Weight Values Research Articles

Turmeric flour supplementation in feed to improve goldfish performance

Goldfish (Carassius auratus) is an ornamental fish that is widely loved and has good prospects for development. This study aims to improve the growth of goldfish (Carassius auratus) fed with feed enriched with turmeric flour. The test fish used were goldfish seeds (Length 3-4 cm and weight 2-3 g). This study was an experimental study with a completely randomized design (CRD) consisting of 4 treatments and three replications consisting of commercial feed (P0), feed enriched with turmeric flour with a dose of 1% (P1); 2% (P2) and 3% (P3). The results showed that adding turmeric flour to the feed statistically significantly affected the seeds' absolute weight and Specific Growth Rate (SGR). Still, they were not significantly different in the seeds' absolute length value, Fed Conversion Ratio (FCR), and Survival Rate (SR). Treatment with a dose of 3% showed the best value in absolute weight of 4.66 ± 0.23 g, absolute length of 2.93 ± 0.12 cm, SGR of 2.68 ± 0.15%, FCR of 1.41 ± 0.03, and feed protein content (50.04%). Turmeric flour has the potential to be used as a supplement in feed because it can increase feed protein content and seed growth and reduce FCR values ​​better than without the addition of turmeric flour.

Analysis of UHT Diamond Milk Supplier Selection With Analytical Hierarchy Process (AHP) Method cafe Milkyway Coffe & Milk In Berau Regency, East Kalimantan

Every business sector certainly wants consistency in production results, this can be realized through collaboration with raw material providers or suppliers who can ensure the consistent availability of raw materials because the production of raw materials is very vital. Therefore, it is necessary to have a good raw material procurement system and supplier selection so that the production process can run smoothly. Milkyway Cafe is the first pioneering UKM of beverage and food business in Berau Regency, East Kalimantan which has a special characteristic of beverage products made from milk which are liked by many customers, especially teenagers, children, and families. There are problems experienced when selecting suppliers who provide raw materials for UHT milk because there are several factors to consider, namely price, delivery, service, and accuracy of quantities. The sample of the research is the owner of the business that regulates the procurement of UHT milk. The results of the analysis and calculation of the Analytical Hierarchy Process (AHP) using Microsoft Excel stated that the chosen alternative, namely the Kompas with a weight value of 0.46, was superior to the Simpang Utama with a weighted value of 0.34 and the Tops Jaya with a weighted value of 0.20. The main factors that are prioritized in the selection of suppliers at Milkyway are service criteria with a weight value of 0.18, the accuracy of the number of goods with a weight value of 0.15, prices with a weight value of 0.08, and delivery with a weight value of 0.06.

Adaptive Filter Pruning via Sensitivity Feedback.

Filter pruning is advocated for accelerating deep neural networks without dedicated hardware or libraries, while maintaining high prediction accuracy. Several works have cast pruning as a variant of l1 -regularized training, which entails two challenges: 1) the l1 -norm is not scaling-invariant (i.e., the regularization penalty depends on weight values) and 2) there is no rule for selecting the penalty coefficient to trade off high pruning ratio for low accuracy drop. To address these issues, we propose a lightweight pruning method termed adaptive sensitivity-based pruning (ASTER) which: 1) achieves scaling-invariance by refraining from modifying unpruned filter weights and 2) dynamically adjusts the pruning threshold concurrently with the training process. ASTER computes the sensitivity of the loss to the threshold on the fly (without retraining); this is carried efficiently by an application of L-BFGS solely on the batch normalization (BN) layers. It then proceeds to adapt the threshold so as to maintain a fine balance between pruning ratio and model capacity. We have conducted extensive experiments on a number of state-of-the-art CNN models on benchmark datasets to illustrate the merits of our approach in terms of both FLOPs reduction and accuracy. For example, on ILSVRC-2012 our method reduces more than 76% FLOPs for ResNet-50 with only 2.0% Top-1 accuracy degradation, while for the MobileNet v2 model it achieves 46.6% FLOPs Drop with a Top-1 Acc. Drop of only 2.77%. Even for a very lightweight classification model like MobileNet v3-small, ASTER saves 16.1% FLOPs with a negligible Top-1 accuracy drop of 0.03%.

CoCoSo framework for multi-attribute decision-making with triangular fuzzy neutrosophic sets: “Innovation and entrepreneurship” evaluation case

The “innovation and Entrepreneurship” education focuses on cultivating students’ “innovation and Entrepreneurship” abilities, reflecting the fundamental requirements of economic progress and social development for the knowledge, ability, and quality structure of talents. Local universities should actively promote the reform of talent cultivation models, establish a scientific “innovation and Entrepreneurship” education target system based on the actual situation of the school, strengthen the construction of “innovation and Entrepreneurship” education courses, build various “innovation and Entrepreneurship” practice platforms, pay attention to the interaction between the first and second classrooms, as well as practical and training platforms, serve the growth and talent development of students, and achieve a comprehensive improvement in the quality of school education, teaching, and talent cultivation. The “innovation and Entrepreneurship” education quality evaluation of local colleges could be considered as multiple attribute decision-making (MADM). Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method was employed to deal with MADM. The triangular fuzzy neutrosophic sets (TFNSs) are employed as a better tool for expressing uncertain information during the “innovation and Entrepreneurship” education quality evaluation of local colleges. In this paper, the triangular fuzzy neutrosophic number CoCoSo (TFNN-CoCoSo) based on the TFNN grey rational coefficients (TFNNGRC) from TFNN positive ideal solution (TFNNPIS) is constructed to cope with the MADM under TFNSs. The information entropy method is employed to compute the weight values based on the TFNNGRC from TFNNPIS under TFNSs. Finally, a numerical example of “innovation and Entrepreneurship” education quality evaluation of local colleges is constructed and some decision comparisons are constructed to verify the TFNN-CoCoSo method.

Generalized and Robust Least Squares Regression.

As a simple yet effective method, least squares regression (LSR) is extensively applied for data regression and classification. Combined with sparse representation, LSR can be extended to feature selection (FS) as well, in which l1 regularization is often applied in embedded FS algorithms. However, because the loss function is in the form of squared error, LSR and its variants are sensitive to noises, which significantly degrades the effectiveness and performance of classification and FS. To cope with the problem, we propose a generalized and robust LSR (GRLSR) for classification and FS, which is made up of arbitrary concave loss function and the l2,p -norm regularization term. Meanwhile, an iterative algorithm is applied to efficiently deal with the nonconvex minimization problem, in which an additional weight to suppress the effect of noises is added to each data point. The weights can be automatically assigned according to the error of the samples. When the error is large, the value of the corresponding weight is small. It is this mechanism that allows GRLSR to reduce the impact of noises and outliers. According to the different formulations of the concave loss function, four specific methods are proposed to clarify the essence of the framework. Comprehensive experiments on corrupted datasets have proven the advantage of the proposed method.

The Linkage between Corporate Research and Development Intensity and Stock Returns: Empirical Evidence

Research and development (R&D) is a significant driver of innovation that leads to superior performance. The present study attempts to examine the relationship between R&D intensity and a firm’s performance at both aggregate and industry levels in the emerging market of India using a battery of R&D intensity measures and stock market returns as a measure of a firm’s performance. The study was conducted on 1097 companies from six R&D-intensive industries. The Fama-French portfolio formation method was used to evaluate the stock market performance of R&D-intensive firms for both equal-weighted (EW) and value-weighted (VW) returns. The findings suggest that R&D intensity and stock returns show a positive relationship. A long–short strategy in R&D-intense firms has yielded 1.43% (t = 4.22) per month in the sample. In general, the results suggest an undervaluation of highly R&D-intensive firms that investors can exploit for above-average returns. The effect is not homogeneous across return schemes (equal-weighted and value-weighted) or across industries. R&D growth measures and R&D capital are not found to have significant impacts on stock returns. Both the market firm size and age are included as control variables, and the results reveal that the relationship is robust to these control variables. The sub-periods ranging from 2000 to 2007 and 2008 to 2019 have been considered in the present study and the results are consistent with the overall sample. The study fills the existing empirical void for R&D intensity and stock returns in relation to the emerging market of India.

Personalized multi-attribute recommendation method based on partial order set

With the rapid development of big data and continuous optimization of online shopping platforms, personalized recommendation has become a standard feature of recommendation methods. In order to effectively provide personalized recommendations to customers, improve recommendation accuracy, and customer satisfaction, it is necessary to consider customers’ preferences for multiple product attributes when making product recommendations. However, existing recommendation methods require precise calculation of product attribute weights, which is computationally expensive, complex, and often results in unstable weight values. This paper proposes a multi-attribute recommendation method based on consumer decision preference information that overcomes the need for weights and reflects personalized customer preferences. Based on the acquisition of customer product attribute preference sequences, a partial order relation for recommended products is constructed using partial order set theory. Finally, the recommended products are determined through the partial order Hasse diagram, where the top layer elements of the Hasse diagram represent the recommended product set. This method addresses challenges that traditional content-based recommendations cannot overcome. The experiment in this paper uses a dataset of 30,000 records from Beeradvocate beer reviews. The experimental results show that, compared to traditional multi-attribute recommendation methods, this method only requires decision-maker preference information to complete product recommendations, requiring less information and having lower computational costs, resulting in more robust results.

Stability and adaptability evaluation of grain sorghum varieties using GGE biplot

In Pakistan, Sorghum can be a good domestic source of high-quality fodder and feed, because of its high protein and sugar contents. Location-specific adaptation of lines/varieties as found in the current study evidently implies that location-specific breeding needs are more importance than concentrating on wider adaptability. Another point of consideration is that it is essential to recognize location-specific cultivars over location and multi-year data for their consideration before commercial release for the sake of stability of the cultivar. This is important not only to sorghum only but also in other crops as well. The G × E interaction of six Pakistani experimental sorghum lines produced by Pedigree method and two check cultivars were evaluated for days to 50% flowering, stalk weight, grain yield and Brix value along with their stability and/or adaptability across two locations and two years, under randomized complete block (RCB) design. Three replications were used for each treatment. The combined analyses of variance of all the studied characters showed that they were affected significantly by environments (E), genotypes (G) and genotype by environment interaction (G × E) in every year except for the environment in Brix value. The ideal genotype evaluation proved that YSS-10 was the best line for the all four environments. Dera Gazi Khan is an ideal location for testing grain sorghum genotypes. The ’Which-won-where’ biplots indicated a crossover type of G × E between experimental lines YSS-10 and YSS-18 for the grain yield

Impact of the SARS-CoV-2 pandemic on the body mass index of children seen in the City of Buenos Aires.

Introduction. Childhood overweight and obesity are a public health problem. The onset of the COVID-19 pandemic may have contributed to this condition. The body mass index (BMI) Z-score has been accepted as an indicator for overweight and obesity diagnosis and follow-up. Objective. To assess whether the prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased during the pandemic. Population and methods. Retrospective, cohort study. Patients included were those seen at public health care facilities in the City of Buenos Aires (CABA), who were aged 2 to 5 years, had weight and height values recorded at 2 different visits, before and after the establishment of the preventive and mandatory social isolation policy. Patients' nutritional status (BMI Z-score) and the variation in this indicator between both visits were recorded. Results. A total of 3866 subjects were assessed; their average age was 3.4 ± 0.8 years; 48.1% were girls. The average interval between both visits was 14.3 ± 2.5 months. The prevalence of overweight/ obesity increased from 12.6% (95% CI: 11.6-13.6) to 20.9% (95% CI: 19.6-22.2), p < 0.001, and so did the BMI Z-score (0.4 ± 1.1 versus 0.8 ± 1.3, p < 0.001). Conclusion. The prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased significantly during the pandemic.

Early development of infants born prematurely who were conceived through assisted reproductive technologies

ObjectiveThis study aims to determine physical and psychomotor development characteristics during the first 24 months of life in prematurely born children conceived with assistive reproductive technologies and to determine specific risk factors for deviation from typical development. Patients and methodsThe study included 308 prematurely born children (154 conceived with assistive reproductive technologies – ART group and 154 conceived naturally – NC group) hospitalized at the Institute for the Health Care of Children and Adolescents of Vojvodina in Serbia. The physical and psychomotor development was monitored during the first two years of life. ResultsBirth weight was statistically significantly higher in the NC group than in the ART group, and IUGR was more often present in the ART group than in the NC group of newborns. The mean values of body weight, length, and head circumference of children from both groups did not differ statistically significantly at 18 months. At 12 and 18 months, children from the ART group significantly more often had below-average scores on the test for assessment of psychomotor development (corrected GDQ <90) than children from the NC group, but not at 24 months. Logistic regression analysis has shown that at 12 and 18 months, multiple pregnancy is an independent risk factor for lower GDQ. ConclusionAt the age of 12 months, prematurely born children conceived with ART do not differ in physical development from prematurely born children after natural conception. At 12 and 18 months, prematurely born children conceived with ART achieve lower global developmental scores than children conceived naturally, but not at 24 months of age. Multiple pregnancies are an independent risk factor for lower achievement on the test for assessment of psychomotor development in prematurely born children.

Maternal separation influences hepatic drug-metabolizing CYP450 gene expression without pathological changes in adult mice.

The principal motive of this study is to explore the influence maternal separation (MS) exhibits on the mRNA expression of major drug metabolizing-cyp450s in parallel with the assessment of pathological changes that can be induced by MS in the livers of experimental mice. Eighteen Balb/c mouse pups, comprising of both males and females, were separated from their mothers after birth. Following a six-week period during when the pups became adults, the mice were sacrificed and their livers were isolated for analysis of weight, pathohistological alterations, and the mRNA expression of drug metabolizing cyp450 genes: cyp1a1, cyp3a11, cyp2d9, and cyp2c29. The study demonstrated that MS markedly downregulated (p<0.05) the mRNA expression of all tested drug-metabolizing cyp450s in livers of female and male mice. Furthermore, the mRNA levels of major drug-metabolizing cyp450s were notably lower (p<0.05) in livers of female MS mice as compared with male MS mice. It was found that values of the total body weight and liver weight of MS mice did not vary significantly (p>0.05) from those of the control groups. Additionally, histological examination revealed that the hepatic tissue of MS mice was normal, similar to that of the control mice. In summary, MS downregulates the gene expression of major hepatic drug-metabolizing cyp450s without inducing pathological alterations in the livers of mice. These findings provide an explanation for the heterogeneity in pharmacokinetics and drug response of patients with early life stress.

Effect of early preventive supplementation with calcium and phosphorus on metabolic bone disease in premature infants

ObjectiveThe objective was to study the effect of early preventive calcium and phosphorus supplementation on metabolic bone disease in preterm infants.MethodsA retrospective analysis of 234 preterm infants with a gestational age < 32 weeks or birth weight < 1500 g who were hospitalized in the Neonatology Department of the Second Hospital of Shandong University from 01.2018 to 12.2020 was conducted. One hundred thirty-two premature infants hospitalized from 01.2018 to 06.2019 did not receive prophylactic calcium and phosphorus supplementation in the early postnatal period. These infants received calcium or phosphorus supplementation at the time of hypocalcaemia or hypophosphatemia diagnosis. One hundred two premature infants hospitalized from 07.2019 to 12.2020 received early preventive calcium and phosphorus supplementation after birth. The levels of serum calcium and phosphorus, alkaline phosphatase, 25-hydroxyvitamin D, calcitonin, and parathyroid hormone at different time points and growth indicators at six months of age were compared between the two groups of infants. The number of cases of metabolic bone disease and fracture between the two groups was compared.Results1) A total of 12 infants (5.13%) among the 234 preterm infants were diagnosed with metabolic bone disease, including 2 (1.96%) in the prophylactic supplementation group and 10 (7.58%) in the nonprophylactic supplementation group. Fractures occurred in 3 premature infants (25.0%) with metabolic bone disease, all of whom were in the group that did not receive prophylactic supplementation. 2) There was no significant difference in serum calcium and calcitonin levels between the two groups. The levels of serum phosphorus and 25 hydroxyvitamin D in the prophylactic supplementation group were higher than those in the nonprophylactic supplementation group (P < 0.05). In comparison, alkaline phosphatase and parathyroid hormone levels were lower in the prophylactic supplementation group than in the nonprophylactic supplementation group (P < 0.05). Preterm infants in the prophylactic supplementation group had higher weight, length, head circumference, and bone density values than those in the nonprophylactic supplementation group (P < 0.05).ConclusionPreventive supplementation with calcium and phosphorus after birth can effectively improve calcium and phosphorus metabolism, and reduce the incidence of metabolic bone disease and fractures in premature infants. This can be further publicized and used clinically.

Neonatal Outcomes among Fetuses with an Abdominal Circumference

Fetal growth restriction (FGR) is defined as an estimated fetal weight (EFW) or abdominal circumference (AC) <10th percentile (%ile) for gestational age (GA). An EFW <3rd %ile for GA is considered severe FGR (sFGR). It remains unknown if fetuses with isolated AC <3rd %ile should be considered sFGR. Our primary objective was to assess composite neonatal outcomes in fetuses with an AC <3rd %ile and overall EFW 3rd to 9th %ile compared with those with an EFW <3rd %ile. This retrospective cohort study was undertaken at a tertiary academic center from January 2016 to December 2021. Inclusion criteria were singleton fetuses with an EFW <3rd %ile (Group 1) or AC <3rd %ile with EFW 3rd to 9th %ile (Group 2) at 28 weeks' gestation or greater. Exclusion criteria were multiple gestations, presence of a major fetal anomaly, resolution of FGR, genetic syndrome, or infection. Composite neonatal outcome was defined by any of the following: neonatal intensive care unit admission >48 hours, necrotizing enterocolitis, sepsis, respiratory distress syndrome, mechanical ventilation, retinopathy of prematurity, seizures, intraventricular hemorrhage, stillbirth, or death before discharge. Small for gestational age (SGA) was defined as birth weight <10th %ile for GA. A total of 743 patients fulfilled our study criteria, with 489 in Group 1 and 254 in Group 2. The composite neonatal outcome occurred in 281 (57.5%) neonates in Group 1 and 53 (20.9%) in Group 2 (p < 0.01). The rates of SGA at birth were 94.9 and 75.6% for Group 1 and Group 2, respectively (OR 5.99, 95% confidence interval 3.65-9.82). Although AC <3rd %ile with EFW 3rd to 9th %ile is associated with a lower frequency of SGA and neonatal morbidity than EFW <3 %ile, fetuses with AC <3 %ile still exhibited moderate rates of these adverse perinatal outcomes. Consideration should be given to inclusion of an AC <3rd %ile with EFW 3rd to 9th %ile as a criterion for sFGR. However, prospective studies comparing delivery at 37 versus 38 to 39 weeks' gestation are needed to ensure improved outcomes before widespread adaptation in clinical practice. · The composite neonatal outcome occurred in 57.5% of fetuses with an overall EFW <3rd %ile and 20.9% of fetuses with an AC <3rd %ile but EFW 3rd to 9th %ile.. · Both groups demonstrated a high positive predictive value for SGA birth weight.. · Consideration should be given to inclusion of an AC <3rd %ile as a criterion for sFGR..

Physical and mechanical properties of grain of spring barley varieties in the conditions of Tatarstan

The aim of the work is to analyze the physical and mechanical properties of grain of spring barley varieties cultivated in the conditions of the Predkamsk zone of the Republic of Tatarstan. The research was conducted in Tatarsky Research Institute of Agriculture FRC of Kazan Research Center RAS in 2015–2022. In the conditions of the Predkamsk zone, on average over the years of research, the late maturing variety Endan was characterized by reliably high values of 1000 grain weight (48.5 g), the early maturing variety Kamashevsky – reliably high values of natural grain weight (686, 3 g/l), convergence from 2.8 x 20 mm sieve (33.9 %) and coarseness (70.02 %), medium maturing variety Raushan – higher variability in 1000 grain weight (18.6 %), convergence from 2.8 and 2.5 x 20 mm sieves (55.6 and 29.7 %, respectively) and coarseness (39.5 %). The direct dependence of the mass of 1000 grains, runoff from the sieve 2.8 x 20 mm and coarseness on the sum of precipitation (r = 0.41/0.58/0.56, respectively), GTC (r = 0.40/0.58/0.55, respectively) and inverse dependence of these physical and mechanical properties on the average daily air temperature (r = -0.51/-0.62/-0.63, respectively) of the interphase period "earing-full ripeness" were established at 1% significance level. Judging by the value of the coefficient of determination (r2), the most closely related to the average daily air temperature are the signs "mass of 1000 grains", "drift from the sieve 2.8 x 20 mm" and "coarseness". The analysis of path coefficients revealed a high direct positive contribution (0.87) of 2.8 x 20 mm sieve runoff and an average direct positive contribution (0.43) of 2.5 x 20 mm sieve runoff to grain yield. Under the conditions of the Predkamsk zone, the prevailing contribution to the total variance of the traits "drift from the sieve 2.8 x 20 mm", "coarseness", "weight of 1000 grains", "bulk grain weight", "drift from the sieve 2.5 x 20 mm" was made by the factor "year", which accounted for (in descending order) 81.7...80.3...76.6...76.2. 68.7 %, respectively.

Using liquid chromatography and mass spectrometry to predict potential biomarkers for missed miscarriage and its metabolic pathways in a tertiary center: A cross-sectional analytic study.

To determine and compare the serum metabolites in missed abortion versus normal early pregnancy using ultra-high-performance liquid chromatography and tandem time-of-flight mass spectrometry, and to determine how these metabolites can be used to predict the potential biomarkers and possible metabolic pathways of a missed abortion. The serum of patients with a missed abortion was used as the experimental group and the serum of patients with an induced abortion during normal early pregnancy was used as the control group. Principal component analysis and orthogonal partial least square discriminant analysis were additionally used to observe the difference in metabolite distribution between the two groups. A variable weight value (variable importance in the projection; VIP) obtained from the orthogonal partial least squares discriminant analysis model more than 1 and P less than 0.05 were taken to indicate significant differences in metabolite screening. After this, enrichment analysis of the metabolic pathways of these metabolites was conducted using Fisher precise test in order to find the metabolic pathway with the highest correlation with the differential metabolites. In total, 30 patients were included in the experimental group, with 30 patients in the control group. Fifty-five metabolites (VIP > 1, P < 0.05) with significant differences related to missed abortion were selected, among which 35 metabolites increased and 20 decreased in patients with a missed abortion. KEGG pathway enrichment analysis showed that the four metabolic pathways with the highest correlation were cholesterol metabolism, arginine biosynthesis, cell apoptosis, and the FoxO signaling pathway. The missed abortion serum metabolites and changes in related metabolic pathways reported in this study provide a basis for the early prediction and diagnosis of a missed abortion.

Modified method for college students’ career planning evaluation based on the probabilistic hesitant fuzzy multiple attributes group decision making

The employment of college graduates is related to the overall situation of China’s social development, and the difficulty of employment has become a social problem that cannot be ignored. Through the analysis of the current situation of employment, it is found that the lack of employment guidance in colleges and universities and the lack of employment concept of college students are important factors for the difficulty of college students’ employment, and college counselors play an irreplaceable role in college students’ career planning. Based on the characteristics of college counselors’ work, the paper constructs a career planning evaluation system, hoping to provide new ideas for counselors’ employment guidance. The college students’ career planning evaluation is a multiple attributes group decision making (MAGDM). Recently, the TODIM and GRA technique has been employed to manage MAGDM. The probabilistic hesitant fuzzy sets (PHFSs) are employed as a useful tool for depicting uncertain information during the college students’ career planning evaluation. In this paper, the probabilistic hesitant fuzzy TODIM-GRA (PHF-TODIM-GRA) technique is built to manage the MAGDM under PHFSs. At last, the numerical example for college students’ career planning evaluation is employed to show the PHF-TODIM-GRA technique. The main contribution of this paper is outlined: (1) the TODIM technique based on GRA technique has been extended to PHFSs based on CRITIC technique; (2) the CRITIC technique is employed to derive weight values under PHFSs. (3) the PHF-TODIM-GRA technique is founded to manage the MAGDM under PHFSs; (4) a numerical case study for college students’ career planning evaluation and some comparative analysis is supplied to validate the proposed PHF-TODIM-GRA technique.

Optimized multiple-attribute group decision-making in uncertainty employing TODIM and EDAS technique and application to product styling design quality evaluation

With the improvement of the public’s aesthetic level, product appearance has become an important influencing factor for consumers to make purchasing decisions. Product styling design is based on this market demand, combining the aesthetic and functional aspects of the product to create a personalized product appearance, in order to better attract consumers, improve the competitiveness and added value of the product. Usually, product styling design involves multiple elements such as product form, color, proportion, etc. The quality evaluation of product styling design is a MAGDM problems. Recently, the TODIM and EDAS technique has been employed to manage MAGDM issues. The interval-valued Pythagorean fuzzy sets (IVPFSs) are employed as a tool for characterizing uncertain information during the quality evaluation of product styling design. In this paper, the interval-valued Pythagorean fuzzy TODIM-EDAS (IVPF-TODIM-EDAS) technique is construct to manage the MAGDM under IVPFSs. Finally, a numerical case study for quality evaluation of product styling design is employed to validate the proposed technique. The main contribution of this paper is managed: (1) the TODIM and EDAS technique was extended to IVPFSs; (2) Entropy technique is employed to manage the weight values under IVPFSs. (3) the IVPF-TODIM-EDAS technique is founded to manage the MAGDM under IVPFSs; (4) Algorithm analysis for quality evaluation of product styling design and comparison analysis are constructed based on one numerical example to verify the feasibility and effectiveness of the IVPF-TODIM-EDAS technique.

Knowledge fusion method of power grid model based on Seq2seq half pointer and half label method

Due to the complexity of the calculation process of the existing methods, the efficiency of data fusion of the power grid model is low. In order to improve the knowledge fusion effect of power grid model, this paper studied the knowledge fusion method of power grid model based on Seq2seq half pointer and half label method. The Text Rank algorithm is used to calculate the weight of semantic nodes of each grid model, and combined with the topological potential method, the semantic information of the grid model is extracted according to the final weight value, and the Seq2Seq semi-pointer semi-label model framework is constructed. The data of the scheduling automation system OMS and the production management system PMS are used as input. The extracted candidate mesh model semantics and the original mesh model semantics are encoded by Seq2Seq half-pointer half-label model. The semantic data of the power grid model is fused and sent to the Seq2Seq encoder. After the training is completed, the effective information is extracted from the power grid model through the Seq2Seq model to complete the knowledge fusion of the power grid model. Experimental results show that this method eliminates the redundant part of the basic attributes of each data source in the substation grid model after knowledge fusion, and the description of each basic attribute is more standardized, unified and perfect. Under different mesh model data dimensions, the support of the proposed method is all above 98%. The model trained by the proposed method tends to be stable after 120 iterations, and the precision, recall and F1 of the test set are 0.98, 0.93 and 0.91, respectively. At the same time, this method has high efficiency in the knowledge fusion processing of the power grid model, and its data processing speed is less than 160 s. The average integrity of the private data of the power grid model is 98.86%, indicating that the proposed method can better ensure the integrity of the data. Finally, compared with the application of other methods under different data amounts, the mean square error obtained by the proposed method is the smallest, indicating that the proposed method effectively improves the fusion accuracy.

TODIM-PROMETHEE method for tourism landscape planning design scheme evaluation based on the virtual reality technology under spherical fuzzy sets

How to explore the potential value of landscape, realize the organic combination of tourism landscape, enrich landscape elements and enhance tourism experience has become an important topic of tourism landscape planning and design, which is also a practical problem that needs to be solved urgently in the process of tourism landscape development and planning in different regions of China. The tourism landscape planning design scheme evaluation based on the virtual reality technology a typical multi-attribute group decision-making (MAGDM) problem. With the complexity of economic activities, uncertain information has an increasing impact on production activities. However, due to the ambiguity and uncertainty of human cognition, the factors affecting the risk of things cannot be accurately expressed. Therefore, selecting spherical fuzzy sets (SFSs) can make the expression of information more accurate and complete. On basis of the TODIM method and the PROMETHEE method, in this study, spherical fuzzy number TOMIM-PROMETHEE (SFN-TOMIM-PROMETHEE) method is implemented to solve the MAGDM problem under SFSs. Furthermore, CRITIC method under SFSs is implemented to determine relative weights. Then a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology is selected to illustrate the effectiveness and practicality of the method. Finally, the comparative analysis shows that the SFN-TOMIM-PROMETHEE method under SFSs is an effective method to deal with MAGDM problems. The main contribution of this paper is managed: (1) the TODIM and PROMETHEE technique was extended to SFSs; (2) CRITIC technique is employed to manage the weight values under SFSs. (3) the SFN-TOMIM-PROMETHEE technique is founded to manage the MAGDM under IVPFSs; (4) a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology and comparison analysis are constructed to verify the feasibility and effectiveness of the SFN-TOMIM-PROMETHEE technique.

Modified TODIM-TOPSIS technique for type-2 neutrosophic number multiple-attribute decision-making and applications to innovation and entrepreneurship education evaluation in vocational colleges

Innovation and entrepreneurship education is an important component of cultivating the comprehensive quality of college students and an important force in promoting economic and social development. Meanwhile, due to changes in the social environment and economic structure, traditional university education is no longer able to meet the needs of contemporary society. Therefore, innovation and reform of innovation and entrepreneurship education for college students are urgent. Innovation and entrepreneurship education for college students needs to keep up with the times, constantly update concepts and techniques, in order to adapt to the ever-changing social and economic environment. The innovation and entrepreneurship education evaluation in the application-oriented vocational colleges is a multiple-attribute decision-making (MADM) problem. Recently, the TODIM and TOPSIS technique has been used to cope with MADM issues. The Type-2 neutrosophic numbers (T2NNs) are employed as a technique for characterizing uncertain information during the innovation and entrepreneurship education evaluation in the application-oriented vocational colleges. In this paper, the Type-2 neutrosophic number TODIM-TOPSIS (T2NN-TODIM-TOPSIS) technique is implemented to solve the MADM under T2NNs. Finally, a numerical case study for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis is implemented to validate the proposed T2NN-TODIM-TOPSIS technique. The main research contribution of this paper is managed: (1) the TODIM and TOPSIS technique was enhanced with T2NNs; (2) Entropy technique is enhanced to manage the weight values with T2NNs. (3) the T2NN-TODIM-TOPSIS technique is founded to manage the MADM with T2NNs; (4) Algorithm framework for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis are constructed based on one numerical example to verify the effectiveness of the T2NN-TODIM-TOPSIS technique.