Saba Sareminia, Zahra Ghayoumian and Fatemeh Haghighat
The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring…
Abstract
Purpose
The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.
Design/methodology/approach
This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.
Findings
The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.
Originality/value
This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.
Details
Keywords
Mohammad Zamani, Zahra Sohrabi, Ladan Aghakhani, Kimia Leilami, Saeed Nosratabadi, Zahra Namkhah, Cain Clark, Neda Haghighat, Omid Asbaghi and Fatemeh Fathi
Previous research indicates that vitamin D and omega-3 co-supplementation may benefit overall health, but current evidence regarding its effects on lipid profile remains unclear…
Abstract
Purpose
Previous research indicates that vitamin D and omega-3 co-supplementation may benefit overall health, but current evidence regarding its effects on lipid profile remains unclear. The present systematic review and meta-analysis aimed to examine the effects of vitamin D and omega-3 co-supplementation on lipid profile (total cholesterol [TC], low-density lipoprotein [LDL], triglyceride [TG] and high-density lipoprotein [HDL]) in adults.
Design/methodology/approach
In this systematic review and meta-analysis, relevant studies were obtained by searching the PubMed, Scopus and Web of Science databases (from inception to January 2022). Weighted mean differences and 95% confidence intervals were estimated via a random-effects model. Heterogeneity, sensitivity analysis and publication bias were reported using standard methods.
Findings
Pooled analysis of six randomized controlled trials (RCTs) revealed that vitamin D and omega-3 co-supplementation yielded significant reductions in TG (p = 0.631). A pooled analysis of five trials indicated a significant association between omega-3 and vitamin D treatment and reductions in TC (p = 0.001) and LDL (p = 0.001). Although, pooled analyses of omega-3 and vitamin D did not significantly affect HDL.
Originality/value
The findings suggest that vitamin D and omega-3 co-supplementation lowers TG, TC and LDL in adults. Future, large-scale, RCTs on various populations are needed to elucidate further beneficial effects of vitamin D and omega-3 co-supplementation on lipid profile and establish guidelines for clinical practice.
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Fatemeh Mostafavi, Mohammad Tahsildoost, Zahra Sadat Zomorodian and Seyed Shayan Shahrestani
In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the…
Abstract
Purpose
In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design.
Design/methodology/approach
A methodology using an image-based deep learning model called pix2pix is proposed to predict the overall daylight, energy and ventilation performance of a given residential building space layout. The proposed methodology is then evaluated by being applied to 300 sample apartment units in Tehran, Iran. Four pix2pix models were trained to predict illuminance, spatial daylight autonomy (sDA), primary energy intensity and ventilation maps. The simulation results were considered ground truth.
Findings
The results showed an average structural similarity index measure (SSIM) of 0.86 and 0.81 for the predicted illuminance and sDA maps, respectively, and an average score of 88% for the predicted primary energy intensity and ventilation representative maps, each of which is outputted within three seconds.
Originality/value
The proposed framework in this study helps upskilling the design professionals involved with the architecture, engineering and construction (AEC) industry through engaging artificial intelligence in human–computer interactions. The specific novelties of this research are: first, evaluating indoor environmental metrics (daylight and ventilation) alongside the energy performance of space layouts using pix2pix model, second, widening the assessment scope to a group of spaces forming an apartment layout at five different floors and third, incorporating the impact of building context on the intended objectives.