does not have a positive and significant effect on customer satisfaction. The Service Quality variable has a T count of 2.030 and a significant value obtained of 0.048 &lt;0.05. Therefore, it can be concluded that the service quality variable has a significant and significant influence on customer satisfaction. The Price variable has a T count of 4.781 and a significant value obtained of 0.000 &lt;0.05. Hence it can be concluded that the service quality variable has an influence and is significant to customer satisfaction. Conclusion: Product quality has no influence on customer satisfaction, while service quality and price have an influence on customer satisfaction at Panama Cafe in Makassar city.

A deep learning framework for quality control process in the motor oil industry

Given the advancements in the modern world, using Multivariate-Multistage Quality Control (MVMSQC) patterns in continuous production industries is deemed crucial and essential. This study examines the importance and necessity of Multivariate-Multistage Quality Control in manufacturing industries, focusing on motor oil production. Motor oil quality significantly influences engine performance. Thus, the primary objective of this research is to enhance accuracy in detecting faults in quality variables, utilizing deep learning algorithms for visual quality control of data, a facet often overlooked in classical statistical methods and reducing process control time. Combining deep learning algorithms such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for controlling numerical variables, and Residual Networks (ResNet) and Dense Convolutional Networks (DenseNet) for controlling image variables have been employed. Additionally, the Honey Bee Mating Optimization Algorithm (GBC) has been utilized to tune the parameters of the LSTM-CNN and ResNet-DenseNet deep learning algorithms. Combining heuristic algorithms and deep learning algorithms enhances the performance of the final models in quality control processes. A case study in the motor oil production industry is examined to demonstrate the real-world application of the proposed model. The proposed LSTM-CNN hybrid algorithm outperforms individual CNN and LSTM algorithms in fault detection, improving performance by 15% and 8%, respectively. Furthermore, in visual components, the proposed ResNet-DenseNet hybrid algorithm has shown higher accuracy than ResNet and DenseNet algorithms, improving performance by 10% and 15%, respectively. This research significantly contributes to developing Multivariate-Multistage Quality Control in manufacturing industries by employing deep learning methods. The primary aim is to identify faults in quality components and utilize deep learning algorithms for visual quality control of data, a facet often overlooked in classical statistical methods. The research significantly advances multivariate-multistage quality control in manufacturing industries by leveraging deep learning methods. It addresses detecting complex nonlinear patterns in large-scale data with high flexibility and minimal time.

A quality‐related distributed process monitoring framework for large‐scale manufacturing processes with multirate sampling measurements

SummaryQuality‐related process monitoring has become a research hot‐spot in the field of industrial control because it is essential to ensure the process safety and product quality. A great number of data driven quality‐related process monitoring methods have been developed for large‐scale manufacturing processes, and most of them are developed based on homogeneous sampling measurement. Therefore, it is necessary to develop quality‐related monitoring methods for large‐scale processes with multirate sampling measurements. In this paper, a new quality‐related distributed monitoring framework for large‐scale manufacturing processes with multirate sampling measurements is proposed. First, a new subsystem decomposition method for multirate sampling processes combining prior knowledge and mutual information is proposed by introducing mathematic expectations. Second, local monitoring model is designed for each subsystem. Multirate partial least squares regression is adopted for modeling among the process and quality variables. The monitoring metrics of the isolation‐based anomaly detection using nearest‐neighbor ensembles are built in prediction space and process space, respectively. Finally, Bayesian inference is introduced to obtain statistical indicators for the plant‐wide processes. The validity of the proposed framework is verified in Tennessee Eastman process and a real hot strip mill process. The results show that the proposed method has favorable effectiveness and significant performance gains compared with state‐of‐the‐art methods.

How a System Is Closing the Evidence-Based Data Management Gap.

To translate raw data into information that is understandable and actionable, healthcare leaders must leverage decision-making tools that can drive strategic innovation, improve processes, and shape the future of healthcare. Continuous changes in healthcare delivery require constant monitoring of an expanding range of data. Population demographics, psychographics, and availability of care all must be considered, as well as provider practice patterns, patient utilization, clinical and service quality, costs, and many other key variables over time. RWJBarnabas Health is navigating significant changes in its approach to managing data. A unified operating model is driving standardization, continuous quality improvement, and cost reductions across the system. The solution is based on an electronic health record system designed to meet the needs of the entire system, an array of carefully selected external data sources, and a business intelligence tool to enable leaders to quickly draw insights from all the available data.

Real-world waste dispersion modelling for benthic integrated multi-trophic aquaculture.

In real-world situations, marine fish farms accommodate multiple fish species and cohorts within the farm, leading to diverse farm layouts influenced by cage dimensions, configurations, and intricate arrangements. These cage management practices are essential to meet production demands, however, farm-level complexities can impact model predictions of waste deposition and benthic impact near fish cages. This is of particular importance when the cages are used for integrated multi-trophic aquaculture (IMTA) with benthic feeders, where this waste not only affects environmental conditions but also provides a potential food source. The Cage Aquaculture Particulate Output and Transport (CAPOT) model incorporated multiple species, cohorts, and cage arrangements to estimate waste distribution from a commercial fish farm in the Mediterranean between October 2018 and July 2019. This spreadsheet model estimated dispersion for individual fish cages using a grid resolution of 5 m x 5 m. The study categorized discrete production periods for each fish cage every month, aligning with intermittent changes in biomass and food inputs due to different cage management practices throughout production. This approach facilitated the use of detailed input data and enhanced model representativeness by considering variations in cage biomass, food types, settling velocities, and configurations. Model outputs, represented in contour plots, indicated higher deposition directly below fish cages that varied monthly throughout fish production cycles. Deposition footprints reflected changes in cage biomass, food inputs, and farm-level practices reflecting this real-world scenario where aquaculture does not follow a production continuum. Moreover, cohort dynamics and cage movements associated with the cage management practices of the fish farm influenced the quantity and fate of wastes distributed around fish cages, revealing variability in deposition footprints. Clearly, these findings have important implications for the design of benthic IMTA systems, with species such as sea cucumber and polychaetes. Variability in waste deposition creates challenges in identifying where the benthic organisms should be placed to allow optimal uptake of waste to meet their food requirements and increase survivability. Evidently, models have an important role to play and this study emphasizes the need for representative input data to describe actual food inputs, cage biomass changes, and management practices for more representative farm-scale modelling and essentially to improve particulate waste management. To effectively mitigate benthic impacts through IMTA, models must quantify and resolve particulate waste distribution and impact around fish farms to maintain a balanced system with net removal of wastes. Resolving farm-level complexities provides vital information about the variability of food availability and quality for extractive organisms that helps improve recycling of organic wastes in integrated systems, demanding a more representative modelling approach.