Quick Evaluation Research Articles

Skin Melanoma Cancer Detection and Classification using Machine Learning

Early identification of melanoma skin cancer is essential for effective therapy. Melanoma is currently recognized as the most lethal type of skin cancer among all others due to its high propensity to metastasize to distant organs if undiagnosed and untreated. In the clinical diagnosis of many disorders, non-invasive medical computer vision or medical image processing is becoming increasingly important. These methods offer an automatic image analysis tool for a quick and accurate lesion evaluation. The steps in this study's methodology include gathering a database of dermoscopy images, pre-processing, segmentation using thresholding, statistical feature extraction using Gray Level Co-occurrence Matrix (GLCM), Asymmetry, Border, Color, Diameter, etc., and feature selection using Principal Component Analysis

Biotensegration of malocclusion and temporomandibular disorders with diseases of the musculoskeletal system and posture defects – a literature review, supported by own observations

Although it enables a quick evaluation, medical diagnostics of the human myofascial-skeletal system is not always used to its full capabilities. This often hampers the objective assessment of a dysfunction and limits treatment options. Dysfunctions of the stomatognathic system, of different aetiology, are becoming more prevalent. Many scientific studies are in to relationships between organs and systems of the human body that can cause dysfunctions of the temporomandibular disorders. Studies investigating correlations between a myofascial-skeletal disorder and temporomandibular disorders are to be found in the literature. To achieve a good understanding of aetiology of these dysfunctions, a holistic view of a patient is advisable, which takes into consideration the fact that the temporomandibular joint is an integral part of the whole body. This study is a review of the literature, supported by own examples on investigating the relationship between myofascial-skeletal disorders and a temporomandibular disorder, which, in the light of current medical knowledge, is attributed to the phenomenon of biotensegrity. A conclusion has been put forward on the basis of 136 scientific reports that a dependency exists between the said dysfunctions.

Metabolic Changes during Sprouting of Rapeseed and Their Consequences for the Volatilome of Cold‐Pressed Oil

AbstractAll the procedures before pressing seeds have a great influence on the flavor of cold‐pressed rapeseed oil. However, the studies on the modification of aroma caused by inappropriate storage leading to sprouting are scarce. Therefore, this study aims to determine the effects of sprouting on the metabolome and volatilome of rapeseed cold‐pressed oil and press cakes. The presence of 56 and 21 nonvolatile metabolites is detected in seeds/press cakes and oil, respectively. Sprouting significantly affects the total contents of all groups of compounds, except sugars. At the same time, 375 volatile organic compounds (VOCs) are detected. The abundance of VOCs in sprouted oil is almost threefold higher compared to control oil, with the biggest contribution of sulfur‐containing compounds (dimethyl sulfide), glucosinolate derivatives (4‐isothiocyanato‐1‐butene), and aldehydes (3‐methylbutanal). A similar tendency is observed in press cake. Moreover, sprouting results in the biggest number of VOCs detected only in this oil (61). The abundance of aroma‐active compounds is much higher in sprouted products compared to corresponding controls, which has a confirmation in sensory analysis. This study shows that simultaneous volatilomics and metabolomics can be used to track the changes in the oil quality caused by the inappropriate storage of seeds. Sprouting leads to metabolic changes in seeds, which intensify the formation of new VOCs and consequently aroma of oils.Practical applications: The results of this study will help to understand the formation of volatile organic compounds (VOCs) during the processing and production of cold‐pressed rapeseed oil. The combination of VOCs with nonvolatile precursors can help to understand the pathways involved in VOCs formation. Moreover, the oil obtained from sprouted seeds is characterized by many VOCs not present in control oil, which can potentially be used to develop tools for quick evaluation if the seeds used for pressing initiated sprouting, which can lead to changes in its sensory quality.

DESIGN SCENARIO AND ANALYSIS FOR PRELIMINARY SPECIFICATION OF STEAM GENERATOR IN THE PELUIT-40

The helical steam generator is connected to an HTGR-type nuclear reactor called PeLUIt-40 for steam production. Steam is used to generate electricity and hydrogen. A once-through helical tube bundle was employed because of its ability to endure mechanical stress due to thermal expansion, high resistance to flow-induced vibrations, and better thermal performance compared to a straight tube one. To produce the targeted steam, a design analysis of the once-through helical steam generator needs to be conducted. A quick evaluation method was used to predict the preliminary specifications required for steam production. Simple thermodynamic calculations combined with empirical heat transfer coefficients covering convective and boiling processes at constant pressure were used to carry out the analysis. Two scenarios were conducted to evaluate the design choice based on the previous design of RDE-10.

A two concentric circles model incorporating availability of ecosystem services and affordability of humans to clarify the ecological security concept

As human influences on natural ecosystems continue to expand, the utilization of natural resources is approaching a threshold where unsustainability threatens the security of human society. As the challenging tradeoffs between human resource demand, ecological sustainability and the security of human society have become more widely recognized, ecological security issues have received extensive attention. However, despite the emergence of substantial body of scientific research on these broader issues, there is still no broad consensus on the definition of ecological security and how it should be applied to mediate resource use and conservation dilemmas. Across the body of published research in this subject area, the criteria and evaluation methods are often so different that the results of different studies are difficult to compare. In this paper, we propose that ecological security refers to the degree to which the condition of ecosystem can support a certain level of socioeconomic development or quality of life. We propose a simple geometric model to quantify ecological security in two dimensions: the availability of ecosystem services and the affordability of humans. The availability dimension is determined by the supply and demand of ecosystem services and the affordability dimension is determined by the cost and the paying capacity balance to obtain ecosystem services. Then, we applied this model to two hypothetical cases to demonstrate its usefulness. The most important feature of the proposed model is that it enables the quick evaluation of important aspects of ecological security for a study area using eight key factors. Although the shape and geographic characteristics of a study area are usually more complex than the hypothetical case, our model can be applied if the conditions are properly simplified or adjusted.

A Data-Driven Approach to the Unified Evaluation of Conventional and Unconventional Hydrocarbon Resources: Application to Low-Mature to Mature Source Rocks in the Liaohe Western Depression

Hydrocarbon potential evaluation is a high priority in oil/gas exploration which is significantly influenced by evaluation methods and subjective cognition. With the aim of quantitatively establishing a hydrocarbon generation and expulsion (HGE) model of source rocks, a data-driven approach is proposed based on abundant and readily available Rock-Eval/total organic carbon content (TOC)/vitrinite reflectance (VRo) datasets. This approach takes into account the original hydrocarbon generation potential (GPIo) and the loss of TOC. Hydrocarbon generation simulation was also adopted in this study. This data-driven method was applied to the Lower Paleogene Shahejie Formation (Es4), which has three sets of superior source rocks (average thickness > 250 m, TOC > 3%). The GPIo of the Es4 low-maturity source rock was 600 mg HC/g TOC. The initial maturity values of hydrocarbon generation and expulsion were 0.36% and 0.46%, respectively. The Gaosheng sub-member of the Es4 source rock had the largest amount of hydrocarbon generation but a limited amount of hydrocarbon expulsion, implying a favorable exploration of shale oil resources. By contrast, the values of the conventional, unconventional tight, and shale oil resource potentials of the Niuxintuo sub-member were 3.20 × 107, 7.70 × 107, and 5.93 × 108 t, respectively, indicating good prospects for tight oil and shale oil exploration. A comparison between the previous method and the data-driven method showed considerable differences in the restoration of GPIo and TOC, and both had their own limitations. This data-driven approach provides a quick and valid source rock evaluation method and can greatly enhance the accuracy of resource assessment.

Comparison of methods to determine electrocatalysts’ surface area in gas diffusion electrode setups: a case study on Pt/C and PtRu/C

In recent years, gas diffusion electrode (GDE) half-cell setups have attracted increasing attention, bridging the gap between fundamental and applied fuel cell research. They allow quick and reliable evaluation of fuel cell catalyst layers and provide a unique possibility to screen different electrocatalysts at close to real experimental conditions. However, benchmarking electrocatalysts’ intrinsic activity and stability is impossible without knowing their electrochemical active surface area (ECSA). In this work, we compare and contrast three methods for the determination of the ECSA: (a) underpotential deposition of hydrogen (Hupd); (b) CO-stripping; and (c) underpotential deposition of copper (Cuupd) in acidic and alkaline electrolytes, using representative electrocatalysts for fuel cell applications (Pt and PtRu-alloys supported on carbon). We demonstrate that, while all methods can be used in GDE setups, CO-stripping is the most convenient and reliable. Additionally, the application of Cuupd offers the possibility to derive the atomic surface ratio in PtRu-alloy catalysts. By discussing the advantages of each method, we hope to guide future research in accurately determining surface area and, hence, the intrinsic performance of realistic catalyst layers.

Designing Collagen-Binding Peptide with Enhanced Properties Using Hydropathic Free Energy Predictions.

Collagen is fundamental to a vast diversity of health functions and potential therapeutics. Short peptides targeting collagen are attractive for designing modular systems for site-specific delivery of bioactive agents. Characterization of peptide-protein binding involves a larger number of potential interactions that require screening methods to target physiological conditions. We build a hydropathy-based free energy estimation tool which allows quick evaluation of peptides binding to collagen. Previous studies showed that pH plays a significant role in collagen structure and stability. Our design tool enables probing peptides for their collagen-binding property across multiple pH conditions. We explored binding features of currently known collagen-binding peptides, collagen type I alpha chain 2 sense peptide (TKKTLRT) and decorin LRR-10 (LRELHLNNN). Based on these analyzes, we engineered a collagen-binding peptide with enhanced properties across a large pH range in contrast to LRR-10 pH dependence. To validate our predictions, we used a quantum-dots-based binding assay to compare the coverage of the peptides on type I collagen. The predicted peptide resulted in improved collagen binding. Hydropathy of the peptide-protein pair is a promising approach to finding compatible pairings with minimal use of computational resources, and our method allows for quick evaluation of peptides for binding to other proteins. Overall, the free-energy-based tool provides an alternative computational screening approach that impacts protein interaction search methods.

ROLE OF ULTRASONOGRAPHY IN EVALUATION OF ACUTE PELVIC PAIN IN FEMALES

Background: Pelvic pain in pregnant as well as non-pregnant females often represents a difcult challenge due to the variety of causes characterized by overlapping clinical symptoms, including gynaecological and non-gynaecological causes. Ultrasound (USG) is one of the best tools for the evaluating the female pelvis. It is very helpful in acute conditions to rule out different lower abdominal pathologies and is key to further management and appropriate treatment. Objectives: To assess the role of USG in acute pelvic pain & evaluate the common aetiologies of acute pelvic pain in females. This prospective observational study was conducted in the Department of Radi Material And Methods: o-diagnosis and Imaging in a tertiary care hospital in Jammu over a period of 6 months (May 2022 to October 2022). Female patients presenting with acute pelvic pain were included in our study. USG examination was performed using Samsung Sonoace R7 machine. Data obtained was compiled and analysed using standard statistical analysis. Results: In our study, the age range of the patients was 21-60 years and most common age group was 21-30 years. On USG, commonest cause of Acute Pelvic pain was ovarian cysts (48%). Ectopic pregnancy was seen in 16% cases while pelvic inammatory disease was seen in 10% cases. Uterine leiomyomas were the cause of acute pelvic pain in 8% of cases. Non-gynaecological causes included appendicular abscess, cystitis and ureteric calculus and were seen in 6% cases. In 12% cases, no diagnosis was made on USG. Conclusions: USG is a commonly used modality in evaluation of acute pelvic pain in females. It is very useful in emergency as it helps in quick evaluation and decision making for operative or medical treatment planning and can help in timely diagnosis without further imaging tests.

Comparative evaluation of textiles for use in textile reinforced concrete

Textile reinforced concrete (TRC) offers many advantages over traditional, steel bar reinforced concrete. The biggest advantage is the corrosion resistance of textiles, which leads to a reduced minimum cover with concrete. This allows for significantly thinner concrete elements, which are also easier to shape because of the excellent draping properties of textiles. For producers of technical textiles there is a need for a quick and easy method to test their products for suitability for use in TRC. In this paper, such a method is proposed: Novel textiles can be evaluated by comparing their properties to those of existing textiles already in use in the construction industry. Three different characteristic values crucial to the suitability of textiles for use in TRC are identified: tensile stress–strain behavior and alkaline resistance of the textiles and the tensile stress–strain behavior of TRC components. For each characteristic value a test method is identified. To validate these test methods and to provide a database for future comparison, the tests are performed on three different impregnated biaxial non-crimp fabrics that are already approved for and used in TRC. These consist of a styrene butadiene rubber impregnated carbon fiber textile, an epoxy resin impregnated alkaline resistant glass textile and a polyvinyl alcohol fiber textile. From these validation tests, key figures that allow for a ranking of new textiles in comparison to the already available textiles are inferred; The tensile strength of the textiles ranges from 880 to 2900 MPa, the alkaline strength degradation is at maximum −0.17 %/day and the tensile strength of the TRC elements ranges from 770 to 2310 MPa. The comparison of these values with those of a new textile enables a quick initial evaluation of the suitability of the new textile for the use in TRC.

Antenna Arrangement in UWB Helmet Brain Applicators for Deep Microwave Hyperthermia.

Deep microwave hyperthermia applicators are typically designed as narrow-band conformal antenna arrays with equally spaced elements, arranged in one or more rings. This solution, while adequate for most body regions, might be sub-optimal for brain treatments. The introduction of ultra-wide-band semi-spherical applicators, with elements arranged around the head and not necessarily aligned, has the potential to enhance the selective thermal dose delivery in this challenging anatomical region. However, the additional degrees of freedom in this design make the problem non-trivial. We address this by treating the antenna arrangement as a global SAR-based optimization process aiming at maximizing target coverage and hot-spot suppression in a given patient. To enable the quick evaluation of a certain arrangement, we propose a novel E-field interpolation technique which calculates the field generated by an antenna at any location around the scalp from a limited number of initial simulations. We evaluate the approximation error against full array simulations. We demonstrate the design technique in the optimization of a helmet applicator for the treatment of a medulloblastoma in a paediatric patient. The optimized applicator achieves 0.3 °C higher T90 than a conventional ring applicator with the same number of elements.

Distance Based Structural Descriptors of Non-conjugated Ethylene Oxide Dendritic Core Decorated with Tetraphenylethylene

Topological descriptors have drawn more interest recently because of the simplicity of generation and quick evaluation times, by avoiding time-consuming laboratory experiments. The distance based descriptors stand out as being pivotal in the QSAR and QSPR analysis of physico-chemical aspects. Dendrimers are branching polymeric molecules distinguished by its systematic growth pattern. Non-conjugated Ethylene oxide dendritic core attached with tetraphenylethylene is one such hyper branched polymer with strong solubility in a majority of organic solvents making them an active constituent for a variety of experimental purposes. No significant amount of research has been carried over based on the topological aspects of this dendrimer. This study effectively establishes the correlation between the chemical and physical attributes of the structure which can further aid in experimental research. In this work, various fundamental distance based descriptors of Ethylene oxide cored dendrimer have been evaluated by converting the original graph to quotient graphs using Djokovic̀-Winkler relation. Moreover, a graphical comparison of these descriptors has also been plotted to help comprehend the growth trend of these numerical values.

Validation of the Concise Assessment Scale for Children's Handwriting (BHK) in an Italian Population.

Handwriting difficulties represent a common complaint among children and may cause a significant delay in motor skills achievement. The Concise Assessment Scale for Children's Handwriting (BHK) assesses handwriting skill in clinical and experimental settings, providing a quick evaluation of handwriting quality and speed through a copying text. The aim of the present study was to validate the Italian adaptation of the BHK in a representative primary school population. Overall, 562 children aged 7-11 from 16 public primary schools of Rome were included and asked to copy a text in 5 min using cursive handwriting. Handwriting quality and copying speed were measured. The included population followed a normal distribution for the BHK quality scores. Sex influenced the total quality scores, whereas school level influenced the copying speed. The BHK quality score was higher in girls (p < 0.05) and resulted as a stable parameter along the school years, without significant variations with regard to the years spent in handwriting exercise (p = 0.76). The handwriting speed was influenced by school level, and significant differences were found for each of the grades from the second to the fifth (p < 0.05), but not for gender (p = 0.47). Both BHK measures represent a helpful tool for the characterization and assessment of children with handwriting difficulties. The present study confirms that sex influences total BHK quality score, while school level influences handwriting speed.

Automatic boundary detection and severity assessment of mitral regurgitation

The most prevalent disease, cardiovascular disease (CVD), has a high mortality rate among people. The prognosis of CVD depends on early diagnosis. In the event of any abnormality, such as valvular regurgitation and stenosis, the blood flow patterns, direction, and velocity are detected using the color Doppler echocardiography. Today’s clinicians determine the regurgitant jet region manually in the echocardiographic images with the aid of a cursor to assess the severity of mitral regurgitation (MR). Manual tracing takes a lot of time and involves both intra and inter-personal variances. This research offers an automatic delineation technique to quantify the regurgitant jet area value to address this problem. The level of MR severity, specifically mild, moderate, and severe, is then connected to the analyzed jet area. The suggested approach combines various segmentation methods, such as color space model, thresholding, and morphological operators, for segmenting echocardiographic pictures. A total of 75 MR-related images from 25 individuals have been evaluated. In light of the regurgitant jet area identified by the suggested technique and contrasted with the manual way of MR assessment, the severity of MR has been assessed. The segmentation procedure can be segmented to remove the imitation areas using the established method. The regurgitant jet region collected using the suggested technique satisfies the clinical objectives in the quick evaluation of MR severity.

Standardization and normative data of the 48-item Yoni short version for the assessment of theory of mind in typical and atypical conditions.

The Yoni task is a computerized tool assessing first-and second-order affective and cognitive Theory of Mind (ToM), accounting for the multidimensional and multi-level mentalizing features. The Italian Yoni task has been validated and standardized in its 98-item version, and a 48-item short version has been proposed for a quick digital evaluation of ToM in clinical contexts. The present study aimed to test the Yoni-48's convergent validity, correlating the tool score with the Reading the Mind in the Eyes test (ET) and Gender Test (GT), its items discrimination ability through the Classical Test Theory, and Rash model, its reliability by evaluating the internal consistency (McDonald's ω, Cronbach's α, Guttman's λ 2, and Guttman's λ 6) and Spearman-Brown ϱSP split-half analysis, and to provide standardization and normative data in the Italian population. Results suggested a good convergent validity with a statistically significant association with ET (p < 0.001), while a null correlation was observed with GT (p = 0.947). The Classical Test Theory and Rash model confirmed a good discrimination ability of the Yoni-48's second-order affective and cognitive ToM items, while weaker discrimination capacity was registered for the first-order ToM items. The inter-item reliability was optimal for clinical purposes (ω, α, λ 2, λ 6 ≥ 0.90). Also, the split-half reliability was high (Spearman-Brown ϱSP = 0.90). For standardization, age and education were revealed as significant predictors of Yoni accuracy scores, except for the first-order ToM score. Instead, age was the only predictor of Yoni's response speed score. The Italian normative data showed a high Yoni accuracy in healthy adults (mean accuracy = 0.85) and speed (mean response time = 0.92). Finally, both accuracy and response time level was balanced between the affective and cognitive components of ToM. This study supports the psychometric properties of the Yoni-48 and provides normative data for the Italian population. Further studies are needed to test the suitability of this short version for profiling the social cognition neurocognitive phenotype.

A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques

A better estimation of the effective porosity of the reservoir rock is a critical task for petrophysicist and well logs analyst. A majority of the current approaches to estimate the effective porosity of the reservoir rocks from well logs are based on the information of the Density-Neutron logs. These approaches usually resulted in the inaccurate estimation of the rock porosity particularly in the naturally fractured carbonates or dolomite rocks. The Nuclear Magnetic Resonance (NMR) based effective porosity is independent of the rock matrix and mineralogy, on contrary it depends on the number of hydrogen nuclei in the pore spaces of the rock. In this study, we have used six machine learning (ML) techniques to predict the NMR based effective porosity in carbonate rocks. The ML models to predict the effective porosity includes deep neural networks (DNN), random forest regressor (RF), decision trees (DT), K-Nearest Neighbors algorithm (KNN), extreme gradient boosting (XGB), and adaptive gradient boosting (AdaBoost). These models were trained on the geophysical well logs such as Gamma ray log (GR), caliper log (Cali), neutron porosity log (NPHI), photoelectric factor log (PE), and bulk density log (RHOB). A total of 4002 data points were obtained from the five wells located in the carbonate field. The tuning of ML models hyperparameters were conducted using a ‘GridSearchCv’ method. Furthermore, the K-fold cross-validation criterion was implemented to improve the accuracy of the ML models. The ML models performances were evaluated using multiple graphical and goodness of fit tests including prediction cross-plots, average absolute percentage error (AAPE), root means square error (RMSE), and coefficient of determination (R2) methods. The prediction results showed that the DNN, RF, and XGB models performed better than the other implemented ML techniques. These methods resulted in a significantly low error and high (R2). The achieved accuracy was above 85% when validated on a blind dataset. This study also offered an empirical model that can be used to quickly estimate the NMR based effective porosity using afore-mentioned well logs. The model can also be used as a standalone package that can be coupled with any logging software for quick evaluation of NMR based effective porosity.

137Cs direct measurement in water via LSC techniques

This work explores the screening technique of 137Cs concentration dissolved in water via the Cherenkov counting method on a Liquid Scintillation Counter Quantulus 1220. In the event of a nuclear emergency or the potential radioactive leakage from the power plants, the prompt detection of two long-lived fission products, 90Sr/90Y and 137Cs, is of the greatest radiological concern. Here we present an innovative, rapid, and simple LSC method for 137Cs content determination that enables quick evaluation of the radioactive contamination status of water samples without any sample pre-treatment. The novelty in the presented Cherenkov counting technique is the addition of ionic liquid 1-butyl-3-methylimidazolium salicylate in a sample vial. Its presence in the amount of ∼1 g increases efficiency up to ∼30% via a wavelength-shifting mechanism, thus reducing the detection limit of the method more than 4 times. Without the ionic liquid's addition, the method's main parameters were detection efficiency of 6.98(11)% and a detection limit of 2.6 Bq L−1 for 300 min of counting in a 20 mL sample volume. Interference with 90Sr/90Y, a radionuclide that can contribute to the Cherenkov radiation spectrum, was also investigated. The method of distinguishing individual radionuclides (137Cs and 90Sr/90Y) in the cumulative Cherenkov spectrum is presented as well.

Spatiotemporal change detection of land use land cover (LULC) in Fashiakhali wildlife sanctuary (FKWS) impact area, Bangladesh, employing multispectral images and GIS

Land cover change has posed significant concerns to biodiversity and climate change in Bangladesh and globally. Despite the country’s designation of forest regions as protected areas to conserve their valuable resources, deforestation and forest conversion remained unabated. Fashiakhali Wildlife Sanctuary (FKWS), a protected area in the Chittagong Hill Tracts, and its surrounding forested impact area have experienced considerable changes over the years, yet are deficient in extensive assessment. This study evaluated the land use land cover (LULC) changes in the FKWS impact area over almost 3 decades (1994–2021) using multispectral remotely sensed data. The Landsat images of 1994, 2001, 2010, and 2021 were classified using a maximum likelihood algorithm and analyzed for change detection. The comparative potential of vegetation indices, including Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI), in forest cover assessment, and the relationship between Land Surface Temperature (LST) and NDVI was also assessed. A significant forest cover loss of around 1117.17 ha (16%) was recorded in the FKWS impact area between 1994 and 2021, with the hugest proportion of 867.78 ha (12.24%) deforested in the first period (1994–2001). Agricultural land also declined by 593.73 ha (8.37%) within the entire period, despite its initial increase of 392.04 ha (5.53%) between 2001 and 2010, being the primary driver of earlier deforestation. However, in the recent decade (2010–2021), settlement expansion of 963.90 ha (13.59%) due to massive human migration in the area contributed to the most remarkable overall land cover change of 1731.51 ha (24.42%). Furthermore, NDVI provided a better and more accurate forest cover assessment than SAVI and was recommended to aid in the quick evaluation and monitoring of the future impacts of agriculture, settlement, and other sorts of land use on the forest cover. In tandem with the widely acknowledged issue of increased temperature due to climate change, an absolute negative correlation was found between the NDVI and LST, confirming the negative impact of climate change on forest loss in the FKWS impact area.

A neural network approach to performance analysis of tandem lines: The value of analytical knowledge

We develop a neural network (NN) metamodeller for efficiently approximating the throughput of different finite-buffer multi-server tandem lines (with varying service rates, number of stations, buffers, and servers). The resulting NN serves as a quick performance evaluation tool and is subsequently used for optimising the tandem-line layout. Specifically, we discuss the optimal allocation of buffer places and optimising service rates where service rates at machines are associated with costs. Our NN metamodelling approach is new as we integrate (biased) analytical queuing knowledge into the training data. The setup and training of the NN metamodeller are discussed in the paper. In particular, we discuss the integration of analytical results from queuing theory. Our numerical studies corroborate the common belief that adding analytical knowledge (in this case from queueing theory) significantly improves the ensuing NN’s prediction power. The framework developed in this paper demonstrates how analytical system knowledge can be integrated with data science in performance evaluation and optimisation. Our message is that even basic NNs, combined with formulae available from OR theory, offer invaluable improvements for building metamodellers in simulation optimisation.

Relate building information modeling to quality management according to the different quality management phases

Buildings are becoming larger and more complex in today’s world. As a result, the old method of personally inspecting a building’s design is no longer efficient, as it is time-consuming and labor-intensive. Establishing and automating systems for inspecting building quality is becoming increasingly crucial. Building Information modeling (BIM) enables for quick decision-making and evaluation by automatically verifying if buildings meet standards. In this case. Real-time quality control and early fault detection are still the most effective methods for decreasing project schedule and expense overrun in the construction process. Current quality control methods on construction sites are inefficient and time-consuming since they only offer data at specified locations and times to reflect the work in progress, limiting a quality manager’s ability to quickly identify and handle faults. The goal of this research is to show how important BIM is in quality management in terms of its many phases. (inspection, control, and quality assurance).